diff --git a/.github/workflows/CI_rosco-compile.yml b/.github/workflows/CI_rosco-compile.yml index 3e4e70c3..97659a44 100644 --- a/.github/workflows/CI_rosco-compile.yml +++ b/.github/workflows/CI_rosco-compile.yml @@ -3,75 +3,146 @@ name: CI_rosco-compile # We run CI on push commits on all branches on: [push, pull_request] -# Specify FORTRAN compiler, used to be "gfortran-10" -env: - FORTRAN_COMPILER: gfortran # A workflow run is made up of one or more jobs that can run sequentially or in parallel jobs: - build: - name: Build (${{ matrix.os }}) - runs-on: ${{ matrix.os }} - strategy: - fail-fast: true - matrix: - os: ["ubuntu-latest", "macOS-latest", "windows-latest"] - python-version: ["3.9"] - - steps: - - name: Checkout repository - uses: actions/checkout@v3 - - - name: Setup environment - uses: conda-incubator/setup-miniconda@v2 - with: - miniconda-version: "latest" - channels: conda-forge, general - auto-update-conda: true - python-version: 3.9 - environment-file: environment.yml - - # Install ROSCO toolbox - - name: Install ROSCO toolbox - shell: bash -l {0} - run: | - python setup.py install + build_pip: + name: Pip Build (${{ matrix.os }}) - ${{ matrix.python-version }} + runs-on: ${{ matrix.os }} + defaults: + run: + shell: bash -l {0} + + strategy: + fail-fast: false #true + matrix: + os: ["ubuntu-latest", "macOS-latest", "windows-latest"] + python-version: ["3.9", "3.10", "3.11"] + + steps: + - name: Setup GNU Fortran + # if: false == contains( matrix.os, 'windows') + uses: awvwgk/setup-fortran@v1 #modflowpy/install-intelfortran-action@v1 # + + - name: checkout repository + uses: actions/checkout@v4 + + - name: Set up Python ${{ matrix.python-version }} + uses: actions/setup-python@v4 + id: cp + with: + python-version: ${{ matrix.python-version }} + update-environment: true + + #- name: Setup tmate session + # if: contains( matrix.os, 'windows') + # uses: mxschmitt/action-tmate@v3 + + # Install ZeroMQ- should be done via Conda + #- name: Install ZeroMQ + # run: | + # sudo apt-get update + # sudo apt-get install libzmq3-dev + + - name: Pip Install ROSCO + run: | + '${{ steps.cp.outputs.python-path }}' -m pip install -e . - # Re-generate registry - - name: Generate Registry - shell: bash -l {0} - run: python ROSCO/rosco_registry/write_registry.py + # Re-generate registry + - name: Generate Registry + run: | + '${{ steps.cp.outputs.python-path }}' rosco/controller/rosco_registry/write_registry.py + + - name: Test run + # skipping pip test on windows for now until wisdem pypi is ready + if: false == contains( matrix.os, 'windows') + run: | + cd Examples + '${{ steps.cp.outputs.python-path }}' 01_turbine_model.py + + + build_and_test_conda: + name: Conda Build (${{ matrix.os }}) - ${{ matrix.python-version }} + runs-on: ${{ matrix.os }} + defaults: + run: + shell: bash -el {0} + + strategy: + fail-fast: false #true + matrix: + os: ["ubuntu-latest", "macOS-latest", "windows-latest"] + python-version: ["3.9", "3.10", "3.11"] + + steps: + - name: checkout repository + uses: actions/checkout@v4 + + - uses: conda-incubator/setup-miniconda@v2 + # https://github.com/marketplace/actions/setup-miniconda + with: + #mamba-version: "*" + miniforge-version: "latest" + auto-update-conda: true + python-version: ${{ matrix.python-version }} + environment-file: environment.yml + activate-environment: test + auto-activate-base: false + + - name: Add dependencies windows specific + if: contains( matrix.os, 'windows') + run: | + conda install -y m2w64-toolchain libpython + gfortran --version + + - name: Add dependencies mac specific + if: contains( matrix.os, 'mac') + run: | + conda install -y compilers + gfortran --version + + # Install + - name: Debug + run: | + conda list + printenv + + #- name: Setup tmate session + # uses: mxschmitt/action-tmate@v3 + # with: + # detached: true + # if: contains( matrix.os, 'windows') + + - name: Conda Install ROSCO + run: | + python -m pip install -e . + + - name: Install OpenFAST + run: | + conda install openfast==3.5.1 - - name: Add dependencies windows - if: true == contains( matrix.os, 'windows') - run: | - conda install -y m2w64-toolchain - - - name: Add dependencies windows - if: true == contains( matrix.os, 'mac') - shell: bash -l {0} - run: | - conda install -y gfortran - - - name: Setup Workspace - run: | - cmake -E make_directory ${{runner.workspace}}/ROSCO/ROSCO/build - - - name: Configure and Build - unix - if: false == contains( matrix.os, 'windows') - shell: bash -l {0} - working-directory: "${{runner.workspace}}/ROSCO/ROSCO/build" - run: | - cmake \ - -DCMAKE_INSTALL_PREFIX:PATH=${{runner.workspace}}/ROSCO/ROSCO/install \ - -DCMAKE_Fortran_COMPILER:STRING=${{env.FORTRAN_COMPILER}} \ - .. - cmake --build . --target install - - - name: Configure and Build - windows - if: true == contains( matrix.os, 'windows') - #shell: bash #-l {0} - working-directory: "${{runner.workspace}}/ROSCO/ROSCO/build" - run: | - cmake -G "MinGW Makefiles" -DCMAKE_INSTALL_PREFIX="${{runner.workspace}}/ROSCO/ROSCO/build" .. - cmake --build . --target install + - name: Generate Registry + run: | + python rosco/controller/rosco_registry/write_registry.py + + - name: Fix example file extensions + run: | + python Examples/Test_Cases/update_libdiscon_extension.py + + - name: Run ROSCO testing + run: | + cd rosco/test + python ROSCO_testing.py + + - name: Run regression testing + if: contains( matrix.os, 'ubuntu') + run: | + cd rosco/test + pytest . + + - name: Test walkthrough notebook + if: contains( matrix.os, 'ubuntu') + run: | + cd Examples + treon ROSCO_walkthrough.ipynb + diff --git a/.github/workflows/CI_rosco-pytools.yml b/.github/workflows/CI_rosco-pytools.yml deleted file mode 100644 index dbfe77ab..00000000 --- a/.github/workflows/CI_rosco-pytools.yml +++ /dev/null @@ -1,209 +0,0 @@ -name: CI_rosco-pytools - -# We run CI on push commits on all branches -on: [push, pull_request] - -# Specify FORTRAN compiler, used to be "gfortran-10" -env: - FC: gfortran - -# A workflow run is made up of one or more jobs that can run sequentially or in parallel -jobs: - build: - name: Build (${{ matrix.os }}) - runs-on: ${{ matrix.os }} - strategy: - fail-fast: true - matrix: - os: ["ubuntu-latest", "macOS-latest", "windows-latest"] - python-version: ["3.9"] - defaults: - run: - shell: bash -l {0} - - steps: - - name: Checkout repository and submodules - uses: actions/checkout@v3 - with: - submodules: recursive - - - name: Setup environment - uses: conda-incubator/setup-miniconda@v2 - with: - miniconda-version: "latest" - channels: conda-forge, general - auto-update-conda: true - python-version: 3.9 - environment-file: environment.yml - - - # Install dependencies of ROSCO toolbox - - name: Add dependencies windows specific - if: true == contains( matrix.os, 'windows') - run: | - conda install -y m2w64-toolchain libpython - env: - FC: gfortran - - - - name: Add dependencies macOS specific - if: true == contains( matrix.os, 'macOS') - run: | - conda install compilers - - # Install ROSCO toolbox - - name: Install ROSCO toolbox on Windows - if: true == contains( matrix.os, 'windows') - env: - FC: gfortran - run: | - python setup.py develop --compile-rosco - - - name: Install ROSCO toolbox - if: false == contains( matrix.os, 'windows') - run: | - python setup.py develop --compile-rosco - - - run_examples: - name: Run Examples - runs-on: ${{ matrix.os }} - strategy: - fail-fast: true - matrix: - os: ["ubuntu-latest"] #, "macOS-latest"] - python-version: ["3.9"] - defaults: - run: - shell: bash -l {0} - - steps: - - name: Checkout repository and submodules - uses: actions/checkout@v3 - with: - submodules: recursive - - - name: Setup environment - uses: conda-incubator/setup-miniconda@v2 - with: - miniconda-version: "latest" - channels: conda-forge, general - auto-update-conda: true - python-version: 3.9 - environment-file: environment.yml - - # setup cmake - - name: Setup Workspace - run: cmake -E make_directory ${{runner.workspace}}/ROSCO/ROSCO/build - - # Install dependencies of ROSCO toolbox - - name: Add dependencies ubuntu specific - run: | - conda install -y wisdem - - - name: Add pyFAST dependency - run: | - git clone http://github.com/OpenFAST/python-toolbox - cd python-toolbox - python -m pip install -e . - - # Install ZeroMQ - - name: Install ZeroMQ - run: sudo apt-get install libzmq3-dev - - # Install ROSCO toolbox - - name: Install ROSCO toolbox - run: | - python setup.py develop - - - name: Configure and Build ROSCO - unix - working-directory: ${{runner.workspace}}/ROSCO/ROSCO/build - run: | - cmake \ - -DCMAKE_INSTALL_PREFIX:PATH=${{runner.workspace}}/ROSCO/ROSCO/install \ - -DZMQ_CLIENT=ON \ - -DCMAKE_Fortran_COMPILER:STRING=${{env.FORTRAN_COMPILER}} \ - .. - cmake --build . --target install - - # Install OpenFAST - - name: Install OpenFAST - run: | - conda install openfast==3.4 - - # Run examples - - name: Run examples - run: | - cd Examples - python test_examples.py - - # Test walkthrough notebook - - name: Test walkthrough notebook - run: | - cd Examples - treon ROSCO_walkthrough.ipynb - - # Archive artifacts - - name: Archive production artifacts - if: success() || failure() - uses: actions/upload-artifact@v3 - with: - name: ROSCO-artifacts - path: | - ${{runner.workspace}} - - run_testing: - name: Run Testing - runs-on: ${{ matrix.os }} - strategy: - fail-fast: true - matrix: - os: ["ubuntu-latest"] #, "macOS-latest"] - python-version: ["3.9"] - defaults: - run: - shell: bash -l {0} - - steps: - - name: Checkout repository and submodules - uses: actions/checkout@v3 - with: - submodules: recursive - - - name: Setup environment - uses: conda-incubator/setup-miniconda@v2 - with: - miniconda-version: "latest" - channels: conda-forge, general - auto-update-conda: true - python-version: 3.9 - environment-file: environment.yml - - - # Install dependencies of ROSCO toolbox - - name: Add dependencies - run: | - conda install -y wisdem - - - # Install ROSCO toolbox - - name: Install ROSCO toolbox - run: | - python setup.py install --compile-rosco - - # Install OpenFAST - - name: Install OpenFAST - run: | - conda install openfast==3.4 - - # Run ROSCO Testing - - name: Run ROSCO testing - run: | - cd ROSCO_testing - python ROSCO_testing.py - - # Regression testing - - name: Run regression testing - run: | - cd ROSCO_testing - python test_checkpoint.py diff --git a/.github/workflows/Publish_ROSCO.yml b/.github/workflows/Publish_ROSCO.yml new file mode 100644 index 00000000..c6d7ba46 --- /dev/null +++ b/.github/workflows/Publish_ROSCO.yml @@ -0,0 +1,72 @@ +name: Build and upload to PyPI +# https://github.com/pypa/cibuildwheel/blob/main/examples/github-deploy.yml + +# Build on every branch push, tag push, and pull request change: +#on: [push, pull_request] +# Alternatively, to publish when a (published) GitHub Release is created, use the following: +on: + release: + types: + - published + +jobs: + build_wheels: + name: Build wheels on ${{ matrix.os }} + runs-on: ${{ matrix.os }} + strategy: + matrix: + os: [ubuntu-latest, windows-latest, macos-latest] + + steps: + - name: Setup GNU Fortran + uses: awvwgk/setup-fortran@v1 + + - name: Checkout + uses: actions/checkout@v4 + + - name: Build wheels + uses: pypa/cibuildwheel@v2.16.2 + + - uses: actions/upload-artifact@v4 + with: + name: cibw-wheels-${{ matrix.os }}-${{ strategy.job-index }} + path: ./wheelhouse/*.whl + + build_sdist: + name: Build source distribution + runs-on: ubuntu-latest + steps: + - uses: actions/checkout@v3 + + - name: Build sdist + run: pipx run build --sdist + + - uses: actions/upload-artifact@v4 + with: + name: cibw-sdist + path: dist/*.tar.gz + + upload_pypi: + needs: [build_wheels, build_sdist] + runs-on: ubuntu-latest + environment: pypi + permissions: + id-token: write # IMPORTANT: this permission is mandatory for trusted publishing + # upload to PyPI on every tag starting with 'v' + #if: github.event_name == 'push' && startsWith(github.ref, 'refs/tags/v') + # alternatively, to publish when a GitHub Release is created, use the following rule: + if: github.event_name == 'release' && github.event.action == 'published' + steps: + - uses: actions/download-artifact@v4 + with: + # unpacks all CIBW artifacts into dist/ + pattern: cibw-* + path: dist + merge-multiple: true + + - name: Upload to PyPI + uses: pypa/gh-action-pypi-publish@release/v1 + #with: + # user: __token__ + # password: ${{ secrets.pypi_password }} + # # To test: repository_url: https://test.pypi.org/legacy/ diff --git a/.readthedocs.yaml b/.readthedocs.yaml index 869209cb..061090c2 100644 --- a/.readthedocs.yaml +++ b/.readthedocs.yaml @@ -5,6 +5,15 @@ # Required version: 2 +# Add build os (and other options) +build: + os: ubuntu-22.04 + tools: + python: "mambaforge-22.9" + +conda: + environment: environment.yml + # Build documentation in the docs/ directory with Sphinx sphinx: builder: html @@ -17,11 +26,9 @@ formats: # Optionally set the version of Python and requirements required to build your docs python: - version: 3.8 install: - requirements: docs/requirements.txt - method: pip path: . extra_requirements: - docs - system_packages: true \ No newline at end of file diff --git a/Examples/01_turbine_model.py b/Examples/01_turbine_model.py index 95a69bac..ab1870d7 100644 --- a/Examples/01_turbine_model.py +++ b/Examples/01_turbine_model.py @@ -15,14 +15,14 @@ # Python Modules import os # ROSCO Modules -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.inputs.validation import load_rosco_yaml import matplotlib.pyplot as plt # Load yaml file this_dir = os.path.dirname(os.path.abspath(__file__)) -tune_dir = os.path.join(this_dir,'../Tune_Cases') +tune_dir = os.path.join(this_dir,'Tune_Cases') parameter_filename = os.path.join(tune_dir,'NREL5MW.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] @@ -34,7 +34,7 @@ turbine.load_from_fast( path_params['FAST_InputFile'], os.path.join(tune_dir,path_params['FAST_directory']), - rot_source='txt',txt_filename=os.path.join(tune_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) + rot_source='txt',txt_filename=os.path.join(tune_dir,path_params['rotor_performance_filename']) ) # Print some basic turbine info diff --git a/Examples/02_ccblade.py b/Examples/02_ccblade.py index 11afd6a2..581603d7 100644 --- a/Examples/02_ccblade.py +++ b/Examples/02_ccblade.py @@ -12,9 +12,9 @@ # Python modules import os # ROSCO toolbox modules -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.utilities import write_rotor_performance -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.utilities import write_rotor_performance +from rosco.toolbox.inputs.validation import load_rosco_yaml # Initialize parameter dictionaries turbine_params = {} control_params = {} @@ -26,7 +26,7 @@ # Load yaml file this_dir = os.path.dirname(os.path.abspath(__file__)) -tune_dir = os.path.join(this_dir,'../Tune_Cases') +tune_dir = os.path.join(this_dir,'Tune_Cases') parameter_filename = os.path.join(tune_dir,'NREL5MW.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] @@ -37,7 +37,7 @@ turbine = ROSCO_turbine.Turbine(turbine_params) turbine.load_from_fast( path_params['FAST_InputFile'], - os.path.join(this_dir,path_params['FAST_directory']), + os.path.join(tune_dir,path_params['FAST_directory']), rot_source='cc-blade', txt_filename=None) diff --git a/Examples/03_tune_controller.py b/Examples/03_tune_controller.py index 4aa19369..9d426e50 100644 --- a/Examples/03_tune_controller.py +++ b/Examples/03_tune_controller.py @@ -14,15 +14,15 @@ import matplotlib.pyplot as plt import os # ROSCO toolbox modules -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.utilities import write_DISCON -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.utilities import write_DISCON +from rosco.toolbox.inputs.validation import load_rosco_yaml # Load yaml file this_dir = os.path.dirname(os.path.abspath(__file__)) -tune_dir = os.path.join(this_dir,'../Tune_Cases') +tune_dir = os.path.join(this_dir,'Tune_Cases') parameter_filename = os.path.join(tune_dir,'NREL5MW.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] @@ -34,7 +34,7 @@ controller = ROSCO_controller.Controller(controller_params) # Load turbine data from OpenFAST and rotor performance text file -cp_filename = os.path.join(tune_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) +cp_filename = os.path.join(tune_dir,path_params['rotor_performance_filename']) turbine.load_from_fast( path_params['FAST_InputFile'], os.path.join(tune_dir,path_params['FAST_directory']), diff --git a/Examples/04_simple_sim.py b/Examples/04_simple_sim.py index aba7e468..a19a2ccb 100644 --- a/Examples/04_simple_sim.py +++ b/Examples/04_simple_sim.py @@ -17,19 +17,20 @@ # Python modules import matplotlib.pyplot as plt import numpy as np -import os, platform +import os # ROSCO toolbox modules -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox import sim as ROSCO_sim -from ROSCO_toolbox import control_interface as ROSCO_ci -from ROSCO_toolbox.utilities import write_DISCON -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco import discon_lib_path as lib_name +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import sim as ROSCO_sim +from rosco.toolbox import control_interface as ROSCO_ci +from rosco.toolbox.utilities import write_DISCON +from rosco.toolbox.inputs.validation import load_rosco_yaml # Load yaml file this_dir = os.path.dirname(os.path.abspath(__file__)) -tune_dir = os.path.join(this_dir,'../Tune_Cases') +tune_dir = os.path.join(this_dir,'Tune_Cases') parameter_filename = os.path.join(tune_dir,'NREL5MW.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] @@ -37,17 +38,11 @@ controller_params = inps['controller_params'] # Specify controller dynamic library path and name -this_dir = os.path.dirname(os.path.abspath(__file__)) -example_out_dir = os.path.join(this_dir,'examples_out') -if not os.path.isdir(example_out_dir): - os.makedirs(example_out_dir) - -if platform.system() == 'Windows': - lib_name = os.path.join(this_dir, '../ROSCO/build/libdiscon.dll') -elif platform.system() == 'Darwin': - lib_name = os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib') -else: - lib_name = os.path.join(this_dir, '../ROSCO/build/libdiscon.so') + +#directories +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) # # Load turbine model from saved pickle turbine = ROSCO_turbine.Turbine @@ -55,7 +50,7 @@ # controller = ROSCO_controller.Controller(controller_params) # Load turbine data from OpenFAST and rotor performance text file -cp_filename = os.path.join(tune_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) +cp_filename = os.path.join(tune_dir,path_params['rotor_performance_filename']) turbine.load_from_fast( path_params['FAST_InputFile'], os.path.join(tune_dir,path_params['FAST_directory']), diff --git a/Examples/05_openfast_sim.py b/Examples/05_openfast_sim.py index 7dd33085..3a45d40d 100644 --- a/Examples/05_openfast_sim.py +++ b/Examples/05_openfast_sim.py @@ -11,22 +11,23 @@ Note - you will need to have a compiled controller in ROSCO/build/ ''' # Python Modules -import yaml +#import yaml import os -import numpy as np -import matplotlib.pyplot as plt +#import numpy as np +#import matplotlib.pyplot as plt # ROSCO toolbox modules -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.utilities import write_DISCON, run_openfast -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.utilities import write_DISCON, run_openfast +from rosco.toolbox.inputs.validation import load_rosco_yaml this_dir = os.path.dirname(os.path.abspath(__file__)) +tune_dir = os.path.join(this_dir,'Tune_Cases') example_out_dir = os.path.join(this_dir,'examples_out') # Load yaml file -parameter_filename = os.path.join(os.path.dirname(this_dir), 'Tune_Cases', 'IEA15MW_MultiOmega.yaml') +parameter_filename = os.path.join(tune_dir, 'IEA15MW_MultiOmega.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] turbine_params = inps['turbine_params'] @@ -39,55 +40,24 @@ # Load turbine data from OpenFAST and rotor performance text file turbine.load_from_fast( path_params['FAST_InputFile'], - os.path.join(this_dir,path_params['FAST_directory']), + os.path.join(tune_dir,path_params['FAST_directory']), rot_source='txt', - txt_filename=os.path.join(this_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) + txt_filename=os.path.join(tune_dir,path_params['rotor_performance_filename']) ) # Tune controller controller.tune_controller(turbine) -# Now double Kp_float and check that it's passed through -Kp_float = -18 -controller_params['Kp_float'] = Kp_float -controller_params['tune_Fl'] = False -controller = ROSCO_controller.Controller(controller_params) -controller.tune_controller(turbine) -np.testing.assert_almost_equal(Kp_float,controller.Kp_float) - # Write parameter input file param_file = os.path.join(this_dir,'DISCON.IN') # This must be named DISCON.IN to be seen by the compiled controller binary. write_DISCON(turbine,controller,param_file=param_file, txt_filename=path_params['rotor_performance_filename']) -# Plot gain schedule -fig, ax = plt.subplots(2,2,constrained_layout=True,sharex=True) -ax = ax.flatten() -ax[0].plot(controller.v[len(controller.v_below_rated)+1:], controller.omega_pc_U) -ax[0].set_ylabel('omega_pc') - -ax[1].plot(controller.v[len(controller.v_below_rated)+1:], controller.zeta_pc_U) -ax[1].set_ylabel('zeta_pc') - -ax[2].plot(controller.v[len(controller.v_below_rated)+1:], controller.pc_gain_schedule.Kp) -ax[2].set_xlabel('Wind Speed') -ax[2].set_ylabel('Proportional Gain') - -ax[3].plot(controller.v[len(controller.v_below_rated)+1:], controller.pc_gain_schedule.Ki) -ax[3].set_xlabel('Wind Speed') -ax[3].set_ylabel('Integral Gain') - -plt.suptitle('Pitch Controller Gains') - -if False: - plt.show() -else: - plt.savefig(os.path.join(example_out_dir,'05_GainSched.png')) - # Run OpenFAST -# --- May need to change fastcall if you use a non-standard command to call openfast +# --- May need to change fastcall if you use a non-standard, conda-installed command to call openfast +# If you run the `fastcall` from the command line where you run this script, it should run OpenFAST fastcall = 'openfast' run_openfast( - os.path.join(this_dir,path_params['FAST_directory']), + os.path.join(tune_dir,path_params['FAST_directory']), fastcall=fastcall, fastfile=path_params['FAST_InputFile'], chdir=True diff --git a/Examples/06_peak_shaving.py b/Examples/06_peak_shaving.py index 525e4fc0..9bfa5228 100644 --- a/Examples/06_peak_shaving.py +++ b/Examples/06_peak_shaving.py @@ -14,13 +14,13 @@ import matplotlib.pyplot as plt import os # ROSCO toolbox modules -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.inputs.validation import load_rosco_yaml this_dir = os.path.dirname(__file__) -tune_dir = os.path.join(this_dir,'../Tune_Cases') +tune_dir = os.path.join(this_dir,'Tune_Cases') example_out_dir = os.path.join(this_dir,'examples_out') if not os.path.isdir(example_out_dir): os.makedirs(example_out_dir) @@ -44,7 +44,7 @@ turbine.load_from_fast( path_params['FAST_InputFile'], os.path.join(tune_dir,path_params['FAST_directory']), - rot_source='txt',txt_filename=os.path.join(tune_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) + rot_source='txt',txt_filename=os.path.join(tune_dir,path_params['rotor_performance_filename']) ) # Tune controller controller.tune_controller(turbine) diff --git a/Examples/07_openfast_outputs.py b/Examples/07_openfast_outputs.py index d50eab99..ed19bc63 100644 --- a/Examples/07_openfast_outputs.py +++ b/Examples/07_openfast_outputs.py @@ -8,14 +8,14 @@ - Trim the time series - Plot some available channels -Note: need to run openfast model in '../Test_Cases/5MW_Land_DLL_WTurb/' to plot +Note: need to run openfast model in 'Test_Cases/5MW_Land_DLL_WTurb/' to plot ''' # Python Modules -import numpy as np +#import numpy as np import matplotlib.pyplot as plt # ROSCO toolbox modules -from ROSCO_toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.ofTools.fast_io import output_processing import os this_dir = os.path.dirname(os.path.abspath(__file__)) @@ -24,7 +24,7 @@ os.makedirs(example_out_dir) # Define openfast output filenames -filenames = ["../Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.outb"] +filenames = ["Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.outb"] # ---- Note: Could load and plot multiple cases, textfiles, and binaries... # filenames = ["../Test_Cases/NREL-5MW/NREL-5MW.outb", # "../Test_Cases/NREL-5MW/NREL-5MW_ex8.outb"] diff --git a/Examples/08_run_turbsim.py b/Examples/08_run_turbsim.py index 488b07ea..bbacb93e 100644 --- a/Examples/08_run_turbsim.py +++ b/Examples/08_run_turbsim.py @@ -8,13 +8,13 @@ ''' # ROSCO toolbox modules -from ROSCO_toolbox.utilities import run_openfast +from rosco.toolbox.utilities import run_openfast import os this_dir = os.path.dirname(os.path.abspath(__file__)) # Define openfast output filenames -wind_directory = os.path.join(this_dir,'../Test_Cases/Wind/') +wind_directory = os.path.join(this_dir,'Test_Cases/Wind/') turbsim_infile = '90m_12mps_twr.inp' run_openfast(wind_directory, fastcall='turbsim', diff --git a/Examples/09_distributed_aero.py b/Examples/09_distributed_aero.py index 234fd6de..810de3f2 100644 --- a/Examples/09_distributed_aero.py +++ b/Examples/09_distributed_aero.py @@ -18,15 +18,16 @@ # Python Modules import os # ROSCO Modules -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox.inputs.validation import load_rosco_yaml this_dir = os.path.dirname(os.path.abspath(__file__)) +tune_dir = os.path.join(this_dir,'Tune_Cases') # Load yaml file -parameter_filename = os.path.join(os.path.dirname(this_dir),'Tune_Cases/BAR.yaml') +parameter_filename = os.path.join(tune_dir,'BAR.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] turbine_params = inps['turbine_params'] @@ -36,7 +37,7 @@ turbine = ROSCO_turbine.Turbine(turbine_params) turbine.load_from_fast( path_params['FAST_InputFile'], - os.path.join(this_dir,path_params['FAST_directory']) + os.path.join(tune_dir,path_params['FAST_directory']) ) # Tune controller diff --git a/Examples/10_linear_params.py b/Examples/10_linear_params.py index 69aa3094..dc09aba6 100644 --- a/Examples/10_linear_params.py +++ b/Examples/10_linear_params.py @@ -12,23 +12,27 @@ # Python Modules import os # ROSCO toolbox modules -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.inputs.validation import load_rosco_yaml import numpy as np +this_dir = os.path.dirname(os.path.abspath(__file__)) +tune_dir = os.path.join(this_dir,'Tune_Cases') + # Load yaml file -parameter_filename = os.path.join( os.path.dirname( os.path.dirname( os.path.realpath(__file__) )), - 'Tune_Cases', 'IEA15MW.yaml') +parameter_filename = os.path.join( tune_dir, 'IEA15MW.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] turbine_params = inps['turbine_params'] controller_params = inps['controller_params'] # Linear file output -this_dir = os.path.dirname(os.path.abspath(__file__)) + + +os.path.join(this_dir,path_params['FAST_directory']) example_out_dir = os.path.join(this_dir,'examples_out') if not os.path.isdir(example_out_dir): os.makedirs(example_out_dir) @@ -40,12 +44,11 @@ controller = ROSCO_controller.Controller(controller_params) # Load turbine data from OpenFAST and rotor performance text file -tune_dir = os.path.join(this_dir,'../Tune_Cases') turbine.load_from_fast( path_params['FAST_InputFile'], - os.path.join(this_dir,path_params['FAST_directory']), + os.path.join(tune_dir,path_params['FAST_directory']), rot_source='txt', - txt_filename=os.path.join(tune_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) + txt_filename=os.path.join(tune_dir,path_params['rotor_performance_filename']) ) # Tune controller diff --git a/Examples/11_robust_tuning.py b/Examples/11_robust_tuning.py index aa4d7df6..171968ae 100644 --- a/Examples/11_robust_tuning.py +++ b/Examples/11_robust_tuning.py @@ -3,6 +3,8 @@ Controller tuning to satisfy a robustness criteria ------------------------------------- NOTE: This example necessitates the mbc3 through either pyFAST or WEIS +pyFAST is the easiest to install by cloning https://github.com/OpenFAST/openfast_toolbox and +running `python setup.py develop` from your conda environment In this example: - setup ROSCO's robust tuning methods for the IEA15MW on the UMaine Semi-sub @@ -16,17 +18,17 @@ import os import numpy as np import matplotlib.pyplot as plt -from ROSCO_toolbox.inputs.validation import load_rosco_yaml -from ROSCO_toolbox.linear.robust_scheduling import rsched_driver, load_linturb -from ROSCO_toolbox.linear.lin_vis import lin_plotting -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox import controller as ROSCO_controller +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.linear.robust_scheduling import rsched_driver, load_linturb +from rosco.toolbox.linear.lin_vis import lin_plotting +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import controller as ROSCO_controller def run_example(): # Shorthand directories this_dir = os.path.dirname(os.path.abspath(__file__)) - tune_dir = os.path.join(this_dir, '../Tune_Cases') - test_dir = os.path.join(this_dir, '../Test_Cases') + tune_dir = os.path.join(this_dir, 'Tune_Cases') + test_dir = os.path.join(this_dir, 'Test_Cases') # ROSCO options parameter_filename = os.path.join(tune_dir, 'IEA15MW_robust.yaml') @@ -43,6 +45,7 @@ def run_example(): # Path options example_out_dir = os.path.join(os.path.dirname(os.path.abspath(__file__)), 'examples_out') + os.makedirs(example_out_dir,exist_ok=True) output_name = '11_robust_scheduling' path_options = {'output_dir': example_out_dir, 'output_name': output_name @@ -53,12 +56,12 @@ def run_example(): controller = ROSCO_controller.Controller(controller_params) turbine.load_from_fast( path_params['FAST_InputFile'], - os.path.join(this_dir, path_params['FAST_directory']), - rot_source='txt', txt_filename=os.path.join(this_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) + os.path.join(tune_dir, path_params['FAST_directory']), + rot_source='txt', txt_filename=os.path.join(tune_dir,path_params['rotor_performance_filename']) ) # Fix path params for robust setup - path_params['FAST_directory'] = os.path.join(this_dir, path_params['FAST_directory']) + path_params['FAST_directory'] = os.path.join(tune_dir, path_params['FAST_directory']) controller.tune_controller(turbine) k_float = controller.Kp_float @@ -78,7 +81,7 @@ def run_example(): options['path_options'] = path_options options['opt_options'] = opt_options - options['linturb_options']['linfile_path'] = os.path.join(this_dir, options['linturb_options']['linfile_path']) + options['linturb_options']['linfile_path'] = os.path.join(tune_dir, options['linturb_options']['linfile_path']) # Run robust scheduling sd = rsched_driver(options) diff --git a/Examples/12_tune_ipc.py b/Examples/12_tune_ipc.py index e435becf..6bb5b9e8 100644 --- a/Examples/12_tune_ipc.py +++ b/Examples/12_tune_ipc.py @@ -10,13 +10,13 @@ ''' # Python Modules -import os, platform +import os import matplotlib.pyplot as plt # ROSCO toolbox modules -from ROSCO_toolbox.ofTools.fast_io import output_processing -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl def main(): this_dir = os.path.dirname(os.path.abspath(__file__)) @@ -26,12 +26,11 @@ def main(): run_dir = os.path.join(example_out_dir, example_name) # Load yaml file (Open Loop Case) - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/NREL2p8.yaml') + parameter_filename = os.path.join(this_dir,'Tune_Cases/NREL2p8.yaml') case_inputs = {} case_inputs[('ServoDyn','Ptch_Cntrl')] = {'vals': [1], 'group': 0} case_inputs[('DISCON_in','IPC_SatMode')] = {'vals': [0,1,2,3], 'group': 1} - # simulation set up diff --git a/Examples/14_open_loop_control.py b/Examples/14_open_loop_control.py index 7ca79462..862b6306 100644 --- a/Examples/14_open_loop_control.py +++ b/Examples/14_open_loop_control.py @@ -11,23 +11,26 @@ ''' # Python Modules -import yaml, os, platform +import os import numpy as np import matplotlib.pyplot as plt # ROSCO toolbox modules -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox import utilities as ROSCO_utilities -from ROSCO_toolbox.ofTools.fast_io import output_processing -from ROSCO_toolbox.inputs.validation import load_rosco_yaml -from ROSCO_toolbox.ofTools.case_gen.CaseLibrary import set_channels -from ROSCO_toolbox.ofTools.case_gen.runFAST_pywrapper import runFAST_pywrapper, runFAST_pywrapper_batch -from ROSCO_toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General +from rosco import discon_lib_path +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import utilities as ROSCO_utilities +from rosco.toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.ofTools.case_gen.CaseLibrary import set_channels +from rosco.toolbox.ofTools.case_gen.runFAST_pywrapper import runFAST_pywrapper, runFAST_pywrapper_batch +from rosco.toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General this_dir = os.path.dirname(os.path.abspath(__file__)) +tune_dir = os.path.join(this_dir,'Tune_Cases') + rosco_dir = os.path.dirname(this_dir) example_out_dir = os.path.join(this_dir,'examples_out') example_out_dir = os.path.join(this_dir,'examples_out') @@ -35,7 +38,7 @@ os.makedirs(example_out_dir) # Load yaml file (Open Loop Case) -parameter_filename = os.path.join(rosco_dir,'Tune_Cases/IEA15MW_OL.yaml') +parameter_filename = os.path.join(tune_dir, 'IEA15MW_OL.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] @@ -75,9 +78,9 @@ # Load turbine data from OpenFAST and rotor performance text file turbine.load_from_fast(path_params['FAST_InputFile'], \ - os.path.join(this_dir,path_params['FAST_directory']), \ + os.path.join(tune_dir,path_params['FAST_directory']), \ rot_source='txt',\ - txt_filename=os.path.join(this_dir,path_params['FAST_directory'],path_params['rotor_performance_filename'])) + txt_filename=os.path.join(tune_dir,path_params['rotor_performance_filename'])) # Tune controller controller.tune_controller(turbine) @@ -87,23 +90,14 @@ ROSCO_utilities.write_DISCON(turbine,controller,param_file=param_file, txt_filename=path_params['rotor_performance_filename']) ### Run OpenFAST using aeroelasticse tools - -# Set rosco_dll -if platform.system() == 'Windows': - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.dll') -elif platform.system() == 'Darwin': - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.dylib') -else: - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.so') - case_inputs = {} -case_inputs[('ServoDyn','DLL_FileName')] = {'vals': [rosco_dll], 'group': 0} +case_inputs[('ServoDyn','DLL_FileName')] = {'vals': [discon_lib_path], 'group': 0} # Apply all discon variables as case inputs discon_vt = ROSCO_utilities.DISCON_dict( turbine, controller, -txt_filename=os.path.join(this_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) +txt_filename=os.path.join(tune_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) ) for discon_input in discon_vt: case_inputs[('DISCON_in',discon_input)] = {'vals': [discon_vt[discon_input]], 'group': 0} @@ -124,7 +118,7 @@ # Run FAST cases fastBatch = runFAST_pywrapper_batch() -fastBatch.FAST_directory = os.path.realpath(os.path.join(rosco_dir,'Tune_Cases',path_params['FAST_directory'])) +fastBatch.FAST_directory = os.path.realpath(os.path.join(tune_dir,path_params['FAST_directory'])) fastBatch.FAST_InputFile = path_params['FAST_InputFile'] fastBatch.channels = channels fastBatch.FAST_runDirectory = run_dir @@ -145,6 +139,22 @@ fastout = op.load_fast_out(out_file, tmin=0) fig, ax = op.plot_fast_out(cases=cases,showplot=False) +# Check that open loop commands are close to control outputs from OpenFAST +fo = fastout[0] +tt = fo['Time'] +valid_ind = tt > 2 # first few timesteps can differ, depending on OpenFAST solve config + +# Compute errors +nacelle_yaw_diff = fo['NacYaw'][valid_ind] - np.degrees(np.interp(tt[valid_ind],olc.ol_timeseries['time'],olc.ol_timeseries['nacelle_yaw'])) +bld_pitch_diff = fo['BldPitch1'][valid_ind] - np.degrees(np.interp(tt[valid_ind],olc.ol_timeseries['time'],olc.ol_timeseries['blade_pitch'])) +gen_tq_diff = fo['GenTq'][valid_ind] - np.interp(tt[valid_ind],olc.ol_timeseries['time'],olc.ol_timeseries['generator_torque'])/1e3 + +# Check diff timeseries +np.testing.assert_allclose(nacelle_yaw_diff, 0, atol = 1e-1) # yaw has dynamics and integration error, tolerance higher +np.testing.assert_allclose(bld_pitch_diff, 0, atol = 1e-3) +np.testing.assert_allclose(gen_tq_diff, 0, atol = 1e-3) + + if False: plt.show() else: diff --git a/Examples/15_pass_through.py b/Examples/15_pass_through.py index f33fd3f7..c0b7916d 100644 --- a/Examples/15_pass_through.py +++ b/Examples/15_pass_through.py @@ -9,8 +9,8 @@ ''' import os -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl #directories @@ -24,7 +24,7 @@ def main(): # Simulation config r = run_FAST_ROSCO() - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/NREL5MW_PassThrough.yaml') + parameter_filename = os.path.join(this_dir,'Tune_Cases/NREL5MW_PassThrough.yaml') run_dir = os.path.join(example_out_dir,'15_PassThrough') os.makedirs(run_dir,exist_ok=True) diff --git a/Examples/16_external_dll.py b/Examples/16_external_dll.py index afb629ec..cb79ab07 100644 --- a/Examples/16_external_dll.py +++ b/Examples/16_external_dll.py @@ -8,8 +8,9 @@ ''' import os, platform -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco import discon_lib_path as lib_name +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl import shutil @@ -19,13 +20,6 @@ example_out_dir = os.path.join(this_dir,'examples_out') os.makedirs(example_out_dir,exist_ok=True) -if platform.system() == 'Windows': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dll')) -elif platform.system() == 'Darwin': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib')) -else: - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.so')) - def main(): @@ -36,16 +30,15 @@ def main(): # Ensure external control paths are okay - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/IEA15MW_ExtInterface.yaml') + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW_ExtInterface.yaml') run_dir = os.path.join(example_out_dir,'16_ExtInterface') os.makedirs(run_dir,exist_ok=True) # Set DLL file and DISCON input dynamically (hard-coded in yaml) controller_params = {} controller_params['DISCON'] = {} - controller_params['OL_Mode'] = 2 controller_params['DISCON']['DLL_FileName'] = copy_lib - controller_params['DISCON']['DLL_InFile'] = os.path.join(rosco_dir,'Test_Cases/NREL-5MW/DISCON.IN') + controller_params['DISCON']['DLL_InFile'] = os.path.join(this_dir,'Test_Cases/NREL-5MW/DISCON.IN') controller_params['DISCON']['DLL_ProcName'] = 'DISCON' # simulation set up @@ -65,4 +58,4 @@ def main(): if __name__=="__main__": - main() \ No newline at end of file + main() diff --git a/Examples/17_zeromq_interface.py b/Examples/17_zeromq_interface.py deleted file mode 100644 index ae8a34ae..00000000 --- a/Examples/17_zeromq_interface.py +++ /dev/null @@ -1,133 +0,0 @@ -''' ------------ 17_zeromq_interface -------------- -Run ROSCO using the ROSCO toolbox control interface and execute communication with ZeroMQ -------------------------------------- - -A demonstrator for ZeroMQ communication. Instead of using ROSCO with with control interface, -one could call ROSCO from OpenFAST, and communicate with ZeroMQ through that. -''' - - -import platform -import os -import matplotlib.pyplot as plt -from ROSCO_toolbox.inputs.validation import load_rosco_yaml -from ROSCO_toolbox.utilities import write_DISCON -from ROSCO_toolbox import control_interface as ROSCO_ci -from ROSCO_toolbox.control_interface import turbine_zmq_server -from ROSCO_toolbox import sim as ROSCO_sim -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox import controller as ROSCO_controller -import numpy as np -import multiprocessing as mp - -def run_zmq(): - connect_zmq = True - s = turbine_zmq_server(network_address="tcp://*:5555", timeout=10.0, verbose=True) - while connect_zmq: - # Get latest measurements from ROSCO - measurements = s.get_measurements() - - # Decide new control input based on measurements - current_time = measurements['Time'] - if current_time <= 10.0: - yaw_setpoint = 0.0 - else: - yaw_setpoint = 20.0 - - # Send new setpoints back to ROSCO - s.send_setpoints(nacelleHeading=yaw_setpoint) - - if measurements['iStatus'] == -1: - connect_zmq = False - s._disconnect() - - -def sim_rosco(): - # Load yaml file - this_dir = os.path.dirname(os.path.abspath(__file__)) - tune_dir = os.path.join(this_dir, '../Tune_Cases') - parameter_filename = os.path.join(tune_dir, 'NREL5MW.yaml') - inps = load_rosco_yaml(parameter_filename) - path_params = inps['path_params'] - turbine_params = inps['turbine_params'] - controller_params = inps['controller_params'] - - # Enable ZeroMQ & yaw control - controller_params['Y_ControlMode'] = 1 - controller_params['ZMQ_Mode'] = 1 - - # Specify controller dynamic library path and name - this_dir = os.path.dirname(os.path.abspath(__file__)) - example_out_dir = os.path.join(this_dir, 'examples_out') - if not os.path.isdir(example_out_dir): - os.makedirs(example_out_dir) - - if platform.system() == 'Windows': - lib_name = os.path.join(this_dir, '../ROSCO/build/libdiscon.dll') - elif platform.system() == 'Darwin': - lib_name = os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib') - else: - lib_name = os.path.join(this_dir, '../ROSCO/build/libdiscon.so') - - # # Load turbine model from saved pickle - turbine = ROSCO_turbine.Turbine - turbine = turbine.load(os.path.join(example_out_dir, '01_NREL5MW_saved.p')) - - # Load turbine data from OpenFAST and rotor performance text file - cp_filename = os.path.join( - tune_dir, path_params['FAST_directory'], path_params['rotor_performance_filename']) - turbine.load_from_fast( - path_params['FAST_InputFile'], - os.path.join(tune_dir, path_params['FAST_directory']), - rot_source='txt', txt_filename=cp_filename - ) - - # Tune controller - controller = ROSCO_controller.Controller(controller_params) - controller.tune_controller(turbine) - - # Write parameter input file - param_filename = os.path.join(this_dir, 'DISCON_zmq.IN') - write_DISCON( - turbine, controller, - param_file=param_filename, - txt_filename=cp_filename - ) - - - # Load controller library - controller_int = ROSCO_ci.ControllerInterface(lib_name, param_filename=param_filename, sim_name='sim-zmq') - - # Load the simulator - sim = ROSCO_sim.Sim(turbine, controller_int) - - # Define a wind speed history - dt = 0.025 - tlen = 100 # length of time to simulate (s) - ws0 = 7 # initial wind speed (m/s) - t = np.arange(0, tlen, dt) - ws = np.ones_like(t) * ws0 - # add steps at every 100s - for i in range(len(t)): - ws[i] = ws[i] + t[i]//100 - - # Define wind directions as zeros - wd = np.zeros_like(t) - - # Run simulator and plot results - sim.sim_ws_wd_series(t, ws, wd, rotor_rpm_init=4, make_plots=True) - - if False: - plt.show() - else: - plt.savefig(os.path.join(example_out_dir, '16_NREL5MW_zmqYaw.png')) - - -if __name__ == "__main__": - p1 = mp.Process(target=run_zmq) - p1.start() - p2 = mp.Process(target=sim_rosco) - p2.start() - p1.join() - p2.join() diff --git a/Examples/17a_zeromq_simple.py b/Examples/17a_zeromq_simple.py new file mode 100644 index 00000000..2ccae2be --- /dev/null +++ b/Examples/17a_zeromq_simple.py @@ -0,0 +1,166 @@ +''' +----------- 17_zeromq_interface -------------- +Run ROSCO using the ROSCO toolbox control interface and execute communication with ZeroMQ +------------------------------------- + +A demonstrator for ZeroMQ communication. Instead of using ROSCO with with control interface, +one could call ROSCO from OpenFAST, and communicate with ZeroMQ through that. +''' + + +import os +import matplotlib.pyplot as plt +from rosco import discon_lib_path +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.utilities import write_DISCON +from rosco.toolbox import control_interface as ROSCO_ci +from rosco.toolbox.control_interface import wfc_zmq_server +from rosco.toolbox import sim as ROSCO_sim +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox.ofTools.fast_io import output_processing +import numpy as np +import multiprocessing as mp + +TIME_CHECK = 30 +DESIRED_YAW_OFFSET = 20 +DESIRED_PITCH_OFFSET = np.deg2rad(2) * np.sin(0.1 * TIME_CHECK) + np.deg2rad(2) + +#directories +this_dir = os.path.dirname(os.path.abspath(__file__)) +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) + +def run_zmq(logfile=None): + # Start the server at the following address + network_address = "tcp://*:5555" + server = wfc_zmq_server(network_address, timeout=60.0, verbose=False, logfile=logfile) + + # Provide the wind farm control algorithm as the wfc_controller method of the server + server.wfc_controller = wfc_controller + + # Run the server to receive measurements and send setpoints + server.runserver() + +def wfc_controller(id,current_time,measurements): + if current_time <= 10.0: + yaw_setpoint = 0.0 + else: + yaw_setpoint = DESIRED_YAW_OFFSET + + # Pitch offset + if current_time >= 10.0: + col_pitch_command = np.deg2rad(2) * np.sin(0.1 * current_time) + np.deg2rad(2) # Implement dynamic induction control + else: + col_pitch_command = 0.0 + + # Send new setpoints back to ROSCO + setpoints = {} + setpoints['ZMQ_TorqueOffset'] = 0.0 + setpoints['ZMQ_YawOffset'] = yaw_setpoint + setpoints['ZMQ_PitOffset(1)'] = col_pitch_command + setpoints['ZMQ_PitOffset(2)'] = col_pitch_command + setpoints['ZMQ_PitOffset(3)'] = col_pitch_command + return setpoints + +def sim_rosco(): + # Load yaml file + this_dir = os.path.dirname(os.path.abspath(__file__)) + tune_dir = os.path.join(this_dir, 'Tune_Cases') + parameter_filename = os.path.join(tune_dir, 'NREL5MW.yaml') + inps = load_rosco_yaml(parameter_filename) + path_params = inps['path_params'] + turbine_params = inps['turbine_params'] + controller_params = inps['controller_params'] + + # Enable ZeroMQ & yaw control + controller_params['Y_ControlMode'] = 1 + controller_params['ZMQ_Mode'] = 1 + controller_params['ZMQ_UpdatePeriod'] = 0.025 + + # # Load turbine model from saved pickle + turbine = ROSCO_turbine.Turbine + turbine = turbine.load(os.path.join(example_out_dir, '01_NREL5MW_saved.p')) + + # Load turbine data from OpenFAST and rotor performance text file + cp_filename = os.path.join( + tune_dir, path_params['rotor_performance_filename']) + turbine.load_from_fast( + path_params['FAST_InputFile'], + os.path.join(tune_dir, path_params['FAST_directory']), + rot_source='txt', txt_filename=cp_filename + ) + + # Tune controller + controller_params['LoggingLevel'] = 2 + controller = ROSCO_controller.Controller(controller_params) + controller.tune_controller(turbine) + + # Write parameter input file + sim_dir = os.path.join(example_out_dir,'17_ZeroMQ') + os.makedirs(sim_dir,exist_ok=True) + param_filename = os.path.join(sim_dir, 'DISCON_zmq.IN') + write_DISCON( + turbine, controller, + param_file=param_filename, + txt_filename=cp_filename + ) + + + # Load controller library + controller_int = ROSCO_ci.ControllerInterface( + discon_lib_path, + param_filename=param_filename, + sim_name=os.path.join(sim_dir,'sim-zmq') + ) + + # Load the simulator + sim = ROSCO_sim.Sim(turbine, controller_int) + + # Define a wind speed history + dt = 0.025 + tlen = 100 # length of time to simulate (s) + ws0 = 7 # initial wind speed (m/s) + t = np.arange(0, tlen, dt) + ws = np.ones_like(t) * ws0 + # add steps at every 100s + for i in range(len(t)): + ws[i] = ws[i] + t[i]//100 + + # Define wind directions as zeros + wd = np.zeros_like(t) + + # Run simulator and plot results + sim.sim_ws_wd_series(t, ws, wd, rotor_rpm_init=4, make_plots=True) + + if False: + plt.show() + else: + plt.savefig(os.path.join(example_out_dir, '17_NREL5MW_ZMQ.png')) + + # Check that info is passed to ROSCO + op = output_processing.output_processing() + local_vars = op.load_fast_out([os.path.join(sim_dir,'sim-zmq.RO.dbg2')], tmin=0) + fig, axs = plt.subplots(2,1) + axs[0].plot(local_vars[0]['Time'],local_vars[0]['ZMQ_YawOffset']) + axs[1].plot(local_vars[0]['Time'],local_vars[0]['ZMQ_PitOffset']) + + if False: + plt.show() + else: + plt.savefig(os.path.join(example_out_dir, '17_NREL5MW_ZMQ_Setpoints.png')) + + # Spot check input at time = 30 sec. + ind_30 = local_vars[0]['Time'] == TIME_CHECK + np.testing.assert_almost_equal(local_vars[0]['ZMQ_YawOffset'][ind_30], DESIRED_YAW_OFFSET) + np.testing.assert_almost_equal(local_vars[0]['ZMQ_PitOffset'][ind_30], DESIRED_PITCH_OFFSET, decimal=3) + +if __name__ == "__main__": + logfile = os.path.join(example_out_dir,os.path.splitext(os.path.basename(__file__))[0]+'.log') + p1 = mp.Process(target=run_zmq,args=(logfile,)) + p1.start() + p2 = mp.Process(target=sim_rosco) + p2.start() + p1.join() + p2.join() diff --git a/Examples/17b_zeromq_multi_openfast.py b/Examples/17b_zeromq_multi_openfast.py new file mode 100644 index 00000000..0de4d9a7 --- /dev/null +++ b/Examples/17b_zeromq_multi_openfast.py @@ -0,0 +1,160 @@ +import os +import numpy as np +import multiprocessing as mp +import matplotlib.pyplot as plt +from rosco.toolbox.control_interface import wfc_zmq_server +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.fast_io import output_processing + + +this_dir = os.path.dirname(os.path.abspath(__file__)) +example_out_dir = os.path.join(this_dir, "examples_out") +os.makedirs(example_out_dir, exist_ok=True) +TIME_CHECK = 20 +DESIRED_YAW_OFFSET = [-10, 10] + + +def run_zmq(logfile=None): + """Start the ZeroMQ server for wind farm control""" + + # Start the server at the following address + network_address = "tcp://*:5555" + server = wfc_zmq_server(network_address, timeout=60.0, verbose=False, logfile = logfile) + + # Provide the wind farm control algorithm as the wfc_controller method of the server + server.wfc_controller = wfc_controller + + # Run the server to receive measurements and send setpoints + server.runserver() + + +def wfc_controller(id, current_time, measurements): + """ + Users needs to define this function to implement wind farm controller. + The user defined function should take as argument the turbine id, the + current time and current measurements and return the setpoints + for the particular turbine for the current time. It should ouput the + setpoints as a dictionary whose keys should be as defined in + wfc_zmq_server.wfc_interface. The wfc_controller method of the wfc_zmq_server + should be overwriten with this fuction, otherwise, an exception is raised and + the simulation stops. + """ + if current_time <= 10.0: + YawOffset = 0.0 + col_pitch_command = 0.0 + else: + col_pitch_command = np.deg2rad(2) * np.sin(0.1 * current_time) + np.deg2rad(2) # Implement dynamic induction control + if id == 1: + YawOffset = DESIRED_YAW_OFFSET[0] + else: + YawOffset = DESIRED_YAW_OFFSET[1] + + + setpoints = {} + setpoints["ZMQ_YawOffset"] = YawOffset + setpoints['ZMQ_PitOffset(1)'] = col_pitch_command + setpoints['ZMQ_PitOffset(2)'] = col_pitch_command + setpoints['ZMQ_PitOffset(3)'] = col_pitch_command + return setpoints + + +def sim_openfast_1(): + """Run the first OpenFAST simulation with ZeroMQ enabled""" + r = run_FAST_ROSCO() + r.tuning_yaml = "NREL5MW.yaml" + r.wind_case_fcn = cl.power_curve + r.wind_case_opts = { + "U": [8], + "TMax": 25, + } + run_dir = os.path.join(example_out_dir, "17b_zeromq_OF1") + r.controller_params = {} + r.controller_params["LoggingLevel"] = 2 + r.controller_params["DISCON"] = {} + r.controller_params["DISCON"]["ZMQ_Mode"] = 1 + r.controller_params["DISCON"]["ZMQ_ID"] = 1 + r.save_dir = run_dir + r.run_FAST() + + +def sim_openfast_2(): + """Run the second OpenFAST simulation with ZeroMQ enabled""" + r = run_FAST_ROSCO() + r.tuning_yaml = "NREL5MW.yaml" + r.wind_case_fcn = cl.power_curve + r.wind_case_opts = { + "U": [8], + "TMax": 25, + } + run_dir = os.path.join(example_out_dir, "17b_zeromq_OF2") + r.save_dir = run_dir + r.controller_params = {} + r.controller_params["DISCON"] = {} + r.controller_params["LoggingLevel"] = 2 + r.controller_params["DISCON"]["ZMQ_Mode"] = 1 + r.controller_params["DISCON"]["ZMQ_ID"] = 2 + r.run_FAST() + + +if __name__ == "__main__": + # Start wind farm control server and two openfast simulation + # as separate processes + logfile = os.path.join(example_out_dir,os.path.splitext(os.path.basename(__file__))[0]+'.log') + p0 = mp.Process(target=run_zmq,args=(logfile,)) + p1 = mp.Process(target=sim_openfast_1) + p2 = mp.Process(target=sim_openfast_2) + + p0.start() + p1.start() + p2.start() + + p0.join() + p1.join() + p2.join() + + ## Run tests + # Check that info is passed to ROSCO for first simulation + op1 = output_processing.output_processing() + debug_file1 = os.path.join( + example_out_dir, + "17b_zeromq_OF1", + "NREL5MW", + "power_curve", + "base", + "NREL5MW_0.RO.dbg2", + ) + local_vars1 = op1.load_fast_out(debug_file1, tmin=0) + + # Check that info is passed to ROSCO for first simulation + op2 = output_processing.output_processing() + debug_file2 = os.path.join( + example_out_dir, + "17b_zeromq_OF2", + "NREL5MW", + "power_curve", + "base", + "NREL5MW_0.RO.dbg2", + ) + local_vars2 = op2.load_fast_out(debug_file2, tmin=0) + + # Generate plots + _, axs = plt.subplots(2, 1) + axs[0].plot(local_vars1[0]["Time"], local_vars1[0]["ZMQ_YawOffset"]) + axs[1].plot(local_vars2[0]["Time"], local_vars2[0]["ZMQ_YawOffset"]) + + if False: + plt.show() + else: + plt.savefig(os.path.join(example_out_dir, "17b_NREL5MW_ZMQ_Setpoints.png")) + + # Spot check input at time = 30 sec. + ind1_30 = local_vars1[0]["Time"] == TIME_CHECK + ind2_30 = local_vars2[0]["Time"] == TIME_CHECK + + np.testing.assert_almost_equal( + local_vars1[0]["ZMQ_YawOffset"][ind1_30], DESIRED_YAW_OFFSET[0] + ) + np.testing.assert_almost_equal( + local_vars2[0]["ZMQ_YawOffset"][ind2_30], DESIRED_YAW_OFFSET[1] + ) diff --git a/Examples/18_pitch_offsets.py b/Examples/18_pitch_offsets.py index ace996c5..74f42201 100644 --- a/Examples/18_pitch_offsets.py +++ b/Examples/18_pitch_offsets.py @@ -7,10 +7,10 @@ ''' -import os, platform -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl -from ROSCO_toolbox.ofTools.fast_io import output_processing +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.ofTools.fast_io import output_processing import numpy as np @@ -20,18 +20,11 @@ example_out_dir = os.path.join(this_dir,'examples_out') os.makedirs(example_out_dir,exist_ok=True) -if platform.system() == 'Windows': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dll')) -elif platform.system() == 'Darwin': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib')) -else: - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.so')) - def main(): # Input yaml and output directory - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/IEA15MW.yaml') + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW.yaml') run_dir = os.path.join(example_out_dir,'18_PitchFaults') os.makedirs(run_dir,exist_ok=True) @@ -74,6 +67,8 @@ def main(): offset_3 = fastout[0]['BldPitch3'] - fastout[0]['BldPitch1'] # check that offset (min,max) is very close to prescribed values + # Note that some OpenFAST configurations (e.g., fixed bottom) do not apply offet on + # first timestep and this example may fail np.testing.assert_almost_equal(offset_2.max(),pitch2_offset,decimal=3) np.testing.assert_almost_equal(offset_2.min(),pitch2_offset,decimal=3) np.testing.assert_almost_equal(offset_3.max(),pitch3_offset,decimal=3) @@ -82,4 +77,4 @@ def main(): if __name__=="__main__": - main() \ No newline at end of file + main() diff --git a/Examples/19_update_discon_version.py b/Examples/19_update_discon_version.py index 342cd4d2..e4cd2960 100644 --- a/Examples/19_update_discon_version.py +++ b/Examples/19_update_discon_version.py @@ -5,7 +5,7 @@ ''' import os -from ROSCO_toolbox.tune import update_discon_version +from rosco.toolbox.tune import update_discon_version this_dir = os.path.dirname(os.path.abspath(__file__)) rosco_dir = os.path.dirname(this_dir) @@ -16,7 +16,7 @@ def main(): old_discon_filename = os.path.join(this_dir,'example_inputs','DISCON_v2.2.0.IN') # An IEA-15MW input # Tuning yaml can be anything, does not have to correspond to old discon - tuning_yaml = os.path.join(rosco_dir,'Tune_Cases','NREL5MW.yaml') # dummy for now + tuning_yaml = os.path.join(this_dir,'Tune_Cases','NREL5MW.yaml') # dummy for now update_discon_version( old_discon_filename, tuning_yaml, diff --git a/Examples/20_active_wake_control.py b/Examples/20_active_wake_control.py index c67555d8..aa936a9f 100644 --- a/Examples/20_active_wake_control.py +++ b/Examples/20_active_wake_control.py @@ -153,39 +153,34 @@ [2] - Frederik, Joeri A., et al. "The helix approach: Using dynamic individual pitch control to enhance wake mixing in wind farms." Wind Energy 23.8 (2020): 1739-1751. ''' -import os, platform -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl -from ROSCO_toolbox.ofTools.fast_io import output_processing -from ROSCO_toolbox.utilities import read_DISCON, DISCON_dict -import numpy as np +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +#from rosco.toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.utilities import read_DISCON #, DISCON_dict +#import numpy as np # Choose your implementation method AWC_Mode = 1 # 1 for SNL implementation, 2 for Coleman Transformation implementation + #directories this_dir = os.path.dirname(os.path.abspath(__file__)) rosco_dir = os.path.dirname(this_dir) example_out_dir = os.path.join(this_dir,'examples_out') os.makedirs(example_out_dir,exist_ok=True) -if platform.system() == 'Windows': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dll')) -elif platform.system() == 'Darwin': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib')) -else: - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.so')) def main(): # Input yaml and output directory - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/NREL2p8.yaml') # will be dummy and overwritten with SNL DISCON params + parameter_filename = os.path.join(this_dir,'Tune_Cases/NREL2p8.yaml') # will be dummy and overwritten with SNL DISCON params run_dir = os.path.join(example_out_dir,'20_active_wake_control/all_cases') os.makedirs(run_dir,exist_ok=True) # Read all DISCON inputs - rosco_vt = read_DISCON(os.path.join(rosco_dir,'Test_Cases','NREL_2p8_127/NREL-2p8-127_DISCON.IN')) + rosco_vt = read_DISCON(os.path.join(this_dir,'Test_Cases','NREL_2p8_127/NREL-2p8-127_DISCON.IN')) # Apply all discon variables as case inputs control_base_case = {} diff --git a/Examples/21_optional_inputs.py b/Examples/21_optional_inputs.py index 8a69b0ac..17b4f90b 100644 --- a/Examples/21_optional_inputs.py +++ b/Examples/21_optional_inputs.py @@ -4,30 +4,23 @@ to the current version ''' -import os, platform -from ROSCO_toolbox import control_interface as ROSCO_ci -from ROSCO_toolbox import sim as ROSCO_sim -from ROSCO_toolbox import turbine as ROSCO_turbine -import numpy as np - - +import os +from rosco import discon_lib_path +from rosco.toolbox import control_interface as ROSCO_ci +#from rosco.toolbox import sim as ROSCO_sim +from rosco.toolbox import turbine as ROSCO_turbine +#import numpy as np + +#directories this_dir = os.path.dirname(os.path.abspath(__file__)) rosco_dir = os.path.dirname(this_dir) - example_out_dir = os.path.join(this_dir,'examples_out') example_in_dir = os.path.join(this_dir,'example_inputs') +os.makedirs(example_out_dir,exist_ok=True) def main(): - # Set up rosco_dll - if platform.system() == 'Windows': - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.dll') - elif platform.system() == 'Darwin': - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.dylib') - else: - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.so') - # Load turbine model from saved pickle turbine = ROSCO_turbine.Turbine turbine = turbine.load(os.path.join(example_out_dir,'01_NREL5MW_saved.p')) @@ -40,7 +33,9 @@ def main(): avi_fail = [] for param_filename in param_filenames: - controller_int = ROSCO_ci.ControllerInterface(rosco_dll,param_filename=param_filename,sim_name='sim1') + controller_int = ROSCO_ci.ControllerInterface(discon_lib_path, + param_filename=param_filename, + sim_name='sim1') controller_int.kill_discon() avi_fail.append(controller_int.aviFAIL.value) @@ -48,4 +43,4 @@ def main(): assert avi_fail == [0,-1], "Unexpected pass/fail" if __name__ == "__main__": - main() \ No newline at end of file + main() diff --git a/Examples/22_cable_control.py b/Examples/22_cable_control.py index 467ed629..ce9a85b2 100644 --- a/Examples/22_cable_control.py +++ b/Examples/22_cable_control.py @@ -7,15 +7,15 @@ ''' -import os, platform -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl -from ROSCO_toolbox.ofTools.fast_io import output_processing +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.ofTools.fast_io import output_processing import numpy as np -from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +from rosco.toolbox.inputs.validation import load_rosco_yaml import matplotlib.pyplot as plt -from ROSCO_toolbox.controller import OpenLoopControl +from rosco.toolbox.controller import OpenLoopControl ''' ROSCO currently supports user-defined hooks for cable control actuation, if CC_Mode = 1. @@ -38,7 +38,7 @@ def main(): # Input yaml and output directory - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/IEA15MW_cable.yaml') + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW_cable.yaml') run_dir = os.path.join(example_out_dir,'22_cable_control') os.makedirs(run_dir,exist_ok=True) @@ -49,7 +49,7 @@ def main(): # Change inputs programatically, read first reader = InputReader_OpenFAST() reader.FAST_InputFile = path_params['FAST_InputFile'] - reader.FAST_directory = os.path.join(rosco_dir,'Tune_Cases',path_params['FAST_directory']) + reader.FAST_directory = os.path.join(this_dir,'Tune_Cases',path_params['FAST_directory']) reader.execute() # Set control line mapping (ChannelID -> Line(s)) @@ -120,7 +120,6 @@ def main(): r.controller_params = controller_params r.save_dir = run_dir r.rosco_dir = rosco_dir - r.run_FAST() @@ -150,4 +149,4 @@ def main(): if __name__=="__main__": - main() \ No newline at end of file + main() diff --git a/Examples/23_structural_control.py b/Examples/23_structural_control.py index 2a49b0f5..63022907 100644 --- a/Examples/23_structural_control.py +++ b/Examples/23_structural_control.py @@ -7,12 +7,14 @@ ''' -import os, platform -from ROSCO_toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl -import numpy as np -from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +#import numpy as np +from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.controller import OpenLoopControl + ''' ROSCO currently supports user-defined hooks for structural control control actuation, if StC_Mode = 1. @@ -20,10 +22,10 @@ In the DISCON input, users must specify StC_GroupIndex relating to the control ChannelID. These indices can be found in the ServoDyn summary file (*SrvD.sum) -In the example below (and hard-coded in ROSCO) a step change of -4e5 N on the first structural controller -is applied at 50 sec. +In the example below, we implement a smooth step change mimicing the exchange of ballast from the +upwind column to the down wind columns -The develop branch (as of Mar 3, 2023) of OpenFAST (v3.5.0, upcoming) is required to run this example +OpenFAST v3.5.0 is required to run this example ''' @@ -33,18 +35,11 @@ example_out_dir = os.path.join(this_dir,'examples_out') os.makedirs(example_out_dir,exist_ok=True) -if platform.system() == 'Windows': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dll')) -elif platform.system() == 'Darwin': - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib')) -else: - lib_name = os.path.realpath(os.path.join(this_dir, '../ROSCO/build/libdiscon.so')) - def main(): # Input yaml and output directory - parameter_filename = os.path.join(rosco_dir,'Tune_Cases/IEA15MW_ballast.yaml') + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW_ballast.yaml') run_dir = os.path.join(example_out_dir,'23_structural_control') os.makedirs(run_dir,exist_ok=True) @@ -55,7 +50,7 @@ def main(): # Change inputs programatically, read first reader = InputReader_OpenFAST() reader.FAST_InputFile = path_params['FAST_InputFile'] - reader.FAST_directory = os.path.join(rosco_dir,'Tune_Cases',path_params['FAST_directory']) + reader.FAST_directory = os.path.join(this_dir,'Tune_Cases',path_params['FAST_directory']) # reader.FAST_directory = '/Users/dzalkind/Tools/ROSCO1/Test_Cases/ptfm_control_archive/IEA-15-240-RWT-UMaineSemi_ballast' reader.execute() @@ -65,6 +60,41 @@ def main(): for StC_file in reader.fst_vt['ServoDyn']['SStCfiles']: reader.fst_vt['SStC'].append(reader.read_StC(StC_file)) + # Set up open loop inputs to ROSCO + t_trans = 60 + t_sigma = 80 + t_max = 200 + + applied_force = [-2e6, 1e6, 1e6] + + olc = OpenLoopControl(t_max=t_max) + olc.interp_timeseries( + 'struct_control_1', + [0,t_trans,t_trans+t_sigma], + [0,0,applied_force[0]] , + 'sigma' + ) + + olc.interp_timeseries( + 'struct_control_2', + [0,t_trans,t_trans+t_sigma], + [0,0,applied_force[1]] , + 'sigma' + ) + + olc.interp_timeseries( + 'struct_control_3', + [0,t_trans,t_trans+t_sigma], + [0,0,applied_force[2]] , + 'sigma' + ) + + + ol_params = olc.write_input(os.path.join(run_dir,'open_loop_ballast.dat')) + + controller_params = {} + controller_params['open_loop'] = ol_params + controller_params['StC_Mode'] = 2 # simulation set up r = run_FAST_ROSCO() @@ -73,16 +103,15 @@ def main(): r.wind_case_fcn = cl.power_curve r.wind_case_opts = { 'U': [9], - 'T_max': 100, + 'TMax': t_max, } r.case_inputs = {} - r.fst_vt = reader.fst_vt - r.save_dir = run_dir - r.rosco_dir = rosco_dir - + r.fst_vt = reader.fst_vt + r.save_dir = run_dir + r.rosco_dir = rosco_dir + r.controller_params = controller_params r.run_FAST() - if __name__=="__main__": - main() \ No newline at end of file + main() diff --git a/Examples/24_floating_feedback.py b/Examples/24_floating_feedback.py new file mode 100644 index 00000000..7da30c70 --- /dev/null +++ b/Examples/24_floating_feedback.py @@ -0,0 +1,157 @@ +''' +----------- 23_structural_control ------------------------ +Run openfast with ROSCO and all the floating feedback methods +----------------------------------------------- + +Floating feedback methods available in ROSCO/ROSCO_Toolbox + +1. Automated tuning, constant for all wind speeds +2. Automated tuning, varies with wind speed +3. Direct tuning, constant for all wind speeds +4. Direct tuning, varies with wind speeds + +''' + +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +import numpy as np +#from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +#from rosco.toolbox.inputs.validation import load_rosco_yaml +#from rosco.toolbox.controller import OpenLoopControl +from rosco.toolbox.tune import yaml_to_objs +from rosco.toolbox.utilities import write_DISCON, read_DISCON +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox.ofTools.fast_io import output_processing +import matplotlib.pyplot as plt + + + +#directories +this_dir = os.path.dirname(os.path.abspath(__file__)) +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) + +def main(): + + # Input yaml and output directory + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW.yaml') + run_dir = os.path.join(example_out_dir,'24_floating_feedback') + os.makedirs(run_dir,exist_ok=True) + + controller, turbine, path_params = yaml_to_objs(parameter_filename) + + # First, let's write the DISCONs for each method + param_files = [] + + # Method 1: Automated tuning, constant for all wind speeds + controller_params_1 = controller.controller_params # numbers correspond to methods above + param_file = os.path.join(run_dir,'DISCON_Fl_1.IN') + param_files.append(param_file) + write_DISCON(turbine,controller, + param_file=param_file, + txt_filename=path_params['rotor_performance_filename']) + + + # Method 2: Automated tuning, all wind speeds + controller_params_2 = controller_params_1.copy() + controller_params_2['U_Fl'] = 'all' + controller_params_2['tune_Fl'] = True + controller = ROSCO_controller.Controller(controller_params_2) + controller.tune_controller(turbine) + param_file = os.path.join(run_dir,'DISCON_Fl_2.IN') + param_files.append(param_file) + write_DISCON(turbine,controller, + param_file=param_file, + txt_filename=path_params['rotor_performance_filename']) + + # Method 3: Direct tuning, constant for all wind speeds + controller_params_3 = controller_params_1.copy() + Kp_float = -18 + controller_params_3['Kp_float'] = Kp_float + controller_params_3['tune_Fl'] = False + controller = ROSCO_controller.Controller(controller_params_3) + controller.tune_controller(turbine) + np.testing.assert_almost_equal(Kp_float,controller.Kp_float) # Check that it's passed through correctly + param_file = os.path.join(run_dir,'DISCON_Fl_3.IN') + param_files.append(param_file) + write_DISCON(turbine,controller, + param_file=param_file, + txt_filename=path_params['rotor_performance_filename']) + + # Method 4: Direct tuning, varies with wind speeds + controller_params_4 = controller_params_1.copy() + controller_params_4['U_Fl'] = [12,16,25] + controller_params_4['Kp_float'] = [-12,-6,-3] + controller_params_4['tune_Fl'] = False + controller = ROSCO_controller.Controller(controller_params_4) + controller.tune_controller(turbine) + param_file = os.path.join(run_dir,'DISCON_Fl_4.IN') + param_files.append(param_file) + write_DISCON(turbine,controller, + param_file=os.path.join(run_dir,'DISCON_Fl_4.IN'), + txt_filename=path_params['rotor_performance_filename']) + + # Read all DISCONs and make into case_inputs + case_inputs = {} + discon_lists = {} + for discon in param_files: + discon_vt = read_DISCON(discon) + for discon_input in discon_vt: + if discon_input not in discon_lists: # initialize + discon_lists[discon_input] = [] + discon_lists[discon_input].append(discon_vt[discon_input]) + + for discon_input, input in discon_lists.items(): + case_inputs[('DISCON_in',discon_input)] = {'vals': input, 'group': 2} + + + # simulation set up + r = run_FAST_ROSCO() + r.tuning_yaml = parameter_filename + r.wind_case_fcn = cl.simp_step # single step wind input + r.wind_case_opts = { + 'U_start': [13], + 'U_end': [16], + 'TMax': 100, + 'TStep': 50, + } + r.case_inputs = case_inputs + r.save_dir = run_dir + r.rosco_dir = rosco_dir + r.n_cores = 4 + r.run_FAST() + + op = output_processing.output_processing() + op_dbg = output_processing.output_processing() + op_dbg2 = output_processing.output_processing() + + out_files = [os.path.join(run_dir,f'IEA15MW/simp_step/base/IEA15MW_{i_case}.outb') for i_case in range(4)] + dbg_files = [os.path.join(run_dir,f'IEA15MW/simp_step/base/IEA15MW_{i_case}.RO.dbg') for i_case in range(4)] + dbg2_files = [os.path.join(run_dir,f'IEA15MW/simp_step/base/IEA15MW_{i_case}.RO.dbg2') for i_case in range(4)] + + fst_out = op.load_fast_out(out_files, tmin=0) + debug_vars = op_dbg.load_fast_out(dbg_files, tmin=0) + local_vars = op_dbg2.load_fast_out(dbg2_files, tmin=0) + + comb_out = [None] * len(fst_out) + for i, (r_out, f_out) in enumerate(zip(debug_vars,fst_out)): + r_out.update(f_out) + comb_out[i] = r_out + for i, (r_out2, f_out) in enumerate(zip(local_vars,comb_out)): + r_out2.update(f_out) + comb_out[i] = r_out2 + + cases = {} + cases['Fl Sigs.'] = ['Wind1VelX','Kp_Float', 'Fl_PitCom', 'BldPitch1','PtfmPitch']#,'PtfmPitch','PtfmYaw','NacYaw'] + fig, ax = op.plot_fast_out(comb_out,cases, showplot=True) + + if False: + plt.show() + else: + plt.savefig(os.path.join(run_dir,'24_floating_feedback.png')) + + +if __name__=="__main__": + main() diff --git a/Examples/25_rotor_position_control.py b/Examples/25_rotor_position_control.py new file mode 100644 index 00000000..fe1abef8 --- /dev/null +++ b/Examples/25_rotor_position_control.py @@ -0,0 +1,115 @@ +''' +----------- 25_rotor_position_control -------------- +Run ROSCO with rotor position control +------------------------------------- + +Run a steady simulation, use the azimuth output as an input to the next steady simulation, with different ICs + +''' + +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.controller import OpenLoopControl +import numpy as np +#import pandas as pd +import matplotlib.pyplot as plt + + +#directories +this_dir = os.path.dirname(os.path.abspath(__file__)) +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) + + +def main(): + + + # Set up paths + parameter_filename = os.path.join(this_dir,'Tune_Cases/NREL2p8.yaml') + run_dir = os.path.join(example_out_dir,'25_rotor_position_control') + os.makedirs(run_dir,exist_ok=True) + + # Steady simualtion with initial RotSpeed of 5 rpm + r = run_FAST_ROSCO() + r.wind_case_fcn = cl.power_curve + r.tuning_yaml = parameter_filename + r.wind_case_opts = { + 'U': [14], + 'TMax': 100, + } + r.save_dir = run_dir + r.run_FAST() + + # Gather azimuth, blade pitch, generator torque output, apply as open loop inputs to ROSCO + op = output_processing.output_processing() + fast_out = op.load_fast_out(os.path.join(run_dir,'NREL2p8/power_curve/base/NREL2p8_0.outb'), tmin=0) + + olc = OpenLoopControl() + olc.ol_timeseries['time'] = fast_out[0]['Time'] + olc.ol_timeseries['blade_pitch1'] = np.radians(fast_out[0]['BldPitch1']) + olc.ol_timeseries['blade_pitch2'] = np.radians(fast_out[0]['BldPitch2']) + olc.ol_timeseries['blade_pitch3'] = np.radians(fast_out[0]['BldPitch3']) + olc.ol_timeseries['generator_torque'] = fast_out[0]['GenTq'] * 1000 + olc.ol_timeseries['azimuth'] = np.radians(fast_out[0]['Azimuth']) + + # Save initial RotSpeed, Azimuth for later + RotSpeed_0 = fast_out[0]['RotSpeed'][0] + Azimuth_0 = fast_out[0]['Azimuth'][0] + + # set up control_params for next run + open_loop = olc.write_input(os.path.join(run_dir,'ol_input.dat')) + controller_params = {} + controller_params['open_loop'] = open_loop + controller_params['OL_Mode'] = 2 # Azimuth tracking open loop + controller_params['PA_Mode'] = 0 # No pitch actuator + controller_params['DISCON'] = {} + + gains = -1800 * np.array([12,1.2,120]) # PID gains of rotor position control + controller_params['DISCON']['RP_Gains'] = np.r_[gains, 2] # Add Tf + controller_params['DISCON']['PC_MinPit'] = np.radians(-20) # Remove lower limit of pitch so it doesn't interfere with open loop input + + + # run again with different IC and rotor position control + r.base_name = 'rpc' + r.tuning_yaml = parameter_filename + # Set initial conditions + r.case_inputs = {} + r.case_inputs[("ElastoDyn","RotSpeed")] = {'vals':[RotSpeed_0 + 1], 'group':0} + r.case_inputs[("ElastoDyn","Azimuth")] = {'vals':[Azimuth_0 + 30], 'group':0} + r.case_inputs[("ServoDyn","Ptch_Cntrl")] = {'vals':[1], 'group':0} + + r.controller_params = controller_params + r.run_FAST() + + # Plot relevant outputs + op = output_processing.output_processing() + op_dbg2 = output_processing.output_processing() + + out_files = [os.path.join(run_dir,f'NREL2p8/power_curve/base/NREL2p8_0.out'), + os.path.join(run_dir,f'rpc/power_curve/base/rpc_0.out')] + dbg2_files = [out.split('.out')[0] + '.RO.dbg2' for out in out_files] + + fst_out = op.load_fast_out(out_files, tmin=0) + local_vars = op_dbg2.load_fast_out(dbg2_files, tmin=0) + + comb_out = [None] * len(fst_out) + for i, (r_out2, f_out) in enumerate(zip(local_vars,fst_out)): + r_out2.update(f_out) + comb_out[i] = r_out2 + + cases = {} + cases['Fl Sigs.'] = ['BldPitch1','GenTq','GenSpeed', 'Azimuth', 'AzError','GenTqAz'] + fig, ax = op.plot_fast_out(comb_out,cases, showplot=True) + + if False: + plt.show() + else: + plt.savefig(os.path.join(run_dir,'25_rotor_position_control.png')) + + + +if __name__=="__main__": + main() diff --git a/Examples/26_marine_hydro.py b/Examples/26_marine_hydro.py new file mode 100644 index 00000000..6773482b --- /dev/null +++ b/Examples/26_marine_hydro.py @@ -0,0 +1,85 @@ +''' +----------- 26_marine_hydro ------------------------ +Run openfast with ROSCO and a MHK turbine +----------------------------------------------- + + +''' + +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +#from rosco.toolbox.ofTools.fast_io import output_processing +#from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +#from rosco.toolbox.inputs.validation import load_rosco_yaml +#import matplotlib.pyplot as plt +#from rosco.toolbox.controller import OpenLoopControl + +''' +Run MHK turbine in OpenFAST with ROSCO torque controller + + +''' + + +#directories +this_dir = os.path.dirname(os.path.abspath(__file__)) +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) + +def main(): + + # Input yaml and output directory + parameter_filename = os.path.join(this_dir,'Tune_Cases/RM1_MHK.yaml') + run_dir = os.path.join(example_out_dir,'26_MHK/0_baseline') + os.makedirs(run_dir,exist_ok=True) + + + # simulation set up + r = run_FAST_ROSCO() + r.tuning_yaml = parameter_filename + # r.wind_case_fcn = cl.simp_step # single step wind input + r.wind_case_fcn = cl.power_curve + r.wind_case_opts = { + 'U': [2.5], + 'TMax': 100.0, + } + r.case_inputs = {} + # r.fst_vt = reader.fst_vt + # r.controller_params = controller_params + r.save_dir = run_dir + r.rosco_dir = rosco_dir + + r.run_FAST() + + print('here') + + + # op = output_processing.output_processing() + # op2 = output_processing.output_processing() + + # md_out = op.load_fast_out([os.path.join(run_dir,'IEA15MW_cable/power_curve/base/IEA15MW_cable_0.MD.Line1.out')], tmin=0) + # local_vars = op2.load_fast_out([os.path.join(run_dir,'IEA15MW_cable/power_curve/base/IEA15MW_cable_0.RO.dbg2')], tmin=0) + + # fig, axs = plt.subplots(4,1) + # axs[0].plot(local_vars[0]['Time'],local_vars[0]['CC_DesiredL'],label='CC_DesiredL') + # axs[1].plot(local_vars[0]['Time'],local_vars[0]['CC_ActuatedL'],label='CC_ActuatedL') + # axs[2].plot(local_vars[0]['Time'],local_vars[0]['CC_ActuatedDL'],label='CC_ActuatedDL') + # axs[3].plot(md_out[0]['Time'],md_out[0]['Seg20Lst'],label='Seg20Lst') + + # [a.legend() for a in axs] + # [a.grid() for a in axs] + + # if False: + # plt.show() + # else: + # plt.savefig(os.path.join(example_out_dir,'22_cable_control.png')) + + # Check that the last segment of line 1 shrinks by 10 m + # np.testing.assert_almost_equal(md_out[0]['Seg20Lst'][-1] - md_out[0]['Seg20Lst'][0], line_ends[0], 2) + + + +if __name__=="__main__": + main() diff --git a/Examples/27_power_ref_control.py b/Examples/27_power_ref_control.py new file mode 100644 index 00000000..ebeba3b6 --- /dev/null +++ b/Examples/27_power_ref_control.py @@ -0,0 +1,103 @@ +''' +----------- 27_power_ref_control ------------------------ +Run openfast with ROSCO and cable control +----------------------------------------------- + +Demonstrate a simulation with a generator reference speed that changes with estimated wind speed + + +''' + +import os +from rosco import discon_lib_path +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +from rosco.toolbox.tune import yaml_to_objs +import numpy as np +#from rosco.toolbox.inputs.validation import load_rosco_yaml +import matplotlib.pyplot as plt + +''' +Set reference rotor speed as a function of wind speed (estimate in ROSCO) + +''' + +FULL_TEST = False + + +#directories +this_dir = os.path.dirname(os.path.abspath(__file__)) +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) +lib_name = discon_lib_path + + +def main(): + + # Input yaml and output directory + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW.yaml') + run_dir = os.path.join(example_out_dir,'27_PRC_0') + os.makedirs(run_dir,exist_ok=True) + + + # Create rotor speed table + controller, _, _ = yaml_to_objs(parameter_filename) + + + # plot original ops + plt.plot(controller.v,controller.omega_op) + + + omega = controller.omega_op + v = controller.v + + # Hold near rated rotor speed, for testing setpoint smoother + near_rated = np.bitwise_and(v > 9, v < 13) + first_near_rated_ind = np.where(near_rated)[0][0] + omega[near_rated] = omega[first_near_rated_ind] + + # add high wind ride-through + v_hwrt = [50] # m/s + omega_hwrt = [0.3] # rad/s + v = np.r_[v,v_hwrt] + omega = np.r_[omega,omega_hwrt] + + # plot new lookup + plt.plot(v,omega,linestyle='--') + + r = run_FAST_ROSCO() + r.tuning_yaml = parameter_filename + r.wind_case_fcn = cl.ramp # single step wind input + + if FULL_TEST: + # Full test + r.wind_case_opts = { + 'U_start': 5, # from 10 to 15 m/s + 'U_end': 35, + 't_start': 100, + 't_end': 2500, + } + else: + # Short test for CI + r.wind_case_opts = { + 'U_start': 25, # from 10 to 15 m/s + 'U_end': 27, + 't_start': 50, + 't_end': 100, + } + r.save_dir = run_dir + r.rosco_dir = rosco_dir + r.controller_params = { + 'PRC_Mode': 1, + 'DISCON': { + 'PRC_Mode': 1, + 'PRC_n': len(v), + 'PRC_WindSpeeds': v, + 'PRC_GenSpeeds': omega, + + }} # Use OutData in control + r.run_FAST() + +if __name__=="__main__": + main() diff --git a/Examples/28_tower_resonance.py b/Examples/28_tower_resonance.py new file mode 100644 index 00000000..912e4081 --- /dev/null +++ b/Examples/28_tower_resonance.py @@ -0,0 +1,110 @@ +''' +----------- 28_tower_resonance ------------------------ +Demonstrate tower resonance avoidance controller +----------------------------------------------- + +Set up and run simulation with tower resonance avoidance + +''' + +import os +from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +#from rosco.toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +from rosco.toolbox.inputs.validation import load_rosco_yaml + +import numpy as np + +rpm2RadSec = 2.0*(np.pi)/60.0 + + +#directories +this_dir = os.path.dirname(os.path.abspath(__file__)) +rosco_dir = os.path.dirname(this_dir) +example_out_dir = os.path.join(this_dir,'examples_out') +os.makedirs(example_out_dir,exist_ok=True) + + +def main(): + + # Input yaml and output directory + parameter_filename = os.path.join(this_dir,'Tune_Cases/IEA15MW.yaml') + run_dir = os.path.join(example_out_dir,'28_TRA_Ramp_0') + os.makedirs(run_dir,exist_ok=True) + + # Change tower programatically, read first + # Read initial input file + inps = load_rosco_yaml(parameter_filename) + path_params = inps['path_params'] + + reader = InputReader_OpenFAST() + reader.FAST_InputFile = path_params['FAST_InputFile'] + reader.FAST_directory = os.path.join(this_dir,'Tune_Cases',path_params['FAST_directory']) + # reader.FAST_directory = '/Users/dzalkind/Tools/ROSCO1/Test_Cases/ptfm_control_archive/IEA-15-240-RWT-UMaineSemi_ballast' + reader.execute() + + # Reduce stiffness to 1/4 original + ed_twr = reader.fst_vt['ElastoDynTower'] + ed_twr['FAStTunr1'] = ed_twr['FAStTunr2'] = ed_twr['SSStTunr1'] = ed_twr['SSStTunr2'] = 0.25 + + # Set DISCON input dynamically through yaml/dict + controller_params = {} + controller_params['TRA_Mode'] = 2 + controller_params['vs_minspd'] = 0. # Reduce minimum rotor speed so that saturation does not interfere with exclusion + controller_params['VS_ControlMode'] = 3. + + # TRA parameters + controller_params['DISCON'] = {} + controller_params['DISCON']['TRA_ExclSpeed'] = 4.75 * rpm2RadSec + controller_params['DISCON']['TRA_ExclBand'] = 1 * rpm2RadSec + controller_params['DISCON']['TRA_RateLimit'] = 0.7916800 / 100 + + # simulation set up + r = run_FAST_ROSCO() + r.tuning_yaml = parameter_filename + + # Wind case + # A few different cases highlight TRA + + # Ramp: good demo of functionality, short for CI + r.wind_case_fcn = cl.ramp + r.wind_case_opts = { + 'U_start': 4, # from 10 to 15 m/s + 'U_end': 10, + 't_start': 100, + 't_end': 300 + } + + # # steady + # r.wind_case_fcn = cl.power_curve + # r.wind_case_opts = { + # 'U': 6.5, # from 10 to 15 m/s + # 'TMax': 400, + # } + + # # turbulence + # r.wind_case_fcn = cl.turb_bts + # r.wind_case_opts = { + # 'TMax': 400, # from 10 to 15 m/s + # 'wind_filenames': ['/Users/dzalkind/Downloads/heavy_test_1ETM_U6.000000_Seed603.0.bts'], + # } + + # Do a run with both tower modes + r.control_sweep_fcn = cl.sweep_yaml_input + r.control_sweep_opts = { + 'control_param': 'TRA_Mode', + 'param_values': [0,1] + } + + r.controller_params = controller_params + r.save_dir = run_dir + r.rosco_dir = rosco_dir + r.case_inputs = {} + r.n_cores = 2 + r.run_FAST() + + + +if __name__=="__main__": + main() diff --git a/Examples/ROSCO_walkthrough.ipynb b/Examples/ROSCO_walkthrough.ipynb index d3f912b7..6988320a 100644 --- a/Examples/ROSCO_walkthrough.ipynb +++ b/Examples/ROSCO_walkthrough.ipynb @@ -34,7 +34,7 @@ "output_type": "stream", "text": [ "WARNING: Be sure to pip install simpy and marmot-agents for offshore BOS runs\n", - "Using ofTools in ROSCO_toolbox...\n" + "Using ofTools in rosco.toolbox...\n" ] } ], @@ -47,15 +47,16 @@ "import numpy as np\n", "\n", "# ROSCO Modules\n", - "from ROSCO_toolbox import turbine as ROSCO_turbine\n", - "from ROSCO_toolbox import utilities as ROSCO_utilities\n", - "from ROSCO_toolbox import sim as ROSCO_sim\n", - "from ROSCO_toolbox import utilities as ROSCO_utilities\n", - "from ROSCO_toolbox import controller as ROSCO_controller\n", - "from ROSCO_toolbox import control_interface as ROSCO_ci\n", - "from ROSCO_toolbox.ofTools.fast_io.output_processing import output_processing\n", + "from rosco import discon_lib_path as lib_name\n", + "from rosco.toolbox import turbine as ROSCO_turbine\n", + "from rosco.toolbox import utilities as ROSCO_utilities\n", + "from rosco.toolbox import sim as ROSCO_sim\n", + "from rosco.toolbox import utilities as ROSCO_utilities\n", + "from rosco.toolbox import controller as ROSCO_controller\n", + "from rosco.toolbox import control_interface as ROSCO_ci\n", + "from rosco.toolbox.ofTools.fast_io.output_processing import output_processing\n", "\n", - "from ROSCO_toolbox.inputs.validation import load_rosco_yaml\n", + "from rosco.toolbox.inputs.validation import load_rosco_yaml\n", "\n" ] }, @@ -92,7 +93,7 @@ "outputs": [], "source": [ "# Load yaml file \n", - "parameter_filename = '../Tune_Cases/NREL5MW.yaml'\n", + "parameter_filename = 'Tune_Cases/NREL5MW.yaml'\n", "inps = load_rosco_yaml(parameter_filename)\n", "path_params = inps['path_params']\n", "turbine_params = inps['turbine_params']\n", @@ -119,6 +120,7 @@ " 'max_torque_rate': 1500000.0,\n", " 'rated_power': 5000000.0,\n", " 'rated_rotor_speed': 1.26711,\n", + " 'reynolds_ref': 0,\n", " 'rotor_inertia': 38677040.613,\n", " 'v_max': 25.0,\n", " 'v_min': 3.0,\n", @@ -164,7 +166,7 @@ }, { "cell_type": "code", - "execution_count": 4, + "execution_count": 6, "metadata": { "slideshow": { "slide_type": "subslide" @@ -179,8 +181,8 @@ "Loading wind turbine data for NREL's ROSCO tuning and simulation processeses\n", "-----------------------------------------------------------------------------\n", "Loading FAST model: NREL-5MW.fst \n", - "Loading rotor performace data from text file: /Users/dzalkind/Tools/ROSCO3/Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt\n", - "Loading rotor performace data from text file: ../Tune_Cases/../Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt\n" + "Loading rotor performace data from text file: /Users/dzalkind/Tools/ROSCO1/Examples/Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt\n", + "Loading rotor performace data from text file: Tune_Cases/../Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt\n" ] } ], @@ -189,8 +191,8 @@ "turbine = ROSCO_turbine.Turbine(turbine_params)\n", "turbine.load_from_fast(\n", " path_params['FAST_InputFile'],\n", - " os.path.join('../Tune_Cases/',path_params['FAST_directory']),\n", - " rot_source='txt',txt_filename=os.path.join('../Tune_Cases/',path_params['FAST_directory'],path_params['rotor_performance_filename'])\n", + " os.path.join('Tune_Cases/',path_params['FAST_directory']),\n", + " rot_source='txt',txt_filename=os.path.join('Tune_Cases',path_params['rotor_performance_filename'])\n", " )\n" ] }, @@ -207,7 +209,7 @@ }, { "cell_type": "code", - "execution_count": 5, + "execution_count": 7, "metadata": { "slideshow": { "slide_type": "subslide" @@ -231,7 +233,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -261,7 +263,7 @@ }, { "cell_type": "code", - "execution_count": 6, + "execution_count": 8, "metadata": { "slideshow": { "slide_type": "subslide" @@ -299,7 +301,7 @@ }, { "cell_type": "code", - "execution_count": 7, + "execution_count": 9, "metadata": { "slideshow": { "slide_type": "subslide" @@ -308,7 +310,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -334,7 +336,7 @@ }, { "cell_type": "code", - "execution_count": 8, + "execution_count": 10, "metadata": { "slideshow": { "slide_type": "slide" @@ -355,7 +357,7 @@ "ROSCO_utilities.write_DISCON(\n", " turbine,controller,\n", " param_file=param_file, \n", - " txt_filename=os.path.join('../Tune_Cases/',path_params['FAST_directory'],path_params['rotor_performance_filename'])\n", + " txt_filename=os.path.join('Tune_Cases/',path_params['rotor_performance_filename'])\n", ")" ] }, @@ -376,7 +378,7 @@ }, { "cell_type": "code", - "execution_count": 9, + "execution_count": 11, "metadata": { "slideshow": { "slide_type": "subslide" @@ -394,7 +396,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -434,7 +436,7 @@ }, { "cell_type": "code", - "execution_count": 10, + "execution_count": 13, "metadata": { "slideshow": { "slide_type": "subslide" @@ -447,74 +449,77 @@ "text": [ " \n", "------------------------------------------------------------------------------\n", - "Running ROSCO-v2.6.0\n", + "Running ROSCO-v2.8.0\n", "A wind turbine controller framework for public use in the scientific field \n", "Developed in collaboration: National Renewable Energy Laboratory \n", " Delft University of Technology, The Netherlands \n", "------------------------------------------------------------------------------\n", + " ROSCO Warning: Did not find correct size F_NotchFreqs in input file. Using default value of [ 0.0000000000000000 ]\n", + " ROSCO Warning: Did not find correct size F_NotchBetaNum in input file. Using default value of [ 0.0000000000000000 ]\n", + " ROSCO Warning: Did not find correct size F_NotchBetaDen in input file. Using default value of [ 0.0000000000000000 ]\n", "Generator speed: 9.5 RPM, Pitch angle: 0.0 deg, Power: 0.0 kW, Est. wind Speed: 10.0 m/s\n", - "Generator speed: 673.4 RPM, Pitch angle: 0.1 deg, Power: 340.8 kW, Est. wind Speed: 4.6 m/s\n", - "Generator speed: 751.3 RPM, Pitch angle: 0.1 deg, Power: 853.4 kW, Est. wind Speed: 7.1 m/s\n", - "Generator speed: 800.7 RPM, Pitch angle: 0.1 deg, Power: 1072.2 kW, Est. wind Speed: 6.8 m/s\n", - "Generator speed: 781.4 RPM, Pitch angle: 0.1 deg, Power: 1190.5 kW, Est. wind Speed: 6.8 m/s\n", - "Generator speed: 765.6 RPM, Pitch angle: 0.1 deg, Power: 1094.1 kW, Est. wind Speed: 6.9 m/s\n", - "Generator speed: 767.7 RPM, Pitch angle: 0.1 deg, Power: 1073.3 kW, Est. wind Speed: 6.9 m/s\n", - "Generator speed: 770.1 RPM, Pitch angle: 0.1 deg, Power: 1084.5 kW, Est. wind Speed: 6.9 m/s\n", - "Generator speed: 770.2 RPM, Pitch angle: 0.1 deg, Power: 1088.2 kW, Est. wind Speed: 6.9 m/s\n", - "Generator speed: 770.1 RPM, Pitch angle: 0.1 deg, Power: 1087.4 kW, Est. wind Speed: 6.9 m/s\n", - "Generator speed: 770.2 RPM, Pitch angle: 0.1 deg, Power: 1088.7 kW, Est. wind Speed: 6.9 m/s\n", - "Generator speed: 838.4 RPM, Pitch angle: 0.1 deg, Power: 1408.9 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 882.6 RPM, Pitch angle: 0.1 deg, Power: 1542.6 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 882.8 RPM, Pitch angle: 0.1 deg, Power: 1674.7 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 873.5 RPM, Pitch angle: 0.1 deg, Power: 1638.1 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 872.7 RPM, Pitch angle: 0.1 deg, Power: 1616.3 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 874.2 RPM, Pitch angle: 0.1 deg, Power: 1617.5 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 875.0 RPM, Pitch angle: 0.1 deg, Power: 1620.4 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 875.4 RPM, Pitch angle: 0.1 deg, Power: 1621.0 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 875.8 RPM, Pitch angle: 0.1 deg, Power: 1620.9 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 876.3 RPM, Pitch angle: 0.1 deg, Power: 1623.7 kW, Est. wind Speed: 7.8 m/s\n", - "Generator speed: 953.2 RPM, Pitch angle: 0.1 deg, Power: 2054.2 kW, Est. wind Speed: 8.8 m/s\n", - "Generator speed: 992.5 RPM, Pitch angle: 0.1 deg, Power: 2266.6 kW, Est. wind Speed: 8.7 m/s\n", - "Generator speed: 987.9 RPM, Pitch angle: 0.1 deg, Power: 2362.9 kW, Est. wind Speed: 8.7 m/s\n", - "Generator speed: 980.6 RPM, Pitch angle: 0.1 deg, Power: 2320.8 kW, Est. wind Speed: 8.7 m/s\n", - "Generator speed: 980.3 RPM, Pitch angle: 0.1 deg, Power: 2302.8 kW, Est. wind Speed: 8.7 m/s\n", - "Generator speed: 981.8 RPM, Pitch angle: 0.1 deg, Power: 2304.0 kW, Est. wind Speed: 8.7 m/s\n", - "Generator speed: 982.7 RPM, Pitch angle: 0.1 deg, Power: 2306.8 kW, Est. wind Speed: 8.8 m/s\n", - "Generator speed: 983.3 RPM, Pitch angle: 0.1 deg, Power: 2307.5 kW, Est. wind Speed: 8.8 m/s\n", - "Generator speed: 983.8 RPM, Pitch angle: 0.1 deg, Power: 2307.5 kW, Est. wind Speed: 8.8 m/s\n", - "Generator speed: 984.4 RPM, Pitch angle: 0.1 deg, Power: 2311.6 kW, Est. wind Speed: 8.8 m/s\n", - "Generator speed: 1069.7 RPM, Pitch angle: 0.1 deg, Power: 2876.5 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1102.9 RPM, Pitch angle: 0.1 deg, Power: 3163.7 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1095.1 RPM, Pitch angle: 0.1 deg, Power: 3221.5 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1088.9 RPM, Pitch angle: 0.1 deg, Power: 3176.5 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1089.1 RPM, Pitch angle: 0.1 deg, Power: 3160.3 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1090.5 RPM, Pitch angle: 0.1 deg, Power: 3162.0 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1091.5 RPM, Pitch angle: 0.1 deg, Power: 3164.7 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1092.1 RPM, Pitch angle: 0.1 deg, Power: 3165.4 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1092.7 RPM, Pitch angle: 0.1 deg, Power: 3165.5 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1093.4 RPM, Pitch angle: 0.1 deg, Power: 3171.1 kW, Est. wind Speed: 9.7 m/s\n", - "Generator speed: 1183.2 RPM, Pitch angle: 2.4 deg, Power: 4016.0 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1175.0 RPM, Pitch angle: 1.6 deg, Power: 4018.1 kW, Est. wind Speed: 10.6 m/s\n", - "Generator speed: 1172.9 RPM, Pitch angle: 1.5 deg, Power: 4066.9 kW, Est. wind Speed: 10.6 m/s\n", - "Generator speed: 1173.1 RPM, Pitch angle: 1.5 deg, Power: 4089.5 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1173.6 RPM, Pitch angle: 1.5 deg, Power: 4104.5 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 1.6 deg, Power: 4097.0 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 1.6 deg, Power: 4096.7 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1173.6 RPM, Pitch angle: 1.6 deg, Power: 4095.1 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1173.6 RPM, Pitch angle: 1.6 deg, Power: 4093.6 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 1.6 deg, Power: 4099.1 kW, Est. wind Speed: 10.7 m/s\n", - "Generator speed: 1174.1 RPM, Pitch angle: 2.6 deg, Power: 4772.0 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1174.7 RPM, Pitch angle: 3.1 deg, Power: 4862.6 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1174.0 RPM, Pitch angle: 3.1 deg, Power: 4886.5 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 3.0 deg, Power: 4885.5 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 3.0 deg, Power: 4882.0 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.5 RPM, Pitch angle: 3.0 deg, Power: 4879.1 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.5 RPM, Pitch angle: 3.0 deg, Power: 4875.4 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.5 RPM, Pitch angle: 3.1 deg, Power: 4872.5 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.5 RPM, Pitch angle: 3.1 deg, Power: 4870.1 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 3.1 deg, Power: 4876.1 kW, Est. wind Speed: 11.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5001.4 kW, Est. wind Speed: 12.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.0 kW, Est. wind Speed: 12.6 m/s\n", + "Generator speed: 563.0 RPM, Pitch angle: 0.1 deg, Power: 446.6 kW, Est. wind Speed: 4.3 m/s\n", + "Generator speed: 698.8 RPM, Pitch angle: 0.1 deg, Power: 800.8 kW, Est. wind Speed: 7.0 m/s\n", + "Generator speed: 752.0 RPM, Pitch angle: 0.1 deg, Power: 987.8 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 768.6 RPM, Pitch angle: 0.1 deg, Power: 1061.2 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 772.3 RPM, Pitch angle: 0.1 deg, Power: 1083.9 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 772.4 RPM, Pitch angle: 0.1 deg, Power: 1088.9 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 772.0 RPM, Pitch angle: 0.1 deg, Power: 1089.0 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 771.6 RPM, Pitch angle: 0.1 deg, Power: 1088.3 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 771.4 RPM, Pitch angle: 0.1 deg, Power: 1087.8 kW, Est. wind Speed: 6.8 m/s\n", + "Generator speed: 771.5 RPM, Pitch angle: 0.1 deg, Power: 1089.4 kW, Est. wind Speed: 6.9 m/s\n", + "Generator speed: 848.5 RPM, Pitch angle: 0.1 deg, Power: 1442.1 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 875.6 RPM, Pitch angle: 0.1 deg, Power: 1571.4 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 882.3 RPM, Pitch angle: 0.1 deg, Power: 1614.7 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 882.9 RPM, Pitch angle: 0.1 deg, Power: 1624.9 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 882.4 RPM, Pitch angle: 0.1 deg, Power: 1625.6 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 881.9 RPM, Pitch angle: 0.1 deg, Power: 1624.5 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 881.6 RPM, Pitch angle: 0.1 deg, Power: 1623.7 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 881.5 RPM, Pitch angle: 0.1 deg, Power: 1623.3 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 881.5 RPM, Pitch angle: 0.1 deg, Power: 1623.1 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 881.6 RPM, Pitch angle: 0.1 deg, Power: 1625.9 kW, Est. wind Speed: 7.8 m/s\n", + "Generator speed: 965.3 RPM, Pitch angle: 0.1 deg, Power: 2107.8 kW, Est. wind Speed: 8.8 m/s\n", + "Generator speed: 990.5 RPM, Pitch angle: 0.1 deg, Power: 2266.5 kW, Est. wind Speed: 8.7 m/s\n", + "Generator speed: 994.7 RPM, Pitch angle: 0.1 deg, Power: 2310.9 kW, Est. wind Speed: 8.7 m/s\n", + "Generator speed: 993.9 RPM, Pitch angle: 0.1 deg, Power: 2317.3 kW, Est. wind Speed: 8.7 m/s\n", + "Generator speed: 992.7 RPM, Pitch angle: 0.1 deg, Power: 2315.2 kW, Est. wind Speed: 8.7 m/s\n", + "Generator speed: 992.1 RPM, Pitch angle: 0.1 deg, Power: 2312.9 kW, Est. wind Speed: 8.7 m/s\n", + "Generator speed: 991.8 RPM, Pitch angle: 0.1 deg, Power: 2311.6 kW, Est. wind Speed: 8.8 m/s\n", + "Generator speed: 991.7 RPM, Pitch angle: 0.1 deg, Power: 2311.1 kW, Est. wind Speed: 8.8 m/s\n", + "Generator speed: 991.7 RPM, Pitch angle: 0.1 deg, Power: 2311.0 kW, Est. wind Speed: 8.8 m/s\n", + "Generator speed: 991.8 RPM, Pitch angle: 0.1 deg, Power: 2314.9 kW, Est. wind Speed: 8.8 m/s\n", + "Generator speed: 1081.7 RPM, Pitch angle: 0.1 deg, Power: 2947.8 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1104.7 RPM, Pitch angle: 0.1 deg, Power: 3135.8 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1106.5 RPM, Pitch angle: 0.1 deg, Power: 3179.3 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1104.5 RPM, Pitch angle: 0.1 deg, Power: 3180.8 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1102.9 RPM, Pitch angle: 0.1 deg, Power: 3175.7 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1102.2 RPM, Pitch angle: 0.1 deg, Power: 3172.2 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1101.9 RPM, Pitch angle: 0.1 deg, Power: 3170.6 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1101.9 RPM, Pitch angle: 0.1 deg, Power: 3170.1 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1101.9 RPM, Pitch angle: 0.1 deg, Power: 3170.0 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1102.0 RPM, Pitch angle: 0.1 deg, Power: 3175.4 kW, Est. wind Speed: 9.7 m/s\n", + "Generator speed: 1181.3 RPM, Pitch angle: 3.0 deg, Power: 4314.8 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1176.8 RPM, Pitch angle: 2.0 deg, Power: 4097.9 kW, Est. wind Speed: 10.6 m/s\n", + "Generator speed: 1173.5 RPM, Pitch angle: 1.5 deg, Power: 4069.2 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.1 RPM, Pitch angle: 1.5 deg, Power: 4087.6 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.5 RPM, Pitch angle: 1.5 deg, Power: 4101.7 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 1.6 deg, Power: 4096.4 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 1.6 deg, Power: 4096.0 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.6 RPM, Pitch angle: 1.6 deg, Power: 4094.2 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.6 RPM, Pitch angle: 1.6 deg, Power: 4092.7 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 1.6 deg, Power: 4098.1 kW, Est. wind Speed: 10.7 m/s\n", + "Generator speed: 1173.4 RPM, Pitch angle: 2.6 deg, Power: 4766.7 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1174.2 RPM, Pitch angle: 3.0 deg, Power: 4852.4 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1174.0 RPM, Pitch angle: 3.0 deg, Power: 4879.3 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.8 RPM, Pitch angle: 3.0 deg, Power: 4884.4 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 3.0 deg, Power: 4882.7 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.6 RPM, Pitch angle: 3.0 deg, Power: 4880.2 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.5 RPM, Pitch angle: 3.0 deg, Power: 4876.4 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.5 RPM, Pitch angle: 3.0 deg, Power: 4873.5 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.5 RPM, Pitch angle: 3.1 deg, Power: 4871.0 kW, Est. wind Speed: 11.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 3.1 deg, Power: 4877.0 kW, Est. wind Speed: 11.7 m/s\n", + "Generator speed: 1173.8 RPM, Pitch angle: 5.9 deg, Power: 5001.4 kW, Est. wind Speed: 12.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.1 kW, Est. wind Speed: 12.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.0 kW, Est. wind Speed: 12.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.0 kW, Est. wind Speed: 12.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.0 kW, Est. wind Speed: 12.6 m/s\n", @@ -523,41 +528,41 @@ "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.0 kW, Est. wind Speed: 12.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 5.9 deg, Power: 5000.0 kW, Est. wind Speed: 12.6 m/s\n", "Generator speed: 1173.8 RPM, Pitch angle: 5.9 deg, Power: 5008.7 kW, Est. wind Speed: 12.6 m/s\n", - "Generator speed: 1173.9 RPM, Pitch angle: 8.1 deg, Power: 5000.9 kW, Est. wind Speed: 13.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", + "Generator speed: 1174.0 RPM, Pitch angle: 8.1 deg, Power: 5001.9 kW, Est. wind Speed: 13.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.1 kW, Est. wind Speed: 13.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.7 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 8.1 deg, Power: 5000.0 kW, Est. wind Speed: 13.7 m/s\n", "Generator speed: 1173.9 RPM, Pitch angle: 8.1 deg, Power: 5009.0 kW, Est. wind Speed: 13.7 m/s\n", - "Generator speed: 1173.9 RPM, Pitch angle: 10.0 deg, Power: 5001.1 kW, Est. wind Speed: 14.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.6 m/s\n", + "Generator speed: 1173.9 RPM, Pitch angle: 10.0 deg, Power: 5001.9 kW, Est. wind Speed: 14.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.1 kW, Est. wind Speed: 14.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.6 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.7 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 10.0 deg, Power: 5000.0 kW, Est. wind Speed: 14.7 m/s\n", "Generator speed: 1173.9 RPM, Pitch angle: 10.0 deg, Power: 5009.4 kW, Est. wind Speed: 14.7 m/s\n", - "Generator speed: 1173.8 RPM, Pitch angle: 11.6 deg, Power: 5001.6 kW, Est. wind Speed: 15.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.6 m/s\n", - "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.6 m/s\n", + "Generator speed: 1173.8 RPM, Pitch angle: 11.6 deg, Power: 5001.7 kW, Est. wind Speed: 15.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.1 kW, Est. wind Speed: 15.6 m/s\n", + "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", "Generator speed: 1173.7 RPM, Pitch angle: 11.6 deg, Power: 5000.0 kW, Est. wind Speed: 15.7 m/s\n", - "Shutting down ../ROSCO/build/libdiscon.dylib\n" + "Shutting down ../lib/libdiscon.dylib\n" ] }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -567,16 +572,6 @@ } ], "source": [ - "# Specify controller dynamic library path and name\n", - "\n", - "if platform.system() == 'Windows':\n", - " ext = 'dll'\n", - "elif platform.system() == 'Darwin':\n", - " ext = 'dylib'\n", - "else:\n", - " ext = 'so'\n", - " \n", - "lib_name = (f'../ROSCO/build/libdiscon.{ext}')\n", "\n", "# Load the simulator and controller interface\n", "controller_int = ROSCO_ci.ControllerInterface(lib_name,param_filename=param_file)\n", @@ -627,7 +622,7 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": 15, "metadata": { "slideshow": { "slide_type": "subslide" @@ -636,7 +631,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -646,7 +641,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -658,16 +653,16 @@ "data": { "text/plain": [ "([
,
],\n", - " [array([,\n", - " ,\n", - " ,\n", - " ], dtype=object),\n", - " array([,\n", - " ,\n", - " ], dtype=object)])" + " [array([,\n", + " ,\n", + " ,\n", + " ], dtype=object),\n", + " array([,\n", + " , ],\n", + " dtype=object)])" ] }, - "execution_count": 11, + "execution_count": 15, "metadata": {}, "output_type": "execute_result" } @@ -677,7 +672,7 @@ "\n", "# Define openfast output filenames, please fill in your own .outb\n", "# filenames = [\"../Test_Cases/5MW_Step/5MW_Step.outb\"]\n", - "filenames = ['../Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.outb']\n", + "filenames = ['Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.outb']\n", "# Load output info and data\n", "fast_out = op.load_fast_out(filenames)\n", "\n", @@ -704,7 +699,7 @@ }, { "cell_type": "code", - "execution_count": 12, + "execution_count": 16, "metadata": { "slideshow": { "slide_type": "subslide" @@ -743,28 +738,14 @@ "\n", "I would finally like to note that there has been a lot of work from a lot of very smart (and really great) people that has gone into all of this, some of which are acknowledged on the [ROSCO toolbox](www.github.com/nrel/ROSCO_toolbox) and [ROSCO](www.github.com/nrel/ROSCO_toolbox) github pages. " ] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] - }, - { - "cell_type": "code", - "execution_count": null, - "metadata": {}, - "outputs": [], - "source": [] } ], "metadata": { "celltoolbar": "Slideshow", "kernelspec": { - "display_name": "rosco-env3", + "display_name": "Python 3 (ipykernel)", "language": "python", - "name": "rosco-env3" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -776,7 +757,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.10.8" + "version": "3.11.7" } }, "nbformat": 4, diff --git a/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst b/Examples/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst similarity index 100% rename from Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst rename to Examples/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst diff --git a/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat b/Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat similarity index 97% rename from Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat rename to Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat index 27bb021c..3c235956 100644 --- a/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat +++ b/Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat @@ -74,7 +74,7 @@ True GenTiStp - Method to stop the generator {T: timed using TimGen ---------------------- CABLE CONTROL ------------------------------------------- 0 CCmode - Cable control mode {0: none, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"../../ROSCO/build/libdiscon.dylib" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"../../../lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] "../NREL-5MW/DISCON.IN" DLL_InFile - Name of input file sent to the DLL (-) [used only with Bladed Interface] "DISCON" DLL_ProcName - Name of procedure in DLL to be called (-) [case sensitive; used only with DLL Interface] "default" DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] diff --git a/Test_Cases/BAR_10/Airfoils/AF00_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF00_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF00_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF00_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF01_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF01_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF01_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF01_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF02_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF02_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF02_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF02_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF03_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF03_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF03_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF03_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF04_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF04_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF04_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF04_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF05_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF05_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF05_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF05_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF06_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF06_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF06_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF06_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF07_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF07_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF07_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF07_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF08_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF08_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF08_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF08_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF09_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF09_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF09_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF09_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF10_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF10_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF10_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF10_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF11_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF11_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF11_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF11_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF12_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF12_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF12_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF12_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF13_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF13_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF13_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF13_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF14_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF14_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF14_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF14_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF15_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF15_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF15_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF15_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF16_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF16_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF16_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF16_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF17_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF17_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF17_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF17_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF18_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF18_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF18_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF18_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF19_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF19_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF19_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF19_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF20_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF20_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF20_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF20_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF21_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF21_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF21_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF21_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF22_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF22_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF22_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF22_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF23_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF23_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF23_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF23_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF24_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF24_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF24_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF24_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF25_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF25_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF25_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF25_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF26_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF26_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF26_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF26_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF27_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF27_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF27_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF27_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF28_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF28_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF28_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF28_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/AF29_Coords.txt b/Examples/Test_Cases/BAR_10/Airfoils/AF29_Coords.txt similarity index 100% rename from Test_Cases/BAR_10/Airfoils/AF29_Coords.txt rename to Examples/Test_Cases/BAR_10/Airfoils/AF29_Coords.txt diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_00.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_00.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_00.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_00.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_01.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_01.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_01.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_01.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_02.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_02.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_02.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_02.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_03.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_03.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_03.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_03.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_04.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_04.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_04.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_04.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_05.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_05.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_05.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_05.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_06.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_06.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_06.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_06.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_07.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_07.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_07.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_07.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_08.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_08.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_08.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_08.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_09.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_09.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_09.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_09.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_10.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_10.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_10.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_10.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_11.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_11.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_11.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_11.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_12.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_12.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_12.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_12.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_13.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_13.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_13.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_13.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_14.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_14.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_14.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_14.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_15.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_15.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_15.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_15.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_16.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_16.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_16.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_16.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_17.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_17.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_17.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_17.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_18.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_18.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_18.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_18.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_19.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_19.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_19.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_19.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_20.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_20.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_20.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_20.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_21.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_21.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_21.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_21.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_22.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_22.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_22.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_22.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_23.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_23.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_23.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_23.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_24.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_24.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_24.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_24.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_25.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_25.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_25.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_25.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_26.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_26.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_26.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_26.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_27.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_27.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_27.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_27.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_28.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_28.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_28.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_28.dat diff --git a/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_29.dat b/Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_29.dat similarity index 100% rename from Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_29.dat rename to Examples/Test_Cases/BAR_10/Airfoils/BAR_10_AeroDyn15_Polar_29.dat diff --git a/Test_Cases/BAR_10/BAR_10.fst b/Examples/Test_Cases/BAR_10/BAR_10.fst similarity index 100% rename from Test_Cases/BAR_10/BAR_10.fst rename to Examples/Test_Cases/BAR_10/BAR_10.fst diff --git a/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat b/Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_AeroDyn15.dat rename to Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat diff --git a/Test_Cases/BAR_10/BAR_10_AeroDyn15_blade.dat b/Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15_blade.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_AeroDyn15_blade.dat rename to Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15_blade.dat diff --git a/Test_Cases/BAR_10/BAR_10_BeamDyn.dat b/Examples/Test_Cases/BAR_10/BAR_10_BeamDyn.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_BeamDyn.dat rename to Examples/Test_Cases/BAR_10/BAR_10_BeamDyn.dat diff --git a/Test_Cases/BAR_10/BAR_10_BeamDyn_Blade.dat b/Examples/Test_Cases/BAR_10/BAR_10_BeamDyn_Blade.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_BeamDyn_Blade.dat rename to Examples/Test_Cases/BAR_10/BAR_10_BeamDyn_Blade.dat diff --git a/Test_Cases/BAR_10/BAR_10_DISCON.IN b/Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN similarity index 58% rename from Test_Cases/BAR_10/BAR_10_DISCON.IN rename to Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN index f750015d..ebbc56f5 100644 --- a/Test_Cases/BAR_10/BAR_10_DISCON.IN +++ b/Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN @@ -1,44 +1,54 @@ ! Controller parameter input file for the BAR_10 wind turbine -! - File written using ROSCO version 2.8.0 controller tuning logic on 04/10/23 +! - File written using ROSCO version 2.8.0 controller tuning logic on 01/05/24 -!------- DEBUG ------------------------------------------------------------ -1 ! LoggingLevel - (0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)) +!------- SIMULATION CONTROL ------------------------------------------------------------ +1 ! LoggingLevel - {0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)} +0 ! DT_Out - {Time step to output .dbg* files, or 0 to match sampling period of OpenFAST} +1 ! Ext_Interface - (0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0.) 0 ! Echo - (0 - no Echo, 1 - Echo input data to .echo) !------- CONTROLLER FLAGS ------------------------------------------------- -2 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals -0 ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} +2 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals 0 ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} -2 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} -1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} -0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} -1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} -2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} -1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} -0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} -0 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} -0 ! TD_Mode - Tower damper mode {0: no tower damper, 1: feed back translational nacelle accelleration to pitch angle} -2 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} -0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time} -0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} -0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} -0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} -0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} -0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} -0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] -0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] +2 ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)} +0 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} +1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} +0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} +1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} +0 ! PRC_Mode - Power reference tracking mode{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints} +2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} +1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} +0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} +0 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} +0 ! TD_Mode - Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle +0 ! TRA_Mode - Tower resonance avoidance mode (0- no tower resonsnace avoidance, 1- use torque control setpoints to avoid a specific frequency +2 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} +0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: rotor position control} +0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} +0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} +0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} +0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} +0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} +0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] +0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] !------- FILTERS ---------------------------------------------------------- -0.81771 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] -0.70000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] -2.61601 ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s] -0.000000 0.500000 ! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] +0.81771 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] +0.70000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] +0 ! F_NumNotchFilts - Number of notch filters placed on sensors +0.0000 ! F_NotchFreqs - Natural frequency of the notch filters. Array with length F_NumNotchFilts +0.0000 ! F_NotchBetaNum - Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] +0.0000 ! F_NotchBetaDen - Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] +0 ! F_GenSpdNotch_N - Number of notch filters on generator speed +0 ! F_GenSpdNotch_Ind - Indices of notch filters on generator speed +0 ! F_TwrTopNotch_N - Number of notch filters on tower top acceleration signal +0 ! F_TwrTopNotch_Ind - Indices of notch filters on tower top acceleration signal 0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. 0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. 0.000000 1.000000 ! F_FlCornerFreq - Natural frequency and damping in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s, -]. -0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. -7.848030 1.000000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control [rad/s, -]. +0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. +7.8480 1.0000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control !------- BLADE PITCH CONTROL ---------------------------------------------- 30 ! PC_GS_n - Amount of gain-scheduling table entries @@ -71,26 +81,33 @@ 70282.09458000 ! VS_MaxTq - Maximum generator torque in Region 3 (HSS side), [Nm]. 0.000000000000 ! VS_MinTq - Minimum generator torque (HSS side), [Nm]. 27.49717000000 ! VS_MinOMSpd - Minimum generator speed [rad/s] -12.67229000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side), [Nm/(rad/s)^2] +11.20801000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side). Only used in VS_ControlMode = 1,3 5000000.000000 ! VS_RtPwr - Wind turbine rated power [W] 63892.81326000 ! VS_RtTq - Rated torque, [Nm]. 75.83317000000 ! VS_RefSpd - Rated generator speed [rad/s] 1 ! VS_n - Number of generator PI torque controller gains -2452.07948000 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -332.357190000 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -9.76 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio [rad]. +9.76 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. +0.314000000000 ! VS_PwrFiltF - Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. !------- SETPOINT SMOOTHER --------------------------------------------- 1.00000 ! SS_VSGain - Variable speed torque controller setpoint smoother gain, [-]. 0.00100 ! SS_PCGain - Collective pitch controller setpoint smoother gain, [-]. +!------- POWER REFERENCE TRACKING -------------------------------------- +2 ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array +0.07854 ! PRC_LPF_Freq - Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] +3.0000 25.0000 ! PRC_WindSpeeds - Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] +0.7917 0.7917 ! PRC_GenSpeeds - Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + !------- WIND SPEED ESTIMATOR --------------------------------------------- 102.996 ! WE_BladeRadius - Blade length (distance from hub center to blade tip), [m] 1 ! WE_CP_n - Amount of parameters in the Cp array 0.0 ! WE_CP - Parameters that define the parameterized CP(lambda) function -0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] +0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] 96.8 ! WE_GearboxRatio - Gearbox ratio [>=1], [-] -311169343.31448 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] +311169343.31448 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] 1.225 ! WE_RhoAir - Air density, [kg m^-3] "Cp_Ct_Cq.BAR_10.txt" ! PerfFileName - File containing rotor performance tables (Cp,Ct,Cq) (absolute path or relative to this file) 36 26 ! PerfTableSize - Size of rotor performance tables, first number refers to number of blade pitch angles, second number referse to number of tip-speed ratios @@ -107,22 +124,27 @@ 0.00000 ! Y_IPC_KP - Yaw-by-IPC proportional controller gain Kp 0.00000 ! Y_IPC_KI - Yaw-by-IPC integral controller gain Ki -!------- TOWER FORE-AFT DAMPING ------------------------------------------- --1.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller [rad s/m] -0.0 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] -0.0 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] +!------- TOWER CONTROL ------------------------------------------------------ +0.00000 ! TRA_ExclSpeed - Rotor speed for exclusion [LSS, rad/s] +0.00000 ! TRA_ExclBand - Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 +0.00000e+00 ! TRA_RateLimit - Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/400. +0.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller, [rad*s/m] +0.00000 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] +0.00000 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] !------- MINIMUM PITCH SATURATION ------------------------------------------- 60 ! PS_BldPitchMin_N - Number of values in minimum blade pitch lookup table (should equal number of values in PS_WindSpeeds and PS_BldPitchMin) -3.0000 3.1818 3.3637 3.5455 3.7274 3.9092 4.0911 4.2729 4.4548 4.6366 4.8185 5.0003 5.1822 5.3640 5.5459 5.7277 5.9096 6.0914 6.2732 6.4551 6.6369 6.8188 7.0006 7.1825 7.3643 7.5462 7.7280 7.9099 8.0917 8.2736 8.8311 9.3887 9.9462 10.5038 11.0613 11.6188 12.1764 12.7339 13.2915 13.8490 14.4066 14.9641 15.5217 16.0792 16.6368 17.1943 17.7519 18.3094 18.8670 19.4245 19.9821 20.5396 21.0972 21.6547 22.2123 22.7698 23.3274 23.8849 24.4425 25.0000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] --0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01505486 -0.01247538 0.00009416 0.01064594 0.02025612 0.02875892 0.04130468 0.05575026 0.06941162 0.08245994 0.09516301 0.10759186 0.11974680 0.13166674 0.14343508 0.15503135 0.16644975 0.17776272 0.18893241 0.19997037 0.21092550 0.22173526 0.23245676 0.24309225 0.25359679 0.26404201 0.27436979 0.28461736 0.29478565 0.30484212 0.31485020 0.32473305 0.33456481 0.34429551 0.35395031 0.36352600 0.37300643 ! PS_BldPitchMin - Minimum blade pitch angles [rad] +3.000 3.182 3.364 3.546 3.727 3.909 4.091 4.273 4.455 4.637 4.818 5.000 5.182 5.364 5.546 5.728 5.910 6.091 6.273 6.455 6.637 6.819 7.001 7.182 7.364 7.546 7.728 7.910 8.092 8.274 8.831 9.389 9.946 10.504 11.061 11.619 12.176 12.734 13.291 13.849 14.407 14.964 15.522 16.079 16.637 17.194 17.752 18.309 18.867 19.425 19.982 20.540 21.097 21.655 22.212 22.770 23.327 23.885 24.442 25.000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] +-0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.015 -0.012 0.000 0.011 0.020 0.029 0.041 0.056 0.069 0.082 0.095 0.108 0.120 0.132 0.143 0.155 0.166 0.178 0.189 0.200 0.211 0.222 0.232 0.243 0.254 0.264 0.274 0.285 0.295 0.305 0.315 0.325 0.335 0.344 0.354 0.364 0.373 ! PS_BldPitchMin - Minimum blade pitch angles [rad] !------- SHUTDOWN ----------------------------------------------------------- 0.698100000000 ! SD_MaxPit - Maximum blade pitch angle to initiate shutdown, [rad] 0.418880000000 ! SD_CornerFreq - Cutoff Frequency for first order low-pass filter for blade pitch angle, [rad/s] !------- Floating ----------------------------------------------------------- -0.000000000000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +1 ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1 +0.0000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +0.0000 ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] !------- FLAP ACTUATION ----------------------------------------------------- 0.000000000000 ! Flp_Angle - Initial or steady state flap angle [rad] @@ -133,26 +155,28 @@ !------- Open Loop Control ----------------------------------------------------- "unused" ! OL_Filename - Input file with open loop timeseries (absolute path or relative to this file) 0 ! Ind_Breakpoint - The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) -0 ! Ind_BldPitch - The column in OL_Filename that contains the blade pitch input in rad + 0 0 0 ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array] 0 ! Ind_GenTq - The column in OL_Filename that contains the generator torque in Nm -0 ! Ind_YawRate - The column in OL_Filename that contains the nacelle yaw rate rad/s +0 ! Ind_YawRate - The column in OL_Filename that contains the yaw rate in rad/s +0 ! Ind_Azimuth - The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) +0.0000 0.0000 0.0000 0.0000 ! RP_Gains - PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) 0 ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N] 0 ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N] !------- Pitch Actuator Model ----------------------------------------------------- -3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] -0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] +3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] +0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] !------- Pitch Actuator Faults ----------------------------------------------------- 0.00000000 0.00000000 0.00000000 ! PF_Offsets - Constant blade pitch offsets for blades 1-3 [rad] !------- Active Wake Control ----------------------------------------------------- -1 ! AWC_NumModes - Number of user-defined AWC forcing modes -1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) -1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) -0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] -1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] -0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] +1 ! AWC_NumModes - Number of user-defined AWC forcing modes +1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) +1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) +0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] +1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] +0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] !------- External Controller Interface ----------------------------------------------------- "unused" ! DLL_FileName - Name/location of the dynamic library in the Bladed-DLL format @@ -161,13 +185,14 @@ !------- ZeroMQ Interface --------------------------------------------------------- "tcp://localhost:5555" ! ZMQ_CommAddress - Communication address for ZMQ server, (e.g. "tcp://localhost:5555") -2 ! ZMQ_UpdatePeriod - Call ZeroMQ every [x] seconds, [s] +1.000000 ! ZMQ_UpdatePeriod - Update period at zmq interface to send measurements and wait for setpoint [sec.] +0 ! ZMQ_ID - Integer identifier of turbine !------- Cable Control --------------------------------------------------------- 1 ! CC_Group_N - Number of cable control groups - 0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL +0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL 20.000000 ! CC_ActTau - Time constant for line actuator [s] !------- Structural Controllers --------------------------------------------------------- 1 ! StC_Group_N - Number of cable control groups - 0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output +0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output diff --git a/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat b/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_ElastoDyn.dat rename to Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat diff --git a/Test_Cases/BAR_10/BAR_10_ElastoDyn_blade.dat b/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn_blade.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_ElastoDyn_blade.dat rename to Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn_blade.dat diff --git a/Test_Cases/BAR_10/BAR_10_ElastoDyn_tower.dat b/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn_tower.dat similarity index 100% rename from Test_Cases/BAR_10/BAR_10_ElastoDyn_tower.dat rename to Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn_tower.dat diff --git a/Test_Cases/BAR_10/BAR_10_InflowFile.dat b/Examples/Test_Cases/BAR_10/BAR_10_InflowFile.dat similarity index 76% rename from Test_Cases/BAR_10/BAR_10_InflowFile.dat rename to Examples/Test_Cases/BAR_10/BAR_10_InflowFile.dat index 3cd7c48f..0cb641ac 100644 --- a/Test_Cases/BAR_10/BAR_10_InflowFile.dat +++ b/Examples/Test_Cases/BAR_10/BAR_10_InflowFile.dat @@ -5,6 +5,7 @@ False Echo - Echo input data to .ech (flag) 1 WindType - switch for wind file type (1=steady; 2=uniform; 3=binary TurbSim FF; 4=binary Bladed-style FF; 5=HAWC format; 6=User defined) 0.0 PropagationDir - Direction of wind propagation (meteoroligical rotation from aligned with X (positive rotates towards -Y) -- degrees) 0 VFlowAng - Upflow angle (degrees) (not used for native Bladed format WindType=7) +False VelInterpCubic - Use cubic interpolation for velocity in time (false=linear, true=cubic) [Used with WindType=2,3,4,5,7] 1 NWindVel - Number of points to output the wind velocity (0 to 9) 0.0 WindVxiList - List of coordinates in the inertial X direction (m) 0.0 WindVyiList - List of coordinates in the inertial Y direction (m) @@ -47,6 +48,19 @@ False TowerFile - Have tower file (.twr) (flag) 0.2 PLExp_Hawc - Power law exponent (-) (used for PL wind profile type only) 0.03 Z0 - Surface roughness length (m) (used for LG wind profile type only) 0 XOffset - Initial offset in +x direction (shift of wind box) +================== LIDAR Parameters =========================================================================== +0 SensorType - Switch for lidar configuration (0 = None, 1 = Single Point Beam(s), 2 = Continuous, 3 = Pulsed) +0 NumPulseGate - Number of lidar measurement gates (used when SensorType = 3) +30 PulseSpacing - Distance between range gates (m) (used when SensorType = 3) +0 NumBeam - Number of lidar measurement beams (0-5)(used when SensorType = 1) +-200 FocalDistanceX - Focal distance co-ordinates of the lidar beam in the x direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceY - Focal distance co-ordinates of the lidar beam in the y direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceZ - Focal distance co-ordinates of the lidar beam in the z direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0.0 0.0 0.0 RotorApexOffsetPos - Offset of the lidar from hub height (m) +17 URefLid - Reference average wind speed for the lidar[m/s] +0.25 MeasurementInterval - Time between each measurement [s] +False LidRadialVel - TRUE => return radial component, FALSE => return 'x' direction estimate +1 ConsiderHubMotion - Flag whether to consider the hub motion's impact on Lidar measurements ====================== OUTPUT ================================================== False SumPrint - Print summary data to .IfW.sum (flag) OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) diff --git a/Test_Cases/BAR_10/BAR_10_ServoDyn.dat b/Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat similarity index 98% rename from Test_Cases/BAR_10/BAR_10_ServoDyn.dat rename to Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat index b13a1212..d095227b 100644 --- a/Test_Cases/BAR_10/BAR_10_ServoDyn.dat +++ b/Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat @@ -74,7 +74,7 @@ True GenTiStp - Method to stop the generator {T: timed usin ---------------------- CABLE CONTROL ------------------------------------------- 0 CCmode - Cable control mode {0: none, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"../../ROSCO/install/lib/libdiscon.dylib" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"../../../lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] "BAR_10_DISCON.IN" DLL_InFile - Name of input file sent to the DLL (-) [used only with Bladed Interface] "DISCON" DLL_ProcName - Name of procedure in DLL to be called (-) [case sensitive; used only with DLL Interface] "default" DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] diff --git a/Test_Cases/BAR_10/Cp_Ct_Cq.BAR_10.txt b/Examples/Test_Cases/BAR_10/Cp_Ct_Cq.BAR_10.txt similarity index 100% rename from Test_Cases/BAR_10/Cp_Ct_Cq.BAR_10.txt rename to Examples/Test_Cases/BAR_10/Cp_Ct_Cq.BAR_10.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_00_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_01_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_02_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_03_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_04_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_05_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_06_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_07_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_08_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_09_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_10_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_11_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_12_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_13_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_14_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_15_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_16_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_17_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_18_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_19_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_20_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_21_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_22_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_23_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_24_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_25_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_26_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_27_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_28_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_29_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_30_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_31_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_32_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_33_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_34_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_35_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_36_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_37_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_38_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_39_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_40_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_41_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_42_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_43_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_44_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_45_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_46_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_47_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_48_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49_Coords.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49_Coords.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49_Coords.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Airfoils/IEA-15-240-RWT_AeroDyn15_Polar_49_Coords.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN similarity index 58% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN index 17c96a1e..cd58ccf8 100644 --- a/Test_Cases/IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN +++ b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN @@ -1,44 +1,54 @@ ! Controller parameter input file for the IEA-15-240-RWT-UMaineSemi wind turbine -! - File written using ROSCO version 2.8.0 controller tuning logic on 04/10/23 +! - File written using ROSCO version 2.8.0 controller tuning logic on 01/05/24 -!------- DEBUG ------------------------------------------------------------ -2 ! LoggingLevel - (0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)) +!------- SIMULATION CONTROL ------------------------------------------------------------ +2 ! LoggingLevel - {0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)} +0 ! DT_Out - {Time step to output .dbg* files, or 0 to match sampling period of OpenFAST} +1 ! Ext_Interface - (0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0.) 0 ! Echo - (0 - no Echo, 1 - Echo input data to .echo) !------- CONTROLLER FLAGS ------------------------------------------------- -2 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals -2 ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} +2 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals 0 ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} -2 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} -1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} -0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} -1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} -2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} -1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} -0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} -2 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} -0 ! TD_Mode - Tower damper mode {0: no tower damper, 1: feed back translational nacelle accelleration to pitch angle} -0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} -0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time} -2 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} -0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} -0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} -0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} -0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} -0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] -0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] +2 ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)} +0 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} +1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} +0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} +1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} +0 ! PRC_Mode - Power reference tracking mode{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints} +2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} +1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} +0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} +2 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} +0 ! TD_Mode - Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle +0 ! TRA_Mode - Tower resonance avoidance mode (0- no tower resonsnace avoidance, 1- use torque control setpoints to avoid a specific frequency +0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} +0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: rotor position control} +2 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} +0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} +0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} +0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} +0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} +0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] +0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] !------- FILTERS ---------------------------------------------------------- -1.00810 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] -0.70000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] -3.35500 ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s] -0.000000 0.250000 ! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] +1.00810 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] +0.70000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] +1 ! F_NumNotchFilts - Number of notch filters placed on sensors +3.3550 ! F_NotchFreqs - Natural frequency of the notch filters. Array with length F_NumNotchFilts +0.0000 ! F_NotchBetaNum - Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] +0.2500 ! F_NotchBetaDen - Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] +0 ! F_GenSpdNotch_N - Number of notch filters on generator speed +0 ! F_GenSpdNotch_Ind - Indices of notch filters on generator speed +1 ! F_TwrTopNotch_N - Number of notch filters on tower top acceleration signal +1 ! F_TwrTopNotch_Ind - Indices of notch filters on tower top acceleration signal 0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. 0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. 0.213000 1.000000 ! F_FlCornerFreq - Natural frequency and damping in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s, -]. -0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. -10.461600 1.000000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control [rad/s, -]. +0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. +10.4616 1.0000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control !------- BLADE PITCH CONTROL ---------------------------------------------- 30 ! PC_GS_n - Amount of gain-scheduling table entries @@ -71,26 +81,33 @@ 21586451.33303 ! VS_MaxTq - Maximum generator torque in Region 3 (HSS side), [Nm]. 0.000000000000 ! VS_MinTq - Minimum generator torque (HSS side), [Nm]. 0.523600000000 ! VS_MinOMSpd - Minimum generator speed [rad/s] -37840583.60628 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side), [Nm/(rad/s)^2] +31393135.82403 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side). Only used in VS_ControlMode = 1,3 15000000.00000 ! VS_RtPwr - Wind turbine rated power [W] 19624046.66639 ! VS_RtTq - Rated torque, [Nm]. 0.791680000000 ! VS_RefSpd - Rated generator speed [rad/s] 1 ! VS_n - Number of generator PI torque controller gains -37877315.85935 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -4588245.18720 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -9.00 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio [rad]. +9.00 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. +0.314000000000 ! VS_PwrFiltF - Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. !------- SETPOINT SMOOTHER --------------------------------------------- 1.00000 ! SS_VSGain - Variable speed torque controller setpoint smoother gain, [-]. 0.00100 ! SS_PCGain - Collective pitch controller setpoint smoother gain, [-]. +!------- POWER REFERENCE TRACKING -------------------------------------- +2 ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array +0.07854 ! PRC_LPF_Freq - Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] +3.0000 25.0000 ! PRC_WindSpeeds - Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] +0.7917 0.7917 ! PRC_GenSpeeds - Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + !------- WIND SPEED ESTIMATOR --------------------------------------------- 120.000 ! WE_BladeRadius - Blade length (distance from hub center to blade tip), [m] 1 ! WE_CP_n - Amount of parameters in the Cp array 0.0 ! WE_CP - Parameters that define the parameterized CP(lambda) function -0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] +0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] 1.0 ! WE_GearboxRatio - Gearbox ratio [>=1], [-] -318628138.00000 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] +318628138.00000 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] 1.225 ! WE_RhoAir - Air density, [kg m^-3] "Cp_Ct_Cq.IEA15MW.txt" ! PerfFileName - File containing rotor performance tables (Cp,Ct,Cq) (absolute path or relative to this file) 36 26 ! PerfTableSize - Size of rotor performance tables, first number refers to number of blade pitch angles, second number referse to number of tip-speed ratios @@ -107,22 +124,27 @@ 0.00000 ! Y_IPC_KP - Yaw-by-IPC proportional controller gain Kp 0.00000 ! Y_IPC_KI - Yaw-by-IPC integral controller gain Ki -!------- TOWER FORE-AFT DAMPING ------------------------------------------- --1.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller [rad s/m] -0.0 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] -0.0 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] +!------- TOWER CONTROL ------------------------------------------------------ +0.00000 ! TRA_ExclSpeed - Rotor speed for exclusion [LSS, rad/s] +0.00000 ! TRA_ExclBand - Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 +0.00000e+00 ! TRA_RateLimit - Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/400. +0.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller, [rad*s/m] +0.00000 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] +0.00000 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] !------- MINIMUM PITCH SATURATION ------------------------------------------- 60 ! PS_BldPitchMin_N - Number of values in minimum blade pitch lookup table (should equal number of values in PS_WindSpeeds and PS_BldPitchMin) -3.0000 3.2669 3.5338 3.8007 4.0676 4.3345 4.6014 4.8683 5.1352 5.4021 5.6690 5.9359 6.2028 6.4697 6.7366 7.0034 7.2703 7.5372 7.8041 8.0710 8.3379 8.6048 8.8717 9.1386 9.4055 9.6724 9.9393 10.2062 10.4731 10.7400 11.2153 11.6907 12.1660 12.6413 13.1167 13.5920 14.0673 14.5427 15.0180 15.4933 15.9687 16.4440 16.9193 17.3947 17.8700 18.3453 18.8207 19.2960 19.7713 20.2467 20.7220 21.1973 21.6727 22.1480 22.6233 23.0987 23.5740 24.0493 24.5247 25.0000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] -0.05997374 0.05997374 0.05997374 0.05997374 0.05997374 0.05995230 0.05568017 0.05139305 0.04630957 0.04053154 0.03444871 0.02774193 0.02083682 0.01377992 0.00660717 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00798358 0.02222567 0.03475505 0.04563791 0.05328450 0.06405592 0.07436594 0.08427713 0.09385932 0.10323575 0.11234777 0.12134295 0.13011531 0.13881511 0.14732690 0.15578898 0.16409463 0.17235500 0.18049466 0.18858365 0.19658691 0.20452181 0.21241204 0.22021131 0.22800500 0.23567545 0.24336643 0.25094186 0.25851588 0.26602564 0.27348266 0.28093357 0.28828297 0.29566389 0.30293290 ! PS_BldPitchMin - Minimum blade pitch angles [rad] +3.000 3.267 3.534 3.801 4.068 4.334 4.601 4.868 5.135 5.402 5.669 5.936 6.203 6.470 6.737 7.003 7.270 7.537 7.804 8.071 8.338 8.605 8.872 9.139 9.406 9.672 9.939 10.206 10.473 10.740 11.215 11.691 12.166 12.641 13.117 13.592 14.067 14.543 15.018 15.493 15.969 16.444 16.919 17.395 17.870 18.345 18.821 19.296 19.771 20.247 20.722 21.197 21.673 22.148 22.623 23.099 23.574 24.049 24.525 25.000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] +0.060 0.060 0.060 0.060 0.060 0.060 0.056 0.051 0.046 0.041 0.034 0.028 0.021 0.014 0.007 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.008 0.022 0.035 0.046 0.053 0.064 0.074 0.084 0.094 0.103 0.112 0.121 0.130 0.139 0.147 0.156 0.164 0.172 0.180 0.189 0.197 0.205 0.212 0.220 0.228 0.236 0.243 0.251 0.259 0.266 0.273 0.281 0.288 0.296 0.303 ! PS_BldPitchMin - Minimum blade pitch angles [rad] !------- SHUTDOWN ----------------------------------------------------------- 0.698100000000 ! SD_MaxPit - Maximum blade pitch angle to initiate shutdown, [rad] 0.418880000000 ! SD_CornerFreq - Cutoff Frequency for first order low-pass filter for blade pitch angle, [rad/s] !------- Floating ----------------------------------------------------------- --9.34645000000 ! Fl_Kp - Nacelle pitching proportional feedback gain [s] +1 ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1 +-9.3465 ! Fl_Kp - Nacelle pitching proportional feedback gain [s] +11.2770 ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] !------- FLAP ACTUATION ----------------------------------------------------- 0.000000000000 ! Flp_Angle - Initial or steady state flap angle [rad] @@ -133,26 +155,28 @@ !------- Open Loop Control ----------------------------------------------------- "unused" ! OL_Filename - Input file with open loop timeseries (absolute path or relative to this file) 0 ! Ind_Breakpoint - The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) -0 ! Ind_BldPitch - The column in OL_Filename that contains the blade pitch input in rad + 0 0 0 ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array] 0 ! Ind_GenTq - The column in OL_Filename that contains the generator torque in Nm -0 ! Ind_YawRate - The column in OL_Filename that contains the nacelle yaw rate rad/s +0 ! Ind_YawRate - The column in OL_Filename that contains the yaw rate in rad/s +0 ! Ind_Azimuth - The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) +0.0000 0.0000 0.0000 0.0000 ! RP_Gains - PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) 0 ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N] 0 ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N] !------- Pitch Actuator Model ----------------------------------------------------- -1.570800000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] -0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] +1.570800000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] +0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] !------- Pitch Actuator Faults ----------------------------------------------------- 0.00000000 0.00000000 0.00000000 ! PF_Offsets - Constant blade pitch offsets for blades 1-3 [rad] !------- Active Wake Control ----------------------------------------------------- -1 ! AWC_NumModes - Number of user-defined AWC forcing modes -1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) -1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) -0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] -1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] -0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] +1 ! AWC_NumModes - Number of user-defined AWC forcing modes +1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) +1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) +0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] +1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] +0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] !------- External Controller Interface ----------------------------------------------------- "unused" ! DLL_FileName - Name/location of the dynamic library in the Bladed-DLL format @@ -161,13 +185,14 @@ !------- ZeroMQ Interface --------------------------------------------------------- "tcp://localhost:5555" ! ZMQ_CommAddress - Communication address for ZMQ server, (e.g. "tcp://localhost:5555") -2 ! ZMQ_UpdatePeriod - Call ZeroMQ every [x] seconds, [s] +1.000000 ! ZMQ_UpdatePeriod - Update period at zmq interface to send measurements and wait for setpoint [sec.] +0 ! ZMQ_ID - Integer identifier of turbine !------- Cable Control --------------------------------------------------------- 1 ! CC_Group_N - Number of cable control groups - 0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL +0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL 20.000000 ! CC_ActTau - Time constant for line actuator [s] !------- Structural Controllers --------------------------------------------------------- 1 ! StC_Group_N - Number of cable control groups - 0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output +0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.1 b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.1 similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.1 rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.1 diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12d b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12d similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12d rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12d diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12s b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12s similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12s rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.12s diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.3 b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.3 similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.3 rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.3 diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.hst b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.hst similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.hst rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.hst diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ss b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ss similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ss rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ss diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ssexctn b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ssexctn similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ssexctn rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/HydroData/IEA-15-240-RWT-UMaineSemi.ssexctn diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn_tower.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn_tower.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn_tower.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn_tower.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_MoorDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_MoorDyn.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_MoorDyn.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_MoorDyn.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat similarity index 98% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat index 51a09d4e..7ea5ee55 100644 --- a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat @@ -74,7 +74,7 @@ True GenTiStp - Method to stop the generator {T: timed usin ---------------------- CABLE CONTROL ------------------------------------------- 0 CCmode - Cable control mode {0: none, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"../../ROSCO/install/lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"../../../lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] "DISCON-UMaineSemi.IN" DLL_InFile - Name of input file sent to the DLL (-) [used only with Bladed Interface] "DISCON" DLL_ProcName - Name of procedure in DLL to be called (-) [case sensitive; used only with DLL Interface] "default" DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15_blade.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15_blade.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15_blade.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_AeroDyn15_blade.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn_blade.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn_blade.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn_blade.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_BeamDyn_blade.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_ElastoDyn_blade.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_ElastoDyn_blade.dat similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_ElastoDyn_blade.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_ElastoDyn_blade.dat diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_InflowFile.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_InflowFile.dat similarity index 76% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_InflowFile.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_InflowFile.dat index f7e3ccc8..bc188532 100644 --- a/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_InflowFile.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT_InflowFile.dat @@ -5,6 +5,7 @@ False Echo - Echo input data to .ech (flag) 1 WindType - switch for wind file type (1=steady; 2=uniform; 3=binary TurbSim FF; 4=binary Bladed-style FF; 5=HAWC format; 6=User defined; 7=native Bladed FF) 0.0 PropagationDir - Direction of wind propagation (meteoroligical rotation from aligned with X (positive rotates towards -Y) -- degrees) 0 VFlowAng - Upflow angle (degrees) (not used for native Bladed format WindType=7) +False VelInterpCubic - Use cubic interpolation for velocity in time (false=linear, true=cubic) [Used with WindType=2,3,4,5,7] 1 NWindVel - Number of points to output the wind velocity (0 to 9) 0.0 WindVxiList - List of coordinates in the inertial X direction (m) 0.0 WindVyiList - List of coordinates in the inertial Y direction (m) @@ -47,6 +48,19 @@ False TowerFile - Have tower file (.twr) (flag) 0.2 PLExp_Hawc - Power law exponent (-) (used for PL wind profile type only) 0.03 Z0 - Surface roughness length (m) (used for LG wind profile type only) 0 XOffset - Initial offset in +x direction (shift of wind box) +================== LIDAR Parameters =========================================================================== +0 SensorType - Switch for lidar configuration (0 = None, 1 = Single Point Beam(s), 2 = Continuous, 3 = Pulsed) +0 NumPulseGate - Number of lidar measurement gates (used when SensorType = 3) +30 PulseSpacing - Distance between range gates (m) (used when SensorType = 3) +0 NumBeam - Number of lidar measurement beams (0-5)(used when SensorType = 1) +-200 FocalDistanceX - Focal distance co-ordinates of the lidar beam in the x direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceY - Focal distance co-ordinates of the lidar beam in the y direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceZ - Focal distance co-ordinates of the lidar beam in the z direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0.0 0.0 0.0 RotorApexOffsetPos - Offset of the lidar from hub height (m) +17 URefLid - Reference average wind speed for the lidar[m/s] +0.25 MeasurementInterval - Time between each measurement [s] +False LidRadialVel - TRUE => return radial component, FALSE => return 'x' direction estimate +1 ConsiderHubMotion - Flag whether to consider the hub motion's impact on Lidar measurements ====================== OUTPUT ================================================== False SumPrint - Print summary data to .IfW.sum (flag) OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col1.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col1.dat similarity index 99% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col1.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col1.dat index 5709eb5f..c35e51c9 100644 --- a/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col1.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col1.dat @@ -3,7 +3,7 @@ Input file for tuned mass damper, module by Matt Lackner, Meghan Glade, and Semy ---------------------- SIMULATION CONTROL -------------------------------------- True Echo - Echo input data to .ech (flag) ---------------------- StC DEGREES OF FREEDOM ---------------------------------- - 5 StC_DOF_MODE - DOF mode (switch) {0: No StC or TLCD DOF; 1: StC_X_DOF, StC_Y_DOF, and/or StC_Z_DOF (three independent StC DOFs); 2: StC_XY_DOF (Omni-Directional StC); 3: TLCD; 4: Prescribed force/moment time series} + 5 StC_DOF_MODE - DOF mode (switch) {0: No StC or TLCD DOF; 1: StC_X_DOF, StC_Y_DOF, and/or StC_Z_DOF (three independent StC DOFs); 2: StC_XY_DOF (Omni-Directional StC); 3: TLCD; 4: Prescribed force/moment time series; 5: Force determined by external DLL} false StC_X_DOF - DOF on or off for StC X (flag) [Used only when StC_DOF_MODE=1] false StC_Y_DOF - DOF on or off for StC Y (flag) [Used only when StC_DOF_MODE=1] false StC_Z_DOF - DOF on or off for StC Z (flag) [Used only when StC_DOF_MODE=1] @@ -92,4 +92,4 @@ False Use_F_TBL - Use spring force from user-defined table (flag) ---------------------- PRESCRIBED TIME SERIES --------------------------------- [used only when StC_DOF_MODE=4] 1 PrescribedForcesCoord- Prescribed forces are in global or local coordinates (switch) {1: global; 2: local} "Bld-TimeForceSeries.dat" PrescribedForcesFile - Time series force and moment (7 columns of time, FX, FY, FZ, MX, MY, MZ) -------------------------------------------------------------------------------- \ No newline at end of file +------------------------------------------------------------------------------- diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col2.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col2.dat similarity index 99% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col2.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col2.dat index 83e86cf8..768c74a8 100644 --- a/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col2.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col2.dat @@ -3,7 +3,7 @@ Input file for tuned mass damper, module by Matt Lackner, Meghan Glade, and Semy ---------------------- SIMULATION CONTROL -------------------------------------- True Echo - Echo input data to .ech (flag) ---------------------- StC DEGREES OF FREEDOM ---------------------------------- - 5 StC_DOF_MODE - DOF mode (switch) {0: No StC or TLCD DOF; 1: StC_X_DOF, StC_Y_DOF, and/or StC_Z_DOF (three independent StC DOFs); 2: StC_XY_DOF (Omni-Directional StC); 3: TLCD; 4: Prescribed force/moment time series} + 5 StC_DOF_MODE - DOF mode (switch) {0: No StC or TLCD DOF; 1: StC_X_DOF, StC_Y_DOF, and/or StC_Z_DOF (three independent StC DOFs); 2: StC_XY_DOF (Omni-Directional StC); 3: TLCD; 4: Prescribed force/moment time series; 5: Force determined by external DLL} false StC_X_DOF - DOF on or off for StC X (flag) [Used only when StC_DOF_MODE=1] false StC_Y_DOF - DOF on or off for StC Y (flag) [Used only when StC_DOF_MODE=1] false StC_Z_DOF - DOF on or off for StC Z (flag) [Used only when StC_DOF_MODE=1] @@ -92,4 +92,4 @@ False Use_F_TBL - Use spring force from user-defined table (flag) ---------------------- PRESCRIBED TIME SERIES --------------------------------- [used only when StC_DOF_MODE=4] 1 PrescribedForcesCoord- Prescribed forces are in global or local coordinates (switch) {1: global; 2: local} "Bld-TimeForceSeries.dat" PrescribedForcesFile - Time series force and moment (7 columns of time, FX, FY, FZ, MX, MY, MZ) -------------------------------------------------------------------------------- \ No newline at end of file +------------------------------------------------------------------------------- diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col3.dat b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col3.dat similarity index 99% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col3.dat rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col3.dat index 0488dc80..c9c5bc66 100644 --- a/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col3.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/StC-Force-Col3.dat @@ -3,7 +3,7 @@ Input file for tuned mass damper, module by Matt Lackner, Meghan Glade, and Semy ---------------------- SIMULATION CONTROL -------------------------------------- True Echo - Echo input data to .ech (flag) ---------------------- StC DEGREES OF FREEDOM ---------------------------------- - 5 StC_DOF_MODE - DOF mode (switch) {0: No StC or TLCD DOF; 1: StC_X_DOF, StC_Y_DOF, and/or StC_Z_DOF (three independent StC DOFs); 2: StC_XY_DOF (Omni-Directional StC); 3: TLCD; 4: Prescribed force/moment time series} + 5 StC_DOF_MODE - DOF mode (switch) {0: No StC or TLCD DOF; 1: StC_X_DOF, StC_Y_DOF, and/or StC_Z_DOF (three independent StC DOFs); 2: StC_XY_DOF (Omni-Directional StC); 3: TLCD; 4: Prescribed force/moment time series; 5: Force determined by external DLL} false StC_X_DOF - DOF on or off for StC X (flag) [Used only when StC_DOF_MODE=1] false StC_Y_DOF - DOF on or off for StC Y (flag) [Used only when StC_DOF_MODE=1] false StC_Z_DOF - DOF on or off for StC Z (flag) [Used only when StC_DOF_MODE=1] @@ -92,4 +92,4 @@ False Use_F_TBL - Use spring force from user-defined table (flag) ---------------------- PRESCRIBED TIME SERIES --------------------------------- [used only when StC_DOF_MODE=4] 1 PrescribedForcesCoord- Prescribed forces are in global or local coordinates (switch) {1: global; 2: local} "Bld-TimeForceSeries.dat" PrescribedForcesFile - Time series force and moment (7 columns of time, FX, FY, FZ, MX, MY, MZ) -------------------------------------------------------------------------------- \ No newline at end of file +------------------------------------------------------------------------------- diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_00.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_01.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_02.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_03.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_04.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_05.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_06.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_07.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_08.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_09.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_10.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_11.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_12.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_13.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_14.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_15.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_16.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_17.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_18.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.1.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.1.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.1.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.1.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.10.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.10.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.10.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.10.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.11.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.11.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.11.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.11.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.12.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.12.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.12.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.12.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.2.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.2.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.2.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.2.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.3.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.3.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.3.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.3.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.4.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.4.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.4.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.4.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.5.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.5.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.5.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.5.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.6.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.6.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.6.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.6.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.7.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.7.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.7.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.7.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.8.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.8.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.8.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.8.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.9.lin b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.9.lin similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.9.lin rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/linearizations/lin_19.9.lin diff --git a/Test_Cases/IEA-15-240-RWT-UMaineSemi/ss_ops.yaml b/Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/ss_ops.yaml similarity index 100% rename from Test_Cases/IEA-15-240-RWT-UMaineSemi/ss_ops.yaml rename to Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi/ss_ops.yaml diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0240.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0240.dat new file mode 100644 index 00000000..94b36abc --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0240.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0240 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0240_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.3120 0.0100 -1 + -160 0.6240 0.0706 -1 + -150 0.9360 0.2428 -1 + -140 0.7699 0.4549 -1 + -130 0.6312 0.6818 -1 + -120 0.4861 0.8973 -1 + -110 0.3275 1.0763 -1 + -100 0.1610 1.1983 -1 + -90 0.0000 1.2500 -1 + -80 -0.1610 1.1983 -1 + -70 -0.3275 1.0763 -1 + -60 -0.4861 0.8973 -1 + -50 -0.6312 0.6818 -1 + -40 -0.7699 0.4549 -1 + -30 -0.9360 0.2428 -1 + -20 -0.6782 0.1306 -1 + -10 -0.6006 0.0183 -2.3658 + -9 -0.5703 0.0150 -2.1354 + -8 -0.5401 0.0124 -1.9128 + -7 -0.4863 0.0111 -1.6564 + -6 -0.3911 0.0101 -1.4075 + -5 -0.2829 0.0093 -1.2098 + -4 -0.1699 0.0086 -1.0246 + -3 -0.0547 0.0076 -0.9055 + -2 0.0671 0.0074 -0.9047 + -1 0.1884 0.0073 -0.9888 + 0 0.3092 0.0074 -1.0777 + 1 0.4307 0.0074 -1.1694 + 2 0.5503 0.0076 -1.2608 + 3 0.6677 0.0078 -1.3557 + 4 0.7807 0.0082 -1.4512 + 5 0.8921 0.0086 -1.5561 + 6 0.9830 0.0097 -1.6648 + 7 1.0196 0.0114 -1.7468 + 8 1.0527 0.0137 -1.8733 + 9 1.0932 0.0166 -2.0257 + 10 1.1352 0.0200 -2.1849 + 11 1.1432 0.0259 -2.3027 + 12 1.1730 0.0313 -2.5537 + 13 1.1826 0.0392 -2.7674 + 14 1.2087 0.0464 -3.0323 + 15 1.2272 0.0550 -3.2908 + 16 1.2557 0.0634 -3.5959 + 17 1.2806 0.0725 -3.9100 + 18 1.3037 0.0825 -4.2419 + 19 1.3252 0.0930 -4.5743 + 20 1.3439 0.1043 -4.9173 + 21 1.3613 0.1159 -5.2685 + 22 1.3809 0.1271 -5.6456 + 23 1.3894 0.1401 -5.9876 + 24 1.3961 0.1532 -6.3248 + 25 1.3970 0.1669 -6.6429 + 26 1.3922 0.1814 -6.9151 + 28 1.3673 0.2112 -7.3108 + 29 1.3488 0.2278 -7.4112 + 30 1.3371 0.2428 -7.5348 + 40 1.0999 0.4549 -1 + 50 0.9017 0.6818 -1 + 60 0.6944 0.8973 -1 + 70 0.4678 1.0763 -1 + 80 0.2300 1.1983 -1 + 90 0.0000 1.2500 -1 + 100 -0.1610 1.1983 -1 + 110 -0.3275 1.0763 -1 + 120 -0.4861 0.8973 -1 + 130 -0.6312 0.6818 -1 + 140 -0.7699 0.4549 -1 + 150 -0.9360 0.2428 -1 + 160 -0.6240 0.0706 -1 + 170 -0.3120 0.0100 -1 + 180 0.0000 0.0100 -1 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.3270 0.0100 -1 + -160 0.6541 0.0587 -1 + -150 0.9811 0.2318 -1 + -140 0.7974 0.4451 -1 + -130 0.6474 0.6736 -1 + -120 0.4948 0.8909 -1 + -110 0.3312 1.0719 -1 + -100 0.1619 1.1961 -1 + -90 0.0000 1.2500 -1 + -80 -0.1619 1.1961 -1 + -70 -0.3312 1.0719 -1 + -60 -0.4948 0.8909 -1 + -50 -0.6474 0.6736 -1 + -40 -0.7974 0.4451 -1 + -30 -0.9811 0.2318 -1 + -20 -0.7169 0.1237 -1 + -10 -0.6467 0.0156 -2.4629 + -9 -0.5996 0.0132 -2.1912 + -8 -0.5801 0.0111 -1.9816 + -7 -0.4950 0.0100 -1.6720 + -6 -0.3910 0.0092 -1.4078 + -5 -0.2810 0.0085 -1.2080 + -4 -0.1639 0.0080 -1.0184 + -3 -0.0454 0.0073 -0.8991 + -1 0.1982 0.0065 -0.9945 + 0 0.3213 0.0064 -1.0853 + 1 0.4423 0.0066 -1.1768 + 2 0.5645 0.0066 -1.2701 + 5 0.8977 0.0083 -1.5589 + 6 0.9769 0.0097 -1.6615 + 7 1.0311 0.0109 -1.7560 + 9 1.1327 0.0147 -2.0745 + 10 1.1526 0.0188 -2.2074 + 11 1.1873 0.0230 -2.3877 + 12 1.2028 0.0291 -2.6164 + 13 1.2313 0.0351 -2.8768 + 14 1.2601 0.0417 -3.1622 + 15 1.2941 0.0485 -3.4718 + 16 1.3216 0.0564 -3.7920 + 17 1.3498 0.0647 -4.1401 + 18 1.3733 0.0740 -4.4868 + 19 1.3966 0.0838 -4.8430 + 20 1.4115 0.0951 -5.1959 + 21 1.4270 0.1066 -5.5559 + 22 1.4404 0.1187 -5.9301 + 23 1.4449 0.1319 -6.2704 + 24 1.4587 0.1437 -6.6837 + 25 1.4594 0.1573 -7.0264 + 26 1.4601 0.1706 -7.3616 + 27 1.4562 0.1845 -7.6585 + 28 1.4482 0.1989 -7.9116 + 29 1.4181 0.2163 -7.9793 + 30 1.4016 0.2318 -8.1104 + 40 1.1391 0.4451 -1 + 50 0.9249 0.6736 -1 + 60 0.7068 0.8909 -1 + 70 0.4731 1.0719 -1 + 80 0.2313 1.1961 -1 + 90 0.0000 1.2500 -1 + 100 -0.1619 1.1961 -1 + 110 -0.3312 1.0719 -1 + 120 -0.4948 0.8909 -1 + 130 -0.6474 0.6736 -1 + 140 -0.7974 0.4451 -1 + 150 -0.9811 0.2318 -1 + 160 -0.6541 0.0587 -1 + 170 -0.3270 0.0100 -1 + 180 0.0000 0.0100 -1 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.3392 0.0100 -1 + -160 0.6784 0.0496 -1 + -150 1.0176 0.2235 -1 + -140 0.8196 0.4377 -1 + -130 0.6605 0.6674 -1 + -120 0.5018 0.8861 -1 + -110 0.3342 1.0686 -1 + -100 0.1627 1.1945 -1 + -90 0.0000 1.2500 -1 + -80 -0.1627 1.1945 -1 + -70 -0.3342 1.0686 -1 + -60 -0.5018 0.8861 -1 + -50 -0.6605 0.6674 -1 + -40 -0.8196 0.4377 -1 + -30 -1.0176 0.2235 -1 + -20 -0.7445 0.1188 -1 + -10 -0.6733 0.0141 -2.5188 + -9 -0.6311 0.0119 -2.2492 + -8 -0.5908 0.0105 -2.0003 + -7 -0.4967 0.0096 -1.6748 + -6 -0.3927 0.0088 -1.4104 + -5 -0.2789 0.0081 -1.2057 + -4 -0.1611 0.0077 -1.0152 + -3 -0.0419 0.0072 -0.8970 + -2 0.0793 0.0064 -0.9117 + -1 0.2025 0.0061 -0.9971 + 0 0.3254 0.0061 -1.0876 + 1 0.4490 0.0061 -1.1811 + 2 0.5682 0.0064 -1.2727 + 4 0.7966 0.0073 -1.4660 + 5 0.8946 0.0084 -1.5586 + 6 0.9801 0.0096 -1.6568 + 7 1.0446 0.0105 -1.7694 + 8 1.1065 0.0117 -1.9317 + 9 1.1411 0.0142 -2.0844 + 10 1.1776 0.0175 -2.2415 + 11 1.2014 0.0220 -2.4154 + 12 1.2315 0.0270 -2.6770 + 13 1.2585 0.0329 -2.9389 + 14 1.2967 0.0387 -3.2543 + 15 1.3269 0.0455 -3.5636 + 16 1.3566 0.0529 -3.8959 + 17 1.3838 0.0611 -4.2519 + 19 1.4278 0.0800 -4.9627 + 20 1.4607 0.0886 -5.3962 + 21 1.4730 0.1002 -5.7535 + 22 1.4807 0.1128 -6.1201 + 23 1.4853 0.1259 -6.4786 + 24 1.4917 0.1388 -6.8685 + 25 1.4944 0.1520 -7.2354 + 26 1.4918 0.1657 -7.5648 + 27 1.4848 0.1800 -7.8540 + 28 1.4765 0.1943 -8.1190 + 29 1.4665 0.2087 -8.3538 + 30 1.4537 0.2235 -8.5446 + 40 1.1708 0.4377 -1 + 50 0.9436 0.6674 -1 + 60 0.7169 0.8861 -1 + 70 0.4775 1.0686 -1 + 80 0.2324 1.1945 -1 + 90 0.0000 1.2500 -1 + 100 -0.1627 1.1945 -1 + 110 -0.3342 1.0686 -1 + 120 -0.5018 0.8861 -1 + 130 -0.6605 0.6674 -1 + 140 -0.8196 0.4377 -1 + 150 -1.0176 0.2235 -1 + 160 -0.6784 0.0496 -1 + 170 -0.3392 0.0100 -1 + 180 0.0000 0.0100 -1 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.4065 0.0100 -1 + -160 0.8130 0.0656 -1 + -150 0.9585 0.2382 -1 + -140 0.7836 0.4508 -1 + -130 0.6393 0.6784 -1 + -120 0.4904 0.8946 -1 + -110 0.3293 1.0744 -1 + -100 0.1615 1.1974 -1 + -90 0.0000 1.2500 -1 + -80 -0.1615 1.1974 -1 + -70 -0.3293 1.0744 -1 + -60 -0.4904 0.8946 -1 + -50 -0.6393 0.6784 -1 + -40 -0.7836 0.4508 -1 + -30 -0.9585 0.2382 -1 + -20 -0.8400 0.1070 -1 + -10 -0.6835 0.0136 -2.5481 + -9 -0.6551 0.0110 -2.2945 + -8 -0.5990 0.0100 -2.0149 + -5 -0.2785 0.0079 -1.2051 + -4 -0.1605 0.0074 -1.0146 + -3 -0.0396 0.0070 -0.8858 + -2 0.0815 0.0064 -0.9130 + -1 0.2046 0.0060 -0.9981 + 0 0.3288 0.0059 -1.0898 + 1 0.4505 0.0059 -1.1819 + 2 0.5696 0.0062 -1.2742 + 3 0.6869 0.0066 -1.3692 + 4 0.7958 0.0074 -1.4563 + 6 0.9864 0.0094 -1.6557 + 7 1.0636 0.0101 -1.7862 + 8 1.1217 0.0112 -1.9495 + 9 1.1532 0.0137 -2.0998 + 11 1.2140 0.0213 -2.4399 + 12 1.2522 0.0256 -2.7207 + 13 1.2922 0.0304 -3.0194 + 15 1.3624 0.0423 -3.6630 + 16 1.3922 0.0494 -4.0053 + 17 1.4225 0.0570 -4.3795 + 18 1.4431 0.0660 -4.7296 + 19 1.4663 0.0753 -5.1108 + 20 1.4819 0.0860 -5.4818 + 22 1.4994 0.1103 -6.2066 + 25 1.5113 0.1495 -7.3351 + 26 1.5098 0.1631 -7.6774 + 30 1.3693 0.2382 -6.1797 + 40 1.1195 0.4508 -1 + 50 0.9133 0.6784 -1 + 60 0.7006 0.8946 -1 + 70 0.4705 1.0744 -1 + 80 0.2307 1.1974 -1 + 90 0.0000 1.2500 -1 + 100 -0.1615 1.1974 -1 + 110 -0.3293 1.0744 -1 + 120 -0.4904 0.8946 -1 + 130 -0.6393 0.6784 -1 + 140 -0.7836 0.4508 -1 + 150 -0.9585 0.2382 -1 + 160 -0.8130 0.0656 -1 + 170 -0.4065 0.0100 -1 + 180 0.0000 0.0100 -1 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.3508 0.0100 -1 + -160 0.7017 0.0400 -1 + -150 1.0525 0.2147 -1 + -140 0.8408 0.4299 -1 + -130 0.6731 0.6609 -1 + -120 0.5085 0.8810 -1 + -110 0.3371 1.0651 -1 + -100 0.1634 1.1927 -1 + -90 0.0000 1.2500 -1 + -80 -0.1634 1.1927 -1 + -70 -0.3371 1.0651 -1 + -60 -0.5085 0.8810 -1 + -50 -0.6731 0.6609 -1 + -40 -0.8408 0.4299 -1 + -30 -1.0525 0.2147 -1 + -20 -0.7646 0.1141 -1 + -10 -0.6811 0.0135 -2.5243 + -9 -0.6851 0.0106 -2.3544 + -8 -0.6061 0.0097 -2.0276 + -6 -0.3941 0.0082 -1.4146 + -4 -0.1596 0.0072 -1.0137 + -3 -0.0388 0.0069 -0.8871 + -2 0.0830 0.0064 -0.9138 + -1 0.2067 0.0059 -0.9994 + 0 0.3302 0.0058 -1.0906 + 1 0.4512 0.0059 -1.1825 + 2 0.5700 0.0062 -1.2762 + 4 0.7938 0.0075 -1.4517 + 5 0.8930 0.0085 -1.5475 + 6 0.9896 0.0093 -1.6620 + 7 1.0843 0.0099 -1.8045 + 8 1.1285 0.0111 -1.9571 + 9 1.1695 0.0131 -2.1205 + 10 1.1873 0.0169 -2.2387 + 11 1.2351 0.0201 -2.4820 + 12 1.2707 0.0244 -2.7598 + 13 1.3094 0.0292 -3.0601 + 14 1.3479 0.0345 -3.3831 + 16 1.4132 0.0475 -4.0705 + 17 1.4381 0.0554 -4.4302 + 18 1.4631 0.0639 -4.7988 + 19 1.4825 0.0734 -5.1723 + 20 1.4971 0.0841 -5.5428 + 21 1.5047 0.0960 -5.8916 + 24 1.5435 0.1310 -7.1532 + 25 1.5472 0.1439 -7.5449 + 26 1.5476 0.1572 -7.9128 + 27 1.5436 0.1707 -8.246 + 28 1.5338 0.1849 -8.5292 + 29 1.5197 0.1997 -8.7629 + 30 1.5036 0.2147 -8.9588 + 40 1.2012 0.4299 -1 + 50 0.9615 0.6609 -1 + 60 0.7265 0.8810 -1 + 70 0.4816 1.0651 -1 + 80 0.2334 1.1927 -1 + 90 0.0000 1.2500 -1 + 100 -0.1634 1.1927 -1 + 110 -0.3371 1.0651 -1 + 120 -0.5085 0.8810 -1 + 130 -0.6731 0.6609 -1 + 140 -0.8408 0.4299 -1 + 150 -1.0525 0.2147 -1 + 160 -0.7017 0.0400 -1 + 170 -0.3508 0.0100 -1 + 180 0.0000 0.0100 -1 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.3695 0.0100 -1 + -160 0.7389 0.0433 -1 + -150 1.0447 0.2176 -1 + -140 0.8361 0.4326 -1 + -130 0.6703 0.6631 -1 + -120 0.5070 0.8827 -1 + -110 0.3365 1.0663 -1 + -100 0.1632 1.1933 -1 + -90 0.0000 1.2500 -1 + -80 -0.1632 1.1933 -1 + -70 -0.3365 1.0663 -1 + -60 -0.5070 0.8827 -1 + -50 -0.6703 0.6631 -1 + -40 -0.8361 0.4326 -1 + -30 -1.0447 0.2176 -1 + -20 -0.7942 0.1103 -1 + -10 -0.6944 0.0129 -2.5538 + -7 -0.5051 0.0088 -1.6890 + -6 -0.3931 0.0082 -1.4033 + -5 -0.2781 0.0075 -1.2051 + -4 -0.1595 0.0071 -1.0133 + -3 -0.0379 0.0068 -0.8899 + -2 0.0846 0.0064 -0.9146 + -1 0.2078 0.0058 -1.0002 + 0 0.3310 0.0058 -1.0908 + 1 0.4519 0.0058 -1.1833 + 2 0.5708 0.0061 -1.2722 + 3 0.6863 0.0066 -1.3593 + 4 0.7943 0.0074 -1.4554 + 5 0.8937 0.0084 -1.5503 + 6 0.9965 0.0090 -1.6685 + 7 1.0919 0.0097 -1.8120 + 8 1.1354 0.0109 -1.9652 + 10 1.2027 0.0161 -2.2646 + 11 1.2478 0.0194 -2.5076 + 12 1.2911 0.0232 -2.8034 + 13 1.3319 0.0276 -3.1135 + 14 1.3618 0.0335 -3.4179 + 15 1.3958 0.0395 -3.7559 + 17 1.4529 0.0540 -4.4787 + 18 1.4764 0.0625 -4.8444 + 19 1.4956 0.0720 -5.2221 + 20 1.5053 0.0831 -5.5750 + 22 1.5459 0.1037 -6.4227 + 23 1.5538 0.1161 -6.8324 + 24 1.5595 0.1287 -7.2408 + 25 1.5622 0.1418 -7.6314 + 26 1.5612 0.1552 -7.9964 + 27 1.5539 0.1691 -8.3139 + 28 1.5433 0.1835 -8.595 + 29 1.5306 0.1980 -8.8443 + 30 1.4925 0.2176 -8.363771554 + 40 1.1944 0.4326 -1 + 50 0.9575 0.6631 -1 + 60 0.7243 0.8827 -1 + 70 0.4807 1.0663 -1 + 80 0.2332 1.1933 -1 + 90 0.0000 1.2500 -1 + 100 -0.1632 1.1933 -1 + 110 -0.3365 1.0663 -1 + 120 -0.5070 0.8827 -1 + 130 -0.6703 0.6631 -1 + 140 -0.8361 0.4326 -1 + 150 -1.0447 0.2176 -1 + 160 -0.7389 0.0433 -1 + 170 -0.3695 0.0100 -1 + 180 0.0000 0.0100 -1 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180 0.0000 0.0100 -1 + -170 0.3561 0.0100 -1 + -160 0.7121 0.0361 -1 + -150 1.0682 0.2110 -1 + -140 0.8504 0.4267 -1 + -130 0.6787 0.6582 -1 + -120 0.5115 0.8789 -1 + -110 0.3384 1.0637 -1 + -100 0.1637 1.1919 -1 + -90 0.0000 1.2500 -1 + -80 -0.1637 1.1919 -1 + -70 -0.3384 1.0637 -1 + -60 -0.5115 0.8789 -1 + -50 -0.6787 0.6582 -1 + -40 -0.8504 0.4267 -1 + -30 -1.0682 0.2110 -1 + -20 -0.7818 0.1117 -1 + -10 -0.7078 0.0124 -2.5820 + -9 -0.6882 0.0105 -2.3471 + -8 -0.6127 0.0092 -2.0403 + -6 -0.3930 0.0081 -1.4009 + -5 -0.2780 0.0074 -1.2048 + -4 -0.1594 0.0069 -1.0132 + -3 -0.0371 0.0067 -0.8903 + -2 0.0857 0.0063 -0.9153 + -1 0.2083 0.0058 -1.0004 + 0 0.3320 0.0057 -1.0916 + 1 0.4508 0.0059 -1.1835 + 2 0.5707 0.0061 -1.2714 + 3 0.6849 0.0067 -1.3575 + 5 0.8968 0.0083 -1.5536 + 6 0.9995 0.0090 -1.6719 + 7 1.0994 0.0095 -1.8194 + 8 1.1396 0.0107 -1.9697 + 11 1.2595 0.0188 -2.5308 + 12 1.3027 0.0225 -2.8278 + 14 1.3829 0.0318 -3.4708 + 16 1.4381 0.0453 -4.1475 + 18 1.4876 0.0613 -4.8828 + 21 1.5477 0.0904 -6.0795 + 22 1.5578 0.1021 -6.4768 + 23 1.5668 0.1143 -6.8990 + 24 1.5715 0.1270 -7.3058 + 25 1.5731 0.1402 -7.6939 + 26 1.5686 0.1540 -8.0423 + 27 1.5615 0.1680 -8.3631 + 28 1.5521 0.1821 -8.6566 + 29 1.5406 0.1964 -8.9183 + 30 1.5260 0.2110 -9.1387 + 40 1.2148 0.4267 -1 + 50 0.9696 0.6582 -1 + 60 0.7308 0.8789 -1 + 70 0.4835 1.0637 -1 + 80 0.2339 1.1919 -1 + 90 0.0000 1.2500 -1 + 100 -0.1637 1.1919 -1 + 110 -0.3384 1.0637 -1 + 120 -0.5115 0.8789 -1 + 130 -0.6787 0.6582 -1 + 140 -0.8504 0.4267 -1 + 150 -1.0682 0.2110 -1 + 160 -0.7121 0.0361 -1 + 170 -0.3561 0.0100 -1 + 180 0.0000 0.0100 -1 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0240_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0240_coords.txt new file mode 100644 index 00000000..99568655 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0240_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0240 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.001740 0.009990 + 0.009990 0.025540 + 0.026840 0.043840 + 0.085380 0.081830 + 0.126020 0.098890 + 0.173070 0.113700 + 0.225630 0.125450 + 0.343100 0.136890 + 0.405650 0.135010 + 0.469030 0.128320 + 0.532130 0.117850 + 0.653880 0.089820 + 0.711010 0.074320 + 0.764750 0.059150 + 0.814500 0.045100 + 0.899560 0.022380 + 0.933650 0.014140 + 0.961390 0.007980 + 0.982280 0.002440 + 0.982280 0.001830 + 0.961390 0.002090 + 0.933510 0.000850 + 0.859090 -0.008040 + 0.813820 -0.016050 + 0.764090 -0.026350 + 0.710600 -0.038510 + 0.594970 -0.065500 + 0.534160 -0.078430 + 0.472340 -0.089680 + 0.410300 -0.098140 + 0.289530 -0.102840 + 0.233070 -0.098960 + 0.180640 -0.091900 + 0.133180 -0.082080 + 0.056790 -0.055970 + 0.029750 -0.040380 + 0.011270 -0.024430 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0247.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0247.dat new file mode 100644 index 00000000..116e81c9 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0247.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0247 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0247_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0127 -1.0184 + -170.000 0.3091 0.0127 -1.0184 + -160.000 0.6183 0.0727 -1.0184 + -150.000 0.9274 0.2433 -1.0184 + -140.000 0.7628 0.4535 -1.0184 + -130.000 0.6254 0.6783 -1.0184 + -120.000 0.4816 0.8918 -1.0184 + -110.000 0.3245 1.0691 -1.0184 + -100.000 0.1595 1.1900 -1.0184 + -90.000 0.0000 1.2413 -1.0184 + -80.000 -0.1595 1.1900 -1.0184 + -70.000 -0.3245 1.0691 -1.0184 + -60.000 -0.4816 0.8918 -1.0184 + -50.000 -0.6254 0.6783 -1.0184 + -40.000 -0.7628 0.4535 -1.0184 + -30.000 -0.9274 0.2433 -1.0184 + -20.000 -0.6720 0.1322 -1.0184 + -10.000 -0.5951 0.0209 -2.3716 + -9.000 -0.5650 0.0176 -2.1434 + -8.000 -0.5351 0.0150 -1.9228 + -7.000 -0.4818 0.0138 -1.6688 + -6.000 -0.3875 0.0128 -1.4222 + -5.000 -0.2803 0.0120 -1.2263 + -4.000 -0.1683 0.0113 -1.0428 + -3.000 -0.0542 0.0103 -0.9248 + -2.000 0.0665 0.0101 -0.9240 + -1.000 0.1867 0.0100 -1.0073 + 0.000 0.3064 0.0101 -1.0954 + 1.000 0.4267 0.0101 -1.1863 + 2.000 0.5452 0.0103 -1.2768 + 3.000 0.6616 0.0105 -1.3708 + 4.000 0.7735 0.0109 -1.4655 + 5.000 0.8839 0.0113 -1.5694 + 6.000 0.9739 0.0124 -1.6771 + 7.000 1.0102 0.0141 -1.7583 + 8.000 1.0430 0.0163 -1.8837 + 9.000 1.0831 0.0192 -2.0347 + 10.000 1.1247 0.0226 -2.1924 + 11.000 1.1327 0.0284 -2.3091 + 12.000 1.1622 0.0338 -2.5578 + 13.000 1.1717 0.0416 -2.7695 + 14.000 1.1976 0.0487 -3.0320 + 15.000 1.2159 0.0573 -3.2881 + 16.000 1.2441 0.0656 -3.5904 + 17.000 1.2688 0.0746 -3.9016 + 18.000 1.2917 0.0845 -4.2305 + 19.000 1.3130 0.0949 -4.5598 + 20.000 1.3315 0.1061 -4.8996 + 21.000 1.3488 0.1176 -5.2476 + 22.000 1.3682 0.1287 -5.6212 + 23.000 1.3766 0.1416 -5.9601 + 24.000 1.3832 0.1546 -6.2942 + 25.000 1.3841 0.1681 -6.6093 + 26.000 1.3794 0.1825 -6.8790 + 28.000 1.3547 0.2120 -7.2711 + 29.000 1.3364 0.2285 -7.3706 + 30.000 1.3248 0.2433 -7.4930 + 40.000 1.0898 0.4535 -1.0184 + 50.000 0.8934 0.6783 -1.0184 + 60.000 0.6880 0.8918 -1.0184 + 70.000 0.4635 1.0691 -1.0184 + 80.000 0.2279 1.1900 -1.0184 + 90.000 0.0000 1.2413 -1.0184 + 100.000 -0.1595 1.1900 -1.0184 + 110.000 -0.3245 1.0691 -1.0184 + 120.000 -0.4816 0.8918 -1.0184 + 130.000 -0.6254 0.6783 -1.0184 + 140.000 -0.7628 0.4535 -1.0184 + 150.000 -0.9274 0.2433 -1.0184 + 160.000 -0.6183 0.0727 -1.0184 + 170.000 -0.3091 0.0127 -1.0184 + 180.000 0.0000 0.0127 -1.0184 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0161 -1.0184 + -170.000 0.3240 0.0161 -1.0184 + -160.000 0.6481 0.0643 -1.0184 + -150.000 0.9721 0.2358 -1.0184 + -140.000 0.7901 0.4472 -1.0184 + -130.000 0.6414 0.6736 -1.0184 + -120.000 0.4902 0.8889 -1.0184 + -110.000 0.3281 1.0682 -1.0184 + -100.000 0.1604 1.1913 -1.0184 + -90.000 0.0000 1.2447 -1.0184 + -80.000 -0.1604 1.1913 -1.0184 + -70.000 -0.3281 1.0682 -1.0184 + -60.000 -0.4902 0.8889 -1.0184 + -50.000 -0.6414 0.6736 -1.0184 + -40.000 -0.7901 0.4472 -1.0184 + -30.000 -0.9721 0.2358 -1.0184 + -20.000 -0.7103 0.1287 -1.0184 + -10.000 -0.6407 0.0216 -2.4678 + -9.000 -0.5941 0.0192 -2.1986 + -8.000 -0.5748 0.0172 -1.9910 + -7.000 -0.4904 0.0161 -1.6842 + -6.000 -0.3874 0.0153 -1.4225 + -5.000 -0.2784 0.0146 -1.2245 + -4.000 -0.1624 0.0141 -1.0367 + -3.000 -0.0450 0.0134 -0.9185 + -1.000 0.1964 0.0126 -1.0130 + 0.000 0.3183 0.0125 -1.1029 + 1.000 0.4382 0.0127 -1.1936 + 2.000 0.5593 0.0127 -1.2860 + 5.000 0.8894 0.0144 -1.5722 + 6.000 0.9679 0.0158 -1.6738 + 7.000 1.0216 0.0170 -1.7675 + 9.000 1.1223 0.0207 -2.0830 + 10.000 1.1420 0.0248 -2.2147 + 11.000 1.1764 0.0290 -2.3933 + 12.000 1.1917 0.0350 -2.6199 + 13.000 1.2200 0.0409 -2.8779 + 14.000 1.2485 0.0475 -3.1607 + 15.000 1.2822 0.0542 -3.4675 + 16.000 1.3094 0.0621 -3.7847 + 17.000 1.3374 0.0703 -4.1296 + 18.000 1.3607 0.0795 -4.4731 + 19.000 1.3837 0.0892 -4.8260 + 20.000 1.3985 0.1004 -5.1757 + 21.000 1.4139 0.1118 -5.5324 + 22.000 1.4271 0.1238 -5.9031 + 23.000 1.4316 0.1369 -6.2403 + 24.000 1.4453 0.1485 -6.6498 + 25.000 1.4460 0.1620 -6.9893 + 26.000 1.4467 0.1752 -7.3214 + 27.000 1.4428 0.1890 -7.6156 + 28.000 1.4349 0.2032 -7.8664 + 29.000 1.4050 0.2205 -7.9334 + 30.000 1.3887 0.2358 -8.0633 + 40.000 1.1286 0.4472 -1.0184 + 50.000 0.9164 0.6736 -1.0184 + 60.000 0.7003 0.8889 -1.0184 + 70.000 0.4687 1.0682 -1.0184 + 80.000 0.2292 1.1913 -1.0184 + 90.000 0.0000 1.2447 -1.0184 + 100.000 -0.1604 1.1913 -1.0184 + 110.000 -0.3281 1.0682 -1.0184 + 120.000 -0.4902 0.8889 -1.0184 + 130.000 -0.6414 0.6736 -1.0184 + 140.000 -0.7901 0.4472 -1.0184 + 150.000 -0.9721 0.2358 -1.0184 + 160.000 -0.6481 0.0643 -1.0184 + 170.000 -0.3240 0.0161 -1.0184 + 180.000 0.0000 0.0161 -1.0184 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0164 -1.0184 + -170.000 0.3361 0.0164 -1.0184 + -160.000 0.6722 0.0556 -1.0184 + -150.000 1.0082 0.2279 -1.0184 + -140.000 0.8121 0.4401 -1.0184 + -130.000 0.6544 0.6677 -1.0184 + -120.000 0.4972 0.8844 -1.0184 + -110.000 0.3311 1.0652 -1.0184 + -100.000 0.1612 1.1899 -1.0184 + -90.000 0.0000 1.2449 -1.0184 + -80.000 -0.1612 1.1899 -1.0184 + -70.000 -0.3311 1.0652 -1.0184 + -60.000 -0.4972 0.8844 -1.0184 + -50.000 -0.6544 0.6677 -1.0184 + -40.000 -0.8121 0.4401 -1.0184 + -30.000 -1.0082 0.2279 -1.0184 + -20.000 -0.7376 0.1242 -1.0184 + -10.000 -0.6671 0.0204 -2.5232 + -9.000 -0.6253 0.0182 -2.2561 + -8.000 -0.5854 0.0169 -2.0095 + -7.000 -0.4921 0.0160 -1.6870 + -6.000 -0.3891 0.0152 -1.4250 + -5.000 -0.2763 0.0145 -1.2222 + -4.000 -0.1596 0.0141 -1.0335 + -3.000 -0.0415 0.0136 -0.9164 + -2.000 0.0786 0.0128 -0.9309 + -1.000 0.2006 0.0125 -1.0155 + 0.000 0.3224 0.0125 -1.1052 + 1.000 0.4449 0.0125 -1.1979 + 2.000 0.5630 0.0128 -1.2886 + 4.000 0.7893 0.0137 -1.4801 + 5.000 0.8864 0.0148 -1.5719 + 6.000 0.9711 0.0160 -1.6692 + 7.000 1.0350 0.0169 -1.7807 + 8.000 1.0963 0.0180 -1.9415 + 9.000 1.1306 0.0205 -2.0928 + 10.000 1.1668 0.0238 -2.2485 + 11.000 1.1903 0.0282 -2.4208 + 12.000 1.2202 0.0332 -2.6800 + 13.000 1.2469 0.0390 -2.9395 + 14.000 1.2848 0.0448 -3.2520 + 15.000 1.3147 0.0515 -3.5584 + 16.000 1.3441 0.0589 -3.8876 + 17.000 1.3711 0.0670 -4.2404 + 19.000 1.4146 0.0857 -4.9446 + 20.000 1.4472 0.0942 -5.3741 + 21.000 1.4594 0.1057 -5.7281 + 22.000 1.4671 0.1182 -6.0914 + 23.000 1.4716 0.1312 -6.4466 + 24.000 1.4780 0.1440 -6.8329 + 25.000 1.4806 0.1570 -7.1964 + 26.000 1.4781 0.1706 -7.5228 + 27.000 1.4711 0.1848 -7.8093 + 28.000 1.4629 0.1990 -8.0719 + 29.000 1.4530 0.2132 -8.3045 + 30.000 1.4403 0.2279 -8.4935 + 40.000 1.1600 0.4401 -1.0184 + 50.000 0.9349 0.6677 -1.0184 + 60.000 0.7103 0.8844 -1.0184 + 70.000 0.4731 1.0652 -1.0184 + 80.000 0.2303 1.1899 -1.0184 + 90.000 0.0000 1.2449 -1.0184 + 100.000 -0.1612 1.1899 -1.0184 + 110.000 -0.3311 1.0652 -1.0184 + 120.000 -0.4972 0.8844 -1.0184 + 130.000 -0.6544 0.6677 -1.0184 + 140.000 -0.8121 0.4401 -1.0184 + 150.000 -1.0082 0.2279 -1.0184 + 160.000 -0.6722 0.0556 -1.0184 + 170.000 -0.3361 0.0164 -1.0184 + 180.000 0.0000 0.0164 -1.0184 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0164 -1.0184 + -170.000 0.4028 0.0164 -1.0184 + -160.000 0.8055 0.0714 -1.0184 + -150.000 0.9497 0.2425 -1.0184 + -140.000 0.7764 0.4531 -1.0184 + -130.000 0.6334 0.6786 -1.0184 + -120.000 0.4859 0.8928 -1.0184 + -110.000 0.3263 1.0710 -1.0184 + -100.000 0.1600 1.1928 -1.0184 + -90.000 0.0000 1.2449 -1.0184 + -80.000 -0.1600 1.1928 -1.0184 + -70.000 -0.3263 1.0710 -1.0184 + -60.000 -0.4859 0.8928 -1.0184 + -50.000 -0.6334 0.6786 -1.0184 + -40.000 -0.7764 0.4531 -1.0184 + -30.000 -0.9497 0.2425 -1.0184 + -20.000 -0.8323 0.1125 -1.0184 + -10.000 -0.6772 0.0199 -2.5523 + -9.000 -0.6491 0.0173 -2.3010 + -8.000 -0.5935 0.0164 -2.0240 + -5.000 -0.2759 0.0143 -1.2216 + -4.000 -0.1590 0.0138 -1.0329 + -3.000 -0.0392 0.0134 -0.9053 + -2.000 0.0807 0.0128 -0.9322 + -1.000 0.2027 0.0124 -1.0165 + 0.000 0.3258 0.0123 -1.1074 + 1.000 0.4464 0.0123 -1.1986 + 2.000 0.5644 0.0126 -1.2901 + 3.000 0.6806 0.0130 -1.3842 + 4.000 0.7885 0.0138 -1.4705 + 6.000 0.9773 0.0158 -1.6681 + 7.000 1.0538 0.0165 -1.7974 + 8.000 1.1114 0.0175 -1.9592 + 9.000 1.1426 0.0200 -2.1081 + 11.000 1.2028 0.0276 -2.4451 + 12.000 1.2407 0.0318 -2.7233 + 13.000 1.2803 0.0366 -3.0192 + 15.000 1.3499 0.0484 -3.6569 + 16.000 1.3794 0.0554 -3.9960 + 17.000 1.4094 0.0629 -4.3668 + 18.000 1.4298 0.0718 -4.7137 + 19.000 1.4528 0.0811 -5.0914 + 20.000 1.4683 0.0917 -5.4589 + 22.000 1.4856 0.1157 -6.1771 + 25.000 1.4974 0.1546 -7.2952 + 26.000 1.4959 0.1680 -7.6343 + 30.000 1.3567 0.2425 -6.1504 + 40.000 1.1092 0.4531 -1.0184 + 50.000 0.9049 0.6786 -1.0184 + 60.000 0.6941 0.8928 -1.0184 + 70.000 0.4662 1.0710 -1.0184 + 80.000 0.2286 1.1928 -1.0184 + 90.000 0.0000 1.2449 -1.0184 + 100.000 -0.1600 1.1928 -1.0184 + 110.000 -0.3263 1.0710 -1.0184 + 120.000 -0.4859 0.8928 -1.0184 + 130.000 -0.6334 0.6786 -1.0184 + 140.000 -0.7764 0.4531 -1.0184 + 150.000 -0.9497 0.2425 -1.0184 + 160.000 -0.8055 0.0714 -1.0184 + 170.000 -0.4028 0.0164 -1.0184 + 180.000 0.0000 0.0164 -1.0184 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0164 -1.0184 + -170.000 0.3476 0.0164 -1.0184 + -160.000 0.6952 0.0461 -1.0184 + -150.000 1.0428 0.2192 -1.0184 + -140.000 0.8331 0.4324 -1.0184 + -130.000 0.6669 0.6613 -1.0184 + -120.000 0.5038 0.8793 -1.0184 + -110.000 0.3340 1.0617 -1.0184 + -100.000 0.1619 1.1882 -1.0184 + -90.000 0.0000 1.2449 -1.0184 + -80.000 -0.1619 1.1882 -1.0184 + -70.000 -0.3340 1.0617 -1.0184 + -60.000 -0.5038 0.8793 -1.0184 + -50.000 -0.6669 0.6613 -1.0184 + -40.000 -0.8331 0.4324 -1.0184 + -30.000 -1.0428 0.2192 -1.0184 + -20.000 -0.7576 0.1195 -1.0184 + -10.000 -0.6748 0.0198 -2.5287 + -9.000 -0.6788 0.0169 -2.3603 + -8.000 -0.6005 0.0161 -2.0366 + -6.000 -0.3905 0.0146 -1.4292 + -4.000 -0.1581 0.0136 -1.0320 + -3.000 -0.0384 0.0133 -0.9066 + -2.000 0.0822 0.0128 -0.9330 + -1.000 0.2048 0.0123 -1.0178 + 0.000 0.3272 0.0122 -1.1082 + 1.000 0.4470 0.0123 -1.1992 + 2.000 0.5647 0.0126 -1.2921 + 4.000 0.7865 0.0139 -1.4660 + 5.000 0.8848 0.0149 -1.5609 + 6.000 0.9805 0.0157 -1.6743 + 7.000 1.0743 0.0163 -1.8155 + 8.000 1.1181 0.0174 -1.9667 + 9.000 1.1587 0.0194 -2.1286 + 10.000 1.1764 0.0232 -2.2457 + 11.000 1.2237 0.0264 -2.4868 + 12.000 1.2590 0.0306 -2.7620 + 13.000 1.2973 0.0354 -3.0595 + 14.000 1.3355 0.0406 -3.3796 + 16.000 1.4002 0.0535 -4.0606 + 17.000 1.4249 0.0613 -4.4170 + 18.000 1.4496 0.0698 -4.7822 + 19.000 1.4688 0.0792 -5.1523 + 20.000 1.4833 0.0898 -5.5194 + 21.000 1.4908 0.1016 -5.8650 + 24.000 1.5293 0.1362 -7.1149 + 25.000 1.5329 0.1490 -7.5030 + 26.000 1.5333 0.1622 -7.8676 + 27.000 1.5294 0.1756 -8.1977 + 28.000 1.5197 0.1896 -8.4783 + 29.000 1.5057 0.2043 -8.7098 + 30.000 1.4898 0.2192 -8.9039 + 40.000 1.1901 0.4324 -1.0184 + 50.000 0.9526 0.6613 -1.0184 + 60.000 0.7198 0.8793 -1.0184 + 70.000 0.4772 1.0617 -1.0184 + 80.000 0.2313 1.1882 -1.0184 + 90.000 0.0000 1.2449 -1.0184 + 100.000 -0.1619 1.1882 -1.0184 + 110.000 -0.3340 1.0617 -1.0184 + 120.000 -0.5038 0.8793 -1.0184 + 130.000 -0.6669 0.6613 -1.0184 + 140.000 -0.8331 0.4324 -1.0184 + 150.000 -1.0428 0.2192 -1.0184 + 160.000 -0.6952 0.0461 -1.0184 + 170.000 -0.3476 0.0164 -1.0184 + 180.000 0.0000 0.0164 -1.0184 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0164 -1.0184 + -170.000 0.3661 0.0164 -1.0184 + -160.000 0.7321 0.0493 -1.0184 + -150.000 1.0351 0.2220 -1.0184 + -140.000 0.8284 0.4351 -1.0184 + -130.000 0.6641 0.6634 -1.0184 + -120.000 0.5023 0.8810 -1.0184 + -110.000 0.3334 1.0629 -1.0184 + -100.000 0.1617 1.1888 -1.0184 + -90.000 0.0000 1.2449 -1.0184 + -80.000 -0.1617 1.1888 -1.0184 + -70.000 -0.3334 1.0629 -1.0184 + -60.000 -0.5023 0.8810 -1.0184 + -50.000 -0.6641 0.6634 -1.0184 + -40.000 -0.8284 0.4351 -1.0184 + -30.000 -1.0351 0.2220 -1.0184 + -20.000 -0.7869 0.1157 -1.0184 + -10.000 -0.6880 0.0192 -2.5579 + -7.000 -0.5004 0.0152 -1.7011 + -6.000 -0.3895 0.0146 -1.4180 + -5.000 -0.2755 0.0139 -1.2216 + -4.000 -0.1580 0.0135 -1.0316 + -3.000 -0.0376 0.0132 -0.9093 + -2.000 0.0838 0.0128 -0.9338 + -1.000 0.2059 0.0122 -1.0186 + 0.000 0.3280 0.0122 -1.1084 + 1.000 0.4477 0.0122 -1.2000 + 2.000 0.5655 0.0125 -1.2881 + 3.000 0.6800 0.0130 -1.3744 + 4.000 0.7870 0.0138 -1.4696 + 5.000 0.8855 0.0148 -1.5637 + 6.000 0.9873 0.0154 -1.6808 + 7.000 1.0818 0.0161 -1.8229 + 8.000 1.1249 0.0172 -1.9747 + 10.000 1.1916 0.0224 -2.2714 + 11.000 1.2363 0.0257 -2.5121 + 12.000 1.2792 0.0294 -2.8052 + 13.000 1.3196 0.0338 -3.1125 + 14.000 1.3493 0.0396 -3.4141 + 15.000 1.3829 0.0456 -3.7489 + 17.000 1.4395 0.0600 -4.4651 + 18.000 1.4628 0.0684 -4.8274 + 19.000 1.4818 0.0778 -5.2016 + 20.000 1.4914 0.0888 -5.5513 + 22.000 1.5317 0.1092 -6.3912 + 23.000 1.5395 0.1215 -6.7971 + 24.000 1.5451 0.1340 -7.2017 + 25.000 1.5478 0.1469 -7.5887 + 26.000 1.5468 0.1602 -7.9504 + 27.000 1.5396 0.1740 -8.2650 + 28.000 1.5291 0.1883 -8.5435 + 29.000 1.5165 0.2026 -8.7905 + 30.000 1.4788 0.2220 -8.3144 + 40.000 1.1834 0.4351 -1.0184 + 50.000 0.9487 0.6634 -1.0184 + 60.000 0.7176 0.8810 -1.0184 + 70.000 0.4763 1.0629 -1.0184 + 80.000 0.2311 1.1888 -1.0184 + 90.000 0.0000 1.2449 -1.0184 + 100.000 -0.1617 1.1888 -1.0184 + 110.000 -0.3334 1.0629 -1.0184 + 120.000 -0.5023 0.8810 -1.0184 + 130.000 -0.6641 0.6634 -1.0184 + 140.000 -0.8284 0.4351 -1.0184 + 150.000 -1.0351 0.2220 -1.0184 + 160.000 -0.7321 0.0493 -1.0184 + 170.000 -0.3661 0.0164 -1.0184 + 180.000 0.0000 0.0164 -1.0184 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0164 -1.0184 + -170.000 0.3528 0.0164 -1.0184 + -160.000 0.7055 0.0422 -1.0184 + -150.000 1.0584 0.2155 -1.0184 + -140.000 0.8426 0.4292 -1.0184 + -130.000 0.6724 0.6586 -1.0184 + -120.000 0.5068 0.8773 -1.0184 + -110.000 0.3353 1.0604 -1.0184 + -100.000 0.1622 1.1874 -1.0184 + -90.000 0.0000 1.2449 -1.0184 + -80.000 -0.1622 1.1874 -1.0184 + -70.000 -0.3353 1.0604 -1.0184 + -60.000 -0.5068 0.8773 -1.0184 + -50.000 -0.6724 0.6586 -1.0184 + -40.000 -0.8426 0.4292 -1.0184 + -30.000 -1.0584 0.2155 -1.0184 + -20.000 -0.7746 0.1171 -1.0184 + -10.000 -0.7013 0.0187 -2.5858 + -9.000 -0.6819 0.0169 -2.3531 + -8.000 -0.6071 0.0156 -2.0491 + -6.000 -0.3894 0.0145 -1.4156 + -5.000 -0.2754 0.0138 -1.2213 + -4.000 -0.1579 0.0133 -1.0315 + -3.000 -0.0368 0.0131 -0.9097 + -2.000 0.0849 0.0127 -0.9345 + -1.000 0.2064 0.0122 -1.0188 + 0.000 0.3289 0.0121 -1.1092 + 1.000 0.4466 0.0123 -1.2002 + 2.000 0.5654 0.0125 -1.2873 + 3.000 0.6786 0.0131 -1.3726 + 5.000 0.8885 0.0147 -1.5669 + 6.000 0.9903 0.0154 -1.6841 + 7.000 1.0893 0.0159 -1.8303 + 8.000 1.1291 0.0170 -1.9792 + 11.000 1.2479 0.0251 -2.5351 + 12.000 1.2907 0.0287 -2.8294 + 14.000 1.3702 0.0380 -3.4665 + 16.000 1.4249 0.0513 -4.1369 + 18.000 1.4739 0.0672 -4.8655 + 21.000 1.5334 0.0960 -6.0511 + 22.000 1.5435 0.1076 -6.4448 + 23.000 1.5524 0.1197 -6.8631 + 24.000 1.5570 0.1323 -7.2661 + 25.000 1.5586 0.1454 -7.6507 + 26.000 1.5542 0.1590 -7.9959 + 27.000 1.5471 0.1729 -8.3137 + 28.000 1.5378 0.1869 -8.6045 + 29.000 1.5264 0.2010 -8.8638 + 30.000 1.5119 0.2155 -9.0822 + 40.000 1.2036 0.4292 -1.0184 + 50.000 0.9607 0.6586 -1.0184 + 60.000 0.7241 0.8773 -1.0184 + 70.000 0.4790 1.0604 -1.0184 + 80.000 0.2317 1.1874 -1.0184 + 90.000 0.0000 1.2449 -1.0184 + 100.000 -0.1622 1.1874 -1.0184 + 110.000 -0.3353 1.0604 -1.0184 + 120.000 -0.5068 0.8773 -1.0184 + 130.000 -0.6724 0.6586 -1.0184 + 140.000 -0.8426 0.4292 -1.0184 + 150.000 -1.0584 0.2155 -1.0184 + 160.000 -0.7055 0.0422 -1.0184 + 170.000 -0.3528 0.0164 -1.0184 + 180.000 0.0000 0.0164 -1.0184 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0247_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0247_coords.txt new file mode 100644 index 00000000..76becdc1 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0247_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0247 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.021573 + 0.027091 0.045571 + 0.060263 0.070519 + 0.105430 0.093593 + 0.161359 0.113695 + 0.226526 0.129332 + 0.299152 0.139084 + 0.377257 0.140958 + 0.458710 0.134375 + 0.541290 0.120926 + 0.622743 0.102688 + 0.700848 0.081979 + 0.773474 0.061268 + 0.838641 0.042604 + 0.894570 0.027238 + 0.939737 0.015604 + 0.972909 0.007552 + 0.993181 0.002511 + 1.000000 0.000000 + 0.993181 -0.000009 + 0.972909 0.000021 + 0.939737 -0.001786 + 0.894570 -0.006851 + 0.838641 -0.015998 + 0.773474 -0.029320 + 0.700848 -0.046093 + 0.622743 -0.064559 + 0.541290 -0.082348 + 0.458710 -0.096978 + 0.377257 -0.106009 + 0.299152 -0.107583 + 0.226526 -0.102345 + 0.161359 -0.091881 + 0.105430 -0.077436 + 0.060263 -0.059906 + 0.027091 -0.040088 + 0.006819 -0.019333 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0259.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0259.dat new file mode 100644 index 00000000..2122f139 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0259.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0259 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0259_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0173 -1.0500 + -170.000 0.3042 0.0173 -1.0500 + -160.000 0.6084 0.0763 -1.0500 + -150.000 0.9126 0.2442 -1.0500 + -140.000 0.7507 0.4510 -1.0500 + -130.000 0.6154 0.6723 -1.0500 + -120.000 0.4739 0.8824 -1.0500 + -110.000 0.3193 1.0569 -1.0500 + -100.000 0.1570 1.1758 -1.0500 + -90.000 0.0000 1.2263 -1.0500 + -80.000 -0.1570 1.1758 -1.0500 + -70.000 -0.3193 1.0569 -1.0500 + -60.000 -0.4739 0.8824 -1.0500 + -50.000 -0.6154 0.6723 -1.0500 + -40.000 -0.7507 0.4510 -1.0500 + -30.000 -0.9126 0.2442 -1.0500 + -20.000 -0.6612 0.1348 -1.0500 + -10.000 -0.5856 0.0253 -2.3817 + -9.000 -0.5560 0.0221 -2.1570 + -8.000 -0.5266 0.0196 -1.9400 + -7.000 -0.4741 0.0183 -1.6900 + -6.000 -0.3813 0.0173 -1.4473 + -5.000 -0.2758 0.0166 -1.2546 + -4.000 -0.1657 0.0159 -1.0740 + -3.000 -0.0533 0.0149 -0.9579 + -2.000 0.0654 0.0147 -0.9571 + -1.000 0.1837 0.0146 -1.0391 + 0.000 0.3015 0.0147 -1.1258 + 1.000 0.4199 0.0147 -1.2152 + 2.000 0.5365 0.0149 -1.3043 + 3.000 0.6510 0.0151 -1.3968 + 4.000 0.7612 0.0155 -1.4899 + 5.000 0.8698 0.0159 -1.5922 + 6.000 0.9584 0.0170 -1.6982 + 7.000 0.9941 0.0186 -1.7781 + 8.000 1.0264 0.0209 -1.9015 + 9.000 1.0659 0.0237 -2.0501 + 10.000 1.1068 0.0270 -2.2053 + 11.000 1.1146 0.0328 -2.3201 + 12.000 1.1437 0.0380 -2.5649 + 13.000 1.1530 0.0457 -2.7732 + 14.000 1.1785 0.0527 -3.0315 + 15.000 1.1965 0.0611 -3.2835 + 16.000 1.2243 0.0693 -3.5810 + 17.000 1.2486 0.0782 -3.8873 + 18.000 1.2711 0.0879 -4.2109 + 19.000 1.2921 0.0982 -4.5349 + 20.000 1.3103 0.1092 -4.8694 + 21.000 1.3273 0.1205 -5.2118 + 22.000 1.3464 0.1314 -5.5795 + 23.000 1.3547 0.1441 -5.9129 + 24.000 1.3612 0.1569 -6.2417 + 25.000 1.3621 0.1702 -6.5518 + 26.000 1.3574 0.1844 -6.8172 + 28.000 1.3331 0.2134 -7.2030 + 29.000 1.3151 0.2296 -7.3009 + 30.000 1.3037 0.2442 -7.4214 + 40.000 1.0724 0.4510 -1.0500 + 50.000 0.8792 0.6723 -1.0500 + 60.000 0.6770 0.8824 -1.0500 + 70.000 0.4561 1.0569 -1.0500 + 80.000 0.2243 1.1758 -1.0500 + 90.000 0.0000 1.2263 -1.0500 + 100.000 -0.1570 1.1758 -1.0500 + 110.000 -0.3193 1.0569 -1.0500 + 120.000 -0.4739 0.8824 -1.0500 + 130.000 -0.6154 0.6723 -1.0500 + 140.000 -0.7507 0.4510 -1.0500 + 150.000 -0.9126 0.2442 -1.0500 + 160.000 -0.6084 0.0763 -1.0500 + 170.000 -0.3042 0.0173 -1.0500 + 180.000 0.0000 0.0173 -1.0500 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0265 -1.0500 + -170.000 0.3188 0.0265 -1.0500 + -160.000 0.6377 0.0740 -1.0500 + -150.000 0.9566 0.2428 -1.0500 + -140.000 0.7775 0.4507 -1.0500 + -130.000 0.6312 0.6735 -1.0500 + -120.000 0.4824 0.8854 -1.0500 + -110.000 0.3229 1.0619 -1.0500 + -100.000 0.1579 1.1829 -1.0500 + -90.000 0.0000 1.2355 -1.0500 + -80.000 -0.1579 1.1829 -1.0500 + -70.000 -0.3229 1.0619 -1.0500 + -60.000 -0.4824 0.8854 -1.0500 + -50.000 -0.6312 0.6735 -1.0500 + -40.000 -0.7775 0.4507 -1.0500 + -30.000 -0.9566 0.2428 -1.0500 + -20.000 -0.6990 0.1374 -1.0500 + -10.000 -0.6305 0.0320 -2.4763 + -9.000 -0.5846 0.0296 -2.2114 + -8.000 -0.5656 0.0276 -2.0071 + -7.000 -0.4826 0.0265 -1.7052 + -6.000 -0.3812 0.0257 -1.4476 + -5.000 -0.2740 0.0250 -1.2528 + -4.000 -0.1598 0.0246 -1.0679 + -3.000 -0.0443 0.0239 -0.9516 + -1.000 0.1932 0.0231 -1.0446 + 0.000 0.3133 0.0230 -1.1332 + 1.000 0.4312 0.0232 -1.2224 + 2.000 0.5504 0.0232 -1.3133 + 5.000 0.8753 0.0248 -1.5949 + 6.000 0.9525 0.0262 -1.6950 + 7.000 1.0053 0.0274 -1.7871 + 9.000 1.1044 0.0311 -2.0976 + 10.000 1.1238 0.0351 -2.2272 + 11.000 1.1576 0.0392 -2.4030 + 12.000 1.1727 0.0451 -2.6260 + 13.000 1.2005 0.0510 -2.8799 + 14.000 1.2286 0.0574 -3.1581 + 15.000 1.2617 0.0640 -3.4600 + 16.000 1.2886 0.0717 -3.7722 + 17.000 1.3161 0.0798 -4.1116 + 18.000 1.3390 0.0889 -4.4496 + 19.000 1.3617 0.0985 -4.7969 + 20.000 1.3762 0.1095 -5.1410 + 21.000 1.3913 0.1207 -5.4920 + 22.000 1.4044 0.1325 -5.8568 + 23.000 1.4088 0.1454 -6.1886 + 24.000 1.4222 0.1569 -6.5916 + 25.000 1.4229 0.1701 -6.9257 + 26.000 1.4236 0.1831 -7.2526 + 27.000 1.4198 0.1966 -7.5420 + 28.000 1.4120 0.2107 -7.7888 + 29.000 1.3826 0.2276 -7.8548 + 30.000 1.3666 0.2428 -7.9826 + 40.000 1.1106 0.4507 -1.0500 + 50.000 0.9018 0.6735 -1.0500 + 60.000 0.6891 0.8854 -1.0500 + 70.000 0.4613 1.0619 -1.0500 + 80.000 0.2255 1.1829 -1.0500 + 90.000 0.0000 1.2355 -1.0500 + 100.000 -0.1579 1.1829 -1.0500 + 110.000 -0.3229 1.0619 -1.0500 + 120.000 -0.4824 0.8854 -1.0500 + 130.000 -0.6312 0.6735 -1.0500 + 140.000 -0.7775 0.4507 -1.0500 + 150.000 -0.9566 0.2428 -1.0500 + 160.000 -0.6377 0.0740 -1.0500 + 170.000 -0.3188 0.0265 -1.0500 + 180.000 0.0000 0.0265 -1.0500 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0273 -1.0500 + -170.000 0.3307 0.0273 -1.0500 + -160.000 0.6614 0.0659 -1.0500 + -150.000 0.9922 0.2354 -1.0500 + -140.000 0.7991 0.4443 -1.0500 + -130.000 0.6440 0.6682 -1.0500 + -120.000 0.4893 0.8814 -1.0500 + -110.000 0.3258 1.0594 -1.0500 + -100.000 0.1586 1.1821 -1.0500 + -90.000 0.0000 1.2363 -1.0500 + -80.000 -0.1586 1.1821 -1.0500 + -70.000 -0.3258 1.0594 -1.0500 + -60.000 -0.4893 0.8814 -1.0500 + -50.000 -0.6440 0.6682 -1.0500 + -40.000 -0.7991 0.4443 -1.0500 + -30.000 -0.9922 0.2354 -1.0500 + -20.000 -0.7259 0.1333 -1.0500 + -10.000 -0.6565 0.0312 -2.5308 + -9.000 -0.6153 0.0291 -2.2680 + -8.000 -0.5760 0.0277 -2.0253 + -7.000 -0.4843 0.0269 -1.7079 + -6.000 -0.3829 0.0261 -1.4501 + -5.000 -0.2719 0.0254 -1.2506 + -4.000 -0.1571 0.0250 -1.0648 + -3.000 -0.0409 0.0245 -0.9496 + -2.000 0.0773 0.0237 -0.9639 + -1.000 0.1974 0.0234 -1.0472 + 0.000 0.3173 0.0234 -1.1354 + 1.000 0.4378 0.0234 -1.2266 + 2.000 0.5540 0.0237 -1.3159 + 4.000 0.7767 0.0246 -1.5044 + 5.000 0.8722 0.0257 -1.5946 + 6.000 0.9556 0.0269 -1.6904 + 7.000 1.0185 0.0277 -1.8002 + 8.000 1.0788 0.0289 -1.9584 + 9.000 1.1126 0.0313 -2.1073 + 10.000 1.1482 0.0346 -2.2605 + 11.000 1.1714 0.0390 -2.4300 + 12.000 1.2007 0.0438 -2.6851 + 13.000 1.2270 0.0496 -2.9404 + 14.000 1.2643 0.0552 -3.2479 + 15.000 1.2937 0.0619 -3.5495 + 16.000 1.3227 0.0691 -3.8735 + 17.000 1.3492 0.0771 -4.2206 + 19.000 1.3921 0.0955 -4.9136 + 20.000 1.4242 0.1039 -5.3363 + 21.000 1.4362 0.1152 -5.6847 + 22.000 1.4437 0.1275 -6.0421 + 23.000 1.4482 0.1403 -6.3916 + 24.000 1.4544 0.1528 -6.7718 + 25.000 1.4570 0.1657 -7.1295 + 26.000 1.4545 0.1791 -7.4507 + 27.000 1.4477 0.1930 -7.7327 + 28.000 1.4396 0.2069 -7.9910 + 29.000 1.4298 0.2210 -8.2200 + 30.000 1.4174 0.2354 -8.4060 + 40.000 1.1415 0.4443 -1.0500 + 50.000 0.9200 0.6682 -1.0500 + 60.000 0.6990 0.8814 -1.0500 + 70.000 0.4656 1.0594 -1.0500 + 80.000 0.2266 1.1821 -1.0500 + 90.000 0.0000 1.2363 -1.0500 + 100.000 -0.1586 1.1821 -1.0500 + 110.000 -0.3258 1.0594 -1.0500 + 120.000 -0.4893 0.8814 -1.0500 + 130.000 -0.6440 0.6682 -1.0500 + 140.000 -0.7991 0.4443 -1.0500 + 150.000 -0.9922 0.2354 -1.0500 + 160.000 -0.6614 0.0659 -1.0500 + 170.000 -0.3307 0.0273 -1.0500 + 180.000 0.0000 0.0273 -1.0500 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0273 -1.0500 + -170.000 0.3963 0.0273 -1.0500 + -160.000 0.7927 0.0815 -1.0500 + -150.000 0.9345 0.2497 -1.0500 + -140.000 0.7640 0.4570 -1.0500 + -130.000 0.6233 0.6789 -1.0500 + -120.000 0.4781 0.8897 -1.0500 + -110.000 0.3211 1.0650 -1.0500 + -100.000 0.1575 1.1850 -1.0500 + -90.000 0.0000 1.2363 -1.0500 + -80.000 -0.1575 1.1850 -1.0500 + -70.000 -0.3211 1.0650 -1.0500 + -60.000 -0.4781 0.8897 -1.0500 + -50.000 -0.6233 0.6789 -1.0500 + -40.000 -0.7640 0.4570 -1.0500 + -30.000 -0.9345 0.2497 -1.0500 + -20.000 -0.8190 0.1218 -1.0500 + -10.000 -0.6664 0.0308 -2.5594 + -9.000 -0.6387 0.0282 -2.3121 + -8.000 -0.5840 0.0273 -2.0395 + -5.000 -0.2715 0.0252 -1.2500 + -4.000 -0.1565 0.0247 -1.0642 + -3.000 -0.0386 0.0243 -0.9387 + -2.000 0.0795 0.0237 -0.9652 + -1.000 0.1995 0.0234 -1.0481 + 0.000 0.3206 0.0233 -1.1376 + 1.000 0.4392 0.0233 -1.2274 + 2.000 0.5554 0.0235 -1.3173 + 3.000 0.6697 0.0239 -1.4100 + 4.000 0.7759 0.0247 -1.4949 + 6.000 0.9617 0.0267 -1.6893 + 7.000 1.0370 0.0273 -1.8165 + 8.000 1.0937 0.0284 -1.9758 + 9.000 1.1244 0.0309 -2.1223 + 11.000 1.1836 0.0383 -2.4539 + 12.000 1.2209 0.0425 -2.7277 + 13.000 1.2599 0.0471 -3.0189 + 15.000 1.3283 0.0587 -3.6464 + 16.000 1.3574 0.0657 -3.9802 + 17.000 1.3869 0.0731 -4.3450 + 18.000 1.4070 0.0819 -4.6864 + 19.000 1.4296 0.0909 -5.0580 + 20.000 1.4449 0.1014 -5.4198 + 22.000 1.4619 0.1250 -6.1264 + 25.000 1.4735 0.1633 -7.2267 + 26.000 1.4721 0.1765 -7.5605 + 30.000 1.3351 0.2497 -6.1002 + 40.000 1.0915 0.4570 -1.0500 + 50.000 0.8905 0.6789 -1.0500 + 60.000 0.6831 0.8897 -1.0500 + 70.000 0.4587 1.0650 -1.0500 + 80.000 0.2249 1.1850 -1.0500 + 90.000 0.0000 1.2363 -1.0500 + 100.000 -0.1575 1.1850 -1.0500 + 110.000 -0.3211 1.0650 -1.0500 + 120.000 -0.4781 0.8897 -1.0500 + 130.000 -0.6233 0.6789 -1.0500 + 140.000 -0.7640 0.4570 -1.0500 + 150.000 -0.9345 0.2497 -1.0500 + 160.000 -0.7927 0.0815 -1.0500 + 170.000 -0.3963 0.0273 -1.0500 + 180.000 0.0000 0.0273 -1.0500 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0273 -1.0500 + -170.000 0.3420 0.0273 -1.0500 + -160.000 0.6842 0.0565 -1.0500 + -150.000 1.0262 0.2268 -1.0500 + -140.000 0.8198 0.4367 -1.0500 + -130.000 0.6563 0.6619 -1.0500 + -120.000 0.4958 0.8765 -1.0500 + -110.000 0.3287 1.0560 -1.0500 + -100.000 0.1593 1.1804 -1.0500 + -90.000 0.0000 1.2363 -1.0500 + -80.000 -0.1593 1.1804 -1.0500 + -70.000 -0.3287 1.0560 -1.0500 + -60.000 -0.4958 0.8765 -1.0500 + -50.000 -0.6563 0.6619 -1.0500 + -40.000 -0.8198 0.4367 -1.0500 + -30.000 -1.0262 0.2268 -1.0500 + -20.000 -0.7455 0.1287 -1.0500 + -10.000 -0.6641 0.0307 -2.5362 + -9.000 -0.6680 0.0278 -2.3705 + -8.000 -0.5909 0.0270 -2.0519 + -6.000 -0.3842 0.0255 -1.4542 + -4.000 -0.1556 0.0245 -1.0634 + -3.000 -0.0378 0.0242 -0.9399 + -2.000 0.0809 0.0237 -0.9660 + -1.000 0.2015 0.0233 -1.0494 + 0.000 0.3219 0.0232 -1.1383 + 1.000 0.4399 0.0233 -1.2279 + 2.000 0.5557 0.0235 -1.3193 + 4.000 0.7740 0.0248 -1.4904 + 5.000 0.8707 0.0258 -1.5838 + 6.000 0.9649 0.0266 -1.6955 + 7.000 1.0572 0.0272 -1.8344 + 8.000 1.1003 0.0283 -1.9832 + 9.000 1.1403 0.0303 -2.1425 + 10.000 1.1576 0.0340 -2.2577 + 11.000 1.2042 0.0371 -2.4950 + 12.000 1.2389 0.0413 -2.7658 + 13.000 1.2767 0.0460 -3.0586 + 14.000 1.3142 0.0511 -3.3735 + 16.000 1.3779 0.0638 -4.0437 + 17.000 1.4021 0.0715 -4.3944 + 18.000 1.4265 0.0798 -4.7538 + 19.000 1.4454 0.0891 -5.1180 + 20.000 1.4597 0.0995 -5.4792 + 21.000 1.4671 0.1111 -5.8193 + 24.000 1.5049 0.1452 -7.0494 + 25.000 1.5085 0.1578 -7.4313 + 26.000 1.5089 0.1708 -7.7900 + 27.000 1.5050 0.1839 -8.1148 + 28.000 1.4955 0.1978 -8.3910 + 29.000 1.4817 0.2122 -8.6188 + 30.000 1.4660 0.2268 -8.8098 + 40.000 1.1712 0.4367 -1.0500 + 50.000 0.9375 0.6619 -1.0500 + 60.000 0.7083 0.8765 -1.0500 + 70.000 0.4696 1.0560 -1.0500 + 80.000 0.2276 1.1804 -1.0500 + 90.000 0.0000 1.2363 -1.0500 + 100.000 -0.1593 1.1804 -1.0500 + 110.000 -0.3287 1.0560 -1.0500 + 120.000 -0.4958 0.8765 -1.0500 + 130.000 -0.6563 0.6619 -1.0500 + 140.000 -0.8198 0.4367 -1.0500 + 150.000 -1.0262 0.2268 -1.0500 + 160.000 -0.6842 0.0565 -1.0500 + 170.000 -0.3420 0.0273 -1.0500 + 180.000 0.0000 0.0273 -1.0500 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0273 -1.0500 + -170.000 0.3603 0.0273 -1.0500 + -160.000 0.7204 0.0597 -1.0500 + -150.000 1.0186 0.2297 -1.0500 + -140.000 0.8152 0.4393 -1.0500 + -130.000 0.6535 0.6640 -1.0500 + -120.000 0.4943 0.8781 -1.0500 + -110.000 0.3281 1.0571 -1.0500 + -100.000 0.1591 1.1810 -1.0500 + -90.000 0.0000 1.2363 -1.0500 + -80.000 -0.1591 1.1810 -1.0500 + -70.000 -0.3281 1.0571 -1.0500 + -60.000 -0.4943 0.8781 -1.0500 + -50.000 -0.6535 0.6640 -1.0500 + -40.000 -0.8152 0.4393 -1.0500 + -30.000 -1.0186 0.2297 -1.0500 + -20.000 -0.7743 0.1250 -1.0500 + -10.000 -0.6770 0.0301 -2.5650 + -7.000 -0.4925 0.0261 -1.7218 + -6.000 -0.3833 0.0255 -1.4432 + -5.000 -0.2711 0.0248 -1.2500 + -4.000 -0.1555 0.0244 -1.0630 + -3.000 -0.0370 0.0241 -0.9427 + -2.000 0.0825 0.0237 -0.9667 + -1.000 0.2026 0.0232 -1.0502 + 0.000 0.3227 0.0232 -1.1385 + 1.000 0.4406 0.0232 -1.2287 + 2.000 0.5565 0.0234 -1.3154 + 3.000 0.6691 0.0239 -1.4003 + 4.000 0.7744 0.0247 -1.4940 + 5.000 0.8714 0.0257 -1.5865 + 6.000 0.9716 0.0263 -1.7018 + 7.000 1.0646 0.0270 -1.8417 + 8.000 1.1070 0.0281 -1.9911 + 10.000 1.1726 0.0332 -2.2830 + 11.000 1.2166 0.0364 -2.5199 + 12.000 1.2588 0.0401 -2.8083 + 13.000 1.2986 0.0444 -3.1107 + 14.000 1.3278 0.0502 -3.4075 + 15.000 1.3609 0.0560 -3.7370 + 17.000 1.4166 0.0702 -4.4417 + 18.000 1.4395 0.0784 -4.7983 + 19.000 1.4582 0.0877 -5.1665 + 20.000 1.4677 0.0985 -5.5106 + 22.000 1.5073 0.1186 -6.3371 + 23.000 1.5150 0.1307 -6.7366 + 24.000 1.5205 0.1430 -7.1348 + 25.000 1.5231 0.1558 -7.5156 + 26.000 1.5222 0.1688 -7.8715 + 27.000 1.5151 0.1824 -8.1811 + 28.000 1.5047 0.1964 -8.4551 + 29.000 1.4923 0.2106 -8.6982 + 30.000 1.4552 0.2297 -8.2297 + 40.000 1.1645 0.4393 -1.0500 + 50.000 0.9336 0.6640 -1.0500 + 60.000 0.7062 0.8781 -1.0500 + 70.000 0.4687 1.0571 -1.0500 + 80.000 0.2274 1.1810 -1.0500 + 90.000 0.0000 1.2363 -1.0500 + 100.000 -0.1591 1.1810 -1.0500 + 110.000 -0.3281 1.0571 -1.0500 + 120.000 -0.4943 0.8781 -1.0500 + 130.000 -0.6535 0.6640 -1.0500 + 140.000 -0.8152 0.4393 -1.0500 + 150.000 -1.0186 0.2297 -1.0500 + 160.000 -0.7204 0.0597 -1.0500 + 170.000 -0.3603 0.0273 -1.0500 + 180.000 0.0000 0.0273 -1.0500 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0273 -1.0500 + -170.000 0.3472 0.0273 -1.0500 + -160.000 0.6943 0.0527 -1.0500 + -150.000 1.0415 0.2232 -1.0500 + -140.000 0.8291 0.4335 -1.0500 + -130.000 0.6617 0.6592 -1.0500 + -120.000 0.4987 0.8744 -1.0500 + -110.000 0.3299 1.0546 -1.0500 + -100.000 0.1596 1.1796 -1.0500 + -90.000 0.0000 1.2363 -1.0500 + -80.000 -0.1596 1.1796 -1.0500 + -70.000 -0.3299 1.0546 -1.0500 + -60.000 -0.4987 0.8744 -1.0500 + -50.000 -0.6617 0.6592 -1.0500 + -40.000 -0.8291 0.4335 -1.0500 + -30.000 -1.0415 0.2232 -1.0500 + -20.000 -0.7623 0.1264 -1.0500 + -10.000 -0.6901 0.0296 -2.5924 + -9.000 -0.6710 0.0277 -2.3634 + -8.000 -0.5974 0.0265 -2.0643 + -6.000 -0.3832 0.0254 -1.4409 + -5.000 -0.2711 0.0247 -1.2497 + -4.000 -0.1554 0.0242 -1.0629 + -3.000 -0.0362 0.0240 -0.9430 + -2.000 0.0836 0.0236 -0.9674 + -1.000 0.2031 0.0232 -1.0504 + 0.000 0.3237 0.0231 -1.1393 + 1.000 0.4395 0.0233 -1.2289 + 2.000 0.5564 0.0234 -1.3146 + 3.000 0.6678 0.0240 -1.3986 + 5.000 0.8744 0.0256 -1.5898 + 6.000 0.9745 0.0263 -1.7051 + 7.000 1.0719 0.0268 -1.8489 + 8.000 1.1111 0.0279 -1.9955 + 11.000 1.2280 0.0358 -2.5425 + 12.000 1.2701 0.0394 -2.8321 + 14.000 1.3483 0.0485 -3.4590 + 16.000 1.4021 0.0617 -4.1188 + 18.000 1.4504 0.0773 -4.8357 + 21.000 1.5090 0.1056 -6.0025 + 22.000 1.5189 0.1170 -6.3899 + 23.000 1.5276 0.1289 -6.8015 + 24.000 1.5322 0.1413 -7.1982 + 25.000 1.5338 0.1542 -7.5766 + 26.000 1.5294 0.1677 -7.9162 + 27.000 1.5225 0.1813 -8.2290 + 28.000 1.5133 0.1950 -8.5152 + 29.000 1.5021 0.2090 -8.7703 + 30.000 1.4878 0.2232 -8.9852 + 40.000 1.1844 0.4335 -1.0500 + 50.000 0.9454 0.6592 -1.0500 + 60.000 0.7125 0.8744 -1.0500 + 70.000 0.4714 1.0546 -1.0500 + 80.000 0.2281 1.1796 -1.0500 + 90.000 0.0000 1.2363 -1.0500 + 100.000 -0.1596 1.1796 -1.0500 + 110.000 -0.3299 1.0546 -1.0500 + 120.000 -0.4987 0.8744 -1.0500 + 130.000 -0.6617 0.6592 -1.0500 + 140.000 -0.8291 0.4335 -1.0500 + 150.000 -1.0415 0.2232 -1.0500 + 160.000 -0.6943 0.0527 -1.0500 + 170.000 -0.3472 0.0273 -1.0500 + 180.000 0.0000 0.0273 -1.0500 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0259_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0259_coords.txt new file mode 100644 index 00000000..94bdcf9e --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0259_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0259 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.022584 + 0.027091 0.047510 + 0.060263 0.073301 + 0.105430 0.097140 + 0.161359 0.117917 + 0.226526 0.134137 + 0.299152 0.144379 + 0.377257 0.146668 + 0.458710 0.140419 + 0.541290 0.127194 + 0.622743 0.109034 + 0.700848 0.088223 + 0.773474 0.067204 + 0.838641 0.048007 + 0.894570 0.031887 + 0.939737 0.019298 + 0.972909 0.010124 + 0.993181 0.003839 + 1.000000 0.000000 + 0.993181 -0.001378 + 0.972909 -0.002676 + 0.939737 -0.005710 + 0.894570 -0.011838 + 0.838641 -0.021843 + 0.773474 -0.035786 + 0.700848 -0.052933 + 0.622743 -0.071538 + 0.541290 -0.089257 + 0.458710 -0.103644 + 0.377257 -0.112299 + 0.299152 -0.113402 + 0.226526 -0.107598 + 0.161359 -0.096465 + 0.105430 -0.081252 + 0.060263 -0.062864 + 0.027091 -0.042119 + 0.006819 -0.020381 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0276.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0276.dat new file mode 100644 index 00000000..05644926 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0276.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0276 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0276_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0237 -1.0947 + -170.000 0.2972 0.0237 -1.0947 + -160.000 0.5944 0.0815 -1.0947 + -150.000 0.8917 0.2455 -1.0947 + -140.000 0.7334 0.4476 -1.0947 + -130.000 0.6013 0.6637 -1.0947 + -120.000 0.4631 0.8690 -1.0947 + -110.000 0.3120 1.0395 -1.0947 + -100.000 0.1534 1.1557 -1.0947 + -90.000 0.0000 1.2050 -1.0947 + -80.000 -0.1534 1.1557 -1.0947 + -70.000 -0.3120 1.0395 -1.0947 + -60.000 -0.4631 0.8690 -1.0947 + -50.000 -0.6013 0.6637 -1.0947 + -40.000 -0.7334 0.4476 -1.0947 + -30.000 -0.8917 0.2455 -1.0947 + -20.000 -0.6461 0.1386 -1.0947 + -10.000 -0.5722 0.0316 -2.3958 + -9.000 -0.5433 0.0285 -2.1764 + -8.000 -0.5145 0.0260 -1.9643 + -7.000 -0.4633 0.0248 -1.7200 + -6.000 -0.3726 0.0238 -1.4829 + -5.000 -0.2695 0.0231 -1.2946 + -4.000 -0.1619 0.0224 -1.1182 + -3.000 -0.0521 0.0215 -1.0047 + -2.000 0.0639 0.0213 -1.0040 + -1.000 0.1795 0.0212 -1.0841 + 0.000 0.2946 0.0213 -1.1688 + 1.000 0.4103 0.0213 -1.2561 + 2.000 0.5242 0.0215 -1.3432 + 3.000 0.6361 0.0216 -1.4336 + 4.000 0.7437 0.0220 -1.5246 + 5.000 0.8498 0.0224 -1.6245 + 6.000 0.9364 0.0235 -1.7280 + 7.000 0.9713 0.0251 -1.8062 + 8.000 1.0028 0.0273 -1.9267 + 9.000 1.0414 0.0300 -2.0719 + 10.000 1.0814 0.0333 -2.2235 + 11.000 1.0890 0.0389 -2.3357 + 12.000 1.1174 0.0440 -2.5748 + 13.000 1.1266 0.0516 -2.7784 + 14.000 1.1514 0.0584 -3.0308 + 15.000 1.1691 0.0666 -3.2770 + 16.000 1.1962 0.0746 -3.5677 + 17.000 1.2199 0.0833 -3.8669 + 18.000 1.2419 0.0928 -4.1831 + 19.000 1.2624 0.1028 -4.4997 + 20.000 1.2802 0.1136 -4.8265 + 21.000 1.2968 0.1246 -5.1610 + 22.000 1.3155 0.1353 -5.5203 + 23.000 1.3236 0.1477 -5.8461 + 24.000 1.3300 0.1602 -6.1673 + 25.000 1.3308 0.1732 -6.4703 + 26.000 1.3263 0.1870 -6.7296 + 28.000 1.3025 0.2154 -7.1066 + 29.000 1.2849 0.2312 -7.2022 + 30.000 1.2738 0.2455 -7.3200 + 40.000 1.0478 0.4476 -1.0947 + 50.000 0.8590 0.6637 -1.0947 + 60.000 0.6615 0.8690 -1.0947 + 70.000 0.4456 1.0395 -1.0947 + 80.000 0.2191 1.1557 -1.0947 + 90.000 0.0000 1.2050 -1.0947 + 100.000 -0.1534 1.1557 -1.0947 + 110.000 -0.3120 1.0395 -1.0947 + 120.000 -0.4631 0.8690 -1.0947 + 130.000 -0.6013 0.6637 -1.0947 + 140.000 -0.7334 0.4476 -1.0947 + 150.000 -0.8917 0.2455 -1.0947 + 160.000 -0.5944 0.0815 -1.0947 + 170.000 -0.2972 0.0237 -1.0947 + 180.000 0.0000 0.0237 -1.0947 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0413 -1.0947 + -170.000 0.3115 0.0413 -1.0947 + -160.000 0.6231 0.0877 -1.0947 + -150.000 0.9346 0.2526 -1.0947 + -140.000 0.7596 0.4558 -1.0947 + -130.000 0.6167 0.6734 -1.0947 + -120.000 0.4714 0.8804 -1.0947 + -110.000 0.3155 1.0529 -1.0947 + -100.000 0.1542 1.1712 -1.0947 + -90.000 0.0000 1.2225 -1.0947 + -80.000 -0.1542 1.1712 -1.0947 + -70.000 -0.3155 1.0529 -1.0947 + -60.000 -0.4714 0.8804 -1.0947 + -50.000 -0.6167 0.6734 -1.0947 + -40.000 -0.7596 0.4558 -1.0947 + -30.000 -0.9346 0.2526 -1.0947 + -20.000 -0.6829 0.1496 -1.0947 + -10.000 -0.6161 0.0466 -2.4883 + -9.000 -0.5712 0.0443 -2.2295 + -8.000 -0.5526 0.0423 -2.0298 + -7.000 -0.4716 0.0413 -1.7349 + -6.000 -0.3725 0.0405 -1.4832 + -5.000 -0.2677 0.0398 -1.2929 + -4.000 -0.1561 0.0394 -1.1123 + -3.000 -0.0432 0.0387 -0.9986 + -1.000 0.1888 0.0379 -1.0895 + 0.000 0.3061 0.0378 -1.1760 + 1.000 0.4213 0.0380 -1.2632 + 2.000 0.5378 0.0380 -1.3520 + 5.000 0.8552 0.0396 -1.6272 + 6.000 0.9306 0.0410 -1.7249 + 7.000 0.9823 0.0421 -1.8149 + 9.000 1.0790 0.0457 -2.1183 + 10.000 1.0980 0.0496 -2.2449 + 11.000 1.1311 0.0536 -2.4167 + 12.000 1.1458 0.0595 -2.6346 + 13.000 1.1730 0.0652 -2.8826 + 14.000 1.2004 0.0715 -3.1545 + 15.000 1.2328 0.0779 -3.4495 + 16.000 1.2590 0.0855 -3.7545 + 17.000 1.2859 0.0934 -4.0861 + 18.000 1.3082 0.1022 -4.4164 + 19.000 1.3304 0.1116 -4.7557 + 20.000 1.3446 0.1223 -5.0919 + 21.000 1.3594 0.1333 -5.4348 + 22.000 1.3722 0.1448 -5.7913 + 23.000 1.3765 0.1574 -6.1155 + 24.000 1.3896 0.1686 -6.5092 + 25.000 1.3903 0.1816 -6.8357 + 26.000 1.3909 0.1943 -7.1550 + 27.000 1.3872 0.2075 -7.4378 + 28.000 1.3796 0.2212 -7.6789 + 29.000 1.3509 0.2378 -7.7434 + 30.000 1.3352 0.2526 -7.8683 + 40.000 1.0851 0.4558 -1.0947 + 50.000 0.8811 0.6734 -1.0947 + 60.000 0.6733 0.8804 -1.0947 + 70.000 0.4507 1.0529 -1.0947 + 80.000 0.2203 1.1712 -1.0947 + 90.000 0.0000 1.2225 -1.0947 + 100.000 -0.1542 1.1712 -1.0947 + 110.000 -0.3155 1.0529 -1.0947 + 120.000 -0.4714 0.8804 -1.0947 + 130.000 -0.6167 0.6734 -1.0947 + 140.000 -0.7596 0.4558 -1.0947 + 150.000 -0.9346 0.2526 -1.0947 + 160.000 -0.6231 0.0877 -1.0947 + 170.000 -0.3115 0.0413 -1.0947 + 180.000 0.0000 0.0413 -1.0947 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0427 -1.0947 + -170.000 0.3231 0.0427 -1.0947 + -160.000 0.6463 0.0804 -1.0947 + -150.000 0.9694 0.2461 -1.0947 + -140.000 0.7808 0.4501 -1.0947 + -130.000 0.6292 0.6689 -1.0947 + -120.000 0.4780 0.8773 -1.0947 + -110.000 0.3184 1.0511 -1.0947 + -100.000 0.1550 1.1711 -1.0947 + -90.000 0.0000 1.2239 -1.0947 + -80.000 -0.1550 1.1711 -1.0947 + -70.000 -0.3184 1.0511 -1.0947 + -60.000 -0.4780 0.8773 -1.0947 + -50.000 -0.6292 0.6689 -1.0947 + -40.000 -0.7808 0.4501 -1.0947 + -30.000 -0.9694 0.2461 -1.0947 + -20.000 -0.7092 0.1463 -1.0947 + -10.000 -0.6414 0.0466 -2.5416 + -9.000 -0.6012 0.0445 -2.2848 + -8.000 -0.5628 0.0432 -2.0477 + -7.000 -0.4732 0.0423 -1.7376 + -6.000 -0.3741 0.0415 -1.4857 + -5.000 -0.2657 0.0409 -1.2907 + -4.000 -0.1535 0.0405 -1.1092 + -3.000 -0.0399 0.0400 -0.9966 + -2.000 0.0755 0.0393 -1.0106 + -1.000 0.1929 0.0390 -1.0920 + 0.000 0.3100 0.0390 -1.1782 + 1.000 0.4277 0.0390 -1.2673 + 2.000 0.5413 0.0393 -1.3545 + 4.000 0.7589 0.0401 -1.5387 + 5.000 0.8522 0.0412 -1.6269 + 6.000 0.9337 0.0423 -1.7204 + 7.000 0.9951 0.0432 -1.8277 + 8.000 1.0541 0.0443 -1.9823 + 9.000 1.0870 0.0467 -2.1278 + 10.000 1.1218 0.0498 -2.2774 + 11.000 1.1445 0.0541 -2.4431 + 12.000 1.1732 0.0589 -2.6923 + 13.000 1.1989 0.0645 -2.9418 + 14.000 1.2353 0.0700 -3.2423 + 15.000 1.2640 0.0765 -3.5369 + 16.000 1.2923 0.0836 -3.8535 + 17.000 1.3183 0.0914 -4.1926 + 19.000 1.3602 0.1094 -4.8697 + 20.000 1.3915 0.1176 -5.2827 + 21.000 1.4032 0.1286 -5.6231 + 22.000 1.4106 0.1406 -5.9723 + 23.000 1.4149 0.1531 -6.3138 + 24.000 1.4210 0.1654 -6.6853 + 25.000 1.4236 0.1780 -7.0348 + 26.000 1.4211 0.1910 -7.3486 + 27.000 1.4145 0.2046 -7.6241 + 28.000 1.4066 0.2183 -7.8765 + 29.000 1.3970 0.2320 -8.1002 + 30.000 1.3848 0.2461 -8.2820 + 40.000 1.1153 0.4501 -1.0947 + 50.000 0.8989 0.6689 -1.0947 + 60.000 0.6829 0.8773 -1.0947 + 70.000 0.4549 1.0511 -1.0947 + 80.000 0.2214 1.1711 -1.0947 + 90.000 0.0000 1.2239 -1.0947 + 100.000 -0.1550 1.1711 -1.0947 + 110.000 -0.3184 1.0511 -1.0947 + 120.000 -0.4780 0.8773 -1.0947 + 130.000 -0.6292 0.6689 -1.0947 + 140.000 -0.7808 0.4501 -1.0947 + 150.000 -0.9694 0.2461 -1.0947 + 160.000 -0.6463 0.0804 -1.0947 + 170.000 -0.3231 0.0427 -1.0947 + 180.000 0.0000 0.0427 -1.0947 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0427 -1.0947 + -170.000 0.3872 0.0427 -1.0947 + -160.000 0.7745 0.0957 -1.0947 + -150.000 0.9131 0.2601 -1.0947 + -140.000 0.7465 0.4626 -1.0947 + -130.000 0.6090 0.6794 -1.0947 + -120.000 0.4672 0.8854 -1.0947 + -110.000 0.3137 1.0567 -1.0947 + -100.000 0.1539 1.1738 -1.0947 + -90.000 0.0000 1.2239 -1.0947 + -80.000 -0.1539 1.1738 -1.0947 + -70.000 -0.3137 1.0567 -1.0947 + -60.000 -0.4672 0.8854 -1.0947 + -50.000 -0.6090 0.6794 -1.0947 + -40.000 -0.7465 0.4626 -1.0947 + -30.000 -0.9131 0.2601 -1.0947 + -20.000 -0.8002 0.1351 -1.0947 + -10.000 -0.6511 0.0461 -2.5695 + -9.000 -0.6241 0.0436 -2.3279 + -8.000 -0.5706 0.0427 -2.0616 + -5.000 -0.2653 0.0407 -1.2901 + -4.000 -0.1529 0.0402 -1.1086 + -3.000 -0.0377 0.0398 -0.9859 + -2.000 0.0776 0.0393 -1.0119 + -1.000 0.1949 0.0389 -1.0929 + 0.000 0.3132 0.0388 -1.1803 + 1.000 0.4292 0.0388 -1.2680 + 2.000 0.5426 0.0391 -1.3559 + 3.000 0.6544 0.0394 -1.4464 + 4.000 0.7581 0.0402 -1.5294 + 6.000 0.9397 0.0421 -1.7194 + 7.000 1.0132 0.0428 -1.8437 + 8.000 1.0686 0.0438 -1.9993 + 9.000 1.0986 0.0462 -2.1424 + 11.000 1.1565 0.0534 -2.4664 + 12.000 1.1929 0.0575 -2.7339 + 13.000 1.2310 0.0621 -3.0185 + 15.000 1.2979 0.0735 -3.6316 + 16.000 1.3263 0.0802 -3.9577 + 17.000 1.3551 0.0875 -4.3142 + 18.000 1.3747 0.0960 -4.6477 + 19.000 1.3968 0.1049 -5.0108 + 20.000 1.4117 0.1151 -5.3642 + 22.000 1.4284 0.1382 -6.0547 + 25.000 1.4397 0.1756 -7.1298 + 26.000 1.4383 0.1885 -7.4558 + 30.000 1.3044 0.2601 -6.0291 + 40.000 1.0665 0.4626 -1.0947 + 50.000 0.8700 0.6794 -1.0947 + 60.000 0.6674 0.8854 -1.0947 + 70.000 0.4482 1.0567 -1.0947 + 80.000 0.2198 1.1738 -1.0947 + 90.000 0.0000 1.2239 -1.0947 + 100.000 -0.1539 1.1738 -1.0947 + 110.000 -0.3137 1.0567 -1.0947 + 120.000 -0.4672 0.8854 -1.0947 + 130.000 -0.6090 0.6794 -1.0947 + 140.000 -0.7465 0.4626 -1.0947 + 150.000 -0.9131 0.2601 -1.0947 + 160.000 -0.7745 0.0957 -1.0947 + 170.000 -0.3872 0.0427 -1.0947 + 180.000 0.0000 0.0427 -1.0947 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0427 -1.0947 + -170.000 0.3342 0.0427 -1.0947 + -160.000 0.6685 0.0713 -1.0947 + -150.000 1.0026 0.2377 -1.0947 + -140.000 0.8010 0.4427 -1.0947 + -130.000 0.6412 0.6628 -1.0947 + -120.000 0.4844 0.8724 -1.0947 + -110.000 0.3211 1.0478 -1.0947 + -100.000 0.1557 1.1694 -1.0947 + -90.000 0.0000 1.2239 -1.0947 + -80.000 -0.1557 1.1694 -1.0947 + -70.000 -0.3211 1.0478 -1.0947 + -60.000 -0.4844 0.8724 -1.0947 + -50.000 -0.6412 0.6628 -1.0947 + -40.000 -0.8010 0.4427 -1.0947 + -30.000 -1.0026 0.2377 -1.0947 + -20.000 -0.7284 0.1419 -1.0947 + -10.000 -0.6488 0.0460 -2.5468 + -9.000 -0.6526 0.0433 -2.3850 + -8.000 -0.5774 0.0424 -2.0737 + -6.000 -0.3754 0.0410 -1.4897 + -4.000 -0.1520 0.0400 -1.1078 + -3.000 -0.0370 0.0397 -0.9872 + -2.000 0.0791 0.0393 -1.0126 + -1.000 0.1969 0.0388 -1.0942 + 0.000 0.3146 0.0387 -1.1810 + 1.000 0.4298 0.0388 -1.2686 + 2.000 0.5430 0.0391 -1.3579 + 4.000 0.7562 0.0403 -1.5250 + 5.000 0.8507 0.0413 -1.6163 + 6.000 0.9427 0.0420 -1.7254 + 7.000 1.0329 0.0426 -1.8611 + 8.000 1.0750 0.0437 -2.0065 + 9.000 1.1141 0.0456 -2.1622 + 10.000 1.1311 0.0493 -2.2748 + 11.000 1.1766 0.0523 -2.5065 + 12.000 1.2105 0.0564 -2.7712 + 13.000 1.2474 0.0610 -3.0573 + 14.000 1.2841 0.0660 -3.3650 + 16.000 1.3463 0.0784 -4.0198 + 17.000 1.3700 0.0859 -4.3625 + 18.000 1.3938 0.0940 -4.7136 + 19.000 1.4123 0.1031 -5.0694 + 20.000 1.4262 0.1133 -5.4224 + 21.000 1.4334 0.1246 -5.7546 + 24.000 1.4704 0.1580 -6.9565 + 25.000 1.4739 0.1702 -7.3296 + 26.000 1.4743 0.1829 -7.6801 + 27.000 1.4705 0.1958 -7.9975 + 28.000 1.4611 0.2093 -8.2673 + 29.000 1.4477 0.2234 -8.4899 + 30.000 1.4324 0.2377 -8.6765 + 40.000 1.1443 0.4427 -1.0947 + 50.000 0.9160 0.6628 -1.0947 + 60.000 0.6921 0.8724 -1.0947 + 70.000 0.4588 1.0478 -1.0947 + 80.000 0.2223 1.1694 -1.0947 + 90.000 0.0000 1.2239 -1.0947 + 100.000 -0.1557 1.1694 -1.0947 + 110.000 -0.3211 1.0478 -1.0947 + 120.000 -0.4844 0.8724 -1.0947 + 130.000 -0.6412 0.6628 -1.0947 + 140.000 -0.8010 0.4427 -1.0947 + 150.000 -1.0026 0.2377 -1.0947 + 160.000 -0.6685 0.0713 -1.0947 + 170.000 -0.3342 0.0427 -1.0947 + 180.000 0.0000 0.0427 -1.0947 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0427 -1.0947 + -170.000 0.3520 0.0427 -1.0947 + -160.000 0.7039 0.0744 -1.0947 + -150.000 0.9952 0.2405 -1.0947 + -140.000 0.7965 0.4453 -1.0947 + -130.000 0.6385 0.6648 -1.0947 + -120.000 0.4830 0.8740 -1.0947 + -110.000 0.3206 1.0489 -1.0947 + -100.000 0.1555 1.1699 -1.0947 + -90.000 0.0000 1.2239 -1.0947 + -80.000 -0.1555 1.1699 -1.0947 + -70.000 -0.3206 1.0489 -1.0947 + -60.000 -0.4830 0.8740 -1.0947 + -50.000 -0.6385 0.6648 -1.0947 + -40.000 -0.7965 0.4453 -1.0947 + -30.000 -0.9952 0.2405 -1.0947 + -20.000 -0.7566 0.1382 -1.0947 + -10.000 -0.6615 0.0454 -2.5749 + -7.000 -0.4812 0.0415 -1.7511 + -6.000 -0.3745 0.0410 -1.4789 + -5.000 -0.2649 0.0403 -1.2901 + -4.000 -0.1519 0.0399 -1.1074 + -3.000 -0.0361 0.0396 -0.9899 + -2.000 0.0806 0.0393 -1.0134 + -1.000 0.1980 0.0387 -1.0949 + 0.000 0.3153 0.0387 -1.1812 + 1.000 0.4305 0.0387 -1.2694 + 2.000 0.5438 0.0390 -1.3540 + 3.000 0.6538 0.0394 -1.4370 + 4.000 0.7567 0.0402 -1.5286 + 5.000 0.8514 0.0412 -1.6190 + 6.000 0.9493 0.0417 -1.7316 + 7.000 1.0402 0.0424 -1.8683 + 8.000 1.0816 0.0435 -2.0142 + 10.000 1.1457 0.0485 -2.2994 + 11.000 1.1887 0.0516 -2.5309 + 12.000 1.2299 0.0553 -2.8127 + 13.000 1.2688 0.0595 -3.1081 + 14.000 1.2973 0.0651 -3.3981 + 15.000 1.3297 0.0708 -3.7201 + 17.000 1.3841 0.0846 -4.4087 + 18.000 1.4065 0.0927 -4.7570 + 19.000 1.4248 0.1017 -5.1168 + 20.000 1.4340 0.1123 -5.4530 + 22.000 1.4727 0.1319 -6.2606 + 23.000 1.4802 0.1438 -6.6509 + 24.000 1.4856 0.1558 -7.0399 + 25.000 1.4882 0.1682 -7.4120 + 26.000 1.4872 0.1810 -7.7597 + 27.000 1.4803 0.1942 -8.0622 + 28.000 1.4702 0.2080 -8.3300 + 29.000 1.4581 0.2218 -8.5675 + 30.000 1.4218 0.2405 -8.1097 + 40.000 1.1378 0.4453 -1.0947 + 50.000 0.9121 0.6648 -1.0947 + 60.000 0.6900 0.8740 -1.0947 + 70.000 0.4579 1.0489 -1.0947 + 80.000 0.2222 1.1699 -1.0947 + 90.000 0.0000 1.2239 -1.0947 + 100.000 -0.1555 1.1699 -1.0947 + 110.000 -0.3206 1.0489 -1.0947 + 120.000 -0.4830 0.8740 -1.0947 + 130.000 -0.6385 0.6648 -1.0947 + 140.000 -0.7965 0.4453 -1.0947 + 150.000 -0.9952 0.2405 -1.0947 + 160.000 -0.7039 0.0744 -1.0947 + 170.000 -0.3520 0.0427 -1.0947 + 180.000 0.0000 0.0427 -1.0947 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0427 -1.0947 + -170.000 0.3392 0.0427 -1.0947 + -160.000 0.6784 0.0675 -1.0947 + -150.000 1.0176 0.2342 -1.0947 + -140.000 0.8101 0.4396 -1.0947 + -130.000 0.6466 0.6602 -1.0947 + -120.000 0.4873 0.8704 -1.0947 + -110.000 0.3224 1.0465 -1.0947 + -100.000 0.1559 1.1686 -1.0947 + -90.000 0.0000 1.2239 -1.0947 + -80.000 -0.1559 1.1686 -1.0947 + -70.000 -0.3224 1.0465 -1.0947 + -60.000 -0.4873 0.8704 -1.0947 + -50.000 -0.6466 0.6602 -1.0947 + -40.000 -0.8101 0.4396 -1.0947 + -30.000 -1.0176 0.2342 -1.0947 + -20.000 -0.7448 0.1396 -1.0947 + -10.000 -0.6743 0.0450 -2.6018 + -9.000 -0.6556 0.0432 -2.3780 + -8.000 -0.5837 0.0419 -2.0858 + -6.000 -0.3744 0.0409 -1.4766 + -5.000 -0.2648 0.0402 -1.2898 + -4.000 -0.1518 0.0397 -1.1073 + -3.000 -0.0353 0.0395 -0.9902 + -2.000 0.0816 0.0392 -1.0140 + -1.000 0.1984 0.0387 -1.0951 + 0.000 0.3163 0.0386 -1.1820 + 1.000 0.4294 0.0388 -1.2695 + 2.000 0.5437 0.0390 -1.3533 + 3.000 0.6525 0.0395 -1.4353 + 5.000 0.8543 0.0411 -1.6221 + 6.000 0.9522 0.0417 -1.7348 + 7.000 1.0473 0.0422 -1.8753 + 8.000 1.0856 0.0434 -2.0185 + 11.000 1.1998 0.0511 -2.5530 + 12.000 1.2410 0.0546 -2.8360 + 14.000 1.3174 0.0635 -3.4485 + 16.000 1.3700 0.0763 -4.0931 + 18.000 1.4171 0.0916 -4.7936 + 21.000 1.4744 0.1193 -5.9336 + 22.000 1.4840 0.1304 -6.3121 + 23.000 1.4926 0.1420 -6.7143 + 24.000 1.4971 0.1541 -7.1018 + 25.000 1.4986 0.1667 -7.4716 + 26.000 1.4943 0.1799 -7.8035 + 27.000 1.4875 0.1932 -8.1091 + 28.000 1.4786 0.2066 -8.3887 + 29.000 1.4676 0.2203 -8.6380 + 30.000 1.4537 0.2342 -8.8479 + 40.000 1.1573 0.4396 -1.0947 + 50.000 0.9237 0.6602 -1.0947 + 60.000 0.6962 0.8704 -1.0947 + 70.000 0.4606 1.0465 -1.0947 + 80.000 0.2228 1.1686 -1.0947 + 90.000 0.0000 1.2239 -1.0947 + 100.000 -0.1559 1.1686 -1.0947 + 110.000 -0.3224 1.0465 -1.0947 + 120.000 -0.4873 0.8704 -1.0947 + 130.000 -0.6466 0.6602 -1.0947 + 140.000 -0.8101 0.4396 -1.0947 + 150.000 -1.0176 0.2342 -1.0947 + 160.000 -0.6784 0.0675 -1.0947 + 170.000 -0.3392 0.0427 -1.0947 + 180.000 0.0000 0.0427 -1.0947 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0276_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0276_coords.txt new file mode 100644 index 00000000..c2553444 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0276_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0276 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.024017 + 0.027091 0.050261 + 0.060263 0.077244 + 0.105430 0.102168 + 0.161359 0.123903 + 0.226526 0.140948 + 0.299152 0.151887 + 0.377257 0.154763 + 0.458710 0.148989 + 0.541290 0.136081 + 0.622743 0.118030 + 0.700848 0.097075 + 0.773474 0.075618 + 0.838641 0.055666 + 0.894570 0.038477 + 0.939737 0.024535 + 0.972909 0.013769 + 0.993181 0.005721 + 1.000000 0.000000 + 0.993181 -0.003319 + 0.972909 -0.006500 + 0.939737 -0.011272 + 0.894570 -0.018909 + 0.838641 -0.030129 + 0.773474 -0.044953 + 0.700848 -0.062630 + 0.622743 -0.081432 + 0.541290 -0.099052 + 0.458710 -0.113095 + 0.377257 -0.121217 + 0.299152 -0.121652 + 0.226526 -0.115046 + 0.161359 -0.102964 + 0.105430 -0.086660 + 0.060263 -0.067057 + 0.027091 -0.044998 + 0.006819 -0.021867 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0329.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0329.dat new file mode 100644 index 00000000..b975b05e --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0329.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0329 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0329_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0440 -1.2342 + -170.000 0.2755 0.0440 -1.2342 + -160.000 0.5509 0.0975 -1.2342 + -150.000 0.8264 0.2495 -1.2342 + -140.000 0.6797 0.4368 -1.2342 + -130.000 0.5573 0.6371 -1.2342 + -120.000 0.4292 0.8274 -1.2342 + -110.000 0.2891 0.9854 -1.2342 + -100.000 0.1421 1.0931 -1.2342 + -90.000 0.0000 1.1387 -1.2342 + -80.000 -0.1421 1.0931 -1.2342 + -70.000 -0.2891 0.9854 -1.2342 + -60.000 -0.4292 0.8274 -1.2342 + -50.000 -0.5573 0.6371 -1.2342 + -40.000 -0.6797 0.4368 -1.2342 + -30.000 -0.8264 0.2495 -1.2342 + -20.000 -0.5988 0.1504 -1.2342 + -10.000 -0.5303 0.0513 -2.4401 + -9.000 -0.5035 0.0484 -2.2366 + -8.000 -0.4769 0.0461 -2.0401 + -7.000 -0.4294 0.0449 -1.8137 + -6.000 -0.3453 0.0440 -1.5940 + -5.000 -0.2498 0.0433 -1.4194 + -4.000 -0.1500 0.0427 -1.2559 + -3.000 -0.0483 0.0418 -1.1508 + -2.000 0.0592 0.0417 -1.1501 + -1.000 0.1663 0.0416 -1.2243 + 0.000 0.2730 0.0417 -1.3028 + 1.000 0.3803 0.0417 -1.3838 + 2.000 0.4859 0.0418 -1.4645 + 3.000 0.5895 0.0420 -1.5483 + 4.000 0.6893 0.0424 -1.6326 + 5.000 0.7876 0.0427 -1.7252 + 6.000 0.8679 0.0437 -1.8212 + 7.000 0.9002 0.0452 -1.8936 + 8.000 0.9294 0.0472 -2.0052 + 9.000 0.9652 0.0498 -2.1398 + 10.000 1.0023 0.0528 -2.2804 + 11.000 1.0093 0.0580 -2.3844 + 12.000 1.0356 0.0628 -2.6060 + 13.000 1.0441 0.0697 -2.7946 + 14.000 1.0672 0.0761 -3.0285 + 15.000 1.0835 0.0837 -3.2567 + 16.000 1.1087 0.0911 -3.5261 + 17.000 1.1306 0.0991 -3.8034 + 18.000 1.1510 0.1080 -4.0965 + 19.000 1.1700 0.1172 -4.3899 + 20.000 1.1865 0.1272 -4.6928 + 21.000 1.2019 0.1375 -5.0028 + 22.000 1.2192 0.1473 -5.3358 + 23.000 1.2267 0.1588 -5.6377 + 24.000 1.2326 0.1704 -5.9354 + 25.000 1.2334 0.1825 -6.2163 + 26.000 1.2292 0.1953 -6.4566 + 28.000 1.2072 0.2216 -6.8060 + 29.000 1.1908 0.2363 -6.8946 + 30.000 1.1805 0.2495 -7.0038 + 40.000 0.9711 0.4368 -1.2342 + 50.000 0.7961 0.6371 -1.2342 + 60.000 0.6131 0.8274 -1.2342 + 70.000 0.4130 0.9854 -1.2342 + 80.000 0.2031 1.0931 -1.2342 + 90.000 0.0000 1.1387 -1.2342 + 100.000 -0.1421 1.0931 -1.2342 + 110.000 -0.2891 0.9854 -1.2342 + 120.000 -0.4292 0.8274 -1.2342 + 130.000 -0.5573 0.6371 -1.2342 + 140.000 -0.6797 0.4368 -1.2342 + 150.000 -0.8264 0.2495 -1.2342 + 160.000 -0.5509 0.0975 -1.2342 + 170.000 -0.2755 0.0440 -1.2342 + 180.000 0.0000 0.0440 -1.2342 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0873 -1.2342 + -170.000 0.2887 0.0873 -1.2342 + -160.000 0.5775 0.1303 -1.2342 + -150.000 0.8662 0.2831 -1.2342 + -140.000 0.7040 0.4714 -1.2342 + -130.000 0.5716 0.6732 -1.2342 + -120.000 0.4369 0.8650 -1.2342 + -110.000 0.2924 1.0248 -1.2342 + -100.000 0.1429 1.1345 -1.2342 + -90.000 0.0000 1.1821 -1.2342 + -80.000 -0.1429 1.1345 -1.2342 + -70.000 -0.2924 1.0248 -1.2342 + -60.000 -0.4369 0.8650 -1.2342 + -50.000 -0.5716 0.6732 -1.2342 + -40.000 -0.7040 0.4714 -1.2342 + -30.000 -0.8662 0.2831 -1.2342 + -20.000 -0.6329 0.1877 -1.2342 + -10.000 -0.5710 0.0922 -2.5258 + -9.000 -0.5294 0.0901 -2.2859 + -8.000 -0.5122 0.0883 -2.1009 + -7.000 -0.4370 0.0873 -1.8275 + -6.000 -0.3452 0.0866 -1.5943 + -5.000 -0.2481 0.0860 -1.4179 + -4.000 -0.1447 0.0855 -1.2505 + -3.000 -0.0401 0.0849 -1.1451 + -1.000 0.1750 0.0842 -1.2294 + 0.000 0.2837 0.0841 -1.3095 + 1.000 0.3905 0.0843 -1.3903 + 2.000 0.4984 0.0843 -1.4727 + 5.000 0.7926 0.0858 -1.7277 + 6.000 0.8625 0.0870 -1.8182 + 7.000 0.9104 0.0881 -1.9017 + 9.000 1.0001 0.0914 -2.1829 + 10.000 1.0176 0.0951 -2.3002 + 11.000 1.0483 0.0988 -2.4594 + 12.000 1.0619 0.1042 -2.6613 + 13.000 1.0871 0.1095 -2.8912 + 14.000 1.1125 0.1153 -3.1432 + 15.000 1.1426 0.1213 -3.4165 + 16.000 1.1668 0.1283 -3.6993 + 17.000 1.1917 0.1356 -4.0066 + 18.000 1.2125 0.1438 -4.3127 + 19.000 1.2331 0.1524 -4.6272 + 20.000 1.2462 0.1624 -4.9387 + 21.000 1.2599 0.1726 -5.2566 + 22.000 1.2717 0.1833 -5.5870 + 23.000 1.2757 0.1949 -5.8874 + 24.000 1.2879 0.2053 -6.2523 + 25.000 1.2885 0.2173 -6.5549 + 26.000 1.2891 0.2291 -6.8508 + 27.000 1.2857 0.2414 -7.1130 + 28.000 1.2786 0.2541 -7.3364 + 29.000 1.2520 0.2694 -7.3962 + 30.000 1.2375 0.2831 -7.5119 + 40.000 1.0057 0.4714 -1.2342 + 50.000 0.8166 0.6732 -1.2342 + 60.000 0.6240 0.8650 -1.2342 + 70.000 0.4177 1.0248 -1.2342 + 80.000 0.2042 1.1345 -1.2342 + 90.000 0.0000 1.1821 -1.2342 + 100.000 -0.1429 1.1345 -1.2342 + 110.000 -0.2924 1.0248 -1.2342 + 120.000 -0.4369 0.8650 -1.2342 + 130.000 -0.5716 0.6732 -1.2342 + 140.000 -0.7040 0.4714 -1.2342 + 150.000 -0.8662 0.2831 -1.2342 + 160.000 -0.5775 0.1303 -1.2342 + 170.000 -0.2887 0.0873 -1.2342 + 180.000 0.0000 0.0873 -1.2342 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0908 -1.2342 + -170.000 0.2995 0.0908 -1.2342 + -160.000 0.5990 0.1258 -1.2342 + -150.000 0.8984 0.2793 -1.2342 + -140.000 0.7236 0.4684 -1.2342 + -130.000 0.5832 0.6712 -1.2342 + -120.000 0.4430 0.8643 -1.2342 + -110.000 0.2951 1.0254 -1.2342 + -100.000 0.1436 1.1366 -1.2342 + -90.000 0.0000 1.1856 -1.2342 + -80.000 -0.1436 1.1366 -1.2342 + -70.000 -0.2951 1.0254 -1.2342 + -60.000 -0.4430 0.8643 -1.2342 + -50.000 -0.5832 0.6712 -1.2342 + -40.000 -0.7236 0.4684 -1.2342 + -30.000 -0.8984 0.2793 -1.2342 + -20.000 -0.6573 0.1869 -1.2342 + -10.000 -0.5945 0.0944 -2.5752 + -9.000 -0.5572 0.0925 -2.3371 + -8.000 -0.5216 0.0912 -2.1174 + -7.000 -0.4385 0.0904 -1.8300 + -6.000 -0.3467 0.0897 -1.5966 + -5.000 -0.2462 0.0891 -1.4158 + -4.000 -0.1422 0.0888 -1.2476 + -3.000 -0.0370 0.0883 -1.1433 + -2.000 0.0700 0.0876 -1.1563 + -1.000 0.1788 0.0874 -1.2317 + 0.000 0.2873 0.0874 -1.3116 + 1.000 0.3964 0.0874 -1.3941 + 2.000 0.5017 0.0876 -1.4750 + 4.000 0.7033 0.0884 -1.6456 + 5.000 0.7898 0.0894 -1.7274 + 6.000 0.8653 0.0904 -1.8141 + 7.000 0.9223 0.0912 -1.9135 + 8.000 0.9769 0.0923 -2.0568 + 9.000 1.0075 0.0945 -2.1916 + 10.000 1.0397 0.0974 -2.3303 + 11.000 1.0607 0.1014 -2.4839 + 12.000 1.0873 0.1058 -2.7148 + 13.000 1.1111 0.1110 -2.9461 + 14.000 1.1448 0.1161 -3.2245 + 15.000 1.1715 0.1221 -3.4976 + 16.000 1.1977 0.1287 -3.7910 + 17.000 1.2217 0.1359 -4.1053 + 19.000 1.2606 0.1526 -4.7329 + 20.000 1.2896 0.1602 -5.1156 + 21.000 1.3005 0.1704 -5.4311 + 22.000 1.3073 0.1816 -5.7547 + 23.000 1.3114 0.1931 -6.0712 + 24.000 1.3170 0.2045 -6.4155 + 25.000 1.3194 0.2162 -6.7394 + 26.000 1.3171 0.2283 -7.0302 + 27.000 1.3109 0.2409 -7.2856 + 28.000 1.3036 0.2535 -7.5195 + 29.000 1.2948 0.2662 -7.7268 + 30.000 1.2835 0.2793 -7.8953 + 40.000 1.0337 0.4684 -1.2342 + 50.000 0.8331 0.6712 -1.2342 + 60.000 0.6329 0.8643 -1.2342 + 70.000 0.4216 1.0254 -1.2342 + 80.000 0.2052 1.1366 -1.2342 + 90.000 0.0000 1.1856 -1.2342 + 100.000 -0.1436 1.1366 -1.2342 + 110.000 -0.2951 1.0254 -1.2342 + 120.000 -0.4430 0.8643 -1.2342 + 130.000 -0.5832 0.6712 -1.2342 + 140.000 -0.7236 0.4684 -1.2342 + 150.000 -0.8984 0.2793 -1.2342 + 160.000 -0.5990 0.1258 -1.2342 + 170.000 -0.2995 0.0908 -1.2342 + 180.000 0.0000 0.0908 -1.2342 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0908 -1.2342 + -170.000 0.3589 0.0908 -1.2342 + -160.000 0.7178 0.1399 -1.2342 + -150.000 0.8463 0.2923 -1.2342 + -140.000 0.6918 0.4800 -1.2342 + -130.000 0.5644 0.6809 -1.2342 + -120.000 0.4330 0.8718 -1.2342 + -110.000 0.2907 1.0306 -1.2342 + -100.000 0.1426 1.1392 -1.2342 + -90.000 0.0000 1.1856 -1.2342 + -80.000 -0.1426 1.1392 -1.2342 + -70.000 -0.2907 1.0306 -1.2342 + -60.000 -0.4330 0.8718 -1.2342 + -50.000 -0.5644 0.6809 -1.2342 + -40.000 -0.6918 0.4800 -1.2342 + -30.000 -0.8463 0.2923 -1.2342 + -20.000 -0.7416 0.1764 -1.2342 + -10.000 -0.6035 0.0940 -2.6010 + -9.000 -0.5784 0.0917 -2.3771 + -8.000 -0.5289 0.0908 -2.1303 + -5.000 -0.2459 0.0889 -1.4153 + -4.000 -0.1417 0.0885 -1.2471 + -3.000 -0.0350 0.0882 -1.1334 + -2.000 0.0720 0.0876 -1.1574 + -1.000 0.1806 0.0873 -1.2325 + 0.000 0.2903 0.0872 -1.3135 + 1.000 0.3977 0.0872 -1.3948 + 2.000 0.5029 0.0874 -1.4763 + 3.000 0.6065 0.0878 -1.5602 + 4.000 0.7026 0.0885 -1.6371 + 6.000 0.8709 0.0903 -1.8131 + 7.000 0.9390 0.0909 -1.9283 + 8.000 0.9903 0.0919 -2.0725 + 9.000 1.0182 0.0941 -2.2052 + 11.000 1.0718 0.1008 -2.5055 + 12.000 1.1056 0.1046 -2.7534 + 13.000 1.1409 0.1088 -3.0171 + 15.000 1.2029 0.1193 -3.5854 + 16.000 1.2292 0.1256 -3.8876 + 17.000 1.2559 0.1323 -4.2180 + 18.000 1.2741 0.1402 -4.5271 + 19.000 1.2946 0.1485 -4.8636 + 20.000 1.3084 0.1579 -5.1912 + 22.000 1.3238 0.1794 -5.8311 + 25.000 1.3343 0.2140 -6.8274 + 26.000 1.3330 0.2260 -7.1297 + 30.000 1.2089 0.2923 -5.8073 + 40.000 0.9884 0.4800 -1.2342 + 50.000 0.8063 0.6809 -1.2342 + 60.000 0.6186 0.8718 -1.2342 + 70.000 0.4154 1.0306 -1.2342 + 80.000 0.2037 1.1392 -1.2342 + 90.000 0.0000 1.1856 -1.2342 + 100.000 -0.1426 1.1392 -1.2342 + 110.000 -0.2907 1.0306 -1.2342 + 120.000 -0.4330 0.8718 -1.2342 + 130.000 -0.5644 0.6809 -1.2342 + 140.000 -0.6918 0.4800 -1.2342 + 150.000 -0.8463 0.2923 -1.2342 + 160.000 -0.7178 0.1399 -1.2342 + 170.000 -0.3589 0.0908 -1.2342 + 180.000 0.0000 0.0908 -1.2342 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0908 -1.2342 + -170.000 0.3097 0.0908 -1.2342 + -160.000 0.6195 0.1173 -1.2342 + -150.000 0.9292 0.2715 -1.2342 + -140.000 0.7423 0.4615 -1.2342 + -130.000 0.5943 0.6655 -1.2342 + -120.000 0.4490 0.8598 -1.2342 + -110.000 0.2976 1.0223 -1.2342 + -100.000 0.1443 1.1350 -1.2342 + -90.000 0.0000 1.1856 -1.2342 + -80.000 -0.1443 1.1350 -1.2342 + -70.000 -0.2976 1.0223 -1.2342 + -60.000 -0.4490 0.8598 -1.2342 + -50.000 -0.5943 0.6655 -1.2342 + -40.000 -0.7423 0.4615 -1.2342 + -30.000 -0.9292 0.2715 -1.2342 + -20.000 -0.6751 0.1827 -1.2342 + -10.000 -0.6013 0.0939 -2.5800 + -9.000 -0.6049 0.0913 -2.4300 + -8.000 -0.5351 0.0905 -2.1415 + -6.000 -0.3479 0.0892 -1.6003 + -4.000 -0.1409 0.0883 -1.2463 + -3.000 -0.0343 0.0881 -1.1345 + -2.000 0.0733 0.0876 -1.1581 + -1.000 0.1825 0.0872 -1.2337 + 0.000 0.2915 0.0871 -1.3142 + 1.000 0.3984 0.0872 -1.3953 + 2.000 0.5032 0.0874 -1.4781 + 4.000 0.7008 0.0886 -1.6330 + 5.000 0.7884 0.0895 -1.7176 + 6.000 0.8737 0.0902 -1.8187 + 7.000 0.9573 0.0907 -1.9445 + 8.000 0.9963 0.0918 -2.0792 + 9.000 1.0325 0.0935 -2.2235 + 10.000 1.0483 0.0969 -2.3279 + 11.000 1.0905 0.0997 -2.5427 + 12.000 1.1219 0.1035 -2.7879 + 13.000 1.1561 0.1078 -3.0531 + 14.000 1.1901 0.1124 -3.3382 + 16.000 1.2477 0.1239 -3.9451 + 17.000 1.2697 0.1309 -4.2627 + 18.000 1.2918 0.1384 -4.5882 + 19.000 1.3089 0.1468 -4.9179 + 20.000 1.3218 0.1562 -5.2450 + 21.000 1.3285 0.1667 -5.5530 + 24.000 1.3627 0.1976 -6.6668 + 25.000 1.3660 0.2090 -7.0127 + 26.000 1.3664 0.2208 -7.3375 + 27.000 1.3628 0.2327 -7.6317 + 28.000 1.3542 0.2452 -7.8817 + 29.000 1.3417 0.2583 -8.0880 + 30.000 1.3275 0.2715 -8.2610 + 40.000 1.0605 0.4615 -1.2342 + 50.000 0.8489 0.6655 -1.2342 + 60.000 0.6414 0.8598 -1.2342 + 70.000 0.4252 1.0223 -1.2342 + 80.000 0.2061 1.1350 -1.2342 + 90.000 0.0000 1.1856 -1.2342 + 100.000 -0.1443 1.1350 -1.2342 + 110.000 -0.2976 1.0223 -1.2342 + 120.000 -0.4490 0.8598 -1.2342 + 130.000 -0.5943 0.6655 -1.2342 + 140.000 -0.7423 0.4615 -1.2342 + 150.000 -0.9292 0.2715 -1.2342 + 160.000 -0.6195 0.1173 -1.2342 + 170.000 -0.3097 0.0908 -1.2342 + 180.000 0.0000 0.0908 -1.2342 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0908 -1.2342 + -170.000 0.3262 0.0908 -1.2342 + -160.000 0.6524 0.1202 -1.2342 + -150.000 0.9224 0.2741 -1.2342 + -140.000 0.7382 0.4639 -1.2342 + -130.000 0.5918 0.6674 -1.2342 + -120.000 0.4476 0.8613 -1.2342 + -110.000 0.2971 1.0234 -1.2342 + -100.000 0.1441 1.1355 -1.2342 + -90.000 0.0000 1.1856 -1.2342 + -80.000 -0.1441 1.1355 -1.2342 + -70.000 -0.2971 1.0234 -1.2342 + -60.000 -0.4476 0.8613 -1.2342 + -50.000 -0.5918 0.6674 -1.2342 + -40.000 -0.7382 0.4639 -1.2342 + -30.000 -0.9224 0.2741 -1.2342 + -20.000 -0.7012 0.1794 -1.2342 + -10.000 -0.6131 0.0934 -2.6061 + -7.000 -0.4460 0.0897 -1.8425 + -6.000 -0.3471 0.0892 -1.5903 + -5.000 -0.2455 0.0886 -1.4153 + -4.000 -0.1408 0.0882 -1.2460 + -3.000 -0.0335 0.0880 -1.1370 + -2.000 0.0747 0.0876 -1.1588 + -1.000 0.1835 0.0871 -1.2344 + 0.000 0.2922 0.0871 -1.3144 + 1.000 0.3990 0.0871 -1.3960 + 2.000 0.5040 0.0874 -1.4745 + 3.000 0.6059 0.0878 -1.5514 + 4.000 0.7013 0.0885 -1.6363 + 5.000 0.7890 0.0894 -1.7201 + 6.000 0.8798 0.0899 -1.8244 + 7.000 0.9640 0.0905 -1.9511 + 8.000 1.0024 0.0916 -2.0864 + 10.000 1.0619 0.0962 -2.3507 + 11.000 1.1017 0.0991 -2.5653 + 12.000 1.1399 0.1025 -2.8264 + 13.000 1.1759 0.1063 -3.1002 + 14.000 1.2023 0.1116 -3.3690 + 15.000 1.2323 0.1168 -3.6674 + 17.000 1.2828 0.1297 -4.3055 + 18.000 1.3035 0.1372 -4.6284 + 19.000 1.3205 0.1455 -4.9619 + 20.000 1.3290 0.1553 -5.2735 + 22.000 1.3649 0.1735 -6.0219 + 23.000 1.3718 0.1845 -6.3836 + 24.000 1.3769 0.1956 -6.7442 + 25.000 1.3793 0.2072 -7.0890 + 26.000 1.3784 0.2190 -7.4113 + 27.000 1.3719 0.2313 -7.6916 + 28.000 1.3626 0.2440 -7.9398 + 29.000 1.3514 0.2568 -8.1599 + 30.000 1.3177 0.2741 -7.7356 + 40.000 1.0545 0.4639 -1.2342 + 50.000 0.8454 0.6674 -1.2342 + 60.000 0.6395 0.8613 -1.2342 + 70.000 0.4244 1.0234 -1.2342 + 80.000 0.2059 1.1355 -1.2342 + 90.000 0.0000 1.1856 -1.2342 + 100.000 -0.1441 1.1355 -1.2342 + 110.000 -0.2971 1.0234 -1.2342 + 120.000 -0.4476 0.8613 -1.2342 + 130.000 -0.5918 0.6674 -1.2342 + 140.000 -0.7382 0.4639 -1.2342 + 150.000 -0.9224 0.2741 -1.2342 + 160.000 -0.6524 0.1202 -1.2342 + 170.000 -0.3262 0.0908 -1.2342 + 180.000 0.0000 0.0908 -1.2342 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0908 -1.2342 + -170.000 0.3144 0.0908 -1.2342 + -160.000 0.6287 0.1138 -1.2342 + -150.000 0.9431 0.2683 -1.2342 + -140.000 0.7508 0.4587 -1.2342 + -130.000 0.5992 0.6631 -1.2342 + -120.000 0.4516 0.8579 -1.2342 + -110.000 0.2988 1.0211 -1.2342 + -100.000 0.1445 1.1343 -1.2342 + -90.000 0.0000 1.1856 -1.2342 + -80.000 -0.1445 1.1343 -1.2342 + -70.000 -0.2988 1.0211 -1.2342 + -60.000 -0.4516 0.8579 -1.2342 + -50.000 -0.5992 0.6631 -1.2342 + -40.000 -0.7508 0.4587 -1.2342 + -30.000 -0.9431 0.2683 -1.2342 + -20.000 -0.6902 0.1806 -1.2342 + -10.000 -0.6249 0.0929 -2.6310 + -9.000 -0.6076 0.0912 -2.4236 + -8.000 -0.5409 0.0901 -2.1527 + -6.000 -0.3470 0.0891 -1.5882 + -5.000 -0.2454 0.0885 -1.4150 + -4.000 -0.1407 0.0881 -1.2459 + -3.000 -0.0328 0.0879 -1.1374 + -2.000 0.0757 0.0875 -1.1594 + -1.000 0.1839 0.0871 -1.2346 + 0.000 0.2931 0.0870 -1.3151 + 1.000 0.3980 0.0872 -1.3962 + 2.000 0.5039 0.0874 -1.4738 + 3.000 0.6047 0.0879 -1.5498 + 5.000 0.7918 0.0893 -1.7230 + 6.000 0.8825 0.0899 -1.8274 + 7.000 0.9707 0.0904 -1.9577 + 8.000 1.0061 0.0914 -2.0904 + 11.000 1.1120 0.0986 -2.5857 + 12.000 1.1501 0.1018 -2.8480 + 14.000 1.2210 0.1100 -3.4157 + 16.000 1.2697 0.1220 -4.0131 + 18.000 1.3134 0.1361 -4.6623 + 21.000 1.3665 0.1618 -5.7189 + 22.000 1.3754 0.1721 -6.0696 + 23.000 1.3833 0.1829 -6.4424 + 24.000 1.3875 0.1941 -6.8016 + 25.000 1.3889 0.2058 -7.1442 + 26.000 1.3849 0.2179 -7.4518 + 27.000 1.3786 0.2303 -7.7351 + 28.000 1.3703 0.2427 -7.9942 + 29.000 1.3602 0.2554 -8.2252 + 30.000 1.3473 0.2683 -8.4198 + 40.000 1.0725 0.4587 -1.2342 + 50.000 0.8561 0.6631 -1.2342 + 60.000 0.6452 0.8579 -1.2342 + 70.000 0.4269 1.0211 -1.2342 + 80.000 0.2065 1.1343 -1.2342 + 90.000 0.0000 1.1856 -1.2342 + 100.000 -0.1445 1.1343 -1.2342 + 110.000 -0.2988 1.0211 -1.2342 + 120.000 -0.4516 0.8579 -1.2342 + 130.000 -0.5992 0.6631 -1.2342 + 140.000 -0.7508 0.4587 -1.2342 + 150.000 -0.9431 0.2683 -1.2342 + 160.000 -0.6287 0.1138 -1.2342 + 170.000 -0.3144 0.0908 -1.2342 + 180.000 0.0000 0.0908 -1.2342 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0329_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0329_coords.txt new file mode 100644 index 00000000..00d5ebe9 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0329_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0329 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.028484 + 0.027091 0.058831 + 0.060263 0.089532 + 0.105430 0.117836 + 0.161359 0.142554 + 0.226526 0.162174 + 0.299152 0.175281 + 0.377257 0.179988 + 0.458710 0.175693 + 0.541290 0.163772 + 0.622743 0.146064 + 0.700848 0.124660 + 0.773474 0.101839 + 0.838641 0.079535 + 0.894570 0.059015 + 0.939737 0.040853 + 0.972909 0.025130 + 0.993181 0.011587 + 1.000000 0.000000 + 0.993181 -0.009368 + 0.972909 -0.018416 + 0.939737 -0.028604 + 0.894570 -0.040942 + 0.838641 -0.055950 + 0.773474 -0.073518 + 0.700848 -0.092848 + 0.622743 -0.112264 + 0.541290 -0.129574 + 0.458710 -0.142543 + 0.377257 -0.149007 + 0.299152 -0.147357 + 0.226526 -0.138252 + 0.161359 -0.123216 + 0.105430 -0.103514 + 0.060263 -0.080124 + 0.027091 -0.053971 + 0.006819 -0.026499 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0444.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0444.dat new file mode 100644 index 00000000..1957eb43 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0444.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0444 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0444_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.0878 -1.5368 + -170.000 0.2283 0.0878 -1.5368 + -160.000 0.4565 0.1322 -1.5368 + -150.000 0.6848 0.2582 -1.5368 + -140.000 0.5632 0.4133 -1.5368 + -130.000 0.4618 0.5793 -1.5368 + -120.000 0.3556 0.7370 -1.5368 + -110.000 0.2396 0.8679 -1.5368 + -100.000 0.1178 0.9572 -1.5368 + -90.000 0.0000 0.9950 -1.5368 + -80.000 -0.1178 0.9572 -1.5368 + -70.000 -0.2396 0.8679 -1.5368 + -60.000 -0.3556 0.7370 -1.5368 + -50.000 -0.4618 0.5793 -1.5368 + -40.000 -0.5632 0.4133 -1.5368 + -30.000 -0.6848 0.2582 -1.5368 + -20.000 -0.4962 0.1761 -1.5368 + -10.000 -0.4394 0.0939 -2.5360 + -9.000 -0.4172 0.0915 -2.3675 + -8.000 -0.3951 0.0896 -2.2046 + -7.000 -0.3558 0.0886 -2.0171 + -6.000 -0.2861 0.0879 -1.8350 + -5.000 -0.2070 0.0873 -1.6903 + -4.000 -0.1243 0.0868 -1.5548 + -3.000 -0.0400 0.0861 -1.4677 + -2.000 0.0491 0.0859 -1.4671 + -1.000 0.1378 0.0859 -1.5286 + 0.000 0.2262 0.0859 -1.5937 + 1.000 0.3151 0.0859 -1.6608 + 2.000 0.4026 0.0861 -1.7276 + 3.000 0.4885 0.0862 -1.7971 + 4.000 0.5711 0.0865 -1.8669 + 5.000 0.6526 0.0868 -1.9437 + 6.000 0.7191 0.0876 -2.0232 + 7.000 0.7459 0.0889 -2.0832 + 8.000 0.7701 0.0905 -2.1757 + 9.000 0.7998 0.0927 -2.2872 + 10.000 0.8305 0.0952 -2.4037 + 11.000 0.8363 0.0995 -2.4899 + 12.000 0.8581 0.1034 -2.6735 + 13.000 0.8652 0.1092 -2.8298 + 14.000 0.8843 0.1145 -3.0236 + 15.000 0.8978 0.1208 -3.2127 + 16.000 0.9186 0.1269 -3.4359 + 17.000 0.9369 0.1336 -3.6657 + 18.000 0.9538 0.1409 -3.9085 + 19.000 0.9695 0.1486 -4.1517 + 20.000 0.9832 0.1568 -4.4027 + 21.000 0.9959 0.1653 -4.6596 + 22.000 1.0102 0.1735 -4.9355 + 23.000 1.0165 0.1830 -5.1857 + 24.000 1.0214 0.1926 -5.4324 + 25.000 1.0220 0.2026 -5.6651 + 26.000 1.0185 0.2132 -5.8642 + 28.000 1.0003 0.2350 -6.1537 + 29.000 0.9868 0.2472 -6.2271 + 30.000 0.9782 0.2582 -6.3176 + 40.000 0.8047 0.4133 -1.5368 + 50.000 0.6597 0.5793 -1.5368 + 60.000 0.5080 0.7370 -1.5368 + 70.000 0.3422 0.8679 -1.5368 + 80.000 0.1683 0.9572 -1.5368 + 90.000 0.0000 0.9950 -1.5368 + 100.000 -0.1178 0.9572 -1.5368 + 110.000 -0.2396 0.8679 -1.5368 + 120.000 -0.3556 0.7370 -1.5368 + 130.000 -0.4618 0.5793 -1.5368 + 140.000 -0.5632 0.4133 -1.5368 + 150.000 -0.6848 0.2582 -1.5368 + 160.000 -0.4565 0.1322 -1.5368 + 170.000 -0.2283 0.0878 -1.5368 + 180.000 0.0000 0.0878 -1.5368 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1872 -1.5368 + -170.000 0.2392 0.1872 -1.5368 + -160.000 0.4785 0.2228 -1.5368 + -150.000 0.7178 0.3494 -1.5368 + -140.000 0.5834 0.5055 -1.5368 + -130.000 0.4736 0.6726 -1.5368 + -120.000 0.3620 0.8316 -1.5368 + -110.000 0.2423 0.9640 -1.5368 + -100.000 0.1184 1.0549 -1.5368 + -90.000 0.0000 1.0943 -1.5368 + -80.000 -0.1184 1.0549 -1.5368 + -70.000 -0.2423 0.9640 -1.5368 + -60.000 -0.3620 0.8316 -1.5368 + -50.000 -0.4736 0.6726 -1.5368 + -40.000 -0.5834 0.5055 -1.5368 + -30.000 -0.7178 0.3494 -1.5368 + -20.000 -0.5245 0.2703 -1.5368 + -10.000 -0.4731 0.1913 -2.6071 + -9.000 -0.4387 0.1895 -2.4083 + -8.000 -0.4244 0.1880 -2.2550 + -7.000 -0.3621 0.1872 -2.0285 + -6.000 -0.2860 0.1866 -1.8352 + -5.000 -0.2056 0.1861 -1.6890 + -4.000 -0.1199 0.1857 -1.5503 + -3.000 -0.0332 0.1852 -1.4630 + -1.000 0.1450 0.1846 -1.5328 + 0.000 0.2351 0.1845 -1.5992 + 1.000 0.3236 0.1847 -1.6662 + 2.000 0.4130 0.1847 -1.7344 + 5.000 0.6567 0.1859 -1.9457 + 6.000 0.7147 0.1869 -2.0208 + 7.000 0.7543 0.1878 -2.0899 + 9.000 0.8287 0.1906 -2.3229 + 10.000 0.8432 0.1936 -2.4202 + 11.000 0.8686 0.1967 -2.5521 + 12.000 0.8799 0.2011 -2.7194 + 13.000 0.9008 0.2055 -2.9099 + 14.000 0.9219 0.2103 -3.1187 + 15.000 0.9467 0.2153 -3.3452 + 16.000 0.9669 0.2211 -3.5794 + 17.000 0.9875 0.2272 -3.8341 + 18.000 1.0047 0.2340 -4.0877 + 19.000 1.0217 0.2411 -4.3483 + 20.000 1.0326 0.2494 -4.6065 + 21.000 1.0440 0.2578 -4.8698 + 22.000 1.0538 0.2667 -5.1436 + 23.000 1.0571 0.2763 -5.3926 + 24.000 1.0672 0.2850 -5.6949 + 25.000 1.0677 0.2949 -5.9456 + 26.000 1.0682 0.3046 -6.1909 + 27.000 1.0653 0.3148 -6.4081 + 28.000 1.0595 0.3254 -6.5932 + 29.000 1.0375 0.3381 -6.6428 + 30.000 1.0254 0.3494 -6.7387 + 40.000 0.8333 0.5055 -1.5368 + 50.000 0.6766 0.6726 -1.5368 + 60.000 0.5171 0.8316 -1.5368 + 70.000 0.3461 0.9640 -1.5368 + 80.000 0.1692 1.0549 -1.5368 + 90.000 0.0000 1.0943 -1.5368 + 100.000 -0.1184 1.0549 -1.5368 + 110.000 -0.2423 0.9640 -1.5368 + 120.000 -0.3620 0.8316 -1.5368 + 130.000 -0.4736 0.6726 -1.5368 + 140.000 -0.5834 0.5055 -1.5368 + 150.000 -0.7178 0.3494 -1.5368 + 160.000 -0.4785 0.2228 -1.5368 + 170.000 -0.2392 0.1872 -1.5368 + 180.000 0.0000 0.1872 -1.5368 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1952 -1.5368 + -170.000 0.2482 0.1952 -1.5368 + -160.000 0.4963 0.2242 -1.5368 + -150.000 0.7445 0.3514 -1.5368 + -140.000 0.5996 0.5081 -1.5368 + -130.000 0.4832 0.6762 -1.5368 + -120.000 0.3671 0.8361 -1.5368 + -110.000 0.2445 0.9697 -1.5368 + -100.000 0.1190 1.0618 -1.5368 + -90.000 0.0000 1.1024 -1.5368 + -80.000 -0.1190 1.0618 -1.5368 + -70.000 -0.2445 0.9697 -1.5368 + -60.000 -0.3671 0.8361 -1.5368 + -50.000 -0.4832 0.6762 -1.5368 + -40.000 -0.5996 0.5081 -1.5368 + -30.000 -0.7445 0.3514 -1.5368 + -20.000 -0.5447 0.2748 -1.5368 + -10.000 -0.4926 0.1982 -2.6480 + -9.000 -0.4617 0.1966 -2.4507 + -8.000 -0.4322 0.1956 -2.2686 + -7.000 -0.3634 0.1949 -2.0305 + -6.000 -0.2873 0.1943 -1.8371 + -5.000 -0.2040 0.1938 -1.6873 + -4.000 -0.1179 0.1935 -1.5480 + -3.000 -0.0307 0.1932 -1.4615 + -2.000 0.0580 0.1926 -1.4722 + -1.000 0.1481 0.1924 -1.5347 + 0.000 0.2381 0.1924 -1.6009 + 1.000 0.3285 0.1924 -1.6693 + 2.000 0.4157 0.1926 -1.7363 + 4.000 0.5828 0.1932 -1.8778 + 5.000 0.6545 0.1940 -1.9455 + 6.000 0.7170 0.1949 -2.0173 + 7.000 0.7642 0.1956 -2.0997 + 8.000 0.8095 0.1965 -2.2185 + 9.000 0.8348 0.1983 -2.3302 + 10.000 0.8615 0.2007 -2.4451 + 11.000 0.8789 0.2040 -2.5723 + 12.000 0.9009 0.2076 -2.7637 + 13.000 0.9207 0.2120 -2.9553 + 14.000 0.9486 0.2162 -3.1860 + 15.000 0.9707 0.2212 -3.4123 + 16.000 0.9925 0.2266 -3.6554 + 17.000 1.0124 0.2326 -3.9159 + 19.000 1.0445 0.2464 -4.4359 + 20.000 1.0686 0.2527 -4.7530 + 21.000 1.0776 0.2612 -5.0144 + 22.000 1.0832 0.2704 -5.2826 + 23.000 1.0866 0.2800 -5.5449 + 24.000 1.0913 0.2894 -5.8301 + 25.000 1.0933 0.2991 -6.0985 + 26.000 1.0914 0.3091 -6.3395 + 27.000 1.0862 0.3196 -6.5511 + 28.000 1.0802 0.3300 -6.7450 + 29.000 1.0729 0.3406 -6.9167 + 30.000 1.0635 0.3514 -7.0563 + 40.000 0.8565 0.5081 -1.5368 + 50.000 0.6903 0.6762 -1.5368 + 60.000 0.5245 0.8361 -1.5368 + 70.000 0.3493 0.9697 -1.5368 + 80.000 0.1700 1.0618 -1.5368 + 90.000 0.0000 1.1024 -1.5368 + 100.000 -0.1190 1.0618 -1.5368 + 110.000 -0.2445 0.9697 -1.5368 + 120.000 -0.3671 0.8361 -1.5368 + 130.000 -0.4832 0.6762 -1.5368 + 140.000 -0.5996 0.5081 -1.5368 + 150.000 -0.7445 0.3514 -1.5368 + 160.000 -0.4963 0.2242 -1.5368 + 170.000 -0.2482 0.1952 -1.5368 + 180.000 0.0000 0.1952 -1.5368 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1952 -1.5368 + -170.000 0.2974 0.1952 -1.5368 + -160.000 0.5948 0.2359 -1.5368 + -150.000 0.7012 0.3622 -1.5368 + -140.000 0.5733 0.5177 -1.5368 + -130.000 0.4677 0.6842 -1.5368 + -120.000 0.3588 0.8424 -1.5368 + -110.000 0.2409 0.9739 -1.5368 + -100.000 0.1181 1.0639 -1.5368 + -90.000 0.0000 1.1024 -1.5368 + -80.000 -0.1181 1.0639 -1.5368 + -70.000 -0.2409 0.9739 -1.5368 + -60.000 -0.3588 0.8424 -1.5368 + -50.000 -0.4677 0.6842 -1.5368 + -40.000 -0.5733 0.5177 -1.5368 + -30.000 -0.7012 0.3622 -1.5368 + -20.000 -0.6145 0.2662 -1.5368 + -10.000 -0.5000 0.1978 -2.6694 + -9.000 -0.4793 0.1959 -2.4839 + -8.000 -0.4382 0.1952 -2.2793 + -5.000 -0.2037 0.1937 -1.6869 + -4.000 -0.1174 0.1933 -1.5475 + -3.000 -0.0290 0.1930 -1.4533 + -2.000 0.0596 0.1926 -1.4732 + -1.000 0.1497 0.1923 -1.5355 + 0.000 0.2405 0.1922 -1.6025 + 1.000 0.3296 0.1922 -1.6699 + 2.000 0.4167 0.1924 -1.7374 + 3.000 0.5025 0.1927 -1.8069 + 4.000 0.5822 0.1933 -1.8707 + 6.000 0.7216 0.1948 -2.0165 + 7.000 0.7781 0.1953 -2.1120 + 8.000 0.8206 0.1961 -2.2315 + 9.000 0.8437 0.1979 -2.3414 + 11.000 0.8881 0.2035 -2.5902 + 12.000 0.9161 0.2066 -2.7957 + 13.000 0.9453 0.2101 -3.0142 + 15.000 0.9967 0.2188 -3.4850 + 16.000 1.0185 0.2240 -3.7355 + 17.000 1.0407 0.2296 -4.0092 + 18.000 1.0557 0.2362 -4.2653 + 19.000 1.0727 0.2430 -4.5442 + 20.000 1.0841 0.2508 -4.8156 + 22.000 1.0969 0.2686 -5.3459 + 25.000 1.1056 0.2973 -6.1715 + 26.000 1.1045 0.3072 -6.4219 + 30.000 1.0018 0.3622 -5.3262 + 40.000 0.8190 0.5177 -1.5368 + 50.000 0.6682 0.6842 -1.5368 + 60.000 0.5125 0.8424 -1.5368 + 70.000 0.3442 0.9739 -1.5368 + 80.000 0.1688 1.0639 -1.5368 + 90.000 0.0000 1.1024 -1.5368 + 100.000 -0.1181 1.0639 -1.5368 + 110.000 -0.2409 0.9739 -1.5368 + 120.000 -0.3588 0.8424 -1.5368 + 130.000 -0.4677 0.6842 -1.5368 + 140.000 -0.5733 0.5177 -1.5368 + 150.000 -0.7012 0.3622 -1.5368 + 160.000 -0.5948 0.2359 -1.5368 + 170.000 -0.2974 0.1952 -1.5368 + 180.000 0.0000 0.1952 -1.5368 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1952 -1.5368 + -170.000 0.2566 0.1952 -1.5368 + -160.000 0.5133 0.2172 -1.5368 + -150.000 0.7700 0.3450 -1.5368 + -140.000 0.6151 0.5024 -1.5368 + -130.000 0.4924 0.6714 -1.5368 + -120.000 0.3720 0.8324 -1.5368 + -110.000 0.2466 0.9671 -1.5368 + -100.000 0.1195 1.0604 -1.5368 + -90.000 0.0000 1.1024 -1.5368 + -80.000 -0.1195 1.0604 -1.5368 + -70.000 -0.2466 0.9671 -1.5368 + -60.000 -0.3720 0.8324 -1.5368 + -50.000 -0.4924 0.6714 -1.5368 + -40.000 -0.6151 0.5024 -1.5368 + -30.000 -0.7700 0.3450 -1.5368 + -20.000 -0.5594 0.2714 -1.5368 + -10.000 -0.4983 0.1978 -2.6520 + -9.000 -0.5012 0.1956 -2.5277 + -8.000 -0.4434 0.1950 -2.2886 + -6.000 -0.2883 0.1939 -1.8402 + -4.000 -0.1168 0.1932 -1.5469 + -3.000 -0.0284 0.1929 -1.4542 + -2.000 0.0607 0.1926 -1.4738 + -1.000 0.1512 0.1922 -1.5364 + 0.000 0.2416 0.1921 -1.6031 + 1.000 0.3301 0.1922 -1.6704 + 2.000 0.4170 0.1924 -1.7389 + 4.000 0.5807 0.1934 -1.8673 + 5.000 0.6533 0.1941 -1.9374 + 6.000 0.7240 0.1947 -2.0211 + 7.000 0.7933 0.1951 -2.1254 + 8.000 0.8256 0.1960 -2.2370 + 9.000 0.8556 0.1975 -2.3566 + 10.000 0.8686 0.2003 -2.4430 + 11.000 0.9036 0.2026 -2.6210 + 12.000 0.9296 0.2057 -2.8243 + 13.000 0.9579 0.2093 -3.0440 + 14.000 0.9861 0.2131 -3.2803 + 16.000 1.0339 0.2226 -3.7832 + 17.000 1.0521 0.2284 -4.0463 + 18.000 1.0704 0.2346 -4.3160 + 19.000 1.0846 0.2416 -4.5892 + 20.000 1.0952 0.2494 -4.8603 + 21.000 1.1008 0.2581 -5.1154 + 24.000 1.1292 0.2837 -6.0384 + 25.000 1.1319 0.2932 -6.3250 + 26.000 1.1322 0.3029 -6.5941 + 27.000 1.1293 0.3128 -6.8379 + 28.000 1.1221 0.3232 -7.0450 + 29.000 1.1118 0.3340 -7.2160 + 30.000 1.1000 0.3450 -7.3593 + 40.000 0.8788 0.5024 -1.5368 + 50.000 0.7034 0.6714 -1.5368 + 60.000 0.5315 0.8324 -1.5368 + 70.000 0.3523 0.9671 -1.5368 + 80.000 0.1708 1.0604 -1.5368 + 90.000 0.0000 1.1024 -1.5368 + 100.000 -0.1195 1.0604 -1.5368 + 110.000 -0.2466 0.9671 -1.5368 + 120.000 -0.3720 0.8324 -1.5368 + 130.000 -0.4924 0.6714 -1.5368 + 140.000 -0.6151 0.5024 -1.5368 + 150.000 -0.7700 0.3450 -1.5368 + 160.000 -0.5133 0.2172 -1.5368 + 170.000 -0.2566 0.1952 -1.5368 + 180.000 0.0000 0.1952 -1.5368 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1952 -1.5368 + -170.000 0.2703 0.1952 -1.5368 + -160.000 0.5406 0.2196 -1.5368 + -150.000 0.7643 0.3471 -1.5368 + -140.000 0.6117 0.5044 -1.5368 + -130.000 0.4904 0.6730 -1.5368 + -120.000 0.3709 0.8337 -1.5368 + -110.000 0.2462 0.9680 -1.5368 + -100.000 0.1194 1.0609 -1.5368 + -90.000 0.0000 1.1024 -1.5368 + -80.000 -0.1194 1.0609 -1.5368 + -70.000 -0.2462 0.9680 -1.5368 + -60.000 -0.3709 0.8337 -1.5368 + -50.000 -0.4904 0.6730 -1.5368 + -40.000 -0.6117 0.5044 -1.5368 + -30.000 -0.7643 0.3471 -1.5368 + -20.000 -0.5810 0.2686 -1.5368 + -10.000 -0.5080 0.1973 -2.6736 + -7.000 -0.3695 0.1943 -2.0409 + -6.000 -0.2876 0.1939 -1.8319 + -5.000 -0.2035 0.1934 -1.6869 + -4.000 -0.1167 0.1931 -1.5466 + -3.000 -0.0277 0.1929 -1.4563 + -2.000 0.0619 0.1926 -1.4744 + -1.000 0.1520 0.1921 -1.5370 + 0.000 0.2422 0.1921 -1.6033 + 1.000 0.3306 0.1921 -1.6709 + 2.000 0.4176 0.1924 -1.7360 + 3.000 0.5021 0.1927 -1.7997 + 4.000 0.5811 0.1933 -1.8700 + 5.000 0.6538 0.1940 -1.9394 + 6.000 0.7290 0.1945 -2.0259 + 7.000 0.7988 0.1950 -2.1309 + 8.000 0.8306 0.1959 -2.2430 + 10.000 0.8799 0.1997 -2.4620 + 11.000 0.9129 0.2021 -2.6398 + 12.000 0.9445 0.2049 -2.8562 + 13.000 0.9744 0.2081 -3.0830 + 14.000 0.9963 0.2124 -3.3057 + 15.000 1.0211 0.2168 -3.5530 + 17.000 1.0629 0.2274 -4.0818 + 18.000 1.0801 0.2336 -4.3493 + 19.000 1.0941 0.2406 -4.6256 + 20.000 1.1012 0.2487 -4.8838 + 22.000 1.1309 0.2638 -5.5040 + 23.000 1.1367 0.2728 -5.8037 + 24.000 1.1409 0.2820 -6.1025 + 25.000 1.1429 0.2916 -6.3882 + 26.000 1.1421 0.3014 -6.6553 + 27.000 1.1368 0.3116 -6.8875 + 28.000 1.1290 0.3221 -7.0932 + 29.000 1.1198 0.3327 -7.2756 + 30.000 1.0919 0.3471 -6.9240 + 40.000 0.8738 0.5044 -1.5368 + 50.000 0.7005 0.6730 -1.5368 + 60.000 0.5299 0.8337 -1.5368 + 70.000 0.3517 0.9680 -1.5368 + 80.000 0.1706 1.0609 -1.5368 + 90.000 0.0000 1.1024 -1.5368 + 100.000 -0.1194 1.0609 -1.5368 + 110.000 -0.2462 0.9680 -1.5368 + 120.000 -0.3709 0.8337 -1.5368 + 130.000 -0.4904 0.6730 -1.5368 + 140.000 -0.6117 0.5044 -1.5368 + 150.000 -0.7643 0.3471 -1.5368 + 160.000 -0.5406 0.2196 -1.5368 + 170.000 -0.2703 0.1952 -1.5368 + 180.000 0.0000 0.1952 -1.5368 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1952 -1.5368 + -170.000 0.2605 0.1952 -1.5368 + -160.000 0.5210 0.2143 -1.5368 + -150.000 0.7815 0.3423 -1.5368 + -140.000 0.6221 0.5001 -1.5368 + -130.000 0.4965 0.6694 -1.5368 + -120.000 0.3742 0.8309 -1.5368 + -110.000 0.2476 0.9661 -1.5368 + -100.000 0.1198 1.0599 -1.5368 + -90.000 0.0000 1.1024 -1.5368 + -80.000 -0.1198 1.0599 -1.5368 + -70.000 -0.2476 0.9661 -1.5368 + -60.000 -0.3742 0.8309 -1.5368 + -50.000 -0.4965 0.6694 -1.5368 + -40.000 -0.6221 0.5001 -1.5368 + -30.000 -0.7815 0.3423 -1.5368 + -20.000 -0.5719 0.2696 -1.5368 + -10.000 -0.5178 0.1970 -2.6942 + -9.000 -0.5035 0.1956 -2.5224 + -8.000 -0.4482 0.1946 -2.2979 + -6.000 -0.2875 0.1938 -1.8301 + -5.000 -0.2034 0.1933 -1.6867 + -4.000 -0.1166 0.1929 -1.5465 + -3.000 -0.0271 0.1928 -1.4566 + -2.000 0.0627 0.1925 -1.4749 + -1.000 0.1524 0.1921 -1.5371 + 0.000 0.2429 0.1921 -1.6039 + 1.000 0.3298 0.1922 -1.6711 + 2.000 0.4175 0.1924 -1.7354 + 3.000 0.5011 0.1928 -1.7984 + 5.000 0.6561 0.1940 -1.9418 + 6.000 0.7312 0.1945 -2.0284 + 7.000 0.8043 0.1948 -2.1363 + 8.000 0.8337 0.1957 -2.2463 + 11.000 0.9214 0.2016 -2.6567 + 12.000 0.9530 0.2044 -2.8740 + 14.000 1.0117 0.2112 -3.3444 + 16.000 1.0521 0.2210 -3.8395 + 18.000 1.0883 0.2327 -4.3774 + 21.000 1.1323 0.2540 -5.2529 + 22.000 1.1397 0.2626 -5.5436 + 23.000 1.1462 0.2715 -5.8524 + 24.000 1.1497 0.2808 -6.1500 + 25.000 1.1508 0.2905 -6.4340 + 26.000 1.1476 0.3006 -6.6888 + 27.000 1.1424 0.3108 -6.9235 + 28.000 1.1355 0.3211 -7.1382 + 29.000 1.1271 0.3316 -7.3297 + 30.000 1.1164 0.3423 -7.4909 + 40.000 0.8887 0.5001 -1.5368 + 50.000 0.7093 0.6694 -1.5368 + 60.000 0.5346 0.8309 -1.5368 + 70.000 0.3537 0.9661 -1.5368 + 80.000 0.1711 1.0599 -1.5368 + 90.000 0.0000 1.1024 -1.5368 + 100.000 -0.1198 1.0599 -1.5368 + 110.000 -0.2476 0.9661 -1.5368 + 120.000 -0.3742 0.8309 -1.5368 + 130.000 -0.4965 0.6694 -1.5368 + 140.000 -0.6221 0.5001 -1.5368 + 150.000 -0.7815 0.3423 -1.5368 + 160.000 -0.5210 0.2143 -1.5368 + 170.000 -0.2605 0.1952 -1.5368 + 180.000 0.0000 0.1952 -1.5368 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0444_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0444_coords.txt new file mode 100644 index 00000000..690c1efd --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0444_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0444 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.038173 + 0.027091 0.077420 + 0.060263 0.116187 + 0.105430 0.151821 + 0.161359 0.183011 + 0.226526 0.208215 + 0.299152 0.226025 + 0.377257 0.234704 + 0.458710 0.233617 + 0.541290 0.223836 + 0.622743 0.206871 + 0.700848 0.184493 + 0.773474 0.158713 + 0.838641 0.131307 + 0.894570 0.103562 + 0.939737 0.076248 + 0.972909 0.049770 + 0.993181 0.024310 + 1.000000 0.000000 + 0.993181 -0.022489 + 0.972909 -0.044262 + 0.939737 -0.066198 + 0.894570 -0.088734 + 0.838641 -0.111957 + 0.773474 -0.135477 + 0.700848 -0.158393 + 0.622743 -0.179140 + 0.541290 -0.195779 + 0.458710 -0.206420 + 0.377257 -0.209286 + 0.299152 -0.203115 + 0.226526 -0.188588 + 0.161359 -0.167145 + 0.105430 -0.140070 + 0.060263 -0.108468 + 0.027091 -0.073433 + 0.006819 -0.036544 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0629.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0629.dat new file mode 100644 index 00000000..c6856a16 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0629.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0629 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0629_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.1584 -2.0237 + -170.000 0.1523 0.1584 -2.0237 + -160.000 0.3046 0.1880 -2.0237 + -150.000 0.4569 0.2721 -2.0237 + -140.000 0.3758 0.3756 -2.0237 + -130.000 0.3081 0.4864 -2.0237 + -120.000 0.2373 0.5916 -2.0237 + -110.000 0.1599 0.6790 -2.0237 + -100.000 0.0786 0.7385 -2.0237 + -90.000 0.0000 0.7637 -2.0237 + -80.000 -0.0786 0.7385 -2.0237 + -70.000 -0.1599 0.6790 -2.0237 + -60.000 -0.2373 0.5916 -2.0237 + -50.000 -0.3081 0.4864 -2.0237 + -40.000 -0.3758 0.3756 -2.0237 + -30.000 -0.4569 0.2721 -2.0237 + -20.000 -0.3311 0.2173 -2.0237 + -10.000 -0.2932 0.1625 -2.6904 + -9.000 -0.2784 0.1609 -2.5779 + -8.000 -0.2637 0.1596 -2.4693 + -7.000 -0.2374 0.1590 -2.3441 + -6.000 -0.1909 0.1585 -2.2226 + -5.000 -0.1381 0.1581 -2.1261 + -4.000 -0.0829 0.1578 -2.0357 + -3.000 -0.0267 0.1573 -1.9776 + -2.000 0.0328 0.1572 -1.9772 + -1.000 0.0920 0.1571 -2.0182 + 0.000 0.1509 0.1572 -2.0616 + 1.000 0.2102 0.1572 -2.1064 + 2.000 0.2686 0.1573 -2.1510 + 3.000 0.3259 0.1574 -2.1973 + 4.000 0.3811 0.1576 -2.2439 + 5.000 0.4355 0.1578 -2.2951 + 6.000 0.4799 0.1583 -2.3482 + 7.000 0.4977 0.1591 -2.3882 + 8.000 0.5139 0.1602 -2.4500 + 9.000 0.5337 0.1617 -2.5244 + 10.000 0.5542 0.1633 -2.6021 + 11.000 0.5581 0.1662 -2.6596 + 12.000 0.5726 0.1688 -2.7821 + 13.000 0.5773 0.1727 -2.8865 + 14.000 0.5900 0.1762 -3.0158 + 15.000 0.5991 0.1804 -3.1420 + 16.000 0.6130 0.1845 -3.2909 + 17.000 0.6251 0.1889 -3.4442 + 18.000 0.6364 0.1938 -3.6062 + 19.000 0.6469 0.1990 -3.7685 + 20.000 0.6560 0.2045 -3.9359 + 21.000 0.6645 0.2101 -4.1074 + 22.000 0.6741 0.2156 -4.2915 + 23.000 0.6782 0.2219 -4.4584 + 24.000 0.6815 0.2283 -4.6230 + 25.000 0.6820 0.2350 -4.7783 + 26.000 0.6796 0.2421 -4.9112 + 28.000 0.6675 0.2567 -5.1044 + 29.000 0.6584 0.2648 -5.1534 + 30.000 0.6527 0.2721 -5.2137 + 40.000 0.5369 0.3756 -2.0237 + 50.000 0.4402 0.4864 -2.0237 + 60.000 0.3390 0.5916 -2.0237 + 70.000 0.2284 0.6790 -2.0237 + 80.000 0.1123 0.7385 -2.0237 + 90.000 0.0000 0.7637 -2.0237 + 100.000 -0.0786 0.7385 -2.0237 + 110.000 -0.1599 0.6790 -2.0237 + 120.000 -0.2373 0.5916 -2.0237 + 130.000 -0.3081 0.4864 -2.0237 + 140.000 -0.3758 0.3756 -2.0237 + 150.000 -0.4569 0.2721 -2.0237 + 160.000 -0.3046 0.1880 -2.0237 + 170.000 -0.1523 0.1584 -2.0237 + 180.000 0.0000 0.1584 -2.0237 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.3478 -2.0237 + -170.000 0.1596 0.3478 -2.0237 + -160.000 0.3193 0.3716 -2.0237 + -150.000 0.4789 0.4561 -2.0237 + -140.000 0.3893 0.5602 -2.0237 + -130.000 0.3160 0.6718 -2.0237 + -120.000 0.2415 0.7778 -2.0237 + -110.000 0.1617 0.8662 -2.0237 + -100.000 0.0790 0.9268 -2.0237 + -90.000 0.0000 0.9531 -2.0237 + -80.000 -0.0790 0.9268 -2.0237 + -70.000 -0.1617 0.8662 -2.0237 + -60.000 -0.2415 0.7778 -2.0237 + -50.000 -0.3160 0.6718 -2.0237 + -40.000 -0.3893 0.5602 -2.0237 + -30.000 -0.4789 0.4561 -2.0237 + -20.000 -0.3500 0.4033 -2.0237 + -10.000 -0.3157 0.3505 -2.7378 + -9.000 -0.2927 0.3494 -2.6052 + -8.000 -0.2832 0.3484 -2.5029 + -7.000 -0.2416 0.3478 -2.3517 + -6.000 -0.1909 0.3474 -2.2228 + -5.000 -0.1372 0.3471 -2.1252 + -4.000 -0.0800 0.3468 -2.0327 + -3.000 -0.0222 0.3465 -1.9744 + -1.000 0.0968 0.3461 -2.0210 + 0.000 0.1568 0.3461 -2.0653 + 1.000 0.2159 0.3462 -2.1100 + 2.000 0.2756 0.3462 -2.1555 + 5.000 0.4382 0.3470 -2.2965 + 6.000 0.4769 0.3477 -2.3466 + 7.000 0.5033 0.3483 -2.3927 + 9.000 0.5529 0.3501 -2.5482 + 10.000 0.5627 0.3521 -2.6131 + 11.000 0.5796 0.3542 -2.7011 + 12.000 0.5872 0.3571 -2.8127 + 13.000 0.6011 0.3601 -2.9399 + 14.000 0.6151 0.3633 -3.0792 + 15.000 0.6317 0.3666 -3.2303 + 16.000 0.6451 0.3705 -3.3866 + 17.000 0.6589 0.3745 -3.5565 + 18.000 0.6704 0.3791 -3.7258 + 19.000 0.6818 0.3838 -3.8997 + 20.000 0.6890 0.3894 -4.0719 + 21.000 0.6966 0.3950 -4.2477 + 22.000 0.7031 0.4009 -4.4304 + 23.000 0.7053 0.4073 -4.5965 + 24.000 0.7121 0.4131 -4.7982 + 25.000 0.7124 0.4197 -4.9655 + 26.000 0.7128 0.4262 -5.1291 + 27.000 0.7109 0.4330 -5.2741 + 28.000 0.7070 0.4400 -5.3976 + 29.000 0.6923 0.4485 -5.4307 + 30.000 0.6842 0.4561 -5.4947 + 40.000 0.5561 0.5602 -2.0237 + 50.000 0.4515 0.6718 -2.0237 + 60.000 0.3450 0.7778 -2.0237 + 70.000 0.2309 0.8662 -2.0237 + 80.000 0.1129 0.9268 -2.0237 + 90.000 0.0000 0.9531 -2.0237 + 100.000 -0.0790 0.9268 -2.0237 + 110.000 -0.1617 0.8662 -2.0237 + 120.000 -0.2415 0.7778 -2.0237 + 130.000 -0.3160 0.6718 -2.0237 + 140.000 -0.3893 0.5602 -2.0237 + 150.000 -0.4789 0.4561 -2.0237 + 160.000 -0.3193 0.3716 -2.0237 + 170.000 -0.1596 0.3478 -2.0237 + 180.000 0.0000 0.3478 -2.0237 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.3632 -2.0237 + -170.000 0.1656 0.3632 -2.0237 + -160.000 0.3312 0.3825 -2.0237 + -150.000 0.4967 0.4674 -2.0237 + -140.000 0.4001 0.5720 -2.0237 + -130.000 0.3224 0.6841 -2.0237 + -120.000 0.2450 0.7908 -2.0237 + -110.000 0.1631 0.8799 -2.0237 + -100.000 0.0794 0.9414 -2.0237 + -90.000 0.0000 0.9685 -2.0237 + -80.000 -0.0794 0.9414 -2.0237 + -70.000 -0.1631 0.8799 -2.0237 + -60.000 -0.2450 0.7908 -2.0237 + -50.000 -0.3224 0.6841 -2.0237 + -40.000 -0.4001 0.5720 -2.0237 + -30.000 -0.4967 0.4674 -2.0237 + -20.000 -0.3634 0.4163 -2.0237 + -10.000 -0.3287 0.3652 -2.7651 + -9.000 -0.3081 0.3641 -2.6335 + -8.000 -0.2884 0.3634 -2.5120 + -7.000 -0.2425 0.3630 -2.3531 + -6.000 -0.1917 0.3626 -2.2240 + -5.000 -0.1361 0.3622 -2.1241 + -4.000 -0.0786 0.3620 -2.0311 + -3.000 -0.0205 0.3618 -1.9734 + -2.000 0.0387 0.3614 -1.9806 + -1.000 0.0989 0.3613 -2.0223 + 0.000 0.1588 0.3613 -2.0664 + 1.000 0.2192 0.3613 -2.1121 + 2.000 0.2774 0.3614 -2.1568 + 4.000 0.3889 0.3619 -2.2512 + 5.000 0.4367 0.3624 -2.2964 + 6.000 0.4784 0.3630 -2.3443 + 7.000 0.5099 0.3634 -2.3993 + 8.000 0.5401 0.3640 -2.4785 + 9.000 0.5570 0.3652 -2.5530 + 10.000 0.5749 0.3668 -2.6297 + 11.000 0.5865 0.3690 -2.7146 + 12.000 0.6012 0.3715 -2.8423 + 13.000 0.6143 0.3743 -2.9702 + 14.000 0.6330 0.3772 -3.1241 + 15.000 0.6477 0.3805 -3.2751 + 16.000 0.6622 0.3841 -3.4373 + 17.000 0.6755 0.3881 -3.6111 + 19.000 0.6970 0.3973 -3.9581 + 20.000 0.7131 0.4015 -4.1697 + 21.000 0.7191 0.4072 -4.3441 + 22.000 0.7228 0.4134 -4.5231 + 23.000 0.7251 0.4197 -4.6981 + 24.000 0.7282 0.4260 -4.8884 + 25.000 0.7295 0.4325 -5.0675 + 26.000 0.7282 0.4392 -5.2283 + 27.000 0.7248 0.4462 -5.3695 + 28.000 0.7208 0.4531 -5.4989 + 29.000 0.7159 0.4602 -5.6135 + 30.000 0.7096 0.4674 -5.7066 + 40.000 0.5715 0.5720 -2.0237 + 50.000 0.4606 0.6841 -2.0237 + 60.000 0.3500 0.7908 -2.0237 + 70.000 0.2331 0.8799 -2.0237 + 80.000 0.1134 0.9414 -2.0237 + 90.000 0.0000 0.9685 -2.0237 + 100.000 -0.0794 0.9414 -2.0237 + 110.000 -0.1631 0.8799 -2.0237 + 120.000 -0.2450 0.7908 -2.0237 + 130.000 -0.3224 0.6841 -2.0237 + 140.000 -0.4001 0.5720 -2.0237 + 150.000 -0.4967 0.4674 -2.0237 + 160.000 -0.3312 0.3825 -2.0237 + 170.000 -0.1656 0.3632 -2.0237 + 180.000 0.0000 0.3632 -2.0237 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.3632 -2.0237 + -170.000 0.1984 0.3632 -2.0237 + -160.000 0.3969 0.3903 -2.0237 + -150.000 0.4679 0.4746 -2.0237 + -140.000 0.3825 0.5784 -2.0237 + -130.000 0.3121 0.6895 -2.0237 + -120.000 0.2394 0.7950 -2.0237 + -110.000 0.1608 0.8828 -2.0237 + -100.000 0.0788 0.9428 -2.0237 + -90.000 0.0000 0.9685 -2.0237 + -80.000 -0.0788 0.9428 -2.0237 + -70.000 -0.1608 0.8828 -2.0237 + -60.000 -0.2394 0.7950 -2.0237 + -50.000 -0.3121 0.6895 -2.0237 + -40.000 -0.3825 0.5784 -2.0237 + -30.000 -0.4679 0.4746 -2.0237 + -20.000 -0.4101 0.4105 -2.0237 + -10.000 -0.3337 0.3649 -2.7794 + -9.000 -0.3198 0.3637 -2.6556 + -8.000 -0.2924 0.3632 -2.5191 + -5.000 -0.1360 0.3621 -2.1238 + -4.000 -0.0783 0.3619 -2.0308 + -3.000 -0.0193 0.3617 -1.9679 + -2.000 0.0398 0.3614 -1.9812 + -1.000 0.0999 0.3612 -2.0228 + 0.000 0.1605 0.3612 -2.0675 + 1.000 0.2199 0.3612 -2.1125 + 2.000 0.2781 0.3613 -2.1575 + 3.000 0.3353 0.3615 -2.2039 + 4.000 0.3885 0.3619 -2.2464 + 6.000 0.4815 0.3629 -2.3438 + 7.000 0.5192 0.3632 -2.4075 + 8.000 0.5476 0.3638 -2.4872 + 9.000 0.5629 0.3650 -2.5606 + 11.000 0.5926 0.3687 -2.7266 + 12.000 0.6113 0.3708 -2.8637 + 13.000 0.6308 0.3731 -3.0095 + 15.000 0.6651 0.3789 -3.3236 + 16.000 0.6796 0.3824 -3.4907 + 17.000 0.6944 0.3861 -3.6734 + 18.000 0.7045 0.3905 -3.8443 + 19.000 0.7158 0.3950 -4.0304 + 20.000 0.7234 0.4003 -4.2115 + 22.000 0.7319 0.4121 -4.5653 + 25.000 0.7378 0.4313 -5.1162 + 26.000 0.7370 0.4379 -5.2833 + 30.000 0.6684 0.4746 -4.5522 + 40.000 0.5465 0.5784 -2.0237 + 50.000 0.4458 0.6895 -2.0237 + 60.000 0.3420 0.7950 -2.0237 + 70.000 0.2297 0.8828 -2.0237 + 80.000 0.1126 0.9428 -2.0237 + 90.000 0.0000 0.9685 -2.0237 + 100.000 -0.0788 0.9428 -2.0237 + 110.000 -0.1608 0.8828 -2.0237 + 120.000 -0.2394 0.7950 -2.0237 + 130.000 -0.3121 0.6895 -2.0237 + 140.000 -0.3825 0.5784 -2.0237 + 150.000 -0.4679 0.4746 -2.0237 + 160.000 -0.3969 0.3903 -2.0237 + 170.000 -0.1984 0.3632 -2.0237 + 180.000 0.0000 0.3632 -2.0237 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.3632 -2.0237 + -170.000 0.1712 0.3632 -2.0237 + -160.000 0.3425 0.3778 -2.0237 + -150.000 0.5138 0.4631 -2.0237 + -140.000 0.4104 0.5681 -2.0237 + -130.000 0.3286 0.6809 -2.0237 + -120.000 0.2482 0.7884 -2.0237 + -110.000 0.1646 0.8782 -2.0237 + -100.000 0.0798 0.9405 -2.0237 + -90.000 0.0000 0.9685 -2.0237 + -80.000 -0.0798 0.9405 -2.0237 + -70.000 -0.1646 0.8782 -2.0237 + -60.000 -0.2482 0.7884 -2.0237 + -50.000 -0.3286 0.6809 -2.0237 + -40.000 -0.4104 0.5681 -2.0237 + -30.000 -0.5138 0.4631 -2.0237 + -20.000 -0.3732 0.4140 -2.0237 + -10.000 -0.3325 0.3649 -2.7678 + -9.000 -0.3344 0.3635 -2.6848 + -8.000 -0.2959 0.3630 -2.5253 + -6.000 -0.1924 0.3623 -2.2261 + -4.000 -0.0779 0.3618 -2.0304 + -3.000 -0.0189 0.3617 -1.9686 + -2.000 0.0405 0.3614 -1.9816 + -1.000 0.1009 0.3612 -2.0234 + 0.000 0.1612 0.3611 -2.0679 + 1.000 0.2203 0.3612 -2.1128 + 2.000 0.2782 0.3613 -2.1585 + 4.000 0.3875 0.3620 -2.2442 + 5.000 0.4359 0.3624 -2.2910 + 6.000 0.4831 0.3628 -2.3468 + 7.000 0.5293 0.3631 -2.4164 + 8.000 0.5509 0.3637 -2.4909 + 9.000 0.5709 0.3647 -2.5707 + 10.000 0.5796 0.3665 -2.6284 + 11.000 0.6029 0.3681 -2.7471 + 12.000 0.6203 0.3702 -2.8827 + 13.000 0.6392 0.3725 -3.0293 + 14.000 0.6580 0.3751 -3.1870 + 16.000 0.6899 0.3815 -3.5226 + 17.000 0.7020 0.3853 -3.6982 + 18.000 0.7142 0.3895 -3.8781 + 19.000 0.7237 0.3941 -4.0604 + 20.000 0.7308 0.3993 -4.2413 + 21.000 0.7345 0.4052 -4.4116 + 24.000 0.7535 0.4222 -5.0274 + 25.000 0.7553 0.4285 -5.2186 + 26.000 0.7555 0.4350 -5.3982 + 27.000 0.7535 0.4416 -5.5609 + 28.000 0.7487 0.4485 -5.6991 + 29.000 0.7419 0.4558 -5.8132 + 30.000 0.7340 0.4631 -5.9088 + 40.000 0.5864 0.5681 -2.0237 + 50.000 0.4694 0.6809 -2.0237 + 60.000 0.3546 0.7884 -2.0237 + 70.000 0.2351 0.8782 -2.0237 + 80.000 0.1139 0.9405 -2.0237 + 90.000 0.0000 0.9685 -2.0237 + 100.000 -0.0798 0.9405 -2.0237 + 110.000 -0.1646 0.8782 -2.0237 + 120.000 -0.2482 0.7884 -2.0237 + 130.000 -0.3286 0.6809 -2.0237 + 140.000 -0.4104 0.5681 -2.0237 + 150.000 -0.5138 0.4631 -2.0237 + 160.000 -0.3425 0.3778 -2.0237 + 170.000 -0.1712 0.3632 -2.0237 + 180.000 0.0000 0.3632 -2.0237 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.3632 -2.0237 + -170.000 0.1804 0.3632 -2.0237 + -160.000 0.3607 0.3794 -2.0237 + -150.000 0.5100 0.4645 -2.0237 + -140.000 0.4081 0.5695 -2.0237 + -130.000 0.3272 0.6820 -2.0237 + -120.000 0.2475 0.7892 -2.0237 + -110.000 0.1643 0.8788 -2.0237 + -100.000 0.0797 0.9408 -2.0237 + -90.000 0.0000 0.9685 -2.0237 + -80.000 -0.0797 0.9408 -2.0237 + -70.000 -0.1643 0.8788 -2.0237 + -60.000 -0.2475 0.7892 -2.0237 + -50.000 -0.3272 0.6820 -2.0237 + -40.000 -0.4081 0.5695 -2.0237 + -30.000 -0.5100 0.4645 -2.0237 + -20.000 -0.3877 0.4121 -2.0237 + -10.000 -0.3390 0.3646 -2.7822 + -7.000 -0.2466 0.3626 -2.3600 + -6.000 -0.1919 0.3623 -2.2206 + -5.000 -0.1358 0.3620 -2.1238 + -4.000 -0.0779 0.3618 -2.0302 + -3.000 -0.0185 0.3616 -1.9699 + -2.000 0.0413 0.3614 -1.9820 + -1.000 0.1014 0.3611 -2.0238 + 0.000 0.1616 0.3611 -2.0680 + 1.000 0.2206 0.3611 -2.1132 + 2.000 0.2786 0.3613 -2.1566 + 3.000 0.3350 0.3615 -2.1991 + 4.000 0.3877 0.3619 -2.2460 + 5.000 0.4363 0.3624 -2.2923 + 6.000 0.4864 0.3627 -2.3500 + 7.000 0.5330 0.3630 -2.4201 + 8.000 0.5543 0.3636 -2.4949 + 10.000 0.5871 0.3661 -2.6410 + 11.000 0.6091 0.3678 -2.7596 + 12.000 0.6303 0.3696 -2.9040 + 13.000 0.6502 0.3718 -3.0554 + 14.000 0.6648 0.3746 -3.2040 + 15.000 0.6814 0.3776 -3.3690 + 17.000 0.7092 0.3846 -3.7218 + 18.000 0.7207 0.3888 -3.9004 + 19.000 0.7301 0.3934 -4.0847 + 20.000 0.7348 0.3989 -4.2570 + 22.000 0.7546 0.4089 -4.6708 + 23.000 0.7585 0.4150 -4.8708 + 24.000 0.7613 0.4211 -5.0702 + 25.000 0.7626 0.4275 -5.2609 + 26.000 0.7621 0.4341 -5.4390 + 27.000 0.7585 0.4408 -5.5940 + 28.000 0.7534 0.4479 -5.7312 + 29.000 0.7472 0.4549 -5.8529 + 30.000 0.7286 0.4645 -5.6184 + 40.000 0.5831 0.5695 -2.0237 + 50.000 0.4674 0.6820 -2.0237 + 60.000 0.3536 0.7892 -2.0237 + 70.000 0.2347 0.8788 -2.0237 + 80.000 0.1138 0.9408 -2.0237 + 90.000 0.0000 0.9685 -2.0237 + 100.000 -0.0797 0.9408 -2.0237 + 110.000 -0.1643 0.8788 -2.0237 + 120.000 -0.2475 0.7892 -2.0237 + 130.000 -0.3272 0.6820 -2.0237 + 140.000 -0.4081 0.5695 -2.0237 + 150.000 -0.5100 0.4645 -2.0237 + 160.000 -0.3607 0.3794 -2.0237 + 170.000 -0.1804 0.3632 -2.0237 + 180.000 0.0000 0.3632 -2.0237 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.3632 -2.0237 + -170.000 0.1738 0.3632 -2.0237 + -160.000 0.3476 0.3759 -2.0237 + -150.000 0.5215 0.4613 -2.0237 + -140.000 0.4151 0.5666 -2.0237 + -130.000 0.3313 0.6796 -2.0237 + -120.000 0.2497 0.7873 -2.0237 + -110.000 0.1652 0.8775 -2.0237 + -100.000 0.0799 0.9401 -2.0237 + -90.000 0.0000 0.9685 -2.0237 + -80.000 -0.0799 0.9401 -2.0237 + -70.000 -0.1652 0.8775 -2.0237 + -60.000 -0.2497 0.7873 -2.0237 + -50.000 -0.3313 0.6796 -2.0237 + -40.000 -0.4151 0.5666 -2.0237 + -30.000 -0.5215 0.4613 -2.0237 + -20.000 -0.3816 0.4128 -2.0237 + -10.000 -0.3455 0.3643 -2.7960 + -9.000 -0.3360 0.3634 -2.6813 + -8.000 -0.2991 0.3628 -2.5315 + -6.000 -0.1918 0.3622 -2.2194 + -5.000 -0.1357 0.3619 -2.1237 + -4.000 -0.0778 0.3617 -2.0301 + -3.000 -0.0181 0.3616 -1.9701 + -2.000 0.0418 0.3614 -1.9823 + -1.000 0.1017 0.3611 -2.0239 + 0.000 0.1621 0.3611 -2.0684 + 1.000 0.2201 0.3612 -2.1133 + 2.000 0.2786 0.3613 -2.1562 + 3.000 0.3343 0.3616 -2.1982 + 5.000 0.4378 0.3623 -2.2939 + 6.000 0.4879 0.3627 -2.3517 + 7.000 0.5367 0.3629 -2.4237 + 8.000 0.5563 0.3635 -2.4971 + 11.000 0.6148 0.3675 -2.7710 + 12.000 0.6359 0.3693 -2.9159 + 14.000 0.6751 0.3738 -3.2298 + 16.000 0.7020 0.3804 -3.5602 + 18.000 0.7262 0.3882 -3.9191 + 21.000 0.7555 0.4024 -4.5033 + 22.000 0.7605 0.4081 -4.6972 + 23.000 0.7648 0.4141 -4.9033 + 24.000 0.7671 0.4203 -5.1019 + 25.000 0.7679 0.4267 -5.2914 + 26.000 0.7657 0.4335 -5.4614 + 27.000 0.7623 0.4403 -5.6180 + 28.000 0.7577 0.4472 -5.7613 + 29.000 0.7521 0.4542 -5.8891 + 30.000 0.7449 0.4613 -5.9967 + 40.000 0.5930 0.5666 -2.0237 + 50.000 0.4733 0.6796 -2.0237 + 60.000 0.3567 0.7873 -2.0237 + 70.000 0.2360 0.8775 -2.0237 + 80.000 0.1142 0.9401 -2.0237 + 90.000 0.0000 0.9685 -2.0237 + 100.000 -0.0799 0.9401 -2.0237 + 110.000 -0.1652 0.8775 -2.0237 + 120.000 -0.2497 0.7873 -2.0237 + 130.000 -0.3313 0.6796 -2.0237 + 140.000 -0.4151 0.5666 -2.0237 + 150.000 -0.5215 0.4613 -2.0237 + 160.000 -0.3476 0.3759 -2.0237 + 170.000 -0.1738 0.3632 -2.0237 + 180.000 0.0000 0.3632 -2.0237 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0629_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0629_coords.txt new file mode 100644 index 00000000..0384c9cb --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0629_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0629 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.053204 + 0.027091 0.106260 + 0.060263 0.157538 + 0.105430 0.204545 + 0.161359 0.245774 + 0.226526 0.279641 + 0.299152 0.304748 + 0.377257 0.319589 + 0.458710 0.323479 + 0.541290 0.317019 + 0.622743 0.301206 + 0.700848 0.277317 + 0.773474 0.246947 + 0.838641 0.211626 + 0.894570 0.172671 + 0.939737 0.131160 + 0.972909 0.087998 + 0.993181 0.044048 + 1.000000 0.000000 + 0.993181 -0.042845 + 0.972909 -0.084360 + 0.939737 -0.124522 + 0.894570 -0.162878 + 0.838641 -0.198845 + 0.773474 -0.231600 + 0.700848 -0.260079 + 0.622743 -0.282891 + 0.541290 -0.298488 + 0.458710 -0.305516 + 0.377257 -0.302801 + 0.299152 -0.289617 + 0.226526 -0.266678 + 0.161359 -0.235296 + 0.105430 -0.196784 + 0.060263 -0.152440 + 0.027091 -0.103626 + 0.006819 -0.052128 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0864.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0864.dat new file mode 100644 index 00000000..d9dc199d --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0864.dat @@ -0,0 +1,560 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_0864 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_0864_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 72 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.2481 -2.6421 + -170.000 0.0558 0.2481 -2.6421 + -160.000 0.1117 0.2589 -2.6421 + -150.000 0.1675 0.2898 -2.6421 + -140.000 0.1378 0.3277 -2.6421 + -130.000 0.1130 0.3683 -2.6421 + -120.000 0.0870 0.4069 -2.6421 + -110.000 0.0586 0.4389 -2.6421 + -100.000 0.0288 0.4607 -2.6421 + -90.000 0.0000 0.4700 -2.6421 + -80.000 -0.0288 0.4607 -2.6421 + -70.000 -0.0586 0.4389 -2.6421 + -60.000 -0.0870 0.4069 -2.6421 + -50.000 -0.1130 0.3683 -2.6421 + -40.000 -0.1378 0.3277 -2.6421 + -30.000 -0.1675 0.2898 -2.6421 + -20.000 -0.1214 0.2697 -2.6421 + -10.000 -0.1075 0.2496 -2.8865 + -9.000 -0.1021 0.2490 -2.8453 + -8.000 -0.0966 0.2485 -2.8054 + -7.000 -0.0870 0.2483 -2.7596 + -6.000 -0.0700 0.2481 -2.7150 + -5.000 -0.0506 0.2480 -2.6796 + -4.000 -0.0304 0.2479 -2.6465 + -3.000 -0.0098 0.2477 -2.6252 + -2.000 0.0120 0.2476 -2.6251 + -1.000 0.0337 0.2476 -2.6401 + 0.000 0.0553 0.2476 -2.6560 + 1.000 0.0771 0.2476 -2.6724 + 2.000 0.0985 0.2477 -2.6888 + 3.000 0.1195 0.2477 -2.7058 + 4.000 0.1397 0.2478 -2.7228 + 5.000 0.1596 0.2479 -2.7416 + 6.000 0.1759 0.2481 -2.7611 + 7.000 0.1825 0.2484 -2.7757 + 8.000 0.1884 0.2488 -2.7984 + 9.000 0.1956 0.2493 -2.8257 + 10.000 0.2031 0.2499 -2.8541 + 11.000 0.2046 0.2510 -2.8752 + 12.000 0.2099 0.2519 -2.9201 + 13.000 0.2116 0.2533 -2.9584 + 14.000 0.2163 0.2546 -3.0058 + 15.000 0.2196 0.2562 -3.0520 + 16.000 0.2247 0.2577 -3.1066 + 17.000 0.2292 0.2593 -3.1628 + 18.000 0.2333 0.2611 -3.2222 + 19.000 0.2371 0.2630 -3.2817 + 20.000 0.2405 0.2650 -3.3431 + 21.000 0.2436 0.2671 -3.4059 + 22.000 0.2471 0.2691 -3.4734 + 23.000 0.2486 0.2714 -3.5346 + 24.000 0.2498 0.2737 -3.5950 + 25.000 0.2500 0.2762 -3.6519 + 26.000 0.2491 0.2788 -3.7006 + 28.000 0.2447 0.2841 -3.7714 + 29.000 0.2414 0.2871 -3.7894 + 30.000 0.2393 0.2898 -3.8115 + 40.000 0.1968 0.3277 -2.6421 + 50.000 0.1614 0.3683 -2.6421 + 60.000 0.1243 0.4069 -2.6421 + 70.000 0.0837 0.4389 -2.6421 + 80.000 0.0412 0.4607 -2.6421 + 90.000 0.0000 0.4700 -2.6421 + 100.000 -0.0288 0.4607 -2.6421 + 110.000 -0.0586 0.4389 -2.6421 + 120.000 -0.0870 0.4069 -2.6421 + 130.000 -0.1130 0.3683 -2.6421 + 140.000 -0.1378 0.3277 -2.6421 + 150.000 -0.1675 0.2898 -2.6421 + 160.000 -0.1117 0.2589 -2.6421 + 170.000 -0.0558 0.2481 -2.6421 + 180.000 0.0000 0.2481 -2.6421 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 69 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.5519 -2.6421 + -170.000 0.0585 0.5519 -2.6421 + -160.000 0.1170 0.5606 -2.6421 + -150.000 0.1756 0.5916 -2.6421 + -140.000 0.1427 0.6298 -2.6421 + -130.000 0.1159 0.6706 -2.6421 + -120.000 0.0885 0.7095 -2.6421 + -110.000 0.0593 0.7419 -2.6421 + -100.000 0.0290 0.7641 -2.6421 + -90.000 0.0000 0.7738 -2.6421 + -80.000 -0.0290 0.7641 -2.6421 + -70.000 -0.0593 0.7419 -2.6421 + -60.000 -0.0885 0.7095 -2.6421 + -50.000 -0.1159 0.6706 -2.6421 + -40.000 -0.1427 0.6298 -2.6421 + -30.000 -0.1756 0.5916 -2.6421 + -20.000 -0.1283 0.5722 -2.6421 + -10.000 -0.1157 0.5529 -2.9039 + -9.000 -0.1073 0.5525 -2.8553 + -8.000 -0.1038 0.5521 -2.8178 + -7.000 -0.0886 0.5519 -2.7624 + -6.000 -0.0700 0.5518 -2.7151 + -5.000 -0.0503 0.5516 -2.6793 + -4.000 -0.0293 0.5515 -2.6454 + -3.000 -0.0081 0.5514 -2.6240 + -1.000 0.0355 0.5513 -2.6411 + 0.000 0.0575 0.5513 -2.6574 + 1.000 0.0791 0.5513 -2.6737 + 2.000 0.1010 0.5513 -2.6904 + 5.000 0.1606 0.5516 -2.7421 + 6.000 0.1748 0.5518 -2.7605 + 7.000 0.1845 0.5521 -2.7774 + 9.000 0.2027 0.5527 -2.8344 + 10.000 0.2063 0.5535 -2.8582 + 11.000 0.2125 0.5542 -2.8904 + 12.000 0.2152 0.5553 -2.9314 + 13.000 0.2203 0.5564 -2.9780 + 14.000 0.2255 0.5576 -3.0290 + 15.000 0.2316 0.5588 -3.0844 + 16.000 0.2365 0.5602 -3.1417 + 17.000 0.2415 0.5617 -3.2040 + 18.000 0.2457 0.5633 -3.2661 + 19.000 0.2499 0.5651 -3.3298 + 20.000 0.2526 0.5671 -3.3930 + 21.000 0.2554 0.5692 -3.4574 + 22.000 0.2578 0.5713 -3.5243 + 23.000 0.2586 0.5737 -3.5852 + 24.000 0.2610 0.5758 -3.6592 + 25.000 0.2612 0.5783 -3.7205 + 26.000 0.2613 0.5806 -3.7805 + 27.000 0.2606 0.5831 -3.8336 + 28.000 0.2592 0.5857 -3.8789 + 29.000 0.2538 0.5888 -3.8910 + 30.000 0.2508 0.5916 -3.9145 + 40.000 0.2038 0.6298 -2.6421 + 50.000 0.1655 0.6706 -2.6421 + 60.000 0.1265 0.7095 -2.6421 + 70.000 0.0847 0.7419 -2.6421 + 80.000 0.0414 0.7641 -2.6421 + 90.000 0.0000 0.7738 -2.6421 + 100.000 -0.0290 0.7641 -2.6421 + 110.000 -0.0593 0.7419 -2.6421 + 120.000 -0.0885 0.7095 -2.6421 + 130.000 -0.1159 0.6706 -2.6421 + 140.000 -0.1427 0.6298 -2.6421 + 150.000 -0.1756 0.5916 -2.6421 + 160.000 -0.1170 0.5606 -2.6421 + 170.000 -0.0585 0.5519 -2.6421 + 180.000 0.0000 0.5519 -2.6421 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 71 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.5765 -2.6421 + -170.000 0.0607 0.5765 -2.6421 + -160.000 0.1214 0.5836 -2.6421 + -150.000 0.1821 0.6147 -2.6421 + -140.000 0.1467 0.6531 -2.6421 + -130.000 0.1182 0.6942 -2.6421 + -120.000 0.0898 0.7333 -2.6421 + -110.000 0.0598 0.7660 -2.6421 + -100.000 0.0291 0.7885 -2.6421 + -90.000 0.0000 0.7984 -2.6421 + -80.000 -0.0291 0.7885 -2.6421 + -70.000 -0.0598 0.7660 -2.6421 + -60.000 -0.0898 0.7333 -2.6421 + -50.000 -0.1182 0.6942 -2.6421 + -40.000 -0.1467 0.6531 -2.6421 + -30.000 -0.1821 0.6147 -2.6421 + -20.000 -0.1332 0.5960 -2.6421 + -10.000 -0.1205 0.5773 -2.9139 + -9.000 -0.1129 0.5769 -2.8656 + -8.000 -0.1057 0.5766 -2.8211 + -7.000 -0.0889 0.5765 -2.7629 + -6.000 -0.0703 0.5763 -2.7155 + -5.000 -0.0499 0.5762 -2.6789 + -4.000 -0.0288 0.5761 -2.6448 + -3.000 -0.0075 0.5760 -2.6237 + -2.000 0.0142 0.5759 -2.6263 + -1.000 0.0362 0.5758 -2.6416 + 0.000 0.0582 0.5758 -2.6578 + 1.000 0.0803 0.5758 -2.6745 + 2.000 0.1017 0.5759 -2.6909 + 4.000 0.1425 0.5760 -2.7255 + 5.000 0.1601 0.5762 -2.7421 + 6.000 0.1754 0.5765 -2.7596 + 7.000 0.1869 0.5766 -2.7798 + 8.000 0.1980 0.5768 -2.8088 + 9.000 0.2042 0.5773 -2.8362 + 10.000 0.2107 0.5779 -2.8643 + 11.000 0.2150 0.5787 -2.8954 + 12.000 0.2204 0.5796 -2.9422 + 13.000 0.2252 0.5806 -2.9891 + 14.000 0.2320 0.5817 -3.0455 + 15.000 0.2374 0.5829 -3.1009 + 16.000 0.2428 0.5842 -3.1603 + 17.000 0.2476 0.5857 -3.2240 + 19.000 0.2555 0.5891 -3.3512 + 20.000 0.2614 0.5906 -3.4288 + 21.000 0.2636 0.5927 -3.4927 + 22.000 0.2650 0.5949 -3.5583 + 23.000 0.2658 0.5973 -3.6225 + 24.000 0.2669 0.5996 -3.6923 + 25.000 0.2674 0.6019 -3.7579 + 26.000 0.2670 0.6044 -3.8169 + 27.000 0.2657 0.6069 -3.8686 + 28.000 0.2642 0.6095 -3.9160 + 29.000 0.2624 0.6121 -3.9580 + 30.000 0.2601 0.6147 -3.9922 + 40.000 0.2095 0.6531 -2.6421 + 50.000 0.1689 0.6942 -2.6421 + 60.000 0.1283 0.7333 -2.6421 + 70.000 0.0854 0.7660 -2.6421 + 80.000 0.0416 0.7885 -2.6421 + 90.000 0.0000 0.7984 -2.6421 + 100.000 -0.0291 0.7885 -2.6421 + 110.000 -0.0598 0.7660 -2.6421 + 120.000 -0.0898 0.7333 -2.6421 + 130.000 -0.1182 0.6942 -2.6421 + 140.000 -0.1467 0.6531 -2.6421 + 150.000 -0.1821 0.6147 -2.6421 + 160.000 -0.1214 0.5836 -2.6421 + 170.000 -0.0607 0.5765 -2.6421 + 180.000 0.0000 0.5765 -2.6421 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 62 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.5765 -2.6421 + -170.000 0.0727 0.5765 -2.6421 + -160.000 0.1455 0.5865 -2.6421 + -150.000 0.1715 0.6174 -2.6421 + -140.000 0.1402 0.6554 -2.6421 + -130.000 0.1144 0.6961 -2.6421 + -120.000 0.0878 0.7348 -2.6421 + -110.000 0.0589 0.7670 -2.6421 + -100.000 0.0289 0.7890 -2.6421 + -90.000 0.0000 0.7984 -2.6421 + -80.000 -0.0289 0.7890 -2.6421 + -70.000 -0.0589 0.7670 -2.6421 + -60.000 -0.0878 0.7348 -2.6421 + -50.000 -0.1144 0.6961 -2.6421 + -40.000 -0.1402 0.6554 -2.6421 + -30.000 -0.1715 0.6174 -2.6421 + -20.000 -0.1503 0.5939 -2.6421 + -10.000 -0.1223 0.5772 -2.9191 + -9.000 -0.1172 0.5767 -2.8738 + -8.000 -0.1072 0.5765 -2.8237 + -5.000 -0.0498 0.5762 -2.6788 + -4.000 -0.0287 0.5761 -2.6447 + -3.000 -0.0071 0.5760 -2.6217 + -2.000 0.0146 0.5759 -2.6265 + -1.000 0.0366 0.5758 -2.6418 + 0.000 0.0588 0.5758 -2.6582 + 1.000 0.0806 0.5758 -2.6747 + 2.000 0.1019 0.5758 -2.6912 + 3.000 0.1229 0.5759 -2.7082 + 4.000 0.1424 0.5761 -2.7238 + 6.000 0.1765 0.5764 -2.7594 + 7.000 0.1903 0.5765 -2.7828 + 8.000 0.2007 0.5767 -2.8120 + 9.000 0.2064 0.5772 -2.8389 + 11.000 0.2172 0.5785 -2.8998 + 12.000 0.2241 0.5793 -2.9500 + 13.000 0.2312 0.5802 -3.0035 + 15.000 0.2438 0.5823 -3.1186 + 16.000 0.2491 0.5836 -3.1799 + 17.000 0.2546 0.5849 -3.2469 + 18.000 0.2582 0.5865 -3.3095 + 19.000 0.2624 0.5882 -3.3777 + 20.000 0.2652 0.5901 -3.4441 + 22.000 0.2683 0.5945 -3.5738 + 25.000 0.2704 0.6015 -3.7758 + 26.000 0.2702 0.6039 -3.8370 + 30.000 0.2450 0.6174 -3.5690 + 40.000 0.2003 0.6554 -2.6421 + 50.000 0.1634 0.6961 -2.6421 + 60.000 0.1254 0.7348 -2.6421 + 70.000 0.0842 0.7670 -2.6421 + 80.000 0.0413 0.7890 -2.6421 + 90.000 0.0000 0.7984 -2.6421 + 100.000 -0.0289 0.7890 -2.6421 + 110.000 -0.0589 0.7670 -2.6421 + 120.000 -0.0878 0.7348 -2.6421 + 130.000 -0.1144 0.6961 -2.6421 + 140.000 -0.1402 0.6554 -2.6421 + 150.000 -0.1715 0.6174 -2.6421 + 160.000 -0.1455 0.5865 -2.6421 + 170.000 -0.0727 0.5765 -2.6421 + 180.000 0.0000 0.5765 -2.6421 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 67 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.5765 -2.6421 + -170.000 0.0628 0.5765 -2.6421 + -160.000 0.1256 0.5819 -2.6421 + -150.000 0.1883 0.6132 -2.6421 + -140.000 0.1505 0.6517 -2.6421 + -130.000 0.1204 0.6930 -2.6421 + -120.000 0.0910 0.7324 -2.6421 + -110.000 0.0603 0.7653 -2.6421 + -100.000 0.0292 0.7882 -2.6421 + -90.000 0.0000 0.7984 -2.6421 + -80.000 -0.0292 0.7882 -2.6421 + -70.000 -0.0603 0.7653 -2.6421 + -60.000 -0.0910 0.7324 -2.6421 + -50.000 -0.1204 0.6930 -2.6421 + -40.000 -0.1505 0.6517 -2.6421 + -30.000 -0.1883 0.6132 -2.6421 + -20.000 -0.1368 0.5952 -2.6421 + -10.000 -0.1219 0.5772 -2.9149 + -9.000 -0.1226 0.5766 -2.8845 + -8.000 -0.1085 0.5765 -2.8260 + -6.000 -0.0705 0.5762 -2.7163 + -4.000 -0.0286 0.5760 -2.6446 + -3.000 -0.0069 0.5760 -2.6219 + -2.000 0.0149 0.5759 -2.6267 + -1.000 0.0370 0.5758 -2.6420 + 0.000 0.0591 0.5758 -2.6583 + 1.000 0.0807 0.5758 -2.6748 + 2.000 0.1020 0.5758 -2.6915 + 4.000 0.1420 0.5761 -2.7229 + 5.000 0.1598 0.5763 -2.7401 + 6.000 0.1771 0.5764 -2.7606 + 7.000 0.1940 0.5765 -2.7861 + 8.000 0.2019 0.5767 -2.8134 + 9.000 0.2093 0.5771 -2.8426 + 10.000 0.2125 0.5778 -2.8638 + 11.000 0.2210 0.5783 -2.9073 + 12.000 0.2274 0.5791 -2.9570 + 13.000 0.2343 0.5800 -3.0108 + 14.000 0.2412 0.5809 -3.0686 + 16.000 0.2529 0.5832 -3.1916 + 17.000 0.2573 0.5847 -3.2559 + 18.000 0.2618 0.5862 -3.3219 + 19.000 0.2653 0.5879 -3.3887 + 20.000 0.2679 0.5898 -3.4550 + 21.000 0.2693 0.5919 -3.5174 + 24.000 0.2762 0.5982 -3.7432 + 25.000 0.2769 0.6005 -3.8133 + 26.000 0.2769 0.6029 -3.8791 + 27.000 0.2762 0.6053 -3.9388 + 28.000 0.2745 0.6078 -3.9894 + 29.000 0.2719 0.6105 -4.0313 + 30.000 0.2691 0.6132 -4.0663 + 40.000 0.2150 0.6517 -2.6421 + 50.000 0.1721 0.6930 -2.6421 + 60.000 0.1300 0.7324 -2.6421 + 70.000 0.0862 0.7653 -2.6421 + 80.000 0.0418 0.7882 -2.6421 + 90.000 0.0000 0.7984 -2.6421 + 100.000 -0.0292 0.7882 -2.6421 + 110.000 -0.0603 0.7653 -2.6421 + 120.000 -0.0910 0.7324 -2.6421 + 130.000 -0.1204 0.6930 -2.6421 + 140.000 -0.1505 0.6517 -2.6421 + 150.000 -0.1883 0.6132 -2.6421 + 160.000 -0.1256 0.5819 -2.6421 + 170.000 -0.0628 0.5765 -2.6421 + 180.000 0.0000 0.5765 -2.6421 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 68 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.5765 -2.6421 + -170.000 0.0661 0.5765 -2.6421 + -160.000 0.1322 0.5825 -2.6421 + -150.000 0.1869 0.6137 -2.6421 + -140.000 0.1496 0.6521 -2.6421 + -130.000 0.1199 0.6934 -2.6421 + -120.000 0.0907 0.7327 -2.6421 + -110.000 0.0602 0.7655 -2.6421 + -100.000 0.0292 0.7883 -2.6421 + -90.000 0.0000 0.7984 -2.6421 + -80.000 -0.0292 0.7883 -2.6421 + -70.000 -0.0602 0.7655 -2.6421 + -60.000 -0.0907 0.7327 -2.6421 + -50.000 -0.1199 0.6934 -2.6421 + -40.000 -0.1496 0.6521 -2.6421 + -30.000 -0.1869 0.6137 -2.6421 + -20.000 -0.1421 0.5945 -2.6421 + -10.000 -0.1243 0.5770 -2.9202 + -7.000 -0.0904 0.5763 -2.7654 + -6.000 -0.0703 0.5762 -2.7143 + -5.000 -0.0498 0.5761 -2.6788 + -4.000 -0.0285 0.5760 -2.6445 + -3.000 -0.0068 0.5760 -2.6224 + -2.000 0.0151 0.5759 -2.6268 + -1.000 0.0372 0.5758 -2.6421 + 0.000 0.0592 0.5758 -2.6584 + 1.000 0.0809 0.5758 -2.6749 + 2.000 0.1021 0.5758 -2.6908 + 3.000 0.1228 0.5759 -2.7064 + 4.000 0.1421 0.5761 -2.7236 + 5.000 0.1599 0.5762 -2.7406 + 6.000 0.1783 0.5763 -2.7617 + 7.000 0.1954 0.5765 -2.7874 + 8.000 0.2032 0.5767 -2.8148 + 10.000 0.2152 0.5776 -2.8684 + 11.000 0.2233 0.5782 -2.9119 + 12.000 0.2310 0.5789 -2.9648 + 13.000 0.2383 0.5797 -3.0203 + 14.000 0.2437 0.5807 -3.0748 + 15.000 0.2498 0.5818 -3.1353 + 17.000 0.2600 0.5844 -3.2646 + 18.000 0.2642 0.5859 -3.3301 + 19.000 0.2676 0.5876 -3.3976 + 20.000 0.2694 0.5896 -3.4608 + 22.000 0.2766 0.5933 -3.6125 + 23.000 0.2780 0.5955 -3.6858 + 24.000 0.2791 0.5978 -3.7589 + 25.000 0.2796 0.6001 -3.8288 + 26.000 0.2794 0.6025 -3.8941 + 27.000 0.2781 0.6050 -3.9509 + 28.000 0.2762 0.6076 -4.0012 + 29.000 0.2739 0.6102 -4.0458 + 30.000 0.2671 0.6137 -3.9598 + 40.000 0.2137 0.6521 -2.6421 + 50.000 0.1713 0.6934 -2.6421 + 60.000 0.1296 0.7327 -2.6421 + 70.000 0.0860 0.7655 -2.6421 + 80.000 0.0417 0.7883 -2.6421 + 90.000 0.0000 0.7984 -2.6421 + 100.000 -0.0292 0.7883 -2.6421 + 110.000 -0.0602 0.7655 -2.6421 + 120.000 -0.0907 0.7327 -2.6421 + 130.000 -0.1199 0.6934 -2.6421 + 140.000 -0.1496 0.6521 -2.6421 + 150.000 -0.1869 0.6137 -2.6421 + 160.000 -0.1322 0.5825 -2.6421 + 170.000 -0.0661 0.5765 -2.6421 + 180.000 0.0000 0.5765 -2.6421 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.000 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 64 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.000 0.0000 0.5765 -2.6421 + -170.000 0.0637 0.5765 -2.6421 + -160.000 0.1274 0.5812 -2.6421 + -150.000 0.1912 0.6125 -2.6421 + -140.000 0.1522 0.6511 -2.6421 + -130.000 0.1215 0.6925 -2.6421 + -120.000 0.0915 0.7320 -2.6421 + -110.000 0.0606 0.7651 -2.6421 + -100.000 0.0293 0.7880 -2.6421 + -90.000 0.0000 0.7984 -2.6421 + -80.000 -0.0293 0.7880 -2.6421 + -70.000 -0.0606 0.7651 -2.6421 + -60.000 -0.0915 0.7320 -2.6421 + -50.000 -0.1215 0.6925 -2.6421 + -40.000 -0.1522 0.6511 -2.6421 + -30.000 -0.1912 0.6125 -2.6421 + -20.000 -0.1399 0.5947 -2.6421 + -10.000 -0.1267 0.5770 -2.9252 + -9.000 -0.1232 0.5766 -2.8832 + -8.000 -0.1096 0.5764 -2.8283 + -6.000 -0.0703 0.5762 -2.7138 + -5.000 -0.0497 0.5761 -2.6788 + -4.000 -0.0285 0.5760 -2.6445 + -3.000 -0.0066 0.5759 -2.6225 + -2.000 0.0153 0.5759 -2.6269 + -1.000 0.0373 0.5758 -2.6422 + 0.000 0.0594 0.5758 -2.6585 + 1.000 0.0807 0.5758 -2.6749 + 2.000 0.1021 0.5758 -2.6907 + 3.000 0.1226 0.5759 -2.7061 + 5.000 0.1605 0.5762 -2.7412 + 6.000 0.1789 0.5763 -2.7623 + 7.000 0.1967 0.5764 -2.7887 + 8.000 0.2039 0.5767 -2.8156 + 11.000 0.2254 0.5781 -2.9160 + 12.000 0.2331 0.5788 -2.9692 + 14.000 0.2475 0.5804 -3.0842 + 16.000 0.2573 0.5828 -3.2053 + 18.000 0.2662 0.5857 -3.3369 + 21.000 0.2770 0.5909 -3.5511 + 22.000 0.2788 0.5930 -3.6222 + 23.000 0.2804 0.5952 -3.6977 + 24.000 0.2812 0.5975 -3.7705 + 25.000 0.2815 0.5998 -3.8400 + 26.000 0.2807 0.6023 -3.9023 + 27.000 0.2794 0.6048 -3.9597 + 28.000 0.2777 0.6073 -4.0122 + 29.000 0.2757 0.6099 -4.0591 + 30.000 0.2731 0.6125 -4.0985 + 40.000 0.2174 0.6511 -2.6421 + 50.000 0.1735 0.6925 -2.6421 + 60.000 0.1308 0.7320 -2.6421 + 70.000 0.0865 0.7651 -2.6421 + 80.000 0.0419 0.7880 -2.6421 + 90.000 0.0000 0.7984 -2.6421 + 100.000 -0.0293 0.7880 -2.6421 + 110.000 -0.0606 0.7651 -2.6421 + 120.000 -0.0915 0.7320 -2.6421 + 130.000 -0.1215 0.6925 -2.6421 + 140.000 -0.1522 0.6511 -2.6421 + 150.000 -0.1912 0.6125 -2.6421 + 160.000 -0.1274 0.5812 -2.6421 + 170.000 -0.0637 0.5765 -2.6421 + 180.000 0.0000 0.5765 -2.6421 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0864_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0864_coords.txt new file mode 100644 index 00000000..8a9382a1 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_0864_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_0864 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.071897 + 0.027091 0.142126 + 0.060263 0.208964 + 0.105430 0.270115 + 0.161359 0.323830 + 0.226526 0.368470 + 0.299152 0.402651 + 0.377257 0.425156 + 0.458710 0.435236 + 0.541290 0.432906 + 0.622743 0.418526 + 0.700848 0.392758 + 0.773474 0.356678 + 0.838641 0.311513 + 0.894570 0.258619 + 0.939737 0.199450 + 0.972909 0.135539 + 0.993181 0.068594 + 1.000000 0.000000 + 0.993181 -0.068161 + 0.972909 -0.134227 + 0.939737 -0.197056 + 0.894570 -0.255087 + 0.838641 -0.306904 + 0.773474 -0.351143 + 0.700848 -0.386540 + 0.622743 -0.411920 + 0.541290 -0.426222 + 0.458710 -0.428757 + 0.377257 -0.419101 + 0.299152 -0.397194 + 0.226526 -0.363795 + 0.161359 -0.320050 + 0.105430 -0.267316 + 0.060263 -0.207125 + 0.027091 -0.141176 + 0.006819 -0.071509 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_1000.dat b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_1000.dat new file mode 100644 index 00000000..7c3e8471 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_1000.dat @@ -0,0 +1,108 @@ +! ------------ AirfoilInfo v1.01.x Input File ---------------------------------- +! NACA6_1000 airfoil, data based on values used for the design of the RM1 tidal current turbine. +! line +! line +! ------------------------------------------------------------------------------ +"default" InterpOrd ! Interpolation order to use for quasi-steady table lookup {1=linear; 3=cubic spline; "default"} [default=1] + 1.0 NonDimArea ! The non-dimensional area of the airfoil (area/chord^2) (set to 1.0 if unsure or unneeded) +@"NACA6_1000_coords.txt" NumCoords ! The number of coordinates in the airfoil shape file. Set to zero if coordinates not included. +"unused" BL_file ! The file name including the boundary layer characteristics of the profile. Ignored if the aeroacoustic module is not called. + 7 NumTabs ! Number of airfoil tables in this file. +! ------------------------------------------------------------------------------ +! data for table 1 +! ------------------------------------------------------------------------------ + 2.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.3 -3.0 + 0.00 0.0 0.3 -3.0 + 180.00 0.0 0.3 -3.0 +! ------------------------------------------------------------------------------ +! data for table 2 +! ------------------------------------------------------------------------------ + 4.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.67 -3.0 + 0.00 0.0 0.67 -3.0 + 180.00 0.0 0.67 -3.0 +! ------------------------------------------------------------------------------ +! data for table 3 +! ------------------------------------------------------------------------------ + 6.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.7 -3.0 + 0.00 0.0 0.7 -3.0 + 180.00 0.0 0.7 -3.0 +! ------------------------------------------------------------------------------ +! data for table 4 +! ------------------------------------------------------------------------------ + 8.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.7 -3.0 + 0.00 0.0 0.7 -3.0 + 180.00 0.0 0.7 -3.0 +! ------------------------------------------------------------------------------ +! data for table 5 +! ------------------------------------------------------------------------------ + 10.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.7 -3.0 + 0.00 0.0 0.7 -3.0 + 180.00 0.0 0.7 -3.0 +! ------------------------------------------------------------------------------ +! data for table 6 +! ------------------------------------------------------------------------------ + 12.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.7 -3.0 + 0.00 0.0 0.7 -3.0 + 180.00 0.0 0.7 -3.0 +! ------------------------------------------------------------------------------ +! data for table 7 +! ------------------------------------------------------------------------------ + 14.0 Re ! Reynolds number in millions + 0 UserProp ! User property (control) setting +False InclUAdata ! Is unsteady aerodynamics data included in this table? If TRUE, then include 30 UA coefficients below this line +!........................................ +! Table of aerodynamics coefficients + 3 NumAlf ! Number of data lines in the following table +! Alpha Cl Cd Cpmin +! (deg) (-) (-) (-) + -180.00 0.0 0.7 -3.0 + 0.00 0.0 0.7 -3.0 + 180.00 0.0 0.7 -3.0 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_1000_coords.txt b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_1000_coords.txt new file mode 100644 index 00000000..e9876cf7 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/Airfoils/NACA6_1000_coords.txt @@ -0,0 +1,47 @@ + 40 NumCoords ! The number of coordinates in the airfoil shape file (including an extra coordinate for airfoil reference). Set to zero if coordinates not included. +! ......... x-y coordinates are next if NumCoords > 0 ............. +! x-y coordinate of airfoil reference +! x/c y/c + 0.25 0 +! coordinates of airfoil shape +! NACA6_1000 Airfoil +! x/c y/c + 0.000000 0.000000 + 0.006819 0.082442 + 0.027091 0.162359 + 0.060263 0.237976 + 0.105430 0.307106 + 0.161359 0.367865 + 0.226526 0.418583 + 0.299152 0.457883 + 0.377257 0.484712 + 0.458710 0.498283 + 0.541290 0.498283 + 0.622743 0.484712 + 0.700848 0.457883 + 0.773474 0.418583 + 0.838641 0.367865 + 0.894570 0.307106 + 0.939737 0.237976 + 0.972909 0.162359 + 0.993181 0.082442 + 1.000000 0.000000 + 0.993181 -0.082442 + 0.972909 -0.162359 + 0.939737 -0.237976 + 0.894570 -0.307106 + 0.838641 -0.367865 + 0.773474 -0.418583 + 0.700848 -0.457883 + 0.622743 -0.484712 + 0.541290 -0.498283 + 0.458710 -0.498283 + 0.377257 -0.484712 + 0.299152 -0.457883 + 0.226526 -0.418583 + 0.161359 -0.367865 + 0.105430 -0.307106 + 0.060263 -0.237976 + 0.027091 -0.162359 + 0.006819 -0.082442 + 0.000000 0.000000 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat new file mode 100644 index 00000000..29c7548a --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat @@ -0,0 +1,38 @@ +------- AERODYN v15.00.* BLADE DEFINITION INPUT FILE ------------------------------------- +Floating MHK turbine hydrodynamic blade input properties, based on the RM1 tidal current rotor +====== Blade Properties ================================================================= +32 NumBlNds - Number of blade nodes used in the analysis (-) +BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID BlCb BlCenBn BlCenBt +(m) (m) (m) (deg) (deg) (m) (-) (-) (m) (m) +0.000 0.00 0.00 0.00 12.86 0.800 1 0.9956 0.0000 0.2000 +0.150 0.00 0.00 0.00 12.86 0.800 1 0.9956 0.0000 0.2000 +0.450 0.00 0.00 0.00 12.86 0.894 2 0.8572 0.0023 0.2202 +0.750 0.00 0.00 0.00 12.86 1.118 3 0.6118 0.0082 0.2637 +1.050 0.00 0.00 0.00 12.86 1.386 4 0.4145 0.0153 0.3027 +1.350 0.00 0.00 0.00 12.86 1.610 5 0.2873 0.0217 0.3131 +1.650 0.00 0.00 0.00 12.86 1.704 6 0.2287 0.0250 0.2973 +1.950 0.00 0.00 0.00 11.54 1.662 7 0.2099 0.0250 0.2753 +2.250 0.00 0.00 0.00 10.44 1.619 8 0.1966 0.0247 0.2565 +2.550 0.00 0.00 0.00 9.50 1.577 9 0.1870 0.0245 0.2386 +2.850 0.00 0.00 0.00 8.71 1.534 9 0.1870 0.0238 0.2321 +3.150 0.00 0.00 0.00 8.02 1.492 9 0.1870 0.0232 0.2258 +3.450 0.00 0.00 0.00 7.43 1.450 9 0.1870 0.0225 0.2194 +3.750 0.00 0.00 0.00 6.91 1.407 9 0.1870 0.0218 0.2129 +4.050 0.00 0.00 0.00 6.45 1.365 9 0.1870 0.0212 0.2066 +4.350 0.00 0.00 0.00 6.04 1.322 9 0.1870 0.0205 0.2001 +4.650 0.00 0.00 0.00 5.68 1.279 9 0.1870 0.0198 0.1935 +4.950 0.00 0.00 0.00 5.35 1.235 9 0.1870 0.0192 0.1869 +5.250 0.00 0.00 0.00 5.05 1.192 9 0.1870 0.0185 0.1804 +5.550 0.00 0.00 0.00 4.77 1.148 9 0.1870 0.0178 0.1737 +5.850 0.00 0.00 0.00 4.51 1.103 9 0.1870 0.0171 0.1669 +6.150 0.00 0.00 0.00 4.26 1.058 9 0.1870 0.0164 0.1601 +6.450 0.00 0.00 0.00 4.03 1.012 9 0.1870 0.0157 0.1531 +6.750 0.00 0.00 0.00 3.80 0.966 9 0.1870 0.0150 0.1462 +7.050 0.00 0.00 0.00 3.57 0.920 9 0.1870 0.0143 0.1392 +7.350 0.00 0.00 0.00 3.35 0.872 9 0.1870 0.0135 0.1320 +7.650 0.00 0.00 0.00 3.13 0.824 9 0.1870 0.0128 0.1247 +7.950 0.00 0.00 0.00 2.90 0.776 9 0.1870 0.0120 0.1174 +8.250 0.00 0.00 0.00 2.67 0.726 9 0.1870 0.0113 0.1099 +8.550 0.00 0.00 0.00 2.43 0.676 9 0.1870 0.0105 0.1023 +8.850 0.00 0.00 0.00 2.18 0.626 9 0.1870 0.0097 0.0947 +9.000 0.00 0.00 0.00 2.18 0.626 9 0.1870 0.0097 0.0947 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Cp_Ct_Cq.txt b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Cp_Ct_Cq.txt new file mode 100644 index 00000000..da7445bf --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Cp_Ct_Cq.txt @@ -0,0 +1,99 @@ +# ----- Rotor performance tables for the MHK_RM1_Floating wind turbine ----- +# ------------ Written on Apr-12-23 using the ROSCO toolbox ------------ + +# Pitch angle vector, 36 entries - x axis (matrix columns) (deg) +-5.0 -4.0 -3.0 -2.0 -1.0 0.0 1.0 2.0 3.0 4.0 5.0 6.0 7.0 8.0 9.0 10.0 11.0 12.0 13.0 14.0 15.0 16.0 17.0 18.0 19.0 20.0 21.0 22.0 23.0 24.0 25.0 26.0 27.0 28.0 29.0 30.0 +# TSR vector, 26 entries - y axis (matrix rows) (-) +2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5 6.0 6.5 7.0 7.5 8.0 8.5 9.0 9.5 10.0 10.5 11.0 11.5 12.0 12.5 13.0 13.5 14.0 14.5 +# Wind speed vector - z axis (m/s) +2.0 + +# Power coefficient + +0.074944 0.079726 0.084378 0.088881 0.093217 0.097364 0.101301 0.105005 0.108455 0.111627 0.114499 0.117048 0.119254 0.121097 0.122559 0.123624 0.124278 0.124507 0.124300 0.123645 0.122533 0.120953 0.118899 0.116363 0.113340 0.109825 0.105817 0.101315 0.096316 0.090822 0.084833 0.078355 0.071398 0.063985 0.056154 0.047964 +0.130952 0.137109 0.142870 0.148203 0.153074 0.157453 0.161312 0.164628 0.167372 0.169517 0.171039 0.171924 0.172157 0.171726 0.170619 0.168827 0.166341 0.163154 0.159260 0.154654 0.149334 0.143297 0.136543 0.129071 0.120881 0.111975 0.102356 0.092036 0.081046 0.069441 0.057307 0.044758 0.031932 0.018970 0.006005 -0.006847 +0.195638 0.202139 0.207875 0.212814 0.216927 0.220183 0.222553 0.224026 0.224594 0.224263 0.222996 0.220777 0.217599 0.213457 0.208343 0.202253 0.195185 0.187134 0.178099 0.168078 0.157067 0.145065 0.132070 0.118086 0.103136 0.087277 0.070607 0.053271 0.035454 0.017370 -0.000779 -0.018814 -0.036579 -0.053937 -0.070772 -0.086985 +0.262033 0.267729 0.272255 0.275602 0.277770 0.278772 0.278626 0.277286 0.274722 0.270950 0.265956 0.259691 0.252150 0.243325 0.233208 0.221791 0.209065 0.195021 0.179649 0.162940 0.144884 0.125492 0.104814 0.082960 0.060099 0.036466 0.012350 -0.011952 -0.036178 -0.060102 -0.083527 -0.106282 -0.128227 -0.149248 -0.169259 -0.188203 +0.322926 0.327173 0.329927 0.331189 0.330966 0.329268 0.326118 0.321556 0.315485 0.307866 0.298685 0.287857 0.275361 0.261178 0.245286 0.227663 0.208287 0.187132 0.164179 0.139430 0.112946 0.084868 0.055418 0.024908 -0.006270 -0.037714 -0.069075 -0.100049 -0.130376 -0.159832 -0.188230 -0.215422 -0.241296 -0.265780 -0.288840 -0.310479 +0.372380 0.375319 0.376595 0.376163 0.373941 0.369893 0.364015 0.356336 0.346830 0.335323 0.321769 0.306044 0.288110 0.267928 0.245459 0.220662 0.193502 0.163952 0.132049 0.097926 0.061824 0.024095 -0.014788 -0.054287 -0.093913 -0.133250 -0.171936 -0.209660 -0.246161 -0.281224 -0.314687 -0.346436 -0.376411 -0.404602 -0.431047 -0.455838 +0.405840 0.408981 0.410112 0.409159 0.406069 0.400647 0.392786 0.382501 0.369826 0.354510 0.336432 0.315446 0.291501 0.264544 0.234524 0.201389 0.165121 0.125794 0.083613 0.038921 -0.007794 -0.055894 -0.104692 -0.153592 -0.202082 -0.249721 -0.296127 -0.340984 -0.384037 -0.425096 -0.464037 -0.500803 -0.535402 -0.567911 -0.598467 -0.627270 +0.419815 0.426133 0.429721 0.430398 0.428020 0.422533 0.413665 0.401397 0.385844 0.366737 0.343872 0.317114 0.286411 0.251710 0.212957 0.170136 0.123352 0.072872 0.019131 -0.037250 -0.095463 -0.154643 -0.214052 -0.273053 -0.331092 -0.387697 -0.442469 -0.495093 -0.545333 -0.593039 -0.638145 -0.680670 -0.720718 -0.758469 -0.794184 -0.828187 +0.416203 0.426901 0.435700 0.440694 0.441121 0.436927 0.428055 0.414373 0.396136 0.373105 0.345026 0.311802 0.273402 0.229785 0.180939 0.126984 0.068233 0.005200 -0.061381 -0.130534 -0.201181 -0.272387 -0.343354 -0.413383 -0.481873 -0.548318 -0.612312 -0.673550 -0.731832 -0.787064 -0.839260 -0.888535 -0.935107 -0.979287 -1.021467 -1.062112 +0.405435 0.418564 0.430778 0.441391 0.446693 0.445250 0.437234 0.422572 0.401692 0.374435 0.340533 0.299965 0.252737 0.198854 0.138441 0.071834 -0.000397 -0.077426 -0.158137 -0.241210 -0.325451 -0.409848 -0.493517 -0.575688 -0.655711 -0.733053 -0.807309 -0.878198 -0.945571 -1.009410 -1.069825 -1.127051 -1.181434 -1.233429 -1.283586 -1.332529 +0.390503 0.406666 0.421413 0.435076 0.446065 0.448699 0.442235 0.426873 0.403229 0.371269 0.330765 0.281798 0.224440 0.158821 0.085281 0.004419 -0.082876 -0.175390 -0.271577 -0.369910 -0.469102 -0.568030 -0.665710 -0.761300 -0.854102 -0.943564 -1.029289 -1.111036 -1.188722 -1.262423 -1.332361 -1.398905 -1.462560 -1.523949 -1.583795 -1.642861 +0.371667 0.391683 0.409587 0.425790 0.440553 0.448186 0.443843 0.427902 0.401216 0.363917 0.315877 0.257305 0.188389 0.109467 0.021145 -0.075662 -0.179678 -0.289215 -0.402371 -0.517492 -0.633155 -0.748106 -0.861259 -0.971696 -1.078673 -1.181626 -1.280179 -1.374141 -1.463512 -1.548474 -1.629388 -1.706786 -1.781347 -1.853884 -1.925308 -1.996461 +0.348976 0.373677 0.395430 0.414664 0.431984 0.444452 0.442628 0.426075 0.395932 0.352522 0.295876 0.226363 0.144361 0.050473 -0.054383 -0.168912 -0.291369 -0.419564 -0.551360 -0.684950 -0.818747 -0.951358 -1.081586 -1.208436 -1.331122 -1.449075 -1.561948 -1.669615 -1.772174 -1.869941 -1.963438 -2.053377 -2.140642 -2.226257 -2.311298 -2.396626 +0.322447 0.352671 0.378963 0.401764 0.421785 0.438064 0.438990 0.421654 0.387518 0.337104 0.270664 0.188770 0.092059 -0.018557 -0.141791 -0.275900 -0.418590 -0.567224 -0.719482 -0.873361 -1.027094 -1.179135 -1.328171 -1.473129 -1.613185 -1.747771 -1.876578 -1.999566 -2.116951 -2.229204 -2.337032 -2.441358 -2.543286 -2.644065 -2.744885 -2.846626 +0.292104 0.328674 0.360194 0.387092 0.410155 0.429464 0.433189 0.414787 0.376018 0.317600 0.240072 0.144265 0.031127 -0.098072 -0.241618 -0.397243 -0.562049 -0.733059 -0.907740 -1.083862 -1.259459 -1.432826 -1.602527 -1.767409 -1.926613 -2.079580 -2.226059 -2.366108 -2.500086 -2.628644 -2.752697 -2.873398 -2.992099 -3.110271 -3.229166 -3.349696 +0.257934 0.301688 0.339118 0.370637 0.397092 0.419035 0.425380 0.405542 0.361401 0.293886 0.203884 0.092545 -0.038828 -0.188556 -0.354435 -0.533590 -0.722527 -0.917988 -1.117178 -1.317621 -1.517135 -1.713843 -1.906181 -2.092918 -2.273163 -2.446378 -2.612385 -2.771358 -2.923825 -3.070638 -3.212946 -3.352157 -3.489890 -3.627813 -3.767210 -3.909048 +0.219932 0.271699 0.315725 0.352385 0.382573 0.407064 0.415649 0.393924 0.343586 0.265797 0.161855 0.033279 -0.118226 -0.290520 -0.480838 -0.685625 -0.900846 -1.122958 -1.348868 -1.575829 -1.801429 -2.023608 -2.240672 -2.451307 -2.654600 -2.850044 -3.037549 -3.217434 -3.390412 -3.557560 -3.720288 -3.880284 -4.039448 -4.199603 -4.362066 -4.527873 +0.178135 0.238694 0.290002 0.332317 0.366567 0.393662 0.404032 0.379897 0.322460 0.233142 0.113714 -0.033886 -0.207507 -0.404491 -0.621444 -0.854066 -1.097853 -1.348937 -1.603896 -1.859687 -2.113658 -2.363555 -2.607543 -2.844231 -3.072689 -3.292456 -3.503551 -3.706453 -3.902085 -4.091779 -4.277226 -4.460416 -4.643543 -4.828535 -5.016766 -5.209342 +0.132703 0.202667 0.261930 0.310408 0.349034 0.378811 0.390525 0.363396 0.297884 0.195706 0.059174 -0.109316 -0.307124 -0.531014 -0.776881 -1.039657 -1.314414 -1.596907 -1.883356 -2.170409 -2.455151 -2.735120 -3.008340 -3.273345 -3.529196 -3.775497 -4.012387 -4.240529 -4.461083 -4.675657 -4.886250 -5.095180 -5.304925 -5.517492 -5.734327 -5.956614 +0.084224 0.163639 0.231485 0.286625 0.329931 0.362460 0.375097 0.344332 0.269698 0.153266 -0.002060 -0.193389 -0.417541 -0.670640 -0.947787 -1.243159 -1.551402 -1.867855 -2.188355 -2.509214 -2.827235 -3.139741 -3.444611 -3.740306 -4.025892 -4.301046 -4.566051 -4.821776 -5.069639 -5.311551 -5.549845 -5.787192 -6.026332 -6.269342 -6.517755 -6.772836 +0.034952 0.121693 0.198644 0.260932 0.309208 0.344544 0.357698 0.322599 0.237730 0.105587 -0.070294 -0.286489 -0.539230 -0.823928 -1.134814 -1.465339 -1.809699 -2.162779 -2.520003 -2.877323 -3.231243 -3.578859 -3.917904 -4.246774 -4.564545 -4.870985 -5.166539 -5.452304 -5.729981 -6.001811 -6.270488 -6.539057 -6.810494 -7.086946 -7.370046 -7.661142 +-0.011115 0.077127 0.163389 0.233290 0.286813 0.324991 0.338262 0.298075 0.201799 0.052429 -0.145838 -0.389008 -0.672666 -0.991441 -1.338622 -1.706972 -2.090192 -2.482680 -2.879417 -3.275962 -3.668506 -4.053914 -4.429770 -4.794407 -5.146925 -5.487194 -5.815843 -6.134218 -6.444332 -6.748781 -7.050649 -7.353371 -7.660131 -7.973156 -8.294185 -8.624661 +-0.050911 0.031047 0.125717 0.203658 0.262692 0.303728 0.316707 0.270625 0.161721 -0.006451 -0.229008 -0.501339 -0.818328 -1.173745 -1.559880 -1.968838 -2.393776 -2.828568 -3.267710 -3.706353 -4.140357 -4.566348 -4.981760 -5.384866 -5.774799 -6.151551 -6.515951 -6.869621 -7.214911 -7.554801 -7.892791 -8.232723 -8.577956 -8.930816 -9.293154 -9.666511 +-0.083826 -0.014210 0.085661 0.171992 0.236785 0.280676 0.292937 0.240111 0.117308 -0.071300 -0.320120 -0.623879 -0.976697 -1.371406 -1.799263 -2.251722 -2.721350 -3.201448 -3.685999 -4.169721 -4.648130 -5.117604 -5.575423 -6.019808 -6.449935 -6.865932 -7.268850 -7.660612 -8.043932 -8.422205 -8.799374 -9.179693 -9.566677 -9.962766 -10.369925 -10.789805 +-0.112321 -0.056414 0.043373 0.138247 0.209032 0.255752 0.266847 0.206391 0.068370 -0.142368 -0.419492 -0.757024 -1.148255 -1.584993 -2.057449 -2.556414 -3.073813 -3.602329 -4.135402 -4.667292 -5.193160 -5.709124 -6.212312 -6.700894 -7.174100 -7.632211 -8.076523 -8.509287 -8.933609 -9.353325 -9.772854 -10.196858 -10.628998 -11.071839 -11.527466 -11.997652 +-0.138289 -0.094091 -0.000597 0.102378 0.179367 0.228869 0.238326 0.169319 0.014717 -0.219903 -0.527445 -0.901172 -1.333484 -1.815079 -2.335120 -2.883708 -3.452066 -4.032220 -4.617034 -5.200293 -5.776782 -6.342352 -6.893976 -7.429778 -7.949056 -8.452259 -8.940954 -9.417741 -9.886149 -10.350489 -10.815681 -11.286791 -11.767617 -12.260864 -12.768741 -13.293158 + + +# Thrust coefficient + +0.173936 0.174545 0.175105 0.175604 0.176027 0.176357 0.176576 0.176665 0.176604 0.176373 0.175951 0.175317 0.174451 0.173333 0.171944 0.170267 0.168285 0.165982 0.163343 0.160355 0.157004 0.153277 0.149165 0.144659 0.139751 0.134439 0.128718 0.122589 0.116054 0.109113 0.101773 0.094042 0.085936 0.077488 0.068744 0.059773 +0.244110 0.244807 0.245270 0.245468 0.245368 0.244940 0.244155 0.242988 0.241410 0.239388 0.236896 0.233914 0.230421 0.226400 0.221834 0.216710 0.211014 0.204738 0.197875 0.190421 0.182376 0.173742 0.164522 0.154724 0.144354 0.133423 0.121945 0.109944 0.097467 0.084590 0.071416 0.058076 0.044718 0.031490 0.018521 0.005920 +0.329058 0.328652 0.327699 0.326163 0.324010 0.321203 0.317708 0.313503 0.308574 0.302916 0.296490 0.289274 0.281258 0.272437 0.262806 0.252366 0.241123 0.229082 0.216256 0.202654 0.188292 0.173184 0.157347 0.140807 0.123614 0.105857 0.087669 0.069222 0.050725 0.032400 0.014449 -0.002964 -0.019698 -0.035638 -0.050689 -0.064777 +0.423724 0.420631 0.416601 0.411609 0.405640 0.398694 0.390781 0.381862 0.371916 0.360960 0.348987 0.335961 0.321889 0.306782 0.290656 0.273525 0.255410 0.236329 0.216303 0.195352 0.173503 0.150806 0.127362 0.103332 0.078936 0.054443 0.030163 0.006389 -0.016641 -0.038731 -0.059724 -0.079492 -0.097938 -0.114987 -0.130589 -0.144718 +0.522708 0.515320 0.506632 0.496639 0.485349 0.472781 0.458970 0.443976 0.427746 0.410278 0.391592 0.371635 0.350431 0.328001 0.304369 0.279560 0.253599 0.226508 0.198319 0.169094 0.138969 0.108161 0.076963 0.045733 0.014882 -0.015203 -0.044217 -0.071919 -0.098118 -0.122660 -0.145431 -0.166347 -0.185356 -0.202436 -0.217593 -0.230865 +0.620986 0.607920 0.593333 0.577234 0.559606 0.540466 0.519860 0.497874 0.474551 0.449800 0.423636 0.395993 0.366897 0.336377 0.304459 0.271170 0.236538 0.200616 0.163534 0.125537 0.086962 0.048236 0.009863 -0.027633 -0.063829 -0.098403 -0.131103 -0.161729 -0.190133 -0.216204 -0.239873 -0.261109 -0.279917 -0.296336 -0.310444 -0.322349 +0.714037 0.694660 0.673585 0.650833 0.626441 0.600346 0.572544 0.543137 0.512256 0.479758 0.445598 0.409704 0.372107 0.332841 0.291934 0.249425 0.205397 0.160063 0.113768 0.066972 0.020233 -0.025799 -0.070499 -0.113396 -0.154133 -0.192434 -0.228087 -0.260935 -0.290868 -0.317827 -0.341795 -0.362800 -0.380914 -0.396253 -0.408976 -0.419282 +0.797619 0.772416 0.745286 0.716196 0.685139 0.652162 0.617157 0.580209 0.541535 0.500976 0.458403 0.413758 0.367089 0.318440 0.267859 0.215464 0.161536 0.106521 0.050989 -0.004371 -0.058762 -0.111433 -0.161837 -0.209563 -0.254300 -0.295806 -0.333907 -0.368486 -0.399482 -0.426887 -0.450748 -0.471165 -0.488287 -0.502317 -0.513506 -0.522151 +0.870407 0.839307 0.807149 0.772800 0.735851 0.696368 0.654402 0.609945 0.563343 0.514447 0.463055 0.409157 0.352830 0.294145 0.233245 0.170467 0.106342 0.041549 -0.023101 -0.086663 -0.148218 -0.207098 -0.262819 -0.315010 -0.363387 -0.407744 -0.447945 -0.483917 -0.515653 -0.543208 -0.566698 -0.586303 -0.602262 -0.614871 -0.624481 -0.631491 +0.937801 0.898777 0.859871 0.820832 0.779117 0.733820 0.685207 0.633320 0.578660 0.521127 0.460477 0.396782 0.330166 0.260796 0.189045 0.115524 0.041008 -0.033579 -0.107154 -0.178587 -0.247028 -0.311881 -0.372693 -0.429119 -0.480906 -0.527879 -0.569945 -0.607081 -0.639338 -0.666842 -0.689787 -0.708441 -0.723135 -0.734268 -0.742302 -0.747750 +1.002272 0.954818 0.907800 0.861790 0.815766 0.765455 0.710516 0.651256 0.588370 0.521837 0.451428 0.377331 0.299768 0.219135 0.136104 0.051544 -0.033517 -0.117878 -0.200191 -0.279333 -0.354544 -0.425257 -0.491041 -0.551574 -0.606630 -0.656072 -0.699848 -0.737992 -0.770621 -0.797933 -0.820208 -0.837806 -0.851169 -0.860810 -0.867314 -0.871279 +1.064598 1.008390 0.952917 0.898894 0.846816 0.792132 0.731177 0.664544 0.593190 0.517221 0.436491 0.351342 0.262208 0.169811 0.075110 -0.020766 -0.116510 -0.210609 -0.301585 -0.388416 -0.470381 -0.546930 -0.617647 -0.682232 -0.740484 -0.792304 -0.837690 -0.876733 -0.909619 -0.936626 -0.958130 -0.974602 -0.986598 -0.994763 -0.999805 -1.002335 +1.125286 1.060007 0.995803 0.933481 0.873901 0.814638 0.747903 0.673814 0.593683 0.507777 0.416109 0.319252 0.217981 0.113352 0.006598 -0.100867 -0.207420 -0.311262 -0.410956 -0.505547 -0.594326 -0.676752 -0.752421 -0.821050 -0.882469 -0.936617 -0.983541 -1.023394 -1.056440 -1.083052 -1.103712 -1.119007 -1.129628 -1.136358 -1.139998 -1.141107 +1.184710 1.110050 1.036840 0.965984 0.898504 0.833644 0.761274 0.679565 0.590284 0.493877 0.390619 0.281434 0.167495 0.050167 -0.069022 -0.188346 -0.305833 -0.419523 -0.528075 -0.630559 -0.726266 -0.814657 -0.895336 -0.968037 -1.032619 -1.089062 -1.137468 -1.178060 -1.211191 -1.237335 -1.257092 -1.271183 -1.280440 -1.285786 -1.288054 -1.287742 +1.243183 1.158809 1.076317 0.996699 0.921110 0.849734 0.771746 0.682183 0.583321 0.475803 0.360302 0.238207 0.111071 -0.019424 -0.151434 -0.282888 -0.411466 -0.535198 -0.652809 -0.763367 -0.866154 -0.960628 -1.046399 -1.123218 -1.190975 -1.249694 -1.299539 -1.340814 -1.373965 -1.399583 -1.418398 -1.431272 -1.439187 -1.443198 -1.444104 -1.442358 +1.300910 1.206519 1.114465 1.025858 0.941977 0.863452 0.779673 0.681967 0.573037 0.453771 0.325405 0.189827 0.048963 -0.095175 -0.240399 -0.384254 -0.524144 -0.658173 -0.785084 -0.903927 -1.013972 -1.114667 -1.205628 -1.286626 -1.357580 -1.418567 -1.469819 -1.511728 -1.544850 -1.569899 -1.587742 -1.599395 -1.606003 -1.608709 -1.608248 -1.605042 +1.358030 1.253357 1.151469 1.053649 0.961301 0.875262 0.785334 0.679149 0.559618 0.427966 0.286133 0.136500 -0.018634 -0.176899 -0.335733 -0.492272 -0.643762 -0.788382 -0.924861 -1.052225 -1.169720 -1.276789 -1.373051 -1.458293 -1.532476 -1.595730 -1.648366 -1.690874 -1.723926 -1.748368 -1.765221 -1.775661 -1.780996 -1.782408 -1.780566 -1.775864 +1.414606 1.299461 1.187483 1.080229 0.979241 0.885469 0.788952 0.673911 0.543212 0.398553 0.242657 0.078384 -0.091569 -0.264451 -0.437297 -0.606831 -0.770255 -0.925787 -1.072124 -1.208256 -1.333409 -1.447015 -1.548693 -1.638256 -1.715703 -1.781230 -1.835235 -1.878313 -1.911261 -1.935071 -1.950921 -1.960159 -1.964252 -1.964367 -1.961118 -1.954875 +1.470532 1.344931 1.222636 1.105728 0.995928 0.894246 0.790705 0.666394 0.523941 0.365671 0.195109 0.015606 -0.169725 -0.357724 -0.544986 -0.727861 -0.903585 -1.070368 -1.226864 -1.372026 -1.505055 -1.625365 -1.732582 -1.826543 -1.907297 -1.975112 -2.030478 -2.074103 -2.106920 -2.130075 -2.144914 -2.152966 -2.155836 -2.154640 -2.149953 -2.142116 +1.525176 1.389818 1.257032 1.130259 1.011475 0.901713 0.790737 0.656712 0.501917 0.329434 0.143594 -0.051741 -0.253016 -0.456636 -0.658718 -0.855321 -1.043728 -1.222114 -1.389084 -1.543550 -1.684675 -1.811862 -1.924743 -2.023186 -2.107295 -2.177416 -2.234138 -2.278294 -2.310959 -2.333441 -2.347264 -2.354147 -2.355801 -2.353275 -2.347110 -2.337621 +1.576091 1.434083 1.290759 1.153917 1.025975 0.907968 0.789164 0.644957 0.477240 0.289934 0.088194 -0.123583 -0.341376 -0.561121 -0.778437 -0.989180 -1.190668 -1.381024 -1.558795 -1.722840 -1.872286 -2.006525 -2.125198 -2.228212 -2.315729 -2.388179 -2.446258 -2.490931 -2.523425 -2.545218 -2.558024 -2.563754 -2.564189 -2.560306 -2.552619 -2.541411 +1.619386 1.477421 1.323881 1.176784 1.039511 0.913087 0.786080 0.631211 0.449991 0.247242 0.028971 -0.199866 -0.434753 -0.671127 -0.904104 -1.129421 -1.344401 -1.547104 -1.736007 -1.909909 -2.067905 -2.209372 -2.333972 -2.441648 -2.532629 -2.607434 -2.666876 -2.712055 -2.744361 -2.765452 -2.777239 -2.781831 -2.781036 -2.775765 -2.766503 -2.753507 +1.652707 1.518703 1.356434 1.198932 1.052154 0.917137 0.781560 0.615550 0.420232 0.201412 -0.034029 -0.280547 -0.533104 -0.786614 -1.035692 -1.276032 -1.504928 -1.720362 -1.920730 -2.104772 -2.271546 -2.420424 -2.551086 -2.663519 -2.758022 -2.835212 -2.896022 -2.941699 -2.973802 -2.994180 -3.004949 -3.008412 -3.006369 -2.999674 -2.988782 -2.973920 +1.676548 1.555748 1.388396 1.220422 1.063964 0.920174 0.775668 0.598036 0.388014 0.152485 -0.100769 -0.365591 -0.636398 -0.907545 -1.173186 -1.429010 -1.672256 -1.900808 -2.112976 -2.307439 -2.483223 -2.639696 -2.776559 -2.893846 -2.991934 -3.071540 -3.133725 -3.179893 -3.211780 -3.231435 -3.241187 -3.243526 -3.240212 -3.232052 -3.219469 -3.202660 +1.694200 1.586793 1.419603 1.241302 1.074992 0.922243 0.768461 0.578719 0.353374 0.100493 -0.171219 -0.454970 -0.744605 -1.033891 -1.316576 -1.588357 -1.846391 -2.088450 -2.312754 -2.517922 -2.702952 -2.867206 -3.010409 -3.132651 -3.234386 -3.316440 -3.380010 -3.426664 -3.458323 -3.477245 -3.485985 -3.487195 -3.482585 -3.472915 -3.458574 -3.439733 +1.707980 1.611070 1.449551 1.261610 1.085283 0.923387 0.759987 0.557635 0.316341 0.045462 -0.245357 -0.548663 -0.857703 -1.165632 -1.465857 -1.754078 -2.027339 -2.283295 -2.520073 -2.736234 -2.930745 -3.102968 -3.252655 -3.379952 -3.485399 -3.569934 -3.634900 -3.682034 -3.713454 -3.731636 -3.739365 -3.739440 -3.733504 -3.722276 -3.706107 -3.685146 + + +# Torque coefficient + +0.037472 0.039863 0.042189 0.044441 0.046608 0.048682 0.050650 0.052503 0.054227 0.055813 0.057249 0.058524 0.059627 0.060548 0.061279 0.061812 0.062139 0.062254 0.062150 0.061823 0.061266 0.060477 0.059449 0.058181 0.056670 0.054913 0.052909 0.050657 0.048158 0.045411 0.042417 0.039178 0.035699 0.031992 0.028077 0.023982 +0.052381 0.054844 0.057148 0.059281 0.061230 0.062981 0.064525 0.065851 0.066949 0.067807 0.068416 0.068770 0.068863 0.068690 0.068248 0.067531 0.066537 0.065262 0.063704 0.061862 0.059734 0.057319 0.054617 0.051628 0.048352 0.044790 0.040942 0.036815 0.032418 0.027777 0.022923 0.017903 0.012773 0.007588 0.002402 -0.002739 +0.065213 0.067380 0.069292 0.070938 0.072309 0.073394 0.074184 0.074675 0.074865 0.074754 0.074332 0.073592 0.072533 0.071152 0.069448 0.067418 0.065062 0.062378 0.059366 0.056026 0.052356 0.048355 0.044023 0.039362 0.034379 0.029092 0.023536 0.017757 0.011818 0.005790 -0.000260 -0.006271 -0.012193 -0.017979 -0.023591 -0.028995 +0.074866 0.076494 0.077787 0.078743 0.079363 0.079649 0.079608 0.079225 0.078492 0.077414 0.075987 0.074198 0.072043 0.069521 0.066631 0.063369 0.059733 0.055720 0.051328 0.046554 0.041395 0.035855 0.029947 0.023703 0.017171 0.010419 0.003529 -0.003415 -0.010337 -0.017172 -0.023865 -0.030366 -0.036636 -0.042642 -0.048360 -0.053772 +0.080732 0.081793 0.082482 0.082797 0.082742 0.082317 0.081529 0.080389 0.078871 0.076967 0.074671 0.071964 0.068840 0.065294 0.061321 0.056916 0.052072 0.046783 0.041045 0.034858 0.028237 0.021217 0.013854 0.006227 -0.001568 -0.009429 -0.017269 -0.025012 -0.032594 -0.039958 -0.047058 -0.053856 -0.060324 -0.066445 -0.072210 -0.077620 +0.082751 0.083404 0.083688 0.083592 0.083098 0.082198 0.080892 0.079186 0.077073 0.074516 0.071504 0.068010 0.064024 0.059540 0.054546 0.049036 0.043000 0.036434 0.029344 0.021761 0.013739 0.005354 -0.003286 -0.012064 -0.020870 -0.029611 -0.038208 -0.046591 -0.054702 -0.062494 -0.069930 -0.076986 -0.083647 -0.089911 -0.095788 -0.101297 +0.081168 0.081796 0.082022 0.081832 0.081214 0.080129 0.078557 0.076500 0.073965 0.070902 0.067286 0.063089 0.058300 0.052909 0.046905 0.040278 0.033024 0.025159 0.016723 0.007784 -0.001559 -0.011179 -0.020938 -0.030718 -0.040416 -0.049944 -0.059225 -0.068197 -0.076807 -0.085019 -0.092807 -0.100161 -0.107080 -0.113582 -0.119693 -0.125454 +0.076330 0.077479 0.078131 0.078254 0.077822 0.076824 0.075212 0.072981 0.070153 0.066679 0.062522 0.057657 0.052075 0.045766 0.038719 0.030934 0.022428 0.013249 0.003478 -0.006773 -0.017357 -0.028117 -0.038919 -0.049646 -0.060199 -0.070490 -0.080449 -0.090017 -0.099151 -0.107825 -0.116026 -0.123758 -0.131040 -0.137904 -0.144397 -0.150580 +0.069367 0.071150 0.072617 0.073449 0.073520 0.072821 0.071343 0.069062 0.066023 0.062184 0.057504 0.051967 0.045567 0.038298 0.030157 0.021164 0.011372 0.000867 -0.010230 -0.021756 -0.033530 -0.045398 -0.057226 -0.068897 -0.080312 -0.091386 -0.102052 -0.112258 -0.121972 -0.131177 -0.139877 -0.148089 -0.155851 -0.163214 -0.170244 -0.177019 +0.062375 0.064394 0.066274 0.067906 0.068722 0.068500 0.067267 0.065011 0.061799 0.057605 0.052390 0.046148 0.038883 0.030593 0.021299 0.011051 -0.000061 -0.011912 -0.024329 -0.037109 -0.050069 -0.063054 -0.075926 -0.088567 -0.100879 -0.112777 -0.124201 -0.135107 -0.145472 -0.155294 -0.164589 -0.173392 -0.181759 -0.189758 -0.197475 -0.205004 +0.055786 0.058095 0.060202 0.062154 0.063724 0.064100 0.063176 0.060982 0.057604 0.053038 0.047252 0.040257 0.032063 0.022689 0.012183 0.000631 -0.011839 -0.025056 -0.038797 -0.052844 -0.067015 -0.081147 -0.095101 -0.108757 -0.122015 -0.134795 -0.147041 -0.158719 -0.169817 -0.180346 -0.190337 -0.199844 -0.208937 -0.217707 -0.226256 -0.234694 +0.049556 0.052224 0.054612 0.056772 0.058740 0.059758 0.059179 0.057054 0.053496 0.048522 0.042117 0.034307 0.025119 0.014596 0.002819 -0.010088 -0.023957 -0.038562 -0.053649 -0.068999 -0.084421 -0.099747 -0.114835 -0.129559 -0.143823 -0.157550 -0.170690 -0.183219 -0.195135 -0.206463 -0.217252 -0.227571 -0.237513 -0.247185 -0.256708 -0.266195 +0.043622 0.046710 0.049429 0.051833 0.053998 0.055556 0.055329 0.053259 0.049491 0.044065 0.036985 0.028295 0.018045 0.006309 -0.006798 -0.021114 -0.036421 -0.052446 -0.068920 -0.085619 -0.102343 -0.118920 -0.135198 -0.151054 -0.166390 -0.181134 -0.195243 -0.208702 -0.221522 -0.233743 -0.245430 -0.256672 -0.267580 -0.278282 -0.288912 -0.299578 +0.037935 0.041491 0.044584 0.047266 0.049622 0.051537 0.051646 0.049606 0.045590 0.039659 0.031843 0.022208 0.010830 -0.002183 -0.016681 -0.032459 -0.049246 -0.066732 -0.084645 -0.102748 -0.120835 -0.138722 -0.156255 -0.173309 -0.189786 -0.205620 -0.220774 -0.235243 -0.249053 -0.262259 -0.274945 -0.287219 -0.299210 -0.311066 -0.322928 -0.334897 +0.032456 0.036519 0.040022 0.043010 0.045573 0.047718 0.048132 0.046087 0.041780 0.035289 0.026675 0.016029 0.003459 -0.010897 -0.026846 -0.044138 -0.062450 -0.081451 -0.100860 -0.120429 -0.139940 -0.159203 -0.178059 -0.196379 -0.214068 -0.231064 -0.247340 -0.262901 -0.277787 -0.292072 -0.305855 -0.319266 -0.332455 -0.345586 -0.358796 -0.372188 +0.027151 0.031757 0.035697 0.039014 0.041799 0.044109 0.044777 0.042689 0.038042 0.030935 0.021462 0.009742 -0.004087 -0.019848 -0.037309 -0.056167 -0.076055 -0.096630 -0.117598 -0.138697 -0.159698 -0.180404 -0.200651 -0.220307 -0.239280 -0.257514 -0.274988 -0.291722 -0.307771 -0.323225 -0.338205 -0.352859 -0.367357 -0.381875 -0.396548 -0.411479 +0.021993 0.027170 0.031573 0.035239 0.038257 0.040706 0.041565 0.039392 0.034359 0.026580 0.016186 0.003328 -0.011823 -0.029052 -0.048084 -0.068562 -0.090085 -0.112296 -0.134887 -0.157583 -0.180143 -0.202361 -0.224067 -0.245131 -0.265460 -0.285004 -0.303755 -0.321743 -0.339041 -0.355756 -0.372029 -0.388028 -0.403945 -0.419960 -0.436207 -0.452787 +0.016965 0.022733 0.027619 0.031649 0.034911 0.037492 0.038479 0.036181 0.030710 0.022204 0.010830 -0.003227 -0.019763 -0.038523 -0.059185 -0.081340 -0.104557 -0.128470 -0.152752 -0.177113 -0.201301 -0.225100 -0.248337 -0.270879 -0.292637 -0.313567 -0.333672 -0.352996 -0.371627 -0.389693 -0.407355 -0.424802 -0.442242 -0.459860 -0.477787 -0.496128 +0.012064 0.018424 0.023812 0.028219 0.031730 0.034437 0.035502 0.033036 0.027080 0.017791 0.005379 -0.009938 -0.027920 -0.048274 -0.070626 -0.094514 -0.119492 -0.145173 -0.171214 -0.197310 -0.223196 -0.248647 -0.273485 -0.297577 -0.320836 -0.343227 -0.364762 -0.385503 -0.405553 -0.425060 -0.444205 -0.463198 -0.482266 -0.501590 -0.521302 -0.541510 +0.007324 0.014229 0.020129 0.024924 0.028690 0.031518 0.032617 0.029942 0.023452 0.013327 -0.000179 -0.016816 -0.036308 -0.058317 -0.082416 -0.108101 -0.134905 -0.162422 -0.190292 -0.218192 -0.245847 -0.273021 -0.299531 -0.325244 -0.350078 -0.374004 -0.397048 -0.419285 -0.440838 -0.461874 -0.482595 -0.503234 -0.524029 -0.545160 -0.566761 -0.588942 +0.002913 0.010141 0.016554 0.021744 0.025767 0.028712 0.029808 0.026883 0.019811 0.008799 -0.005858 -0.023874 -0.044936 -0.068661 -0.094568 -0.122112 -0.150808 -0.180232 -0.210000 -0.239777 -0.269270 -0.298238 -0.326492 -0.353898 -0.380379 -0.405915 -0.430545 -0.454359 -0.477498 -0.500151 -0.522541 -0.544921 -0.567541 -0.590579 -0.614170 -0.638429 +-0.000889 0.006170 0.013071 0.018663 0.022945 0.025999 0.027061 0.023846 0.016144 0.004194 -0.011667 -0.031121 -0.053813 -0.079315 -0.107090 -0.136558 -0.167215 -0.198614 -0.230353 -0.262077 -0.293480 -0.324313 -0.354382 -0.383553 -0.411754 -0.438976 -0.465267 -0.490737 -0.515547 -0.539903 -0.564052 -0.588270 -0.612810 -0.637852 -0.663535 -0.689973 +-0.003916 0.002388 0.009671 0.015666 0.020207 0.023364 0.024362 0.020817 0.012440 -0.000496 -0.017616 -0.038565 -0.062948 -0.090288 -0.119991 -0.151449 -0.184137 -0.217582 -0.251362 -0.285104 -0.318489 -0.351258 -0.383212 -0.414220 -0.444215 -0.473196 -0.501227 -0.528432 -0.554993 -0.581139 -0.607138 -0.633286 -0.659843 -0.686986 -0.714858 -0.743578 +-0.006209 -0.001053 0.006345 0.012740 0.017540 0.020791 0.021699 0.017786 0.008689 -0.005281 -0.023713 -0.046213 -0.072348 -0.101586 -0.133279 -0.166794 -0.201581 -0.237144 -0.273037 -0.308868 -0.344306 -0.379082 -0.412994 -0.445912 -0.477773 -0.508588 -0.538433 -0.567453 -0.595847 -0.623867 -0.651805 -0.679977 -0.708643 -0.737983 -0.768143 -0.799245 +-0.008023 -0.004030 0.003098 0.009875 0.014931 0.018268 0.019060 0.014742 0.004884 -0.010169 -0.029964 -0.054073 -0.082018 -0.113214 -0.146961 -0.182601 -0.219558 -0.257309 -0.295386 -0.333378 -0.370940 -0.407795 -0.443737 -0.478635 -0.512436 -0.545158 -0.576895 -0.607806 -0.638115 -0.668095 -0.698061 -0.728347 -0.759214 -0.790846 -0.823390 -0.856975 +-0.009537 -0.006489 -0.000041 0.007061 0.012370 0.015784 0.016436 0.011677 0.001015 -0.015166 -0.036375 -0.062150 -0.091964 -0.125178 -0.161043 -0.198876 -0.238074 -0.278084 -0.318416 -0.358641 -0.398399 -0.437404 -0.475447 -0.512399 -0.548211 -0.582914 -0.616617 -0.649499 -0.681803 -0.713827 -0.745909 -0.778399 -0.811560 -0.845577 -0.880603 -0.916770 + diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN b/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN new file mode 100644 index 00000000..322213ff --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN @@ -0,0 +1,198 @@ +! Controller parameter input file for the MHK_RM1_Floating wind turbine +! - File written using ROSCO version 2.8.0 controller tuning logic on 01/05/24 + +!------- SIMULATION CONTROL ------------------------------------------------------------ +2 ! LoggingLevel - {0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)} +0 ! DT_Out - {Time step to output .dbg* files, or 0 to match sampling period of OpenFAST} +1 ! Ext_Interface - (0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0.) +0 ! Echo - (0 - no Echo, 1 - Echo input data to .echo) + +!------- CONTROLLER FLAGS ------------------------------------------------- +1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals +0 ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} +3 ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)} +1 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} +1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} +0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} +1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} +0 ! PRC_Mode - Power reference tracking mode{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints} +0 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} +0 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} +0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} +1 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} +0 ! TD_Mode - Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle +0 ! TRA_Mode - Tower resonance avoidance mode (0- no tower resonsnace avoidance, 1- use torque control setpoints to avoid a specific frequency +0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} +0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: rotor position control} +0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} +0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} +0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} +0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} +0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} +0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] +0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] + +!------- FILTERS ---------------------------------------------------------- +15.07080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] +0.00000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] +2 ! F_NumNotchFilts - Number of notch filters placed on sensors +1.0000 2.4200 ! F_NotchFreqs - Natural frequency of the notch filters. Array with length F_NumNotchFilts +0.0000 0.0000 ! F_NotchBetaNum - Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] +0.2500 0.2500 ! F_NotchBetaDen - Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] +2 ! F_GenSpdNotch_N - Number of notch filters on generator speed +1 2 ! F_GenSpdNotch_Ind - Indices of notch filters on generator speed +2 ! F_TwrTopNotch_N - Number of notch filters on tower top acceleration signal +1 2 ! F_TwrTopNotch_Ind - Indices of notch filters on tower top acceleration signal +0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. +0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. +0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. +0.661300 1.000000 ! F_FlCornerFreq - Natural frequency and damping in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s, -]. +1.50000 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. +0.0000 1.0000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control + +!------- BLADE PITCH CONTROL ---------------------------------------------- +30 ! PC_GS_n - Amount of gain-scheduling table entries +0.030335 0.049075 0.063610 0.076093 0.087460 0.097196 0.106672 0.115225 0.123634 0.131302 0.139019 0.146056 0.153083 0.159873 0.166338 0.172854 0.178999 0.185046 0.191143 0.196863 0.202559 0.208301 0.213742 0.219137 0.224575 0.229836 0.234972 0.240145 0.245291 0.250200 ! PC_GS_angles - Gain-schedule table: pitch angles [rad]. +-0.010178 -0.008780 -0.007625 -0.006655 -0.005829 -0.005116 -0.004495 -0.003950 -0.003467 -0.003036 -0.002650 -0.002301 -0.001984 -0.001696 -0.001432 -0.001190 -0.000966 -0.000760 -0.000568 -0.000390 -0.000225 -0.000069 0.000076 0.000212 0.000340 0.000461 0.000575 0.000682 0.000784 0.000881 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. +-0.005272 -0.004770 -0.004355 -0.004007 -0.003710 -0.003454 -0.003232 -0.003036 -0.002862 -0.002708 -0.002569 -0.002443 -0.002330 -0.002226 -0.002132 -0.002045 -0.001964 -0.001890 -0.001822 -0.001758 -0.001698 -0.001642 -0.001590 -0.001541 -0.001495 -0.001452 -0.001411 -0.001372 -0.001336 -0.001301 ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-]. +0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 ! PC_GS_KD - Gain-schedule table: pitch controller kd gains +0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 ! PC_GS_TF - Gain-schedule table: pitch controller tf gains (derivative filter) +1.570000000000 ! PC_MaxPit - Maximum physical pitch limit, [rad]. +0.000690000000 ! PC_MinPit - Minimum physical pitch limit, [rad]. +0.174500000000 ! PC_MaxRat - Maximum pitch rate (in absolute value) in pitch controller, [rad/s]. +-0.17450000000 ! PC_MinRat - Minimum pitch rate (in absolute value) in pitch controller, [rad/s]. +63.81200000000 ! PC_RefSpd - Desired (reference) HSS speed for pitch controller, [rad/s]. +0.000690000000 ! PC_FinePit - Record 5: Below-rated pitch angle set-point, [rad] +0.017450000000 ! PC_Switch - Angle above lowest minimum pitch angle for switch, [rad] + +!------- INDIVIDUAL PITCH CONTROL ----------------------------------------- +1.600000 2.000000 ! IPC_Vramp - Start and end wind speeds for cut-in ramp function. First entry: IPC inactive, second entry: IPC fully active. [m/s] +2 ! IPC_SatMode - IPC Saturation method (0 - no saturation (except by PC_MinPit), 1 - saturate by PS_BldPitchMin, 2 - saturate sotfly (full IPC cycle) by PC_MinPit, 3 - saturate softly by PS_BldPitchMin) +0.3 ! IPC_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from IPC), [rad] +0.000e+00 0.000e+00 ! IPC_KP - Proportional gain for the individual pitch controller: first parameter for 1P reductions, second for 2P reductions, [-] +0.000e+00 0.000e+00 ! IPC_KI - Integral gain for the individual pitch controller: first parameter for 1P reductions, second for 2P reductions, [-] +0.000000 0.000000 ! IPC_aziOffset - Phase offset added to the azimuth angle for the individual pitch controller, [rad]. +0.0 ! IPC_CornerFreqAct - Corner frequency of the first-order actuators model, to induce a phase lag in the IPC signal {0: Disable}, [rad/s] + +!------- VS TORQUE CONTROL ------------------------------------------------ +94.40000000000 ! VS_GenEff - Generator efficiency mechanical power -> electrical power, [should match the efficiency defined in the generator properties!], [%] +8300.335630000 ! VS_ArSatTq - Above rated generator torque PI control saturation, [Nm] +1500000.000000 ! VS_MaxRat - Maximum torque rate (in absolute value) in torque controller, [Nm/s]. +12450.50344000 ! VS_MaxTq - Maximum generator torque in Region 3 (HSS side), [Nm]. +0.000000000000 ! VS_MinTq - Minimum generator torque (HSS side), [Nm]. +19.00309000000 ! VS_MinOMSpd - Minimum generator speed [rad/s] +1.142870000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side). Only used in VS_ControlMode = 1,3 +500000.0000000 ! VS_RtPwr - Wind turbine rated power [W] +8300.335630000 ! VS_RtTq - Rated torque, [Nm]. +63.81200000000 ! VS_RefSpd - Rated generator speed [rad/s] +1 ! VS_n - Number of generator PI torque controller gains +-63.8796200000 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) +-84.4329000000 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) +7.17 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. +0.314000000000 ! VS_PwrFiltF - Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. + +!------- SETPOINT SMOOTHER --------------------------------------------- +1.00000 ! SS_VSGain - Variable speed torque controller setpoint smoother gain, [-]. +0.00100 ! SS_PCGain - Collective pitch controller setpoint smoother gain, [-]. + +!------- POWER REFERENCE TRACKING -------------------------------------- +2 ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array +0.07854 ! PRC_LPF_Freq - Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] +3.0000 25.0000 ! PRC_WindSpeeds - Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] +0.7917 0.7917 ! PRC_GenSpeeds - Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + +!------- WIND SPEED ESTIMATOR --------------------------------------------- +10.000 ! WE_BladeRadius - Blade length (distance from hub center to blade tip), [m] +1 ! WE_CP_n - Amount of parameters in the Cp array +0.0 ! WE_CP - Parameters that define the parameterized CP(lambda) function +0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] +53.0 ! WE_GearboxRatio - Gearbox ratio [>=1], [-] +484024.50000 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] +1025.000 ! WE_RhoAir - Air density, [kg m^-3] +"MHK_RM1_Cp_Ct_Cq.txt" ! PerfFileName - File containing rotor performance tables (Cp,Ct,Cq) (absolute path or relative to this file) +36 26 ! PerfTableSize - Size of rotor performance tables, first number refers to number of blade pitch angles, second number referse to number of tip-speed ratios +60 ! WE_FOPoles_N - Number of first-order system poles used in EKF +0.5000 0.5517 0.6034 0.6552 0.7069 0.7586 0.8103 0.8621 0.9138 0.9655 1.0172 1.0690 1.1207 1.1724 1.2241 1.2759 1.3276 1.3793 1.4310 1.4828 1.5345 1.5862 1.6379 1.6897 1.7414 1.7931 1.8448 1.8966 1.9483 2.0000 2.0333 2.0667 2.1000 2.1333 2.1667 2.2000 2.2333 2.2667 2.3000 2.3333 2.3667 2.4000 2.4333 2.4667 2.5000 2.5333 2.5667 2.6000 2.6333 2.6667 2.7000 2.7333 2.7667 2.8000 2.8333 2.8667 2.9000 2.9333 2.9667 3.0000 ! WE_FOPoles_v - Wind speeds corresponding to first-order system poles [m/s] +-0.14364445 -0.15850422 -0.17336400 -0.18822377 -0.20308354 -0.21794331 -0.23280308 -0.24766285 -0.26252262 -0.27738239 -0.29224216 -0.30710193 -0.32196171 -0.33682148 -0.35168125 -0.36654102 -0.38140079 -0.39626056 -0.41112033 -0.42598010 -0.44083987 -0.45569965 -0.47055942 -0.48666545 -0.50602877 -0.52082936 -0.60274133 -0.60720589 -0.60927938 -0.55668516 0.17844923 0.15174296 0.10860051 0.05753679 0.00176535 -0.05812003 -0.11803585 -0.18146508 -0.24666701 -0.31440662 -0.38335107 -0.45418067 -0.52480063 -0.59662243 -0.67000720 -0.74481113 -0.82056059 -0.89753628 -0.97589183 -1.05446405 -1.13345094 -1.21374047 -1.29379323 -1.37507241 -1.45808464 -1.54093580 -1.62426617 -1.70957888 -1.79610923 -1.88140848 ! WE_FOPoles - First order system poles [1/s] + +!------- YAW CONTROL ------------------------------------------------------ +0.00000 ! Y_uSwitch - Wind speed to switch between Y_ErrThresh. If zero, only the second value of Y_ErrThresh is used [m/s] +4.000000 8.000000 ! Y_ErrThresh - Yaw error threshold/deadbands. Turbine begins to yaw when it passes this. If Y_uSwitch is zero, only the second value is used. [deg]. +0.00870 ! Y_Rate - Yaw rate [rad/s] +0.00000 ! Y_MErrSet - Integrator saturation (maximum signal amplitude contribution to pitch from yaw-by-IPC), [rad] +0.00000 ! Y_IPC_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from yaw-by-IPC), [rad] +0.00000 ! Y_IPC_KP - Yaw-by-IPC proportional controller gain Kp +0.00000 ! Y_IPC_KI - Yaw-by-IPC integral controller gain Ki + +!------- TOWER CONTROL ------------------------------------------------------ +0.00000 ! TRA_ExclSpeed - Rotor speed for exclusion [LSS, rad/s] +0.00000 ! TRA_ExclBand - Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 +0.00000e+00 ! TRA_RateLimit - Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/400. +0.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller, [rad*s/m] +0.00000 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] +0.00000 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] + +!------- MINIMUM PITCH SATURATION ------------------------------------------- +60 ! PS_BldPitchMin_N - Number of values in minimum blade pitch lookup table (should equal number of values in PS_WindSpeeds and PS_BldPitchMin) +0.500 0.552 0.603 0.655 0.707 0.759 0.810 0.862 0.914 0.966 1.017 1.069 1.121 1.172 1.224 1.276 1.328 1.379 1.431 1.483 1.534 1.586 1.638 1.690 1.741 1.793 1.845 1.897 1.948 2.000 2.033 2.067 2.100 2.133 2.167 2.200 2.233 2.267 2.300 2.333 2.367 2.400 2.433 2.467 2.500 2.533 2.567 2.600 2.633 2.667 2.700 2.733 2.767 2.800 2.833 2.867 2.900 2.933 2.967 3.000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] +0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 ! PS_BldPitchMin - Minimum blade pitch angles [rad] + +!------- SHUTDOWN ----------------------------------------------------------- +0.436300000000 ! SD_MaxPit - Maximum blade pitch angle to initiate shutdown, [rad] +0.418880000000 ! SD_CornerFreq - Cutoff Frequency for first order low-pass filter for blade pitch angle, [rad/s] + +!------- Floating ----------------------------------------------------------- +1 ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1 +-0.3999 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +2.1000 ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] + +!------- FLAP ACTUATION ----------------------------------------------------- +0.000000000000 ! Flp_Angle - Initial or steady state flap angle [rad] +0.00000000e+00 ! Flp_Kp - Blade root bending moment proportional gain for flap control [s] +0.00000000e+00 ! Flp_Ki - Flap displacement integral gain for flap control [-] +0.174500000000 ! Flp_MaxPit - Maximum (and minimum) flap pitch angle [rad] + +!------- Open Loop Control ----------------------------------------------------- +"unused" ! OL_Filename - Input file with open loop timeseries (absolute path or relative to this file) +0 ! Ind_Breakpoint - The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) + 0 0 0 ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array] +0 ! Ind_GenTq - The column in OL_Filename that contains the generator torque in Nm +0 ! Ind_YawRate - The column in OL_Filename that contains the yaw rate in rad/s +0 ! Ind_Azimuth - The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) +0.0000 0.0000 0.0000 0.0000 ! RP_Gains - PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) +0 ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N] +0 ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N] + +!------- Pitch Actuator Model ----------------------------------------------------- +3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] +0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] + +!------- Pitch Actuator Faults ----------------------------------------------------- +0.00000000 0.00000000 0.00000000 ! PF_Offsets - Constant blade pitch offsets for blades 1-3 [rad] + +!------- Active Wake Control ----------------------------------------------------- +1 ! AWC_NumModes - Number of user-defined AWC forcing modes +1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) +1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) +0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] +1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] +0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] + +!------- External Controller Interface ----------------------------------------------------- +"unused" ! DLL_FileName - Name/location of the dynamic library in the Bladed-DLL format +"unused" ! DLL_InFile - Name of input file sent to the DLL (-) +"DISCON" ! DLL_ProcName - Name of procedure in DLL to be called (-) + +!------- ZeroMQ Interface --------------------------------------------------------- +"tcp://localhost:5555" ! ZMQ_CommAddress - Communication address for ZMQ server, (e.g. "tcp://localhost:5555") +1.000000 ! ZMQ_UpdatePeriod - Update period at zmq interface to send measurements and wait for setpoint [sec.] +0 ! ZMQ_ID - Integer identifier of turbine + +!------- Cable Control --------------------------------------------------------- +1 ! CC_Group_N - Number of cable control groups +0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL +20.000000 ! CC_ActTau - Time constant for line actuator [s] + +!------- Structural Controllers --------------------------------------------------------- +1 ! StC_Group_N - Number of cable control groups +0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat new file mode 100644 index 00000000..df6ab8c8 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat @@ -0,0 +1,107 @@ +------- ELASTODYN V1.00.* INDIVIDUAL BLADE INPUT FILE -------------------------- +Floating MHK turbine structural blade input properties, based on the RM1 tidal current rotor +---------------------- BLADE PARAMETERS ---------------------------------------- + 75 NBlInpSt - Number of blade input stations (-) + 1 BldFlDmp(1) - Blade flap mode #1 structural damping in percent of critical (%) + 1 BldFlDmp(2) - Blade flap mode #2 structural damping in percent of critical (%) + 1 BldEdDmp(1) - Blade edge mode #1 structural damping in percent of critical (%) +---------------------- BLADE ADJUSTMENT FACTORS -------------------------------- + 1 FlStTunr(1) - Blade flapwise modal stiffness tuner, 1st mode (-) + 1 FlStTunr(2) - Blade flapwise modal stiffness tuner, 2nd mode (-) + 2.5 AdjBlMs - Factor to adjust blade mass density (-) + 1.0E-05 AdjFlSt - Factor to adjust blade flap stiffness (-) + 1.0E-05 AdjEdSt - Factor to adjust blade edge stiffness (-) +---------------------- DISTRIBUTED BLADE PROPERTIES ---------------------------- +BlFract PitchAxis StrcTwst BMassDen FlpStff EdgStff +(-) (-) (deg) (kg/m) (Nm^2) (Nm^2) +0.0000 0.5000 12.860 818.68 2.43E+14 2.52E+14 +0.0083 0.4953 12.860 833.60 2.47E+14 2.69E+14 +0.0167 0.4907 12.860 846.44 2.47E+14 2.84E+14 +0.0250 0.4860 12.860 858.68 2.46E+14 3.00E+14 +0.0333 0.4813 12.860 870.32 2.44E+14 3.15E+14 +0.0417 0.4701 12.860 900.64 2.50E+14 3.59E+14 +0.0500 0.4590 12.860 932.64 2.49E+14 4.03E+14 +0.0583 0.4478 12.860 681.32 1.70E+14 1.12E+14 +0.0667 0.4366 12.860 628.00 1.48E+14 1.11E+14 +0.0750 0.4233 12.860 575.28 1.30E+14 1.10E+14 +0.0833 0.4100 12.860 528.96 1.12E+14 1.07E+14 +0.0917 0.3967 12.860 458.92 8.82E+13 9.56E+13 +0.1000 0.3834 12.860 401.60 6.72E+13 8.55E+13 +0.1083 0.3722 12.860 411.16 6.45E+13 9.15E+13 +0.1167 0.3611 12.860 410.28 6.00E+13 9.53E+13 +0.1250 0.3499 12.860 415.36 5.62E+13 1.01E+14 +0.1333 0.3387 12.860 421.00 5.17E+13 1.06E+14 +0.1417 0.3340 12.860 421.28 4.94E+13 1.08E+14 +0.1500 0.3294 12.860 421.40 4.70E+13 1.10E+14 +0.1583 0.3247 12.860 424.96 4.45E+13 1.12E+14 +0.1667 0.3200 12.860 435.48 4.30E+13 1.16E+14 +0.1750 0.3200 12.530 428.40 4.09E+13 1.13E+14 +0.1833 0.3200 12.200 423.88 3.89E+13 1.10E+14 +0.1917 0.3200 11.870 435.68 3.84E+13 1.15E+14 +0.2000 0.3200 11.540 430.60 3.62E+13 1.12E+14 +0.2083 0.3200 11.265 434.52 3.57E+13 1.11E+14 +0.2167 0.3200 10.990 430.28 3.41E+13 1.09E+14 +0.2250 0.3200 10.715 426.04 3.26E+13 1.06E+14 +0.2333 0.3200 10.440 421.84 3.11E+13 1.03E+14 +0.2500 0.3200 9.970 415.00 2.91E+13 9.84E+13 +0.2667 0.3200 9.500 411.20 2.72E+13 9.54E+13 +0.2833 0.3200 9.105 395.88 2.54E+13 8.96E+13 +0.3000 0.3200 8.710 390.40 2.43E+13 8.59E+13 +0.3167 0.3200 8.365 377.84 2.26E+13 8.06E+13 +0.3333 0.3200 8.020 362.44 2.15E+13 7.34E+13 +0.3500 0.3200 7.725 347.48 2.00E+13 6.87E+13 +0.3667 0.3200 7.430 335.60 1.85E+13 6.42E+13 +0.3833 0.3200 7.170 330.64 1.77E+13 6.14E+13 +0.4000 0.3200 6.910 318.96 1.63E+13 5.72E+13 +0.4167 0.3200 6.680 302.84 1.50E+13 5.33E+13 +0.4333 0.3200 6.450 298.24 1.43E+13 5.09E+13 +0.4500 0.3200 6.245 287.12 1.32E+13 4.73E+13 +0.4667 0.3200 6.040 267.24 1.19E+13 4.12E+13 +0.4833 0.3200 5.860 256.68 1.09E+13 3.81E+13 +0.5000 0.3200 5.680 249.96 1.04E+13 3.62E+13 +0.5167 0.3200 5.515 239.68 9.42E+12 3.33E+13 +0.5333 0.3200 5.350 227.76 8.54E+12 3.06E+13 +0.5500 0.3200 5.200 215.64 7.73E+12 2.81E+13 +0.5667 0.3200 5.050 206.16 6.97E+12 2.58E+13 +0.5833 0.3200 4.910 188.80 6.17E+12 2.17E+13 +0.6000 0.3200 4.770 179.80 5.51E+12 1.97E+13 +0.6167 0.3200 4.640 176.28 5.19E+12 1.85E+13 +0.6333 0.3200 4.510 165.32 4.61E+12 1.68E+13 +0.6500 0.3200 4.385 156.80 4.07E+12 1.51E+13 +0.6667 0.3200 4.260 144.88 3.57E+12 1.36E+13 +0.6833 0.3200 4.145 136.80 3.11E+12 1.21E+13 +0.7000 0.3200 4.030 128.92 2.69E+12 1.08E+13 +0.7167 0.3200 3.915 119.36 2.31E+12 9.55E+12 +0.7333 0.3200 3.800 111.96 1.96E+12 8.42E+12 +0.7500 0.3200 3.685 103.00 1.65E+12 7.39E+12 +0.7667 0.3200 3.570 94.72 1.37E+12 6.45E+12 +0.7833 0.3200 3.460 87.96 1.12E+12 5.57E+12 +0.8000 0.3200 3.350 79.76 8.91E+11 4.77E+12 +0.8167 0.3200 3.240 73.52 6.93E+11 4.05E+12 +0.8333 0.3200 3.130 71.44 6.36E+11 3.72E+12 +0.8500 0.3200 3.015 64.00 4.76E+11 3.11E+12 +0.8667 0.3200 2.900 57.24 3.38E+11 2.56E+12 +0.8833 0.3200 2.785 50.36 2.19E+11 2.04E+12 +0.9000 0.3200 2.670 48.68 1.98E+11 1.84E+12 +0.9167 0.3200 2.550 47.00 1.78E+11 1.66E+12 +0.9333 0.3200 2.430 45.32 1.59E+11 1.49E+12 +0.9500 0.3200 2.305 46.76 1.98E+11 1.51E+12 +0.9667 0.3200 2.180 44.04 1.76E+11 1.34E+12 +0.9833 0.3200 2.060 42.28 1.56E+11 1.19E+12 +1.0000 0.3200 2.060 42.28 1.56E+11 1.19E+12 +---------------------- BLADE MODE SHAPES --------------------------------------- + 1.88070 BldFl1Sh(2) - Flap mode 1, coeff of x^2 +-1.44580 BldFl1Sh(3) - , coeff of x^3 + 0.71967 BldFl1Sh(4) - , coeff of x^4 +-0.03633 BldFl1Sh(5) - , coeff of x^5 +-0.11822 BldFl1Sh(6) - , coeff of x^6 +-5.52180 BldFl2Sh(2) - Flap mode 2, coeff of x^2 + 7.45710 BldFl2Sh(3) - , coeff of x^3 + 2.84170 BldFl2Sh(4) - , coeff of x^4 +-3.97820 BldFl2Sh(5) - , coeff of x^5 + 0.20116 BldFl2Sh(6) - , coeff of x^6 + 2.48090 BldEdgSh(2) - Edge mode 1, coeff of x^2 +-4.17160 BldEdgSh(3) - , coeff of x^3 + 5.03260 BldEdgSh(4) - , coeff of x^4 +-2.86170 BldEdgSh(5) - , coeff of x^5 + 0.51983 BldEdgSh(6) - , coeff of x^6 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat new file mode 100644 index 00000000..3c04a12f --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat @@ -0,0 +1,52 @@ +------- ELASTODYN V1.00.* TOWER INPUT FILE ------------------------------------- +Floating MHK turbine structural tower input properties, based on the RM1 tidal current rotor +---------------------- TOWER PARAMETERS ---------------------------------------- + 11 NTwInpSt - Number of input stations to specify tower geometry + 1 TwrFADmp(1) - Tower 1st fore-aft mode structural damping ratio (%) + 1 TwrFADmp(2) - Tower 2nd fore-aft mode structural damping ratio (%) + 1 TwrSSDmp(1) - Tower 1st side-to-side mode structural damping ratio (%) + 1 TwrSSDmp(2) - Tower 2nd side-to-side mode structural damping ratio (%) +---------------------- TOWER ADJUSTMUNT FACTORS -------------------------------- + 1 FAStTunr(1) - Tower fore-aft modal stiffness tuner, 1st mode (-) + 1 FAStTunr(2) - Tower fore-aft modal stiffness tuner, 2nd mode (-) + 1 SSStTunr(1) - Tower side-to-side stiffness tuner, 1st mode (-) + 1 SSStTunr(2) - Tower side-to-side stiffness tuner, 2nd mode (-) + 1 AdjTwMa - Factor to adjust tower mass density (-) + 1.0E-03 AdjFASt - Factor to adjust tower fore-aft stiffness (-) + 1.0E-03 AdjSSSt - Factor to adjust tower side-to-side stiffness (-) +---------------------- DISTRIBUTED TOWER PROPERTIES ---------------------------- +HtFract TMassDen TwFAStif TwSSStif +(-) (kg/m) (Nm^2) (Nm^2) +0.0000000E+00 5076.39 1.27E+11 1.27E+11 +1.0000000E-01 5076.39 1.27E+11 1.27E+11 +2.0000000E-01 5076.39 1.27E+11 1.27E+11 +3.0000000E-01 5076.39 1.27E+11 1.27E+11 +4.0000000E-01 5076.39 1.27E+11 1.27E+11 +5.0000000E-01 5076.39 1.27E+11 1.27E+11 +6.0000000E-01 5076.39 1.27E+11 1.27E+11 +7.0000000E-01 5076.39 1.27E+11 1.27E+11 +8.0000000E-01 5076.39 1.27E+11 1.27E+11 +9.0000000E-01 5076.39 1.27E+11 1.27E+11 +1.0000000E+00 5076.39 1.27E+11 1.27E+11 +---------------------- TOWER FORE-AFT MODE SHAPES ------------------------------ + -5.6786 TwFAM1Sh(2) - Mode 1, coefficient of x^2 term + 41.5614 TwFAM1Sh(3) - , coefficient of x^3 term + -93.3287 TwFAM1Sh(4) - , coefficient of x^4 term + 89.2568 TwFAM1Sh(5) - , coefficient of x^5 term + -30.8109 TwFAM1Sh(6) - , coefficient of x^6 term + 0.6979 TwFAM2Sh(2) - Mode 2, coefficient of x^2 term + 1.2146 TwFAM2Sh(3) - , coefficient of x^3 term + -1.6999 TwFAM2Sh(4) - , coefficient of x^4 term + 0.8473 TwFAM2Sh(5) - , coefficient of x^5 term + -0.0599 TwFAM2Sh(6) - , coefficient of x^6 term +---------------------- TOWER SIDE-TO-SIDE MODE SHAPES -------------------------- + 0.5640 TwSSM1Sh(2) - Mode 1, coefficient of x^2 term + 4.7082 TwSSM1Sh(3) - , coefficient of x^3 term + -14.9130 TwSSM1Sh(4) - , coefficient of x^4 term + 18.2340 TwSSM1Sh(5) - , coefficient of x^5 term + -7.5932 TwSSM1Sh(6) - , coefficient of x^6 term + 0.9525 TwSSM2Sh(2) - Mode 2, coefficient of x^2 term + 0.4369 TwSSM2Sh(3) - , coefficient of x^3 term + -1.1374 TwSSM2Sh(4) - , coefficient of x^4 term + 1.1954 TwSSM2Sh(5) - , coefficient of x^5 term + -0.4474 TwSSM2Sh(6) - , coefficient of x^6 term \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.1 b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.1 new file mode 100644 index 00000000..c32060dc --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.1 @@ -0,0 +1,4220 @@ + -1.000000E+00 1 1 1.999545E+03 + -1.000000E+00 1 5 -1.038155E+04 + -1.000000E+00 2 2 2.266626E+03 + -1.000000E+00 2 4 1.450345E+04 + -1.000000E+00 3 3 2.167146E+03 + -1.000000E+00 4 2 1.451960E+04 + -1.000000E+00 4 4 2.703220E+05 + -1.000000E+00 5 1 -1.039882E+04 + -1.000000E+00 5 5 8.266187E+05 + -1.000000E+00 6 6 9.046082E+05 + 0.000000E+00 1 1 1.411834E+03 + 0.000000E+00 1 5 -9.031812E+03 + 0.000000E+00 2 2 1.657916E+03 + 0.000000E+00 2 4 1.228014E+04 + 0.000000E+00 3 3 2.166489E+03 + 0.000000E+00 4 2 1.229162E+04 + 0.000000E+00 4 4 2.611510E+05 + 0.000000E+00 5 1 -9.043577E+03 + 0.000000E+00 5 5 8.192453E+05 + 0.000000E+00 6 6 6.521804E+05 + 1.000000E-01 1 1 1.647323E+03 6.332432E-04 + 1.000000E-01 1 5 -9.712987E+03 1.055422E-06 + 1.000000E-01 2 2 1.921107E+03 -6.797895E-06 + 1.000000E-01 2 4 1.298169E+04 -4.832497E-06 + 1.000000E-01 3 3 2.120432E+03 -1.464990E-06 + 1.000000E-01 4 2 1.312899E+04 2.916794E-05 + 1.000000E-01 4 4 2.638432E+05 2.756118E-05 + 1.000000E-01 5 1 -9.566795E+03 -3.792644E-03 + 1.000000E-01 5 5 8.247277E+05 -3.473593E-07 + 1.000000E-01 6 6 8.442138E+05 7.588721E+03 + 2.000000E-01 1 1 1.489483E+03 -5.117749E-03 + 2.000000E-01 1 5 -9.217624E+03 7.927747E-03 + 2.000000E-01 2 2 1.736418E+03 8.147049E-03 + 2.000000E-01 2 4 1.245268E+04 1.932775E-02 + 2.000000E-01 3 3 2.164448E+03 9.414506E-04 + 2.000000E-01 4 2 1.251272E+04 -4.435483E-02 + 2.000000E-01 4 4 2.615695E+05 -1.109551E-01 + 2.000000E-01 5 1 -9.202860E+03 1.644901E-04 + 2.000000E-01 5 5 8.194167E+05 -1.930356E-04 + 2.000000E-01 6 6 6.884296E+05 -1.733961E-01 + 3.000000E-01 1 1 1.444033E+03 6.269322E-03 + 3.000000E-01 1 5 -9.111029E+03 7.101058E-03 + 3.000000E-01 2 2 1.690542E+03 1.995744E-02 + 3.000000E-01 2 4 1.235828E+04 2.445857E-02 + 3.000000E-01 3 3 2.169583E+03 1.453299E-03 + 3.000000E-01 4 2 1.236276E+04 -1.233631E-01 + 3.000000E-01 4 4 2.614335E+05 -1.543396E-01 + 3.000000E-01 5 1 -9.125158E+03 3.700770E-04 + 3.000000E-01 5 5 8.191486E+05 -7.132935E-04 + 3.000000E-01 6 6 6.673795E+05 -4.440385E-02 + 4.000000E-01 1 1 1.425401E+03 -4.108052E-02 + 4.000000E-01 1 5 -9.064186E+03 5.634245E-02 + 4.000000E-01 2 2 1.671785E+03 -6.710615E-03 + 4.000000E-01 2 4 1.231083E+04 -6.929412E-02 + 4.000000E-01 3 3 2.166178E+03 5.495228E-03 + 4.000000E-01 4 2 1.232969E+04 -6.580804E-02 + 4.000000E-01 4 4 2.612587E+05 6.190121E-02 + 4.000000E-01 5 1 -9.060692E+03 6.707626E-03 + 4.000000E-01 5 5 8.194138E+05 -6.489989E-03 + 4.000000E-01 6 6 6.587328E+05 -1.063728E+01 + 5.000000E-01 1 1 1.414171E+03 3.453698E-01 + 5.000000E-01 1 5 -9.040007E+03 -3.437867E-01 + 5.000000E-01 2 2 1.660540E+03 3.550050E-01 + 5.000000E-01 2 4 1.228412E+04 2.817520E-01 + 5.000000E-01 3 3 2.162501E+03 2.197521E-02 + 5.000000E-01 4 2 1.229900E+04 5.180726E-03 + 5.000000E-01 4 4 2.611725E+05 8.319525E-01 + 5.000000E-01 5 1 -9.049924E+03 -4.966549E-02 + 5.000000E-01 5 5 8.193651E+05 8.510031E-02 + 5.000000E-01 6 6 6.535414E+05 1.552287E+02 + 6.000000E-01 1 1 1.405576E+03 7.597563E-02 + 6.000000E-01 1 5 -9.019186E+03 3.253367E-02 + 6.000000E-01 2 2 1.652408E+03 -6.845129E-02 + 6.000000E-01 2 4 1.226468E+04 -3.525721E-01 + 6.000000E-01 3 3 2.164061E+03 2.654704E-02 + 6.000000E-01 4 2 1.227475E+04 -2.927428E-01 + 6.000000E-01 4 4 2.610847E+05 9.614539E-01 + 6.000000E-01 5 1 -9.029830E+03 -4.355243E-05 + 6.000000E-01 5 5 8.191937E+05 -2.194798E-02 + 6.000000E-01 6 6 6.497349E+05 -5.169302E+01 + 7.000000E-01 1 1 1.395932E+03 2.687031E+00 + 7.000000E-01 1 5 -8.998733E+03 -2.345758E+00 + 7.000000E-01 2 2 1.643188E+03 2.431145E+00 + 7.000000E-01 2 4 1.224100E+04 2.120982E+00 + 7.000000E-01 3 3 2.166201E+03 5.592055E-02 + 7.000000E-01 4 2 1.225460E+04 6.609563E-01 + 7.000000E-01 4 4 2.610094E+05 3.439912E+00 + 7.000000E-01 5 1 -9.010243E+03 -4.799671E-01 + 7.000000E-01 5 5 8.189821E+05 4.613745E-01 + 7.000000E-01 6 6 6.454252E+05 1.170501E+03 + 8.000001E-01 1 1 1.384360E+03 1.642901E-01 + 8.000001E-01 1 5 -8.978327E+03 2.553241E+00 + 8.000001E-01 2 2 1.631998E+03 -1.413633E-02 + 8.000001E-01 2 4 1.221956E+04 -2.684513E+00 + 8.000001E-01 3 3 2.165785E+03 4.677046E-02 + 8.000001E-01 4 2 1.223349E+04 -4.235556E-01 + 8.000001E-01 4 4 2.609263E+05 2.081753E+00 + 8.000001E-01 5 1 -8.987876E+03 -9.826274E-03 + 8.000001E-01 5 5 8.190675E+05 -5.485277E-01 + 8.000001E-01 6 6 6.402148E+05 -3.896221E+01 + 9.000001E-01 1 1 1.378177E+03 7.398844E+00 + 9.000001E-01 1 5 -8.957874E+03 -6.925296E+00 + 9.000001E-01 2 2 1.627581E+03 5.964404E+00 + 9.000001E-01 2 4 1.220009E+04 4.984253E+00 + 9.000001E-01 3 3 2.165009E+03 1.034568E-01 + 9.000001E-01 4 2 1.220971E+04 5.667600E-01 + 9.000001E-01 4 4 2.608499E+05 7.644433E+00 + 9.000001E-01 5 1 -8.968889E+03 -1.710251E+00 + 9.000001E-01 5 5 8.189044E+05 1.618641E+00 + 9.000001E-01 6 6 6.380893E+05 2.840782E+03 + 1.000000E+00 1 1 1.362969E+03 1.615517E+00 + 1.000000E+00 1 5 -8.932901E+03 5.044086E+00 + 1.000000E+00 2 2 1.611138E+03 9.922764E-01 + 1.000000E+00 2 4 1.216958E+04 -5.591891E+00 + 1.000000E+00 3 3 2.165247E+03 2.016310E-01 + 1.000000E+00 4 2 1.218151E+04 -1.473536E+00 + 1.000000E+00 4 4 2.607715E+05 7.036344E+00 + 1.000000E+00 5 1 -8.944518E+03 -3.480948E-01 + 1.000000E+00 5 5 8.189051E+05 -1.422689E+00 + 1.000000E+00 6 6 6.303638E+05 4.558491E+02 + 1.100000E+00 1 1 1.363987E+03 -2.531477E+00 + 1.100000E+00 1 5 -8.926103E+03 6.271327E+00 + 1.100000E+00 2 2 1.611693E+03 -1.364930E+00 + 1.100000E+00 2 4 1.216229E+04 -4.610226E+00 + 1.100000E+00 3 3 2.165244E+03 2.358969E-01 + 1.100000E+00 4 2 1.216006E+04 -6.359519E+00 + 1.100000E+00 4 4 2.606747E+05 5.233872E-02 + 1.100000E+00 5 1 -8.920106E+03 1.063921E+00 + 1.100000E+00 5 5 8.188067E+05 -2.253227E+00 + 1.100000E+00 6 6 6.310228E+05 -1.073627E+03 + 1.200000E+00 1 1 1.341250E+03 1.548859E+01 + 1.200000E+00 1 5 -8.873159E+03 -6.809859E+00 + 1.200000E+00 2 2 1.586134E+03 1.391513E+01 + 1.200000E+00 2 4 1.211250E+04 4.959229E+00 + 1.200000E+00 3 3 2.164715E+03 3.401773E-01 + 1.200000E+00 4 2 1.212701E+04 3.459318E+00 + 1.200000E+00 4 4 2.605578E+05 1.085976E+01 + 1.200000E+00 5 1 -8.887145E+03 -5.441040E+00 + 1.200000E+00 5 5 8.187148E+05 2.547801E+00 + 1.200000E+00 6 6 6.198414E+05 6.079765E+03 + 1.300000E+00 1 1 1.317477E+03 1.786603E+01 + 1.300000E+00 1 5 -8.835250E+03 -4.428756E+00 + 1.300000E+00 2 2 1.567642E+03 1.936374E+01 + 1.300000E+00 2 4 1.207500E+04 -3.296340E+00 + 1.300000E+00 3 3 2.163520E+03 6.429050E-01 + 1.300000E+00 4 2 1.208866E+04 1.633794E+00 + 1.300000E+00 4 4 2.604250E+05 1.361215E+01 + 1.300000E+00 5 1 -8.846683E+03 -7.834044E+00 + 1.300000E+00 5 5 8.186024E+05 2.022286E+00 + 1.300000E+00 6 6 6.112214E+05 7.741492E+03 + 1.400000E+00 1 1 1.302752E+03 4.014243E+01 + 1.400000E+00 1 5 -8.796211E+03 -2.097240E+01 + 1.400000E+00 2 2 1.559435E+03 3.202108E+01 + 1.400000E+00 2 4 1.202891E+04 4.779904E+00 + 1.400000E+00 3 3 2.164057E+03 9.372752E-01 + 1.400000E+00 4 2 1.204261E+04 3.293264E+00 + 1.400000E+00 4 4 2.602875E+05 2.683385E+01 + 1.400000E+00 5 1 -8.809545E+03 -1.970354E+01 + 1.400000E+00 5 5 8.184987E+05 1.044662E+01 + 1.400000E+00 6 6 6.065062E+05 1.238738E+04 + 1.500000E+00 1 1 1.305815E+03 6.491683E+01 + 1.500000E+00 1 5 -8.772146E+03 -5.825910E+01 + 1.500000E+00 2 2 1.552037E+03 5.264654E+01 + 1.500000E+00 2 4 1.198437E+04 1.699949E+01 + 1.500000E+00 3 3 2.163969E+03 8.035405E-01 + 1.500000E+00 4 2 1.199230E+04 -6.595213E+00 + 1.500000E+00 4 4 2.601701E+05 4.169799E+01 + 1.500000E+00 5 1 -8.775944E+03 -3.643074E+01 + 1.500000E+00 5 5 8.183611E+05 3.319314E+01 + 1.500000E+00 6 6 6.043392E+05 1.849497E+04 + 1.600000E+00 1 1 1.252716E+03 3.327114E+01 + 1.600000E+00 1 5 -8.693517E+03 -1.871183E+01 + 1.600000E+00 2 2 1.525129E+03 4.072418E+01 + 1.600000E+00 2 4 1.192106E+04 1.475205E+01 + 1.600000E+00 3 3 2.162847E+03 2.077548E+00 + 1.600000E+00 4 2 1.193497E+04 1.744354E+01 + 1.600000E+00 4 4 2.599660E+05 2.792954E+01 + 1.600000E+00 5 1 -8.706070E+03 -2.088443E+01 + 1.600000E+00 5 5 8.181992E+05 1.237664E+01 + 1.600000E+00 6 6 5.862862E+05 1.873653E+04 + 1.700000E+00 1 1 1.263750E+03 4.159086E+01 + 1.700000E+00 1 5 -8.659005E+03 -3.006438E+01 + 1.700000E+00 2 2 1.499287E+03 5.819635E+01 + 1.700000E+00 2 4 1.187052E+04 1.416955E+01 + 1.700000E+00 3 3 2.164139E+03 8.063655E-01 + 1.700000E+00 4 2 1.188380E+04 1.460832E+01 + 1.700000E+00 4 4 2.597760E+05 4.624529E+01 + 1.700000E+00 5 1 -8.672770E+03 -2.952167E+01 + 1.700000E+00 5 5 8.180617E+05 2.236001E+01 + 1.700000E+00 6 6 5.827302E+05 2.159274E+04 + 1.800000E+00 1 1 1.189232E+03 1.561305E+02 + 1.800000E+00 1 5 -8.555380E+03 -1.342970E+02 + 1.800000E+00 2 2 1.504885E+03 9.247465E+01 + 1.800000E+00 2 4 1.178999E+04 3.150293E+01 + 1.800000E+00 3 3 2.163042E+03 1.313273E+00 + 1.800000E+00 4 2 1.180293E+04 3.034780E+01 + 1.800000E+00 4 4 2.595717E+05 6.551591E+01 + 1.800000E+00 5 1 -8.569188E+03 -1.318952E+02 + 1.800000E+00 5 5 8.178374E+05 1.150578E+02 + 1.800000E+00 6 6 5.727449E+05 3.621642E+04 + 1.900000E+00 1 1 1.226731E+03 5.598594E+01 + 1.900000E+00 1 5 -8.539219E+03 -5.221244E+01 + 1.900000E+00 2 2 1.484238E+03 6.774551E+01 + 1.900000E+00 2 4 1.170991E+04 5.493768E+01 + 1.900000E+00 3 3 2.162584E+03 1.752707E+00 + 1.900000E+00 4 2 1.172212E+04 5.261831E+01 + 1.900000E+00 4 4 2.593096E+05 8.803828E+01 + 1.900000E+00 5 1 -8.551688E+03 -5.053044E+01 + 1.900000E+00 5 5 8.176388E+05 4.843289E+01 + 1.900000E+00 6 6 5.656957E+05 3.362212E+04 + 2.000000E+00 1 1 1.087300E+03 1.198298E+02 + 2.000000E+00 1 5 -8.342403E+03 -1.376728E+02 + 2.000000E+00 2 2 1.441709E+03 1.099168E+02 + 2.000000E+00 2 4 1.162081E+04 1.143344E+02 + 2.000000E+00 3 3 2.162366E+03 1.870794E+00 + 2.000000E+00 4 2 1.163232E+04 1.028961E+02 + 2.000000E+00 4 4 2.590200E+05 1.522620E+02 + 2.000000E+00 5 1 -8.362664E+03 -1.267002E+02 + 2.000000E+00 5 5 8.172602E+05 1.471770E+02 + 2.000000E+00 6 6 5.488098E+05 5.315241E+04 + 2.100000E+00 1 1 1.255987E+03 1.175194E+02 + 2.100000E+00 1 5 -8.462438E+03 -1.145313E+02 + 2.100000E+00 2 2 1.445970E+03 1.372894E+02 + 2.100000E+00 2 4 1.156079E+04 1.278852E+02 + 2.100000E+00 3 3 2.162340E+03 2.534883E+00 + 2.100000E+00 4 2 1.157829E+04 1.415270E+02 + 2.100000E+00 4 4 2.587445E+05 1.772284E+02 + 2.100000E+00 5 1 -8.483445E+03 -1.251749E+02 + 2.100000E+00 5 5 8.172242E+05 1.242277E+02 + 2.100000E+00 6 6 5.477408E+05 5.859570E+04 + 2.200000E+00 1 1 1.161857E+03 8.277615E+01 + 2.200000E+00 1 5 -8.305616E+03 -9.694767E+01 + 2.200000E+00 2 2 1.429704E+03 1.234183E+02 + 2.200000E+00 2 4 1.147599E+04 1.348589E+02 + 2.200000E+00 3 3 2.161439E+03 4.401815E+00 + 2.200000E+00 4 2 1.149046E+04 1.381628E+02 + 2.200000E+00 4 4 2.583983E+05 2.061866E+02 + 2.200000E+00 5 1 -8.319411E+03 -9.914822E+01 + 2.200000E+00 5 5 8.168261E+05 1.187337E+02 + 2.200000E+00 6 6 5.324512E+05 5.808795E+04 + 2.300000E+00 1 1 1.015164E+03 1.006042E+02 + 2.300000E+00 1 5 -8.054513E+03 -1.371125E+02 + 2.300000E+00 2 2 1.385527E+03 1.660816E+02 + 2.300000E+00 2 4 1.133986E+04 1.926234E+02 + 2.300000E+00 3 3 2.164200E+03 5.022234E+00 + 2.300000E+00 4 2 1.135328E+04 1.947626E+02 + 2.300000E+00 4 4 2.579466E+05 2.966538E+02 + 2.300000E+00 5 1 -8.066244E+03 -1.383375E+02 + 2.300000E+00 5 5 8.162890E+05 1.932015E+02 + 2.300000E+00 6 6 5.070252E+05 7.404296E+04 + 2.400000E+00 1 1 1.214906E+03 5.852307E+02 + 2.400000E+00 1 5 -8.268893E+03 -8.177158E+02 + 2.400000E+00 2 2 1.387516E+03 1.894508E+02 + 2.400000E+00 2 4 1.122504E+04 2.547854E+02 + 2.400000E+00 3 3 2.163273E+03 2.346359E+00 + 2.400000E+00 4 2 1.123836E+04 2.560267E+02 + 2.400000E+00 4 4 2.574243E+05 4.518562E+02 + 2.400000E+00 5 1 -8.282180E+03 -8.209977E+02 + 2.400000E+00 5 5 8.163470E+05 1.156790E+03 + 2.400000E+00 6 6 5.116156E+05 1.178427E+05 + 2.500000E+00 1 1 1.246471E+03 2.142013E+02 + 2.500000E+00 1 5 -8.248199E+03 -3.329355E+02 + 2.500000E+00 2 2 1.357654E+03 2.025255E+02 + 2.500000E+00 2 4 1.107015E+04 3.476158E+02 + 2.500000E+00 3 3 2.161670E+03 2.311961E+00 + 2.500000E+00 4 2 1.108291E+04 3.480320E+02 + 2.500000E+00 4 4 2.568296E+05 7.940952E+02 + 2.500000E+00 5 1 -8.261192E+03 -3.337436E+02 + 2.500000E+00 5 5 8.160553E+05 5.377015E+02 + 2.500000E+00 6 6 5.215977E+05 1.176396E+05 + 2.600000E+00 1 1 1.152141E+03 1.682242E+02 + 2.600000E+00 1 5 -8.041700E+03 -2.895229E+02 + 2.600000E+00 2 2 1.304580E+03 2.326107E+02 + 2.600000E+00 2 4 1.090560E+04 5.031878E+02 + 2.600000E+00 3 3 2.160825E+03 3.126930E+00 + 2.600000E+00 4 2 1.091793E+04 5.049114E+02 + 2.600000E+00 4 4 2.563096E+05 1.381231E+03 + 2.600000E+00 5 1 -8.053100E+03 -2.900639E+02 + 2.600000E+00 5 5 8.154575E+05 5.286125E+02 + 2.600000E+00 6 6 5.093822E+05 1.192501E+05 + 2.700000E+00 1 1 1.035172E+03 1.608131E+02 + 2.700000E+00 1 5 -7.790863E+03 -3.237605E+02 + 2.700000E+00 2 2 1.266582E+03 3.277071E+02 + 2.700000E+00 2 4 1.085689E+04 7.817658E+02 + 2.700000E+00 3 3 2.160143E+03 4.236008E+00 + 2.700000E+00 4 2 1.086863E+04 7.819337E+02 + 2.700000E+00 4 4 2.564252E+05 2.109151E+03 + 2.700000E+00 5 1 -7.802771E+03 -3.243824E+02 + 2.700000E+00 5 5 8.147674E+05 6.867380E+02 + 2.700000E+00 6 6 4.884454E+05 1.238860E+05 + 2.799999E+00 1 1 8.628414E+02 1.778566E+02 + 2.799999E+00 1 5 -7.430020E+03 -3.774420E+02 + 2.799999E+00 2 2 1.293632E+03 3.825009E+02 + 2.799999E+00 2 4 1.088742E+04 8.311805E+02 + 2.799999E+00 3 3 2.159710E+03 5.450130E+00 + 2.799999E+00 4 2 1.089878E+04 8.314925E+02 + 2.799999E+00 4 4 2.562536E+05 1.832187E+03 + 2.799999E+00 5 1 -7.441687E+03 -3.780771E+02 + 2.799999E+00 5 5 8.138429E+05 8.621034E+02 + 2.799999E+00 6 6 4.470920E+05 1.495096E+05 + 2.899999E+00 1 1 4.788242E+02 4.073611E+02 + 2.899999E+00 1 5 -6.634616E+03 -7.981046E+02 + 2.899999E+00 2 2 1.286692E+03 4.327466E+02 + 2.899999E+00 2 4 1.075176E+04 9.386442E+02 + 2.899999E+00 3 3 2.160150E+03 7.244529E+00 + 2.899999E+00 4 2 1.076280E+04 9.389468E+02 + 2.899999E+00 4 4 2.554582E+05 2.041500E+03 + 2.899999E+00 5 1 -6.647493E+03 -7.984279E+02 + 2.899999E+00 5 5 8.120112E+05 1.683417E+03 + 2.899999E+00 6 6 4.254066E+05 2.188972E+05 + 2.999999E+00 1 1 8.676102E+02 1.330944E+03 + 2.999999E+00 1 5 -7.176687E+03 -2.660807E+03 + 2.999999E+00 2 2 1.320125E+03 4.957027E+02 + 2.999999E+00 2 4 1.069429E+04 1.124392E+03 + 2.999999E+00 3 3 2.161853E+03 8.607779E+00 + 2.999999E+00 4 2 1.070511E+04 1.124652E+03 + 2.999999E+00 4 4 2.548333E+05 2.578703E+03 + 2.999999E+00 5 1 -7.188262E+03 -2.658969E+03 + 2.999999E+00 5 5 8.124259E+05 5.464042E+03 + 2.999999E+00 6 6 4.548885E+05 2.814697E+05 + 3.099999E+00 1 1 1.489484E+03 9.715460E+02 + 3.099999E+00 1 5 -8.387819E+03 -2.143894E+03 + 3.099999E+00 2 2 1.352241E+03 4.908422E+02 + 3.099999E+00 2 4 1.064030E+04 1.206893E+03 + 3.099999E+00 3 3 2.164565E+03 8.339890E+00 + 3.099999E+00 4 2 1.065052E+04 1.207257E+03 + 3.099999E+00 4 4 2.542144E+05 3.023530E+03 + 3.099999E+00 5 1 -8.397405E+03 -2.142834E+03 + 3.099999E+00 5 5 8.144962E+05 4.911563E+03 + 3.099999E+00 6 6 4.956156E+05 3.123367E+05 + 3.199999E+00 1 1 1.552024E+03 6.866681E+02 + 3.199999E+00 1 5 -8.523776E+03 -1.651808E+03 + 3.199999E+00 2 2 1.317350E+03 4.811824E+02 + 3.199999E+00 2 4 1.045333E+04 1.308174E+03 + 3.199999E+00 3 3 2.165616E+03 5.539555E+00 + 3.199999E+00 4 2 1.046322E+04 1.308772E+03 + 3.199999E+00 4 4 2.533207E+05 3.628707E+03 + 3.199999E+00 5 1 -8.532786E+03 -1.651589E+03 + 3.199999E+00 5 5 8.144799E+05 4.254115E+03 + 3.199999E+00 6 6 5.333272E+05 3.238614E+05 + 3.299999E+00 1 1 1.519504E+03 5.044711E+02 + 3.299999E+00 1 5 -8.430406E+03 -1.328371E+03 + 3.299999E+00 2 2 1.244961E+03 5.202350E+02 + 3.299999E+00 2 4 1.019846E+04 1.549934E+03 + 3.299999E+00 3 3 2.164487E+03 3.300210E+00 + 3.299999E+00 4 2 1.020778E+04 1.550881E+03 + 3.299999E+00 4 4 2.523155E+05 4.681091E+03 + 3.299999E+00 5 1 -8.438989E+03 -1.328675E+03 + 3.299999E+00 5 5 8.139069E+05 3.954610E+03 + 3.299999E+00 6 6 5.629063E+05 3.183922E+05 + 3.399999E+00 1 1 1.429316E+03 3.587855E+02 + 3.399999E+00 1 5 -8.166790E+03 -1.082057E+03 + 3.399999E+00 2 2 1.186506E+03 6.180828E+02 + 3.399999E+00 2 4 1.000604E+04 1.949967E+03 + 3.399999E+00 3 3 2.162645E+03 2.077040E+00 + 3.399999E+00 4 2 1.001519E+04 1.951426E+03 + 3.399999E+00 4 4 2.515476E+05 6.202599E+03 + 3.399999E+00 5 1 -8.174550E+03 -1.082855E+03 + 3.399999E+00 5 5 8.128979E+05 3.939292E+03 + 3.399999E+00 6 6 5.734689E+05 2.999054E+05 + 3.499999E+00 1 1 1.253319E+03 2.631412E+02 + 3.499999E+00 1 5 -7.686133E+03 -1.006373E+03 + 3.499999E+00 2 2 1.168802E+03 7.364794E+02 + 3.499999E+00 2 4 9.936361E+03 2.405336E+03 + 3.499999E+00 3 3 2.159954E+03 2.400041E+00 + 3.499999E+00 4 2 9.945477E+03 2.407414E+03 + 3.499999E+00 4 4 2.511583E+05 7.909718E+03 + 3.499999E+00 5 1 -7.692891E+03 -1.008493E+03 + 3.499999E+00 5 5 8.114382E+05 4.566627E+03 + 3.499999E+00 6 6 5.554653E+05 2.852625E+05 + 3.599999E+00 1 1 1.035358E+03 2.876351E+02 + 3.599999E+00 1 5 -7.169593E+03 -1.269149E+03 + 3.599999E+00 2 2 1.171625E+03 8.513398E+02 + 3.599999E+00 2 4 9.931645E+03 2.860456E+03 + 3.599999E+00 3 3 2.158543E+03 4.722716E+00 + 3.599999E+00 4 2 9.940586E+03 2.863186E+03 + 3.599999E+00 4 4 2.509897E+05 9.670100E+03 + 3.599999E+00 5 1 -7.176320E+03 -1.273618E+03 + 3.599999E+00 5 5 8.102191E+05 6.195654E+03 + 3.599999E+00 6 6 5.199856E+05 2.974018E+05 + 3.699999E+00 1 1 8.653893E+02 4.021774E+02 + 3.699999E+00 1 5 -6.861894E+03 -1.715858E+03 + 3.699999E+00 2 2 1.176039E+03 9.740475E+02 + 3.699999E+00 2 4 9.947188E+03 3.355576E+03 + 3.699999E+00 3 3 2.159710E+03 6.722109E+00 + 3.699999E+00 4 2 9.956570E+03 3.358951E+03 + 3.699999E+00 4 4 2.509371E+05 1.161879E+04 + 3.699999E+00 5 1 -6.869617E+03 -1.722578E+03 + 3.699999E+00 5 5 8.099283E+05 8.157991E+03 + 3.699999E+00 6 6 4.924562E+05 3.377067E+05 + 3.799999E+00 1 1 7.344095E+02 5.368340E+02 + 3.799999E+00 1 5 -6.670849E+03 -2.110418E+03 + 3.799999E+00 2 2 1.187228E+03 1.129501E+03 + 3.799999E+00 2 4 1.001379E+04 3.962422E+03 + 3.799999E+00 3 3 2.161339E+03 6.376057E+00 + 3.799999E+00 4 2 1.002361E+04 3.966385E+03 + 3.799999E+00 4 4 2.511428E+05 1.396322E+04 + 3.799999E+00 5 1 -6.680824E+03 -2.118444E+03 + 3.799999E+00 5 5 8.101197E+05 9.580111E+03 + 3.799999E+00 6 6 4.834378E+05 3.896431E+05 + 3.899998E+00 1 1 5.949812E+02 6.974046E+02 + 3.899998E+00 1 5 -6.384929E+03 -2.498325E+03 + 3.899998E+00 2 2 1.238032E+03 1.334278E+03 + 3.899998E+00 2 4 1.024290E+04 4.716964E+03 + 3.899998E+00 3 3 2.161552E+03 5.115295E+00 + 3.899998E+00 4 2 1.025345E+04 4.721289E+03 + 3.899998E+00 4 4 2.519866E+05 1.676777E+04 + 3.899998E+00 5 1 -6.396908E+03 -2.506805E+03 + 3.899998E+00 5 5 8.099074E+05 1.060047E+04 + 3.899998E+00 6 6 4.874768E+05 4.423460E+05 + 3.999998E+00 1 1 4.450232E+02 9.303323E+02 + 3.999998E+00 1 5 -5.969588E+03 -3.085815E+03 + 3.999998E+00 2 2 1.378535E+03 1.572897E+03 + 3.999998E+00 2 4 1.078900E+04 5.550558E+03 + 3.999998E+00 3 3 2.160886E+03 4.168301E+00 + 3.999998E+00 4 2 1.080032E+04 5.554992E+03 + 3.999998E+00 4 4 2.539513E+05 1.975279E+04 + 3.999998E+00 5 1 -5.983599E+03 -3.094308E+03 + 3.999998E+00 5 5 8.089868E+05 1.202890E+04 + 3.999998E+00 6 6 4.982582E+05 4.964733E+05 + 4.099998E+00 1 1 3.213549E+02 1.272431E+03 + 4.099998E+00 1 5 -5.556480E+03 -4.045225E+03 + 4.099998E+00 2 2 1.644181E+03 1.786194E+03 + 4.099998E+00 2 4 1.175033E+04 6.261296E+03 + 4.099998E+00 3 3 2.159966E+03 3.734381E+00 + 4.099998E+00 4 2 1.176255E+04 6.265514E+03 + 4.099998E+00 4 4 2.573100E+05 2.222593E+04 + 4.099998E+00 5 1 -5.572396E+03 -4.053451E+03 + 4.099998E+00 5 5 8.077581E+05 1.462175E+04 + 4.099998E+00 6 6 5.168934E+05 5.566446E+05 + 4.199998E+00 1 1 2.837065E+02 1.745616E+03 + 4.199998E+00 1 5 -5.372986E+03 -5.475365E+03 + 4.199998E+00 2 2 2.021457E+03 1.891318E+03 + 4.199998E+00 2 4 1.306499E+04 6.578083E+03 + 4.199998E+00 3 3 2.159081E+03 3.634046E+00 + 4.199998E+00 4 2 1.307794E+04 6.581710E+03 + 4.199998E+00 4 4 2.618055E+05 2.329030E+04 + 4.199998E+00 5 1 -5.391368E+03 -5.482950E+03 + 4.199998E+00 5 5 8.070315E+05 1.884529E+04 + 4.199998E+00 6 6 5.500119E+05 6.233448E+05 + 4.299998E+00 1 1 4.283814E+02 2.352158E+03 + 4.299998E+00 1 5 -5.764863E+03 -7.385773E+03 + 4.299998E+00 2 2 2.437146E+03 1.823655E+03 + 4.299998E+00 2 4 1.447431E+04 6.295638E+03 + 4.299998E+00 3 3 2.158338E+03 3.688311E+00 + 4.299998E+00 4 2 1.448777E+04 6.298275E+03 + 4.299998E+00 4 4 2.665226E+05 2.228728E+04 + 4.299998E+00 5 1 -5.785992E+03 -7.391787E+03 + 4.299998E+00 5 5 8.080489E+05 2.478460E+04 + 4.299998E+00 6 6 6.038834E+05 6.911415E+05 + 4.399998E+00 1 1 9.079855E+02 3.018073E+03 + 4.399998E+00 1 5 -7.247806E+03 -9.523347E+03 + 4.399998E+00 2 2 2.782287E+03 1.581769E+03 + 4.399998E+00 2 4 1.560401E+04 5.428034E+03 + 4.399998E+00 3 3 2.157615E+03 3.792120E+00 + 4.399998E+00 4 2 1.561741E+04 5.429461E+03 + 4.399998E+00 4 4 2.701726E+05 1.932651E+04 + 4.399998E+00 5 1 -7.272055E+03 -9.525975E+03 + 4.399998E+00 5 5 8.125672E+05 3.159983E+04 + 4.399998E+00 6 6 6.810822E+05 7.511041E+05 + 4.499998E+00 1 1 1.844521E+03 3.468470E+03 + 4.499998E+00 1 5 -1.022216E+04 -1.098010E+04 + 4.499998E+00 2 2 2.973472E+03 1.241134E+03 + 4.499998E+00 2 4 1.617862E+04 4.252971E+03 + 4.499998E+00 3 3 2.157036E+03 3.889959E+00 + 4.499998E+00 4 2 1.619135E+04 4.253312E+03 + 4.499998E+00 4 4 2.718470E+05 1.542462E+04 + 4.499998E+00 5 1 -1.024756E+04 -1.097690E+04 + 4.499998E+00 5 5 8.219297E+05 3.629821E+04 + 4.499998E+00 6 6 7.797110E+05 7.932092E+05 + 4.599998E+00 1 1 3.006497E+03 3.288463E+03 + 4.599998E+00 1 5 -1.393009E+04 -1.040451E+04 + 4.599998E+00 2 2 3.003075E+03 9.052584E+02 + 4.599998E+00 2 4 1.619231E+04 3.134248E+03 + 4.599998E+00 3 3 2.156441E+03 3.947880E+00 + 4.599998E+00 4 2 1.620390E+04 3.133939E+03 + 4.599998E+00 4 4 2.715950E+05 1.185781E+04 + 4.599998E+00 5 1 -1.395269E+04 -1.039487E+04 + 4.599998E+00 5 5 8.336579E+05 3.448041E+04 + 4.599998E+00 6 6 8.930994E+05 8.082519E+05 + 4.699998E+00 1 1 3.794680E+03 2.495065E+03 + 4.699998E+00 1 5 -1.642829E+04 -7.858628E+03 + 4.699998E+00 2 2 2.923092E+03 6.415554E+02 + 4.699998E+00 2 4 1.584282E+04 2.298043E+03 + 4.699998E+00 3 3 2.155818E+03 3.930626E+00 + 4.699998E+00 4 2 1.585324E+04 2.297627E+03 + 4.699998E+00 4 4 2.701639E+05 9.380751E+03 + 4.699998E+00 5 1 -1.644485E+04 -7.845549E+03 + 4.699998E+00 5 5 8.414570E+05 2.637521E+04 + 4.699998E+00 6 6 1.010009E+06 7.903299E+05 + 4.799998E+00 1 1 3.985248E+03 1.611070E+03 + 4.799998E+00 1 5 -1.700283E+04 -5.037604E+03 + 4.799998E+00 2 2 2.794854E+03 4.658022E+02 + 4.799998E+00 2 4 1.535110E+04 1.786286E+03 + 4.799998E+00 3 3 2.155229E+03 3.795074E+00 + 4.799998E+00 4 2 1.536034E+04 1.786196E+03 + 4.799998E+00 4 4 2.683482E+05 8.090887E+03 + 4.799998E+00 5 1 -1.701342E+04 -5.024928E+03 + 4.799998E+00 5 5 8.430764E+05 1.747628E+04 + 4.799998E+00 6 6 1.116654E+06 7.396004E+05 + 4.899998E+00 1 1 3.827402E+03 9.634639E+02 + 4.899998E+00 1 5 -1.646776E+04 -2.990666E+03 + 4.899998E+00 2 2 2.660283E+03 3.640230E+02 + 4.899998E+00 2 4 1.486350E+04 1.538998E+03 + 4.899998E+00 3 3 2.154426E+03 3.535414E+00 + 4.899998E+00 4 2 1.487189E+04 1.539512E+03 + 4.899998E+00 4 4 2.666564E+05 7.737369E+03 + 4.899998E+00 5 1 -1.647437E+04 -2.980337E+03 + 4.899998E+00 5 5 8.411734E+05 1.114036E+04 + 4.899998E+00 6 6 1.200763E+06 6.633247E+05 + 4.999998E+00 1 1 3.566480E+03 5.624658E+02 + 4.999998E+00 1 5 -1.561565E+04 -1.741451E+03 + 4.999998E+00 2 2 2.540084E+03 3.146508E+02 + 4.999998E+00 2 4 1.444920E+04 1.473245E+03 + 4.999998E+00 3 3 2.153303E+03 3.274325E+00 + 4.999998E+00 4 2 1.445684E+04 1.474538E+03 + 4.999998E+00 4 4 2.653165E+05 8.002011E+03 + 4.999998E+00 5 1 -1.562004E+04 -1.733859E+03 + 4.999998E+00 5 5 8.383096E+05 7.408785E+03 + 4.999998E+00 6 6 1.255646E+06 5.736627E+05 + 5.099998E+00 1 1 3.311354E+03 3.283456E+02 + 5.099998E+00 1 5 -1.479400E+04 -1.026911E+03 + 5.099998E+00 2 2 2.441361E+03 2.988572E+02 + 5.099998E+00 2 4 1.412894E+04 1.518558E+03 + 5.099998E+00 3 3 2.151823E+03 3.256433E+00 + 5.099998E+00 4 2 1.413615E+04 1.520705E+03 + 5.099998E+00 4 4 2.643879E+05 8.620332E+03 + 5.099998E+00 5 1 -1.479733E+04 -1.021795E+03 + 5.099998E+00 5 5 8.355992E+05 5.414550E+03 + 5.099998E+00 6 6 1.281620E+06 4.832948E+05 + 5.199997E+00 1 1 3.093402E+03 1.941337E+02 + 5.199997E+00 1 5 -1.409953E+04 -6.287033E+02 + 5.199997E+00 2 2 2.364365E+03 3.029778E+02 + 5.199997E+00 2 4 1.389976E+04 1.624414E+03 + 5.199997E+00 3 3 2.150268E+03 3.657035E+00 + 5.199997E+00 4 2 1.390667E+04 1.627437E+03 + 5.199997E+00 4 4 2.638413E+05 9.404403E+03 + 5.199997E+00 5 1 -1.410244E+04 -6.256587E+02 + 5.199997E+00 5 5 8.333331E+05 4.449737E+03 + 5.199997E+00 6 6 1.284211E+06 4.016602E+05 + 5.299997E+00 1 1 2.915262E+03 1.179255E+02 + 5.299997E+00 1 5 -1.353667E+04 -4.115366E+02 + 5.299997E+00 2 2 2.306565E+03 3.179202E+02 + 5.299997E+00 2 4 1.374927E+04 1.757467E+03 + 5.299997E+00 3 3 2.148804E+03 4.470127E+00 + 5.299997E+00 4 2 1.375611E+04 1.761369E+03 + 5.299997E+00 4 4 2.636210E+05 1.023076E+04 + 5.299997E+00 5 1 -1.353960E+04 -4.101665E+02 + 5.299997E+00 5 5 8.315229E+05 4.081402E+03 + 5.299997E+00 6 6 1.270988E+06 3.336173E+05 + 5.399997E+00 1 1 2.771403E+03 7.535029E+01 + 5.399997E+00 1 5 -1.308473E+04 -2.980706E+02 + 5.399997E+00 2 2 2.264599E+03 3.379569E+02 + 5.399997E+00 2 4 1.366264E+04 1.896994E+03 + 5.399997E+00 3 3 2.147620E+03 5.584976E+00 + 5.399997E+00 4 2 1.366955E+04 1.901729E+03 + 5.399997E+00 4 4 2.636598E+05 1.102346E+04 + 5.399997E+00 5 1 -1.308783E+04 -2.980390E+02 + 5.399997E+00 5 5 8.301076E+05 4.066760E+03 + 5.399997E+00 6 6 1.249024E+06 2.801717E+05 + 5.499997E+00 1 1 2.654982E+03 5.237862E+01 + 5.499997E+00 1 5 -1.271948E+04 -2.452442E+02 + 5.499997E+00 2 2 2.235198E+03 3.596556E+02 + 5.499997E+00 2 4 1.362563E+04 2.030902E+03 + 5.499997E+00 3 3 2.146740E+03 6.866094E+00 + 5.499997E+00 4 2 1.363269E+04 2.036442E+03 + 5.499997E+00 4 4 2.638968E+05 1.173945E+04 + 5.499997E+00 5 1 -1.272269E+04 -2.462640E+02 + 5.499997E+00 5 5 8.290118E+05 4.272639E+03 + 5.499997E+00 6 6 1.223694E+06 2.399705E+05 + 5.599997E+00 1 1 2.559889E+03 4.090048E+01 + 5.599997E+00 1 5 -1.242047E+04 -2.296341E+02 + 5.599997E+00 2 2 2.215537E+03 3.810944E+02 + 5.599997E+00 2 4 1.362599E+04 2.152860E+03 + 5.599997E+00 3 3 2.146235E+03 8.188703E+00 + 5.599997E+00 4 2 1.363331E+04 2.159134E+03 + 5.599997E+00 4 4 2.642781E+05 1.235779E+04 + 5.599997E+00 5 1 -1.242398E+04 -2.314803E+02 + 5.599997E+00 5 5 8.281864E+05 4.624792E+03 + 5.599997E+00 6 6 1.198520E+06 2.106349E+05 + 5.699997E+00 1 1 2.481134E+03 3.622530E+01 + 5.699997E+00 1 5 -1.217205E+04 -2.390406E+02 + 5.699997E+00 2 2 2.203338E+03 4.012977E+02 + 5.699997E+00 2 4 1.365389E+04 2.260206E+03 + 5.699997E+00 3 3 2.146061E+03 9.437527E+00 + 5.699997E+00 4 2 1.366151E+04 2.267152E+03 + 5.699997E+00 4 4 2.647607E+05 1.287284E+04 + 5.699997E+00 5 1 -1.217571E+04 -2.415526E+02 + 5.699997E+00 5 5 8.276000E+05 5.077591E+03 + 5.699997E+00 6 6 1.175510E+06 1.896114E+05 + 5.799997E+00 1 1 2.414801E+03 3.571963E+01 + 5.799997E+00 1 5 -1.196363E+04 -2.675559E+02 + 5.799997E+00 2 2 2.196878E+03 4.198519E+02 + 5.799997E+00 2 4 1.370169E+04 2.352441E+03 + 5.799997E+00 3 3 2.146153E+03 1.050976E+01 + 5.799997E+00 4 2 1.370968E+04 2.360014E+03 + 5.799997E+00 4 4 2.653059E+05 1.328700E+04 + 5.799997E+00 5 1 -1.196734E+04 -2.706225E+02 + 5.799997E+00 5 5 8.272393E+05 5.595674E+03 + 5.799997E+00 6 6 1.155582E+06 1.745987E+05 + 5.899997E+00 1 1 2.357922E+03 3.801922E+01 + 5.899997E+00 1 5 -1.178885E+04 -3.124327E+02 + 5.899997E+00 2 2 2.194862E+03 4.366475E+02 + 5.899997E+00 2 4 1.376376E+04 2.430229E+03 + 5.899997E+00 3 3 2.146511E+03 1.132461E+01 + 5.899997E+00 4 2 1.377225E+04 2.438366E+03 + 5.899997E+00 4 4 2.658924E+05 1.360790E+04 + 5.899997E+00 5 1 -1.179261E+04 -3.160218E+02 + 5.899997E+00 5 5 8.270986E+05 6.141441E+03 + 5.899997E+00 6 6 1.138981E+06 1.637083E+05 + 5.999997E+00 1 1 2.308324E+03 4.254660E+01 + 5.999997E+00 1 5 -1.164482E+04 -3.718600E+02 + 5.999997E+00 2 2 2.196359E+03 4.517130E+02 + 5.999997E+00 2 4 1.383614E+04 2.494713E+03 + 5.999997E+00 3 3 2.146963E+03 1.182240E+01 + 5.999997E+00 4 2 1.384510E+04 2.503334E+03 + 5.999997E+00 4 4 2.665013E+05 1.384496E+04 + 5.999997E+00 5 1 -1.164849E+04 -3.759966E+02 + 5.999997E+00 5 5 8.271738E+05 6.672120E+03 + 5.999997E+00 6 6 1.125527E+06 1.554829E+05 + 6.099997E+00 1 1 2.264572E+03 4.916754E+01 + 6.099997E+00 1 5 -1.153115E+04 -4.434497E+02 + 6.099997E+00 2 2 2.200714E+03 4.651149E+02 + 6.099997E+00 2 4 1.391590E+04 2.547103E+03 + 6.099997E+00 3 3 2.147508E+03 1.197464E+01 + 6.099997E+00 4 2 1.392542E+04 2.556143E+03 + 6.099997E+00 4 4 2.671198E+05 1.400747E+04 + 6.099997E+00 5 1 -1.153461E+04 -4.482232E+02 + 6.099997E+00 5 5 8.274449E+05 7.137406E+03 + 6.099997E+00 6 6 1.114846E+06 1.488498E+05 + 6.199996E+00 1 1 2.225845E+03 5.791336E+01 + 6.199996E+00 1 5 -1.144855E+04 -5.233252E+02 + 6.199996E+00 2 2 2.207427E+03 4.769182E+02 + 6.199996E+00 2 4 1.400112E+04 2.588469E+03 + 6.199996E+00 3 3 2.147983E+03 1.177742E+01 + 6.199996E+00 4 2 1.401124E+04 2.597856E+03 + 6.199996E+00 4 4 2.677387E+05 1.410379E+04 + 6.199996E+00 5 1 -1.145172E+04 -5.288552E+02 + 6.199996E+00 5 5 8.278942E+05 7.486343E+03 + 6.199996E+00 6 6 1.106466E+06 1.430567E+05 + 6.299996E+00 1 1 2.191787E+03 6.876836E+01 + 6.299996E+00 1 5 -1.139713E+04 -6.060628E+02 + 6.299996E+00 2 2 2.216136E+03 4.871554E+02 + 6.299996E+00 2 4 1.409027E+04 2.619675E+03 + 6.299996E+00 3 3 2.148326E+03 1.125918E+01 + 6.299996E+00 4 2 1.410091E+04 2.629354E+03 + 6.299996E+00 4 4 2.683526E+05 1.414116E+04 + 6.299996E+00 5 1 -1.140029E+04 -6.124946E+02 + 6.299996E+00 5 5 8.284701E+05 7.676410E+03 + 6.299996E+00 6 6 1.099910E+06 1.376037E+05 + 6.399996E+00 1 1 2.162298E+03 8.153858E+01 + 6.399996E+00 1 5 -1.137579E+04 -6.853342E+02 + 6.399996E+00 2 2 2.226521E+03 4.958389E+02 + 6.399996E+00 2 4 1.418227E+04 2.641381E+03 + 6.399996E+00 3 3 2.148450E+03 1.045967E+01 + 6.399996E+00 4 2 1.419349E+04 2.651291E+03 + 6.399996E+00 4 4 2.689549E+05 1.412553E+04 + 6.399996E+00 5 1 -1.137890E+04 -6.927547E+02 + 6.399996E+00 5 5 8.291241E+05 7.681978E+03 + 6.399996E+00 6 6 1.094727E+06 1.321838E+05 + 6.499996E+00 1 1 2.137414E+03 9.581681E+01 + 6.499996E+00 1 5 -1.138117E+04 -7.549782E+02 + 6.499996E+00 2 2 2.238330E+03 5.029627E+02 + 6.499996E+00 2 4 1.427607E+04 2.654099E+03 + 6.499996E+00 3 3 2.148310E+03 9.437737E+00 + 6.499996E+00 4 2 1.428792E+04 2.664201E+03 + 6.499996E+00 4 4 2.695456E+05 1.406176E+04 + 6.499996E+00 5 1 -1.138441E+04 -7.634878E+02 + 6.499996E+00 5 5 8.297768E+05 7.499819E+03 + 6.499996E+00 6 6 1.090528E+06 1.266324E+05 + 6.599996E+00 1 1 2.117061E+03 1.110347E+02 + 6.599996E+00 1 5 -1.140839E+04 -8.100574E+02 + 6.599996E+00 2 2 2.251300E+03 5.085111E+02 + 6.599996E+00 2 4 1.437086E+04 2.658243E+03 + 6.599996E+00 3 3 2.147839E+03 8.258938E+00 + 6.599996E+00 4 2 1.438327E+04 2.668446E+03 + 6.599996E+00 4 4 2.701200E+05 1.395409E+04 + 6.599996E+00 5 1 -1.141190E+04 -8.196803E+02 + 6.599996E+00 5 5 8.303829E+05 7.147120E+03 + 6.599996E+00 6 6 1.086990E+06 1.208826E+05 + 6.699996E+00 1 1 2.101058E+03 1.265616E+02 + 6.699996E+00 1 5 -1.145151E+04 -8.475231E+02 + 6.699996E+00 2 2 2.265208E+03 5.124736E+02 + 6.699996E+00 2 4 1.446587E+04 2.654156E+03 + 6.699996E+00 3 3 2.147059E+03 6.990735E+00 + 6.699996E+00 4 2 1.447884E+04 2.664420E+03 + 6.699996E+00 4 4 2.706753E+05 1.380617E+04 + 6.699996E+00 5 1 -1.145549E+04 -8.582006E+02 + 6.699996E+00 5 5 8.309059E+05 6.657472E+03 + 6.699996E+00 6 6 1.083849E+06 1.149360E+05 + 6.799996E+00 1 1 2.089061E+03 1.418042E+02 + 6.799996E+00 1 5 -1.150458E+04 -8.662194E+02 + 6.799996E+00 2 2 2.279823E+03 5.148475E+02 + 6.799996E+00 2 4 1.456021E+04 2.642193E+03 + 6.799996E+00 3 3 2.145892E+03 5.702897E+00 + 6.799996E+00 4 2 1.457378E+04 2.652465E+03 + 6.799996E+00 4 4 2.712104E+05 1.362124E+04 + 6.799996E+00 5 1 -1.150923E+04 -8.779100E+02 + 6.799996E+00 5 5 8.313066E+05 6.069667E+03 + 6.799996E+00 6 6 1.080908E+06 1.088340E+05 + 6.899996E+00 1 1 2.080629E+03 1.562687E+02 + 6.899996E+00 1 5 -1.156227E+04 -8.666884E+02 + 6.899996E+00 2 2 2.294929E+03 5.156463E+02 + 6.899996E+00 2 4 1.465322E+04 2.622711E+03 + 6.899996E+00 3 3 2.144403E+03 4.455389E+00 + 6.899996E+00 4 2 1.466733E+04 2.632958E+03 + 6.899996E+00 4 4 2.717231E+05 1.340240E+04 + 6.899996E+00 5 1 -1.156771E+04 -8.792554E+02 + 6.899996E+00 5 5 8.315797E+05 5.424942E+03 + 6.899996E+00 6 6 1.078029E+06 1.026409E+05 + 6.999996E+00 1 1 2.075260E+03 1.695943E+02 + 6.999996E+00 1 5 -1.162010E+04 -8.505952E+02 + 6.999996E+00 2 2 2.310312E+03 5.149020E+02 + 6.999996E+00 2 4 1.474421E+04 2.596136E+03 + 6.999996E+00 3 3 2.142583E+03 3.305560E+00 + 6.999996E+00 4 2 1.475881E+04 2.606313E+03 + 6.999996E+00 4 4 2.722094E+05 1.315296E+04 + 6.999996E+00 5 1 -1.162643E+04 -8.639541E+02 + 6.999996E+00 5 5 8.317351E+05 4.758364E+03 + 6.999996E+00 6 6 1.075111E+06 9.642911E+04 + 7.099996E+00 1 1 2.072439E+03 1.815470E+02 + 7.099996E+00 1 5 -1.167486E+04 -8.202302E+02 + 7.099996E+00 2 2 2.325777E+03 5.126632E+02 + 7.099996E+00 2 4 1.483244E+04 2.562913E+03 + 7.099996E+00 3 3 2.140477E+03 2.306333E+00 + 7.099996E+00 4 2 1.484754E+04 2.572995E+03 + 7.099996E+00 4 4 2.726711E+05 1.287586E+04 + 7.099996E+00 5 1 -1.168208E+04 -8.342277E+02 + 7.099996E+00 5 5 8.317692E+05 4.099196E+03 + 7.099996E+00 6 6 1.072095E+06 9.026942E+04 + 7.199996E+00 1 1 2.071695E+03 1.920041E+02 + 7.199996E+00 1 5 -1.172426E+04 -7.781377E+02 + 7.199996E+00 2 2 2.341146E+03 5.089946E+02 + 7.199996E+00 2 4 1.491744E+04 2.523556E+03 + 7.199996E+00 3 3 2.138098E+03 1.499131E+00 + 7.199996E+00 4 2 1.493301E+04 2.533487E+03 + 7.199996E+00 4 4 2.731030E+05 1.257439E+04 + 7.199996E+00 5 1 -1.173251E+04 -7.926338E+02 + 7.199996E+00 5 5 8.317095E+05 3.469617E+03 + 7.199996E+00 6 6 1.068946E+06 8.422774E+04 + 7.299995E+00 1 1 2.072606E+03 2.009275E+02 + 7.299995E+00 1 5 -1.176687E+04 -7.268240E+02 + 7.299995E+00 2 2 2.356259E+03 5.039792E+02 + 7.299995E+00 2 4 1.499860E+04 2.478589E+03 + 7.299995E+00 3 3 2.135474E+03 9.279532E-01 + 7.299995E+00 4 2 1.501468E+04 2.488349E+03 + 7.299995E+00 4 4 2.735058E+05 1.225183E+04 + 7.299995E+00 5 1 -1.177615E+04 -7.416753E+02 + 7.299995E+00 5 5 8.315663E+05 2.884156E+03 + 7.299995E+00 6 6 1.065660E+06 7.835938E+04 + 7.399995E+00 1 1 2.074787E+03 2.083378E+02 + 7.399995E+00 1 5 -1.180199E+04 -6.685760E+02 + 7.399995E+00 2 2 2.370966E+03 4.977119E+02 + 7.399995E+00 2 4 1.507554E+04 2.428592E+03 + 7.399995E+00 3 3 2.132635E+03 6.037473E-01 + 7.399995E+00 4 2 1.509203E+04 2.438173E+03 + 7.399995E+00 4 4 2.738805E+05 1.191124E+04 + 7.399995E+00 5 1 -1.181220E+04 -6.836787E+02 + 7.399995E+00 5 5 8.313497E+05 2.351062E+03 + 7.399995E+00 6 6 1.062236E+06 7.270938E+04 + 7.499995E+00 1 1 2.077932E+03 2.142973E+02 + 7.499995E+00 1 5 -1.182921E+04 -6.054490E+02 + 7.499995E+00 2 2 2.385135E+03 4.902971E+02 + 7.499995E+00 2 4 1.514793E+04 2.374177E+03 + 7.499995E+00 3 3 2.129649E+03 5.671070E-01 + 7.499995E+00 4 2 1.516477E+04 2.383516E+03 + 7.499995E+00 4 4 2.742241E+05 1.155591E+04 + 7.499995E+00 5 1 -1.184038E+04 -6.206963E+02 + 7.499995E+00 5 5 8.310848E+05 1.877915E+03 + 7.499995E+00 6 6 1.058691E+06 6.731214E+04 + 7.599995E+00 1 1 2.081773E+03 2.188925E+02 + 7.599995E+00 1 5 -1.184871E+04 -5.391864E+02 + 7.599995E+00 2 2 2.398670E+03 4.818479E+02 + 7.599995E+00 2 4 1.521542E+04 2.315932E+03 + 7.599995E+00 3 3 2.126565E+03 8.177404E-01 + 7.599995E+00 4 2 1.523262E+04 2.325047E+03 + 7.599995E+00 4 4 2.745371E+05 1.118883E+04 + 7.599995E+00 5 1 -1.186081E+04 -5.544869E+02 + 7.599995E+00 5 5 8.307815E+05 1.463640E+03 + 7.599995E+00 6 6 1.055047E+06 6.219123E+04 + 7.699995E+00 1 1 2.086093E+03 2.222232E+02 + 7.699995E+00 1 5 -1.186067E+04 -4.712784E+02 + 7.699995E+00 2 2 2.411483E+03 4.724805E+02 + 7.699995E+00 2 4 1.527788E+04 2.254471E+03 + 7.699995E+00 3 3 2.123444E+03 1.365790E+00 + 7.699995E+00 4 2 1.529545E+04 2.263340E+03 + 7.699995E+00 4 4 2.748192E+05 1.081316E+04 + 7.699995E+00 5 1 -1.187376E+04 -4.865450E+02 + 7.699995E+00 5 5 8.304544E+05 1.108845E+03 + 7.699995E+00 6 6 1.051326E+06 5.736161E+04 + 7.799995E+00 1 1 2.090712E+03 2.243958E+02 + 7.799995E+00 1 5 -1.186565E+04 -4.029154E+02 + 7.799995E+00 2 2 2.423494E+03 4.623121E+02 + 7.799995E+00 2 4 1.533516E+04 2.190390E+03 + 7.799995E+00 3 3 2.120203E+03 2.217513E+00 + 7.799995E+00 4 2 1.535297E+04 2.198995E+03 + 7.799995E+00 4 4 2.750714E+05 1.043161E+04 + 7.799995E+00 5 1 -1.187954E+04 -4.180592E+02 + 7.799995E+00 5 5 8.301100E+05 8.121940E+02 + 7.799995E+00 6 6 1.047555E+06 5.283081E+04 + 7.899995E+00 1 1 2.095488E+03 2.255192E+02 + 7.899995E+00 1 5 -1.186409E+04 -3.351206E+02 + 7.899995E+00 2 2 2.434678E+03 4.514663E+02 + 7.899995E+00 2 4 1.538724E+04 2.124265E+03 + 7.899995E+00 3 3 2.116944E+03 3.360539E+00 + 7.899995E+00 4 2 1.540535E+04 2.132591E+03 + 7.899995E+00 4 4 2.752947E+05 1.004683E+04 + 7.899995E+00 5 1 -1.187884E+04 -3.501150E+02 + 7.899995E+00 5 5 8.297590E+05 5.689839E+02 + 7.899995E+00 6 6 1.043756E+06 4.859913E+04 + 7.999995E+00 1 1 2.100296E+03 2.256954E+02 + 7.999995E+00 1 5 -1.185661E+04 -2.686796E+02 + 7.999995E+00 2 2 2.444984E+03 4.400553E+02 + 7.999995E+00 2 4 1.543411E+04 2.056642E+03 + 7.999995E+00 3 3 2.113878E+03 4.791380E+00 + 7.999995E+00 4 2 1.545251E+04 2.064698E+03 + 7.999995E+00 4 4 2.754896E+05 9.661417E+03 + 7.999995E+00 5 1 -1.187211E+04 -2.834257E+02 + 7.999995E+00 5 5 8.294042E+05 3.772042E+02 + 7.999995E+00 6 6 1.039954E+06 4.466331E+04 + 8.099995E+00 1 1 2.105043E+03 2.250288E+02 + 8.099995E+00 1 5 -1.184374E+04 -2.042322E+02 + 8.099995E+00 2 2 2.454391E+03 4.281921E+02 + 8.099995E+00 2 4 1.547590E+04 1.988044E+03 + 8.099995E+00 3 3 2.110774E+03 6.490849E+00 + 8.099995E+00 4 2 1.549449E+04 1.995820E+03 + 8.099995E+00 4 4 2.756571E+05 9.277499E+03 + 8.099995E+00 5 1 -1.186001E+04 -2.187066E+02 + 8.099995E+00 5 5 8.290612E+05 2.299006E+02 + 8.099995E+00 6 6 1.036167E+06 4.101462E+04 + 8.199995E+00 1 1 2.109657E+03 2.236175E+02 + 8.199995E+00 1 5 -1.182620E+04 -1.422705E+02 + 8.199995E+00 2 2 2.462898E+03 4.159829E+02 + 8.199995E+00 2 4 1.551268E+04 1.918951E+03 + 8.199995E+00 3 3 2.107748E+03 8.447360E+00 + 8.199995E+00 4 2 1.553151E+04 1.926441E+03 + 8.199995E+00 4 4 2.757995E+05 8.897201E+03 + 8.199995E+00 5 1 -1.184303E+04 -1.564419E+02 + 8.199995E+00 5 5 8.287231E+05 1.246058E+02 + 8.199995E+00 6 6 1.032420E+06 3.764148E+04 + 8.299995E+00 1 1 2.114084E+03 2.215516E+02 + 8.299995E+00 1 5 -1.180446E+04 -8.315440E+01 + 8.299995E+00 2 2 2.470516E+03 4.035282E+02 + 8.299995E+00 2 4 1.554465E+04 1.849790E+03 + 8.299995E+00 3 3 2.104778E+03 1.064496E+01 + 8.299995E+00 4 2 1.556365E+04 1.857000E+03 + 8.299995E+00 4 4 2.759166E+05 8.522346E+03 + 8.299995E+00 5 1 -1.182185E+04 -9.698260E+01 + 8.299995E+00 5 5 8.284002E+05 5.721358E+01 + 8.299995E+00 6 6 1.028722E+06 3.453144E+04 + 8.399996E+00 1 1 2.118270E+03 2.189154E+02 + 8.399996E+00 1 5 -1.177912E+04 -2.715824E+01 + 8.399996E+00 2 2 2.477254E+03 3.909195E+02 + 8.399996E+00 2 4 1.557200E+04 1.780962E+03 + 8.399996E+00 3 3 2.102108E+03 1.305641E+01 + 8.399996E+00 4 2 1.559114E+04 1.787888E+03 + 8.399996E+00 4 4 2.760100E+05 8.154471E+03 + 8.399996E+00 5 1 -1.179728E+04 -4.061836E+01 + 8.399996E+00 5 5 8.280962E+05 2.171890E+01 + 8.399996E+00 6 6 1.025088E+06 3.166960E+04 + 8.499996E+00 1 1 2.122186E+03 2.157903E+02 + 8.499996E+00 1 5 -1.175079E+04 2.553195E+01 + 8.499996E+00 2 2 2.483139E+03 3.782419E+02 + 8.499996E+00 2 4 1.559496E+04 1.712812E+03 + 8.499996E+00 3 3 2.099453E+03 1.566890E+01 + 8.499996E+00 4 2 1.561420E+04 1.719462E+03 + 8.499996E+00 4 4 2.760831E+05 7.794858E+03 + 8.499996E+00 5 1 -1.176919E+04 1.244153E+01 + 8.499996E+00 5 5 8.278067E+05 1.413896E+01 + 8.499996E+00 6 6 1.021530E+06 2.904142E+04 + 8.599997E+00 1 1 2.125807E+03 2.122490E+02 + 8.599997E+00 1 5 -1.171985E+04 7.481567E+01 + 8.599997E+00 2 2 2.488220E+03 3.655711E+02 + 8.599997E+00 2 4 1.561375E+04 1.645655E+03 + 8.599997E+00 3 3 2.097045E+03 1.845528E+01 + 8.599997E+00 4 2 1.563320E+04 1.652033E+03 + 8.599997E+00 4 4 2.761368E+05 7.444747E+03 + 8.599997E+00 5 1 -1.173875E+04 6.210162E+01 + 8.599997E+00 5 5 8.275368E+05 3.248663E+01 + 8.599997E+00 6 6 1.018057E+06 2.663150E+04 + 8.699997E+00 1 1 2.129122E+03 2.083591E+02 + 8.699997E+00 1 5 -1.168679E+04 1.206401E+02 + 8.699997E+00 2 2 2.492500E+03 3.529729E+02 + 8.699997E+00 2 4 1.562877E+04 1.579750E+03 + 8.699997E+00 3 3 2.094784E+03 2.139310E+01 + 8.699997E+00 4 2 1.564822E+04 1.585861E+03 + 8.699997E+00 4 4 2.761712E+05 7.104951E+03 + 8.699997E+00 5 1 -1.170619E+04 1.083546E+02 + 8.699997E+00 5 5 8.272876E+05 7.108610E+01 + 8.699997E+00 6 6 1.014673E+06 2.442441E+04 + 8.799997E+00 1 1 2.132108E+03 2.041796E+02 + 8.799997E+00 1 5 -1.165208E+04 1.630059E+02 + 8.799997E+00 2 2 2.496054E+03 3.405104E+02 + 8.799997E+00 2 4 1.564011E+04 1.515317E+03 + 8.799997E+00 3 3 2.092668E+03 2.446405E+01 + 8.799997E+00 4 2 1.565965E+04 1.521175E+03 + 8.799997E+00 4 4 2.761891E+05 6.776250E+03 + 8.799997E+00 5 1 -1.167177E+04 1.511158E+02 + 8.799997E+00 5 5 8.270590E+05 1.277786E+02 + 8.799997E+00 6 6 1.011389E+06 2.240512E+04 + 8.899998E+00 1 1 2.134787E+03 1.997698E+02 + 8.899998E+00 1 5 -1.161606E+04 2.019601E+02 + 8.899998E+00 2 2 2.498899E+03 3.282321E+02 + 8.899998E+00 2 4 1.564816E+04 1.452547E+03 + 8.899998E+00 3 3 2.090809E+03 2.764819E+01 + 8.899998E+00 4 2 1.566773E+04 1.458146E+03 + 8.899998E+00 4 4 2.761923E+05 6.459099E+03 + 8.899998E+00 5 1 -1.163613E+04 1.904809E+02 + 8.899998E+00 5 5 8.268539E+05 1.984217E+02 + 8.899998E+00 6 6 1.008203E+06 2.055934E+04 + 8.999998E+00 1 1 2.137139E+03 1.951779E+02 + 8.999998E+00 1 5 -1.157913E+04 2.375940E+02 + 8.999998E+00 2 2 2.501099E+03 3.161833E+02 + 8.999998E+00 2 4 1.565312E+04 1.391578E+03 + 8.999998E+00 3 3 2.089147E+03 3.091510E+01 + 8.999998E+00 4 2 1.567273E+04 1.396935E+03 + 8.999998E+00 4 4 2.761813E+05 6.153932E+03 + 8.999998E+00 5 1 -1.159956E+04 2.265213E+02 + 8.999998E+00 5 5 8.266658E+05 2.798887E+02 + 8.999998E+00 6 6 1.005116E+06 1.887311E+04 + 9.099998E+00 1 1 2.139179E+03 1.904497E+02 + 9.099998E+00 1 5 -1.154158E+04 2.699872E+02 + 9.099998E+00 2 2 2.502697E+03 3.043991E+02 + 9.099998E+00 2 4 1.565532E+04 1.332532E+03 + 9.099998E+00 3 3 2.087586E+03 3.426651E+01 + 9.099998E+00 4 2 1.567497E+04 1.337655E+03 + 9.099998E+00 4 4 2.761585E+05 5.861023E+03 + 9.099998E+00 5 1 -1.156220E+04 2.593232E+02 + 9.099998E+00 5 5 8.264962E+05 3.718103E+02 + 9.099998E+00 6 6 1.002138E+06 1.733350E+04 + 9.199999E+00 1 1 2.140917E+03 1.856276E+02 + 9.199999E+00 1 5 -1.150366E+04 2.992821E+02 + 9.199999E+00 2 2 2.503735E+03 2.929104E+02 + 9.199999E+00 2 4 1.565494E+04 1.275499E+03 + 9.199999E+00 3 3 2.086263E+03 3.766659E+01 + 9.199999E+00 4 2 1.567466E+04 1.280395E+03 + 9.199999E+00 4 4 2.761253E+05 5.580450E+03 + 9.199999E+00 5 1 -1.152461E+04 2.890033E+02 + 9.199999E+00 5 5 8.263453E+05 4.689281E+02 + 9.199999E+00 6 6 9.992583E+05 1.592806E+04 + 9.299999E+00 1 1 2.142360E+03 1.807444E+02 + 9.299999E+00 1 5 -1.146577E+04 3.256198E+02 + 9.299999E+00 2 2 2.504263E+03 2.817413E+02 + 9.299999E+00 2 4 1.565232E+04 1.220524E+03 + 9.299999E+00 3 3 2.085159E+03 4.110686E+01 + 9.299999E+00 4 2 1.567206E+04 1.225203E+03 + 9.299999E+00 4 4 2.760819E+05 5.312197E+03 + 9.299999E+00 5 1 -1.148686E+04 3.157380E+02 + 9.299999E+00 5 5 8.262131E+05 5.715813E+02 + 9.299999E+00 6 6 9.964791E+05 1.464538E+04 + 9.400000E+00 1 1 2.143522E+03 1.758346E+02 + 9.400000E+00 1 5 -1.142796E+04 3.491375E+02 + 9.400000E+00 2 2 2.504321E+03 2.709106E+02 + 9.400000E+00 2 4 1.564766E+04 1.167654E+03 + 9.400000E+00 3 3 2.084164E+03 4.457240E+01 + 9.400000E+00 4 2 1.566744E+04 1.172125E+03 + 9.400000E+00 4 4 2.760290E+05 5.056130E+03 + 9.400000E+00 5 1 -1.144924E+04 3.396265E+02 + 9.400000E+00 5 5 8.260980E+05 6.765178E+02 + 9.400000E+00 6 6 9.938049E+05 1.347482E+04 + 9.500000E+00 1 1 2.144417E+03 1.709239E+02 + 9.500000E+00 1 5 -1.139042E+04 3.700067E+02 + 9.500000E+00 2 2 2.503960E+03 2.604297E+02 + 9.500000E+00 2 4 1.564121E+04 1.116898E+03 + 9.500000E+00 3 3 2.083362E+03 4.804810E+01 + 9.500000E+00 4 2 1.566090E+04 1.121167E+03 + 9.500000E+00 4 4 2.759722E+05 4.812139E+03 + 9.500000E+00 5 1 -1.141188E+04 3.608785E+02 + 9.500000E+00 5 5 8.260032E+05 7.829916E+02 + 9.500000E+00 6 6 9.912272E+05 1.240666E+04 + 9.600000E+00 1 1 2.145063E+03 1.660383E+02 + 9.600000E+00 1 5 -1.135346E+04 3.883761E+02 + 9.600000E+00 2 2 2.503218E+03 2.503093E+02 + 9.600000E+00 2 4 1.563313E+04 1.068251E+03 + 9.600000E+00 3 3 2.082737E+03 5.152150E+01 + 9.600000E+00 4 2 1.565285E+04 1.072326E+03 + 9.600000E+00 4 4 2.759075E+05 4.579906E+03 + 9.600000E+00 5 1 -1.137502E+04 3.796046E+02 + 9.600000E+00 5 5 8.259168E+05 8.892158E+02 + 9.600000E+00 6 6 9.887462E+05 1.143185E+04 + 9.700001E+00 1 1 2.145472E+03 1.611957E+02 + 9.700001E+00 1 5 -1.131713E+04 4.044158E+02 + 9.700001E+00 2 2 2.502142E+03 2.405545E+02 + 9.700001E+00 2 4 1.562367E+04 1.021697E+03 + 9.700001E+00 3 3 2.082276E+03 5.498514E+01 + 9.700001E+00 4 2 1.564341E+04 1.025586E+03 + 9.700001E+00 4 4 2.758360E+05 4.359174E+03 + 9.700001E+00 5 1 -1.133862E+04 3.960084E+02 + 9.700001E+00 5 5 8.258537E+05 9.951490E+02 + 9.700001E+00 6 6 9.863594E+05 1.054168E+04 + 9.800001E+00 1 1 2.145671E+03 1.564165E+02 + 9.800001E+00 1 5 -1.128141E+04 4.183023E+02 + 9.800001E+00 2 2 2.500755E+03 2.311662E+02 + 9.800001E+00 2 4 1.561294E+04 9.772015E+02 + 9.800001E+00 3 3 2.081937E+03 5.842216E+01 + 9.800001E+00 4 2 1.563265E+04 9.809180E+02 + 9.800001E+00 4 4 2.757614E+05 4.149600E+03 + 9.800001E+00 5 1 -1.130307E+04 4.102207E+02 + 9.800001E+00 5 5 8.257966E+05 1.098057E+03 + 9.800001E+00 6 6 9.840654E+05 9.728938E+03 + 9.900002E+00 1 1 2.145658E+03 1.517129E+02 + 9.900002E+00 1 5 -1.124661E+04 4.301864E+02 + 9.900002E+00 2 2 2.499100E+03 2.221429E+02 + 9.900002E+00 2 4 1.560114E+04 9.347197E+02 + 9.900002E+00 3 3 2.081755E+03 6.183162E+01 + 9.900002E+00 4 2 1.562081E+04 9.382680E+02 + 9.900002E+00 4 4 2.756829E+05 3.950739E+03 + 9.900002E+00 5 1 -1.126836E+04 4.224308E+02 + 9.900002E+00 5 5 8.257466E+05 1.198787E+03 + 9.900002E+00 6 6 9.818568E+05 8.986440E+03 + 1.000000E+01 1 1 2.145465E+03 1.470993E+02 + 1.000000E+01 1 5 -1.121264E+04 4.402153E+02 + 1.000000E+01 2 2 2.497211E+03 2.134834E+02 + 1.000000E+01 2 4 1.558852E+04 8.942076E+02 + 1.000000E+01 3 3 2.081736E+03 6.520229E+01 + 1.000000E+01 4 2 1.560818E+04 8.975975E+02 + 1.000000E+01 4 4 2.756025E+05 3.762234E+03 + 1.000000E+01 5 1 -1.123443E+04 4.327898E+02 + 1.000000E+01 5 5 8.257079E+05 1.295562E+03 + 1.000000E+01 6 6 9.797342E+05 8.307854E+03 + 1.010000E+01 1 1 2.145102E+03 1.425842E+02 + 1.010000E+01 1 5 -1.117965E+04 4.485279E+02 + 1.010000E+01 2 2 2.495111E+03 2.051799E+02 + 1.010000E+01 2 4 1.557513E+04 8.556025E+02 + 1.010000E+01 3 3 2.081813E+03 6.852578E+01 + 1.010000E+01 4 2 1.559459E+04 8.588407E+02 + 1.010000E+01 4 4 2.755189E+05 3.583694E+03 + 1.010000E+01 5 1 -1.120152E+04 4.414140E+02 + 1.010000E+01 5 5 8.256924E+05 1.389465E+03 + 1.010000E+01 6 6 9.776943E+05 7.687389E+03 + 1.020000E+01 1 1 2.144577E+03 1.381759E+02 + 1.020000E+01 1 5 -1.114771E+04 4.553047E+02 + 1.020000E+01 2 2 2.492841E+03 1.972271E+02 + 1.020000E+01 2 4 1.556101E+04 8.188411E+02 + 1.020000E+01 3 3 2.082054E+03 7.180158E+01 + 1.020000E+01 4 2 1.558062E+04 8.219407E+02 + 1.020000E+01 4 4 2.754333E+05 3.414641E+03 + 1.020000E+01 5 1 -1.116960E+04 4.484713E+02 + 1.020000E+01 5 5 8.256652E+05 1.478140E+03 + 1.020000E+01 6 6 9.757329E+05 7.119680E+03 + 1.030000E+01 1 1 2.143912E+03 1.338805E+02 + 1.030000E+01 1 5 -1.111675E+04 4.606376E+02 + 1.030000E+01 2 2 2.490404E+03 1.896145E+02 + 1.030000E+01 2 4 1.554646E+04 7.838583E+02 + 1.030000E+01 3 3 2.082380E+03 7.501859E+01 + 1.030000E+01 4 2 1.556596E+04 7.868245E+02 + 1.030000E+01 4 4 2.753469E+05 3.254677E+03 + 1.030000E+01 5 1 -1.113858E+04 4.540824E+02 + 1.030000E+01 5 5 8.256712E+05 1.562478E+03 + 1.030000E+01 6 6 9.738463E+05 6.599924E+03 + 1.040000E+01 1 1 2.143127E+03 1.297027E+02 + 1.040000E+01 1 5 -1.108676E+04 4.646914E+02 + 1.040000E+01 2 2 2.487852E+03 1.823339E+02 + 1.040000E+01 2 4 1.553150E+04 7.505894E+02 + 1.040000E+01 3 3 2.082812E+03 7.818211E+01 + 1.040000E+01 4 2 1.555099E+04 7.534227E+02 + 1.040000E+01 4 4 2.752601E+05 3.103319E+03 + 1.040000E+01 5 1 -1.110876E+04 4.584017E+02 + 1.040000E+01 5 5 8.256668E+05 1.642683E+03 + 1.040000E+01 6 6 9.720320E+05 6.123848E+03 + 1.050000E+01 1 1 2.142212E+03 1.256457E+02 + 1.050000E+01 1 5 -1.105802E+04 4.675668E+02 + 1.050000E+01 2 2 2.485180E+03 1.753749E+02 + 1.050000E+01 2 4 1.551622E+04 7.189579E+02 + 1.050000E+01 3 3 2.083348E+03 8.127702E+01 + 1.050000E+01 4 2 1.553561E+04 7.216663E+02 + 1.050000E+01 4 4 2.751720E+05 2.960191E+03 + 1.050000E+01 5 1 -1.107979E+04 4.615325E+02 + 1.050000E+01 5 5 8.256658E+05 1.717788E+03 + 1.050000E+01 6 6 9.702887E+05 5.687414E+03 + 1.060000E+01 1 1 2.141205E+03 1.217116E+02 + 1.060000E+01 1 5 -1.103006E+04 4.693828E+02 + 1.060000E+01 2 2 2.482431E+03 1.687262E+02 + 1.060000E+01 2 4 1.550066E+04 6.888983E+02 + 1.060000E+01 3 3 2.083969E+03 8.431265E+01 + 1.060000E+01 4 2 1.552005E+04 6.914917E+02 + 1.060000E+01 4 4 2.750842E+05 2.824860E+03 + 1.060000E+01 5 1 -1.105195E+04 4.635920E+02 + 1.060000E+01 5 5 8.256779E+05 1.788114E+03 + 1.060000E+01 6 6 9.686122E+05 5.287014E+03 + 1.070000E+01 1 1 2.140107E+03 1.179014E+02 + 1.070000E+01 1 5 -1.100345E+04 4.702292E+02 + 1.070000E+01 2 2 2.479598E+03 1.623760E+02 + 1.070000E+01 2 4 1.548502E+04 6.603346E+02 + 1.070000E+01 3 3 2.084695E+03 8.728065E+01 + 1.070000E+01 4 2 1.550429E+04 6.628145E+02 + 1.070000E+01 4 4 2.749969E+05 2.696889E+03 + 1.070000E+01 5 1 -1.102518E+04 4.646789E+02 + 1.070000E+01 5 5 8.256959E+05 1.853688E+03 + 1.070000E+01 6 6 9.669974E+05 4.919559E+03 + 1.080000E+01 1 1 2.138926E+03 1.142137E+02 + 1.080000E+01 1 5 -1.097759E+04 4.702310E+02 + 1.080000E+01 2 2 2.476715E+03 1.563144E+02 + 1.080000E+01 2 4 1.546918E+04 6.331996E+02 + 1.080000E+01 3 3 2.085490E+03 9.018382E+01 + 1.080000E+01 4 2 1.548842E+04 6.355766E+02 + 1.080000E+01 4 4 2.749096E+05 2.575933E+03 + 1.080000E+01 5 1 -1.099937E+04 4.648986E+02 + 1.080000E+01 5 5 8.257069E+05 1.914251E+03 + 1.080000E+01 6 6 9.654451E+05 4.581916E+03 + 1.090001E+01 1 1 2.137670E+03 1.106502E+02 + 1.090001E+01 1 5 -1.095299E+04 4.694513E+02 + 1.090001E+01 2 2 2.473783E+03 1.505286E+02 + 1.090001E+01 2 4 1.545333E+04 6.074255E+02 + 1.090001E+01 3 3 2.086341E+03 9.301959E+01 + 1.090001E+01 4 2 1.547258E+04 6.097039E+02 + 1.090001E+01 4 4 2.748224E+05 2.461529E+03 + 1.090001E+01 5 1 -1.097454E+04 4.643502E+02 + 1.090001E+01 5 5 8.257381E+05 1.970232E+03 + 1.090001E+01 6 6 9.639502E+05 4.271438E+03 + 1.100001E+01 1 1 2.136364E+03 1.072084E+02 + 1.100001E+01 1 5 -1.092918E+04 4.680009E+02 + 1.100001E+01 2 2 2.470831E+03 1.450070E+02 + 1.100001E+01 2 4 1.543755E+04 5.829437E+02 + 1.100001E+01 3 3 2.087261E+03 9.578189E+01 + 1.100001E+01 4 2 1.545666E+04 5.851293E+02 + 1.100001E+01 4 4 2.747374E+05 2.353424E+03 + 1.100001E+01 5 1 -1.095086E+04 4.630921E+02 + 1.100001E+01 5 5 8.257575E+05 2.021854E+03 + 1.100001E+01 6 6 9.625105E+05 3.985717E+03 + 1.110001E+01 1 1 2.134999E+03 1.038862E+02 + 1.110001E+01 1 5 -1.090647E+04 4.659317E+02 + 1.110001E+01 2 2 2.467854E+03 1.397381E+02 + 1.110001E+01 2 4 1.542175E+04 5.596920E+02 + 1.110001E+01 3 3 2.088266E+03 9.847754E+01 + 1.110001E+01 4 2 1.544090E+04 5.617880E+02 + 1.110001E+01 4 4 2.746530E+05 2.251185E+03 + 1.110001E+01 5 1 -1.092806E+04 4.612215E+02 + 1.110001E+01 5 5 8.257892E+05 2.068661E+03 + 1.110001E+01 6 6 9.611222E+05 3.722606E+03 + 1.120001E+01 1 1 2.133589E+03 1.006825E+02 + 1.120001E+01 1 5 -1.088462E+04 4.633327E+02 + 1.120001E+01 2 2 2.464867E+03 1.347108E+02 + 1.120001E+01 2 4 1.540606E+04 5.376023E+02 + 1.120001E+01 3 3 2.089307E+03 1.011065E+02 + 1.120001E+01 4 2 1.542512E+04 5.396155E+02 + 1.120001E+01 4 4 2.745692E+05 2.154438E+03 + 1.120001E+01 5 1 -1.090628E+04 4.588030E+02 + 1.120001E+01 5 5 8.258142E+05 2.111276E+03 + 1.120001E+01 6 6 9.597874E+05 3.480049E+03 + 1.130001E+01 1 1 2.132145E+03 9.759343E+01 + 1.130001E+01 1 5 -1.086372E+04 4.602499E+02 + 1.130001E+01 2 2 2.461884E+03 1.299144E+02 + 1.130001E+01 2 4 1.539056E+04 5.166194E+02 + 1.130001E+01 3 3 2.090402E+03 1.036618E+02 + 1.130001E+01 4 2 1.540961E+04 5.185527E+02 + 1.130001E+01 4 4 2.744871E+05 2.062993E+03 + 1.130001E+01 5 1 -1.088540E+04 4.559028E+02 + 1.130001E+01 5 5 8.258488E+05 2.149967E+03 + 1.130001E+01 6 6 9.584996E+05 3.256323E+03 + 1.140001E+01 1 1 2.130662E+03 9.461726E+01 + 1.140001E+01 1 5 -1.084381E+04 4.567544E+02 + 1.140001E+01 2 2 2.458892E+03 1.253371E+02 + 1.140001E+01 2 4 1.537518E+04 4.966835E+02 + 1.140001E+01 3 3 2.091546E+03 1.061545E+02 + 1.140001E+01 4 2 1.539409E+04 4.985375E+02 + 1.140001E+01 4 4 2.744073E+05 1.976416E+03 + 1.140001E+01 5 1 -1.086519E+04 4.525659E+02 + 1.140001E+01 5 5 8.258861E+05 2.184761E+03 + 1.140001E+01 6 6 9.572577E+05 3.049736E+03 + 1.150001E+01 1 1 2.129159E+03 9.174998E+01 + 1.150001E+01 1 5 -1.082464E+04 4.528948E+02 + 1.150001E+01 2 2 2.455925E+03 1.209695E+02 + 1.150001E+01 2 4 1.535997E+04 4.777368E+02 + 1.150001E+01 3 3 2.092718E+03 1.085756E+02 + 1.150001E+01 4 2 1.537888E+04 4.795195E+02 + 1.150001E+01 4 4 2.743275E+05 1.894500E+03 + 1.150001E+01 5 1 -1.084610E+04 4.488746E+02 + 1.150001E+01 5 5 8.259156E+05 2.215852E+03 + 1.150001E+01 6 6 9.560608E+05 2.858746E+03 + 1.160001E+01 1 1 2.127638E+03 8.898923E+01 + 1.160001E+01 1 5 -1.080628E+04 4.487243E+02 + 1.160001E+01 2 2 2.452972E+03 1.168008E+02 + 1.160001E+01 2 4 1.534493E+04 4.597283E+02 + 1.160001E+01 3 3 2.093933E+03 1.109317E+02 + 1.160001E+01 4 2 1.536379E+04 4.614388E+02 + 1.160001E+01 4 4 2.742490E+05 1.816965E+03 + 1.160001E+01 5 1 -1.082768E+04 4.448535E+02 + 1.160001E+01 5 5 8.259459E+05 2.243294E+03 + 1.160001E+01 6 6 9.549045E+05 2.682162E+03 + 1.170001E+01 1 1 2.126100E+03 8.633121E+01 + 1.170001E+01 1 5 -1.078880E+04 4.442795E+02 + 1.170001E+01 2 2 2.450047E+03 1.128212E+02 + 1.170001E+01 2 4 1.533011E+04 4.426050E+02 + 1.170001E+01 3 3 2.095180E+03 1.132257E+02 + 1.170001E+01 4 2 1.534890E+04 4.442519E+02 + 1.170001E+01 4 4 2.741736E+05 1.743508E+03 + 1.170001E+01 5 1 -1.081031E+04 4.405491E+02 + 1.170001E+01 5 5 8.259912E+05 2.267439E+03 + 1.170001E+01 6 6 9.537879E+05 2.518749E+03 + 1.180001E+01 1 1 2.124550E+03 8.377260E+01 + 1.180001E+01 1 5 -1.077201E+04 4.396074E+02 + 1.180001E+01 2 2 2.447151E+03 1.090218E+02 + 1.180001E+01 2 4 1.531550E+04 4.263197E+02 + 1.180001E+01 3 3 2.096469E+03 1.154567E+02 + 1.180001E+01 4 2 1.533431E+04 4.279048E+02 + 1.180001E+01 4 4 2.740985E+05 1.673901E+03 + 1.180001E+01 5 1 -1.079330E+04 4.360281E+02 + 1.180001E+01 5 5 8.260214E+05 2.288327E+03 + 1.180001E+01 6 6 9.527109E+05 2.367267E+03 + 1.190001E+01 1 1 2.122995E+03 8.131019E+01 + 1.190001E+01 1 5 -1.075599E+04 4.347395E+02 + 1.190001E+01 2 2 2.444285E+03 1.053936E+02 + 1.190001E+01 2 4 1.530115E+04 4.108290E+02 + 1.190001E+01 3 3 2.097785E+03 1.176215E+02 + 1.190001E+01 4 2 1.531993E+04 4.123534E+02 + 1.190001E+01 4 4 2.740252E+05 1.607962E+03 + 1.190001E+01 5 1 -1.077738E+04 4.312895E+02 + 1.190001E+01 5 5 8.260572E+05 2.306321E+03 + 1.190001E+01 6 6 9.516712E+05 2.226846E+03 + 1.200001E+01 1 1 2.121434E+03 7.894044E+01 + 1.200001E+01 1 5 -1.074063E+04 4.297101E+02 + 1.200001E+01 2 2 2.441449E+03 1.019280E+02 + 1.200001E+01 2 4 1.528709E+04 3.960870E+02 + 1.200001E+01 3 3 2.099118E+03 1.197286E+02 + 1.200001E+01 4 2 1.530580E+04 3.975568E+02 + 1.200001E+01 4 4 2.739543E+05 1.545426E+03 + 1.200001E+01 5 1 -1.076188E+04 4.263846E+02 + 1.200001E+01 5 5 8.260926E+05 2.321299E+03 + 1.200001E+01 6 6 9.506649E+05 2.096431E+03 + 1.210001E+01 1 1 2.119878E+03 7.666012E+01 + 1.210001E+01 1 5 -1.072603E+04 4.245444E+02 + 1.210001E+01 2 2 2.438656E+03 9.861677E+01 + 1.210001E+01 2 4 1.527324E+04 3.820515E+02 + 1.210001E+01 3 3 2.100477E+03 1.217811E+02 + 1.210001E+01 4 2 1.529188E+04 3.834702E+02 + 1.210001E+01 4 4 2.738842E+05 1.486106E+03 + 1.210001E+01 5 1 -1.074728E+04 4.213397E+02 + 1.210001E+01 5 5 8.261277E+05 2.333569E+03 + 1.210001E+01 6 6 9.496948E+05 1.975356E+03 + 1.220001E+01 1 1 2.118321E+03 7.446576E+01 + 1.220001E+01 1 5 -1.071203E+04 4.192750E+02 + 1.220001E+01 2 2 2.435906E+03 9.545207E+01 + 1.220001E+01 2 4 1.525966E+04 3.686877E+02 + 1.220001E+01 3 3 2.101841E+03 1.237651E+02 + 1.220001E+01 4 2 1.527830E+04 3.700542E+02 + 1.220001E+01 4 4 2.738165E+05 1.429824E+03 + 1.220001E+01 5 1 -1.073302E+04 4.161903E+02 + 1.220001E+01 5 5 8.261690E+05 2.343536E+03 + 1.220001E+01 6 6 9.487539E+05 1.862762E+03 + 1.230001E+01 1 1 2.116769E+03 7.235358E+01 + 1.230001E+01 1 5 -1.069859E+04 4.139212E+02 + 1.230001E+01 2 2 2.433190E+03 9.242647E+01 + 1.230001E+01 2 4 1.524637E+04 3.559544E+02 + 1.230001E+01 3 3 2.103232E+03 1.256946E+02 + 1.230001E+01 4 2 1.526485E+04 3.572729E+02 + 1.230001E+01 4 4 2.737493E+05 1.376394E+03 + 1.230001E+01 5 1 -1.071966E+04 4.109430E+02 + 1.230001E+01 5 5 8.261975E+05 2.351000E+03 + 1.230001E+01 6 6 9.478432E+05 1.758019E+03 + 1.240001E+01 1 1 2.115230E+03 7.032137E+01 + 1.240001E+01 1 5 -1.068579E+04 4.085052E+02 + 1.240001E+01 2 2 2.430518E+03 8.953334E+01 + 1.240001E+01 2 4 1.523330E+04 3.438208E+02 + 1.240001E+01 3 3 2.104630E+03 1.275721E+02 + 1.240001E+01 4 2 1.525182E+04 3.450954E+02 + 1.240001E+01 4 4 2.736838E+05 1.325624E+03 + 1.240001E+01 5 1 -1.070680E+04 4.056277E+02 + 1.240001E+01 5 5 8.262332E+05 2.356286E+03 + 1.240001E+01 6 6 9.469648E+05 1.660457E+03 + 1.250001E+01 1 1 2.113698E+03 6.836533E+01 + 1.250001E+01 1 5 -1.067347E+04 4.030426E+02 + 1.250001E+01 2 2 2.427898E+03 8.676517E+01 + 1.250001E+01 2 4 1.522051E+04 3.322523E+02 + 1.250001E+01 3 3 2.106044E+03 1.293969E+02 + 1.250001E+01 4 2 1.523901E+04 3.334811E+02 + 1.250001E+01 4 4 2.736212E+05 1.277405E+03 + 1.250001E+01 5 1 -1.069435E+04 4.002670E+02 + 1.250001E+01 5 5 8.262628E+05 2.359874E+03 + 1.250001E+01 6 6 9.461124E+05 1.569530E+03 + 1.260001E+01 1 1 2.112180E+03 6.648254E+01 + 1.260001E+01 1 5 -1.066185E+04 3.975528E+02 + 1.260001E+01 2 2 2.425312E+03 8.411627E+01 + 1.260001E+01 2 4 1.520798E+04 3.212180E+02 + 1.260001E+01 3 3 2.107452E+03 1.311695E+02 + 1.260001E+01 4 2 1.522640E+04 3.224063E+02 + 1.260001E+01 4 4 2.735586E+05 1.231549E+03 + 1.260001E+01 5 1 -1.068282E+04 3.948681E+02 + 1.260001E+01 5 5 8.263016E+05 2.361182E+03 + 1.260001E+01 6 6 9.452871E+05 1.484709E+03 + 1.270001E+01 1 1 2.110668E+03 6.466995E+01 + 1.270001E+01 1 5 -1.065067E+04 3.920472E+02 + 1.270001E+01 2 2 2.422773E+03 8.158038E+01 + 1.270001E+01 2 4 1.519573E+04 3.106885E+02 + 1.270001E+01 3 3 2.108894E+03 1.328926E+02 + 1.270001E+01 4 2 1.521411E+04 3.118379E+02 + 1.270001E+01 4 4 2.734992E+05 1.187930E+03 + 1.270001E+01 5 1 -1.067151E+04 3.894570E+02 + 1.270001E+01 5 5 8.263347E+05 2.360984E+03 + 1.270001E+01 6 6 9.444876E+05 1.405492E+03 + 1.280001E+01 1 1 2.109177E+03 6.292468E+01 + 1.280001E+01 1 5 -1.063990E+04 3.865463E+02 + 1.280001E+01 2 2 2.420291E+03 7.915163E+01 + 1.280001E+01 2 4 1.518379E+04 3.006381E+02 + 1.280001E+01 3 3 2.110333E+03 1.345651E+02 + 1.280001E+01 4 2 1.520208E+04 3.017477E+02 + 1.280001E+01 4 4 2.734404E+05 1.146440E+03 + 1.280001E+01 5 1 -1.066063E+04 3.840481E+02 + 1.280001E+01 5 5 8.263615E+05 2.359094E+03 + 1.280001E+01 6 6 9.437115E+05 1.331517E+03 + 1.290001E+01 1 1 2.107699E+03 6.124414E+01 + 1.290001E+01 1 5 -1.062966E+04 3.810516E+02 + 1.290001E+01 2 2 2.417847E+03 7.682533E+01 + 1.290001E+01 2 4 1.517203E+04 2.910394E+02 + 1.290001E+01 3 3 2.111769E+03 1.361919E+02 + 1.290001E+01 4 2 1.519037E+04 2.921137E+02 + 1.290001E+01 4 4 2.733828E+05 1.106919E+03 + 1.290001E+01 5 1 -1.065035E+04 3.786324E+02 + 1.290001E+01 5 5 8.263971E+05 2.355927E+03 + 1.290001E+01 6 6 9.429603E+05 1.262324E+03 + 1.300001E+01 1 1 2.106239E+03 5.962539E+01 + 1.300001E+01 1 5 -1.061992E+04 3.755821E+02 + 1.300001E+01 2 2 2.415445E+03 7.459554E+01 + 1.300001E+01 2 4 1.516055E+04 2.818689E+02 + 1.300001E+01 3 3 2.113217E+03 1.377701E+02 + 1.300001E+01 4 2 1.517887E+04 2.829082E+02 + 1.300001E+01 4 4 2.733258E+05 1.069281E+03 + 1.300001E+01 5 1 -1.064062E+04 3.732501E+02 + 1.300001E+01 5 5 8.264338E+05 2.351114E+03 + 1.300001E+01 6 6 9.422327E+05 1.197565E+03 + 1.310001E+01 1 1 2.104794E+03 5.806616E+01 + 1.310001E+01 1 5 -1.061043E+04 3.701445E+02 + 1.310001E+01 2 2 2.413100E+03 7.245785E+01 + 1.310001E+01 2 4 1.514936E+04 2.731026E+02 + 1.310001E+01 3 3 2.114666E+03 1.393071E+02 + 1.310001E+01 4 2 1.516762E+04 2.741091E+02 + 1.310001E+01 4 4 2.732713E+05 1.033417E+03 + 1.310001E+01 5 1 -1.063108E+04 3.678736E+02 + 1.310001E+01 5 5 8.264561E+05 2.345078E+03 + 1.310001E+01 6 6 9.415256E+05 1.136929E+03 + 1.320001E+01 1 1 2.103368E+03 5.656347E+01 + 1.320001E+01 1 5 -1.060147E+04 3.647414E+02 + 1.320001E+01 2 2 2.410791E+03 7.040732E+01 + 1.320001E+01 2 4 1.513839E+04 2.647195E+02 + 1.320001E+01 3 3 2.116120E+03 1.407977E+02 + 1.320001E+01 4 2 1.515654E+04 2.656937E+02 + 1.320001E+01 4 4 2.732178E+05 9.992125E+02 + 1.320001E+01 5 1 -1.062196E+04 3.625555E+02 + 1.320001E+01 5 5 8.264901E+05 2.337926E+03 + 1.320001E+01 6 6 9.408400E+05 1.080085E+03 + 1.330001E+01 1 1 2.101961E+03 5.511522E+01 + 1.330001E+01 1 5 -1.059288E+04 3.593916E+02 + 1.330001E+01 2 2 2.408532E+03 6.844022E+01 + 1.330001E+01 2 4 1.512766E+04 2.567007E+02 + 1.330001E+01 3 3 2.117555E+03 1.422505E+02 + 1.330001E+01 4 2 1.514582E+04 2.576465E+02 + 1.330001E+01 4 4 2.731667E+05 9.666104E+02 + 1.330001E+01 5 1 -1.061341E+04 3.572649E+02 + 1.330001E+01 5 5 8.265143E+05 2.329631E+03 + 1.330001E+01 6 6 9.401749E+05 1.026808E+03 + 1.340001E+01 1 1 2.100570E+03 5.371916E+01 + 1.340001E+01 1 5 -1.058467E+04 3.540811E+02 + 1.340001E+01 2 2 2.406317E+03 6.655184E+01 + 1.340001E+01 2 4 1.511717E+04 2.490257E+02 + 1.340001E+01 3 3 2.119003E+03 1.436666E+02 + 1.340001E+01 4 2 1.513535E+04 2.499415E+02 + 1.340001E+01 4 4 2.731150E+05 9.354659E+02 + 1.340001E+01 5 1 -1.060515E+04 3.520350E+02 + 1.340001E+01 5 5 8.265472E+05 2.320512E+03 + 1.340001E+01 6 6 9.395264E+05 9.767414E+02 + 1.350002E+01 1 1 2.099205E+03 5.237311E+01 + 1.350002E+01 1 5 -1.057670E+04 3.488342E+02 + 1.350002E+01 2 2 2.404147E+03 6.473885E+01 + 1.350002E+01 2 4 1.510695E+04 2.416740E+02 + 1.350002E+01 3 3 2.120441E+03 1.450347E+02 + 1.350002E+01 4 2 1.512504E+04 2.425639E+02 + 1.350002E+01 4 4 2.730665E+05 9.057045E+02 + 1.350002E+01 5 1 -1.059721E+04 3.468398E+02 + 1.350002E+01 5 5 8.265730E+05 2.310202E+03 + 1.350002E+01 6 6 9.388989E+05 9.297352E+02 + 1.360002E+01 1 1 2.097856E+03 5.107493E+01 + 1.360002E+01 1 5 -1.056917E+04 3.436465E+02 + 1.360002E+01 2 2 2.402019E+03 6.299704E+01 + 1.360002E+01 2 4 1.509691E+04 2.346342E+02 + 1.360002E+01 3 3 2.121882E+03 1.463661E+02 + 1.360002E+01 4 2 1.511499E+04 2.354969E+02 + 1.360002E+01 4 4 2.730179E+05 8.773123E+02 + 1.360002E+01 5 1 -1.058957E+04 3.417159E+02 + 1.360002E+01 5 5 8.265993E+05 2.299260E+03 + 1.360002E+01 6 6 9.382879E+05 8.855363E+02 + 1.370002E+01 1 1 2.096529E+03 4.982215E+01 + 1.370002E+01 1 5 -1.056192E+04 3.385222E+02 + 1.370002E+01 2 2 2.399936E+03 6.132322E+01 + 1.370002E+01 2 4 1.508712E+04 2.278861E+02 + 1.370002E+01 3 3 2.123323E+03 1.476655E+02 + 1.370002E+01 4 2 1.510520E+04 2.287258E+02 + 1.370002E+01 4 4 2.729711E+05 8.501495E+02 + 1.370002E+01 5 1 -1.058229E+04 3.366470E+02 + 1.370002E+01 5 5 8.266270E+05 2.287270E+03 + 1.370002E+01 6 6 9.376954E+05 8.439335E+02 + 1.380002E+01 1 1 2.095216E+03 4.861351E+01 + 1.380002E+01 1 5 -1.055499E+04 3.334639E+02 + 1.380002E+01 2 2 2.397894E+03 5.971392E+01 + 1.380002E+01 2 4 1.507760E+04 2.214170E+02 + 1.380002E+01 3 3 2.124749E+03 1.489263E+02 + 1.380002E+01 4 2 1.509560E+04 2.222306E+02 + 1.380002E+01 4 4 2.729254E+05 8.241840E+02 + 1.380002E+01 5 1 -1.057513E+04 3.316495E+02 + 1.380002E+01 5 5 8.266494E+05 2.275118E+03 + 1.380002E+01 6 6 9.371171E+05 8.048163E+02 + 1.390002E+01 1 1 2.093933E+03 4.744718E+01 + 1.390002E+01 1 5 -1.054833E+04 3.284787E+02 + 1.390002E+01 2 2 2.395897E+03 5.816627E+01 + 1.390002E+01 2 4 1.506825E+04 2.152124E+02 + 1.390002E+01 3 3 2.126180E+03 1.501581E+02 + 1.390002E+01 4 2 1.508624E+04 2.160014E+02 + 1.390002E+01 4 4 2.728797E+05 7.993529E+02 + 1.390002E+01 5 1 -1.056856E+04 3.267156E+02 + 1.390002E+01 5 5 8.266769E+05 2.261749E+03 + 1.390002E+01 6 6 9.365554E+05 7.679352E+02 + 1.400002E+01 1 1 2.092667E+03 4.632070E+01 + 1.400002E+01 1 5 -1.054198E+04 3.235636E+02 + 1.400002E+01 2 2 2.393941E+03 5.667736E+01 + 1.400002E+01 2 4 1.505914E+04 2.092574E+02 + 1.400002E+01 3 3 2.127597E+03 1.513539E+02 + 1.400002E+01 4 2 1.507707E+04 2.100287E+02 + 1.400002E+01 4 4 2.728362E+05 7.755717E+02 + 1.400002E+01 5 1 -1.056215E+04 3.218545E+02 + 1.400002E+01 5 5 8.266979E+05 2.248237E+03 + 1.400002E+01 6 6 9.360094E+05 7.331602E+02 + 1.410002E+01 1 1 2.091419E+03 4.523307E+01 + 1.410002E+01 1 5 -1.053582E+04 3.187205E+02 + 1.410002E+01 2 2 2.392023E+03 5.524433E+01 + 1.410002E+01 2 4 1.505023E+04 2.035427E+02 + 1.410002E+01 3 3 2.129027E+03 1.525149E+02 + 1.410002E+01 4 2 1.506817E+04 2.042896E+02 + 1.410002E+01 4 4 2.727942E+05 7.528195E+02 + 1.410002E+01 5 1 -1.055597E+04 3.170571E+02 + 1.410002E+01 5 5 8.267213E+05 2.234132E+03 + 1.410002E+01 6 6 9.354781E+05 7.003802E+02 + 1.420002E+01 1 1 2.090195E+03 4.418240E+01 + 1.420002E+01 1 5 -1.052992E+04 3.139538E+02 + 1.420002E+01 2 2 2.390145E+03 5.386454E+01 + 1.420002E+01 2 4 1.504148E+04 1.980522E+02 + 1.420002E+01 3 3 2.130434E+03 1.536453E+02 + 1.420002E+01 4 2 1.505939E+04 1.987785E+02 + 1.420002E+01 4 4 2.727521E+05 7.310227E+02 + 1.420002E+01 5 1 -1.055006E+04 3.123406E+02 + 1.420002E+01 5 5 8.267371E+05 2.219379E+03 + 1.420002E+01 6 6 9.349612E+05 6.694067E+02 + 1.430002E+01 1 1 2.088986E+03 4.316705E+01 + 1.430002E+01 1 5 -1.052431E+04 3.092633E+02 + 1.430002E+01 2 2 2.388311E+03 5.253564E+01 + 1.430002E+01 2 4 1.503297E+04 1.927776E+02 + 1.430002E+01 3 3 2.131842E+03 1.547496E+02 + 1.430002E+01 4 2 1.505086E+04 1.934848E+02 + 1.430002E+01 4 4 2.727125E+05 7.101144E+02 + 1.430002E+01 5 1 -1.054430E+04 3.076932E+02 + 1.430002E+01 5 5 8.267571E+05 2.204616E+03 + 1.430002E+01 6 6 9.344564E+05 6.401974E+02 + 1.440002E+01 1 1 2.087800E+03 4.218559E+01 + 1.440002E+01 1 5 -1.051887E+04 3.046481E+02 + 1.440002E+01 2 2 2.386503E+03 5.125491E+01 + 1.440002E+01 2 4 1.502466E+04 1.877069E+02 + 1.440002E+01 3 3 2.133250E+03 1.558226E+02 + 1.440002E+01 4 2 1.504250E+04 1.883958E+02 + 1.440002E+01 4 4 2.726728E+05 6.900616E+02 + 1.440002E+01 5 1 -1.053893E+04 3.031208E+02 + 1.440002E+01 5 5 8.267798E+05 2.189091E+03 + 1.440002E+01 6 6 9.339664E+05 6.125146E+02 + 1.450002E+01 1 1 2.086630E+03 4.123684E+01 + 1.450002E+01 1 5 -1.051367E+04 3.001110E+02 + 1.450002E+01 2 2 2.384744E+03 5.002060E+01 + 1.450002E+01 2 4 1.501651E+04 1.828318E+02 + 1.450002E+01 3 3 2.134643E+03 1.568708E+02 + 1.450002E+01 4 2 1.503431E+04 1.835009E+02 + 1.450002E+01 4 4 2.726331E+05 6.708359E+02 + 1.450002E+01 5 1 -1.053365E+04 2.986237E+02 + 1.450002E+01 5 5 8.268024E+05 2.173301E+03 + 1.450002E+01 6 6 9.334872E+05 5.863661E+02 + 1.460002E+01 1 1 2.085483E+03 4.031923E+01 + 1.460002E+01 1 5 -1.050862E+04 2.956489E+02 + 1.460002E+01 2 2 2.383020E+03 4.882990E+01 + 1.460002E+01 2 4 1.500857E+04 1.781401E+02 + 1.460002E+01 3 3 2.136024E+03 1.578860E+02 + 1.460002E+01 4 2 1.502636E+04 1.787920E+02 + 1.460002E+01 4 4 2.725966E+05 6.523698E+02 + 1.460002E+01 5 1 -1.052853E+04 2.942045E+02 + 1.460002E+01 5 5 8.268162E+05 2.157346E+03 + 1.460002E+01 6 6 9.330229E+05 5.616545E+02 + 1.470002E+01 1 1 2.084361E+03 3.943158E+01 + 1.470002E+01 1 5 -1.050388E+04 2.912632E+02 + 1.470002E+01 2 2 2.381325E+03 4.768178E+01 + 1.470002E+01 2 4 1.500078E+04 1.736267E+02 + 1.470002E+01 3 3 2.137404E+03 1.588762E+02 + 1.470002E+01 4 2 1.501855E+04 1.742603E+02 + 1.470002E+01 4 4 2.725603E+05 6.346516E+02 + 1.470002E+01 5 1 -1.052373E+04 2.898618E+02 + 1.470002E+01 5 5 8.268378E+05 2.141207E+03 + 1.470002E+01 6 6 9.325686E+05 5.382223E+02 + 1.480002E+01 1 1 2.083249E+03 3.857278E+01 + 1.480002E+01 1 5 -1.049920E+04 2.869577E+02 + 1.480002E+01 2 2 2.379666E+03 4.657336E+01 + 1.480002E+01 2 4 1.499321E+04 1.692799E+02 + 1.480002E+01 3 3 2.138773E+03 1.598436E+02 + 1.480002E+01 4 2 1.501094E+04 1.698969E+02 + 1.480002E+01 4 4 2.725249E+05 6.176179E+02 + 1.480002E+01 5 1 -1.051915E+04 2.855866E+02 + 1.480002E+01 5 5 8.268512E+05 2.124499E+03 + 1.480002E+01 6 6 9.321253E+05 5.160158E+02 + 1.490002E+01 1 1 2.082164E+03 3.774136E+01 + 1.490002E+01 1 5 -1.049480E+04 2.827262E+02 + 1.490002E+01 2 2 2.378054E+03 4.550396E+01 + 1.490002E+01 2 4 1.498577E+04 1.650944E+02 + 1.490002E+01 3 3 2.140139E+03 1.607877E+02 + 1.490002E+01 4 2 1.500344E+04 1.656964E+02 + 1.490002E+01 4 4 2.724897E+05 6.012692E+02 + 1.490002E+01 5 1 -1.051463E+04 2.813920E+02 + 1.490002E+01 5 5 8.268743E+05 2.108086E+03 + 1.490002E+01 6 6 9.316939E+05 4.950198E+02 + 1.500002E+01 1 1 2.081091E+03 3.693649E+01 + 1.500002E+01 1 5 -1.049057E+04 2.785714E+02 + 1.500002E+01 2 2 2.376464E+03 4.447095E+01 + 1.500002E+01 2 4 1.497853E+04 1.610604E+02 + 1.500002E+01 3 3 2.141480E+03 1.617033E+02 + 1.500002E+01 4 2 1.499619E+04 1.616474E+02 + 1.500002E+01 4 4 2.724553E+05 5.855309E+02 + 1.500002E+01 5 1 -1.051033E+04 2.772770E+02 + 1.500002E+01 5 5 8.268852E+05 2.091138E+03 + 1.500002E+01 6 6 9.312731E+05 4.750409E+02 + 1.510002E+01 1 1 2.080040E+03 3.615698E+01 + 1.510002E+01 1 5 -1.048644E+04 2.744925E+02 + 1.510002E+01 2 2 2.374910E+03 4.347293E+01 + 1.510002E+01 2 4 1.497140E+04 1.571724E+02 + 1.510002E+01 3 3 2.142820E+03 1.626021E+02 + 1.510002E+01 4 2 1.498905E+04 1.577446E+02 + 1.510002E+01 4 4 2.724219E+05 5.703980E+02 + 1.510002E+01 5 1 -1.050612E+04 2.732291E+02 + 1.510002E+01 5 5 8.268959E+05 2.074233E+03 + 1.510002E+01 6 6 9.308612E+05 4.561140E+02 + 1.520002E+01 1 1 2.079005E+03 3.540192E+01 + 1.520002E+01 1 5 -1.048248E+04 2.704842E+02 + 1.520002E+01 2 2 2.373389E+03 4.250876E+01 + 1.520002E+01 2 4 1.496444E+04 1.534227E+02 + 1.520002E+01 3 3 2.144167E+03 1.634731E+02 + 1.520002E+01 4 2 1.498212E+04 1.539825E+02 + 1.520002E+01 4 4 2.723893E+05 5.558321E+02 + 1.520002E+01 5 1 -1.050218E+04 2.692577E+02 + 1.520002E+01 5 5 8.269194E+05 2.057312E+03 + 1.520002E+01 6 6 9.304605E+05 4.380757E+02 + 1.530002E+01 1 1 2.077990E+03 3.467028E+01 + 1.530002E+01 1 5 -1.047869E+04 2.665553E+02 + 1.530002E+01 2 2 2.371897E+03 4.157639E+01 + 1.530002E+01 2 4 1.495767E+04 1.498059E+02 + 1.530002E+01 3 3 2.145491E+03 1.643267E+02 + 1.530002E+01 4 2 1.497529E+04 1.503531E+02 + 1.530002E+01 4 4 2.723578E+05 5.418108E+02 + 1.530002E+01 5 1 -1.049838E+04 2.653550E+02 + 1.530002E+01 5 5 8.269261E+05 2.040102E+03 + 1.530002E+01 6 6 9.300689E+05 4.209901E+02 + 1.540002E+01 1 1 2.076993E+03 3.396120E+01 + 1.540002E+01 1 5 -1.047507E+04 2.626942E+02 + 1.540002E+01 2 2 2.370436E+03 4.067495E+01 + 1.540002E+01 2 4 1.495101E+04 1.463179E+02 + 1.540002E+01 3 3 2.146810E+03 1.651566E+02 + 1.540002E+01 4 2 1.496861E+04 1.468497E+02 + 1.540002E+01 4 4 2.723265E+05 5.283426E+02 + 1.540002E+01 5 1 -1.049469E+04 2.615269E+02 + 1.540002E+01 5 5 8.269438E+05 2.023000E+03 + 1.540002E+01 6 6 9.296864E+05 4.047350E+02 + 1.550002E+01 1 1 2.076013E+03 3.327344E+01 + 1.550002E+01 1 5 -1.047153E+04 2.589065E+02 + 1.550002E+01 2 2 2.369007E+03 3.980273E+01 + 1.550002E+01 2 4 1.494455E+04 1.429486E+02 + 1.550002E+01 3 3 2.148116E+03 1.659677E+02 + 1.550002E+01 4 2 1.496212E+04 1.434692E+02 + 1.550002E+01 4 4 2.722966E+05 5.153308E+02 + 1.550002E+01 5 1 -1.049112E+04 2.577680E+02 + 1.550002E+01 5 5 8.269541E+05 2.005682E+03 + 1.550002E+01 6 6 9.293126E+05 3.892980E+02 + 1.560002E+01 1 1 2.075051E+03 3.260694E+01 + 1.560002E+01 1 5 -1.046815E+04 2.551922E+02 + 1.560002E+01 2 2 2.367606E+03 3.895897E+01 + 1.560002E+01 2 4 1.493817E+04 1.396942E+02 + 1.560002E+01 3 3 2.149407E+03 1.667584E+02 + 1.560002E+01 4 2 1.495576E+04 1.402030E+02 + 1.560002E+01 4 4 2.722664E+05 5.027727E+02 + 1.560002E+01 5 1 -1.048774E+04 2.540764E+02 + 1.560002E+01 5 5 8.269706E+05 1.988470E+03 + 1.560002E+01 6 6 9.289479E+05 3.745744E+02 + 1.570002E+01 1 1 2.074105E+03 3.196018E+01 + 1.570002E+01 1 5 -1.046487E+04 2.515442E+02 + 1.570002E+01 2 2 2.366228E+03 3.814221E+01 + 1.570002E+01 2 4 1.493197E+04 1.365507E+02 + 1.570002E+01 3 3 2.150707E+03 1.675297E+02 + 1.570002E+01 4 2 1.494948E+04 1.370478E+02 + 1.570002E+01 4 4 2.722373E+05 4.906886E+02 + 1.570002E+01 5 1 -1.048435E+04 2.504556E+02 + 1.570002E+01 5 5 8.269825E+05 1.971414E+03 + 1.570002E+01 6 6 9.285927E+05 3.605742E+02 + 1.580002E+01 1 1 2.073177E+03 3.133257E+01 + 1.580002E+01 1 5 -1.046171E+04 2.479682E+02 + 1.580002E+01 2 2 2.364879E+03 3.735137E+01 + 1.580002E+01 2 4 1.492585E+04 1.335133E+02 + 1.580002E+01 3 3 2.151987E+03 1.682820E+02 + 1.580002E+01 4 2 1.494334E+04 1.340023E+02 + 1.580002E+01 4 4 2.722095E+05 4.790283E+02 + 1.580002E+01 5 1 -1.048124E+04 2.469087E+02 + 1.580002E+01 5 5 8.269909E+05 1.953933E+03 + 1.580002E+01 6 6 9.282444E+05 3.471773E+02 + 1.590002E+01 1 1 2.072261E+03 3.072359E+01 + 1.590002E+01 1 5 -1.045869E+04 2.444564E+02 + 1.590002E+01 2 2 2.363563E+03 3.658521E+01 + 1.590002E+01 2 4 1.491990E+04 1.305775E+02 + 1.590002E+01 3 3 2.153257E+03 1.690168E+02 + 1.590002E+01 4 2 1.493744E+04 1.310534E+02 + 1.590002E+01 4 4 2.721814E+05 4.677970E+02 + 1.590002E+01 5 1 -1.047818E+04 2.434140E+02 + 1.590002E+01 5 5 8.270022E+05 1.936942E+03 + 1.590002E+01 6 6 9.279032E+05 3.344916E+02 + 1.600002E+01 1 1 2.071366E+03 3.013219E+01 + 1.600002E+01 1 5 -1.045578E+04 2.410121E+02 + 1.600002E+01 2 2 2.362272E+03 3.584298E+01 + 1.600002E+01 2 4 1.491406E+04 1.277372E+02 + 1.600002E+01 3 3 2.154517E+03 1.697373E+02 + 1.600002E+01 4 2 1.493153E+04 1.282041E+02 + 1.600002E+01 4 4 2.721539E+05 4.569208E+02 + 1.600002E+01 5 1 -1.047521E+04 2.400044E+02 + 1.600002E+01 5 5 8.270164E+05 1.919702E+03 + 1.600002E+01 6 6 9.275708E+05 3.223495E+02 + 1.610003E+01 1 1 2.070484E+03 2.955817E+01 + 1.610003E+01 1 5 -1.045294E+04 2.376343E+02 + 1.610003E+01 2 2 2.361004E+03 3.512328E+01 + 1.610003E+01 2 4 1.490836E+04 1.249913E+02 + 1.610003E+01 3 3 2.155781E+03 1.704411E+02 + 1.610003E+01 4 2 1.492584E+04 1.254452E+02 + 1.610003E+01 4 4 2.721288E+05 4.464518E+02 + 1.610003E+01 5 1 -1.047237E+04 2.366466E+02 + 1.610003E+01 5 5 8.270226E+05 1.902542E+03 + 1.610003E+01 6 6 9.272455E+05 3.107794E+02 + 1.620003E+01 1 1 2.069616E+03 2.900060E+01 + 1.620003E+01 1 5 -1.045020E+04 2.343210E+02 + 1.620003E+01 2 2 2.359761E+03 3.442596E+01 + 1.620003E+01 2 4 1.490279E+04 1.223333E+02 + 1.620003E+01 3 3 2.157026E+03 1.711245E+02 + 1.620003E+01 4 2 1.492020E+04 1.227781E+02 + 1.620003E+01 4 4 2.721026E+05 4.363372E+02 + 1.620003E+01 5 1 -1.046956E+04 2.333506E+02 + 1.620003E+01 5 5 8.270325E+05 1.885493E+03 + 1.620003E+01 6 6 9.269280E+05 2.997424E+02 + 1.630003E+01 1 1 2.068766E+03 2.845874E+01 + 1.630003E+01 1 5 -1.044763E+04 2.310678E+02 + 1.630003E+01 2 2 2.358545E+03 3.374945E+01 + 1.630003E+01 2 4 1.489730E+04 1.197599E+02 + 1.630003E+01 3 3 2.158250E+03 1.717934E+02 + 1.630003E+01 4 2 1.491471E+04 1.201951E+02 + 1.630003E+01 4 4 2.720770E+05 4.265562E+02 + 1.630003E+01 5 1 -1.046698E+04 2.301221E+02 + 1.630003E+01 5 5 8.270442E+05 1.868405E+03 + 1.630003E+01 6 6 9.266187E+05 2.891885E+02 + 1.640003E+01 1 1 2.067928E+03 2.793233E+01 + 1.640003E+01 1 5 -1.044513E+04 2.278778E+02 + 1.640003E+01 2 2 2.357353E+03 3.309323E+01 + 1.640003E+01 2 4 1.489195E+04 1.172682E+02 + 1.640003E+01 3 3 2.159478E+03 1.724470E+02 + 1.640003E+01 4 2 1.490937E+04 1.176936E+02 + 1.640003E+01 4 4 2.720522E+05 4.170867E+02 + 1.640003E+01 5 1 -1.046442E+04 2.269559E+02 + 1.640003E+01 5 5 8.270501E+05 1.851661E+03 + 1.640003E+01 6 6 9.263129E+05 2.791281E+02 + 1.650003E+01 1 1 2.067111E+03 2.742050E+01 + 1.650003E+01 1 5 -1.044264E+04 2.247480E+02 + 1.650003E+01 2 2 2.356185E+03 3.245648E+01 + 1.650003E+01 2 4 1.488669E+04 1.148537E+02 + 1.650003E+01 3 3 2.160696E+03 1.730935E+02 + 1.650003E+01 4 2 1.490406E+04 1.152725E+02 + 1.650003E+01 4 4 2.720282E+05 4.079402E+02 + 1.650003E+01 5 1 -1.046200E+04 2.238463E+02 + 1.650003E+01 5 5 8.270595E+05 1.834824E+03 + 1.650003E+01 6 6 9.260153E+05 2.694910E+02 + 1.660003E+01 1 1 2.066301E+03 2.692302E+01 + 1.660003E+01 1 5 -1.044032E+04 2.216787E+02 + 1.660003E+01 2 2 2.355030E+03 3.183842E+01 + 1.660003E+01 2 4 1.488153E+04 1.125153E+02 + 1.660003E+01 3 3 2.161904E+03 1.737168E+02 + 1.660003E+01 4 2 1.489894E+04 1.129257E+02 + 1.660003E+01 4 4 2.720042E+05 3.991012E+02 + 1.660003E+01 5 1 -1.045955E+04 2.207931E+02 + 1.660003E+01 5 5 8.270729E+05 1.817911E+03 + 1.660003E+01 6 6 9.257228E+05 2.602718E+02 + 1.670003E+01 1 1 2.065512E+03 2.643911E+01 + 1.670003E+01 1 5 -1.043803E+04 2.186671E+02 + 1.670003E+01 2 2 2.353910E+03 3.123835E+01 + 1.670003E+01 2 4 1.487652E+04 1.102490E+02 + 1.670003E+01 3 3 2.163101E+03 1.743276E+02 + 1.670003E+01 4 2 1.489390E+04 1.106499E+02 + 1.670003E+01 4 4 2.719815E+05 3.905549E+02 + 1.670003E+01 5 1 -1.045730E+04 2.178046E+02 + 1.670003E+01 5 5 8.270786E+05 1.801339E+03 + 1.670003E+01 6 6 9.254366E+05 2.514675E+02 + 1.680003E+01 1 1 2.064729E+03 2.596842E+01 + 1.680003E+01 1 5 -1.043582E+04 2.157118E+02 + 1.680003E+01 2 2 2.352802E+03 3.065560E+01 + 1.680003E+01 2 4 1.487159E+04 1.080519E+02 + 1.680003E+01 3 3 2.164293E+03 1.749266E+02 + 1.680003E+01 4 2 1.488892E+04 1.084453E+02 + 1.680003E+01 4 4 2.719588E+05 3.822675E+02 + 1.680003E+01 5 1 -1.045502E+04 2.148672E+02 + 1.680003E+01 5 5 8.270844E+05 1.784897E+03 + 1.680003E+01 6 6 9.251572E+05 2.430606E+02 + 1.690003E+01 1 1 2.063964E+03 2.551030E+01 + 1.690003E+01 1 5 -1.043371E+04 2.128134E+02 + 1.690003E+01 2 2 2.351719E+03 3.008941E+01 + 1.690003E+01 2 4 1.486673E+04 1.059205E+02 + 1.690003E+01 3 3 2.165474E+03 1.755150E+02 + 1.690003E+01 4 2 1.488408E+04 1.063057E+02 + 1.690003E+01 4 4 2.719358E+05 3.742552E+02 + 1.690003E+01 5 1 -1.045286E+04 2.119846E+02 + 1.690003E+01 5 5 8.270939E+05 1.768436E+03 + 1.690003E+01 6 6 9.248847E+05 2.349536E+02 + 1.700003E+01 1 1 2.063209E+03 2.506457E+01 + 1.700003E+01 1 5 -1.043165E+04 2.099697E+02 + 1.700003E+01 2 2 2.350652E+03 2.953933E+01 + 1.700003E+01 2 4 1.486197E+04 1.038516E+02 + 1.700003E+01 3 3 2.166653E+03 1.760840E+02 + 1.700003E+01 4 2 1.487930E+04 1.042311E+02 + 1.700003E+01 4 4 2.719141E+05 3.664562E+02 + 1.700003E+01 5 1 -1.045088E+04 2.091586E+02 + 1.700003E+01 5 5 8.271021E+05 1.752063E+03 + 1.700003E+01 6 6 9.246164E+05 2.272261E+02 + 1.710003E+01 1 1 2.062470E+03 2.463075E+01 + 1.710003E+01 1 5 -1.042968E+04 2.071769E+02 + 1.710003E+01 2 2 2.349615E+03 2.900439E+01 + 1.710003E+01 2 4 1.485737E+04 1.018465E+02 + 1.710003E+01 3 3 2.167818E+03 1.766457E+02 + 1.710003E+01 4 2 1.487468E+04 1.022170E+02 + 1.710003E+01 4 4 2.718934E+05 3.589480E+02 + 1.710003E+01 5 1 -1.044881E+04 2.063858E+02 + 1.710003E+01 5 5 8.271076E+05 1.735944E+03 + 1.710003E+01 6 6 9.243549E+05 2.198451E+02 + 1.720003E+01 1 1 2.061742E+03 2.420838E+01 + 1.720003E+01 1 5 -1.042781E+04 2.044397E+02 + 1.720003E+01 2 2 2.348598E+03 2.848452E+01 + 1.720003E+01 2 4 1.485284E+04 9.989874E+01 + 1.720003E+01 3 3 2.168974E+03 1.771941E+02 + 1.720003E+01 4 2 1.487010E+04 1.002615E+02 + 1.720003E+01 4 4 2.718733E+05 3.516508E+02 + 1.720003E+01 5 1 -1.044685E+04 2.036589E+02 + 1.720003E+01 5 5 8.271099E+05 1.719808E+03 + 1.720003E+01 6 6 9.240961E+05 2.127342E+02 + 1.730003E+01 1 1 2.061026E+03 2.379716E+01 + 1.730003E+01 1 5 -1.042594E+04 2.017511E+02 + 1.730003E+01 2 2 2.347590E+03 2.797889E+01 + 1.730003E+01 2 4 1.484834E+04 9.800805E+01 + 1.730003E+01 3 3 2.170129E+03 1.777283E+02 + 1.730003E+01 4 2 1.486565E+04 9.836308E+01 + 1.730003E+01 4 4 2.718520E+05 3.445775E+02 + 1.730003E+01 5 1 -1.044493E+04 2.009904E+02 + 1.730003E+01 5 5 8.271202E+05 1.704027E+03 + 1.730003E+01 6 6 9.238454E+05 2.059225E+02 + 1.740003E+01 1 1 2.060324E+03 2.339627E+01 + 1.740003E+01 1 5 -1.042415E+04 1.991144E+02 + 1.740003E+01 2 2 2.346608E+03 2.748712E+01 + 1.740003E+01 2 4 1.484396E+04 9.617191E+01 + 1.740003E+01 3 3 2.171259E+03 1.782491E+02 + 1.740003E+01 4 2 1.486128E+04 9.652121E+01 + 1.740003E+01 4 4 2.718323E+05 3.377369E+02 + 1.740003E+01 5 1 -1.044318E+04 1.983685E+02 + 1.740003E+01 5 5 8.271267E+05 1.688139E+03 + 1.740003E+01 6 6 9.235982E+05 1.994094E+02 + 1.750003E+01 1 1 2.059634E+03 2.300596E+01 + 1.750003E+01 1 5 -1.042243E+04 1.965280E+02 + 1.750003E+01 2 2 2.345637E+03 2.700851E+01 + 1.750003E+01 2 4 1.483970E+04 9.438749E+01 + 1.750003E+01 3 3 2.172393E+03 1.787659E+02 + 1.750003E+01 4 2 1.485691E+04 9.473090E+01 + 1.750003E+01 4 4 2.718115E+05 3.310837E+02 + 1.750003E+01 5 1 -1.044150E+04 1.957994E+02 + 1.750003E+01 5 5 8.271300E+05 1.672497E+03 + 1.750003E+01 6 6 9.233557E+05 1.931149E+02 + 1.760003E+01 1 1 2.058954E+03 2.262552E+01 + 1.760003E+01 1 5 -1.042073E+04 1.939864E+02 + 1.760003E+01 2 2 2.344687E+03 2.654274E+01 + 1.760003E+01 2 4 1.483547E+04 9.265537E+01 + 1.760003E+01 3 3 2.173507E+03 1.792697E+02 + 1.760003E+01 4 2 1.485272E+04 9.298941E+01 + 1.760003E+01 4 4 2.717932E+05 3.246413E+02 + 1.760003E+01 5 1 -1.043976E+04 1.932696E+02 + 1.760003E+01 5 5 8.271320E+05 1.657040E+03 + 1.760003E+01 6 6 9.231200E+05 1.871032E+02 + 1.770003E+01 1 1 2.058286E+03 2.225474E+01 + 1.770003E+01 1 5 -1.041911E+04 1.914942E+02 + 1.770003E+01 2 2 2.343760E+03 2.608939E+01 + 1.770003E+01 2 4 1.483137E+04 9.096959E+01 + 1.770003E+01 3 3 2.174629E+03 1.797623E+02 + 1.770003E+01 4 2 1.484857E+04 9.129957E+01 + 1.770003E+01 4 4 2.717740E+05 3.183698E+02 + 1.770003E+01 5 1 -1.043807E+04 1.907895E+02 + 1.770003E+01 5 5 8.271378E+05 1.641710E+03 + 1.770003E+01 6 6 9.228866E+05 1.813262E+02 + 1.780003E+01 1 1 2.057630E+03 2.189306E+01 + 1.780003E+01 1 5 -1.041756E+04 1.890476E+02 + 1.780003E+01 2 2 2.342843E+03 2.564802E+01 + 1.780003E+01 2 4 1.482732E+04 8.933209E+01 + 1.780003E+01 3 3 2.175732E+03 1.802451E+02 + 1.780003E+01 4 2 1.484451E+04 8.965611E+01 + 1.780003E+01 4 4 2.717548E+05 3.123017E+02 + 1.780003E+01 5 1 -1.043651E+04 1.883601E+02 + 1.780003E+01 5 5 8.271411E+05 1.626481E+03 + 1.780003E+01 6 6 9.226586E+05 1.758039E+02 + 1.790003E+01 1 1 2.056979E+03 2.154061E+01 + 1.790003E+01 1 5 -1.041605E+04 1.866453E+02 + 1.790003E+01 2 2 2.341945E+03 2.521803E+01 + 1.790003E+01 2 4 1.482331E+04 8.773805E+01 + 1.790003E+01 3 3 2.176833E+03 1.807188E+02 + 1.790003E+01 4 2 1.484051E+04 8.805619E+01 + 1.790003E+01 4 4 2.717376E+05 3.063807E+02 + 1.790003E+01 5 1 -1.043498E+04 1.859703E+02 + 1.790003E+01 5 5 8.271443E+05 1.611391E+03 + 1.790003E+01 6 6 9.224355E+05 1.704742E+02 + 1.800003E+01 1 1 2.056345E+03 2.119668E+01 + 1.800003E+01 1 5 -1.041461E+04 1.842881E+02 + 1.800003E+01 2 2 2.341061E+03 2.479934E+01 + 1.800003E+01 2 4 1.481941E+04 8.618948E+01 + 1.800003E+01 3 3 2.177930E+03 1.811826E+02 + 1.800003E+01 4 2 1.483661E+04 8.650233E+01 + 1.800003E+01 4 4 2.717198E+05 3.006520E+02 + 1.800003E+01 5 1 -1.043344E+04 1.836254E+02 + 1.800003E+01 5 5 8.271499E+05 1.596410E+03 + 1.800003E+01 6 6 9.222149E+05 1.653296E+02 + 1.810003E+01 1 1 2.055720E+03 2.086128E+01 + 1.810003E+01 1 5 -1.041317E+04 1.819731E+02 + 1.810003E+01 2 2 2.340197E+03 2.439112E+01 + 1.810003E+01 2 4 1.481561E+04 8.468084E+01 + 1.810003E+01 3 3 2.179028E+03 1.816369E+02 + 1.810003E+01 4 2 1.483279E+04 8.498753E+01 + 1.810003E+01 4 4 2.717028E+05 2.950850E+02 + 1.810003E+01 5 1 -1.043208E+04 1.813213E+02 + 1.810003E+01 5 5 8.271562E+05 1.581557E+03 + 1.810003E+01 6 6 9.220011E+05 1.603738E+02 + 1.820003E+01 1 1 2.055104E+03 2.053393E+01 + 1.820003E+01 1 5 -1.041181E+04 1.796993E+02 + 1.820003E+01 2 2 2.339348E+03 2.399349E+01 + 1.820003E+01 2 4 1.481184E+04 8.321352E+01 + 1.820003E+01 3 3 2.180094E+03 1.820844E+02 + 1.820003E+01 4 2 1.482906E+04 8.351611E+01 + 1.820003E+01 4 4 2.716851E+05 2.896564E+02 + 1.820003E+01 5 1 -1.043072E+04 1.790640E+02 + 1.820003E+01 5 5 8.271657E+05 1.567039E+03 + 1.820003E+01 6 6 9.217888E+05 1.556339E+02 + 1.830003E+01 1 1 2.054502E+03 2.021455E+01 + 1.830003E+01 1 5 -1.041048E+04 1.774697E+02 + 1.830003E+01 2 2 2.338513E+03 2.360573E+01 + 1.830003E+01 2 4 1.480814E+04 8.178493E+01 + 1.830003E+01 3 3 2.181152E+03 1.825197E+02 + 1.830003E+01 4 2 1.482531E+04 8.208099E+01 + 1.830003E+01 4 4 2.716680E+05 2.844013E+02 + 1.830003E+01 5 1 -1.042929E+04 1.768469E+02 + 1.830003E+01 5 5 8.271634E+05 1.552448E+03 + 1.830003E+01 6 6 9.215821E+05 1.510820E+02 + 1.840003E+01 1 1 2.053909E+03 1.990290E+01 + 1.840003E+01 1 5 -1.040918E+04 1.752774E+02 + 1.840003E+01 2 2 2.337692E+03 2.322764E+01 + 1.840003E+01 2 4 1.480456E+04 8.039359E+01 + 1.840003E+01 3 3 2.182225E+03 1.829501E+02 + 1.840003E+01 4 2 1.482169E+04 8.068610E+01 + 1.840003E+01 4 4 2.716522E+05 2.792823E+02 + 1.840003E+01 5 1 -1.042802E+04 1.746610E+02 + 1.840003E+01 5 5 8.271635E+05 1.538224E+03 + 1.840003E+01 6 6 9.213790E+05 1.466810E+02 + 1.850003E+01 1 1 2.053320E+03 1.959850E+01 + 1.850003E+01 1 5 -1.040793E+04 1.731259E+02 + 1.850003E+01 2 2 2.336886E+03 2.285887E+01 + 1.850003E+01 2 4 1.480099E+04 7.903979E+01 + 1.850003E+01 3 3 2.183267E+03 1.833716E+02 + 1.850003E+01 4 2 1.481814E+04 7.932382E+01 + 1.850003E+01 4 4 2.716357E+05 2.743032E+02 + 1.850003E+01 5 1 -1.042672E+04 1.725223E+02 + 1.850003E+01 5 5 8.271721E+05 1.523950E+03 + 1.850003E+01 6 6 9.211794E+05 1.424494E+02 + 1.860003E+01 1 1 2.052746E+03 1.930129E+01 + 1.860003E+01 1 5 -1.040671E+04 1.710121E+02 + 1.860003E+01 2 2 2.336096E+03 2.249916E+01 + 1.860003E+01 2 4 1.479749E+04 7.771886E+01 + 1.860003E+01 3 3 2.184322E+03 1.837843E+02 + 1.860003E+01 4 2 1.481466E+04 7.800043E+01 + 1.860003E+01 4 4 2.716191E+05 2.694428E+02 + 1.860003E+01 5 1 -1.042551E+04 1.704225E+02 + 1.860003E+01 5 5 8.271738E+05 1.509914E+03 + 1.860003E+01 6 6 9.209849E+05 1.383857E+02 + 1.870004E+01 1 1 2.052183E+03 1.901094E+01 + 1.870004E+01 1 5 -1.040557E+04 1.689366E+02 + 1.870004E+01 2 2 2.335311E+03 2.214833E+01 + 1.870004E+01 2 4 1.479409E+04 7.643378E+01 + 1.870004E+01 3 3 2.185352E+03 1.841807E+02 + 1.870004E+01 4 2 1.481118E+04 7.670943E+01 + 1.870004E+01 4 4 2.716044E+05 2.647291E+02 + 1.870004E+01 5 1 -1.042427E+04 1.683552E+02 + 1.870004E+01 5 5 8.271734E+05 1.495996E+03 + 1.870004E+01 6 6 9.207909E+05 1.344660E+02 + 1.880004E+01 1 1 2.051628E+03 1.872726E+01 + 1.880004E+01 1 5 -1.040444E+04 1.668994E+02 + 1.880004E+01 2 2 2.334550E+03 2.180602E+01 + 1.880004E+01 2 4 1.479072E+04 7.518122E+01 + 1.880004E+01 3 3 2.186382E+03 1.845765E+02 + 1.880004E+01 4 2 1.480782E+04 7.545424E+01 + 1.880004E+01 4 4 2.715896E+05 2.601515E+02 + 1.880004E+01 5 1 -1.042326E+04 1.663279E+02 + 1.880004E+01 5 5 8.271764E+05 1.482188E+03 + 1.880004E+01 6 6 9.206021E+05 1.306727E+02 + 1.890004E+01 1 1 2.051073E+03 1.845038E+01 + 1.890004E+01 1 5 -1.040334E+04 1.648945E+02 + 1.890004E+01 2 2 2.333793E+03 2.147164E+01 + 1.890004E+01 2 4 1.478741E+04 7.396050E+01 + 1.890004E+01 3 3 2.187406E+03 1.849668E+02 + 1.890004E+01 4 2 1.480450E+04 7.422672E+01 + 1.890004E+01 4 4 2.715736E+05 2.557082E+02 + 1.890004E+01 5 1 -1.042207E+04 1.643343E+02 + 1.890004E+01 5 5 8.271801E+05 1.468711E+03 + 1.890004E+01 6 6 9.204173E+05 1.270228E+02 + 1.900004E+01 1 1 2.050531E+03 1.817950E+01 + 1.900004E+01 1 5 -1.040224E+04 1.629282E+02 + 1.900004E+01 2 2 2.333057E+03 2.114543E+01 + 1.900004E+01 2 4 1.478419E+04 7.276846E+01 + 1.900004E+01 3 3 2.188413E+03 1.853446E+02 + 1.900004E+01 4 2 1.480126E+04 7.303304E+01 + 1.900004E+01 4 4 2.715604E+05 2.513305E+02 + 1.900004E+01 5 1 -1.042097E+04 1.623760E+02 + 1.900004E+01 5 5 8.271833E+05 1.455291E+03 + 1.900004E+01 6 6 9.202351E+05 1.234795E+02 + 1.910004E+01 1 1 2.050006E+03 1.791492E+01 + 1.910004E+01 1 5 -1.040121E+04 1.609936E+02 + 1.910004E+01 2 2 2.332327E+03 2.082673E+01 + 1.910004E+01 2 4 1.478098E+04 7.160725E+01 + 1.910004E+01 3 3 2.189432E+03 1.857226E+02 + 1.910004E+01 4 2 1.479808E+04 7.186718E+01 + 1.910004E+01 4 4 2.715451E+05 2.471007E+02 + 1.910004E+01 5 1 -1.041999E+04 1.604564E+02 + 1.910004E+01 5 5 8.271872E+05 1.441932E+03 + 1.910004E+01 6 6 9.200559E+05 1.201205E+02 + 1.920004E+01 1 1 2.049483E+03 1.765621E+01 + 1.920004E+01 1 5 -1.040026E+04 1.590964E+02 + 1.920004E+01 2 2 2.331615E+03 2.051542E+01 + 1.920004E+01 2 4 1.477788E+04 7.047442E+01 + 1.920004E+01 3 3 2.190425E+03 1.860850E+02 + 1.920004E+01 4 2 1.479489E+04 7.072854E+01 + 1.920004E+01 4 4 2.715305E+05 2.429766E+02 + 1.920004E+01 5 1 -1.041893E+04 1.585637E+02 + 1.920004E+01 5 5 8.271846E+05 1.428767E+03 + 1.920004E+01 6 6 9.198796E+05 1.168207E+02 + 1.930004E+01 1 1 2.048965E+03 1.740320E+01 + 1.930004E+01 1 5 -1.039924E+04 1.572290E+02 + 1.930004E+01 2 2 2.330912E+03 2.021156E+01 + 1.930004E+01 2 4 1.477479E+04 6.936960E+01 + 1.930004E+01 3 3 2.191418E+03 1.864453E+02 + 1.930004E+01 4 2 1.479185E+04 6.962022E+01 + 1.930004E+01 4 4 2.715169E+05 2.389581E+02 + 1.930004E+01 5 1 -1.041793E+04 1.567098E+02 + 1.930004E+01 5 5 8.271876E+05 1.415792E+03 + 1.930004E+01 6 6 9.197066E+05 1.136690E+02 + 1.940004E+01 1 1 2.048461E+03 1.715591E+01 + 1.940004E+01 1 5 -1.039833E+04 1.553941E+02 + 1.940004E+01 2 2 2.330222E+03 1.991453E+01 + 1.940004E+01 2 4 1.477176E+04 6.829047E+01 + 1.940004E+01 3 3 2.192412E+03 1.867998E+02 + 1.940004E+01 4 2 1.478880E+04 6.853768E+01 + 1.940004E+01 4 4 2.715025E+05 2.350184E+02 + 1.940004E+01 5 1 -1.041693E+04 1.548798E+02 + 1.940004E+01 5 5 8.271892E+05 1.402910E+03 + 1.940004E+01 6 6 9.195372E+05 1.106253E+02 + 1.950004E+01 1 1 2.047965E+03 1.691395E+01 + 1.950004E+01 1 5 -1.039738E+04 1.535927E+02 + 1.950004E+01 2 2 2.329543E+03 1.962435E+01 + 1.950004E+01 2 4 1.476878E+04 6.723826E+01 + 1.950004E+01 3 3 2.193378E+03 1.871498E+02 + 1.950004E+01 4 2 1.478586E+04 6.748221E+01 + 1.950004E+01 4 4 2.714897E+05 2.312206E+02 + 1.950004E+01 5 1 -1.041604E+04 1.530889E+02 + 1.950004E+01 5 5 8.271920E+05 1.390185E+03 + 1.950004E+01 6 6 9.193708E+05 1.076600E+02 + 1.960004E+01 1 1 2.047471E+03 1.667731E+01 + 1.960004E+01 1 5 -1.039650E+04 1.518212E+02 + 1.960004E+01 2 2 2.328873E+03 1.934076E+01 + 1.960004E+01 2 4 1.476587E+04 6.621005E+01 + 1.960004E+01 3 3 2.194353E+03 1.874906E+02 + 1.960004E+01 4 2 1.478289E+04 6.645112E+01 + 1.960004E+01 4 4 2.714757E+05 2.274843E+02 + 1.960004E+01 5 1 -1.041511E+04 1.513279E+02 + 1.960004E+01 5 5 8.271972E+05 1.377511E+03 + 1.960004E+01 6 6 9.192068E+05 1.048207E+02 + 1.970004E+01 1 1 2.046986E+03 1.644575E+01 + 1.970004E+01 1 5 -1.039560E+04 1.500790E+02 + 1.970004E+01 2 2 2.328215E+03 1.906352E+01 + 1.970004E+01 2 4 1.476300E+04 6.520600E+01 + 1.970004E+01 3 3 2.195329E+03 1.878243E+02 + 1.970004E+01 4 2 1.477999E+04 6.544521E+01 + 1.970004E+01 4 4 2.714634E+05 2.238466E+02 + 1.970004E+01 5 1 -1.041429E+04 1.495925E+02 + 1.970004E+01 5 5 8.271948E+05 1.365125E+03 + 1.970004E+01 6 6 9.190450E+05 1.020527E+02 + 1.980004E+01 1 1 2.046512E+03 1.621911E+01 + 1.980004E+01 1 5 -1.039480E+04 1.483693E+02 + 1.980004E+01 2 2 2.327573E+03 1.879211E+01 + 1.980004E+01 2 4 1.476018E+04 6.422812E+01 + 1.980004E+01 3 3 2.196280E+03 1.881516E+02 + 1.980004E+01 4 2 1.477718E+04 6.445956E+01 + 1.980004E+01 4 4 2.714500E+05 2.203193E+02 + 1.980004E+01 5 1 -1.041339E+04 1.478867E+02 + 1.980004E+01 5 5 8.271914E+05 1.352687E+03 + 1.980004E+01 6 6 9.188865E+05 9.938832E+01 + 1.990004E+01 1 1 2.046042E+03 1.599738E+01 + 1.990004E+01 1 5 -1.039398E+04 1.466865E+02 + 1.990004E+01 2 2 2.326934E+03 1.852710E+01 + 1.990004E+01 2 4 1.475738E+04 6.326960E+01 + 1.990004E+01 3 3 2.197233E+03 1.884762E+02 + 1.990004E+01 4 2 1.477441E+04 6.349908E+01 + 1.990004E+01 4 4 2.714381E+05 2.168449E+02 + 1.990004E+01 5 1 -1.041256E+04 1.462119E+02 + 1.990004E+01 5 5 8.271924E+05 1.340653E+03 + 1.990004E+01 6 6 9.187299E+05 9.683757E+01 + 2.000004E+01 1 1 2.045585E+03 1.578026E+01 + 2.000004E+01 1 5 -1.039323E+04 1.450318E+02 + 2.000004E+01 2 2 2.326304E+03 1.826778E+01 + 2.000004E+01 2 4 1.475468E+04 6.233554E+01 + 2.000004E+01 3 3 2.198189E+03 1.887917E+02 + 2.000004E+01 4 2 1.477165E+04 6.256093E+01 + 2.000004E+01 4 4 2.714253E+05 2.135000E+02 + 2.000004E+01 5 1 -1.041179E+04 1.445639E+02 + 2.000004E+01 5 5 8.271966E+05 1.328640E+03 + 2.000004E+01 6 6 9.185784E+05 9.434976E+01 + 2.010004E+01 1 1 2.045125E+03 1.556776E+01 + 2.010004E+01 1 5 -1.039244E+04 1.434056E+02 + 2.010004E+01 2 2 2.325691E+03 1.801404E+01 + 2.010004E+01 2 4 1.475198E+04 6.142097E+01 + 2.010004E+01 3 3 2.199134E+03 1.891055E+02 + 2.010004E+01 4 2 1.476897E+04 6.164350E+01 + 2.010004E+01 4 4 2.714142E+05 2.101818E+02 + 2.010004E+01 5 1 -1.041102E+04 1.429480E+02 + 2.010004E+01 5 5 8.271989E+05 1.316722E+03 + 2.010004E+01 6 6 9.184271E+05 9.191343E+01 + 2.020004E+01 1 1 2.044676E+03 1.535972E+01 + 2.020004E+01 1 5 -1.039172E+04 1.418049E+02 + 2.020004E+01 2 2 2.325084E+03 1.776595E+01 + 2.020004E+01 2 4 1.474935E+04 6.052758E+01 + 2.020004E+01 3 3 2.200063E+03 1.894135E+02 + 2.020004E+01 4 2 1.476634E+04 6.074775E+01 + 2.020004E+01 4 4 2.714013E+05 2.069709E+02 + 2.020004E+01 5 1 -1.041023E+04 1.413513E+02 + 2.020004E+01 5 5 8.272012E+05 1.305076E+03 + 2.020004E+01 6 6 9.182805E+05 8.961385E+01 + 2.030004E+01 1 1 2.044239E+03 1.515596E+01 + 2.030004E+01 1 5 -1.039100E+04 1.402321E+02 + 2.030004E+01 2 2 2.324486E+03 1.752291E+01 + 2.030004E+01 2 4 1.474676E+04 5.965457E+01 + 2.030004E+01 3 3 2.200991E+03 1.897112E+02 + 2.030004E+01 4 2 1.476376E+04 5.987170E+01 + 2.030004E+01 4 4 2.713893E+05 2.038347E+02 + 2.030004E+01 5 1 -1.040953E+04 1.397888E+02 + 2.030004E+01 5 5 8.272011E+05 1.293445E+03 + 2.030004E+01 6 6 9.181336E+05 8.735389E+01 + 2.040004E+01 1 1 2.043802E+03 1.495623E+01 + 2.040004E+01 1 5 -1.039028E+04 1.386837E+02 + 2.040004E+01 2 2 2.323908E+03 1.728514E+01 + 2.040004E+01 2 4 1.474422E+04 5.880129E+01 + 2.040004E+01 3 3 2.201927E+03 1.900100E+02 + 2.040004E+01 4 2 1.476116E+04 5.901313E+01 + 2.040004E+01 4 4 2.713787E+05 2.007744E+02 + 2.040004E+01 5 1 -1.040880E+04 1.382498E+02 + 2.040004E+01 5 5 8.271992E+05 1.281930E+03 + 2.040004E+01 6 6 9.179906E+05 8.516948E+01 + 2.050004E+01 1 1 2.043376E+03 1.476065E+01 + 2.050004E+01 1 5 -1.038959E+04 1.371617E+02 + 2.050004E+01 2 2 2.323322E+03 1.705247E+01 + 2.050004E+01 2 4 1.474168E+04 5.796666E+01 + 2.050004E+01 3 3 2.202838E+03 1.902937E+02 + 2.050004E+01 4 2 1.475862E+04 5.817687E+01 + 2.050004E+01 4 4 2.713673E+05 1.977805E+02 + 2.050004E+01 5 1 -1.040812E+04 1.367334E+02 + 2.050004E+01 5 5 8.271939E+05 1.270525E+03 + 2.050004E+01 6 6 9.178493E+05 8.307088E+01 + 2.060004E+01 1 1 2.042954E+03 1.456914E+01 + 2.060004E+01 1 5 -1.038892E+04 1.356651E+02 + 2.060004E+01 2 2 2.322754E+03 1.682451E+01 + 2.060004E+01 2 4 1.473921E+04 5.715059E+01 + 2.060004E+01 3 3 2.203731E+03 1.905823E+02 + 2.060004E+01 4 2 1.475616E+04 5.735726E+01 + 2.060004E+01 4 4 2.713563E+05 1.948603E+02 + 2.060004E+01 5 1 -1.040740E+04 1.352437E+02 + 2.060004E+01 5 5 8.271967E+05 1.259360E+03 + 2.060004E+01 6 6 9.177097E+05 8.102791E+01 + 2.070004E+01 1 1 2.042534E+03 1.438127E+01 + 2.070004E+01 1 5 -1.038830E+04 1.341935E+02 + 2.070004E+01 2 2 2.322198E+03 1.660144E+01 + 2.070004E+01 2 4 1.473680E+04 5.635143E+01 + 2.070004E+01 3 3 2.204645E+03 1.908608E+02 + 2.070004E+01 4 2 1.475372E+04 5.655698E+01 + 2.070004E+01 4 4 2.713456E+05 1.919953E+02 + 2.070004E+01 5 1 -1.040679E+04 1.337789E+02 + 2.070004E+01 5 5 8.271989E+05 1.248252E+03 + 2.070004E+01 6 6 9.175752E+05 7.903664E+01 + 2.080004E+01 1 1 2.042128E+03 1.419732E+01 + 2.080004E+01 1 5 -1.038767E+04 1.327458E+02 + 2.080004E+01 2 2 2.321642E+03 1.638292E+01 + 2.080004E+01 2 4 1.473439E+04 5.556999E+01 + 2.080004E+01 3 3 2.205545E+03 1.911388E+02 + 2.080004E+01 4 2 1.475132E+04 5.577240E+01 + 2.080004E+01 4 4 2.713351E+05 1.891891E+02 + 2.080004E+01 5 1 -1.040618E+04 1.323369E+02 + 2.080004E+01 5 5 8.272017E+05 1.237373E+03 + 2.080004E+01 6 6 9.174412E+05 7.712577E+01 + 2.090004E+01 1 1 2.041725E+03 1.401705E+01 + 2.090004E+01 1 5 -1.038704E+04 1.313200E+02 + 2.090004E+01 2 2 2.321099E+03 1.616871E+01 + 2.090004E+01 2 4 1.473205E+04 5.480648E+01 + 2.090004E+01 3 3 2.206437E+03 1.914103E+02 + 2.090004E+01 4 2 1.474894E+04 5.500297E+01 + 2.090004E+01 4 4 2.713241E+05 1.864643E+02 + 2.090004E+01 5 1 -1.040560E+04 1.309183E+02 + 2.090004E+01 5 5 8.272052E+05 1.226451E+03 + 2.090004E+01 6 6 9.173101E+05 7.527367E+01 + 2.100004E+01 1 1 2.041327E+03 1.384010E+01 + 2.100004E+01 1 5 -1.038649E+04 1.299190E+02 + 2.100004E+01 2 2 2.320566E+03 1.595914E+01 + 2.100004E+01 2 4 1.472971E+04 5.405708E+01 + 2.100004E+01 3 3 2.207311E+03 1.916773E+02 + 2.100004E+01 4 2 1.474664E+04 5.425408E+01 + 2.100004E+01 4 4 2.713145E+05 1.837754E+02 + 2.100004E+01 5 1 -1.040490E+04 1.295189E+02 + 2.100004E+01 5 5 8.272031E+05 1.215755E+03 + 2.100004E+01 6 6 9.171781E+05 7.347575E+01 + 2.110004E+01 1 1 2.040935E+03 1.366674E+01 + 2.110004E+01 1 5 -1.038594E+04 1.285374E+02 + 2.110004E+01 2 2 2.320041E+03 1.575354E+01 + 2.110004E+01 2 4 1.472747E+04 5.332546E+01 + 2.110004E+01 3 3 2.208215E+03 1.919347E+02 + 2.110004E+01 4 2 1.474433E+04 5.351843E+01 + 2.110004E+01 4 4 2.713036E+05 1.811644E+02 + 2.110004E+01 5 1 -1.040444E+04 1.281440E+02 + 2.110004E+01 5 5 8.272006E+05 1.205271E+03 + 2.110004E+01 6 6 9.170503E+05 7.173104E+01 + 2.120004E+01 1 1 2.040545E+03 1.349668E+01 + 2.120004E+01 1 5 -1.038537E+04 1.271811E+02 + 2.120004E+01 2 2 2.319518E+03 1.555222E+01 + 2.120004E+01 2 4 1.472518E+04 5.260789E+01 + 2.120004E+01 3 3 2.209068E+03 1.921973E+02 + 2.120004E+01 4 2 1.474211E+04 5.279823E+01 + 2.120004E+01 4 4 2.712929E+05 1.785933E+02 + 2.120004E+01 5 1 -1.040375E+04 1.267931E+02 + 2.120004E+01 5 5 8.272009E+05 1.194779E+03 + 2.120004E+01 6 6 9.169239E+05 7.004704E+01 + 2.130005E+01 1 1 2.040163E+03 1.333006E+01 + 2.130005E+01 1 5 -1.038483E+04 1.258438E+02 + 2.130005E+01 2 2 2.319005E+03 1.535498E+01 + 2.130005E+01 2 4 1.472300E+04 5.190788E+01 + 2.130005E+01 3 3 2.209932E+03 1.924512E+02 + 2.130005E+01 4 2 1.473989E+04 5.209476E+01 + 2.130005E+01 4 4 2.712835E+05 1.761176E+02 + 2.130005E+01 5 1 -1.040319E+04 1.254624E+02 + 2.130005E+01 5 5 8.271999E+05 1.184527E+03 + 2.130005E+01 6 6 9.168002E+05 6.840921E+01 + 2.140005E+01 1 1 2.039790E+03 1.316657E+01 + 2.140005E+01 1 5 -1.038429E+04 1.245276E+02 + 2.140005E+01 2 2 2.318509E+03 1.516140E+01 + 2.140005E+01 2 4 1.472081E+04 5.122044E+01 + 2.140005E+01 3 3 2.210812E+03 1.927012E+02 + 2.140005E+01 4 2 1.473769E+04 5.140326E+01 + 2.140005E+01 4 4 2.712734E+05 1.736811E+02 + 2.140005E+01 5 1 -1.040272E+04 1.241534E+02 + 2.140005E+01 5 5 8.271966E+05 1.174315E+03 + 2.140005E+01 6 6 9.166779E+05 6.679897E+01 + 2.150005E+01 1 1 2.039421E+03 1.300604E+01 + 2.150005E+01 1 5 -1.038382E+04 1.232327E+02 + 2.150005E+01 2 2 2.318014E+03 1.497173E+01 + 2.150005E+01 2 4 1.471868E+04 5.054661E+01 + 2.150005E+01 3 3 2.211674E+03 1.929450E+02 + 2.150005E+01 4 2 1.473557E+04 5.072710E+01 + 2.150005E+01 4 4 2.712644E+05 1.712669E+02 + 2.150005E+01 5 1 -1.040220E+04 1.228634E+02 + 2.150005E+01 5 5 8.271976E+05 1.164182E+03 + 2.150005E+01 6 6 9.165571E+05 6.528036E+01 + 2.160005E+01 1 1 2.039057E+03 1.284880E+01 + 2.160005E+01 1 5 -1.038330E+04 1.219590E+02 + 2.160005E+01 2 2 2.317519E+03 1.478582E+01 + 2.160005E+01 2 4 1.471653E+04 4.988591E+01 + 2.160005E+01 3 3 2.212511E+03 1.931867E+02 + 2.160005E+01 4 2 1.473342E+04 5.006529E+01 + 2.160005E+01 4 4 2.712549E+05 1.689041E+02 + 2.160005E+01 5 1 -1.040170E+04 1.215938E+02 + 2.160005E+01 5 5 8.272002E+05 1.154037E+03 + 2.160005E+01 6 6 9.164384E+05 6.376656E+01 + 2.170005E+01 1 1 2.038695E+03 1.269431E+01 + 2.170005E+01 1 5 -1.038282E+04 1.207042E+02 + 2.170005E+01 2 2 2.317043E+03 1.460325E+01 + 2.170005E+01 2 4 1.471450E+04 4.924081E+01 + 2.170005E+01 3 3 2.213365E+03 1.934295E+02 + 2.170005E+01 4 2 1.473132E+04 4.941448E+01 + 2.170005E+01 4 4 2.712455E+05 1.666196E+02 + 2.170005E+01 5 1 -1.040119E+04 1.203417E+02 + 2.170005E+01 5 5 8.271990E+05 1.144272E+03 + 2.170005E+01 6 6 9.163224E+05 6.229789E+01 + 2.180005E+01 1 1 2.038337E+03 1.254278E+01 + 2.180005E+01 1 5 -1.038239E+04 1.194680E+02 + 2.180005E+01 2 2 2.316567E+03 1.442472E+01 + 2.180005E+01 2 4 1.471242E+04 4.860685E+01 + 2.180005E+01 3 3 2.214200E+03 1.936623E+02 + 2.180005E+01 4 2 1.472929E+04 4.878252E+01 + 2.180005E+01 4 4 2.712359E+05 1.643719E+02 + 2.180005E+01 5 1 -1.040068E+04 1.191137E+02 + 2.180005E+01 5 5 8.271991E+05 1.134515E+03 + 2.180005E+01 6 6 9.162071E+05 6.089412E+01 + 2.190005E+01 1 1 2.037989E+03 1.239400E+01 + 2.190005E+01 1 5 -1.038188E+04 1.182522E+02 + 2.190005E+01 2 2 2.316103E+03 1.424912E+01 + 2.190005E+01 2 4 1.471041E+04 4.798604E+01 + 2.190005E+01 3 3 2.215061E+03 1.938943E+02 + 2.190005E+01 4 2 1.472726E+04 4.815831E+01 + 2.190005E+01 4 4 2.712270E+05 1.621767E+02 + 2.190005E+01 5 1 -1.040027E+04 1.179015E+02 + 2.190005E+01 5 5 8.271982E+05 1.124841E+03 + 2.190005E+01 6 6 9.160946E+05 5.951931E+01 + 2.200005E+01 1 1 2.037649E+03 1.224808E+01 + 2.200005E+01 1 5 -1.038147E+04 1.170528E+02 + 2.200005E+01 2 2 2.315639E+03 1.407682E+01 + 2.200005E+01 2 4 1.470844E+04 4.737843E+01 + 2.200005E+01 3 3 2.215873E+03 1.941264E+02 + 2.200005E+01 4 2 1.472529E+04 4.754744E+01 + 2.200005E+01 4 4 2.712183E+05 1.600185E+02 + 2.200005E+01 5 1 -1.039992E+04 1.167101E+02 + 2.200005E+01 5 5 8.271976E+05 1.115430E+03 + 2.200005E+01 6 6 9.159816E+05 5.819202E+01 + 2.210005E+01 1 1 2.037308E+03 1.210470E+01 + 2.210005E+01 1 5 -1.038102E+04 1.158736E+02 + 2.210005E+01 2 2 2.315182E+03 1.390803E+01 + 2.210005E+01 2 4 1.470646E+04 4.678249E+01 + 2.210005E+01 3 3 2.216712E+03 1.943450E+02 + 2.210005E+01 4 2 1.472329E+04 4.695055E+01 + 2.210005E+01 4 4 2.712093E+05 1.579354E+02 + 2.210005E+01 5 1 -1.039939E+04 1.155343E+02 + 2.210005E+01 5 5 8.271957E+05 1.106022E+03 + 2.210005E+01 6 6 9.158721E+05 5.688284E+01 + 2.220005E+01 1 1 2.036969E+03 1.196400E+01 + 2.220005E+01 1 5 -1.038063E+04 1.147114E+02 + 2.220005E+01 2 2 2.314739E+03 1.374230E+01 + 2.220005E+01 2 4 1.470454E+04 4.619685E+01 + 2.220005E+01 3 3 2.217524E+03 1.945665E+02 + 2.220005E+01 4 2 1.472136E+04 4.636358E+01 + 2.220005E+01 4 4 2.712004E+05 1.558597E+02 + 2.220005E+01 5 1 -1.039897E+04 1.143771E+02 + 2.220005E+01 5 5 8.271941E+05 1.096781E+03 + 2.220005E+01 6 6 9.157641E+05 5.563345E+01 + 2.230005E+01 1 1 2.036637E+03 1.182575E+01 + 2.230005E+01 1 5 -1.038026E+04 1.135683E+02 + 2.230005E+01 2 2 2.314296E+03 1.357960E+01 + 2.230005E+01 2 4 1.470264E+04 4.562354E+01 + 2.230005E+01 3 3 2.218334E+03 1.947845E+02 + 2.230005E+01 4 2 1.471949E+04 4.578807E+01 + 2.230005E+01 4 4 2.711918E+05 1.538298E+02 + 2.230005E+01 5 1 -1.039849E+04 1.132363E+02 + 2.230005E+01 5 5 8.271973E+05 1.087464E+03 + 2.230005E+01 6 6 9.156574E+05 5.442185E+01 + 2.240005E+01 1 1 2.036311E+03 1.168988E+01 + 2.240005E+01 1 5 -1.037981E+04 1.124409E+02 + 2.240005E+01 2 2 2.313863E+03 1.341987E+01 + 2.240005E+01 2 4 1.470077E+04 4.506102E+01 + 2.240005E+01 3 3 2.219161E+03 1.949962E+02 + 2.240005E+01 4 2 1.471759E+04 4.522205E+01 + 2.240005E+01 4 4 2.711828E+05 1.518387E+02 + 2.240005E+01 5 1 -1.039809E+04 1.121140E+02 + 2.240005E+01 5 5 8.271967E+05 1.078192E+03 + 2.240005E+01 6 6 9.155534E+05 5.319827E+01 + 2.250005E+01 1 1 2.035988E+03 1.155664E+01 + 2.250005E+01 1 5 -1.037943E+04 1.113303E+02 + 2.250005E+01 2 2 2.313435E+03 1.326312E+01 + 2.250005E+01 2 4 1.469893E+04 4.451097E+01 + 2.250005E+01 3 3 2.219965E+03 1.952088E+02 + 2.250005E+01 4 2 1.471570E+04 4.466977E+01 + 2.250005E+01 4 4 2.711756E+05 1.499245E+02 + 2.250005E+01 5 1 -1.039769E+04 1.110101E+02 + 2.250005E+01 5 5 8.271958E+05 1.069337E+03 + 2.250005E+01 6 6 9.154492E+05 5.207079E+01 + 2.260005E+01 1 1 2.035668E+03 1.142559E+01 + 2.260005E+01 1 5 -1.037899E+04 1.102374E+02 + 2.260005E+01 2 2 2.313012E+03 1.310918E+01 + 2.260005E+01 2 4 1.469711E+04 4.396895E+01 + 2.260005E+01 3 3 2.220759E+03 1.954165E+02 + 2.260005E+01 4 2 1.471388E+04 4.412612E+01 + 2.260005E+01 4 4 2.711669E+05 1.480203E+02 + 2.260005E+01 5 1 -1.039733E+04 1.099194E+02 + 2.260005E+01 5 5 8.271949E+05 1.060400E+03 + 2.260005E+01 6 6 9.153475E+05 5.092782E+01 + 2.270005E+01 1 1 2.035357E+03 1.129714E+01 + 2.270005E+01 1 5 -1.037867E+04 1.091581E+02 + 2.270005E+01 2 2 2.312599E+03 1.295820E+01 + 2.270005E+01 2 4 1.469534E+04 4.343785E+01 + 2.270005E+01 3 3 2.221554E+03 1.956181E+02 + 2.270005E+01 4 2 1.471213E+04 4.359325E+01 + 2.270005E+01 4 4 2.711593E+05 1.461311E+02 + 2.270005E+01 5 1 -1.039698E+04 1.088451E+02 + 2.270005E+01 5 5 8.271948E+05 1.051773E+03 + 2.270005E+01 6 6 9.152474E+05 4.985772E+01 + 2.280005E+01 1 1 2.035051E+03 1.117065E+01 + 2.280005E+01 1 5 -1.037832E+04 1.080965E+02 + 2.280005E+01 2 2 2.312185E+03 1.280977E+01 + 2.280005E+01 2 4 1.469355E+04 4.291696E+01 + 2.280005E+01 3 3 2.222362E+03 1.958172E+02 + 2.280005E+01 4 2 1.471033E+04 4.307096E+01 + 2.280005E+01 4 4 2.711515E+05 1.443114E+02 + 2.280005E+01 5 1 -1.039657E+04 1.077888E+02 + 2.280005E+01 5 5 8.271949E+05 1.042962E+03 + 2.280005E+01 6 6 9.151476E+05 4.881584E+01 + 2.290005E+01 1 1 2.034748E+03 1.104653E+01 + 2.290005E+01 1 5 -1.037800E+04 1.070498E+02 + 2.290005E+01 2 2 2.311784E+03 1.266404E+01 + 2.290005E+01 2 4 1.469180E+04 4.240533E+01 + 2.290005E+01 3 3 2.223147E+03 1.960163E+02 + 2.290005E+01 4 2 1.470862E+04 4.255819E+01 + 2.290005E+01 4 4 2.711436E+05 1.425061E+02 + 2.290005E+01 5 1 -1.039627E+04 1.067465E+02 + 2.290005E+01 5 5 8.271956E+05 1.034468E+03 + 2.290005E+01 6 6 9.150489E+05 4.774730E+01 + 2.300005E+01 1 1 2.034443E+03 1.092434E+01 + 2.300005E+01 1 5 -1.037765E+04 1.060190E+02 + 2.300005E+01 2 2 2.311383E+03 1.252069E+01 + 2.300005E+01 2 4 1.469011E+04 4.190488E+01 + 2.300005E+01 3 3 2.223921E+03 1.962105E+02 + 2.300005E+01 4 2 1.470688E+04 4.205219E+01 + 2.300005E+01 4 4 2.711359E+05 1.407608E+02 + 2.300005E+01 5 1 -1.039589E+04 1.057175E+02 + 2.300005E+01 5 5 8.271911E+05 1.025958E+03 + 2.300005E+01 6 6 9.149519E+05 4.675128E+01 + 2.310005E+01 1 1 2.034148E+03 1.080445E+01 + 2.310005E+01 1 5 -1.037733E+04 1.050034E+02 + 2.310005E+01 2 2 2.310981E+03 1.237996E+01 + 2.310005E+01 2 4 1.468841E+04 4.141182E+01 + 2.310005E+01 3 3 2.224703E+03 1.964054E+02 + 2.310005E+01 4 2 1.470514E+04 4.155864E+01 + 2.310005E+01 4 4 2.711282E+05 1.390386E+02 + 2.310005E+01 5 1 -1.039559E+04 1.047043E+02 + 2.310005E+01 5 5 8.271901E+05 1.017580E+03 + 2.310005E+01 6 6 9.148575E+05 4.576733E+01 + 2.320005E+01 1 1 2.033849E+03 1.068652E+01 + 2.320005E+01 1 5 -1.037704E+04 1.040022E+02 + 2.320005E+01 2 2 2.310599E+03 1.224202E+01 + 2.320005E+01 2 4 1.468675E+04 4.092871E+01 + 2.320005E+01 3 3 2.225478E+03 1.965968E+02 + 2.320005E+01 4 2 1.470356E+04 4.107518E+01 + 2.320005E+01 4 4 2.711210E+05 1.373338E+02 + 2.320005E+01 5 1 -1.039518E+04 1.037093E+02 + 2.320005E+01 5 5 8.271895E+05 1.009331E+03 + 2.320005E+01 6 6 9.147649E+05 4.482122E+01 + 2.330005E+01 1 1 2.033559E+03 1.057042E+01 + 2.330005E+01 1 5 -1.037676E+04 1.030166E+02 + 2.330005E+01 2 2 2.310214E+03 1.210602E+01 + 2.330005E+01 2 4 1.468507E+04 4.045424E+01 + 2.330005E+01 3 3 2.226240E+03 1.967788E+02 + 2.330005E+01 4 2 1.470188E+04 4.059764E+01 + 2.330005E+01 4 4 2.711132E+05 1.356642E+02 + 2.330005E+01 5 1 -1.039495E+04 1.027238E+02 + 2.330005E+01 5 5 8.271878E+05 1.001008E+03 + 2.330005E+01 6 6 9.146716E+05 4.388947E+01 + 2.340005E+01 1 1 2.033273E+03 1.045655E+01 + 2.340005E+01 1 5 -1.037643E+04 1.020423E+02 + 2.340005E+01 2 2 2.309837E+03 1.197268E+01 + 2.340005E+01 2 4 1.468345E+04 3.998836E+01 + 2.340005E+01 3 3 2.227008E+03 1.969655E+02 + 2.340005E+01 4 2 1.470022E+04 4.013037E+01 + 2.340005E+01 4 4 2.711061E+05 1.340341E+02 + 2.340005E+01 5 1 -1.039461E+04 1.017547E+02 + 2.340005E+01 5 5 8.271899E+05 9.931252E+02 + 2.340005E+01 6 6 9.145817E+05 4.299681E+01 + 2.350005E+01 1 1 2.032994E+03 1.034446E+01 + 2.350005E+01 1 5 -1.037612E+04 1.010847E+02 + 2.350005E+01 2 2 2.309460E+03 1.184148E+01 + 2.350005E+01 2 4 1.468187E+04 3.953109E+01 + 2.350005E+01 3 3 2.227773E+03 1.971446E+02 + 2.350005E+01 4 2 1.469865E+04 3.967077E+01 + 2.350005E+01 4 4 2.710999E+05 1.324319E+02 + 2.350005E+01 5 1 -1.039433E+04 1.007999E+02 + 2.350005E+01 5 5 8.271886E+05 9.849613E+02 + 2.350005E+01 6 6 9.144915E+05 4.211162E+01 + 2.360005E+01 1 1 2.032715E+03 1.023431E+01 + 2.360005E+01 1 5 -1.037586E+04 1.001379E+02 + 2.360005E+01 2 2 2.309094E+03 1.171263E+01 + 2.360005E+01 2 4 1.468028E+04 3.908125E+01 + 2.360005E+01 3 3 2.228521E+03 1.973266E+02 + 2.360005E+01 4 2 1.469707E+04 3.922056E+01 + 2.360005E+01 4 4 2.710927E+05 1.308755E+02 + 2.360005E+01 5 1 -1.039407E+04 9.985751E+01 + 2.360005E+01 5 5 8.271896E+05 9.771481E+02 + 2.360005E+01 6 6 9.144030E+05 4.124708E+01 + 2.370005E+01 1 1 2.032438E+03 1.012587E+01 + 2.370005E+01 1 5 -1.037555E+04 9.920699E+01 + 2.370005E+01 2 2 2.308731E+03 1.158590E+01 + 2.370005E+01 2 4 1.467874E+04 3.863985E+01 + 2.370005E+01 3 3 2.229279E+03 1.975036E+02 + 2.370005E+01 4 2 1.469549E+04 3.877715E+01 + 2.370005E+01 4 4 2.710864E+05 1.293232E+02 + 2.370005E+01 5 1 -1.039373E+04 9.892930E+01 + 2.370005E+01 5 5 8.271887E+05 9.692566E+02 + 2.370005E+01 6 6 9.143159E+05 4.041645E+01 + 2.380005E+01 1 1 2.032171E+03 1.001928E+01 + 2.380005E+01 1 5 -1.037528E+04 9.828754E+01 + 2.380005E+01 2 2 2.308376E+03 1.146121E+01 + 2.380005E+01 2 4 1.467721E+04 3.820537E+01 + 2.380005E+01 3 3 2.230031E+03 1.976775E+02 + 2.380005E+01 4 2 1.469398E+04 3.834073E+01 + 2.380005E+01 4 4 2.710787E+05 1.278101E+02 + 2.380005E+01 5 1 -1.039351E+04 9.801326E+01 + 2.380005E+01 5 5 8.271858E+05 9.615890E+02 + 2.380005E+01 6 6 9.142285E+05 3.960041E+01 + 2.390005E+01 1 1 2.031903E+03 9.914342E+00 + 2.390005E+01 1 5 -1.037502E+04 9.738152E+01 + 2.390005E+01 2 2 2.308018E+03 1.133885E+01 + 2.390005E+01 2 4 1.467568E+04 3.777906E+01 + 2.390005E+01 3 3 2.230778E+03 1.978476E+02 + 2.390005E+01 4 2 1.469244E+04 3.791449E+01 + 2.390005E+01 4 4 2.710722E+05 1.263223E+02 + 2.390005E+01 5 1 -1.039319E+04 9.711163E+01 + 2.390005E+01 5 5 8.271860E+05 9.539293E+02 + 2.390005E+01 6 6 9.141447E+05 3.882231E+01 + 2.400006E+01 1 1 2.031634E+03 9.811126E+00 + 2.400006E+01 1 5 -1.037478E+04 9.648814E+01 + 2.400006E+01 2 2 2.307672E+03 1.121838E+01 + 2.400006E+01 2 4 1.467422E+04 3.736005E+01 + 2.400006E+01 3 3 2.231508E+03 1.980149E+02 + 2.400006E+01 4 2 1.469097E+04 3.749390E+01 + 2.400006E+01 4 4 2.710653E+05 1.248615E+02 + 2.400006E+01 5 1 -1.039290E+04 9.622011E+01 + 2.400006E+01 5 5 8.271822E+05 9.463295E+02 + 2.400006E+01 6 6 9.140606E+05 3.803633E+01 + 2.410006E+01 1 1 2.031377E+03 9.709634E+00 + 2.410006E+01 1 5 -1.037453E+04 9.560735E+01 + 2.410006E+01 2 2 2.307326E+03 1.109978E+01 + 2.410006E+01 2 4 1.467273E+04 3.694786E+01 + 2.410006E+01 3 3 2.232253E+03 1.981839E+02 + 2.410006E+01 4 2 1.468944E+04 3.707983E+01 + 2.410006E+01 4 4 2.710592E+05 1.234255E+02 + 2.410006E+01 5 1 -1.039270E+04 9.534648E+01 + 2.410006E+01 5 5 8.271782E+05 9.387194E+02 + 2.410006E+01 6 6 9.139781E+05 3.730908E+01 + 2.420006E+01 1 1 2.031112E+03 9.609752E+00 + 2.420006E+01 1 5 -1.037431E+04 9.473851E+01 + 2.420006E+01 2 2 2.306985E+03 1.098335E+01 + 2.420006E+01 2 4 1.467128E+04 3.654422E+01 + 2.420006E+01 3 3 2.232986E+03 1.983488E+02 + 2.420006E+01 4 2 1.468798E+04 3.667476E+01 + 2.420006E+01 4 4 2.710523E+05 1.220480E+02 + 2.420006E+01 5 1 -1.039244E+04 9.447757E+01 + 2.420006E+01 5 5 8.271759E+05 9.313820E+02 + 2.420006E+01 6 6 9.138958E+05 3.654898E+01 + 2.430006E+01 1 1 2.030863E+03 9.511484E+00 + 2.430006E+01 1 5 -1.037415E+04 9.388129E+01 + 2.430006E+01 2 2 2.306656E+03 1.086845E+01 + 2.430006E+01 2 4 1.466984E+04 3.614560E+01 + 2.430006E+01 3 3 2.233718E+03 1.985104E+02 + 2.430006E+01 4 2 1.468658E+04 3.627436E+01 + 2.430006E+01 4 4 2.710465E+05 1.206483E+02 + 2.430006E+01 5 1 -1.039221E+04 9.362186E+01 + 2.430006E+01 5 5 8.271740E+05 9.240085E+02 + 2.430006E+01 6 6 9.138143E+05 3.586105E+01 + 2.440006E+01 1 1 2.030609E+03 9.414827E+00 + 2.440006E+01 1 5 -1.037391E+04 9.303546E+01 + 2.440006E+01 2 2 2.306322E+03 1.075568E+01 + 2.440006E+01 2 4 1.466841E+04 3.575534E+01 + 2.440006E+01 3 3 2.234436E+03 1.986674E+02 + 2.440006E+01 4 2 1.468513E+04 3.588192E+01 + 2.440006E+01 4 4 2.710398E+05 1.192928E+02 + 2.440006E+01 5 1 -1.039196E+04 9.278113E+01 + 2.440006E+01 5 5 8.271754E+05 9.168135E+02 + 2.440006E+01 6 6 9.137352E+05 3.514493E+01 + 2.450006E+01 1 1 2.030361E+03 9.319529E+00 + 2.450006E+01 1 5 -1.037363E+04 9.220276E+01 + 2.450006E+01 2 2 2.305993E+03 1.064490E+01 + 2.450006E+01 2 4 1.466702E+04 3.537190E+01 + 2.450006E+01 3 3 2.235165E+03 1.988278E+02 + 2.450006E+01 4 2 1.468375E+04 3.549681E+01 + 2.450006E+01 4 4 2.710335E+05 1.179643E+02 + 2.450006E+01 5 1 -1.039174E+04 9.194997E+01 + 2.450006E+01 5 5 8.271759E+05 9.095566E+02 + 2.450006E+01 6 6 9.136572E+05 3.445596E+01 + 2.460006E+01 1 1 2.030117E+03 9.225826E+00 + 2.460006E+01 1 5 -1.037340E+04 9.138032E+01 + 2.460006E+01 2 2 2.305668E+03 1.053581E+01 + 2.460006E+01 2 4 1.466565E+04 3.499251E+01 + 2.460006E+01 3 3 2.235873E+03 1.989822E+02 + 2.460006E+01 4 2 1.468234E+04 3.511721E+01 + 2.460006E+01 4 4 2.710272E+05 1.166416E+02 + 2.460006E+01 5 1 -1.039152E+04 9.113002E+01 + 2.460006E+01 5 5 8.271744E+05 9.025378E+02 + 2.460006E+01 6 6 9.135802E+05 3.381790E+01 + 2.470006E+01 1 1 2.029873E+03 9.133606E+00 + 2.470006E+01 1 5 -1.037318E+04 9.056837E+01 + 2.470006E+01 2 2 2.305353E+03 1.042826E+01 + 2.470006E+01 2 4 1.466428E+04 3.462143E+01 + 2.470006E+01 3 3 2.236587E+03 1.991355E+02 + 2.470006E+01 4 2 1.468099E+04 3.474391E+01 + 2.470006E+01 4 4 2.710212E+05 1.153483E+02 + 2.470006E+01 5 1 -1.039129E+04 9.032232E+01 + 2.470006E+01 5 5 8.271716E+05 8.955177E+02 + 2.470006E+01 6 6 9.135034E+05 3.313776E+01 + 2.480006E+01 1 1 2.029630E+03 9.042878E+00 + 2.480006E+01 1 5 -1.037298E+04 8.976824E+01 + 2.480006E+01 2 2 2.305035E+03 1.032270E+01 + 2.480006E+01 2 4 1.466295E+04 3.425539E+01 + 2.480006E+01 3 3 2.237302E+03 1.992867E+02 + 2.480006E+01 4 2 1.467967E+04 3.437832E+01 + 2.480006E+01 4 4 2.710157E+05 1.140821E+02 + 2.480006E+01 5 1 -1.039106E+04 8.952290E+01 + 2.480006E+01 5 5 8.271679E+05 8.886054E+02 + 2.480006E+01 6 6 9.134277E+05 3.253455E+01 + 2.490006E+01 1 1 2.029394E+03 8.953331E+00 + 2.490006E+01 1 5 -1.037281E+04 8.897883E+01 + 2.490006E+01 2 2 2.304724E+03 1.021857E+01 + 2.490006E+01 2 4 1.466162E+04 3.389667E+01 + 2.490006E+01 3 3 2.237998E+03 1.994348E+02 + 2.490006E+01 4 2 1.467831E+04 3.401699E+01 + 2.490006E+01 4 4 2.710087E+05 1.128555E+02 + 2.490006E+01 5 1 -1.039082E+04 8.874215E+01 + 2.490006E+01 5 5 8.271696E+05 8.818109E+02 + 2.490006E+01 6 6 9.133528E+05 3.192215E+01 + 2.500006E+01 1 1 2.029163E+03 8.865359E+00 + 2.500006E+01 1 5 -1.037263E+04 8.819851E+01 + 2.500006E+01 2 2 2.304419E+03 1.011612E+01 + 2.500006E+01 2 4 1.466032E+04 3.354252E+01 + 2.500006E+01 3 3 2.238706E+03 1.995865E+02 + 2.500006E+01 4 2 1.467700E+04 3.366219E+01 + 2.500006E+01 4 4 2.710033E+05 1.116153E+02 + 2.500006E+01 5 1 -1.039066E+04 8.796290E+01 + 2.500006E+01 5 5 8.271669E+05 8.751105E+02 + 2.500006E+01 6 6 9.132793E+05 3.132604E+01 + 2.510006E+01 1 1 2.028934E+03 8.778656E+00 + 2.510006E+01 1 5 -1.037237E+04 8.743025E+01 + 2.510006E+01 2 2 2.304118E+03 1.001532E+01 + 2.510006E+01 2 4 1.465900E+04 3.319426E+01 + 2.510006E+01 3 3 2.239400E+03 1.997308E+02 + 2.510006E+01 4 2 1.467571E+04 3.331283E+01 + 2.510006E+01 4 4 2.709972E+05 1.104066E+02 + 2.510006E+01 5 1 -1.039050E+04 8.719435E+01 + 2.510006E+01 5 5 8.271693E+05 8.684067E+02 + 2.510006E+01 6 6 9.132068E+05 3.071132E+01 + 2.520006E+01 1 1 2.028703E+03 8.693321E+00 + 2.520006E+01 1 5 -1.037219E+04 8.667213E+01 + 2.520006E+01 2 2 2.303819E+03 9.916179E+00 + 2.520006E+01 2 4 1.465776E+04 3.285224E+01 + 2.520006E+01 3 3 2.240094E+03 1.998740E+02 + 2.520006E+01 4 2 1.467443E+04 3.297049E+01 + 2.520006E+01 4 4 2.709916E+05 1.092366E+02 + 2.520006E+01 5 1 -1.039028E+04 8.643800E+01 + 2.520006E+01 5 5 8.271694E+05 8.618149E+02 + 2.520006E+01 6 6 9.131358E+05 3.016357E+01 + 2.530006E+01 1 1 2.028479E+03 8.609179E+00 + 2.530006E+01 1 5 -1.037204E+04 8.592427E+01 + 2.530006E+01 2 2 2.303526E+03 9.818414E+00 + 2.530006E+01 2 4 1.465649E+04 3.251585E+01 + 2.530006E+01 3 3 2.240780E+03 2.000163E+02 + 2.530006E+01 4 2 1.467319E+04 3.263248E+01 + 2.530006E+01 4 4 2.709859E+05 1.080735E+02 + 2.530006E+01 5 1 -1.039008E+04 8.569388E+01 + 2.530006E+01 5 5 8.271659E+05 8.552576E+02 + 2.530006E+01 6 6 9.130642E+05 2.958306E+01 + 2.540006E+01 1 1 2.028260E+03 8.526321E+00 + 2.540006E+01 1 5 -1.037186E+04 8.518460E+01 + 2.540006E+01 2 2 2.303233E+03 9.722049E+00 + 2.540006E+01 2 4 1.465524E+04 3.218387E+01 + 2.540006E+01 3 3 2.241477E+03 2.001544E+02 + 2.540006E+01 4 2 1.467192E+04 3.229755E+01 + 2.540006E+01 4 4 2.709805E+05 1.069268E+02 + 2.540006E+01 5 1 -1.038993E+04 8.495767E+01 + 2.540006E+01 5 5 8.271612E+05 8.487145E+02 + 2.540006E+01 6 6 9.129948E+05 2.904381E+01 + 2.550006E+01 1 1 2.028036E+03 8.444819E+00 + 2.550006E+01 1 5 -1.037168E+04 8.445553E+01 + 2.550006E+01 2 2 2.302943E+03 9.627226E+00 + 2.550006E+01 2 4 1.465403E+04 3.185727E+01 + 2.550006E+01 3 3 2.242153E+03 2.002938E+02 + 2.550006E+01 4 2 1.467067E+04 3.196987E+01 + 2.550006E+01 4 4 2.709756E+05 1.058044E+02 + 2.550006E+01 5 1 -1.038976E+04 8.422741E+01 + 2.550006E+01 5 5 8.271586E+05 8.422817E+02 + 2.550006E+01 6 6 9.129251E+05 2.850357E+01 + 2.560006E+01 1 1 2.027823E+03 8.364308E+00 + 2.560006E+01 1 5 -1.037155E+04 8.373588E+01 + 2.560006E+01 2 2 2.302657E+03 9.533985E+00 + 2.560006E+01 2 4 1.465281E+04 3.153700E+01 + 2.560006E+01 3 3 2.242827E+03 2.004348E+02 + 2.560006E+01 4 2 1.466947E+04 3.164940E+01 + 2.560006E+01 4 4 2.709701E+05 1.047038E+02 + 2.560006E+01 5 1 -1.038962E+04 8.351262E+01 + 2.560006E+01 5 5 8.271565E+05 8.359814E+02 + 2.560006E+01 6 6 9.128584E+05 2.799725E+01 + 2.570006E+01 1 1 2.027606E+03 8.285014E+00 + 2.570006E+01 1 5 -1.037137E+04 8.302389E+01 + 2.570006E+01 2 2 2.302380E+03 9.442121E+00 + 2.570006E+01 2 4 1.465162E+04 3.121981E+01 + 2.570006E+01 3 3 2.243504E+03 2.005645E+02 + 2.570006E+01 4 2 1.466828E+04 3.133272E+01 + 2.570006E+01 4 4 2.709648E+05 1.036158E+02 + 2.570006E+01 5 1 -1.038941E+04 8.280424E+01 + 2.570006E+01 5 5 8.271548E+05 8.298326E+02 + 2.570006E+01 6 6 9.127900E+05 2.749338E+01 + 2.580006E+01 1 1 2.027392E+03 8.206997E+00 + 2.580006E+01 1 5 -1.037125E+04 8.232254E+01 + 2.580006E+01 2 2 2.302102E+03 9.351472E+00 + 2.580006E+01 2 4 1.465043E+04 3.090963E+01 + 2.580006E+01 3 3 2.244165E+03 2.007012E+02 + 2.580006E+01 4 2 1.466709E+04 3.101912E+01 + 2.580006E+01 4 4 2.709602E+05 1.025484E+02 + 2.580006E+01 5 1 -1.038929E+04 8.210590E+01 + 2.580006E+01 5 5 8.271551E+05 8.235336E+02 + 2.580006E+01 6 6 9.127228E+05 2.699221E+01 + 2.590006E+01 1 1 2.027182E+03 8.130158E+00 + 2.590006E+01 1 5 -1.037112E+04 8.162987E+01 + 2.590006E+01 2 2 2.301826E+03 9.262368E+00 + 2.590006E+01 2 4 1.464928E+04 3.060220E+01 + 2.590006E+01 3 3 2.244849E+03 2.008306E+02 + 2.590006E+01 4 2 1.466592E+04 3.071286E+01 + 2.590006E+01 4 4 2.709549E+05 1.014891E+02 + 2.590006E+01 5 1 -1.038912E+04 8.141292E+01 + 2.590006E+01 5 5 8.271537E+05 8.174359E+02 + 2.590006E+01 6 6 9.126582E+05 2.651291E+01 + 2.600006E+01 1 1 2.026976E+03 8.054261E+00 + 2.600006E+01 1 5 -1.037096E+04 8.094625E+01 + 2.600006E+01 2 2 2.301557E+03 9.174356E+00 + 2.600006E+01 2 4 1.464809E+04 3.030066E+01 + 2.600006E+01 3 3 2.245509E+03 2.009578E+02 + 2.600006E+01 4 2 1.466478E+04 3.040839E+01 + 2.600006E+01 4 4 2.709496E+05 1.004428E+02 + 2.600006E+01 5 1 -1.038898E+04 8.073370E+01 + 2.600006E+01 5 5 8.271520E+05 8.113566E+02 + 2.600006E+01 6 6 9.125938E+05 2.603255E+01 + 2.610006E+01 1 1 2.026770E+03 7.979511E+00 + 2.610006E+01 1 5 -1.037085E+04 8.027102E+01 + 2.610006E+01 2 2 2.301287E+03 9.087890E+00 + 2.610006E+01 2 4 1.464696E+04 3.000399E+01 + 2.610006E+01 3 3 2.246179E+03 2.010886E+02 + 2.610006E+01 4 2 1.466362E+04 3.011195E+01 + 2.610006E+01 4 4 2.709448E+05 9.942530E+01 + 2.610006E+01 5 1 -1.038877E+04 8.006023E+01 + 2.610006E+01 5 5 8.271528E+05 8.053268E+02 + 2.610006E+01 6 6 9.125300E+05 2.558108E+01 + 2.620006E+01 1 1 2.026568E+03 7.906063E+00 + 2.620006E+01 1 5 -1.037070E+04 7.960527E+01 + 2.620006E+01 2 2 2.301020E+03 9.002596E+00 + 2.620006E+01 2 4 1.464582E+04 2.971134E+01 + 2.620006E+01 3 3 2.246840E+03 2.012124E+02 + 2.620006E+01 4 2 1.466249E+04 2.982026E+01 + 2.620006E+01 4 4 2.709401E+05 9.841453E+01 + 2.620006E+01 5 1 -1.038868E+04 7.939495E+01 + 2.620006E+01 5 5 8.271547E+05 7.993817E+02 + 2.620006E+01 6 6 9.124662E+05 2.512825E+01 + 2.630006E+01 1 1 2.026369E+03 7.833481E+00 + 2.630006E+01 1 5 -1.037054E+04 7.894700E+01 + 2.630006E+01 2 2 2.300758E+03 8.918515E+00 + 2.630006E+01 2 4 1.464473E+04 2.942456E+01 + 2.630006E+01 3 3 2.247492E+03 2.013382E+02 + 2.630006E+01 4 2 1.466139E+04 2.953014E+01 + 2.630006E+01 4 4 2.709352E+05 9.743958E+01 + 2.630006E+01 5 1 -1.038856E+04 7.873937E+01 + 2.630006E+01 5 5 8.271514E+05 7.933781E+02 + 2.630006E+01 6 6 9.124036E+05 2.467591E+01 + 2.640006E+01 1 1 2.026170E+03 7.761918E+00 + 2.640006E+01 1 5 -1.037043E+04 7.829729E+01 + 2.640006E+01 2 2 2.300500E+03 8.835664E+00 + 2.640006E+01 2 4 1.464364E+04 2.913994E+01 + 2.640006E+01 3 3 2.248145E+03 2.014608E+02 + 2.640006E+01 4 2 1.466025E+04 2.924344E+01 + 2.640006E+01 4 4 2.709298E+05 9.645932E+01 + 2.640006E+01 5 1 -1.038839E+04 7.809048E+01 + 2.640006E+01 5 5 8.271487E+05 7.876584E+02 + 2.640006E+01 6 6 9.123422E+05 2.422641E+01 + 2.650006E+01 1 1 2.025971E+03 7.691275E+00 + 2.650006E+01 1 5 -1.037028E+04 7.765542E+01 + 2.650006E+01 2 2 2.300242E+03 8.754071E+00 + 2.650006E+01 2 4 1.464257E+04 2.886089E+01 + 2.650006E+01 3 3 2.248790E+03 2.015837E+02 + 2.650006E+01 4 2 1.465918E+04 2.896592E+01 + 2.650006E+01 4 4 2.709252E+05 9.550850E+01 + 2.650006E+01 5 1 -1.038830E+04 7.745103E+01 + 2.650006E+01 5 5 8.271478E+05 7.818662E+02 + 2.650006E+01 6 6 9.122811E+05 2.380852E+01 + 2.660007E+01 1 1 2.025781E+03 7.621777E+00 + 2.660007E+01 1 5 -1.037016E+04 7.702213E+01 + 2.660007E+01 2 2 2.299993E+03 8.673573E+00 + 2.660007E+01 2 4 1.464148E+04 2.858478E+01 + 2.660007E+01 3 3 2.249433E+03 2.017079E+02 + 2.660007E+01 4 2 1.465809E+04 2.868768E+01 + 2.660007E+01 4 4 2.709197E+05 9.456152E+01 + 2.660007E+01 5 1 -1.038811E+04 7.682086E+01 + 2.660007E+01 5 5 8.271452E+05 7.761916E+02 + 2.660007E+01 6 6 9.122217E+05 2.341624E+01 + 2.670007E+01 1 1 2.025589E+03 7.553147E+00 + 2.670007E+01 1 5 -1.036999E+04 7.639590E+01 + 2.670007E+01 2 2 2.299744E+03 8.594369E+00 + 2.670007E+01 2 4 1.464042E+04 2.831405E+01 + 2.670007E+01 3 3 2.250092E+03 2.018210E+02 + 2.670007E+01 4 2 1.465705E+04 2.841756E+01 + 2.670007E+01 4 4 2.709153E+05 9.364024E+01 + 2.670007E+01 5 1 -1.038798E+04 7.619834E+01 + 2.670007E+01 5 5 8.271442E+05 7.705438E+02 + 2.670007E+01 6 6 9.121616E+05 2.302403E+01 + 2.680007E+01 1 1 2.025398E+03 7.485611E+00 + 2.680007E+01 1 5 -1.036985E+04 7.577713E+01 + 2.680007E+01 2 2 2.299498E+03 8.516093E+00 + 2.680007E+01 2 4 1.463934E+04 2.804749E+01 + 2.680007E+01 3 3 2.250717E+03 2.019380E+02 + 2.680007E+01 4 2 1.465599E+04 2.814923E+01 + 2.680007E+01 4 4 2.709104E+05 9.271354E+01 + 2.680007E+01 5 1 -1.038785E+04 7.557999E+01 + 2.680007E+01 5 5 8.271412E+05 7.649456E+02 + 2.680007E+01 6 6 9.121021E+05 2.261722E+01 + 2.690007E+01 1 1 2.025213E+03 7.418912E+00 + 2.690007E+01 1 5 -1.036984E+04 7.516774E+01 + 2.690007E+01 2 2 2.299252E+03 8.439022E+00 + 2.690007E+01 2 4 1.463833E+04 2.778351E+01 + 2.690007E+01 3 3 2.251357E+03 2.020509E+02 + 2.690007E+01 4 2 1.465495E+04 2.788507E+01 + 2.690007E+01 4 4 2.709064E+05 9.180151E+01 + 2.690007E+01 5 1 -1.038777E+04 7.497178E+01 + 2.690007E+01 5 5 8.271384E+05 7.593719E+02 + 2.690007E+01 6 6 9.120447E+05 2.221501E+01 + 2.700007E+01 1 1 2.025029E+03 7.353319E+00 + 2.700007E+01 1 5 -1.036971E+04 7.456400E+01 + 2.700007E+01 2 2 2.299008E+03 8.362997E+00 + 2.700007E+01 2 4 1.463733E+04 2.752589E+01 + 2.700007E+01 3 3 2.251990E+03 2.021681E+02 + 2.700007E+01 4 2 1.465391E+04 2.762262E+01 + 2.700007E+01 4 4 2.709012E+05 9.091588E+01 + 2.700007E+01 5 1 -1.038770E+04 7.436827E+01 + 2.700007E+01 5 5 8.271402E+05 7.539083E+02 + 2.700007E+01 6 6 9.119880E+05 2.184375E+01 + 2.710007E+01 1 1 2.024842E+03 7.288342E+00 + 2.710007E+01 1 5 -1.036959E+04 7.396838E+01 + 2.710007E+01 2 2 2.298773E+03 8.288078E+00 + 2.710007E+01 2 4 1.463628E+04 2.726971E+01 + 2.710007E+01 3 3 2.252618E+03 2.022818E+02 + 2.710007E+01 4 2 1.465294E+04 2.736761E+01 + 2.710007E+01 4 4 2.708975E+05 9.004169E+01 + 2.710007E+01 5 1 -1.038757E+04 7.377531E+01 + 2.710007E+01 5 5 8.271379E+05 7.485558E+02 + 2.710007E+01 6 6 9.119296E+05 2.146154E+01 + 2.720007E+01 1 1 2.024660E+03 7.224402E+00 + 2.720007E+01 1 5 -1.036949E+04 7.338126E+01 + 2.720007E+01 2 2 2.298535E+03 8.214152E+00 + 2.720007E+01 2 4 1.463534E+04 2.701756E+01 + 2.720007E+01 3 3 2.253254E+03 2.023945E+02 + 2.720007E+01 4 2 1.465191E+04 2.711414E+01 + 2.720007E+01 4 4 2.708927E+05 8.917516E+01 + 2.720007E+01 5 1 -1.038744E+04 7.319016E+01 + 2.720007E+01 5 5 8.271361E+05 7.432085E+02 + 2.720007E+01 6 6 9.118745E+05 2.110249E+01 + 2.730007E+01 1 1 2.024485E+03 7.161346E+00 + 2.730007E+01 1 5 -1.036944E+04 7.279700E+01 + 2.730007E+01 2 2 2.298305E+03 8.141392E+00 + 2.730007E+01 2 4 1.463432E+04 2.676848E+01 + 2.730007E+01 3 3 2.253865E+03 2.025052E+02 + 2.730007E+01 4 2 1.465092E+04 2.686798E+01 + 2.730007E+01 4 4 2.708882E+05 8.831751E+01 + 2.730007E+01 5 1 -1.038731E+04 7.260977E+01 + 2.730007E+01 5 5 8.271354E+05 7.380906E+02 + 2.730007E+01 6 6 9.118178E+05 2.074540E+01 + 2.740007E+01 1 1 2.024305E+03 7.099033E+00 + 2.740007E+01 1 5 -1.036927E+04 7.222258E+01 + 2.740007E+01 2 2 2.298073E+03 8.069516E+00 + 2.740007E+01 2 4 1.463330E+04 2.652415E+01 + 2.740007E+01 3 3 2.254494E+03 2.026157E+02 + 2.740007E+01 4 2 1.464994E+04 2.662088E+01 + 2.740007E+01 4 4 2.708835E+05 8.749374E+01 + 2.740007E+01 5 1 -1.038720E+04 7.203725E+01 + 2.740007E+01 5 5 8.271338E+05 7.327724E+02 + 2.740007E+01 6 6 9.117642E+05 2.041133E+01 + 2.750007E+01 1 1 2.024130E+03 7.037647E+00 + 2.750007E+01 1 5 -1.036916E+04 7.165567E+01 + 2.750007E+01 2 2 2.297844E+03 7.998565E+00 + 2.750007E+01 2 4 1.463234E+04 2.628375E+01 + 2.750007E+01 3 3 2.255115E+03 2.027203E+02 + 2.750007E+01 4 2 1.464895E+04 2.637799E+01 + 2.750007E+01 4 4 2.708794E+05 8.667188E+01 + 2.750007E+01 5 1 -1.038707E+04 7.146989E+01 + 2.750007E+01 5 5 8.271309E+05 7.276382E+02 + 2.750007E+01 6 6 9.117089E+05 2.006933E+01 + 2.760007E+01 1 1 2.023955E+03 6.977025E+00 + 2.760007E+01 1 5 -1.036909E+04 7.109379E+01 + 2.760007E+01 2 2 2.297618E+03 7.928640E+00 + 2.760007E+01 2 4 1.463141E+04 2.604533E+01 + 2.760007E+01 3 3 2.255740E+03 2.028272E+02 + 2.760007E+01 4 2 1.464803E+04 2.613900E+01 + 2.760007E+01 4 4 2.708758E+05 8.586026E+01 + 2.760007E+01 5 1 -1.038699E+04 7.091207E+01 + 2.760007E+01 5 5 8.271269E+05 7.225269E+02 + 2.760007E+01 6 6 9.116554E+05 1.974953E+01 + 2.770007E+01 1 1 2.023784E+03 6.917323E+00 + 2.770007E+01 1 5 -1.036900E+04 7.053949E+01 + 2.770007E+01 2 2 2.297396E+03 7.859682E+00 + 2.770007E+01 2 4 1.463049E+04 2.581096E+01 + 2.770007E+01 3 3 2.256353E+03 2.029345E+02 + 2.770007E+01 4 2 1.464711E+04 2.590321E+01 + 2.770007E+01 4 4 2.708718E+05 8.506426E+01 + 2.770007E+01 5 1 -1.038695E+04 7.036079E+01 + 2.770007E+01 5 5 8.271243E+05 7.174827E+02 + 2.770007E+01 6 6 9.116028E+05 1.942171E+01 + 2.780007E+01 1 1 2.023617E+03 6.858329E+00 + 2.780007E+01 1 5 -1.036893E+04 6.999146E+01 + 2.780007E+01 2 2 2.297175E+03 7.791627E+00 + 2.780007E+01 2 4 1.462958E+04 2.557955E+01 + 2.780007E+01 3 3 2.256959E+03 2.030356E+02 + 2.780007E+01 4 2 1.464617E+04 2.567141E+01 + 2.780007E+01 4 4 2.708678E+05 8.427245E+01 + 2.780007E+01 5 1 -1.038686E+04 6.981249E+01 + 2.780007E+01 5 5 8.271239E+05 7.124775E+02 + 2.780007E+01 6 6 9.115508E+05 1.909354E+01 + 2.790007E+01 1 1 2.023452E+03 6.800189E+00 + 2.790007E+01 1 5 -1.036882E+04 6.944979E+01 + 2.790007E+01 2 2 2.296957E+03 7.724570E+00 + 2.790007E+01 2 4 1.462867E+04 2.535101E+01 + 2.790007E+01 3 3 2.257559E+03 2.031380E+02 + 2.790007E+01 4 2 1.464524E+04 2.544406E+01 + 2.790007E+01 4 4 2.708638E+05 8.349791E+01 + 2.790007E+01 5 1 -1.038676E+04 6.927383E+01 + 2.790007E+01 5 5 8.271224E+05 7.076198E+02 + 2.790007E+01 6 6 9.114988E+05 1.877842E+01 + 2.800007E+01 1 1 2.023283E+03 6.742652E+00 + 2.800007E+01 1 5 -1.036878E+04 6.891540E+01 + 2.800007E+01 2 2 2.296742E+03 7.658345E+00 + 2.800007E+01 2 4 1.462775E+04 2.512676E+01 + 2.800007E+01 3 3 2.258170E+03 2.032396E+02 + 2.800007E+01 4 2 1.464432E+04 2.521779E+01 + 2.800007E+01 4 4 2.708600E+05 8.273849E+01 + 2.800007E+01 5 1 -1.038664E+04 6.874118E+01 + 2.800007E+01 5 5 8.271211E+05 7.025291E+02 + 2.800007E+01 6 6 9.114471E+05 1.849010E+01 + 2.810007E+01 1 1 2.023123E+03 6.686055E+00 + 2.810007E+01 1 5 -1.036874E+04 6.838612E+01 + 2.810007E+01 2 2 2.296533E+03 7.593006E+00 + 2.810007E+01 2 4 1.462683E+04 2.490490E+01 + 2.810007E+01 3 3 2.258761E+03 2.033406E+02 + 2.810007E+01 4 2 1.464339E+04 2.499499E+01 + 2.810007E+01 4 4 2.708557E+05 8.199215E+01 + 2.810007E+01 5 1 -1.038655E+04 6.821239E+01 + 2.810007E+01 5 5 8.271199E+05 6.977377E+02 + 2.810007E+01 6 6 9.113975E+05 1.816499E+01 + 2.820007E+01 1 1 2.022958E+03 6.630203E+00 + 2.820007E+01 1 5 -1.036865E+04 6.786447E+01 + 2.820007E+01 2 2 2.296320E+03 7.528441E+00 + 2.820007E+01 2 4 1.462592E+04 2.468571E+01 + 2.820007E+01 3 3 2.259373E+03 2.034409E+02 + 2.820007E+01 4 2 1.464251E+04 2.477601E+01 + 2.820007E+01 4 4 2.708516E+05 8.123376E+01 + 2.820007E+01 5 1 -1.038648E+04 6.769152E+01 + 2.820007E+01 5 5 8.271199E+05 6.929471E+02 + 2.820007E+01 6 6 9.113474E+05 1.788164E+01 + 2.830007E+01 1 1 2.022800E+03 6.574834E+00 + 2.830007E+01 1 5 -1.036855E+04 6.734870E+01 + 2.830007E+01 2 2 2.296111E+03 7.464828E+00 + 2.830007E+01 2 4 1.462505E+04 2.447008E+01 + 2.830007E+01 3 3 2.259954E+03 2.035383E+02 + 2.830007E+01 4 2 1.464161E+04 2.455857E+01 + 2.830007E+01 4 4 2.708472E+05 8.050271E+01 + 2.830007E+01 5 1 -1.038641E+04 6.717837E+01 + 2.830007E+01 5 5 8.271189E+05 6.880599E+02 + 2.830007E+01 6 6 9.112978E+05 1.759614E+01 + 2.840007E+01 1 1 2.022639E+03 6.520379E+00 + 2.840007E+01 1 5 -1.036848E+04 6.683736E+01 + 2.840007E+01 2 2 2.295906E+03 7.402006E+00 + 2.840007E+01 2 4 1.462417E+04 2.425698E+01 + 2.840007E+01 3 3 2.260552E+03 2.036387E+02 + 2.840007E+01 4 2 1.464076E+04 2.434486E+01 + 2.840007E+01 4 4 2.708432E+05 7.977916E+01 + 2.840007E+01 5 1 -1.038631E+04 6.666644E+01 + 2.840007E+01 5 5 8.271157E+05 6.834644E+02 + 2.840007E+01 6 6 9.112480E+05 1.732650E+01 + 2.850007E+01 1 1 2.022484E+03 6.466599E+00 + 2.850007E+01 1 5 -1.036837E+04 6.633269E+01 + 2.850007E+01 2 2 2.295702E+03 7.340121E+00 + 2.850007E+01 2 4 1.462332E+04 2.404779E+01 + 2.850007E+01 3 3 2.261145E+03 2.037362E+02 + 2.850007E+01 4 2 1.463989E+04 2.413595E+01 + 2.850007E+01 4 4 2.708399E+05 7.907157E+01 + 2.850007E+01 5 1 -1.038626E+04 6.616535E+01 + 2.850007E+01 5 5 8.271139E+05 6.787702E+02 + 2.850007E+01 6 6 9.112001E+05 1.703636E+01 + 2.860007E+01 1 1 2.022328E+03 6.413464E+00 + 2.860007E+01 1 5 -1.036833E+04 6.583296E+01 + 2.860007E+01 2 2 2.295498E+03 7.278941E+00 + 2.860007E+01 2 4 1.462247E+04 2.384022E+01 + 2.860007E+01 3 3 2.261726E+03 2.038280E+02 + 2.860007E+01 4 2 1.463903E+04 2.392797E+01 + 2.860007E+01 4 4 2.708364E+05 7.836884E+01 + 2.860007E+01 5 1 -1.038620E+04 6.566795E+01 + 2.860007E+01 5 5 8.271121E+05 6.740529E+02 + 2.860007E+01 6 6 9.111522E+05 1.674174E+01 + 2.870007E+01 1 1 2.022170E+03 6.361094E+00 + 2.870007E+01 1 5 -1.036829E+04 6.534035E+01 + 2.870007E+01 2 2 2.295301E+03 7.218606E+00 + 2.870007E+01 2 4 1.462165E+04 2.363672E+01 + 2.870007E+01 3 3 2.262323E+03 2.039178E+02 + 2.870007E+01 4 2 1.463819E+04 2.372230E+01 + 2.870007E+01 4 4 2.708327E+05 7.768160E+01 + 2.870007E+01 5 1 -1.038616E+04 6.517496E+01 + 2.870007E+01 5 5 8.271101E+05 6.694837E+02 + 2.870007E+01 6 6 9.111051E+05 1.650031E+01 + 2.880007E+01 1 1 2.022024E+03 6.309087E+00 + 2.880007E+01 1 5 -1.036821E+04 6.485181E+01 + 2.880007E+01 2 2 2.295105E+03 7.158854E+00 + 2.880007E+01 2 4 1.462082E+04 2.343510E+01 + 2.880007E+01 3 3 2.262901E+03 2.040123E+02 + 2.880007E+01 4 2 1.463736E+04 2.351902E+01 + 2.880007E+01 4 4 2.708287E+05 7.700045E+01 + 2.880007E+01 5 1 -1.038609E+04 6.468934E+01 + 2.880007E+01 5 5 8.271091E+05 6.650147E+02 + 2.880007E+01 6 6 9.110579E+05 1.625590E+01 + 2.890007E+01 1 1 2.021871E+03 6.258068E+00 + 2.890007E+01 1 5 -1.036815E+04 6.437022E+01 + 2.890007E+01 2 2 2.294912E+03 7.100051E+00 + 2.890007E+01 2 4 1.461996E+04 2.323535E+01 + 2.890007E+01 3 3 2.263477E+03 2.041029E+02 + 2.890007E+01 4 2 1.463655E+04 2.331953E+01 + 2.890007E+01 4 4 2.708250E+05 7.632709E+01 + 2.890007E+01 5 1 -1.038606E+04 6.420971E+01 + 2.890007E+01 5 5 8.271060E+05 6.604647E+02 + 2.890007E+01 6 6 9.110112E+05 1.598374E+01 + 2.900007E+01 1 1 2.021721E+03 6.207590E+00 + 2.900007E+01 1 5 -1.036804E+04 6.389341E+01 + 2.900007E+01 2 2 2.294715E+03 7.041935E+00 + 2.900007E+01 2 4 1.461917E+04 2.304024E+01 + 2.900007E+01 3 3 2.264055E+03 2.041899E+02 + 2.900007E+01 4 2 1.463569E+04 2.312125E+01 + 2.900007E+01 4 4 2.708212E+05 7.566386E+01 + 2.900007E+01 5 1 -1.038595E+04 6.373272E+01 + 2.900007E+01 5 5 8.271059E+05 6.560548E+02 + 2.900007E+01 6 6 9.109660E+05 1.574792E+01 + 2.910007E+01 1 1 2.021573E+03 6.157659E+00 + 2.910007E+01 1 5 -1.036800E+04 6.342225E+01 + 2.910007E+01 2 2 2.294522E+03 6.984544E+00 + 2.910007E+01 2 4 1.461833E+04 2.284501E+01 + 2.910007E+01 3 3 2.264625E+03 2.042838E+02 + 2.910007E+01 4 2 1.463491E+04 2.292676E+01 + 2.910007E+01 4 4 2.708181E+05 7.500017E+01 + 2.910007E+01 5 1 -1.038590E+04 6.326410E+01 + 2.910007E+01 5 5 8.271073E+05 6.516302E+02 + 2.910007E+01 6 6 9.109204E+05 1.547230E+01 + 2.920008E+01 1 1 2.021426E+03 6.108489E+00 + 2.920008E+01 1 5 -1.036796E+04 6.295671E+01 + 2.920008E+01 2 2 2.294335E+03 6.927901E+00 + 2.920008E+01 2 4 1.461756E+04 2.265427E+01 + 2.920008E+01 3 3 2.265196E+03 2.043726E+02 + 2.920008E+01 4 2 1.463408E+04 2.273553E+01 + 2.920008E+01 4 4 2.708147E+05 7.435568E+01 + 2.920008E+01 5 1 -1.038581E+04 6.280007E+01 + 2.920008E+01 5 5 8.271033E+05 6.472724E+02 + 2.920008E+01 6 6 9.108755E+05 1.525361E+01 + 2.930008E+01 1 1 2.021280E+03 6.059825E+00 + 2.930008E+01 1 5 -1.036789E+04 6.249568E+01 + 2.930008E+01 2 2 2.294149E+03 6.872046E+00 + 2.930008E+01 2 4 1.461680E+04 2.246572E+01 + 2.930008E+01 3 3 2.265770E+03 2.044607E+02 + 2.930008E+01 4 2 1.463332E+04 2.254597E+01 + 2.930008E+01 4 4 2.708115E+05 7.371797E+01 + 2.930008E+01 5 1 -1.038576E+04 6.234050E+01 + 2.930008E+01 5 5 8.270998E+05 6.429332E+02 + 2.930008E+01 6 6 9.108319E+05 1.502413E+01 + 2.940008E+01 1 1 2.021138E+03 6.011852E+00 + 2.940008E+01 1 5 -1.036782E+04 6.203848E+01 + 2.940008E+01 2 2 2.293958E+03 6.816762E+00 + 2.940008E+01 2 4 1.461598E+04 2.227993E+01 + 2.940008E+01 3 3 2.266332E+03 2.045479E+02 + 2.940008E+01 4 2 1.463253E+04 2.235858E+01 + 2.940008E+01 4 4 2.708084E+05 7.308825E+01 + 2.940008E+01 5 1 -1.038572E+04 6.188339E+01 + 2.940008E+01 5 5 8.270981E+05 6.387080E+02 + 2.940008E+01 6 6 9.107879E+05 1.480074E+01 + 2.950008E+01 1 1 2.020998E+03 5.964438E+00 + 2.950008E+01 1 5 -1.036776E+04 6.158921E+01 + 2.950008E+01 2 2 2.293778E+03 6.762341E+00 + 2.950008E+01 2 4 1.461521E+04 2.209564E+01 + 2.950008E+01 3 3 2.266894E+03 2.046373E+02 + 2.950008E+01 4 2 1.463177E+04 2.217491E+01 + 2.950008E+01 4 4 2.708047E+05 7.246009E+01 + 2.950008E+01 5 1 -1.038566E+04 6.143720E+01 + 2.950008E+01 5 5 8.270965E+05 6.344276E+02 + 2.950008E+01 6 6 9.107442E+05 1.456672E+01 + 2.960008E+01 1 1 2.020856E+03 5.917544E+00 + 2.960008E+01 1 5 -1.036768E+04 6.114288E+01 + 2.960008E+01 2 2 2.293596E+03 6.708459E+00 + 2.960008E+01 2 4 1.461445E+04 2.191437E+01 + 2.960008E+01 3 3 2.267466E+03 2.047225E+02 + 2.960008E+01 4 2 1.463100E+04 2.199310E+01 + 2.960008E+01 4 4 2.708009E+05 7.186835E+01 + 2.960008E+01 5 1 -1.038560E+04 6.099097E+01 + 2.960008E+01 5 5 8.270942E+05 6.302792E+02 + 2.960008E+01 6 6 9.107021E+05 1.434396E+01 + 2.970008E+01 1 1 2.020719E+03 5.871214E+00 + 2.970008E+01 1 5 -1.036767E+04 6.070256E+01 + 2.970008E+01 2 2 2.293414E+03 6.655274E+00 + 2.970008E+01 2 4 1.461368E+04 2.173527E+01 + 2.970008E+01 3 3 2.268023E+03 2.048034E+02 + 2.970008E+01 4 2 1.463019E+04 2.181270E+01 + 2.970008E+01 4 4 2.707975E+05 7.125802E+01 + 2.970008E+01 5 1 -1.038563E+04 6.055035E+01 + 2.970008E+01 5 5 8.270915E+05 6.261959E+02 + 2.970008E+01 6 6 9.106592E+05 1.412324E+01 + 2.980008E+01 1 1 2.020583E+03 5.825470E+00 + 2.980008E+01 1 5 -1.036769E+04 6.026657E+01 + 2.980008E+01 2 2 2.293240E+03 6.602677E+00 + 2.980008E+01 2 4 1.461294E+04 2.155863E+01 + 2.980008E+01 3 3 2.268576E+03 2.048897E+02 + 2.980008E+01 4 2 1.462945E+04 2.163625E+01 + 2.980008E+01 4 4 2.707938E+05 7.064493E+01 + 2.980008E+01 5 1 -1.038553E+04 6.011567E+01 + 2.980008E+01 5 5 8.270897E+05 6.220324E+02 + 2.980008E+01 6 6 9.106178E+05 1.393097E+01 + 2.990008E+01 1 1 2.020447E+03 5.780306E+00 + 2.990008E+01 1 5 -1.036763E+04 5.983643E+01 + 2.990008E+01 2 2 2.293064E+03 6.550907E+00 + 2.990008E+01 2 4 1.461221E+04 2.138336E+01 + 2.990008E+01 3 3 2.269145E+03 2.049725E+02 + 2.990008E+01 4 2 1.462872E+04 2.146172E+01 + 2.990008E+01 4 4 2.707909E+05 7.004963E+01 + 2.990008E+01 5 1 -1.038549E+04 5.968921E+01 + 2.990008E+01 5 5 8.270876E+05 6.179717E+02 + 2.990008E+01 6 6 9.105762E+05 1.371025E+01 + 3.000008E+01 1 1 2.020311E+03 5.735516E+00 + 3.000008E+01 1 5 -1.036755E+04 5.940879E+01 + 3.000008E+01 2 2 2.292889E+03 6.499515E+00 + 3.000008E+01 2 4 1.461148E+04 2.121048E+01 + 3.000008E+01 3 3 2.269689E+03 2.050517E+02 + 3.000008E+01 4 2 1.462802E+04 2.128679E+01 + 3.000008E+01 4 4 2.707882E+05 6.946275E+01 + 3.000008E+01 5 1 -1.038544E+04 5.926148E+01 + 3.000008E+01 5 5 8.270874E+05 6.139026E+02 + 3.000008E+01 6 6 9.105343E+05 1.350836E+01 + 3.010008E+01 1 1 2.020176E+03 5.691556E+00 + 3.010008E+01 1 5 -1.036749E+04 5.898837E+01 + 3.010008E+01 2 2 2.292721E+03 6.448809E+00 + 3.010008E+01 2 4 1.461075E+04 2.104004E+01 + 3.010008E+01 3 3 2.270232E+03 2.051338E+02 + 3.010008E+01 4 2 1.462729E+04 2.111545E+01 + 3.010008E+01 4 4 2.707848E+05 6.888127E+01 + 3.010008E+01 5 1 -1.038534E+04 5.883812E+01 + 3.010008E+01 5 5 8.270859E+05 6.097963E+02 + 3.010008E+01 6 6 9.104941E+05 1.329061E+01 + 3.020008E+01 1 1 2.020045E+03 5.647838E+00 + 3.020008E+01 1 5 -1.036748E+04 5.856982E+01 + 3.020008E+01 2 2 2.292547E+03 6.398825E+00 + 3.020008E+01 2 4 1.461003E+04 2.087177E+01 + 3.020008E+01 3 3 2.270784E+03 2.052098E+02 + 3.020008E+01 4 2 1.462657E+04 2.094711E+01 + 3.020008E+01 4 4 2.707821E+05 6.832902E+01 + 3.020008E+01 5 1 -1.038530E+04 5.842654E+01 + 3.020008E+01 5 5 8.270849E+05 6.059205E+02 + 3.020008E+01 6 6 9.104534E+05 1.311851E+01 + 3.030008E+01 1 1 2.019914E+03 5.604763E+00 + 3.030008E+01 1 5 -1.036745E+04 5.815787E+01 + 3.030008E+01 2 2 2.292382E+03 6.349491E+00 + 3.030008E+01 2 4 1.460933E+04 2.070590E+01 + 3.030008E+01 3 3 2.271326E+03 2.052895E+02 + 3.030008E+01 4 2 1.462586E+04 2.078091E+01 + 3.030008E+01 4 4 2.707782E+05 6.777458E+01 + 3.030008E+01 5 1 -1.038526E+04 5.801655E+01 + 3.030008E+01 5 5 8.270829E+05 6.018796E+02 + 3.030008E+01 6 6 9.104129E+05 1.291759E+01 + 3.040008E+01 1 1 2.019788E+03 5.562180E+00 + 3.040008E+01 1 5 -1.036744E+04 5.774894E+01 + 3.040008E+01 2 2 2.292213E+03 6.300581E+00 + 3.040008E+01 2 4 1.460862E+04 2.054165E+01 + 3.040008E+01 3 3 2.271875E+03 2.053652E+02 + 3.040008E+01 4 2 1.462515E+04 2.061540E+01 + 3.040008E+01 4 4 2.707755E+05 6.721703E+01 + 3.040008E+01 5 1 -1.038523E+04 5.760820E+01 + 3.040008E+01 5 5 8.270799E+05 5.981005E+02 + 3.040008E+01 6 6 9.103738E+05 1.272697E+01 + 3.050008E+01 1 1 2.019657E+03 5.520111E+00 + 3.050008E+01 1 5 -1.036739E+04 5.734531E+01 + 3.050008E+01 2 2 2.292048E+03 6.252312E+00 + 3.050008E+01 2 4 1.460792E+04 2.037868E+01 + 3.050008E+01 3 3 2.272415E+03 2.054393E+02 + 3.050008E+01 4 2 1.462445E+04 2.045273E+01 + 3.050008E+01 4 4 2.707728E+05 6.665411E+01 + 3.050008E+01 5 1 -1.038520E+04 5.720720E+01 + 3.050008E+01 5 5 8.270796E+05 5.941226E+02 + 3.050008E+01 6 6 9.103344E+05 1.254307E+01 + 3.060008E+01 1 1 2.019536E+03 5.478503E+00 + 3.060008E+01 1 5 -1.036736E+04 5.694650E+01 + 3.060008E+01 2 2 2.291885E+03 6.204667E+00 + 3.060008E+01 2 4 1.460723E+04 2.022026E+01 + 3.060008E+01 3 3 2.272950E+03 2.055196E+02 + 3.060008E+01 4 2 1.462376E+04 2.029109E+01 + 3.060008E+01 4 4 2.707699E+05 6.612585E+01 + 3.060008E+01 5 1 -1.038516E+04 5.680798E+01 + 3.060008E+01 5 5 8.270776E+05 5.904149E+02 + 3.060008E+01 6 6 9.102960E+05 1.237752E+01 + 3.070008E+01 1 1 2.019405E+03 5.437555E+00 + 3.070008E+01 1 5 -1.036729E+04 5.655041E+01 + 3.070008E+01 2 2 2.291720E+03 6.157564E+00 + 3.070008E+01 2 4 1.460656E+04 2.006185E+01 + 3.070008E+01 3 3 2.273484E+03 2.055976E+02 + 3.070008E+01 4 2 1.462307E+04 2.013314E+01 + 3.070008E+01 4 4 2.707660E+05 6.559805E+01 + 3.070008E+01 5 1 -1.038508E+04 5.641356E+01 + 3.070008E+01 5 5 8.270776E+05 5.865265E+02 + 3.070008E+01 6 6 9.102575E+05 1.220172E+01 + 3.080008E+01 1 1 2.019276E+03 5.396836E+00 + 3.080008E+01 1 5 -1.036728E+04 5.615812E+01 + 3.080008E+01 2 2 2.291559E+03 6.110959E+00 + 3.080008E+01 2 4 1.460588E+04 1.990582E+01 + 3.080008E+01 3 3 2.274016E+03 2.056712E+02 + 3.080008E+01 4 2 1.462238E+04 1.997769E+01 + 3.080008E+01 4 4 2.707626E+05 6.506673E+01 + 3.080008E+01 5 1 -1.038507E+04 5.602548E+01 + 3.080008E+01 5 5 8.270770E+05 5.828536E+02 + 3.080008E+01 6 6 9.102211E+05 1.201544E+01 + 3.090008E+01 1 1 2.019156E+03 5.356817E+00 + 3.090008E+01 1 5 -1.036729E+04 5.577095E+01 + 3.090008E+01 2 2 2.291398E+03 6.064867E+00 + 3.090008E+01 2 4 1.460524E+04 1.975068E+01 + 3.090008E+01 3 3 2.274535E+03 2.057437E+02 + 3.090008E+01 4 2 1.462171E+04 1.982124E+01 + 3.090008E+01 4 4 2.707598E+05 6.454514E+01 + 3.090008E+01 5 1 -1.038501E+04 5.563477E+01 + 3.090008E+01 5 5 8.270751E+05 5.790355E+02 + 3.090008E+01 6 6 9.101829E+05 1.183959E+01 + 3.100008E+01 1 1 2.019033E+03 5.317164E+00 + 3.100008E+01 1 5 -1.036725E+04 5.538704E+01 + 3.100008E+01 2 2 2.291246E+03 6.019514E+00 + 3.100008E+01 2 4 1.460456E+04 1.959860E+01 + 3.100008E+01 3 3 2.275073E+03 2.058216E+02 + 3.100008E+01 4 2 1.462105E+04 1.966796E+01 + 3.100008E+01 4 4 2.707573E+05 6.404614E+01 + 3.100008E+01 5 1 -1.038495E+04 5.525334E+01 + 3.100008E+01 5 5 8.270769E+05 5.755447E+02 + 3.100008E+01 6 6 9.101450E+05 1.168376E+01 + 3.110008E+01 1 1 2.018913E+03 5.277853E+00 + 3.110008E+01 1 5 -1.036723E+04 5.500767E+01 + 3.110008E+01 2 2 2.291091E+03 5.974467E+00 + 3.110008E+01 2 4 1.460391E+04 1.944839E+01 + 3.110008E+01 3 3 2.275623E+03 2.058917E+02 + 3.110008E+01 4 2 1.462045E+04 1.951746E+01 + 3.110008E+01 4 4 2.707550E+05 6.353241E+01 + 3.110008E+01 5 1 -1.038495E+04 5.487522E+01 + 3.110008E+01 5 5 8.270759E+05 5.717247E+02 + 3.110008E+01 6 6 9.101077E+05 1.152268E+01 + 3.120008E+01 1 1 2.018791E+03 5.239028E+00 + 3.120008E+01 1 5 -1.036722E+04 5.463159E+01 + 3.120008E+01 2 2 2.290933E+03 5.930074E+00 + 3.120008E+01 2 4 1.460327E+04 1.929932E+01 + 3.120008E+01 3 3 2.276146E+03 2.059699E+02 + 3.120008E+01 4 2 1.461975E+04 1.936892E+01 + 3.120008E+01 4 4 2.707526E+05 6.303081E+01 + 3.120008E+01 5 1 -1.038495E+04 5.449835E+01 + 3.120008E+01 5 5 8.270733E+05 5.683505E+02 + 3.120008E+01 6 6 9.100716E+05 1.135478E+01 + 3.130008E+01 1 1 2.018671E+03 5.200728E+00 + 3.130008E+01 1 5 -1.036720E+04 5.426095E+01 + 3.130008E+01 2 2 2.290780E+03 5.886132E+00 + 3.130008E+01 2 4 1.460259E+04 1.915292E+01 + 3.130008E+01 3 3 2.276664E+03 2.060374E+02 + 3.130008E+01 4 2 1.461911E+04 1.922163E+01 + 3.130008E+01 4 4 2.707492E+05 6.254450E+01 + 3.130008E+01 5 1 -1.038491E+04 5.413215E+01 + 3.130008E+01 5 5 8.270704E+05 5.646052E+02 + 3.130008E+01 6 6 9.100346E+05 1.118837E+01 + 3.140008E+01 1 1 2.018555E+03 5.162685E+00 + 3.140008E+01 1 5 -1.036716E+04 5.389315E+01 + 3.140008E+01 2 2 2.290628E+03 5.842745E+00 + 3.140008E+01 2 4 1.460196E+04 1.900646E+01 + 3.140008E+01 3 3 2.277192E+03 2.061052E+02 + 3.140008E+01 4 2 1.461847E+04 1.907387E+01 + 3.140008E+01 4 4 2.707464E+05 6.204185E+01 + 3.140008E+01 5 1 -1.038491E+04 5.376302E+01 + 3.140008E+01 5 5 8.270689E+05 5.611432E+02 + 3.140008E+01 6 6 9.100006E+05 1.101737E+01 + 3.150008E+01 1 1 2.018440E+03 5.125191E+00 + 3.150008E+01 1 5 -1.036712E+04 5.352942E+01 + 3.150008E+01 2 2 2.290478E+03 5.799845E+00 + 3.150008E+01 2 4 1.460136E+04 1.886304E+01 + 3.150008E+01 3 3 2.277707E+03 2.061735E+02 + 3.150008E+01 4 2 1.461787E+04 1.893100E+01 + 3.150008E+01 4 4 2.707439E+05 6.156284E+01 + 3.150008E+01 5 1 -1.038488E+04 5.339945E+01 + 3.150008E+01 5 5 8.270657E+05 5.576572E+02 + 3.150008E+01 6 6 9.099652E+05 1.087240E+01 + 3.160008E+01 1 1 2.018327E+03 5.088073E+00 + 3.160008E+01 1 5 -1.036709E+04 5.316983E+01 + 3.160008E+01 2 2 2.290333E+03 5.757326E+00 + 3.160008E+01 2 4 1.460073E+04 1.872107E+01 + 3.160008E+01 3 3 2.278215E+03 2.062425E+02 + 3.160008E+01 4 2 1.461724E+04 1.878803E+01 + 3.160008E+01 4 4 2.707412E+05 6.109447E+01 + 3.160008E+01 5 1 -1.038488E+04 5.304378E+01 + 3.160008E+01 5 5 8.270635E+05 5.541365E+02 + 3.160008E+01 6 6 9.099310E+05 1.072399E+01 + 3.170008E+01 1 1 2.018213E+03 5.051478E+00 + 3.170008E+01 1 5 -1.036707E+04 5.281169E+01 + 3.170008E+01 2 2 2.290188E+03 5.715494E+00 + 3.170008E+01 2 4 1.460011E+04 1.858160E+01 + 3.170008E+01 3 3 2.278729E+03 2.063118E+02 + 3.170008E+01 4 2 1.461665E+04 1.864968E+01 + 3.170008E+01 4 4 2.707382E+05 6.062715E+01 + 3.170008E+01 5 1 -1.038485E+04 5.268708E+01 + 3.170008E+01 5 5 8.270635E+05 5.507777E+02 + 3.170008E+01 6 6 9.098956E+05 1.056697E+01 + 3.180009E+01 1 1 2.018096E+03 5.015356E+00 + 3.180009E+01 1 5 -1.036704E+04 5.246017E+01 + 3.180009E+01 2 2 2.290042E+03 5.674034E+00 + 3.180009E+01 2 4 1.459948E+04 1.844287E+01 + 3.180009E+01 3 3 2.279241E+03 2.063776E+02 + 3.180009E+01 4 2 1.461601E+04 1.850991E+01 + 3.180009E+01 4 4 2.707358E+05 6.015704E+01 + 3.180009E+01 5 1 -1.038482E+04 5.233337E+01 + 3.180009E+01 5 5 8.270618E+05 5.472370E+02 + 3.180009E+01 6 6 9.098625E+05 1.042886E+01 + 3.190009E+01 1 1 2.017987E+03 4.979373E+00 + 3.190009E+01 1 5 -1.036703E+04 5.211030E+01 + 3.190009E+01 2 2 2.289895E+03 5.632864E+00 + 3.190009E+01 2 4 1.459887E+04 1.830628E+01 + 3.190009E+01 3 3 2.279764E+03 2.064400E+02 + 3.190009E+01 4 2 1.461540E+04 1.837126E+01 + 3.190009E+01 4 4 2.707333E+05 5.970638E+01 + 3.190009E+01 5 1 -1.038481E+04 5.198465E+01 + 3.190009E+01 5 5 8.270599E+05 5.440458E+02 + 3.190009E+01 6 6 9.098271E+05 1.028428E+01 + 3.200008E+01 1 1 2.017874E+03 4.943982E+00 + 3.200008E+01 1 5 -1.036702E+04 5.176426E+01 + 3.200008E+01 2 2 2.289757E+03 5.592231E+00 + 3.200008E+01 2 4 1.459829E+04 1.817052E+01 + 3.200008E+01 3 3 2.280292E+03 2.065081E+02 + 3.200008E+01 4 2 1.461478E+04 1.823516E+01 + 3.200008E+01 4 4 2.707302E+05 5.924137E+01 + 3.200008E+01 5 1 -1.038482E+04 5.163935E+01 + 3.200008E+01 5 5 8.270562E+05 5.406495E+02 + 3.200008E+01 6 6 9.097942E+05 1.014167E+01 + 3.210008E+01 1 1 2.017764E+03 4.908949E+00 + 3.210008E+01 1 5 -1.036700E+04 5.142149E+01 + 3.210008E+01 2 2 2.289612E+03 5.552336E+00 + 3.210008E+01 2 4 1.459767E+04 1.803678E+01 + 3.210008E+01 3 3 2.280788E+03 2.065727E+02 + 3.210008E+01 4 2 1.461417E+04 1.810139E+01 + 3.210008E+01 4 4 2.707278E+05 5.879571E+01 + 3.210008E+01 5 1 -1.038478E+04 5.129827E+01 + 3.210008E+01 5 5 8.270566E+05 5.372954E+02 + 3.210008E+01 6 6 9.097607E+05 1.001906E+01 + 3.220008E+01 1 1 2.017659E+03 4.874296E+00 + 3.220008E+01 1 5 -1.036699E+04 5.108210E+01 + 3.220008E+01 2 2 2.289474E+03 5.512514E+00 + 3.220008E+01 2 4 1.459714E+04 1.790340E+01 + 3.220008E+01 3 3 2.281296E+03 2.066397E+02 + 3.220008E+01 4 2 1.461361E+04 1.796741E+01 + 3.220008E+01 4 4 2.707253E+05 5.835419E+01 + 3.220008E+01 5 1 -1.038477E+04 5.096151E+01 + 3.220008E+01 5 5 8.270564E+05 5.340329E+02 + 3.220008E+01 6 6 9.097281E+05 9.872394E+00 + 3.230008E+01 1 1 2.017551E+03 4.839922E+00 + 3.230008E+01 1 5 -1.036698E+04 5.074788E+01 + 3.230008E+01 2 2 2.289334E+03 5.473316E+00 + 3.230008E+01 2 4 1.459653E+04 1.777277E+01 + 3.230008E+01 3 3 2.281800E+03 2.067076E+02 + 3.230008E+01 4 2 1.461301E+04 1.783599E+01 + 3.230008E+01 4 4 2.707227E+05 5.790337E+01 + 3.230008E+01 5 1 -1.038477E+04 5.062877E+01 + 3.230008E+01 5 5 8.270556E+05 5.307462E+02 + 3.230008E+01 6 6 9.096941E+05 9.739921E+00 + 3.240008E+01 1 1 2.017437E+03 4.805939E+00 + 3.240008E+01 1 5 -1.036695E+04 5.041497E+01 + 3.240008E+01 2 2 2.289196E+03 5.434473E+00 + 3.240008E+01 2 4 1.459595E+04 1.764435E+01 + 3.240008E+01 3 3 2.282287E+03 2.067744E+02 + 3.240008E+01 4 2 1.461248E+04 1.770653E+01 + 3.240008E+01 4 4 2.707203E+05 5.750328E+01 + 3.240008E+01 5 1 -1.038471E+04 5.029712E+01 + 3.240008E+01 5 5 8.270545E+05 5.275226E+02 + 3.240008E+01 6 6 9.096628E+05 9.595244E+00 + 3.250008E+01 1 1 2.017340E+03 4.772391E+00 + 3.250008E+01 1 5 -1.036696E+04 5.008792E+01 + 3.250008E+01 2 2 2.289060E+03 5.396129E+00 + 3.250008E+01 2 4 1.459537E+04 1.751562E+01 + 3.250008E+01 3 3 2.282792E+03 2.068363E+02 + 3.250008E+01 4 2 1.461189E+04 1.757891E+01 + 3.250008E+01 4 4 2.707179E+05 5.705292E+01 + 3.250008E+01 5 1 -1.038473E+04 4.996671E+01 + 3.250008E+01 5 5 8.270538E+05 5.243102E+02 + 3.250008E+01 6 6 9.096309E+05 9.462701E+00 + 3.260007E+01 1 1 2.017234E+03 4.739207E+00 + 3.260007E+01 1 5 -1.036696E+04 4.976168E+01 + 3.260007E+01 2 2 2.288923E+03 5.358119E+00 + 3.260007E+01 2 4 1.459480E+04 1.738945E+01 + 3.260007E+01 3 3 2.283295E+03 2.068985E+02 + 3.260007E+01 4 2 1.461133E+04 1.745126E+01 + 3.260007E+01 4 4 2.707153E+05 5.663148E+01 + 3.260007E+01 5 1 -1.038470E+04 4.964454E+01 + 3.260007E+01 5 5 8.270504E+05 5.211184E+02 + 3.260007E+01 6 6 9.095991E+05 9.349185E+00 + 3.270007E+01 1 1 2.017130E+03 4.706257E+00 + 3.270007E+01 1 5 -1.036695E+04 4.943787E+01 + 3.270007E+01 2 2 2.288792E+03 5.320659E+00 + 3.270007E+01 2 4 1.459423E+04 1.726386E+01 + 3.270007E+01 3 3 2.283775E+03 2.069594E+02 + 3.270007E+01 4 2 1.461072E+04 1.732748E+01 + 3.270007E+01 4 4 2.707130E+05 5.620590E+01 + 3.270007E+01 5 1 -1.038468E+04 4.932141E+01 + 3.270007E+01 5 5 8.270479E+05 5.179899E+02 + 3.270007E+01 6 6 9.095683E+05 9.226877E+00 + 3.280007E+01 1 1 2.017021E+03 4.673912E+00 + 3.280007E+01 1 5 -1.036695E+04 4.911926E+01 + 3.280007E+01 2 2 2.288657E+03 5.283504E+00 + 3.280007E+01 2 4 1.459371E+04 1.714091E+01 + 3.280007E+01 3 3 2.284278E+03 2.070224E+02 + 3.280007E+01 4 2 1.461020E+04 1.720206E+01 + 3.280007E+01 4 4 2.707109E+05 5.580116E+01 + 3.280007E+01 5 1 -1.038467E+04 4.900334E+01 + 3.280007E+01 5 5 8.270487E+05 5.147988E+02 + 3.280007E+01 6 6 9.095362E+05 9.102610E+00 + 3.290007E+01 1 1 2.016920E+03 4.641672E+00 + 3.290007E+01 1 5 -1.036695E+04 4.880312E+01 + 3.290007E+01 2 2 2.288530E+03 5.246795E+00 + 3.290007E+01 2 4 1.459318E+04 1.701746E+01 + 3.290007E+01 3 3 2.284770E+03 2.070830E+02 + 3.290007E+01 4 2 1.460967E+04 1.707979E+01 + 3.290007E+01 4 4 2.707084E+05 5.538412E+01 + 3.290007E+01 5 1 -1.038466E+04 4.868804E+01 + 3.290007E+01 5 5 8.270472E+05 5.117176E+02 + 3.290007E+01 6 6 9.095062E+05 8.964191E+00 + 3.300007E+01 1 1 2.016823E+03 4.609921E+00 + 3.300007E+01 1 5 -1.036692E+04 4.849102E+01 + 3.300007E+01 2 2 2.288396E+03 5.210488E+00 + 3.300007E+01 2 4 1.459259E+04 1.689742E+01 + 3.300007E+01 3 3 2.285267E+03 2.071416E+02 + 3.300007E+01 4 2 1.460912E+04 1.695896E+01 + 3.300007E+01 4 4 2.707057E+05 5.499294E+01 + 3.300007E+01 5 1 -1.038465E+04 4.837271E+01 + 3.300007E+01 5 5 8.270472E+05 5.086148E+02 + 3.300007E+01 6 6 9.094754E+05 8.860820E+00 + 3.310007E+01 1 1 2.016723E+03 4.578347E+00 + 3.310007E+01 1 5 -1.036692E+04 4.818066E+01 + 3.310007E+01 2 2 2.288265E+03 5.174525E+00 + 3.310007E+01 2 4 1.459206E+04 1.677721E+01 + 3.310007E+01 3 3 2.285750E+03 2.072039E+02 + 3.310007E+01 4 2 1.460856E+04 1.683876E+01 + 3.310007E+01 4 4 2.707030E+05 5.458032E+01 + 3.310007E+01 5 1 -1.038462E+04 4.806683E+01 + 3.310007E+01 5 5 8.270457E+05 5.056040E+02 + 3.310007E+01 6 6 9.094449E+05 8.742088E+00 + 3.320007E+01 1 1 2.016624E+03 4.547227E+00 + 3.320007E+01 1 5 -1.036691E+04 4.787306E+01 + 3.320007E+01 2 2 2.288140E+03 5.138874E+00 + 3.320007E+01 2 4 1.459153E+04 1.665984E+01 + 3.320007E+01 3 3 2.286236E+03 2.072601E+02 + 3.320007E+01 4 2 1.460801E+04 1.671791E+01 + 3.320007E+01 4 4 2.707005E+05 5.419601E+01 + 3.320007E+01 5 1 -1.038464E+04 4.775983E+01 + 3.320007E+01 5 5 8.270449E+05 5.025326E+02 + 3.320007E+01 6 6 9.094157E+05 8.613149E+00 + 3.330006E+01 1 1 2.016520E+03 4.516479E+00 + 3.330006E+01 1 5 -1.036689E+04 4.756926E+01 + 3.330006E+01 2 2 2.288014E+03 5.103774E+00 + 3.330006E+01 2 4 1.459101E+04 1.654124E+01 + 3.330006E+01 3 3 2.286714E+03 2.073202E+02 + 3.330006E+01 4 2 1.460747E+04 1.660173E+01 + 3.330006E+01 4 4 2.706984E+05 5.380000E+01 + 3.330006E+01 5 1 -1.038461E+04 4.745464E+01 + 3.330006E+01 5 5 8.270425E+05 4.996131E+02 + 3.330006E+01 6 6 9.093857E+05 8.524786E+00 + 3.340006E+01 1 1 2.016426E+03 4.485881E+00 + 3.340006E+01 1 5 -1.036688E+04 4.726738E+01 + 3.340006E+01 2 2 2.287889E+03 5.068748E+00 + 3.340006E+01 2 4 1.459050E+04 1.642647E+01 + 3.340006E+01 3 3 2.287211E+03 2.073812E+02 + 3.340006E+01 4 2 1.460694E+04 1.648383E+01 + 3.340006E+01 4 4 2.706957E+05 5.341031E+01 + 3.340006E+01 5 1 -1.038461E+04 4.715745E+01 + 3.340006E+01 5 5 8.270424E+05 4.966593E+02 + 3.340006E+01 6 6 9.093561E+05 8.395782E+00 + 3.350006E+01 1 1 2.016330E+03 4.455670E+00 + 3.350006E+01 1 5 -1.036687E+04 4.696966E+01 + 3.350006E+01 2 2 2.287764E+03 5.034426E+00 + 3.350006E+01 2 4 1.458995E+04 1.631194E+01 + 3.350006E+01 3 3 2.287693E+03 2.074359E+02 + 3.350006E+01 4 2 1.460639E+04 1.636994E+01 + 3.350006E+01 4 4 2.706933E+05 5.303030E+01 + 3.350006E+01 5 1 -1.038459E+04 4.685500E+01 + 3.350006E+01 5 5 8.270410E+05 4.938537E+02 + 3.350006E+01 6 6 9.093272E+05 8.291888E+00 + 3.360006E+01 1 1 2.016233E+03 4.425919E+00 + 3.360006E+01 1 5 -1.036687E+04 4.667384E+01 + 3.360006E+01 2 2 2.287640E+03 5.000275E+00 + 3.360006E+01 2 4 1.458945E+04 1.619874E+01 + 3.360006E+01 3 3 2.288165E+03 2.074917E+02 + 3.360006E+01 4 2 1.460593E+04 1.625585E+01 + 3.360006E+01 4 4 2.706908E+05 5.266426E+01 + 3.360006E+01 5 1 -1.038460E+04 4.656364E+01 + 3.360006E+01 5 5 8.270392E+05 4.909771E+02 + 3.360006E+01 6 6 9.092985E+05 8.204824E+00 + 3.370006E+01 1 1 2.016138E+03 4.396338E+00 + 3.370006E+01 1 5 -1.036684E+04 4.638142E+01 + 3.370006E+01 2 2 2.287520E+03 4.966541E+00 + 3.370006E+01 2 4 1.458894E+04 1.608651E+01 + 3.370006E+01 3 3 2.288650E+03 2.075475E+02 + 3.370006E+01 4 2 1.460541E+04 1.614312E+01 + 3.370006E+01 4 4 2.706893E+05 5.229510E+01 + 3.370006E+01 5 1 -1.038457E+04 4.627055E+01 + 3.370006E+01 5 5 8.270355E+05 4.880962E+02 + 3.370006E+01 6 6 9.092703E+05 8.084464E+00 + 3.380006E+01 1 1 2.016045E+03 4.367103E+00 + 3.380006E+01 1 5 -1.036684E+04 4.609216E+01 + 3.380006E+01 2 2 2.287403E+03 4.933120E+00 + 3.380006E+01 2 4 1.458843E+04 1.597518E+01 + 3.380006E+01 3 3 2.289120E+03 2.076039E+02 + 3.380006E+01 4 2 1.460491E+04 1.603291E+01 + 3.380006E+01 4 4 2.706877E+05 5.190708E+01 + 3.380006E+01 5 1 -1.038455E+04 4.598060E+01 + 3.380006E+01 5 5 8.270350E+05 4.853094E+02 + 3.380006E+01 6 6 9.092412E+05 7.976162E+00 + 3.390005E+01 1 1 2.015949E+03 4.338196E+00 + 3.390005E+01 1 5 -1.036685E+04 4.580481E+01 + 3.390005E+01 2 2 2.287287E+03 4.900265E+00 + 3.390005E+01 2 4 1.458795E+04 1.586637E+01 + 3.390005E+01 3 3 2.289604E+03 2.076568E+02 + 3.390005E+01 4 2 1.460442E+04 1.592403E+01 + 3.390005E+01 4 4 2.706852E+05 5.156547E+01 + 3.390005E+01 5 1 -1.038453E+04 4.569720E+01 + 3.390005E+01 5 5 8.270338E+05 4.825604E+02 + 3.390005E+01 6 6 9.092121E+05 7.871105E+00 + 3.400005E+01 1 1 2.015856E+03 4.309593E+00 + 3.400005E+01 1 5 -1.036685E+04 4.552005E+01 + 3.400005E+01 2 2 2.287164E+03 4.867426E+00 + 3.400005E+01 2 4 1.458746E+04 1.575765E+01 + 3.400005E+01 3 3 2.290076E+03 2.077110E+02 + 3.400005E+01 4 2 1.460389E+04 1.581393E+01 + 3.400005E+01 4 4 2.706827E+05 5.119024E+01 + 3.400005E+01 5 1 -1.038452E+04 4.541109E+01 + 3.400005E+01 5 5 8.270326E+05 4.797548E+02 + 3.400005E+01 6 6 9.091851E+05 7.758340E+00 + 3.410005E+01 1 1 2.015768E+03 4.281193E+00 + 3.410005E+01 1 5 -1.036686E+04 4.523862E+01 + 3.410005E+01 2 2 2.287047E+03 4.835074E+00 + 3.410005E+01 2 4 1.458695E+04 1.565111E+01 + 3.410005E+01 3 3 2.290538E+03 2.077658E+02 + 3.410005E+01 4 2 1.460339E+04 1.570616E+01 + 3.410005E+01 4 4 2.706812E+05 5.084045E+01 + 3.410005E+01 5 1 -1.038454E+04 4.513220E+01 + 3.410005E+01 5 5 8.270311E+05 4.770114E+02 + 3.410005E+01 6 6 9.091584E+05 7.683731E+00 + 3.420005E+01 1 1 2.015675E+03 4.253048E+00 + 3.420005E+01 1 5 -1.036686E+04 4.495928E+01 + 3.420005E+01 2 2 2.286929E+03 4.803030E+00 + 3.420005E+01 2 4 1.458647E+04 1.554398E+01 + 3.420005E+01 3 3 2.291025E+03 2.078207E+02 + 3.420005E+01 4 2 1.460291E+04 1.560094E+01 + 3.420005E+01 4 4 2.706788E+05 5.048122E+01 + 3.420005E+01 5 1 -1.038451E+04 4.485680E+01 + 3.420005E+01 5 5 8.270290E+05 4.742709E+02 + 3.420005E+01 6 6 9.091312E+05 7.576797E+00 + 3.430005E+01 1 1 2.015585E+03 4.225290E+00 + 3.430005E+01 1 5 -1.036684E+04 4.468171E+01 + 3.430005E+01 2 2 2.286815E+03 4.771332E+00 + 3.430005E+01 2 4 1.458599E+04 1.543985E+01 + 3.430005E+01 3 3 2.291477E+03 2.078787E+02 + 3.430005E+01 4 2 1.460240E+04 1.549469E+01 + 3.430005E+01 4 4 2.706766E+05 5.015277E+01 + 3.430005E+01 5 1 -1.038451E+04 4.457838E+01 + 3.430005E+01 5 5 8.270272E+05 4.715522E+02 + 3.430005E+01 6 6 9.091040E+05 7.477554E+00 + 3.440005E+01 1 1 2.015496E+03 4.197728E+00 + 3.440005E+01 1 5 -1.036685E+04 4.440840E+01 + 3.440005E+01 2 2 2.286698E+03 4.739777E+00 + 3.440005E+01 2 4 1.458552E+04 1.533499E+01 + 3.440005E+01 3 3 2.291962E+03 2.079289E+02 + 3.440005E+01 4 2 1.460196E+04 1.538827E+01 + 3.440005E+01 4 4 2.706739E+05 4.978912E+01 + 3.440005E+01 5 1 -1.038449E+04 4.430622E+01 + 3.440005E+01 5 5 8.270241E+05 4.688404E+02 + 3.440005E+01 6 6 9.090772E+05 7.395940E+00 + 3.450005E+01 1 1 2.015405E+03 4.170412E+00 + 3.450005E+01 1 5 -1.036687E+04 4.413768E+01 + 3.450005E+01 2 2 2.286585E+03 4.708874E+00 + 3.450005E+01 2 4 1.458503E+04 1.523254E+01 + 3.450005E+01 3 3 2.292417E+03 2.079803E+02 + 3.450005E+01 4 2 1.460149E+04 1.528508E+01 + 3.450005E+01 4 4 2.706719E+05 4.945317E+01 + 3.450005E+01 5 1 -1.038447E+04 4.403661E+01 + 3.450005E+01 5 5 8.270231E+05 4.661466E+02 + 3.450005E+01 6 6 9.090508E+05 7.301067E+00 + 3.460004E+01 1 1 2.015315E+03 4.143480E+00 + 3.460004E+01 1 5 -1.036686E+04 4.386974E+01 + 3.460004E+01 2 2 2.286471E+03 4.678228E+00 + 3.460004E+01 2 4 1.458455E+04 1.513015E+01 + 3.460004E+01 3 3 2.292882E+03 2.080340E+02 + 3.460004E+01 4 2 1.460100E+04 1.518415E+01 + 3.460004E+01 4 4 2.706701E+05 4.910672E+01 + 3.460004E+01 5 1 -1.038452E+04 4.376566E+01 + 3.460004E+01 5 5 8.270216E+05 4.635054E+02 + 3.460004E+01 6 6 9.090237E+05 7.195186E+00 + 3.470004E+01 1 1 2.015227E+03 4.116714E+00 + 3.470004E+01 1 5 -1.036687E+04 4.360286E+01 + 3.470004E+01 2 2 2.286358E+03 4.647609E+00 + 3.470004E+01 2 4 1.458411E+04 1.502911E+01 + 3.470004E+01 3 3 2.293344E+03 2.080855E+02 + 3.470004E+01 4 2 1.460052E+04 1.508169E+01 + 3.470004E+01 4 4 2.706681E+05 4.875842E+01 + 3.470004E+01 5 1 -1.038448E+04 4.350167E+01 + 3.470004E+01 5 5 8.270191E+05 4.608852E+02 + 3.470004E+01 6 6 9.089982E+05 7.106136E+00 + 3.480004E+01 1 1 2.015142E+03 4.090320E+00 + 3.480004E+01 1 5 -1.036687E+04 4.333912E+01 + 3.480004E+01 2 2 2.286249E+03 4.617640E+00 + 3.480004E+01 2 4 1.458365E+04 1.492969E+01 + 3.480004E+01 3 3 2.293805E+03 2.081361E+02 + 3.480004E+01 4 2 1.460007E+04 1.498302E+01 + 3.480004E+01 4 4 2.706668E+05 4.842900E+01 + 3.480004E+01 5 1 -1.038448E+04 4.323824E+01 + 3.480004E+01 5 5 8.270191E+05 4.582971E+02 + 3.480004E+01 6 6 9.089728E+05 7.022690E+00 + 3.490004E+01 1 1 2.015057E+03 4.064059E+00 + 3.490004E+01 1 5 -1.036686E+04 4.307823E+01 + 3.490004E+01 2 2 2.286138E+03 4.587818E+00 + 3.490004E+01 2 4 1.458317E+04 1.483146E+01 + 3.490004E+01 3 3 2.294267E+03 2.081891E+02 + 3.490004E+01 4 2 1.459957E+04 1.488393E+01 + 3.490004E+01 4 4 2.706646E+05 4.811267E+01 + 3.490004E+01 5 1 -1.038453E+04 4.297769E+01 + 3.490004E+01 5 5 8.270183E+05 4.556540E+02 + 3.490004E+01 6 6 9.089462E+05 6.917991E+00 + 3.500004E+01 1 1 2.014974E+03 4.038242E+00 + 3.500004E+01 1 5 -1.036686E+04 4.281962E+01 + 3.500004E+01 2 2 2.286031E+03 4.558277E+00 + 3.500004E+01 2 4 1.458272E+04 1.473320E+01 + 3.500004E+01 3 3 2.294720E+03 2.082394E+02 + 3.500004E+01 4 2 1.459917E+04 1.478656E+01 + 3.500004E+01 4 4 2.706616E+05 4.778054E+01 + 3.500004E+01 5 1 -1.038451E+04 4.272221E+01 + 3.500004E+01 5 5 8.270163E+05 4.531314E+02 + 3.500004E+01 6 6 9.089202E+05 6.880600E+00 + 3.510004E+01 1 1 2.014890E+03 4.012558E+00 + 3.510004E+01 1 5 -1.036687E+04 4.256192E+01 + 3.510004E+01 2 2 2.285925E+03 4.529027E+00 + 3.510004E+01 2 4 1.458226E+04 1.463627E+01 + 3.510004E+01 3 3 2.295181E+03 2.082935E+02 + 3.510004E+01 4 2 1.459873E+04 1.468997E+01 + 3.510004E+01 4 4 2.706599E+05 4.745867E+01 + 3.510004E+01 5 1 -1.038449E+04 4.246300E+01 + 3.510004E+01 5 5 8.270154E+05 4.506443E+02 + 3.510004E+01 6 6 9.088964E+05 6.768374E+00 + 3.520004E+01 1 1 2.014806E+03 3.987145E+00 + 3.520004E+01 1 5 -1.036688E+04 4.230813E+01 + 3.520004E+01 2 2 2.285819E+03 4.500180E+00 + 3.520004E+01 2 4 1.458183E+04 1.454078E+01 + 3.520004E+01 3 3 2.295638E+03 2.083421E+02 + 3.520004E+01 4 2 1.459829E+04 1.459465E+01 + 3.520004E+01 4 4 2.706578E+05 4.714349E+01 + 3.520004E+01 5 1 -1.038453E+04 4.221143E+01 + 3.520004E+01 5 5 8.270118E+05 4.480451E+02 + 3.520004E+01 6 6 9.088716E+05 6.701797E+00 + 3.530003E+01 1 1 2.014721E+03 3.961967E+00 + 3.530003E+01 1 5 -1.036688E+04 4.205690E+01 + 3.530003E+01 2 2 2.285710E+03 4.471429E+00 + 3.530003E+01 2 4 1.458140E+04 1.444557E+01 + 3.530003E+01 3 3 2.296075E+03 2.083899E+02 + 3.530003E+01 4 2 1.459782E+04 1.449875E+01 + 3.530003E+01 4 4 2.706565E+05 4.682458E+01 + 3.530003E+01 5 1 -1.038452E+04 4.196109E+01 + 3.530003E+01 5 5 8.270114E+05 4.454631E+02 + 3.530003E+01 6 6 9.088451E+05 6.628009E+00 + 3.540003E+01 1 1 2.014641E+03 3.937112E+00 + 3.540003E+01 1 5 -1.036688E+04 4.180603E+01 + 3.540003E+01 2 2 2.285606E+03 4.443066E+00 + 3.540003E+01 2 4 1.458094E+04 1.435173E+01 + 3.540003E+01 3 3 2.296527E+03 2.084387E+02 + 3.540003E+01 4 2 1.459735E+04 1.440475E+01 + 3.540003E+01 4 4 2.706543E+05 4.650591E+01 + 3.540003E+01 5 1 -1.038454E+04 4.170706E+01 + 3.540003E+01 5 5 8.270109E+05 4.429214E+02 + 3.540003E+01 6 6 9.088219E+05 6.531374E+00 + 3.550003E+01 1 1 2.014556E+03 3.912279E+00 + 3.550003E+01 1 5 -1.036689E+04 4.155991E+01 + 3.550003E+01 2 2 2.285500E+03 4.415036E+00 + 3.550003E+01 2 4 1.458051E+04 1.425879E+01 + 3.550003E+01 3 3 2.296977E+03 2.084841E+02 + 3.550003E+01 4 2 1.459695E+04 1.431260E+01 + 3.550003E+01 4 4 2.706526E+05 4.621085E+01 + 3.550003E+01 5 1 -1.038454E+04 4.146176E+01 + 3.550003E+01 5 5 8.270087E+05 4.403772E+02 + 3.550003E+01 6 6 9.087980E+05 6.446043E+00 + 3.560003E+01 1 1 2.014475E+03 3.887846E+00 + 3.560003E+01 1 5 -1.036690E+04 4.131449E+01 + 3.560003E+01 2 2 2.285396E+03 4.387096E+00 + 3.560003E+01 2 4 1.458007E+04 1.416779E+01 + 3.560003E+01 3 3 2.297422E+03 2.085316E+02 + 3.560003E+01 4 2 1.459651E+04 1.421849E+01 + 3.560003E+01 4 4 2.706507E+05 4.590120E+01 + 3.560003E+01 5 1 -1.038455E+04 4.121673E+01 + 3.560003E+01 5 5 8.270053E+05 4.379384E+02 + 3.560003E+01 6 6 9.087743E+05 6.395988E+00 + 3.570003E+01 1 1 2.014398E+03 3.863588E+00 + 3.570003E+01 1 5 -1.036689E+04 4.107110E+01 + 3.570003E+01 2 2 2.285297E+03 4.359519E+00 + 3.570003E+01 2 4 1.457967E+04 1.407619E+01 + 3.570003E+01 3 3 2.297862E+03 2.085768E+02 + 3.570003E+01 4 2 1.459609E+04 1.412744E+01 + 3.570003E+01 4 4 2.706492E+05 4.560065E+01 + 3.570003E+01 5 1 -1.038456E+04 4.097281E+01 + 3.570003E+01 5 5 8.270068E+05 4.355299E+02 + 3.570003E+01 6 6 9.087491E+05 6.296206E+00 + 3.580003E+01 1 1 2.014319E+03 3.839559E+00 + 3.580003E+01 1 5 -1.036694E+04 4.082942E+01 + 3.580003E+01 2 2 2.285198E+03 4.332125E+00 + 3.580003E+01 2 4 1.457925E+04 1.398566E+01 + 3.580003E+01 3 3 2.298314E+03 2.086242E+02 + 3.580003E+01 4 2 1.459565E+04 1.403448E+01 + 3.580003E+01 4 4 2.706472E+05 4.530075E+01 + 3.580003E+01 5 1 -1.038456E+04 4.073407E+01 + 3.580003E+01 5 5 8.270059E+05 4.330670E+02 + 3.580003E+01 6 6 9.087256E+05 6.223383E+00 + 3.590002E+01 1 1 2.014238E+03 3.815865E+00 + 3.590002E+01 1 5 -1.036691E+04 4.059029E+01 + 3.590002E+01 2 2 2.285099E+03 4.305130E+00 + 3.590002E+01 2 4 1.457883E+04 1.389585E+01 + 3.590002E+01 3 3 2.298744E+03 2.086712E+02 + 3.590002E+01 4 2 1.459520E+04 1.394486E+01 + 3.590002E+01 4 4 2.706457E+05 4.501206E+01 + 3.590002E+01 5 1 -1.038456E+04 4.049460E+01 + 3.590002E+01 5 5 8.270036E+05 4.307480E+02 + 3.590002E+01 6 6 9.087024E+05 6.137192E+00 + 3.600002E+01 1 1 2.014161E+03 3.792371E+00 + 3.600002E+01 1 5 -1.036691E+04 4.035513E+01 + 3.600002E+01 2 2 2.284994E+03 4.278384E+00 + 3.600002E+01 2 4 1.457840E+04 1.380830E+01 + 3.600002E+01 3 3 2.299196E+03 2.087150E+02 + 3.600002E+01 4 2 1.459481E+04 1.385685E+01 + 3.600002E+01 4 4 2.706433E+05 4.471947E+01 + 3.600002E+01 5 1 -1.038454E+04 4.025945E+01 + 3.600002E+01 5 5 8.270007E+05 4.284082E+02 + 3.600002E+01 6 6 9.086797E+05 6.051591E+00 + 3.610002E+01 1 1 2.014086E+03 3.769116E+00 + 3.610002E+01 1 5 -1.036692E+04 4.011861E+01 + 3.610002E+01 2 2 2.284889E+03 4.251763E+00 + 3.610002E+01 2 4 1.457801E+04 1.371976E+01 + 3.610002E+01 3 3 2.299630E+03 2.087659E+02 + 3.610002E+01 4 2 1.459439E+04 1.376857E+01 + 3.610002E+01 4 4 2.706420E+05 4.443511E+01 + 3.610002E+01 5 1 -1.038457E+04 4.002705E+01 + 3.610002E+01 5 5 8.269984E+05 4.259442E+02 + 3.610002E+01 6 6 9.086563E+05 5.992987E+00 + 3.620002E+01 1 1 2.014006E+03 3.746111E+00 + 3.620002E+01 1 5 -1.036692E+04 3.988753E+01 + 3.620002E+01 2 2 2.284796E+03 4.225507E+00 + 3.620002E+01 2 4 1.457761E+04 1.363379E+01 + 3.620002E+01 3 3 2.300075E+03 2.088064E+02 + 3.620002E+01 4 2 1.459399E+04 1.368159E+01 + 3.620002E+01 4 4 2.706406E+05 4.413845E+01 + 3.620002E+01 5 1 -1.038455E+04 3.979681E+01 + 3.620002E+01 5 5 8.269968E+05 4.236597E+02 + 3.620002E+01 6 6 9.086326E+05 5.921138E+00 + 3.630002E+01 1 1 2.013929E+03 3.723092E+00 + 3.630002E+01 1 5 -1.036695E+04 3.965751E+01 + 3.630002E+01 2 2 2.284698E+03 4.199479E+00 + 3.630002E+01 2 4 1.457719E+04 1.354688E+01 + 3.630002E+01 3 3 2.300512E+03 2.088537E+02 + 3.630002E+01 4 2 1.459358E+04 1.359741E+01 + 3.630002E+01 4 4 2.706387E+05 4.384367E+01 + 3.630002E+01 5 1 -1.038454E+04 3.956541E+01 + 3.630002E+01 5 5 8.269961E+05 4.213336E+02 + 3.630002E+01 6 6 9.086108E+05 5.842680E+00 + 3.640002E+01 1 1 2.013854E+03 3.700585E+00 + 3.640002E+01 1 5 -1.036697E+04 3.942788E+01 + 3.640002E+01 2 2 2.284603E+03 4.173742E+00 + 3.640002E+01 2 4 1.457679E+04 1.346271E+01 + 3.640002E+01 3 3 2.300946E+03 2.088989E+02 + 3.640002E+01 4 2 1.459318E+04 1.351140E+01 + 3.640002E+01 4 4 2.706373E+05 4.358760E+01 + 3.640002E+01 5 1 -1.038452E+04 3.933470E+01 + 3.640002E+01 5 5 8.269940E+05 4.189568E+02 + 3.640002E+01 6 6 9.085887E+05 5.776129E+00 + 3.650002E+01 1 1 2.013779E+03 3.678185E+00 + 3.650002E+01 1 5 -1.036697E+04 3.920206E+01 + 3.650002E+01 2 2 2.284505E+03 4.148209E+00 + 3.650002E+01 2 4 1.457640E+04 1.337872E+01 + 3.650002E+01 3 3 2.301379E+03 2.089395E+02 + 3.650002E+01 4 2 1.459278E+04 1.342655E+01 + 3.650002E+01 4 4 2.706354E+05 4.330577E+01 + 3.650002E+01 5 1 -1.038458E+04 3.911081E+01 + 3.650002E+01 5 5 8.269932E+05 4.167011E+02 + 3.650002E+01 6 6 9.085653E+05 5.710447E+00 + 3.660001E+01 1 1 2.013702E+03 3.655786E+00 + 3.660001E+01 1 5 -1.036700E+04 3.897875E+01 + 3.660001E+01 2 2 2.284407E+03 4.122929E+00 + 3.660001E+01 2 4 1.457599E+04 1.329549E+01 + 3.660001E+01 3 3 2.301822E+03 2.089806E+02 + 3.660001E+01 4 2 1.459241E+04 1.334303E+01 + 3.660001E+01 4 4 2.706338E+05 4.303092E+01 + 3.660001E+01 5 1 -1.038457E+04 3.888433E+01 + 3.660001E+01 5 5 8.269909E+05 4.144677E+02 + 3.660001E+01 6 6 9.085432E+05 5.643402E+00 + 3.670001E+01 1 1 2.013626E+03 3.633783E+00 + 3.670001E+01 1 5 -1.036702E+04 3.875596E+01 + 3.670001E+01 2 2 2.284314E+03 4.097974E+00 + 3.670001E+01 2 4 1.457557E+04 1.321278E+01 + 3.670001E+01 3 3 2.302231E+03 2.090245E+02 + 3.670001E+01 4 2 1.459203E+04 1.326114E+01 + 3.670001E+01 4 4 2.706321E+05 4.275087E+01 + 3.670001E+01 5 1 -1.038457E+04 3.866187E+01 + 3.670001E+01 5 5 8.269919E+05 4.121606E+02 + 3.670001E+01 6 6 9.085218E+05 5.589066E+00 + 3.680001E+01 1 1 2.013556E+03 3.612016E+00 + 3.680001E+01 1 5 -1.036702E+04 3.853417E+01 + 3.680001E+01 2 2 2.284221E+03 4.073206E+00 + 3.680001E+01 2 4 1.457519E+04 1.313062E+01 + 3.680001E+01 3 3 2.302670E+03 2.090670E+02 + 3.680001E+01 4 2 1.459163E+04 1.317922E+01 + 3.680001E+01 4 4 2.706300E+05 4.247728E+01 + 3.680001E+01 5 1 -1.038457E+04 3.844415E+01 + 3.680001E+01 5 5 8.269908E+05 4.100852E+02 + 3.680001E+01 6 6 9.084987E+05 5.498926E+00 + 3.690001E+01 1 1 2.013482E+03 3.590358E+00 + 3.690001E+01 1 5 -1.036704E+04 3.831614E+01 + 3.690001E+01 2 2 2.284130E+03 4.048556E+00 + 3.690001E+01 2 4 1.457481E+04 1.305051E+01 + 3.690001E+01 3 3 2.303093E+03 2.091085E+02 + 3.690001E+01 4 2 1.459121E+04 1.309833E+01 + 3.690001E+01 4 4 2.706278E+05 4.222427E+01 + 3.690001E+01 5 1 -1.038462E+04 3.822642E+01 + 3.690001E+01 5 5 8.269888E+05 4.077679E+02 + 3.690001E+01 6 6 9.084771E+05 5.438470E+00 + 3.700001E+01 1 1 2.013411E+03 3.568935E+00 + 3.700001E+01 1 5 -1.036705E+04 3.809861E+01 + 3.700001E+01 2 2 2.284034E+03 4.024170E+00 + 3.700001E+01 2 4 1.457443E+04 1.296999E+01 + 3.700001E+01 3 3 2.303524E+03 2.091532E+02 + 3.700001E+01 4 2 1.459083E+04 1.301700E+01 + 3.700001E+01 4 4 2.706268E+05 4.195294E+01 + 3.700001E+01 5 1 -1.038460E+04 3.800803E+01 + 3.700001E+01 5 5 8.269881E+05 4.056193E+02 + 3.700001E+01 6 6 9.084576E+05 5.370837E+00 + 3.710001E+01 1 1 2.013341E+03 3.547757E+00 + 3.710001E+01 1 5 -1.036708E+04 3.788406E+01 + 3.710001E+01 2 2 2.283948E+03 3.999992E+00 + 3.710001E+01 2 4 1.457402E+04 1.289058E+01 + 3.710001E+01 3 3 2.303947E+03 2.091963E+02 + 3.710001E+01 4 2 1.459046E+04 1.293688E+01 + 3.710001E+01 4 4 2.706248E+05 4.168304E+01 + 3.710001E+01 5 1 -1.038466E+04 3.779264E+01 + 3.710001E+01 5 5 8.269868E+05 4.035041E+02 + 3.710001E+01 6 6 9.084366E+05 5.309042E+00 + 3.720000E+01 1 1 2.013268E+03 3.526645E+00 + 3.720000E+01 1 5 -1.036708E+04 3.767033E+01 + 3.720000E+01 2 2 2.283854E+03 3.976116E+00 + 3.720000E+01 2 4 1.457367E+04 1.281155E+01 + 3.720000E+01 3 3 2.304385E+03 2.092408E+02 + 3.720000E+01 4 2 1.459005E+04 1.285758E+01 + 3.720000E+01 4 4 2.706232E+05 4.142688E+01 + 3.720000E+01 5 1 -1.038470E+04 3.758187E+01 + 3.720000E+01 5 5 8.269874E+05 4.013394E+02 + 3.720000E+01 6 6 9.084147E+05 5.268166E+00 + 3.730000E+01 1 1 2.013203E+03 3.505867E+00 + 3.730000E+01 1 5 -1.036710E+04 3.745911E+01 + 3.730000E+01 2 2 2.283767E+03 3.952397E+00 + 3.730000E+01 2 4 1.457329E+04 1.273373E+01 + 3.730000E+01 3 3 2.304789E+03 2.092828E+02 + 3.730000E+01 4 2 1.458973E+04 1.277789E+01 + 3.730000E+01 4 4 2.706211E+05 4.117779E+01 + 3.730000E+01 5 1 -1.038467E+04 3.736903E+01 + 3.730000E+01 5 5 8.269850E+05 3.992006E+02 + 3.730000E+01 6 6 9.083945E+05 5.198104E+00 + 3.740000E+01 1 1 2.013130E+03 3.485213E+00 + 3.740000E+01 1 5 -1.036711E+04 3.724977E+01 + 3.740000E+01 2 2 2.283678E+03 3.928882E+00 + 3.740000E+01 2 4 1.457293E+04 1.265645E+01 + 3.740000E+01 3 3 2.305208E+03 2.093207E+02 + 3.740000E+01 4 2 1.458937E+04 1.270025E+01 + 3.740000E+01 4 4 2.706199E+05 4.090831E+01 + 3.740000E+01 5 1 -1.038471E+04 3.716008E+01 + 3.740000E+01 5 5 8.269840E+05 3.971006E+02 + 3.740000E+01 6 6 9.083726E+05 5.127429E+00 + 3.750000E+01 1 1 2.013062E+03 3.464626E+00 + 3.750000E+01 1 5 -1.036713E+04 3.704184E+01 + 3.750000E+01 2 2 2.283589E+03 3.905577E+00 + 3.750000E+01 2 4 1.457256E+04 1.257989E+01 + 3.750000E+01 3 3 2.305638E+03 2.093643E+02 + 3.750000E+01 4 2 1.458899E+04 1.262277E+01 + 3.750000E+01 4 4 2.706178E+05 4.067010E+01 + 3.750000E+01 5 1 -1.038468E+04 3.695582E+01 + 3.750000E+01 5 5 8.269815E+05 3.950205E+02 + 3.750000E+01 6 6 9.083530E+05 5.055467E+00 + 3.760000E+01 1 1 2.012994E+03 3.444397E+00 + 3.760000E+01 1 5 -1.036714E+04 3.683575E+01 + 3.760000E+01 2 2 2.283505E+03 3.882526E+00 + 3.760000E+01 2 4 1.457218E+04 1.250433E+01 + 3.760000E+01 3 3 2.306049E+03 2.094059E+02 + 3.760000E+01 4 2 1.458862E+04 1.254721E+01 + 3.760000E+01 4 4 2.706166E+05 4.042308E+01 + 3.760000E+01 5 1 -1.038471E+04 3.674814E+01 + 3.760000E+01 5 5 8.269804E+05 3.929808E+02 + 3.760000E+01 6 6 9.083321E+05 5.009821E+00 + 3.770000E+01 1 1 2.012924E+03 3.424435E+00 + 3.770000E+01 1 5 -1.036716E+04 3.663164E+01 + 3.770000E+01 2 2 2.283417E+03 3.859690E+00 + 3.770000E+01 2 4 1.457186E+04 1.242942E+01 + 3.770000E+01 3 3 2.306469E+03 2.094432E+02 + 3.770000E+01 4 2 1.458825E+04 1.247189E+01 + 3.770000E+01 4 4 2.706153E+05 4.017995E+01 + 3.770000E+01 5 1 -1.038473E+04 3.654385E+01 + 3.770000E+01 5 5 8.269794E+05 3.909111E+02 + 3.770000E+01 6 6 9.083129E+05 4.935872E+00 + 3.780000E+01 1 1 2.012855E+03 3.404402E+00 + 3.780000E+01 1 5 -1.036719E+04 3.642873E+01 + 3.780000E+01 2 2 2.283328E+03 3.837123E+00 + 3.780000E+01 2 4 1.457149E+04 1.235525E+01 + 3.780000E+01 3 3 2.306896E+03 2.094768E+02 + 3.780000E+01 4 2 1.458791E+04 1.239871E+01 + 3.780000E+01 4 4 2.706136E+05 3.994192E+01 + 3.780000E+01 5 1 -1.038474E+04 3.633950E+01 + 3.780000E+01 5 5 8.269797E+05 3.887933E+02 + 3.780000E+01 6 6 9.082928E+05 4.908989E+00 + 3.789999E+01 1 1 2.012790E+03 3.384700E+00 + 3.789999E+01 1 5 -1.036722E+04 3.622715E+01 + 3.789999E+01 2 2 2.283242E+03 3.814688E+00 + 3.789999E+01 2 4 1.457112E+04 1.228125E+01 + 3.789999E+01 3 3 2.307300E+03 2.095214E+02 + 3.789999E+01 4 2 1.458755E+04 1.232306E+01 + 3.789999E+01 4 4 2.706118E+05 3.969556E+01 + 3.789999E+01 5 1 -1.038474E+04 3.613874E+01 + 3.789999E+01 5 5 8.269791E+05 3.867734E+02 + 3.789999E+01 6 6 9.082722E+05 4.846871E+00 + 3.799999E+01 1 1 2.012723E+03 3.365166E+00 + 3.799999E+01 1 5 -1.036720E+04 3.602869E+01 + 3.799999E+01 2 2 2.283159E+03 3.792426E+00 + 3.799999E+01 2 4 1.457075E+04 1.220757E+01 + 3.799999E+01 3 3 2.307712E+03 2.095591E+02 + 3.799999E+01 4 2 1.458715E+04 1.225121E+01 + 3.799999E+01 4 4 2.706106E+05 3.944532E+01 + 3.799999E+01 5 1 -1.038480E+04 3.594152E+01 + 3.799999E+01 5 5 8.269774E+05 3.848085E+02 + 3.799999E+01 6 6 9.082527E+05 4.783886E+00 + 3.809999E+01 1 1 2.012658E+03 3.345552E+00 + 3.809999E+01 1 5 -1.036724E+04 3.583174E+01 + 3.809999E+01 2 2 2.283075E+03 3.770509E+00 + 3.809999E+01 2 4 1.457042E+04 1.213552E+01 + 3.809999E+01 3 3 2.308125E+03 2.095937E+02 + 3.809999E+01 4 2 1.458683E+04 1.217951E+01 + 3.809999E+01 4 4 2.706095E+05 3.921399E+01 + 3.809999E+01 5 1 -1.038483E+04 3.574688E+01 + 3.809999E+01 5 5 8.269768E+05 3.828458E+02 + 3.809999E+01 6 6 9.082335E+05 4.741799E+00 + 3.819999E+01 1 1 2.012592E+03 3.326407E+00 + 3.819999E+01 1 5 -1.036726E+04 3.563541E+01 + 3.819999E+01 2 2 2.282995E+03 3.748651E+00 + 3.819999E+01 2 4 1.457009E+04 1.206382E+01 + 3.819999E+01 3 3 2.308525E+03 2.096333E+02 + 3.819999E+01 4 2 1.458648E+04 1.210816E+01 + 3.819999E+01 4 4 2.706083E+05 3.897776E+01 + 3.819999E+01 5 1 -1.038485E+04 3.555049E+01 + 3.819999E+01 5 5 8.269772E+05 3.807567E+02 + 3.819999E+01 6 6 9.082136E+05 4.687849E+00 + 3.829999E+01 1 1 2.012526E+03 3.307404E+00 + 3.829999E+01 1 5 -1.036724E+04 3.544145E+01 + 3.829999E+01 2 2 2.282908E+03 3.726984E+00 + 3.829999E+01 2 4 1.456975E+04 1.199241E+01 + 3.829999E+01 3 3 2.308938E+03 2.096743E+02 + 3.829999E+01 4 2 1.458615E+04 1.203561E+01 + 3.829999E+01 4 4 2.706067E+05 3.873753E+01 + 3.829999E+01 5 1 -1.038487E+04 3.535653E+01 + 3.829999E+01 5 5 8.269764E+05 3.789005E+02 + 3.829999E+01 6 6 9.081937E+05 4.622365E+00 + 3.839999E+01 1 1 2.012460E+03 3.288520E+00 + 3.839999E+01 1 5 -1.036725E+04 3.524835E+01 + 3.839999E+01 2 2 2.282827E+03 3.705519E+00 + 3.839999E+01 2 4 1.456940E+04 1.192247E+01 + 3.839999E+01 3 3 2.309349E+03 2.097117E+02 + 3.839999E+01 4 2 1.458581E+04 1.196471E+01 + 3.839999E+01 4 4 2.706051E+05 3.850977E+01 + 3.839999E+01 5 1 -1.038487E+04 3.516337E+01 + 3.839999E+01 5 5 8.269758E+05 3.769133E+02 + 3.839999E+01 6 6 9.081760E+05 4.576396E+00 + 3.849998E+01 1 1 2.012400E+03 3.269788E+00 + 3.849998E+01 1 5 -1.036728E+04 3.505717E+01 + 3.849998E+01 2 2 2.282749E+03 3.684276E+00 + 3.849998E+01 2 4 1.456908E+04 1.185255E+01 + 3.849998E+01 3 3 2.309770E+03 2.097465E+02 + 3.849998E+01 4 2 1.458546E+04 1.189483E+01 + 3.849998E+01 4 4 2.706033E+05 3.826764E+01 + 3.849998E+01 5 1 -1.038490E+04 3.497512E+01 + 3.849998E+01 5 5 8.269746E+05 3.749321E+02 + 3.849998E+01 6 6 9.081566E+05 4.542968E+00 + 3.859998E+01 1 1 2.012333E+03 3.251281E+00 + 3.859998E+01 1 5 -1.036730E+04 3.486726E+01 + 3.859998E+01 2 2 2.282667E+03 3.663255E+00 + 3.859998E+01 2 4 1.456875E+04 1.178283E+01 + 3.859998E+01 3 3 2.310175E+03 2.097849E+02 + 3.859998E+01 4 2 1.458510E+04 1.182453E+01 + 3.859998E+01 4 4 2.706021E+05 3.803108E+01 + 3.859998E+01 5 1 -1.038491E+04 3.478324E+01 + 3.859998E+01 5 5 8.269734E+05 3.729440E+02 + 3.859998E+01 6 6 9.081362E+05 4.490300E+00 + 3.869998E+01 1 1 2.012272E+03 3.232926E+00 + 3.869998E+01 1 5 -1.036729E+04 3.467992E+01 + 3.869998E+01 2 2 2.282588E+03 3.642359E+00 + 3.869998E+01 2 4 1.456842E+04 1.171539E+01 + 3.869998E+01 3 3 2.310576E+03 2.098226E+02 + 3.869998E+01 4 2 1.458475E+04 1.175802E+01 + 3.869998E+01 4 4 2.706006E+05 3.779966E+01 + 3.869998E+01 5 1 -1.038495E+04 3.459625E+01 + 3.869998E+01 5 5 8.269721E+05 3.711460E+02 + 3.869998E+01 6 6 9.081186E+05 4.421749E+00 + 3.879998E+01 1 1 2.012209E+03 3.214651E+00 + 3.879998E+01 1 5 -1.036732E+04 3.449369E+01 + 3.879998E+01 2 2 2.282503E+03 3.621585E+00 + 3.879998E+01 2 4 1.456807E+04 1.164711E+01 + 3.879998E+01 3 3 2.310982E+03 2.098570E+02 + 3.879998E+01 4 2 1.458442E+04 1.168894E+01 + 3.879998E+01 4 4 2.705990E+05 3.758459E+01 + 3.879998E+01 5 1 -1.038493E+04 3.441256E+01 + 3.879998E+01 5 5 8.269718E+05 3.691244E+02 + 3.879998E+01 6 6 9.081011E+05 4.378713E+00 + 3.889998E+01 1 1 2.012145E+03 3.196586E+00 + 3.889998E+01 1 5 -1.036732E+04 3.430721E+01 + 3.889998E+01 2 2 2.282424E+03 3.601162E+00 + 3.889998E+01 2 4 1.456774E+04 1.157895E+01 + 3.889998E+01 3 3 2.311388E+03 2.098934E+02 + 3.889998E+01 4 2 1.458407E+04 1.162211E+01 + 3.889998E+01 4 4 2.705974E+05 3.737069E+01 + 3.889998E+01 5 1 -1.038494E+04 3.422789E+01 + 3.889998E+01 5 5 8.269711E+05 3.673767E+02 + 3.889998E+01 6 6 9.080827E+05 4.334402E+00 + 3.899998E+01 1 1 2.012087E+03 3.178778E+00 + 3.899998E+01 1 5 -1.036735E+04 3.412605E+01 + 3.899998E+01 2 2 2.282347E+03 3.580716E+00 + 3.899998E+01 2 4 1.456744E+04 1.151269E+01 + 3.899998E+01 3 3 2.311785E+03 2.099304E+02 + 3.899998E+01 4 2 1.458380E+04 1.155437E+01 + 3.899998E+01 4 4 2.705961E+05 3.714309E+01 + 3.899998E+01 5 1 -1.038495E+04 3.404263E+01 + 3.899998E+01 5 5 8.269695E+05 3.653286E+02 + 3.899998E+01 6 6 9.080644E+05 4.290007E+00 + 3.909998E+01 1 1 2.012023E+03 3.160982E+00 + 3.909998E+01 1 5 -1.036734E+04 3.394199E+01 + 3.909998E+01 2 2 2.282269E+03 3.560430E+00 + 3.909998E+01 2 4 1.456711E+04 1.144674E+01 + 3.909998E+01 3 3 2.312187E+03 2.099666E+02 + 3.909998E+01 4 2 1.458347E+04 1.148686E+01 + 3.909998E+01 4 4 2.705946E+05 3.693652E+01 + 3.909998E+01 5 1 -1.038495E+04 3.386298E+01 + 3.909998E+01 5 5 8.269674E+05 3.635599E+02 + 3.909998E+01 6 6 9.080466E+05 4.254579E+00 + 3.919997E+01 1 1 2.011962E+03 3.143251E+00 + 3.919997E+01 1 5 -1.036736E+04 3.376207E+01 + 3.919997E+01 2 2 2.282194E+03 3.540502E+00 + 3.919997E+01 2 4 1.456678E+04 1.138097E+01 + 3.919997E+01 3 3 2.312580E+03 2.099987E+02 + 3.919997E+01 4 2 1.458313E+04 1.141975E+01 + 3.919997E+01 4 4 2.705932E+05 3.670096E+01 + 3.919997E+01 5 1 -1.038498E+04 3.368402E+01 + 3.919997E+01 5 5 8.269670E+05 3.616775E+02 + 3.919997E+01 6 6 9.080277E+05 4.215195E+00 + 3.929997E+01 1 1 2.011903E+03 3.125883E+00 + 3.929997E+01 1 5 -1.036737E+04 3.358359E+01 + 3.929997E+01 2 2 2.282120E+03 3.520800E+00 + 3.929997E+01 2 4 1.456644E+04 1.131631E+01 + 3.929997E+01 3 3 2.312969E+03 2.100336E+02 + 3.929997E+01 4 2 1.458281E+04 1.135574E+01 + 3.929997E+01 4 4 2.705918E+05 3.649755E+01 + 3.929997E+01 5 1 -1.038500E+04 3.350385E+01 + 3.929997E+01 5 5 8.269663E+05 3.599503E+02 + 3.929997E+01 6 6 9.080109E+05 4.157808E+00 + 3.939997E+01 1 1 2.011847E+03 3.108540E+00 + 3.939997E+01 1 5 -1.036739E+04 3.340415E+01 + 3.939997E+01 2 2 2.282038E+03 3.501162E+00 + 3.939997E+01 2 4 1.456614E+04 1.125108E+01 + 3.939997E+01 3 3 2.313376E+03 2.100708E+02 + 3.939997E+01 4 2 1.458250E+04 1.129232E+01 + 3.939997E+01 4 4 2.705904E+05 3.627639E+01 + 3.939997E+01 5 1 -1.038502E+04 3.332632E+01 + 3.939997E+01 5 5 8.269655E+05 3.581561E+02 + 3.939997E+01 6 6 9.079923E+05 4.111275E+00 + 3.949997E+01 1 1 2.011782E+03 3.091426E+00 + 3.949997E+01 1 5 -1.036741E+04 3.322937E+01 + 3.949997E+01 2 2 2.281966E+03 3.481546E+00 + 3.949997E+01 2 4 1.456584E+04 1.118835E+01 + 3.949997E+01 3 3 2.313766E+03 2.101021E+02 + 3.949997E+01 4 2 1.458219E+04 1.122677E+01 + 3.949997E+01 4 4 2.705893E+05 3.608713E+01 + 3.949997E+01 5 1 -1.038504E+04 3.315043E+01 + 3.949997E+01 5 5 8.269635E+05 3.563717E+02 + 3.949997E+01 6 6 9.079751E+05 4.073586E+00 + 3.959997E+01 1 1 2.011724E+03 3.074402E+00 + 3.959997E+01 1 5 -1.036742E+04 3.305470E+01 + 3.959997E+01 2 2 2.281890E+03 3.462407E+00 + 3.959997E+01 2 4 1.456552E+04 1.112596E+01 + 3.959997E+01 3 3 2.314161E+03 2.101375E+02 + 3.959997E+01 4 2 1.458187E+04 1.116395E+01 + 3.959997E+01 4 4 2.705877E+05 3.588458E+01 + 3.959997E+01 5 1 -1.038506E+04 3.297411E+01 + 3.959997E+01 5 5 8.269639E+05 3.546119E+02 + 3.959997E+01 6 6 9.079575E+05 4.041151E+00 + 3.969997E+01 1 1 2.011666E+03 3.057555E+00 + 3.969997E+01 1 5 -1.036745E+04 3.288111E+01 + 3.969997E+01 2 2 2.281816E+03 3.443227E+00 + 3.969997E+01 2 4 1.456520E+04 1.106171E+01 + 3.969997E+01 3 3 2.314552E+03 2.101746E+02 + 3.969997E+01 4 2 1.458156E+04 1.110115E+01 + 3.969997E+01 4 4 2.705866E+05 3.565243E+01 + 3.969997E+01 5 1 -1.038508E+04 3.280614E+01 + 3.969997E+01 5 5 8.269627E+05 3.527347E+02 + 3.969997E+01 6 6 9.079406E+05 3.996453E+00 + 3.979996E+01 1 1 2.011607E+03 3.040918E+00 + 3.979996E+01 1 5 -1.036748E+04 3.270905E+01 + 3.979996E+01 2 2 2.281746E+03 3.424165E+00 + 3.979996E+01 2 4 1.456488E+04 1.100041E+01 + 3.979996E+01 3 3 2.314941E+03 2.102100E+02 + 3.979996E+01 4 2 1.458128E+04 1.103920E+01 + 3.979996E+01 4 4 2.705856E+05 3.546384E+01 + 3.979996E+01 5 1 -1.038511E+04 3.263005E+01 + 3.979996E+01 5 5 8.269610E+05 3.510912E+02 + 3.979996E+01 6 6 9.079243E+05 3.931697E+00 + 3.989996E+01 1 1 2.011553E+03 3.024139E+00 + 3.989996E+01 1 5 -1.036750E+04 3.253902E+01 + 3.989996E+01 2 2 2.281671E+03 3.405334E+00 + 3.989996E+01 2 4 1.456459E+04 1.093907E+01 + 3.989996E+01 3 3 2.315334E+03 2.102411E+02 + 3.989996E+01 4 2 1.458096E+04 1.097808E+01 + 3.989996E+01 4 4 2.705842E+05 3.526117E+01 + 3.989996E+01 5 1 -1.038511E+04 3.246190E+01 + 3.989996E+01 5 5 8.269589E+05 3.492199E+02 + 3.989996E+01 6 6 9.079063E+05 3.901466E+00 + 3.999996E+01 1 1 2.011493E+03 3.007740E+00 + 3.999996E+01 1 5 -1.036752E+04 3.236941E+01 + 3.999996E+01 2 2 2.281596E+03 3.386753E+00 + 3.999996E+01 2 4 1.456432E+04 1.087715E+01 + 3.999996E+01 3 3 2.315724E+03 2.102723E+02 + 3.999996E+01 4 2 1.458065E+04 1.091650E+01 + 3.999996E+01 4 4 2.705826E+05 3.505007E+01 + 3.999996E+01 5 1 -1.038512E+04 3.229579E+01 + 3.999996E+01 5 5 8.269584E+05 3.475764E+02 + 3.999996E+01 6 6 9.078898E+05 3.849471E+00 + 4.009996E+01 1 1 2.011437E+03 2.991410E+00 + 4.009996E+01 1 5 -1.036753E+04 3.220149E+01 + 4.009996E+01 2 2 2.281525E+03 3.368227E+00 + 4.009996E+01 2 4 1.456400E+04 1.081634E+01 + 4.009996E+01 3 3 2.316114E+03 2.103059E+02 + 4.009996E+01 4 2 1.458038E+04 1.085643E+01 + 4.009996E+01 4 4 2.705809E+05 3.484414E+01 + 4.009996E+01 5 1 -1.038514E+04 3.212786E+01 + 4.009996E+01 5 5 8.269564E+05 3.458421E+02 + 4.009996E+01 6 6 9.078736E+05 3.824381E+00 + 4.019996E+01 1 1 2.011378E+03 2.975131E+00 + 4.019996E+01 1 5 -1.036755E+04 3.203527E+01 + 4.019996E+01 2 2 2.281455E+03 3.349832E+00 + 4.019996E+01 2 4 1.456370E+04 1.075585E+01 + 4.019996E+01 3 3 2.316508E+03 2.103378E+02 + 4.019996E+01 4 2 1.458008E+04 1.079508E+01 + 4.019996E+01 4 4 2.705806E+05 3.464214E+01 + 4.019996E+01 5 1 -1.038515E+04 3.195966E+01 + 4.019996E+01 5 5 8.269543E+05 3.441451E+02 + 4.019996E+01 6 6 9.078556E+05 3.771292E+00 + 4.029996E+01 1 1 2.011323E+03 2.959233E+00 + 4.029996E+01 1 5 -1.036756E+04 3.186870E+01 + 4.029996E+01 2 2 2.281383E+03 3.331590E+00 + 4.029996E+01 2 4 1.456340E+04 1.069608E+01 + 4.029996E+01 3 3 2.316894E+03 2.103727E+02 + 4.029996E+01 4 2 1.457977E+04 1.073504E+01 + 4.029996E+01 4 4 2.705788E+05 3.445746E+01 + 4.029996E+01 5 1 -1.038517E+04 3.179680E+01 + 4.029996E+01 5 5 8.269531E+05 3.424527E+02 + 4.029996E+01 6 6 9.078409E+05 3.741815E+00 + 4.039996E+01 1 1 2.011270E+03 2.943222E+00 + 4.039996E+01 1 5 -1.036760E+04 3.170504E+01 + 4.039996E+01 2 2 2.281312E+03 3.313582E+00 + 4.039996E+01 2 4 1.456310E+04 1.063782E+01 + 4.039996E+01 3 3 2.317275E+03 2.104019E+02 + 4.039996E+01 4 2 1.457948E+04 1.067604E+01 + 4.039996E+01 4 4 2.705776E+05 3.426579E+01 + 4.039996E+01 5 1 -1.038520E+04 3.163220E+01 + 4.039996E+01 5 5 8.269516E+05 3.407807E+02 + 4.039996E+01 6 6 9.078230E+05 3.692379E+00 + 4.049995E+01 1 1 2.011215E+03 2.927410E+00 + 4.049995E+01 1 5 -1.036761E+04 3.154235E+01 + 4.049995E+01 2 2 2.281241E+03 3.295801E+00 + 4.049995E+01 2 4 1.456282E+04 1.057935E+01 + 4.049995E+01 3 3 2.317661E+03 2.104317E+02 + 4.049995E+01 4 2 1.457920E+04 1.061816E+01 + 4.049995E+01 4 4 2.705764E+05 3.407467E+01 + 4.049995E+01 5 1 -1.038521E+04 3.146976E+01 + 4.049995E+01 5 5 8.269507E+05 3.390747E+02 + 4.049995E+01 6 6 9.078081E+05 3.641167E+00 + 4.059995E+01 1 1 2.011161E+03 2.911773E+00 + 4.059995E+01 1 5 -1.036765E+04 3.138105E+01 + 4.059995E+01 2 2 2.281172E+03 3.278031E+00 + 4.059995E+01 2 4 1.456253E+04 1.052094E+01 + 4.059995E+01 3 3 2.318038E+03 2.104649E+02 + 4.059995E+01 4 2 1.457890E+04 1.056202E+01 + 4.059995E+01 4 4 2.705752E+05 3.388414E+01 + 4.059995E+01 5 1 -1.038523E+04 3.130933E+01 + 4.059995E+01 5 5 8.269500E+05 3.374234E+02 + 4.059995E+01 6 6 9.077920E+05 3.624387E+00 + 4.069995E+01 1 1 2.011105E+03 2.896175E+00 + 4.069995E+01 1 5 -1.036766E+04 3.122051E+01 + 4.069995E+01 2 2 2.281105E+03 3.260370E+00 + 4.069995E+01 2 4 1.456222E+04 1.046322E+01 + 4.069995E+01 3 3 2.318431E+03 2.104967E+02 + 4.069995E+01 4 2 1.457862E+04 1.050220E+01 + 4.069995E+01 4 4 2.705737E+05 3.368925E+01 + 4.069995E+01 5 1 -1.038527E+04 3.115114E+01 + 4.069995E+01 5 5 8.269492E+05 3.357729E+02 + 4.069995E+01 6 6 9.077761E+05 3.580951E+00 + 4.079995E+01 1 1 2.011051E+03 2.880900E+00 + 4.079995E+01 1 5 -1.036768E+04 3.106174E+01 + 4.079995E+01 2 2 2.281037E+03 3.242859E+00 + 4.079995E+01 2 4 1.456197E+04 1.040636E+01 + 4.079995E+01 3 3 2.318805E+03 2.105277E+02 + 4.079995E+01 4 2 1.457835E+04 1.044448E+01 + 4.079995E+01 4 4 2.705726E+05 3.350297E+01 + 4.079995E+01 5 1 -1.038528E+04 3.099028E+01 + 4.079995E+01 5 5 8.269483E+05 3.340829E+02 + 4.079995E+01 6 6 9.077611E+05 3.535315E+00 + 4.089995E+01 1 1 2.010996E+03 2.865503E+00 + 4.089995E+01 1 5 -1.036770E+04 3.090385E+01 + 4.089995E+01 2 2 2.280970E+03 3.225686E+00 + 4.089995E+01 2 4 1.456167E+04 1.035017E+01 + 4.089995E+01 3 3 2.319184E+03 2.105570E+02 + 4.089995E+01 4 2 1.457807E+04 1.038748E+01 + 4.089995E+01 4 4 2.705714E+05 3.332624E+01 + 4.089995E+01 5 1 -1.038528E+04 3.082990E+01 + 4.089995E+01 5 5 8.269490E+05 3.325596E+02 + 4.089995E+01 6 6 9.077447E+05 3.518167E+00 + 4.099995E+01 1 1 2.010943E+03 2.850343E+00 + 4.099995E+01 1 5 -1.036770E+04 3.074819E+01 + 4.099995E+01 2 2 2.280899E+03 3.208411E+00 + 4.099995E+01 2 4 1.456140E+04 1.029359E+01 + 4.099995E+01 3 3 2.319558E+03 2.105878E+02 + 4.099995E+01 4 2 1.457776E+04 1.033150E+01 + 4.099995E+01 4 4 2.705698E+05 3.313728E+01 + 4.099995E+01 5 1 -1.038530E+04 3.067612E+01 + 4.099995E+01 5 5 8.269471E+05 3.307766E+02 + 4.099995E+01 6 6 9.077286E+05 3.497452E+00 + 4.109995E+01 1 1 2.010892E+03 2.835345E+00 + 4.109995E+01 1 5 -1.036773E+04 3.059193E+01 + 4.109995E+01 2 2 2.280834E+03 3.191469E+00 + 4.109995E+01 2 4 1.456115E+04 1.023820E+01 + 4.109995E+01 3 3 2.319937E+03 2.106193E+02 + 4.109995E+01 4 2 1.457750E+04 1.027547E+01 + 4.109995E+01 4 4 2.705685E+05 3.296493E+01 + 4.109995E+01 5 1 -1.038534E+04 3.052301E+01 + 4.109995E+01 5 5 8.269469E+05 3.293317E+02 + 4.109995E+01 6 6 9.077132E+05 3.431105E+00 + 4.119994E+01 1 1 2.010840E+03 2.820436E+00 + 4.119994E+01 1 5 -1.036777E+04 3.043818E+01 + 4.119994E+01 2 2 2.280764E+03 3.174535E+00 + 4.119994E+01 2 4 1.456088E+04 1.018240E+01 + 4.119994E+01 3 3 2.320303E+03 2.106497E+02 + 4.119994E+01 4 2 1.457721E+04 1.022033E+01 + 4.119994E+01 4 4 2.705678E+05 3.277423E+01 + 4.119994E+01 5 1 -1.038538E+04 3.036722E+01 + 4.119994E+01 5 5 8.269467E+05 3.276874E+02 + 4.119994E+01 6 6 9.076984E+05 3.423158E+00 + 4.129994E+01 1 1 2.010787E+03 2.805636E+00 + 4.129994E+01 1 5 -1.036778E+04 3.028543E+01 + 4.129994E+01 2 2 2.280697E+03 3.157800E+00 + 4.129994E+01 2 4 1.456059E+04 1.012721E+01 + 4.129994E+01 3 3 2.320671E+03 2.106786E+02 + 4.129994E+01 4 2 1.457696E+04 1.016713E+01 + 4.129994E+01 4 4 2.705668E+05 3.258274E+01 + 4.129994E+01 5 1 -1.038539E+04 3.021600E+01 + 4.129994E+01 5 5 8.269446E+05 3.261401E+02 + 4.129994E+01 6 6 9.076834E+05 3.391908E+00 + 4.139994E+01 1 1 2.010738E+03 2.790935E+00 + 4.139994E+01 1 5 -1.036780E+04 3.013216E+01 + 4.139994E+01 2 2 2.280635E+03 3.140967E+00 + 4.139994E+01 2 4 1.456034E+04 1.007382E+01 + 4.139994E+01 3 3 2.321048E+03 2.107092E+02 + 4.139994E+01 4 2 1.457667E+04 1.010970E+01 + 4.139994E+01 4 4 2.705659E+05 3.242693E+01 + 4.139994E+01 5 1 -1.038540E+04 3.006433E+01 + 4.139994E+01 5 5 8.269430E+05 3.246499E+02 + 4.139994E+01 6 6 9.076686E+05 3.320487E+00 + 4.149994E+01 1 1 2.010685E+03 2.776349E+00 + 4.149994E+01 1 5 -1.036781E+04 2.998286E+01 + 4.149994E+01 2 2 2.280570E+03 3.124676E+00 + 4.149994E+01 2 4 1.456005E+04 1.001935E+01 + 4.149994E+01 3 3 2.321431E+03 2.107393E+02 + 4.149994E+01 4 2 1.457639E+04 1.005757E+01 + 4.149994E+01 4 4 2.705651E+05 3.223020E+01 + 4.149994E+01 5 1 -1.038540E+04 2.991556E+01 + 4.149994E+01 5 5 8.269421E+05 3.229818E+02 + 4.149994E+01 6 6 9.076525E+05 3.292625E+00 + 4.159994E+01 1 1 2.010633E+03 2.761979E+00 + 4.159994E+01 1 5 -1.036784E+04 2.983413E+01 + 4.159994E+01 2 2 2.280502E+03 3.108115E+00 + 4.159994E+01 2 4 1.455977E+04 9.966230E+00 + 4.159994E+01 3 3 2.321802E+03 2.107699E+02 + 4.159994E+01 4 2 1.457613E+04 1.000151E+01 + 4.159994E+01 4 4 2.705635E+05 3.205392E+01 + 4.159994E+01 5 1 -1.038544E+04 2.976593E+01 + 4.159994E+01 5 5 8.269400E+05 3.214334E+02 + 4.159994E+01 6 6 9.076379E+05 3.296375E+00 + 4.169994E+01 1 1 2.010583E+03 2.747638E+00 + 4.169994E+01 1 5 -1.036785E+04 2.968378E+01 + 4.169994E+01 2 2 2.280436E+03 3.091906E+00 + 4.169994E+01 2 4 1.455952E+04 9.914182E+00 + 4.169994E+01 3 3 2.322174E+03 2.108015E+02 + 4.169994E+01 4 2 1.457589E+04 9.948250E+00 + 4.169994E+01 4 4 2.705623E+05 3.190782E+01 + 4.169994E+01 5 1 -1.038545E+04 2.961996E+01 + 4.169994E+01 5 5 8.269397E+05 3.200453E+02 + 4.169994E+01 6 6 9.076232E+05 3.239015E+00 + 4.179993E+01 1 1 2.010532E+03 2.733359E+00 + 4.179993E+01 1 5 -1.036787E+04 2.953878E+01 + 4.179993E+01 2 2 2.280375E+03 3.075854E+00 + 4.179993E+01 2 4 1.455924E+04 9.861310E+00 + 4.179993E+01 3 3 2.322546E+03 2.108277E+02 + 4.179993E+01 4 2 1.457561E+04 9.894742E+00 + 4.179993E+01 4 4 2.705612E+05 3.172332E+01 + 4.179993E+01 5 1 -1.038547E+04 2.947310E+01 + 4.179993E+01 5 5 8.269386E+05 3.183591E+02 + 4.179993E+01 6 6 9.076082E+05 3.194246E+00 + 4.189993E+01 1 1 2.010479E+03 2.719279E+00 + 4.189993E+01 1 5 -1.036789E+04 2.939155E+01 + 4.189993E+01 2 2 2.280311E+03 3.059813E+00 + 4.189993E+01 2 4 1.455897E+04 9.809370E+00 + 4.189993E+01 3 3 2.322901E+03 2.108558E+02 + 4.189993E+01 4 2 1.457534E+04 9.842846E+00 + 4.189993E+01 4 4 2.705602E+05 3.155300E+01 + 4.189993E+01 5 1 -1.038547E+04 2.932571E+01 + 4.189993E+01 5 5 8.269378E+05 3.168844E+02 + 4.189993E+01 6 6 9.075934E+05 3.168942E+00 + 4.199993E+01 1 1 2.010434E+03 2.705281E+00 + 4.199993E+01 1 5 -1.036793E+04 2.924620E+01 + 4.199993E+01 2 2 2.280251E+03 3.044036E+00 + 4.199993E+01 2 4 1.455869E+04 9.758191E+00 + 4.199993E+01 3 3 2.323268E+03 2.108832E+02 + 4.199993E+01 4 2 1.457507E+04 9.791515E+00 + 4.199993E+01 4 4 2.705584E+05 3.139161E+01 + 4.199993E+01 5 1 -1.038549E+04 2.918254E+01 + 4.199993E+01 5 5 8.269366E+05 3.153878E+02 + 4.199993E+01 6 6 9.075792E+05 3.160925E+00 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.3 b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.3 new file mode 100644 index 00000000..2bfe7b48 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.3 @@ -0,0 +1,10080 @@ + 1.000000E-01 0.000000E+00 1 3.928387E-05 9.000026E+01 -1.752301E-10 3.928387E-05 + 1.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E-01 0.000000E+00 3 5.096992E-06 2.330833E-04 5.096992E-06 2.073492E-11 + 1.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E-01 0.000000E+00 5 2.129045E-05 -8.999974E+01 9.931642E-11 -2.129045E-05 + 1.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E-01 3.000000E+01 1 2.479953E-05 9.000016E+01 -6.785025E-11 2.479953E-05 + 1.000000E-01 3.000000E+01 2 1.030077E-05 9.000000E+01 -3.776052E-13 1.030077E-05 + 1.000000E-01 3.000000E+01 3 6.027945E-06 2.529555E-05 6.027945E-06 2.661282E-12 + 1.000000E-01 3.000000E+01 4 4.842914E-05 -8.999998E+01 1.348501E-11 -4.842914E-05 + 1.000000E-01 3.000000E+01 5 1.310311E-05 -8.999985E+01 3.597847E-11 -1.310311E-05 + 1.000000E-01 3.000000E+01 6 1.316677E-04 -1.799997E+02 -1.316677E-04 -7.396868E-10 + 1.000000E-01 6.000000E+01 1 2.777314E-05 9.000978E+01 -4.741620E-09 2.777314E-05 + 1.000000E-01 6.000000E+01 2 3.752036E-06 9.000040E+01 -2.665548E-11 3.752036E-06 + 1.000000E-01 6.000000E+01 3 4.212014E-06 1.799998E+02 -4.212014E-06 1.676656E-11 + 1.000000E-01 6.000000E+01 4 1.801150E-05 -8.999966E+01 1.074628E-10 -1.801150E-05 + 1.000000E-01 6.000000E+01 5 1.438257E-05 -8.998517E+01 3.722973E-09 -1.438257E-05 + 1.000000E-01 6.000000E+01 6 2.408331E-04 2.416988E-04 2.408331E-04 1.015940E-09 + 1.000000E-01 9.000000E+01 1 3.569052E-10 9.000000E+01 -3.883185E-16 3.569052E-10 + 1.000000E-01 9.000000E+01 2 6.679657E-06 -8.999947E+01 6.145705E-11 -6.679657E-06 + 1.000000E-01 9.000000E+01 3 8.607126E-07 1.438843E-03 8.607126E-07 2.161469E-11 + 1.000000E-01 9.000000E+01 4 3.630382E-05 9.000039E+01 -2.475569E-10 3.630382E-05 + 1.000000E-01 9.000000E+01 5 1.129626E-10 9.000000E+01 -7.992531E-17 1.129626E-10 + 1.000000E-01 9.000000E+01 6 2.390679E-10 1.799993E+02 -2.390679E-10 2.915754E-15 + 2.000000E-01 0.000000E+00 1 4.794502E-03 -7.108732E+01 1.554026E-03 -4.535664E-03 + 2.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000000E-01 0.000000E+00 3 5.115628E-03 1.557186E+01 4.927857E-03 1.373273E-03 + 2.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000000E-01 0.000000E+00 5 3.931623E-04 -1.080528E+02 -1.218386E-04 -3.738074E-04 + 2.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000000E-01 3.000000E+01 1 7.095869E-03 -7.712666E+01 1.580935E-03 -6.917514E-03 + 2.000000E-01 3.000000E+01 2 4.226396E-03 1.086416E+02 -1.350958E-03 4.004665E-03 + 2.000000E-01 3.000000E+01 3 3.649259E-03 1.847425E+01 3.461199E-03 1.156371E-03 + 2.000000E-01 3.000000E+01 4 2.471381E-02 -7.209129E+01 7.599527E-03 -2.351637E-02 + 2.000000E-01 3.000000E+01 5 4.199853E-04 8.719241E+01 2.057174E-05 4.194811E-04 + 2.000000E-01 3.000000E+01 6 2.909344E-02 -1.673242E+02 -2.838435E-02 -6.384108E-03 + 2.000000E-01 6.000000E+01 1 2.047991E-03 -7.983326E+01 3.614978E-04 -2.015834E-03 + 2.000000E-01 6.000000E+01 2 1.384893E-03 -1.384165E+01 1.344677E-03 -3.313209E-04 + 2.000000E-01 6.000000E+01 3 3.288509E-03 -1.597656E+02 -3.085559E-03 -1.137370E-03 + 2.000000E-01 6.000000E+01 4 7.811303E-03 1.663535E+02 -7.590788E-03 1.842930E-03 + 2.000000E-01 6.000000E+01 5 7.411336E-04 -8.593498E+01 5.253779E-05 -7.392691E-04 + 2.000000E-01 6.000000E+01 6 3.474759E-02 6.111718E+00 3.455009E-02 3.699487E-03 + 2.000000E-01 9.000000E+01 1 1.420143E-08 -8.680801E+01 7.907613E-10 -1.417940E-08 + 2.000000E-01 9.000000E+01 2 1.406377E-02 1.025577E+02 -3.057782E-03 1.372733E-02 + 2.000000E-01 9.000000E+01 3 7.963536E-04 -1.482715E+02 -6.773379E-04 -4.187988E-04 + 2.000000E-01 9.000000E+01 4 7.866052E-02 -7.677493E+01 1.799571E-02 -7.657436E-02 + 2.000000E-01 9.000000E+01 5 2.518591E-09 9.854890E+01 -3.743971E-10 2.490607E-09 + 2.000000E-01 9.000000E+01 6 5.488987E-08 5.854488E+01 2.864320E-08 4.682376E-08 + 3.000000E-01 0.000000E+00 1 3.888490E-02 -9.719932E+01 -4.873109E-03 -3.857834E-02 + 3.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.000000E-01 0.000000E+00 3 1.602358E-02 1.495198E+02 -1.380919E-02 8.127803E-03 + 3.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.000000E-01 0.000000E+00 5 4.695172E-04 -3.361153E+01 3.910186E-04 -2.599056E-04 + 3.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.000000E-01 3.000000E+01 1 4.646594E-03 5.454666E+01 2.695209E-03 3.785060E-03 + 3.000000E-01 3.000000E+01 2 7.563305E-03 1.047204E+01 7.437328E-03 1.374674E-03 + 3.000000E-01 3.000000E+01 3 1.330938E-02 -8.915330E+01 1.966758E-04 -1.330793E-02 + 3.000000E-01 3.000000E+01 4 4.322376E-02 -1.644875E+02 -4.164920E-02 -1.156016E-02 + 3.000000E-01 3.000000E+01 5 2.016536E-03 -1.208179E+02 -1.033095E-03 -1.731801E-03 + 3.000000E-01 3.000000E+01 6 8.285185E-02 7.853923E+01 1.646241E-02 8.119986E-02 + 3.000000E-01 6.000000E+01 1 2.509840E-02 -1.168346E+02 -1.132984E-02 -2.239563E-02 + 3.000000E-01 6.000000E+01 2 7.971748E-03 -4.328616E+01 5.802942E-03 -5.465769E-03 + 3.000000E-01 6.000000E+01 3 1.678508E-02 3.530571E+01 1.369797E-02 9.700751E-03 + 3.000000E-01 6.000000E+01 4 3.282496E-02 1.413052E+02 -2.561945E-02 2.052126E-02 + 3.000000E-01 6.000000E+01 5 5.603014E-04 1.154969E+02 -2.411888E-04 5.057327E-04 + 3.000000E-01 6.000000E+01 6 1.670086E-01 -1.458209E+02 -1.381638E-01 -9.382232E-02 + 3.000000E-01 9.000000E+01 1 2.949139E-07 -9.067712E+01 -3.485205E-09 -2.948933E-07 + 3.000000E-01 9.000000E+01 2 4.167762E-02 1.074692E+02 -1.251132E-02 3.975539E-02 + 3.000000E-01 9.000000E+01 3 2.107524E-02 1.002967E+02 -3.767119E-03 2.073582E-02 + 3.000000E-01 9.000000E+01 4 2.493339E-01 -7.362067E+01 7.031103E-02 -2.392149E-01 + 3.000000E-01 9.000000E+01 5 5.106316E-08 -9.276367E+01 -2.462081E-09 -5.100377E-08 + 3.000000E-01 9.000000E+01 6 3.944706E-07 3.112561E+01 3.376811E-07 2.039081E-07 + 4.000000E-01 0.000000E+00 1 1.307384E-01 -5.282935E+01 7.899095E-02 -1.041775E-01 + 4.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.000000E-01 0.000000E+00 3 2.012498E-02 5.517360E+01 1.149321E-02 1.652032E-02 + 4.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.000000E-01 0.000000E+00 5 6.834955E-03 1.047795E+02 -1.743601E-03 6.608818E-03 + 4.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.000000E-01 3.000000E+01 1 5.314526E-02 -1.338230E+02 -3.679949E-02 -3.834339E-02 + 4.000000E-01 3.000000E+01 2 4.128766E-02 -9.884937E+01 -6.351586E-03 -4.079618E-02 + 4.000000E-01 3.000000E+01 3 2.686598E-02 -1.495038E+02 -2.314942E-02 -1.363397E-02 + 4.000000E-01 3.000000E+01 4 1.264045E-01 1.048542E+02 -3.240515E-02 1.221802E-01 + 4.000000E-01 3.000000E+01 5 4.001336E-03 7.631565E+01 9.466071E-04 3.887753E-03 + 4.000000E-01 3.000000E+01 6 5.532191E-01 -1.786506E+02 -5.530657E-01 -1.302844E-02 + 4.000000E-01 6.000000E+01 1 3.044731E-02 1.381135E+02 -2.266707E-02 2.032837E-02 + 4.000000E-01 6.000000E+01 2 7.044896E-02 8.796443E+01 2.502343E-03 7.040451E-02 + 4.000000E-01 6.000000E+01 3 6.615130E-02 -1.709194E+02 -6.532224E-02 -1.044024E-02 + 4.000000E-01 6.000000E+01 4 3.611451E-01 -8.312469E+01 4.323230E-02 -3.585481E-01 + 4.000000E-01 6.000000E+01 5 6.043765E-03 5.819611E+01 3.185145E-03 5.136336E-03 + 4.000000E-01 6.000000E+01 6 3.507415E-01 -1.755146E+02 -3.496673E-01 -2.742958E-02 + 4.000000E-01 9.000000E+01 1 5.332167E-07 -9.304235E+01 -2.829999E-08 -5.324652E-07 + 4.000000E-01 9.000000E+01 2 3.888678E-02 1.746534E+02 -3.871759E-02 3.623477E-03 + 4.000000E-01 9.000000E+01 3 5.207599E-02 1.688102E+02 -5.108601E-02 1.010584E-02 + 4.000000E-01 9.000000E+01 4 1.950537E-01 1.483926E+01 1.885483E-01 4.995484E-02 + 4.000000E-01 9.000000E+01 5 2.097070E-07 8.940276E+01 2.185888E-09 2.096956E-07 + 4.000000E-01 9.000000E+01 6 5.884815E-07 -8.653599E+00 5.817823E-07 -8.854307E-08 + 5.000000E-01 0.000000E+00 1 3.081082E-01 8.983705E+01 8.762858E-04 3.081069E-01 + 5.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.000000E-01 0.000000E+00 3 2.407918E-02 2.501227E+01 2.182096E-02 1.018097E-02 + 5.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.000000E-01 0.000000E+00 5 4.103291E-02 -9.531126E+01 -3.798261E-03 -4.085674E-02 + 5.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.000000E-01 3.000000E+01 1 9.193930E-02 1.028800E+02 -2.049419E-02 8.962601E-02 + 5.000000E-01 3.000000E+01 2 1.244288E-02 1.155199E+02 -5.360694E-03 1.122890E-02 + 5.000000E-01 3.000000E+01 3 5.293012E-02 9.640726E+01 -5.906723E-03 5.259950E-02 + 5.000000E-01 3.000000E+01 4 3.355523E-01 -5.319021E+01 2.010497E-01 -2.686529E-01 + 5.000000E-01 3.000000E+01 5 3.948701E-03 6.551472E+01 1.636576E-03 3.593585E-03 + 5.000000E-01 3.000000E+01 6 1.075385E+00 2.140287E+01 1.001224E+00 3.924331E-01 + 5.000000E-01 6.000000E+01 1 1.267945E-01 1.144335E+02 -5.244690E-02 1.154391E-01 + 5.000000E-01 6.000000E+01 2 8.339784E-02 1.031805E+02 -1.901636E-02 8.120085E-02 + 5.000000E-01 6.000000E+01 3 6.141623E-02 -1.751663E+02 -6.119780E-02 -5.175158E-03 + 5.000000E-01 6.000000E+01 4 4.040240E-01 -6.234457E+01 1.875290E-01 -3.578662E-01 + 5.000000E-01 6.000000E+01 5 1.285017E-02 4.696736E+01 8.769150E-03 9.393029E-03 + 5.000000E-01 6.000000E+01 6 1.832786E+00 1.790019E+02 -1.832507E+00 3.192545E-02 + 5.000000E-01 9.000000E+01 1 1.766503E-06 8.096854E+01 2.773000E-07 1.744602E-06 + 5.000000E-01 9.000000E+01 2 2.347312E-01 6.647649E+01 9.368712E-02 2.152242E-01 + 5.000000E-01 9.000000E+01 3 3.180214E-02 1.300939E+02 -2.048190E-02 2.432833E-02 + 5.000000E-01 9.000000E+01 4 4.249727E-01 -8.168529E+01 6.145542E-02 -4.205057E-01 + 5.000000E-01 9.000000E+01 5 1.556368E-07 9.600702E+01 -1.628744E-08 1.547822E-07 + 5.000000E-01 9.000000E+01 6 7.300903E-05 1.775445E+02 -7.294200E-05 3.127902E-06 + 6.000000E-01 0.000000E+00 1 1.872266E-01 -1.771957E+02 -1.870024E-01 -9.159982E-03 + 6.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.000000E-01 0.000000E+00 3 2.174157E-02 1.385365E+02 -1.629265E-02 1.439602E-02 + 6.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.000000E-01 0.000000E+00 5 7.292495E-03 -1.096383E+02 -2.450872E-03 -6.868312E-03 + 6.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.000000E-01 3.000000E+01 1 2.012022E-01 1.017873E+02 -4.110143E-02 1.969594E-01 + 6.000000E-01 3.000000E+01 2 9.185858E-02 1.075576E+02 -2.771054E-02 8.757925E-02 + 6.000000E-01 3.000000E+01 3 5.708990E-02 -1.741342E+02 -5.679097E-02 -5.834544E-03 + 6.000000E-01 3.000000E+01 4 3.475970E-01 -7.517700E+01 8.892706E-02 -3.360293E-01 + 6.000000E-01 3.000000E+01 5 3.762222E-02 -8.768892E+01 1.517118E-03 -3.759162E-02 + 6.000000E-01 3.000000E+01 6 5.433523E-01 -8.032565E+01 9.130932E-02 -5.356252E-01 + 6.000000E-01 6.000000E+01 1 6.134738E-02 -6.685158E+01 2.411654E-02 -5.640827E-02 + 6.000000E-01 6.000000E+01 2 2.838711E-01 -5.865669E+01 1.476598E-01 -2.424446E-01 + 6.000000E-01 6.000000E+01 3 7.000349E-02 3.677592E+01 5.607161E-02 4.191018E-02 + 6.000000E-01 6.000000E+01 4 8.238294E-01 1.504999E+02 -7.170240E-01 4.056741E-01 + 6.000000E-01 6.000000E+01 5 1.140813E-02 -4.424509E+01 8.172348E-03 -7.959786E-03 + 6.000000E-01 6.000000E+01 6 9.150789E-01 3.374132E+01 7.609373E-01 5.082753E-01 + 6.000000E-01 9.000000E+01 1 7.724071E-07 6.753969E+01 2.950931E-07 7.138157E-07 + 6.000000E-01 9.000000E+01 2 2.032647E-01 9.344522E+01 -1.221503E-02 2.028973E-01 + 6.000000E-01 9.000000E+01 3 5.020192E-02 6.025718E+01 2.490556E-02 4.358836E-02 + 6.000000E-01 9.000000E+01 4 9.899581E-01 -8.339436E+01 1.138798E-01 -9.833862E-01 + 6.000000E-01 9.000000E+01 5 4.465225E-07 -1.031010E+02 -1.012124E-07 -4.349005E-07 + 6.000000E-01 9.000000E+01 6 9.935205E-06 -1.697474E+02 -9.776565E-06 -1.768350E-06 + 7.000000E-01 0.000000E+00 1 8.027183E-01 6.060232E+01 3.940291E-01 6.993552E-01 + 7.000000E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.000000E-01 0.000000E+00 3 1.692642E-01 3.964836E+01 1.303292E-01 1.080031E-01 + 7.000000E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.000000E-01 0.000000E+00 5 1.808603E-01 -1.052378E+02 -4.753476E-02 -1.745018E-01 + 7.000000E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.000000E-01 3.000000E+01 1 1.148481E-01 -1.690576E+02 -1.127600E-01 -2.180065E-02 + 7.000000E-01 3.000000E+01 2 1.608283E-01 4.394753E+00 1.603555E-01 1.232391E-02 + 7.000000E-01 3.000000E+01 3 7.954486E-03 -1.564072E+02 -7.289595E-03 -3.183652E-03 + 7.000000E-01 3.000000E+01 4 8.603882E-01 8.365328E+01 9.511141E-02 8.551151E-01 + 7.000000E-01 3.000000E+01 5 7.463598E-02 -6.266520E+01 3.427203E-02 -6.630202E-02 + 7.000000E-01 3.000000E+01 6 9.527321E+00 1.384091E+02 -7.125519E+00 6.324304E+00 + 7.000000E-01 6.000000E+01 1 4.940590E-01 -1.497921E+02 -4.269682E-01 -2.485807E-01 + 7.000000E-01 6.000000E+01 2 4.148615E-01 -1.045590E+02 -1.042866E-01 -4.015400E-01 + 7.000000E-01 6.000000E+01 3 1.437976E-01 2.332423E+01 1.320463E-01 5.693434E-02 + 7.000000E-01 6.000000E+01 4 1.464140E+00 -7.177795E+01 4.578373E-01 -1.390716E+00 + 7.000000E-01 6.000000E+01 5 6.378181E-02 7.214042E+01 1.956094E-02 6.070822E-02 + 7.000000E-01 6.000000E+01 6 1.511462E+01 -1.530150E+01 1.457881E+01 -3.988723E+00 + 7.000000E-01 9.000000E+01 1 1.589562E-06 -5.732171E+01 8.582388E-07 -1.337959E-06 + 7.000000E-01 9.000000E+01 2 6.702136E-01 5.452286E+01 3.889773E-01 5.457866E-01 + 7.000000E-01 9.000000E+01 3 1.072043E-01 8.414521E+01 1.093565E-02 1.066451E-01 + 7.000000E-01 9.000000E+01 4 1.161876E+00 -5.514134E+01 6.640748E-01 -9.533941E-01 + 7.000000E-01 9.000000E+01 5 3.845822E-07 -1.378897E+02 -2.853046E-07 -2.578852E-07 + 7.000000E-01 9.000000E+01 6 2.159800E-04 1.604690E+02 -2.035527E-04 7.220576E-05 + 8.000001E-01 0.000000E+00 1 4.028370E+00 -5.588440E+01 2.259370E+00 -3.335119E+00 + 8.000001E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.000001E-01 0.000000E+00 3 2.095643E-01 -3.923662E+00 2.090731E-01 -1.433992E-02 + 8.000001E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.000001E-01 0.000000E+00 5 7.912704E-01 1.254263E+02 -4.586639E-01 6.447762E-01 + 8.000001E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.000001E-01 3.000000E+01 1 5.347347E-01 -7.389597E+01 1.483259E-01 -5.137515E-01 + 8.000001E-01 3.000000E+01 2 3.749571E-01 4.094019E+01 2.832404E-01 2.456985E-01 + 8.000001E-01 3.000000E+01 3 2.190640E-01 -1.435698E+02 -1.762548E-01 -1.300895E-01 + 8.000001E-01 3.000000E+01 4 1.997968E+00 -5.941833E+01 1.016498E+00 -1.720060E+00 + 8.000001E-01 3.000000E+01 5 1.540143E-01 1.044117E+02 -3.833220E-02 1.491678E-01 + 8.000001E-01 3.000000E+01 6 1.853185E+01 -1.581446E+02 -1.719990E+01 -6.898758E+00 + 8.000001E-01 6.000000E+01 1 2.647785E-01 -9.986835E+00 2.607664E-01 -4.591838E-02 + 8.000001E-01 6.000000E+01 2 3.127118E-02 -1.723142E+02 -3.099025E-02 -4.182242E-03 + 8.000001E-01 6.000000E+01 3 2.191740E-01 -1.447901E+02 -1.790750E-01 -1.263701E-01 + 8.000001E-01 6.000000E+01 4 1.036278E+00 -4.005235E+01 7.932259E-01 -6.668315E-01 + 8.000001E-01 6.000000E+01 5 1.151183E-01 -1.673150E+02 -1.123085E-01 -2.527882E-02 + 8.000001E-01 6.000000E+01 6 2.461483E+00 -1.095917E+01 2.416592E+00 -4.679509E-01 + 8.000001E-01 9.000000E+01 1 1.617859E-06 1.135123E+02 -6.454394E-07 1.483535E-06 + 8.000001E-01 9.000000E+01 2 1.755162E+00 -7.329680E+01 5.044584E-01 -1.681106E+00 + 8.000001E-01 9.000000E+01 3 8.098494E-02 6.427621E+01 3.515016E-02 7.295907E-02 + 8.000001E-01 9.000000E+01 4 1.641137E+00 -6.077317E+01 8.013152E-01 -1.432210E+00 + 8.000001E-01 9.000000E+01 5 5.084881E-07 -8.231286E+01 6.801734E-08 -5.039184E-07 + 8.000001E-01 9.000000E+01 6 2.693365E-04 2.322025E+01 2.475192E-04 1.061904E-04 + 9.000001E-01 0.000000E+00 1 1.068581E+00 6.843844E+01 3.927042E-01 9.938048E-01 + 9.000001E-01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.000001E-01 0.000000E+00 3 5.909093E-02 -1.017197E+02 -1.200281E-02 -5.785906E-02 + 9.000001E-01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.000001E-01 0.000000E+00 5 2.806859E-01 -1.200122E+02 -1.403947E-01 -2.430512E-01 + 9.000001E-01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.000001E-01 3.000000E+01 1 6.341945E-01 -6.897472E+01 2.275362E-01 -5.919712E-01 + 9.000001E-01 3.000000E+01 2 2.360800E-01 1.247190E+02 -1.344599E-01 1.940472E-01 + 9.000001E-01 3.000000E+01 3 3.962129E-02 -6.630566E+00 3.935628E-02 -4.574955E-03 + 9.000001E-01 3.000000E+01 4 1.353328E+00 2.196399E+01 1.255102E+00 5.061766E-01 + 9.000001E-01 3.000000E+01 5 1.222350E-01 1.242814E+02 -6.884973E-02 1.010005E-01 + 9.000001E-01 3.000000E+01 6 3.158235E+01 -3.682267E+01 2.528149E+01 -1.892858E+01 + 9.000001E-01 6.000000E+01 1 1.149328E+00 7.111678E+01 3.719688E-01 1.087471E+00 + 9.000001E-01 6.000000E+01 2 1.495766E+00 5.134853E+01 9.342274E-01 1.168133E+00 + 9.000001E-01 6.000000E+01 3 1.335133E-01 1.577747E+02 -1.235937E-01 5.050145E-02 + 9.000001E-01 6.000000E+01 4 6.085460E-01 -1.030611E+02 -1.375258E-01 -5.928026E-01 + 9.000001E-01 6.000000E+01 5 1.975831E-01 -1.385824E+02 -1.481691E-01 -1.307095E-01 + 9.000001E-01 6.000000E+01 6 3.867049E+00 -6.315012E+01 1.746570E+00 -3.450154E+00 + 9.000001E-01 9.000000E+01 1 2.148013E-06 -3.934335E+01 1.661189E-06 -1.361768E-06 + 9.000001E-01 9.000000E+01 2 5.254689E-01 6.716647E+01 2.039109E-01 4.842912E-01 + 9.000001E-01 9.000000E+01 3 2.646114E-01 -2.418865E+01 2.413789E-01 -1.084225E-01 + 9.000001E-01 9.000000E+01 4 1.538332E+00 9.886794E+01 -2.371452E-01 1.519943E+00 + 9.000001E-01 9.000000E+01 5 5.961102E-07 -1.758145E+02 -5.945204E-07 -4.350777E-08 + 9.000001E-01 9.000000E+01 6 2.369981E-04 1.465884E+02 -1.978308E-04 1.305030E-04 + 1.000000E+00 0.000000E+00 1 4.498790E+00 1.417020E+02 -3.530643E+00 2.788131E+00 + 1.000000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E+00 0.000000E+00 3 4.891869E-01 1.280575E+02 -3.015603E-01 3.851821E-01 + 1.000000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E+00 0.000000E+00 5 1.111608E+00 -4.117408E+01 8.367217E-01 -7.318260E-01 + 1.000000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E+00 3.000000E+01 1 9.384710E-01 6.006435E+01 4.683224E-01 8.132662E-01 + 1.000000E+00 3.000000E+01 2 5.688173E-01 6.984396E+01 1.960020E-01 5.339816E-01 + 1.000000E+00 3.000000E+01 3 3.170465E-01 1.560125E+02 -2.896644E-01 1.288915E-01 + 1.000000E+00 3.000000E+01 4 2.548091E+00 -1.309901E+02 -1.671366E+00 -1.923358E+00 + 1.000000E+00 3.000000E+01 5 2.532068E-01 -1.020614E+02 -5.291017E-02 -2.476170E-01 + 1.000000E+00 3.000000E+01 6 1.370568E+01 8.000809E+01 2.378060E+00 1.349780E+01 + 1.000000E+00 6.000000E+01 1 1.063347E+00 1.199143E+02 -5.302954E-01 9.216798E-01 + 1.000000E+00 6.000000E+01 2 9.221056E-01 -1.749147E+02 -9.184759E-01 -8.173476E-02 + 1.000000E+00 6.000000E+01 3 5.232720E-01 -1.733326E+02 -5.197331E-01 -6.075449E-02 + 1.000000E+00 6.000000E+01 4 5.569331E-01 -2.655671E+01 4.981723E-01 -2.489956E-01 + 1.000000E+00 6.000000E+01 5 4.033430E-01 -6.104259E+01 1.952823E-01 -3.529170E-01 + 1.000000E+00 6.000000E+01 6 9.770492E+00 4.874333E+01 6.442988E+00 7.345094E+00 + 1.000000E+00 9.000000E+01 1 3.758858E-06 3.555691E+01 3.057976E-06 2.185818E-06 + 1.000000E+00 9.000000E+01 2 2.487580E+00 1.172793E+02 -1.140129E+00 2.210919E+00 + 1.000000E+00 9.000000E+01 3 9.679143E-02 8.315680E+00 9.577379E-02 1.399865E-02 + 1.000000E+00 9.000000E+01 4 2.912810E+00 -1.650378E+02 -2.814055E+00 -7.520341E-01 + 1.000000E+00 9.000000E+01 5 6.350767E-07 -1.537991E+02 -5.698235E-07 -2.803990E-07 + 1.000000E+00 9.000000E+01 6 3.296134E-04 -1.187178E+02 -1.583778E-04 -2.890700E-04 + 1.100000E+00 0.000000E+00 1 2.409579E+00 1.689714E+02 -2.365078E+00 4.609488E-01 + 1.100000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.100000E+00 0.000000E+00 3 7.349316E-01 -1.583984E+02 -6.833147E-01 -2.705651E-01 + 1.100000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.100000E+00 0.000000E+00 5 6.515889E-01 2.371388E+00 6.510308E-01 2.696060E-02 + 1.100000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.100000E+00 3.000000E+01 1 1.383384E+00 -2.329154E+01 1.270645E+00 -5.470040E-01 + 1.100000E+00 3.000000E+01 2 7.300221E-01 -7.040385E+01 2.448408E-01 -6.877392E-01 + 1.100000E+00 3.000000E+01 3 2.772623E-01 -6.642005E+01 1.109128E-01 -2.541117E-01 + 1.100000E+00 3.000000E+01 4 2.365005E+00 1.220531E+02 -1.255120E+00 2.004475E+00 + 1.100000E+00 3.000000E+01 5 1.840076E-01 1.413332E+02 -1.436718E-01 1.149662E-01 + 1.100000E+00 3.000000E+01 6 1.300902E+01 -7.074613E+00 1.290998E+01 -1.602214E+00 + 1.100000E+00 6.000000E+01 1 6.888239E-01 1.965264E+01 6.486992E-01 2.316631E-01 + 1.100000E+00 6.000000E+01 2 1.274021E+00 7.086687E+01 4.175786E-01 1.203644E+00 + 1.100000E+00 6.000000E+01 3 3.023910E-01 -1.388350E+02 -2.276452E-01 -1.990427E-01 + 1.100000E+00 6.000000E+01 4 4.212014E+00 1.605077E+02 -3.970607E+00 1.405468E+00 + 1.100000E+00 6.000000E+01 5 6.740979E-02 1.239330E+02 -3.762972E-02 5.592928E-02 + 1.100000E+00 6.000000E+01 6 6.277072E+00 -1.779185E+02 -6.272930E+00 -2.279956E-01 + 1.100000E+00 9.000000E+01 1 9.634122E-07 1.621139E+02 -9.168493E-07 2.958890E-07 + 1.100000E+00 9.000000E+01 2 3.993272E-01 -1.672850E+02 -3.895345E-01 -8.789238E-02 + 1.100000E+00 9.000000E+01 3 3.142914E-01 1.432106E+02 -2.516979E-01 1.882212E-01 + 1.100000E+00 9.000000E+01 4 3.689179E+00 -3.181832E+01 3.134784E+00 -1.945037E+00 + 1.100000E+00 9.000000E+01 5 4.653694E-07 -5.811555E+01 2.458118E-07 -3.951522E-07 + 1.100000E+00 9.000000E+01 6 6.607713E-05 2.584140E-01 6.607646E-05 2.980184E-07 + 1.200000E+00 0.000000E+00 1 1.443482E+00 -1.671270E+02 -1.407202E+00 -3.215949E-01 + 1.200000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.200000E+00 0.000000E+00 3 4.628122E-01 -1.645647E+02 -4.461193E-01 -1.231774E-01 + 1.200000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.200000E+00 0.000000E+00 5 5.352653E-01 4.020810E+01 4.087847E-01 3.455489E-01 + 1.200000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.200000E+00 3.000000E+01 1 2.075541E+00 1.748229E+02 -2.067074E+00 1.872850E-01 + 1.200000E+00 3.000000E+01 2 1.362046E+00 1.108371E+02 -4.844972E-01 1.272962E+00 + 1.200000E+00 3.000000E+01 3 8.534918E-01 -1.128969E+02 -3.320719E-01 -7.862421E-01 + 1.200000E+00 3.000000E+01 4 2.205437E+00 1.177562E+01 2.159022E+00 4.500845E-01 + 1.200000E+00 3.000000E+01 5 6.961068E-01 -5.783009E+00 6.925641E-01 -7.014059E-02 + 1.200000E+00 3.000000E+01 6 1.774967E+01 -7.653576E+01 4.132805E+00 -1.726183E+01 + 1.200000E+00 6.000000E+01 1 2.512922E+00 1.082590E+02 -7.873306E-01 2.386397E+00 + 1.200000E+00 6.000000E+01 2 4.185233E+00 8.515934E+01 3.531708E-01 4.170305E+00 + 1.200000E+00 6.000000E+01 3 3.349589E-01 5.579454E+01 1.883012E-01 2.770200E-01 + 1.200000E+00 6.000000E+01 4 1.705958E+00 2.558417E+01 1.538692E+00 7.366951E-01 + 1.200000E+00 6.000000E+01 5 9.582613E-01 -7.502637E+01 2.475901E-01 -9.257234E-01 + 1.200000E+00 6.000000E+01 6 1.168844E+02 1.558077E+02 -1.066191E+02 4.789923E+01 + 1.200000E+00 9.000000E+01 1 3.344430E-06 -1.190675E+02 -1.624855E-06 -2.923193E-06 + 1.200000E+00 9.000000E+01 2 3.579329E+00 -7.162445E+01 1.128362E+00 -3.396821E+00 + 1.200000E+00 9.000000E+01 3 5.534689E-01 1.540251E+02 -4.975608E-01 2.424069E-01 + 1.200000E+00 9.000000E+01 4 1.741812E+00 1.029711E+02 -3.909655E-01 1.697367E+00 + 1.200000E+00 9.000000E+01 5 1.616718E-06 8.714442E+01 8.054281E-08 1.614711E-06 + 1.200000E+00 9.000000E+01 6 4.290794E-04 -2.489748E+01 3.892018E-04 -1.806407E-04 + 1.300000E+00 0.000000E+00 1 7.003986E+00 1.314920E+02 -4.640247E+00 5.246325E+00 + 1.300000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.300000E+00 0.000000E+00 3 6.571900E-01 -1.645828E+02 -6.335413E-01 -1.747112E-01 + 1.300000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.300000E+00 0.000000E+00 5 2.849876E+00 -4.921009E+01 1.861788E+00 -2.157670E+00 + 1.300000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.300000E+00 3.000000E+01 1 2.263089E+00 1.555407E+02 -2.059990E+00 9.370242E-01 + 1.300000E+00 3.000000E+01 2 2.027119E+00 1.166973E+02 -9.107381E-01 1.811013E+00 + 1.300000E+00 3.000000E+01 3 5.080034E-01 6.292294E+01 2.312373E-01 4.523238E-01 + 1.300000E+00 3.000000E+01 4 4.724977E+00 -4.095230E+01 3.568564E+00 -3.096894E+00 + 1.300000E+00 3.000000E+01 5 6.495391E-01 -1.060814E+01 6.384380E-01 -1.195743E-01 + 1.300000E+00 3.000000E+01 6 3.506529E+01 7.157618E+01 1.108216E+01 3.326801E+01 + 1.300000E+00 6.000000E+01 1 9.093643E-01 8.503635E+01 7.868150E-02 9.059540E-01 + 1.300000E+00 6.000000E+01 2 2.073938E+00 1.441509E+02 -1.681056E+00 1.214607E+00 + 1.300000E+00 6.000000E+01 3 1.249524E+00 2.353761E+00 1.248470E+00 5.131713E-02 + 1.300000E+00 6.000000E+01 4 1.618520E+00 -1.168375E+02 -7.307007E-01 -1.444189E+00 + 1.300000E+00 6.000000E+01 5 5.895178E-01 -1.037552E+02 -1.401722E-01 -5.726107E-01 + 1.300000E+00 6.000000E+01 6 1.155252E+02 4.325387E+01 8.413983E+01 7.916157E+01 + 1.300000E+00 9.000000E+01 1 7.389086E-06 3.724580E+01 5.882055E-06 4.472139E-06 + 1.300000E+00 9.000000E+01 2 2.336719E+00 -1.787105E+02 -2.336127E+00 -5.258447E-02 + 1.300000E+00 9.000000E+01 3 4.543476E-01 -1.128423E+02 -1.763758E-01 -4.187163E-01 + 1.300000E+00 9.000000E+01 4 2.450729E+00 1.110250E+02 -8.792601E-01 2.287569E+00 + 1.300000E+00 9.000000E+01 5 3.034535E-06 -1.440656E+02 -2.457031E-06 -1.780843E-06 + 1.300000E+00 9.000000E+01 6 4.249371E-04 -1.246016E+02 -2.413078E-04 -3.497743E-04 + 1.400000E+00 0.000000E+00 1 1.171565E+01 7.347941E+01 3.331463E+00 1.123200E+01 + 1.400000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.400000E+00 0.000000E+00 3 2.655761E-01 -3.997689E+01 2.035120E-01 -1.706269E-01 + 1.400000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.400000E+00 0.000000E+00 5 5.973072E+00 -1.114528E+02 -2.184563E+00 -5.559251E+00 + 1.400000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.400000E+00 3.000000E+01 1 1.173266E+01 7.165550E+01 3.692616E+00 1.113642E+01 + 1.400000E+00 3.000000E+01 2 4.782632E+00 5.907642E+01 2.457768E+00 4.102797E+00 + 1.400000E+00 3.000000E+01 3 1.455644E+00 6.325904E+01 6.549782E-01 1.299963E+00 + 1.400000E+00 3.000000E+01 4 5.447604E+00 1.608448E+02 -5.145986E+00 1.787515E+00 + 1.400000E+00 3.000000E+01 5 5.153780E+00 -1.096298E+02 -1.731364E+00 -4.854259E+00 + 1.400000E+00 3.000000E+01 6 2.281675E+01 9.611151E+01 -2.429159E+00 2.268707E+01 + 1.400000E+00 6.000000E+01 1 1.157303E+01 -1.016479E+02 -2.336565E+00 -1.133470E+01 + 1.400000E+00 6.000000E+01 2 1.292264E+01 -9.645769E+01 -1.453401E+00 -1.284064E+01 + 1.400000E+00 6.000000E+01 3 6.924345E-01 1.279500E+02 -4.258292E-01 5.460174E-01 + 1.400000E+00 6.000000E+01 4 5.056304E+00 1.624172E+02 -4.820082E+00 1.527424E+00 + 1.400000E+00 6.000000E+01 5 5.463288E+00 7.882168E+01 1.059131E+00 5.359642E+00 + 1.400000E+00 6.000000E+01 6 1.273826E+02 1.634732E+02 -1.221200E+02 3.623571E+01 + 1.400000E+00 9.000000E+01 1 7.535232E-06 1.578394E+02 -6.978606E-06 2.842320E-06 + 1.400000E+00 9.000000E+01 2 1.086191E+01 6.206549E+01 5.088391E+00 9.596318E+00 + 1.400000E+00 9.000000E+01 3 9.402484E-02 -1.133706E+02 -3.729743E-02 -8.631090E-02 + 1.400000E+00 9.000000E+01 4 3.135868E+00 1.319860E+01 3.053032E+00 7.160037E-01 + 1.400000E+00 9.000000E+01 5 4.244722E-06 -2.349240E+01 3.892890E-06 -1.692062E-06 + 1.400000E+00 9.000000E+01 6 4.178208E-04 1.586816E+02 -3.892313E-04 1.518986E-04 + 1.500000E+00 0.000000E+00 1 2.253690E+01 2.170131E+01 2.093958E+01 8.333425E+00 + 1.500000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.500000E+00 0.000000E+00 3 8.662427E-01 1.083845E+02 -2.732056E-01 8.220311E-01 + 1.500000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.500000E+00 0.000000E+00 5 1.326415E+01 -1.582939E+02 -1.232364E+01 -4.905677E+00 + 1.500000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.500000E+00 3.000000E+01 1 3.378882E+00 9.253078E+00 3.334915E+00 5.433093E-01 + 1.500000E+00 3.000000E+01 2 7.914361E+00 2.474301E+01 7.187777E+00 3.312547E+00 + 1.500000E+00 3.000000E+01 3 5.950861E-01 -3.377501E+01 4.946517E-01 -3.308280E-01 + 1.500000E+00 3.000000E+01 4 8.162408E+00 -1.378921E+02 -6.055557E+00 -5.473128E+00 + 1.500000E+00 3.000000E+01 5 1.556425E+00 1.701120E+02 -1.533305E+00 2.672737E-01 + 1.500000E+00 3.000000E+01 6 3.121408E+01 -1.125936E+02 -1.199218E+01 -2.881851E+01 + 1.500000E+00 6.000000E+01 1 8.058857E+00 1.511977E+01 7.779881E+00 2.102053E+00 + 1.500000E+00 6.000000E+01 2 1.575511E+01 2.624129E+01 1.413138E+01 6.966158E+00 + 1.500000E+00 6.000000E+01 3 1.023166E+00 1.520826E+02 -9.040931E-01 4.790444E-01 + 1.500000E+00 6.000000E+01 4 3.840172E+00 5.642629E+01 2.123651E+00 3.199536E+00 + 1.500000E+00 6.000000E+01 5 5.091404E+00 -1.611259E+02 -4.817647E+00 -1.647017E+00 + 1.500000E+00 6.000000E+01 6 1.822460E+01 1.319307E+02 -1.217826E+01 1.355825E+01 + 1.500000E+00 9.000000E+01 1 7.987765E-06 1.628710E+02 -7.633459E-06 2.352590E-06 + 1.500000E+00 9.000000E+01 2 5.198710E+00 1.088665E+02 -1.681076E+00 4.919408E+00 + 1.500000E+00 9.000000E+01 3 6.865063E-01 4.361718E+01 4.970066E-01 4.735772E-01 + 1.500000E+00 9.000000E+01 4 7.910254E+00 1.620439E+01 7.595998E+00 2.207472E+00 + 1.500000E+00 9.000000E+01 5 4.914498E-06 -2.147218E+01 4.573409E-06 -1.798949E-06 + 1.500000E+00 9.000000E+01 6 5.152921E-04 1.271103E+02 -3.109023E-04 4.109327E-04 + 1.600000E+00 0.000000E+00 1 2.117395E+01 -6.286393E+01 9.657549E+00 -1.884324E+01 + 1.600000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.600000E+00 0.000000E+00 3 6.416135E-02 1.035933E+02 -1.507976E-02 6.236409E-02 + 1.600000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.600000E+00 0.000000E+00 5 1.372208E+01 1.168204E+02 -6.191330E+00 1.224594E+01 + 1.600000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.600000E+00 3.000000E+01 1 1.415636E+00 3.696273E+01 1.131131E+00 8.512152E-01 + 1.600000E+00 3.000000E+01 2 2.140322E+00 3.397316E+01 1.774968E+00 1.196021E+00 + 1.600000E+00 3.000000E+01 3 2.697981E+00 -4.465592E+01 1.919183E+00 -1.896270E+00 + 1.600000E+00 3.000000E+01 4 3.825750E+00 1.541572E+02 -3.443149E+00 1.667660E+00 + 1.600000E+00 3.000000E+01 5 3.813242E-01 -1.302608E+02 -2.464376E-01 -2.909925E-01 + 1.600000E+00 3.000000E+01 6 5.789972E+01 -1.640426E+02 -5.566863E+01 -1.591795E+01 + 1.600000E+00 6.000000E+01 1 6.619334E+00 1.283833E+02 -4.110074E+00 5.188725E+00 + 1.600000E+00 6.000000E+01 2 1.838614E+01 1.424945E+02 -1.458563E+01 1.119418E+01 + 1.600000E+00 6.000000E+01 3 2.027168E+00 -1.594750E+02 -1.898481E+00 -7.107591E-01 + 1.600000E+00 6.000000E+01 4 9.656239E+00 1.708991E+02 -9.534679E+00 1.527363E+00 + 1.600000E+00 6.000000E+01 5 4.125096E+00 -4.624290E+01 2.852927E+00 -2.979468E+00 + 1.600000E+00 6.000000E+01 6 2.767762E+01 -1.623947E+02 -2.638127E+01 -8.371320E+00 + 1.600000E+00 9.000000E+01 1 1.362756E-06 -1.219808E+02 -7.217633E-07 -1.155925E-06 + 1.600000E+00 9.000000E+01 2 1.583243E+01 -3.573277E+01 1.285197E+01 -9.246226E+00 + 1.600000E+00 9.000000E+01 3 6.111758E-01 6.304171E+01 2.770716E-01 5.447634E-01 + 1.600000E+00 9.000000E+01 4 4.628506E+00 -3.940343E+01 3.576426E+00 -2.938068E+00 + 1.600000E+00 9.000000E+01 5 9.186458E-07 1.975923E+01 8.645574E-07 3.105651E-07 + 1.600000E+00 9.000000E+01 6 4.913512E-04 5.417681E+01 2.875809E-04 3.984009E-04 + 1.700000E+00 0.000000E+00 1 1.530682E+01 -5.350866E+01 9.102983E+00 -1.230587E+01 + 1.700000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.700000E+00 0.000000E+00 3 5.826858E-01 4.770614E+01 3.921086E-01 4.310145E-01 + 1.700000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.700000E+00 0.000000E+00 5 1.124916E+01 1.277608E+02 -6.888609E+00 8.893294E+00 + 1.700000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.700000E+00 3.000000E+01 1 5.635712E+00 8.176098E+01 8.076141E-01 5.577545E+00 + 1.700000E+00 3.000000E+01 2 7.947534E+00 8.021186E+01 1.351125E+00 7.831843E+00 + 1.700000E+00 3.000000E+01 3 1.510188E+00 -3.053736E+01 1.300722E+00 -7.673268E-01 + 1.700000E+00 3.000000E+01 4 1.109124E+01 6.744710E+01 4.253893E+00 1.024305E+01 + 1.700000E+00 3.000000E+01 5 4.486289E+00 -9.376264E+01 -2.944054E-01 -4.476618E+00 + 1.700000E+00 3.000000E+01 6 3.115220E+01 1.183897E+02 -1.481183E+01 2.740564E+01 + 1.700000E+00 6.000000E+01 1 3.911623E+00 -7.028982E+00 3.882225E+00 -4.786707E-01 + 1.700000E+00 6.000000E+01 2 4.845512E+00 -4.624642E+01 3.350954E+00 -3.500014E+00 + 1.700000E+00 6.000000E+01 3 1.029428E+00 -5.107076E+00 1.025342E+00 -9.163695E-02 + 1.700000E+00 6.000000E+01 4 1.075074E+01 -9.466867E+01 -8.750406E-01 -1.071507E+01 + 1.700000E+00 6.000000E+01 5 3.100899E+00 1.428822E+02 -2.472644E+00 1.871257E+00 + 1.700000E+00 6.000000E+01 6 9.706261E+01 1.629150E+02 -9.277924E+01 2.851603E+01 + 1.700000E+00 9.000000E+01 1 7.440038E-06 -3.070845E+01 6.396773E-06 -3.799403E-06 + 1.700000E+00 9.000000E+01 2 1.270294E+01 -8.442886E+01 1.233221E+00 -1.264294E+01 + 1.700000E+00 9.000000E+01 3 4.901777E-01 -1.579370E+02 -4.542825E-01 -1.841238E-01 + 1.700000E+00 9.000000E+01 4 8.660085E+00 -1.339957E+02 -6.015331E+00 -6.229998E+00 + 1.700000E+00 9.000000E+01 5 6.433670E-06 1.572520E+02 -5.933221E-06 2.487768E-06 + 1.700000E+00 9.000000E+01 6 6.261227E-04 1.977188E+01 5.892108E-04 2.118024E-04 + 1.800000E+00 0.000000E+00 1 1.563779E+01 -2.521997E+01 1.414717E+01 -6.663180E+00 + 1.800000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.800000E+00 0.000000E+00 3 8.863202E-01 8.969315E+00 8.754823E-01 1.381822E-01 + 1.800000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.800000E+00 0.000000E+00 5 1.281577E+01 1.564779E+02 -1.175086E+01 5.114805E+00 + 1.800000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.800000E+00 3.000000E+01 1 2.043249E+01 -1.258618E+02 -1.197001E+01 -1.655915E+01 + 1.800000E+00 3.000000E+01 2 1.070184E+01 -1.181437E+02 -5.047898E+00 -9.436531E+00 + 1.800000E+00 3.000000E+01 3 1.688774E+00 -5.875546E+01 8.759534E-01 -1.443837E+00 + 1.800000E+00 3.000000E+01 4 9.695031E+00 7.104430E+01 3.149306E+00 9.169270E+00 + 1.800000E+00 3.000000E+01 5 1.565632E+01 5.198190E+01 9.642890E+00 1.233430E+01 + 1.800000E+00 3.000000E+01 6 2.845789E+02 -2.323301E+01 2.615019E+02 -1.122582E+02 + 1.800000E+00 6.000000E+01 1 1.510823E+01 -1.385775E+02 -1.132893E+01 -9.995703E+00 + 1.800000E+00 6.000000E+01 2 1.004253E+01 -8.650637E+01 6.119674E-01 -1.002386E+01 + 1.800000E+00 6.000000E+01 3 1.388990E+00 6.042284E+00 1.381273E+00 1.462084E-01 + 1.800000E+00 6.000000E+01 4 1.351580E+01 -1.059756E+02 -3.719937E+00 -1.299381E+01 + 1.800000E+00 6.000000E+01 5 1.413674E+01 4.748552E+01 9.553273E+00 1.042028E+01 + 1.800000E+00 6.000000E+01 6 3.829813E+02 -1.331674E+01 3.726835E+02 -8.821362E+01 + 1.800000E+00 9.000000E+01 1 5.628297E-06 1.162374E+02 -2.488218E-06 5.048415E-06 + 1.800000E+00 9.000000E+01 2 6.767492E+00 -4.651331E+01 4.657294E+00 -4.910047E+00 + 1.800000E+00 9.000000E+01 3 1.506869E+00 -6.931219E+01 5.323405E-01 -1.409705E+00 + 1.800000E+00 9.000000E+01 4 1.066799E+01 -9.853442E+01 -1.583167E+00 -1.054986E+01 + 1.800000E+00 9.000000E+01 5 4.086576E-06 -6.425894E+01 1.774819E-06 -3.681049E-06 + 1.800000E+00 9.000000E+01 6 6.607128E-04 -2.933037E+01 5.760159E-04 -3.236466E-04 + 1.900000E+00 0.000000E+00 1 2.451026E+01 -1.332121E+02 -1.678221E+01 -1.786365E+01 + 1.900000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.900000E+00 0.000000E+00 3 1.532402E+00 2.599337E+01 1.377392E+00 6.716014E-01 + 1.900000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.900000E+00 0.000000E+00 5 2.241921E+01 4.611429E+01 1.554149E+01 1.615807E+01 + 1.900000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.900000E+00 3.000000E+01 1 1.175581E+01 -9.466068E+01 -9.552123E-01 -1.171694E+01 + 1.900000E+00 3.000000E+01 2 9.560308E+00 -9.428857E+01 -7.149178E-01 -9.533540E+00 + 1.900000E+00 3.000000E+01 3 1.041836E+00 -5.468043E+01 6.023233E-01 -8.500760E-01 + 1.900000E+00 3.000000E+01 4 8.651684E+00 7.486741E+01 2.258555E+00 8.351681E+00 + 1.900000E+00 3.000000E+01 5 8.733264E+00 8.609362E+01 5.949658E-01 8.712974E+00 + 1.900000E+00 3.000000E+01 6 1.218528E+02 1.527181E+02 -1.082982E+02 5.585350E+01 + 1.900000E+00 6.000000E+01 1 4.766725E+00 1.457030E+02 -3.937923E+00 2.685968E+00 + 1.900000E+00 6.000000E+01 2 7.627123E+00 6.175206E+01 3.609826E+00 6.718791E+00 + 1.900000E+00 6.000000E+01 3 1.806216E+00 -1.179529E+00 1.805833E+00 -3.718132E-02 + 1.900000E+00 6.000000E+01 4 2.338598E+00 5.864749E+01 1.216777E+00 1.997122E+00 + 1.900000E+00 6.000000E+01 5 4.262382E+00 -1.407905E+01 4.134345E+00 -1.036868E+00 + 1.900000E+00 6.000000E+01 6 1.326395E+02 -1.746618E+02 -1.320642E+02 -1.234013E+01 + 1.900000E+00 9.000000E+01 1 5.604497E-06 6.239099E+00 5.571302E-06 6.090841E-07 + 1.900000E+00 9.000000E+01 2 1.889650E+01 -1.268181E+02 -1.132423E+01 -1.512744E+01 + 1.900000E+00 9.000000E+01 3 1.551565E+00 -1.180688E+02 -7.300589E-01 -1.369075E+00 + 1.900000E+00 9.000000E+01 4 2.209306E+01 -1.472831E+02 -1.858802E+01 -1.194106E+01 + 1.900000E+00 9.000000E+01 5 6.493098E-06 -1.682033E+02 -6.355958E-06 -1.327448E-06 + 1.900000E+00 9.000000E+01 6 5.750424E-04 -4.119217E+01 4.327223E-04 -3.787153E-04 + 2.000000E+00 0.000000E+00 1 5.821302E+00 -6.600632E+01 2.367150E+00 -5.318286E+00 + 2.000000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000000E+00 0.000000E+00 3 8.212474E-01 -5.246426E+00 8.178069E-01 -7.509445E-02 + 2.000000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000000E+00 0.000000E+00 5 5.942253E+00 1.149928E+02 -2.510632E+00 5.385824E+00 + 2.000000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000000E+00 3.000000E+01 1 2.971290E+01 1.648385E+02 -2.867867E+01 7.771135E+00 + 2.000000E+00 3.000000E+01 2 2.109365E+01 -1.544192E+02 -1.902600E+01 -9.107873E+00 + 2.000000E+00 3.000000E+01 3 1.116087E+00 1.449782E+02 -9.140012E-01 6.405092E-01 + 2.000000E+00 3.000000E+01 4 1.737694E+01 1.613567E+02 -1.646511E+01 5.554991E+00 + 2.000000E+00 3.000000E+01 5 3.115120E+01 -2.130091E+01 2.902312E+01 -1.131617E+01 + 2.000000E+00 3.000000E+01 6 1.132266E+02 -9.659354E+01 -1.300126E+01 -1.124777E+02 + 2.000000E+00 6.000000E+01 1 1.129384E+01 -7.250443E+01 3.395290E+00 -1.077139E+01 + 2.000000E+00 6.000000E+01 2 8.313642E+00 1.825148E+01 7.895391E+00 2.603735E+00 + 2.000000E+00 6.000000E+01 3 3.279949E+00 -2.767537E+01 2.904701E+00 -1.523410E+00 + 2.000000E+00 6.000000E+01 4 1.487036E+01 1.412784E+01 1.442059E+01 3.629652E+00 + 2.000000E+00 6.000000E+01 5 1.104694E+01 1.092108E+02 -3.634940E+00 1.043178E+01 + 2.000000E+00 6.000000E+01 6 5.640735E+02 1.091309E+02 -1.848626E+02 5.329210E+02 + 2.000000E+00 9.000000E+01 1 1.187785E-05 8.651313E+01 7.224082E-07 1.185586E-05 + 2.000000E+00 9.000000E+01 2 3.749706E+01 -1.751489E+02 -3.736274E+01 -3.170978E+00 + 2.000000E+00 9.000000E+01 3 1.734941E+00 -6.733071E+01 6.686662E-01 -1.600908E+00 + 2.000000E+00 9.000000E+01 4 3.541190E+01 -1.760981E+02 -3.532981E+01 -2.409709E+00 + 2.000000E+00 9.000000E+01 5 1.130888E-05 -8.963467E+01 7.210677E-08 -1.130865E-05 + 2.000000E+00 9.000000E+01 6 7.684740E-04 -6.270164E+01 3.524407E-04 -6.828893E-04 + 2.100000E+00 0.000000E+00 1 3.469384E+01 -1.632826E+02 -3.322751E+01 -9.979723E+00 + 2.100000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.100000E+00 0.000000E+00 3 3.800893E-01 1.574097E+02 -3.509271E-01 1.460069E-01 + 2.100000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.100000E+00 0.000000E+00 5 3.752528E+01 1.653084E+01 3.597424E+01 1.067712E+01 + 2.100000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.100000E+00 3.000000E+01 1 3.390757E+00 4.897110E+01 2.225828E+00 2.557914E+00 + 2.100000E+00 3.000000E+01 2 8.254489E+00 -9.804829E+01 -1.155693E+00 -8.173185E+00 + 2.100000E+00 3.000000E+01 3 2.355528E+00 1.350706E+02 -1.667662E+00 1.663556E+00 + 2.100000E+00 3.000000E+01 4 4.972169E+00 2.617470E+01 4.462290E+00 2.193272E+00 + 2.100000E+00 3.000000E+01 5 8.047062E+00 -1.089703E+02 -2.615923E+00 -7.610003E+00 + 2.100000E+00 3.000000E+01 6 1.375585E+02 1.384727E+02 -1.029817E+02 9.119812E+01 + 2.100000E+00 6.000000E+01 1 9.750317E+00 -1.259258E+02 -5.720868E+00 -7.895591E+00 + 2.100000E+00 6.000000E+01 2 3.188938E+00 4.149963E+01 2.388387E+00 2.113039E+00 + 2.100000E+00 6.000000E+01 3 2.481020E+00 -4.064047E+01 1.882626E+00 -1.615914E+00 + 2.100000E+00 6.000000E+01 4 1.363382E+01 6.727907E+01 5.265969E+00 1.257579E+01 + 2.100000E+00 6.000000E+01 5 1.113503E+01 5.728171E+01 6.018582E+00 9.368325E+00 + 2.100000E+00 6.000000E+01 6 1.587328E+02 1.919057E+01 1.499120E+02 5.217724E+01 + 2.100000E+00 9.000000E+01 1 7.526227E-06 -6.560124E+01 3.108969E-06 -6.854080E-06 + 2.100000E+00 9.000000E+01 2 2.984016E+01 1.745603E+02 -2.970577E+01 2.828802E+00 + 2.100000E+00 9.000000E+01 3 2.147939E+00 -1.599565E+02 -2.017844E+00 -7.361711E-01 + 2.100000E+00 9.000000E+01 4 2.823634E+01 1.683424E+02 -2.765389E+01 5.705529E+00 + 2.100000E+00 9.000000E+01 5 8.384823E-06 1.164150E+02 -3.730158E-06 7.509405E-06 + 2.100000E+00 9.000000E+01 6 6.949179E-04 -1.031911E+02 -1.585795E-04 -6.765822E-04 + 2.200000E+00 0.000000E+00 1 1.840914E+01 1.246068E+02 -1.045532E+01 1.515199E+01 + 2.200000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.200000E+00 0.000000E+00 3 3.016562E+00 7.359667E+01 8.518687E-01 2.893780E+00 + 2.200000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.200000E+00 0.000000E+00 5 2.189817E+01 -5.459550E+01 1.268660E+01 -1.784881E+01 + 2.200000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.200000E+00 3.000000E+01 1 1.003793E+01 1.687380E+02 -9.844638E+00 1.960372E+00 + 2.200000E+00 3.000000E+01 2 7.348200E+00 -1.333114E+02 -5.040593E+00 -5.346819E+00 + 2.200000E+00 3.000000E+01 3 3.990573E+00 1.612579E+02 -3.778970E+00 1.282207E+00 + 2.200000E+00 3.000000E+01 4 2.769185E+00 1.150331E+02 -1.171758E+00 2.509058E+00 + 2.200000E+00 3.000000E+01 5 1.299058E+01 -2.709982E+01 1.156440E+01 -5.917757E+00 + 2.200000E+00 3.000000E+01 6 4.706312E+02 6.546182E+01 1.954529E+02 4.281260E+02 + 2.200000E+00 6.000000E+01 1 9.554170E+00 -5.325864E+01 5.715340E+00 -7.656177E+00 + 2.200000E+00 6.000000E+01 2 5.871254E+00 -1.696238E+02 -5.775238E+00 -1.057474E+00 + 2.200000E+00 6.000000E+01 3 4.580588E+00 -6.968203E+00 4.546754E+00 -5.557101E-01 + 2.200000E+00 6.000000E+01 4 9.044420E+00 9.761833E+01 -1.199051E+00 8.964586E+00 + 2.200000E+00 6.000000E+01 5 1.148960E+01 1.325676E+02 -7.772250E+00 8.461858E+00 + 2.200000E+00 6.000000E+01 6 4.873628E+02 -1.109005E+02 -1.738651E+02 -4.552949E+02 + 2.200000E+00 9.000000E+01 1 6.787387E-06 2.305665E+01 6.245197E-06 2.658220E-06 + 2.200000E+00 9.000000E+01 2 1.074581E+01 1.732706E+02 -1.067178E+01 1.259205E+00 + 2.200000E+00 9.000000E+01 3 4.149904E+00 -1.095534E+02 -1.388911E+00 -3.910579E+00 + 2.200000E+00 9.000000E+01 4 6.907977E+00 1.615725E+02 -6.553764E+00 2.183648E+00 + 2.200000E+00 9.000000E+01 5 8.732525E-06 -1.405445E+02 -6.742548E-06 -5.549329E-06 + 2.200000E+00 9.000000E+01 6 7.234850E-04 -1.137432E+02 -2.913027E-04 -6.622486E-04 + 2.300000E+00 0.000000E+00 1 6.652022E+00 1.714180E+02 -6.577542E+00 9.926440E-01 + 2.300000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.300000E+00 0.000000E+00 3 3.341569E+00 9.958330E+01 -5.563088E-01 3.294936E+00 + 2.300000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.300000E+00 0.000000E+00 5 8.600190E+00 -1.346889E+01 8.363655E+00 -2.003134E+00 + 2.300000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.300000E+00 3.000000E+01 1 2.813330E+01 1.017791E+02 -5.743085E+00 2.754087E+01 + 2.300000E+00 3.000000E+01 2 1.331318E+01 1.719806E+02 -1.318299E+01 1.857306E+00 + 2.300000E+00 3.000000E+01 3 5.697778E+00 1.764393E+02 -5.686778E+00 3.538708E-01 + 2.300000E+00 3.000000E+01 4 1.458461E+01 1.343526E+02 -1.019570E+01 1.042874E+01 + 2.300000E+00 3.000000E+01 5 4.251502E+01 -7.939967E+01 7.820933E+00 -4.178947E+01 + 2.300000E+00 3.000000E+01 6 2.409720E+02 1.194129E+01 2.357574E+02 4.985936E+01 + 2.300000E+00 6.000000E+01 1 8.122261E+00 -2.673362E+00 8.113421E+00 -3.788389E-01 + 2.300000E+00 6.000000E+01 2 1.754300E+01 -7.681292E+01 4.002109E+00 -1.708040E+01 + 2.300000E+00 6.000000E+01 3 3.457100E+00 6.086721E+01 1.683038E+00 3.019755E+00 + 2.300000E+00 6.000000E+01 4 1.385956E+01 -4.006794E+01 1.060647E+01 -8.921338E+00 + 2.300000E+00 6.000000E+01 5 1.238480E+01 -1.746265E+02 -1.233038E+01 -1.159803E+00 + 2.300000E+00 6.000000E+01 6 8.567575E+02 -1.341973E+02 -5.972726E+02 -6.142466E+02 + 2.300000E+00 9.000000E+01 1 8.110849E-06 5.452580E+01 4.707020E-06 6.605288E-06 + 2.300000E+00 9.000000E+01 2 1.484728E+01 -1.770321E+02 -1.482736E+01 -7.687485E-01 + 2.300000E+00 9.000000E+01 3 3.613738E+00 -4.756544E+01 2.438361E+00 -2.667114E+00 + 2.300000E+00 9.000000E+01 4 1.042713E+01 -1.320228E+02 -6.980190E+00 -7.746091E+00 + 2.300000E+00 9.000000E+01 5 1.129052E-05 -1.152556E+02 -4.817187E-06 -1.021129E-05 + 2.300000E+00 9.000000E+01 6 6.935667E-04 -1.311100E+02 -4.560248E-04 -5.225670E-04 + 2.400000E+00 0.000000E+00 1 6.691988E+01 1.437616E+02 -5.397520E+01 3.955941E+01 + 2.400000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.400000E+00 0.000000E+00 3 2.040703E+00 1.177941E+02 -9.515707E-01 1.805265E+00 + 2.400000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.400000E+00 0.000000E+00 5 9.895098E+01 -3.651546E+01 7.952654E+01 -5.887976E+01 + 2.400000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.400000E+00 3.000000E+01 1 2.056048E+01 -7.887166E+01 3.968325E+00 -2.017389E+01 + 2.400000E+00 3.000000E+01 2 1.794580E+01 -6.599496E+01 7.300655E+00 -1.639366E+01 + 2.400000E+00 3.000000E+01 3 4.279415E+00 -1.772949E+02 -4.274646E+00 -2.019664E-01 + 2.400000E+00 3.000000E+01 4 2.314850E+01 -5.315101E+01 1.388234E+01 -1.852386E+01 + 2.400000E+00 3.000000E+01 5 2.366356E+01 1.133196E+02 -9.367453E+00 2.173051E+01 + 2.400000E+00 3.000000E+01 6 2.629239E+01 1.162468E+02 -1.162751E+01 2.358158E+01 + 2.400000E+00 6.000000E+01 1 1.101585E+01 -7.089606E+01 3.605299E+00 -1.040917E+01 + 2.400000E+00 6.000000E+01 2 2.194420E+01 -7.073899E+01 7.238779E+00 -2.071589E+01 + 2.400000E+00 6.000000E+01 3 2.151742E+00 1.444439E+02 -1.750542E+00 1.251238E+00 + 2.400000E+00 6.000000E+01 4 2.502406E+01 -4.151780E+01 1.873676E+01 -1.658726E+01 + 2.400000E+00 6.000000E+01 5 1.221794E+01 1.362352E+02 -8.823617E+00 8.451142E+00 + 2.400000E+00 6.000000E+01 6 5.474531E+02 -1.368706E+02 -3.995377E+02 -3.742652E+02 + 2.400000E+00 9.000000E+01 1 1.443677E-05 1.781123E+02 -1.442893E-05 4.755645E-07 + 2.400000E+00 9.000000E+01 2 2.785631E+01 -1.771170E+02 -2.782105E+01 -1.401092E+00 + 2.400000E+00 9.000000E+01 3 1.413268E+00 2.660327E+01 1.263643E+00 6.328756E-01 + 2.400000E+00 9.000000E+01 4 1.771157E+01 -1.481608E+02 -1.504654E+01 -9.343523E+00 + 2.400000E+00 9.000000E+01 5 2.027583E-05 -8.507624E+00 2.005272E-05 -2.999627E-06 + 2.400000E+00 9.000000E+01 6 9.715804E-04 -1.369534E+02 -7.100300E-04 -6.631936E-04 + 2.500000E+00 0.000000E+00 1 5.129078E+01 1.138478E+02 -2.073730E+01 4.691171E+01 + 2.500000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.500000E+00 0.000000E+00 3 1.529491E+00 1.225288E+02 -8.224432E-01 1.289546E+00 + 2.500000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.500000E+00 0.000000E+00 5 8.451809E+01 -6.702504E+01 3.298985E+01 -7.781374E+01 + 2.500000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.500000E+00 3.000000E+01 1 4.145443E+01 -4.538499E+01 2.911509E+01 -2.950900E+01 + 2.500000E+00 3.000000E+01 2 3.950846E+01 -6.894279E+01 1.419539E+01 -3.687017E+01 + 2.500000E+00 3.000000E+01 3 3.751704E+00 1.699554E+02 -3.694198E+00 6.543530E-01 + 2.500000E+00 3.000000E+01 4 6.341410E+01 -6.394818E+01 2.785045E+01 -5.697105E+01 + 2.500000E+00 3.000000E+01 5 6.103278E+01 1.379704E+02 -4.533508E+01 4.086234E+01 + 2.500000E+00 3.000000E+01 6 2.903393E+02 5.470456E+01 1.677559E+02 2.369702E+02 + 2.500000E+00 6.000000E+01 1 4.370257E+00 1.419348E+02 -3.440747E+00 2.694514E+00 + 2.500000E+00 6.000000E+01 2 1.341662E+01 -6.668523E+01 5.310061E+00 -1.232108E+01 + 2.500000E+00 6.000000E+01 3 1.843527E+00 1.454165E+02 -1.517775E+00 1.046398E+00 + 2.500000E+00 6.000000E+01 4 2.508925E+01 1.343679E+01 2.440248E+01 5.830053E+00 + 2.500000E+00 6.000000E+01 5 1.784713E+01 -8.089987E+01 2.822708E+00 -1.762249E+01 + 2.500000E+00 6.000000E+01 6 2.772294E+02 3.482975E+01 2.275645E+02 1.583367E+02 + 2.500000E+00 9.000000E+01 1 4.373749E-06 -8.041764E+01 7.280764E-07 -4.312723E-06 + 2.500000E+00 9.000000E+01 2 3.571795E+01 1.595034E+02 -3.345677E+01 1.250667E+01 + 2.500000E+00 9.000000E+01 3 1.586350E+00 9.202799E+01 -5.613745E-02 1.585356E+00 + 2.500000E+00 9.000000E+01 4 3.055895E+01 1.481671E+02 -2.596258E+01 1.611813E+01 + 2.500000E+00 9.000000E+01 5 2.473950E-06 1.016150E+02 -4.980903E-07 2.423290E-06 + 2.500000E+00 9.000000E+01 6 8.151199E-04 -1.394990E+02 -6.198129E-04 -5.293887E-04 + 2.600000E+00 0.000000E+00 1 2.374993E+01 8.941797E+01 2.412556E-01 2.374870E+01 + 2.600000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.600000E+00 0.000000E+00 3 1.379885E+00 1.207559E+02 -7.056479E-01 1.185809E+00 + 2.600000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.600000E+00 0.000000E+00 5 3.882188E+01 -9.195899E+01 -1.327094E+00 -3.879919E+01 + 2.600000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.600000E+00 3.000000E+01 1 2.512787E+01 -7.338380E+01 7.185550E+00 -2.407857E+01 + 2.600000E+00 3.000000E+01 2 3.913450E+01 -7.277780E+01 1.158687E+01 -3.737986E+01 + 2.600000E+00 3.000000E+01 3 4.915434E+00 1.651986E+02 -4.752327E+00 1.255740E+00 + 2.600000E+00 3.000000E+01 4 7.238557E+01 -6.670432E+01 2.862678E+01 -6.648442E+01 + 2.600000E+00 3.000000E+01 5 3.821024E+01 9.774843E+01 -5.151649E+00 3.786136E+01 + 2.600000E+00 3.000000E+01 6 7.005328E+02 1.571709E+01 6.743406E+02 1.897657E+02 + 2.600000E+00 6.000000E+01 1 1.314660E+01 1.011741E+02 -2.547699E+00 1.289738E+01 + 2.600000E+00 6.000000E+01 2 1.136843E+01 9.581977E+01 -1.152753E+00 1.130984E+01 + 2.600000E+00 6.000000E+01 3 2.856414E+00 1.617910E+02 -2.713374E+00 8.925833E-01 + 2.600000E+00 6.000000E+01 4 6.483476E+01 8.739442E+01 2.947407E+00 6.476773E+01 + 2.600000E+00 6.000000E+01 5 4.451958E+01 -7.846105E+01 8.905430E+00 -4.361979E+01 + 2.600000E+00 6.000000E+01 6 9.317444E+02 2.763584E+01 8.254451E+02 4.321898E+02 + 2.600000E+00 9.000000E+01 1 4.715702E-06 -1.099771E+02 -1.611092E-06 -4.431955E-06 + 2.600000E+00 9.000000E+01 2 4.229353E+01 1.186479E+02 -2.027663E+01 3.711604E+01 + 2.600000E+00 9.000000E+01 3 1.893995E+00 1.071196E+02 -5.575296E-01 1.810077E+00 + 2.600000E+00 9.000000E+01 4 5.444688E+01 9.005308E+01 -5.043561E-02 5.444685E+01 + 2.600000E+00 9.000000E+01 5 4.799822E-06 -1.704821E+00 4.797698E-06 -1.427964E-07 + 2.600000E+00 9.000000E+01 6 8.340525E-04 -1.562957E+02 -7.636857E-04 -3.353025E-04 + 2.700000E+00 0.000000E+00 1 1.285704E+01 1.376649E+02 -9.504169E+00 8.658763E+00 + 2.700000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.700000E+00 0.000000E+00 3 1.071230E+00 1.054962E+02 -2.862057E-01 1.032289E+00 + 2.700000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.700000E+00 0.000000E+00 5 2.219130E+01 -2.058312E+01 2.077468E+01 -7.801703E+00 + 2.700000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.700000E+00 3.000000E+01 1 1.246238E+01 -1.406525E+02 -9.637338E+00 -7.901432E+00 + 2.700000E+00 3.000000E+01 2 1.873427E+01 -5.288271E+01 1.130517E+01 -1.493874E+01 + 2.700000E+00 3.000000E+01 3 5.321106E+00 1.741083E+02 -5.292998E+00 5.462034E-01 + 2.700000E+00 3.000000E+01 4 4.667109E+01 -3.742222E+01 3.706520E+01 -2.836127E+01 + 2.700000E+00 3.000000E+01 5 2.527288E+01 2.607484E+01 2.270062E+01 1.110856E+01 + 2.700000E+00 3.000000E+01 6 7.275867E+02 4.028961E+00 7.257886E+02 5.112075E+01 + 2.700000E+00 6.000000E+01 1 3.480887E+01 1.156737E+02 -1.508077E+01 3.137241E+01 + 2.700000E+00 6.000000E+01 2 3.563494E+01 1.025745E+02 -7.758019E+00 3.478020E+01 + 2.700000E+00 6.000000E+01 3 3.903898E+00 1.766144E+02 -3.897084E+00 2.305482E-01 + 2.700000E+00 6.000000E+01 4 1.007721E+02 1.107006E+02 -3.562133E+01 9.426632E+01 + 2.700000E+00 6.000000E+01 5 7.932731E+01 -6.428683E+01 3.441743E+01 -7.147211E+01 + 2.700000E+00 6.000000E+01 6 1.200961E+03 1.413786E+01 1.164585E+03 2.933418E+02 + 2.700000E+00 9.000000E+01 1 1.373922E-05 -5.906470E+01 7.062917E-06 -1.178479E-05 + 2.700000E+00 9.000000E+01 2 8.003942E+01 8.975844E+01 3.374447E-01 8.003871E+01 + 2.700000E+00 9.000000E+01 3 1.309628E+00 1.092766E+02 -4.323460E-01 1.236205E+00 + 2.700000E+00 9.000000E+01 4 1.853950E+02 7.520155E+01 4.735352E+01 1.792455E+02 + 2.700000E+00 9.000000E+01 5 1.659808E-05 1.194172E+02 -8.152405E-06 1.445803E-05 + 2.700000E+00 9.000000E+01 6 8.618580E-04 -1.684376E+02 -8.443682E-04 -1.727471E-04 + 2.799999E+00 0.000000E+00 1 3.084495E+01 1.363763E+02 -2.232826E+01 2.128050E+01 + 2.799999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.799999E+00 0.000000E+00 3 1.018026E+00 4.981052E+01 6.569498E-01 7.776847E-01 + 2.799999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.799999E+00 0.000000E+00 5 6.890652E+01 -3.809226E+01 5.423070E+01 -4.251048E+01 + 2.799999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.799999E+00 3.000000E+01 1 7.436464E+00 6.883179E+01 2.685361E+00 6.934684E+00 + 2.799999E+00 3.000000E+01 2 4.692299E+00 1.573202E+01 4.516528E+00 1.272262E+00 + 2.799999E+00 3.000000E+01 3 5.127012E+00 1.705119E+02 -5.056873E+00 8.451540E-01 + 2.799999E+00 3.000000E+01 4 1.385750E+01 2.200511E+01 1.284799E+01 5.192256E+00 + 2.799999E+00 3.000000E+01 5 2.142159E+01 -1.054122E+02 -5.693040E+00 -2.065124E+01 + 2.799999E+00 3.000000E+01 6 1.663048E+02 3.039669E+01 1.434450E+02 8.414754E+01 + 2.799999E+00 6.000000E+01 1 4.148475E+01 1.089419E+02 -1.346630E+01 3.923829E+01 + 2.799999E+00 6.000000E+01 2 4.794329E+01 9.155702E+01 -1.302705E+00 4.792559E+01 + 2.799999E+00 6.000000E+01 3 4.497569E+00 1.653757E+02 -4.351856E+00 1.135548E+00 + 2.799999E+00 6.000000E+01 4 1.051302E+02 9.357171E+01 -6.549361E+00 1.049260E+02 + 2.799999E+00 6.000000E+01 5 9.666524E+01 -7.074407E+01 3.187907E+01 -9.125729E+01 + 2.799999E+00 6.000000E+01 6 1.340882E+03 3.476051E+00 1.338415E+03 8.129942E+01 + 2.799999E+00 9.000000E+01 1 1.634091E-05 -2.739770E+01 1.450801E-05 -7.519499E-06 + 2.799999E+00 9.000000E+01 2 1.083563E+02 9.151974E+01 -2.873775E+00 1.083182E+02 + 2.799999E+00 9.000000E+01 3 3.234695E+00 7.527977E+01 8.219343E-01 3.128526E+00 + 2.799999E+00 9.000000E+01 4 2.391108E+02 9.031908E+01 -1.331573E+00 2.391071E+02 + 2.799999E+00 9.000000E+01 5 2.194817E-05 1.451231E+02 -1.800589E-05 1.255030E-05 + 2.799999E+00 9.000000E+01 6 1.012854E-03 -1.762982E+02 -1.010741E-03 -6.539427E-05 + 2.899999E+00 0.000000E+00 1 5.913933E+01 7.511961E+01 1.518710E+01 5.715604E+01 + 2.899999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.899999E+00 0.000000E+00 3 1.474937E+00 3.119394E+01 1.261689E+00 7.639238E-01 + 2.899999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.899999E+00 0.000000E+00 5 1.361311E+02 -9.472819E+01 -1.122113E+01 -1.356678E+02 + 2.899999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.899999E+00 3.000000E+01 1 1.404502E+01 7.505493E+01 3.622111E+00 1.356993E+01 + 2.899999E+00 3.000000E+01 2 1.182106E+01 -9.669734E+01 -1.378627E+00 -1.174040E+01 + 2.899999E+00 3.000000E+01 3 6.231650E+00 1.707256E+02 -6.150188E+00 1.004316E+00 + 2.899999E+00 3.000000E+01 4 2.915959E+01 -1.004853E+02 -5.306571E+00 -2.867267E+01 + 2.899999E+00 3.000000E+01 5 3.683768E+01 -1.315670E+02 -2.444164E+01 -2.756121E+01 + 2.899999E+00 3.000000E+01 6 8.204958E+02 1.632954E+02 -7.858704E+02 2.358412E+02 + 2.899999E+00 6.000000E+01 1 5.087309E+01 1.082702E+02 -1.594861E+01 4.830852E+01 + 2.899999E+00 6.000000E+01 2 5.881094E+01 8.293089E+01 7.237651E+00 5.836389E+01 + 2.899999E+00 6.000000E+01 3 6.112622E+00 1.666014E+02 -5.946246E+00 1.416439E+00 + 2.899999E+00 6.000000E+01 4 1.303272E+02 8.085902E+01 2.070435E+01 1.286721E+02 + 2.899999E+00 6.000000E+01 5 1.126831E+02 -7.312285E+01 3.271422E+01 -1.078298E+02 + 2.899999E+00 6.000000E+01 6 1.045594E+03 7.533033E+00 1.036570E+03 1.370750E+02 + 2.899999E+00 9.000000E+01 1 2.153102E-05 2.575455E+01 1.939221E-05 9.355592E-06 + 2.899999E+00 9.000000E+01 2 1.126526E+02 8.799042E+01 3.950352E+00 1.125833E+02 + 2.899999E+00 9.000000E+01 3 4.730039E+00 9.452670E+01 -3.733119E-01 4.715284E+00 + 2.899999E+00 9.000000E+01 4 2.431560E+02 8.754437E+01 1.041817E+01 2.429327E+02 + 2.899999E+00 9.000000E+01 5 3.590472E-05 -1.538434E+02 -3.222781E-05 -1.582773E-05 + 2.899999E+00 9.000000E+01 6 1.082301E-03 -1.765180E+02 -1.080303E-03 -6.573328E-05 + 2.999999E+00 0.000000E+00 1 1.535824E+02 7.256065E+01 4.602804E+01 1.465229E+02 + 2.999999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.999999E+00 0.000000E+00 3 1.969451E+00 5.637770E+01 1.090516E+00 1.639974E+00 + 2.999999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.999999E+00 0.000000E+00 5 3.425206E+02 -1.060463E+02 -9.467750E+01 -3.291755E+02 + 2.999999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.999999E+00 3.000000E+01 1 5.881850E+01 -1.358674E+02 -4.221578E+01 -4.095662E+01 + 2.999999E+00 3.000000E+01 2 3.964449E+01 -9.267473E+01 -1.850040E+00 -3.960130E+01 + 2.999999E+00 3.000000E+01 3 6.848557E+00 1.763287E+02 -6.834503E+00 4.385305E-01 + 2.999999E+00 3.000000E+01 4 9.575523E+01 -9.607970E+01 -1.014161E+01 -9.521666E+01 + 2.999999E+00 3.000000E+01 5 1.050537E+02 5.814314E+01 5.544724E+01 8.922939E+01 + 2.999999E+00 3.000000E+01 6 1.311709E+03 1.717300E+02 -1.298069E+03 1.886731E+02 + 2.999999E+00 6.000000E+01 1 4.004496E+01 1.390207E+02 -3.023180E+01 2.626094E+01 + 2.999999E+00 6.000000E+01 2 5.293253E+01 8.055581E+01 8.685534E+00 5.221508E+01 + 2.999999E+00 6.000000E+01 3 7.548622E+00 1.712188E+02 -7.460140E+00 1.152391E+00 + 2.999999E+00 6.000000E+01 4 1.187431E+02 7.564075E+01 2.944842E+01 1.150335E+02 + 2.999999E+00 6.000000E+01 5 8.239848E+01 -4.672632E+01 5.648284E+01 -5.999332E+01 + 2.999999E+00 6.000000E+01 6 2.921517E+02 2.838828E+01 2.570193E+02 1.389019E+02 + 2.999999E+00 9.000000E+01 1 2.870632E-05 1.225683E+02 -1.545275E-05 2.419226E-05 + 2.999999E+00 9.000000E+01 2 1.085063E+02 8.412341E+01 1.110955E+01 1.079361E+02 + 2.999999E+00 9.000000E+01 3 6.175937E+00 1.148498E+02 -2.595377E+00 5.604125E+00 + 2.999999E+00 9.000000E+01 4 2.412059E+02 8.263962E+01 3.090086E+01 2.392184E+02 + 2.999999E+00 9.000000E+01 5 7.033809E-05 -5.379518E+01 4.154685E-05 -5.675655E-05 + 2.999999E+00 9.000000E+01 6 1.061258E-03 -1.797259E+02 -1.061246E-03 -5.077388E-06 + 3.099999E+00 0.000000E+00 1 1.352772E+02 7.965231E+01 2.429864E+01 1.330770E+02 + 3.099999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.099999E+00 0.000000E+00 3 4.043180E+00 9.310086E+01 -2.187111E-01 4.037260E+00 + 3.099999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.099999E+00 0.000000E+00 5 3.204205E+02 -1.041802E+02 -7.849390E+01 -3.106574E+02 + 3.099999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.099999E+00 3.000000E+01 1 1.023205E+02 -1.063303E+02 -2.876989E+01 -9.819260E+01 + 3.099999E+00 3.000000E+01 2 5.650270E+01 -9.243196E+01 -2.397580E+00 -5.645181E+01 + 3.099999E+00 3.000000E+01 3 5.845279E+00 -1.780309E+02 -5.841827E+00 -2.008460E-01 + 3.099999E+00 3.000000E+01 4 1.438770E+02 -9.665790E+01 -1.668124E+01 -1.429067E+02 + 3.099999E+00 3.000000E+01 5 2.320557E+02 8.034755E+01 3.890910E+01 2.287705E+02 + 3.099999E+00 3.000000E+01 6 1.158180E+03 1.715860E+02 -1.145714E+03 1.694695E+02 + 3.099999E+00 6.000000E+01 1 1.398031E+01 1.693249E+02 -1.373836E+01 2.589702E+00 + 3.099999E+00 6.000000E+01 2 3.398200E+01 6.586255E+01 1.389616E+01 3.101085E+01 + 3.099999E+00 6.000000E+01 3 7.300803E+00 -1.706796E+02 -7.204419E+00 -1.182402E+00 + 3.099999E+00 6.000000E+01 4 7.537634E+01 5.599914E+01 4.215086E+01 6.248919E+01 + 3.099999E+00 6.000000E+01 5 2.412563E+01 2.367664E+01 2.209489E+01 9.688235E+00 + 3.099999E+00 6.000000E+01 6 5.216992E+02 1.745547E+02 -5.193450E+02 4.950640E+01 + 3.099999E+00 9.000000E+01 1 2.174027E-05 -1.530094E+02 -1.937235E-05 -9.866681E-06 + 3.099999E+00 9.000000E+01 2 9.793117E+01 7.983202E+01 1.728826E+01 9.639310E+01 + 3.099999E+00 9.000000E+01 3 6.437273E+00 1.435798E+02 -5.179974E+00 3.821827E+00 + 3.099999E+00 9.000000E+01 4 2.273067E+02 7.777940E+01 4.811544E+01 2.221559E+02 + 3.099999E+00 9.000000E+01 5 6.417438E-05 1.557107E+01 6.181907E-05 1.722655E-05 + 3.099999E+00 9.000000E+01 6 1.061670E-03 1.746794E+02 -1.057096E-03 9.844666E-05 + 3.199999E+00 0.000000E+00 1 9.313126E+01 7.703487E+01 2.089476E+01 9.075704E+01 + 3.199999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.199999E+00 0.000000E+00 3 6.376946E+00 1.272288E+02 -3.858049E+00 5.077490E+00 + 3.199999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.199999E+00 0.000000E+00 5 2.207682E+02 -1.136822E+02 -8.867440E+01 -2.021768E+02 + 3.199999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.199999E+00 3.000000E+01 1 1.148556E+02 -1.046191E+02 -2.898855E+01 -1.111372E+02 + 3.199999E+00 3.000000E+01 2 6.264732E+01 -1.008677E+02 -1.181164E+01 -6.152375E+01 + 3.199999E+00 3.000000E+01 3 4.421484E+00 -1.709751E+02 -4.366747E+00 -6.935720E-01 + 3.199999E+00 3.000000E+01 4 1.708979E+02 -1.044649E+02 -4.268807E+01 -1.654806E+02 + 3.199999E+00 3.000000E+01 5 2.763033E+02 7.809556E+01 5.699586E+01 2.703609E+02 + 3.199999E+00 3.000000E+01 6 7.071581E+02 1.658765E+02 -6.857822E+02 1.725552E+02 + 3.199999E+00 6.000000E+01 1 1.593430E+01 -1.136228E+02 -6.385092E+00 -1.459906E+01 + 3.199999E+00 6.000000E+01 2 1.738074E+01 2.798335E+01 1.534865E+01 8.155304E+00 + 3.199999E+00 6.000000E+01 3 4.390622E+00 1.773398E+02 -4.385890E+00 2.037780E-01 + 3.199999E+00 6.000000E+01 4 4.314693E+01 -5.031633E+00 4.298066E+01 -3.784233E+00 + 3.199999E+00 6.000000E+01 5 8.151366E+01 8.811880E+01 2.675864E+00 8.146973E+01 + 3.199999E+00 6.000000E+01 6 1.115759E+03 1.776656E+02 -1.114833E+03 4.544571E+01 + 3.199999E+00 9.000000E+01 1 1.641946E-05 -1.242221E+02 -9.234337E-06 -1.357666E-05 + 3.199999E+00 9.000000E+01 2 8.466059E+01 7.749667E+01 1.832870E+01 8.265273E+01 + 3.199999E+00 9.000000E+01 3 5.032353E+00 1.462475E+02 -4.184126E+00 2.796008E+00 + 3.199999E+00 9.000000E+01 4 2.031117E+02 7.519678E+01 5.189503E+01 1.963702E+02 + 3.199999E+00 9.000000E+01 5 4.495156E-05 3.121729E+01 3.844293E-05 2.329773E-05 + 3.199999E+00 9.000000E+01 6 1.099406E-03 1.695473E+02 -1.081162E-03 1.994592E-04 + 3.299999E+00 0.000000E+00 1 4.678250E+01 8.237811E+01 6.204999E+00 4.636917E+01 + 3.299999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.299999E+00 0.000000E+00 3 7.054717E+00 1.426483E+02 -5.607983E+00 4.280135E+00 + 3.299999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.299999E+00 0.000000E+00 5 1.004503E+02 -1.286896E+02 -6.279161E+01 -7.840590E+01 + 3.299999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.299999E+00 3.000000E+01 1 1.055210E+02 -1.072739E+02 -3.133335E+01 -1.007616E+02 + 3.299999E+00 3.000000E+01 2 6.150303E+01 -1.091924E+02 -2.021861E+01 -5.808468E+01 + 3.299999E+00 3.000000E+01 3 2.173652E+00 -1.587816E+02 -2.026295E+00 -7.866974E-01 + 3.299999E+00 3.000000E+01 4 1.770257E+02 -1.119721E+02 -6.623500E+01 -1.641676E+02 + 3.299999E+00 3.000000E+01 5 2.544291E+02 7.011642E+01 8.653385E+01 2.392614E+02 + 3.299999E+00 3.000000E+01 6 2.318566E+02 1.571164E+02 -2.136087E+02 9.015990E+01 + 3.299999E+00 6.000000E+01 1 3.435871E+01 -9.594345E+01 -3.557737E+00 -3.417402E+01 + 3.299999E+00 6.000000E+01 2 2.065511E+01 -6.633234E+01 8.291598E+00 -1.891780E+01 + 3.299999E+00 6.000000E+01 3 3.711243E+00 1.619598E+02 -3.528796E+00 1.149315E+00 + 3.299999E+00 6.000000E+01 4 9.041335E+01 -7.612052E+01 2.168839E+01 -8.777351E+01 + 3.299999E+00 6.000000E+01 5 1.689747E+02 9.353695E+01 -1.042441E+01 1.686529E+02 + 3.299999E+00 6.000000E+01 6 1.552885E+03 1.734821E+02 -1.542848E+03 1.762744E+02 + 3.299999E+00 9.000000E+01 1 1.429221E-05 -1.106028E+02 -5.029259E-06 -1.337811E-05 + 3.299999E+00 9.000000E+01 2 6.621753E+01 7.656819E+01 1.538153E+01 6.440629E+01 + 3.299999E+00 9.000000E+01 3 5.661932E+00 1.466332E+02 -4.728658E+00 3.114044E+00 + 3.299999E+00 9.000000E+01 4 1.632255E+02 7.372087E+01 4.575491E+01 1.566814E+02 + 3.299999E+00 9.000000E+01 5 3.369616E-05 3.174554E+01 2.865498E-05 1.772915E-05 + 3.299999E+00 9.000000E+01 6 1.156401E-03 1.667464E+02 -1.125600E-03 2.651193E-04 + 3.399999E+00 0.000000E+00 1 1.361654E+01 1.252903E+02 -7.866537E+00 1.111431E+01 + 3.399999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.399999E+00 0.000000E+00 3 6.630826E+00 1.534148E+02 -5.929750E+00 2.967477E+00 + 3.399999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.399999E+00 0.000000E+00 5 3.057225E+01 1.626662E+02 -2.918381E+01 9.108666E+00 + 3.399999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.399999E+00 3.000000E+01 1 7.400742E+01 -1.119290E+02 -2.763857E+01 -6.865280E+01 + 3.399999E+00 3.000000E+01 2 5.104679E+01 -1.168010E+02 -2.301664E+01 -4.556325E+01 + 3.399999E+00 3.000000E+01 3 1.701708E-01 1.513890E+02 -1.493914E-01 8.148818E-02 + 3.399999E+00 3.000000E+01 4 1.543932E+02 -1.191935E+02 -7.530685E+01 -1.347819E+02 + 3.399999E+00 3.000000E+01 5 1.754636E+02 5.171851E+01 1.087042E+02 1.377348E+02 + 3.399999E+00 3.000000E+01 6 1.745534E+02 -3.068357E+01 1.501157E+02 -8.907393E+01 + 3.399999E+00 6.000000E+01 1 5.649395E+01 -9.294634E+01 -2.903829E+00 -5.641927E+01 + 3.399999E+00 6.000000E+01 2 4.890638E+01 -9.335667E+01 -2.863540E+00 -4.882248E+01 + 3.399999E+00 6.000000E+01 3 1.974456E+00 1.499715E+02 -1.709438E+00 9.880779E-01 + 3.399999E+00 6.000000E+01 4 1.835228E+02 -9.412207E+01 -1.319192E+01 -1.830480E+02 + 3.399999E+00 6.000000E+01 5 2.654980E+02 9.541576E+01 -2.505829E+01 2.643128E+02 + 3.399999E+00 6.000000E+01 6 1.884565E+03 1.682920E+02 -1.845355E+03 3.824237E+02 + 3.399999E+00 9.000000E+01 1 1.524115E-05 -9.668856E+01 -1.775174E-06 -1.513742E-05 + 3.399999E+00 9.000000E+01 2 4.834594E+01 7.256494E+01 1.448564E+01 4.612479E+01 + 3.399999E+00 9.000000E+01 3 6.366030E+00 1.568401E+02 -5.852995E+00 2.503754E+00 + 3.399999E+00 9.000000E+01 4 1.239776E+02 6.965963E+01 4.309418E+01 1.162469E+02 + 3.399999E+00 9.000000E+01 5 2.766623E-05 2.271446E+01 2.552046E-05 1.068301E-05 + 3.399999E+00 9.000000E+01 6 1.139374E-03 1.668813E+02 -1.109638E-03 2.586038E-04 + 3.499999E+00 0.000000E+00 1 8.050917E+00 1.672397E+02 -7.852081E+00 1.778225E+00 + 3.499999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.499999E+00 0.000000E+00 3 5.365941E+00 1.646354E+02 -5.174159E+00 1.421762E+00 + 3.499999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.499999E+00 0.000000E+00 5 2.002238E+01 1.748561E+02 -1.994174E+01 1.795141E+00 + 3.499999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.499999E+00 3.000000E+01 1 3.266153E+01 -1.400336E+02 -2.503250E+01 -2.097973E+01 + 3.499999E+00 3.000000E+01 2 3.473077E+01 -1.264799E+02 -2.064885E+01 -2.792581E+01 + 3.499999E+00 3.000000E+01 3 1.774829E+00 8.915792E+01 2.608388E-02 1.774637E+00 + 3.499999E+00 3.000000E+01 4 1.095299E+02 -1.286510E+02 -6.840970E+01 -8.553900E+01 + 3.499999E+00 3.000000E+01 5 1.383809E+02 -1.414545E+00 1.383387E+02 -3.416065E+00 + 3.499999E+00 3.000000E+01 6 4.447607E+02 -3.494680E+01 3.645633E+02 -2.547658E+02 + 3.499999E+00 6.000000E+01 1 7.875937E+01 -8.723781E+01 3.795474E+00 -7.866786E+01 + 3.499999E+00 6.000000E+01 2 7.877679E+01 -1.023097E+02 -1.679493E+01 -7.696567E+01 + 3.499999E+00 6.000000E+01 3 2.027775E+00 3.002265E+01 1.755703E+00 1.014581E+00 + 3.499999E+00 6.000000E+01 4 2.833362E+02 -1.022665E+02 -6.019749E+01 -2.768676E+02 + 3.499999E+00 6.000000E+01 5 3.520478E+02 9.965697E+01 -5.905570E+01 3.470592E+02 + 3.499999E+00 6.000000E+01 6 2.114968E+03 1.639057E+02 -2.032075E+03 5.863102E+02 + 3.499999E+00 9.000000E+01 1 1.697149E-05 -7.374596E+01 4.750265E-06 -1.629314E-05 + 3.499999E+00 9.000000E+01 2 3.708871E+01 6.821251E+01 1.376604E+01 3.443935E+01 + 3.499999E+00 9.000000E+01 3 6.407467E+00 1.718145E+02 -6.342189E+00 9.122886E-01 + 3.499999E+00 9.000000E+01 4 9.978592E+01 6.746081E+01 3.824947E+01 9.216402E+01 + 3.499999E+00 9.000000E+01 5 2.805061E-05 1.040976E+01 2.758892E-05 5.068373E-06 + 3.499999E+00 9.000000E+01 6 1.127239E-03 1.654328E+02 -1.091002E-03 2.835178E-04 + 3.599999E+00 0.000000E+00 1 2.577330E+01 9.237114E+01 -1.066301E+00 2.575124E+01 + 3.599999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.599999E+00 0.000000E+00 3 4.057404E+00 1.715391E+02 -4.013245E+00 5.969842E-01 + 3.599999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.599999E+00 0.000000E+00 5 1.168028E+02 -9.787395E+01 -1.600130E+01 -1.157016E+02 + 3.599999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.599999E+00 3.000000E+01 1 3.466184E+01 1.459034E+02 -2.870325E+01 1.943107E+01 + 3.599999E+00 3.000000E+01 2 1.695292E+01 -1.442497E+02 -1.375849E+01 -9.904814E+00 + 3.599999E+00 3.000000E+01 3 3.636840E+00 1.338848E+02 -2.521097E+00 2.621197E+00 + 3.599999E+00 3.000000E+01 4 5.423851E+01 -1.489744E+02 -4.647898E+01 -2.795567E+01 + 3.599999E+00 3.000000E+01 5 2.045745E+02 -3.209956E+01 1.733004E+02 -1.087093E+02 + 3.599999E+00 3.000000E+01 6 4.912776E+02 -3.812108E+01 3.864920E+02 -3.032781E+02 + 3.599999E+00 6.000000E+01 1 8.862406E+01 -8.002473E+01 1.535174E+01 -8.728429E+01 + 3.599999E+00 6.000000E+01 2 1.076934E+02 -1.082558E+02 -3.373612E+01 -1.022729E+02 + 3.599999E+00 6.000000E+01 3 6.449351E+00 2.759315E+01 5.715795E+00 2.987276E+00 + 3.599999E+00 6.000000E+01 4 3.844471E+02 -1.080811E+02 -1.193178E+02 -3.654625E+02 + 3.599999E+00 6.000000E+01 5 3.885133E+02 1.044001E+02 -9.662006E+01 3.763072E+02 + 3.599999E+00 6.000000E+01 6 2.230641E+03 1.606511E+02 -2.104650E+03 7.390564E+02 + 3.599999E+00 9.000000E+01 1 1.746707E-05 -4.613996E+01 1.210292E-05 -1.259436E-05 + 3.599999E+00 9.000000E+01 2 3.031299E+01 7.251962E+01 9.105392E+00 2.891313E+01 + 3.599999E+00 9.000000E+01 3 5.550235E+00 -1.756765E+02 -5.534440E+00 -4.184227E-01 + 3.599999E+00 9.000000E+01 4 8.694468E+01 7.543147E+01 2.186988E+01 8.414919E+01 + 3.599999E+00 9.000000E+01 5 2.958998E-05 1.050274E+01 2.909423E-05 5.393735E-06 + 3.599999E+00 9.000000E+01 6 1.111655E-03 1.640854E+02 -1.069047E-03 3.048207E-04 + 3.699999E+00 0.000000E+00 1 6.448834E+01 8.812731E+01 2.107403E+00 6.445390E+01 + 3.699999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.699999E+00 0.000000E+00 3 4.135828E+00 1.736109E+02 -4.110141E+00 4.602304E-01 + 3.699999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.699999E+00 0.000000E+00 5 2.780600E+02 -8.937009E+01 3.056895E+00 -2.780432E+02 + 3.699999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.699999E+00 3.000000E+01 1 4.616284E+01 1.214222E+02 -2.406658E+01 3.939299E+01 + 3.699999E+00 3.000000E+01 2 6.240627E+00 1.255741E+02 -3.630517E+00 5.075901E+00 + 3.699999E+00 3.000000E+01 3 5.365453E+00 1.765769E+02 -5.355880E+00 3.203621E-01 + 3.699999E+00 3.000000E+01 4 3.015887E+01 1.169264E+02 -1.365729E+01 2.688932E+01 + 3.699999E+00 3.000000E+01 5 2.150159E+02 -4.157241E+01 1.608572E+02 -1.426772E+02 + 3.699999E+00 3.000000E+01 6 2.990040E+02 -4.463598E+01 2.127668E+02 -2.100802E+02 + 3.699999E+00 6.000000E+01 1 8.421621E+01 -7.756512E+01 1.813427E+01 -8.224061E+01 + 3.699999E+00 6.000000E+01 2 1.357168E+02 -1.126557E+02 -5.227703E+01 -1.252444E+02 + 3.699999E+00 6.000000E+01 3 9.447015E+00 4.043707E+01 7.190301E+00 6.127451E+00 + 3.699999E+00 6.000000E+01 4 4.851443E+02 -1.124662E+02 -1.853927E+02 -4.483242E+02 + 3.699999E+00 6.000000E+01 5 3.718708E+02 1.051254E+02 -9.703284E+01 3.589882E+02 + 3.699999E+00 6.000000E+01 6 2.221244E+03 1.585461E+02 -2.067339E+03 8.124263E+02 + 3.699999E+00 9.000000E+01 1 1.675151E-05 -1.914058E+01 1.582543E-05 -5.492601E-06 + 3.699999E+00 9.000000E+01 2 2.606002E+01 9.104572E+01 -4.755977E-01 2.605568E+01 + 3.699999E+00 9.000000E+01 3 4.797679E+00 -1.754465E+02 -4.782536E+00 -3.808895E-01 + 3.699999E+00 9.000000E+01 4 8.483791E+01 9.507306E+01 -7.501873E+00 8.450558E+01 + 3.699999E+00 9.000000E+01 5 2.136629E-05 2.694220E+01 1.904728E-05 9.680883E-06 + 3.699999E+00 9.000000E+01 6 1.095377E-03 1.630527E+02 -1.047808E-03 3.192936E-04 + 3.799999E+00 0.000000E+00 1 9.680605E+01 8.504037E+01 8.369260E+00 9.644360E+01 + 3.799999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.799999E+00 0.000000E+00 3 5.284828E+00 -1.749997E+02 -5.264716E+00 -4.606299E-01 + 3.799999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.799999E+00 0.000000E+00 5 4.108856E+02 -8.898692E+01 7.264781E+00 -4.108213E+02 + 3.799999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.799999E+00 3.000000E+01 1 4.886696E+01 9.373832E+01 -3.186108E+00 4.876299E+01 + 3.799999E+00 3.000000E+01 2 1.746278E+01 5.889301E+01 9.021933E+00 1.495170E+01 + 3.799999E+00 3.000000E+01 3 6.057806E+00 -1.521841E+02 -5.357835E+00 -2.826767E+00 + 3.799999E+00 3.000000E+01 4 7.572858E+01 6.843237E+01 2.783778E+01 7.042639E+01 + 3.799999E+00 3.000000E+01 5 1.618238E+02 -6.106374E+01 7.829624E+01 -1.416215E+02 + 3.799999E+00 3.000000E+01 6 1.136665E+02 1.716626E+02 -1.124651E+02 1.648192E+01 + 3.799999E+00 6.000000E+01 1 7.506390E+01 -8.244417E+01 9.870318E+00 -7.441214E+01 + 3.799999E+00 6.000000E+01 2 1.623081E+02 -1.157113E+02 -7.041512E+01 -1.462383E+02 + 3.799999E+00 6.000000E+01 3 9.810149E+00 4.842605E+01 6.509879E+00 7.338972E+00 + 3.799999E+00 6.000000E+01 4 5.820505E+02 -1.156258E+02 -2.517319E+02 -5.247988E+02 + 3.799999E+00 6.000000E+01 5 3.351341E+02 1.002252E+02 -5.949224E+01 3.298113E+02 + 3.799999E+00 6.000000E+01 6 2.078295E+03 1.573983E+02 -1.918680E+03 7.987352E+02 + 3.799999E+00 9.000000E+01 1 1.561437E-05 5.050616E+00 1.555374E-05 1.374623E-06 + 3.799999E+00 9.000000E+01 2 2.564585E+01 1.215206E+02 -1.340777E+01 2.186187E+01 + 3.799999E+00 9.000000E+01 3 5.158154E+00 -1.783746E+02 -5.156078E+00 -1.463055E-01 + 3.799999E+00 9.000000E+01 4 9.451308E+01 1.181360E+02 -4.456914E+01 8.334455E+01 + 3.799999E+00 9.000000E+01 5 5.694140E-06 -1.429422E+02 -4.544086E-06 -3.431402E-06 + 3.799999E+00 9.000000E+01 6 1.075892E-03 1.624064E+02 -1.025566E-03 3.252031E-04 + 3.899998E+00 0.000000E+00 1 1.199427E+02 7.651603E+01 2.796745E+01 1.166365E+02 + 3.899998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.899998E+00 0.000000E+00 3 6.305821E+00 -1.622106E+02 -6.004313E+00 -1.926551E+00 + 3.899998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.899998E+00 0.000000E+00 5 4.949913E+02 -9.490263E+01 -4.230329E+01 -4.931804E+02 + 3.899998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.899998E+00 3.000000E+01 1 6.339765E+01 6.585059E+01 2.593709E+01 5.784919E+01 + 3.899998E+00 3.000000E+01 2 3.166013E+01 3.966199E+01 2.437271E+01 2.020731E+01 + 3.899998E+00 3.000000E+01 3 5.663646E+00 -1.308824E+02 -3.706906E+00 -4.282024E+00 + 3.899998E+00 3.000000E+01 4 1.285910E+02 5.258181E+01 7.813549E+01 1.021298E+02 + 3.899998E+00 3.000000E+01 5 1.490516E+02 -1.063731E+02 -4.201637E+01 -1.430070E+02 + 3.899998E+00 3.000000E+01 6 6.498409E+02 1.471119E+02 -5.456924E+02 3.528640E+02 + 3.899998E+00 6.000000E+01 1 6.852900E+01 -9.329747E+01 -3.941782E+00 -6.841554E+01 + 3.899998E+00 6.000000E+01 2 1.866383E+02 -1.175325E+02 -8.627378E+01 -1.655013E+02 + 3.899998E+00 6.000000E+01 3 8.832902E+00 4.766920E+01 5.948164E+00 6.529892E+00 + 3.899998E+00 6.000000E+01 4 6.714777E+02 -1.176640E+02 -3.117577E+02 -5.947179E+02 + 3.899998E+00 6.000000E+01 5 3.008390E+02 9.106235E+01 -5.577679E+00 3.007873E+02 + 3.899998E+00 6.000000E+01 6 1.807456E+03 1.565780E+02 -1.658525E+03 7.184641E+02 + 3.899998E+00 9.000000E+01 1 1.434072E-05 2.640816E+01 1.284425E-05 6.378219E-06 + 3.899998E+00 9.000000E+01 2 2.865577E+01 1.522909E+02 -2.536953E+01 1.332442E+01 + 3.899998E+00 9.000000E+01 3 5.945359E+00 -1.762351E+02 -5.932528E+00 -3.903839E-01 + 3.899998E+00 9.000000E+01 4 1.056488E+02 1.360561E+02 -7.606926E+01 7.331535E+01 + 3.899998E+00 9.000000E+01 5 3.824207E-05 -1.125429E+02 -1.466106E-05 -3.532010E-05 + 3.899998E+00 9.000000E+01 6 1.051411E-03 1.620507E+02 -1.000238E-03 3.240192E-04 + 3.999998E+00 0.000000E+00 1 1.436809E+02 6.415221E+01 6.264229E+01 1.293064E+02 + 3.999998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.999998E+00 0.000000E+00 3 6.736756E+00 -1.539550E+02 -6.052634E+00 -2.957956E+00 + 3.999998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.999998E+00 0.000000E+00 5 5.601800E+02 -1.058728E+02 -1.532105E+02 -5.388211E+02 + 3.999998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.999998E+00 3.000000E+01 1 8.682338E+01 5.205758E+01 5.338503E+01 6.847144E+01 + 3.999998E+00 3.000000E+01 2 4.819812E+01 2.988014E+01 4.179112E+01 2.401169E+01 + 3.999998E+00 3.000000E+01 3 4.733355E+00 -1.156061E+02 -2.045673E+00 -4.268475E+00 + 3.999998E+00 3.000000E+01 4 1.867685E+02 4.412656E+01 1.340631E+02 1.300368E+02 + 3.999998E+00 3.000000E+01 5 2.228042E+02 -1.358351E+02 -1.598257E+02 -1.552336E+02 + 3.999998E+00 3.000000E+01 6 1.290208E+03 1.445139E+02 -1.050561E+03 7.489717E+02 + 3.999998E+00 6.000000E+01 1 6.732007E+01 -1.073700E+02 -2.009781E+01 -6.425006E+01 + 3.999998E+00 6.000000E+01 2 2.078974E+02 -1.181541E+02 -9.809530E+01 -1.832993E+02 + 3.999998E+00 6.000000E+01 3 7.912072E+00 3.934391E+01 6.118838E+00 5.016046E+00 + 3.999998E+00 6.000000E+01 4 7.497960E+02 -1.185743E+02 -3.586257E+02 -6.584692E+02 + 3.999998E+00 6.000000E+01 5 2.748507E+02 7.875133E+01 5.361447E+01 2.695708E+02 + 3.999998E+00 6.000000E+01 6 1.442472E+03 1.549349E+02 -1.306630E+03 6.110990E+02 + 3.999998E+00 9.000000E+01 1 1.314687E-05 4.594492E+01 9.141666E-06 9.448280E-06 + 3.999998E+00 9.000000E+01 2 3.048443E+01 1.780125E+02 -3.046609E+01 1.057267E+00 + 3.999998E+00 9.000000E+01 3 6.787580E+00 -1.731823E+02 -6.739584E+00 -8.057644E-01 + 3.999998E+00 9.000000E+01 4 1.024031E+02 1.458316E+02 -8.472736E+01 5.751231E+01 + 3.999998E+00 9.000000E+01 5 6.856214E-05 -9.788301E+01 -9.403356E-06 -6.791424E-05 + 3.999998E+00 9.000000E+01 6 1.022519E-03 1.618751E+02 -9.717822E-04 3.180952E-04 + 4.099998E+00 0.000000E+00 1 1.769769E+02 5.216186E+01 1.085635E+02 1.397670E+02 + 4.099998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.099998E+00 0.000000E+00 3 6.656598E+00 -1.504145E+02 -5.788711E+00 -3.286505E+00 + 4.099998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.099998E+00 0.000000E+00 5 6.470839E+02 -1.186960E+02 -3.107056E+02 -5.676087E+02 + 4.099998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.099998E+00 3.000000E+01 1 1.083780E+02 4.710453E+01 7.376889E+01 7.939737E+01 + 4.099998E+00 3.000000E+01 2 6.552439E+01 2.731570E+01 5.821786E+01 3.006869E+01 + 4.099998E+00 3.000000E+01 3 3.793626E+00 -1.018131E+02 -7.766338E-01 -3.713279E+00 + 4.099998E+00 3.000000E+01 4 2.468741E+02 4.157050E+01 1.846964E+02 1.638111E+02 + 4.099998E+00 3.000000E+01 5 3.059917E+02 -1.451601E+02 -2.511432E+02 -1.748085E+02 + 4.099998E+00 3.000000E+01 6 1.953405E+03 1.440962E+02 -1.582263E+03 1.145528E+03 + 4.099998E+00 6.000000E+01 1 7.278704E+01 -1.211571E+02 -3.765905E+01 -6.228763E+01 + 4.099998E+00 6.000000E+01 2 2.250607E+02 -1.174773E+02 -1.038424E+02 -1.996724E+02 + 4.099998E+00 6.000000E+01 3 7.562171E+00 2.844657E+01 6.649127E+00 3.602157E+00 + 4.099998E+00 6.000000E+01 4 8.121299E+02 -1.182283E+02 -3.841263E+02 -7.155431E+02 + 4.099998E+00 6.000000E+01 5 2.641593E+02 6.395090E+01 1.160033E+02 2.373255E+02 + 4.099998E+00 6.000000E+01 6 1.038762E+03 1.507644E+02 -9.064431E+02 5.073342E+02 + 4.099998E+00 9.000000E+01 1 1.218451E-05 6.544556E+01 5.063365E-06 1.108262E-05 + 4.099998E+00 9.000000E+01 2 2.692613E+01 -1.580917E+02 -2.498158E+01 -1.004675E+01 + 4.099998E+00 9.000000E+01 3 7.728706E+00 -1.708995E+02 -7.631421E+00 -1.222420E+00 + 4.099998E+00 9.000000E+01 4 7.902838E+01 1.398593E+02 -6.041432E+01 5.094698E+01 + 4.099998E+00 9.000000E+01 5 9.701904E-05 -8.663662E+01 5.691952E-06 -9.685192E-05 + 4.099998E+00 9.000000E+01 6 9.907717E-04 1.618420E+02 -9.414321E-04 3.087624E-04 + 4.199998E+00 0.000000E+00 1 2.222129E+02 4.372376E+01 1.605889E+02 1.535896E+02 + 4.199998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.199998E+00 0.000000E+00 3 6.272953E+00 -1.497196E+02 -5.417120E+00 -3.163029E+00 + 4.199998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.199998E+00 0.000000E+00 5 7.777079E+02 -1.293957E+02 -4.935896E+02 -6.009982E+02 + 4.199998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.199998E+00 3.000000E+01 1 1.235069E+02 4.672363E+01 8.466619E+01 8.991985E+01 + 4.199998E+00 3.000000E+01 2 7.948988E+01 2.993484E+01 6.888541E+01 3.966662E+01 + 4.199998E+00 3.000000E+01 3 3.152623E+00 -8.481982E+01 2.846442E-01 -3.139747E+00 + 4.199998E+00 3.000000E+01 4 2.969751E+02 4.384402E+01 2.141868E+02 2.057139E+02 + 4.199998E+00 3.000000E+01 5 3.638582E+02 -1.468557E+02 -3.046570E+02 -1.989394E+02 + 4.199998E+00 3.000000E+01 6 2.577388E+03 1.443839E+02 -2.095253E+03 1.500947E+03 + 4.199998E+00 6.000000E+01 1 8.496262E+01 -1.310437E+02 -5.578941E+01 -6.407954E+01 + 4.199998E+00 6.000000E+01 2 2.361464E+02 -1.153644E+02 -1.011588E+02 -2.133824E+02 + 4.199998E+00 6.000000E+01 3 7.540276E+00 1.941462E+01 7.111519E+00 2.506401E+00 + 4.199998E+00 6.000000E+01 4 8.499861E+02 -1.165007E+02 -3.792712E+02 -7.606771E+02 + 4.199998E+00 6.000000E+01 5 2.771346E+02 4.957950E+01 1.796919E+02 2.109843E+02 + 4.199998E+00 6.000000E+01 6 6.496003E+02 1.407102E+02 -5.027601E+02 4.113549E+02 + 4.199998E+00 9.000000E+01 1 1.162693E-05 8.708602E+01 5.910740E-07 1.161190E-05 + 4.199998E+00 9.000000E+01 2 1.717420E+01 -1.257395E+02 -1.003147E+01 -1.393998E+01 + 4.199998E+00 9.000000E+01 3 8.776693E+00 -1.691979E+02 -8.621174E+00 -1.644905E+00 + 4.199998E+00 9.000000E+01 4 7.172317E+01 9.604378E+01 -7.551608E+00 7.132451E+01 + 4.199998E+00 9.000000E+01 5 1.239009E-04 -7.636890E+01 2.919967E-05 -1.204110E-04 + 4.199998E+00 9.000000E+01 6 9.571696E-04 1.619692E+02 -9.101634E-04 2.962704E-04 + 4.299998E+00 0.000000E+00 1 2.769825E+02 4.001219E+01 2.121430E+02 1.780860E+02 + 4.299998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.299998E+00 0.000000E+00 3 5.694993E+00 -1.497345E+02 -4.918758E+00 -2.870323E+00 + 4.299998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.299998E+00 0.000000E+00 5 9.487909E+02 -1.354382E+02 -6.760075E+02 -6.657462E+02 + 4.299998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.299998E+00 3.000000E+01 1 1.304576E+02 4.986138E+01 8.409808E+01 9.973315E+01 + 4.299998E+00 3.000000E+01 2 8.628721E+01 3.583747E+01 6.995141E+01 5.052013E+01 + 4.299998E+00 3.000000E+01 3 2.998477E+00 -6.388546E+01 1.319831E+00 -2.692380E+00 + 4.299998E+00 3.000000E+01 4 3.243755E+02 4.959517E+01 2.102551E+02 2.470067E+02 + 4.299998E+00 3.000000E+01 5 3.863448E+02 -1.441945E+02 -3.133285E+02 -2.260256E+02 + 4.299998E+00 3.000000E+01 6 3.126312E+03 1.450128E+02 -2.561323E+03 1.792609E+03 + 4.299998E+00 6.000000E+01 1 1.021343E+02 -1.351964E+02 -7.246703E+01 -7.197182E+01 + 4.299998E+00 6.000000E+01 2 2.381832E+02 -1.119180E+02 -8.890878E+01 -2.209671E+02 + 4.299998E+00 6.000000E+01 3 7.493745E+00 1.328287E+01 7.293269E+00 1.721753E+00 + 4.299998E+00 6.000000E+01 4 8.518859E+02 -1.135350E+02 -3.401663E+02 -7.810228E+02 + 4.299998E+00 6.000000E+01 5 3.114526E+02 4.011540E+01 2.381828E+02 2.006780E+02 + 4.299998E+00 6.000000E+01 6 3.336525E+02 1.111197E+02 -1.202209E+02 3.112410E+02 + 4.299998E+00 9.000000E+01 1 1.169914E-05 1.126883E+02 -4.512574E-06 1.079382E-05 + 4.299998E+00 9.000000E+01 2 1.171045E+01 -3.668459E+01 9.391036E+00 -6.995934E+00 + 4.299998E+00 9.000000E+01 3 9.869135E+00 -1.678559E+02 -9.648279E+00 -2.076180E+00 + 4.299998E+00 9.000000E+01 4 1.410076E+02 6.587157E+01 5.764157E+01 1.286880E+02 + 4.299998E+00 9.000000E+01 5 1.475130E-04 -6.556328E+01 6.102437E-05 -1.342986E-04 + 4.299998E+00 9.000000E+01 6 9.218401E-04 1.622708E+02 -8.780588E-04 2.807167E-04 + 4.399998E+00 0.000000E+00 1 3.343017E+02 4.143633E+01 2.506232E+02 2.212366E+02 + 4.399998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.399998E+00 0.000000E+00 3 4.950696E+00 -1.486069E+02 -4.225980E+00 -2.578854E+00 + 4.399998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.399998E+00 0.000000E+00 5 1.134238E+03 -1.358509E+02 -8.138492E+02 -7.900288E+02 + 4.399998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.399998E+00 3.000000E+01 1 1.271773E+02 5.689435E+01 6.946230E+01 1.065320E+02 + 4.399998E+00 3.000000E+01 2 8.429147E+01 4.361216E+01 6.102916E+01 5.814200E+01 + 4.399998E+00 3.000000E+01 3 3.361035E+00 -4.464866E+01 2.391139E+00 -2.361993E+00 + 4.399998E+00 3.000000E+01 4 3.224410E+02 5.764745E+01 1.725470E+02 2.723889E+02 + 4.399998E+00 3.000000E+01 5 3.667534E+02 -1.374053E+02 -2.699893E+02 -2.482214E+02 + 4.399998E+00 3.000000E+01 6 3.582413E+03 1.460116E+02 -2.970361E+03 2.002658E+03 + 4.399998E+00 6.000000E+01 1 1.208290E+02 -1.332758E+02 -8.282953E+01 -8.797112E+01 + 4.399998E+00 6.000000E+01 2 2.289413E+02 -1.076797E+02 -6.952862E+01 -2.181281E+02 + 4.399998E+00 6.000000E+01 3 7.232306E+00 9.682171E+00 7.129288E+00 1.216348E+00 + 4.399998E+00 6.000000E+01 4 8.101049E+02 -1.099217E+02 -2.760321E+02 -7.616274E+02 + 4.399998E+00 6.000000E+01 5 3.493807E+02 3.800619E+01 2.752925E+02 2.151300E+02 + 4.399998E+00 6.000000E+01 6 3.082111E+02 3.977768E+01 2.368704E+02 1.971967E+02 + 4.399998E+00 9.000000E+01 1 9.736978E-06 -1.223660E+02 -5.212446E-06 -8.224301E-06 + 4.399998E+00 9.000000E+01 2 2.901769E+01 2.097297E+01 2.709525E+01 1.038623E+01 + 4.399998E+00 9.000000E+01 3 1.092908E+01 -1.668187E+02 -1.064114E+01 -2.492191E+00 + 4.399998E+00 9.000000E+01 4 2.484756E+02 6.239579E+01 1.151340E+02 2.201915E+02 + 4.399998E+00 9.000000E+01 5 1.173416E-04 -7.779848E+01 2.480024E-05 -1.146909E-04 + 4.399998E+00 9.000000E+01 6 8.845504E-04 1.627181E+02 -8.446172E-04 2.627760E-04 + 4.499998E+00 0.000000E+00 1 3.779098E+02 4.799015E+01 2.529193E+02 2.807982E+02 + 4.499998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.499998E+00 0.000000E+00 3 4.052723E+00 -1.444656E+02 -3.297972E+00 -2.355407E+00 + 4.499998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.499998E+00 0.000000E+00 5 1.275649E+03 -1.306416E+02 -8.308618E+02 -9.679617E+02 + 4.499998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.499998E+00 3.000000E+01 1 1.105494E+02 6.842512E+01 4.065087E+01 1.028040E+02 + 4.499998E+00 3.000000E+01 2 7.465453E+01 5.225248E+01 4.570224E+01 5.903053E+01 + 4.499998E+00 3.000000E+01 3 4.060913E+00 -3.087147E+01 3.485565E+00 -2.083710E+00 + 4.499998E+00 3.000000E+01 4 2.938735E+02 6.712950E+01 1.142138E+02 2.707708E+02 + 4.499998E+00 3.000000E+01 5 2.988004E+02 -1.262189E+02 -1.765529E+02 -2.410618E+02 + 4.499998E+00 3.000000E+01 6 3.932096E+03 1.475261E+02 -3.317257E+03 2.111204E+03 + 4.499998E+00 6.000000E+01 1 1.344396E+02 -1.256581E+02 -7.837117E+01 -1.092335E+02 + 4.499998E+00 6.000000E+01 2 2.091497E+02 -1.035040E+02 -4.883919E+01 -2.033674E+02 + 4.499998E+00 6.000000E+01 3 6.686349E+00 8.363100E+00 6.615248E+00 9.725019E-01 + 4.499998E+00 6.000000E+01 4 7.285418E+02 -1.065712E+02 -2.077849E+02 -6.982826E+02 + 4.499998E+00 6.000000E+01 5 3.606620E+02 4.315837E+01 2.630906E+02 2.466990E+02 + 4.499998E+00 6.000000E+01 6 5.779142E+02 6.874489E+00 5.737595E+02 6.917333E+01 + 4.499998E+00 9.000000E+01 1 1.015033E-05 -1.126452E+02 -3.908118E-06 -9.367806E-06 + 4.499998E+00 9.000000E+01 2 5.162467E+01 4.145635E+01 3.869064E+01 3.417807E+01 + 4.499998E+00 9.000000E+01 3 1.188245E+01 -1.660739E+02 -1.153318E+01 -2.859762E+00 + 4.499998E+00 9.000000E+01 4 3.639225E+02 6.548040E+01 1.510294E+02 3.311037E+02 + 4.499998E+00 9.000000E+01 5 1.262468E-04 -7.941154E+01 2.319828E-05 -1.240971E-04 + 4.499998E+00 9.000000E+01 6 8.453398E-04 1.632377E+02 -8.094208E-04 2.437979E-04 + 4.599998E+00 0.000000E+00 1 3.841077E+02 5.818426E+01 2.024975E+02 3.263947E+02 + 4.599998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.599998E+00 0.000000E+00 3 3.049386E+00 -1.344309E+02 -2.134718E+00 -2.177552E+00 + 4.599998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.599998E+00 0.000000E+00 5 1.292093E+03 -1.214620E+02 -6.743853E+02 -1.102138E+03 + 4.599998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.599998E+00 3.000000E+01 1 8.041452E+01 8.405013E+01 8.335629E+00 7.998132E+01 + 4.599998E+00 3.000000E+01 2 6.048987E+01 6.132509E+01 2.902542E+01 5.307118E+01 + 4.599998E+00 3.000000E+01 3 4.875956E+00 -2.113382E+01 4.548004E+00 -1.758014E+00 + 4.599998E+00 3.000000E+01 4 2.488913E+02 7.771290E+01 5.296669E+01 2.431901E+02 + 4.599998E+00 3.000000E+01 5 1.903443E+02 -1.115959E+02 -7.005787E+01 -1.769826E+02 + 4.599998E+00 3.000000E+01 6 4.159670E+03 1.496618E+02 -3.590040E+03 2.101063E+03 + 4.599998E+00 6.000000E+01 1 1.341561E+02 -1.141581E+02 -5.490426E+01 -1.224067E+02 + 4.599998E+00 6.000000E+01 2 1.825358E+02 -1.001821E+02 -3.226822E+01 -1.796610E+02 + 4.599998E+00 6.000000E+01 3 5.846311E+00 9.632482E+00 5.763885E+00 9.782497E-01 + 4.599998E+00 6.000000E+01 4 6.221777E+02 -1.043536E+02 -1.542407E+02 -6.027560E+02 + 4.599998E+00 6.000000E+01 5 3.155230E+02 5.339978E+01 1.881236E+02 2.533066E+02 + 4.599998E+00 6.000000E+01 6 8.984623E+02 -4.113700E+00 8.961475E+02 -6.445203E+01 + 4.599998E+00 9.000000E+01 1 1.011548E-05 -1.062156E+02 -2.824781E-06 -9.713065E-06 + 4.599998E+00 9.000000E+01 2 7.347574E+01 5.378092E+01 4.341493E+01 5.927755E+01 + 4.599998E+00 9.000000E+01 3 1.265103E+01 -1.656356E+02 -1.225552E+01 -3.138562E+00 + 4.599998E+00 9.000000E+01 4 4.728514E+02 6.973167E+01 1.638038E+02 4.435728E+02 + 4.599998E+00 9.000000E+01 5 1.366691E-04 -8.105184E+01 2.125763E-05 -1.350058E-04 + 4.599998E+00 9.000000E+01 6 8.048025E-04 1.637364E+02 -7.725970E-04 2.253906E-04 + 4.699998E+00 0.000000E+00 1 3.460417E+02 6.870765E+01 1.256570E+02 3.224208E+02 + 4.699998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.699998E+00 0.000000E+00 3 2.093747E+00 -1.122938E+02 -7.942743E-01 -1.937241E+00 + 4.699998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.699998E+00 0.000000E+00 5 1.162250E+03 -1.118040E+02 -4.316968E+02 -1.079103E+03 + 4.699998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.699998E+00 3.000000E+01 1 4.541433E+01 1.033159E+02 -1.045981E+01 4.419337E+01 + 4.699998E+00 3.000000E+01 2 4.515564E+01 7.131896E+01 1.446332E+01 4.277667E+01 + 4.699998E+00 3.000000E+01 3 5.617669E+00 -1.294745E+01 5.474845E+00 -1.258679E+00 + 4.699998E+00 3.000000E+01 4 1.996091E+02 8.985918E+01 4.906016E-01 1.996085E+02 + 4.699998E+00 3.000000E+01 5 7.648222E+01 -9.556819E+01 -7.421094E+00 -7.612133E+01 + 4.699998E+00 3.000000E+01 6 4.250005E+03 1.524145E+02 -3.766867E+03 1.968059E+03 + 4.699998E+00 6.000000E+01 1 1.177873E+02 -1.023044E+02 -2.510108E+01 -1.150816E+02 + 4.699998E+00 6.000000E+01 2 1.535583E+02 -9.816393E+01 -2.180615E+01 -1.520021E+02 + 4.699998E+00 6.000000E+01 3 4.744053E+00 1.478502E+01 4.586978E+00 1.210649E+00 + 4.699998E+00 6.000000E+01 4 5.082306E+02 -1.038524E+02 -1.216815E+02 -4.934490E+02 + 4.699998E+00 6.000000E+01 5 2.164927E+02 6.491900E+01 9.177108E+01 1.960795E+02 + 4.699998E+00 6.000000E+01 6 1.220451E+03 -9.020590E+00 1.205357E+03 -1.913538E+02 + 4.699998E+00 9.000000E+01 1 9.939735E-06 -1.026334E+02 -2.173937E-06 -9.699089E-06 + 4.699998E+00 9.000000E+01 2 9.290768E+01 6.229543E+01 4.319396E+01 8.225642E+01 + 4.699998E+00 9.000000E+01 3 1.314444E+01 -1.656420E+02 -1.273388E+01 -3.259555E+00 + 4.699998E+00 9.000000E+01 4 5.692185E+02 7.359039E+01 1.608055E+02 5.460323E+02 + 4.699998E+00 9.000000E+01 5 1.475656E-04 -8.213509E+01 2.019256E-05 -1.461775E-04 + 4.699998E+00 9.000000E+01 6 7.639885E-04 1.641319E+02 -7.348755E-04 2.088932E-04 + 4.799998E+00 0.000000E+00 1 2.851581E+02 7.683483E+01 6.494731E+01 2.776635E+02 + 4.799998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.799998E+00 0.000000E+00 3 1.573121E+00 -6.936901E+01 5.542859E-01 -1.472236E+00 + 4.799998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.799998E+00 0.000000E+00 5 9.603394E+02 -1.045776E+02 -2.417084E+02 -9.294238E+02 + 4.799998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.799998E+00 3.000000E+01 1 1.800440E+01 1.379652E+02 -1.337255E+01 1.205543E+01 + 4.799998E+00 3.000000E+01 2 3.116061E+01 8.419940E+01 3.149298E+00 3.100105E+01 + 4.799998E+00 3.000000E+01 3 6.096856E+00 -4.478701E+00 6.078238E+00 -4.760943E-01 + 4.799998E+00 3.000000E+01 4 1.558646E+02 1.047826E+02 -3.976906E+01 1.507056E+02 + 4.799998E+00 3.000000E+01 5 8.520231E+00 7.131519E+01 2.729558E+00 8.071175E+00 + 4.799998E+00 3.000000E+01 6 4.196128E+03 1.556629E+02 -3.823245E+03 1.729244E+03 + 4.799998E+00 6.000000E+01 1 9.337648E+01 -9.295598E+01 -4.815296E+00 -9.325224E+01 + 4.799998E+00 6.000000E+01 2 1.254169E+02 -9.756944E+01 -1.652089E+01 -1.243240E+02 + 4.799998E+00 6.000000E+01 3 3.493744E+00 2.757178E+01 3.096965E+00 1.617113E+00 + 4.799998E+00 6.000000E+01 4 3.988786E+02 -1.054398E+02 -1.061915E+02 -3.844834E+02 + 4.799998E+00 6.000000E+01 5 9.889384E+01 7.518446E+01 2.528795E+01 9.560602E+01 + 4.799998E+00 6.000000E+01 6 1.526965E+03 -1.134167E+01 1.497147E+03 -3.002918E+02 + 4.799998E+00 9.000000E+01 1 9.805247E-06 -1.010645E+02 -1.881760E-06 -9.622985E-06 + 4.799998E+00 9.000000E+01 2 1.096895E+02 6.836515E+01 4.044143E+01 1.019621E+02 + 4.799998E+00 9.000000E+01 3 1.328537E+01 -1.665575E+02 -1.292139E+01 -3.088449E+00 + 4.799998E+00 9.000000E+01 4 6.525575E+02 7.666199E+01 1.505419E+02 6.349554E+02 + 4.799998E+00 9.000000E+01 5 1.578573E-04 -8.271859E+01 2.000726E-05 -1.565842E-04 + 4.799998E+00 9.000000E+01 6 7.240947E-04 1.643738E+02 -6.973319E-04 1.950419E-04 + 4.899998E+00 0.000000E+00 1 2.242526E+02 8.205466E+01 3.099806E+01 2.220998E+02 + 4.899998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.899998E+00 0.000000E+00 3 1.730230E+00 -2.364791E+01 1.584938E+00 -6.940214E-01 + 4.899998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.899998E+00 0.000000E+00 5 7.637006E+02 -1.005024E+02 -1.392053E+02 -7.509065E+02 + 4.899998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.899998E+00 3.000000E+01 1 1.331560E+01 -1.353097E+02 -9.466311E+00 -9.364521E+00 + 4.899998E+00 3.000000E+01 2 2.033665E+01 1.046555E+02 -5.145310E+00 1.967499E+01 + 4.899998E+00 3.000000E+01 3 6.114715E+00 5.298188E+00 6.088590E+00 5.646272E-01 + 4.899998E+00 3.000000E+01 4 1.244294E+02 1.236556E+02 -6.895877E+01 1.035730E+02 + 4.899998E+00 3.000000E+01 5 5.477603E+01 1.016458E+02 -1.105713E+01 5.364843E+01 + 4.899998E+00 3.000000E+01 6 4.006181E+03 1.592074E+02 -3.745264E+03 1.422142E+03 + 4.899998E+00 6.000000E+01 1 6.913773E+01 -8.669994E+01 3.979922E+00 -6.902308E+01 + 4.899998E+00 6.000000E+01 2 9.966670E+01 -9.837323E+01 -1.451354E+01 -9.860430E+01 + 4.899998E+00 6.000000E+01 3 2.494493E+00 5.765803E+01 1.334482E+00 2.107523E+00 + 4.899998E+00 6.000000E+01 4 3.002386E+02 -1.096119E+02 -1.007742E+02 -2.828211E+02 + 4.899998E+00 6.000000E+01 5 9.884706E+00 -1.214070E+02 -5.151062E+00 -8.436466E+00 + 4.899998E+00 6.000000E+01 6 1.805199E+03 -1.231811E+01 1.763640E+03 -3.851199E+02 + 4.899998E+00 9.000000E+01 1 9.782155E-06 -1.006720E+02 -1.811526E-06 -9.612956E-06 + 4.899998E+00 9.000000E+01 2 1.241622E+02 7.274443E+01 3.683076E+01 1.185738E+02 + 4.899998E+00 9.000000E+01 3 1.312218E+01 -1.693184E+02 -1.289481E+01 -2.432216E+00 + 4.899998E+00 9.000000E+01 4 7.247023E+02 7.897560E+01 1.385827E+02 7.113286E+02 + 4.899998E+00 9.000000E+01 5 1.670554E-04 -8.305560E+01 2.019804E-05 -1.658299E-04 + 4.899998E+00 9.000000E+01 6 6.861564E-04 1.644506E+02 -6.610429E-04 1.839371E-04 + 4.999998E+00 0.000000E+00 1 1.726201E+02 8.508228E+01 1.479787E+01 1.719847E+02 + 4.999998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.999998E+00 0.000000E+00 3 1.957078E+00 6.319008E+00 1.945188E+00 2.154040E-01 + 4.999998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.999998E+00 0.000000E+00 5 6.035105E+02 -9.911384E+01 -9.559399E+01 -5.958915E+02 + 4.999998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.999998E+00 3.000000E+01 1 2.238787E+01 -1.032164E+02 -5.118547E+00 -2.179489E+01 + 4.999998E+00 3.000000E+01 2 1.473204E+01 1.385222E+02 -1.103742E+01 9.757474E+00 + 4.999998E+00 3.000000E+01 3 5.556369E+00 1.667700E+01 5.322656E+00 1.594544E+00 + 4.999998E+00 3.000000E+01 4 1.086218E+02 1.453653E+02 -8.937321E+01 6.173428E+01 + 4.999998E+00 3.000000E+01 5 7.309184E+01 1.132108E+02 -2.880659E+01 6.717587E+01 + 4.999998E+00 3.000000E+01 6 3.704331E+03 1.628360E+02 -3.539354E+03 1.093178E+03 + 4.999998E+00 6.000000E+01 1 4.828257E+01 -8.284464E+01 6.014091E+00 -4.790655E+01 + 4.999998E+00 6.000000E+01 2 7.673846E+01 -1.006174E+02 -1.413899E+01 -7.542466E+01 + 4.999998E+00 6.000000E+01 3 2.660417E+00 1.029868E+02 -5.978680E-01 2.592368E+00 + 4.999998E+00 6.000000E+01 4 2.149162E+02 -1.176101E+02 -9.960352E+01 -1.904419E+02 + 4.999998E+00 6.000000E+01 5 9.926028E+01 -9.857103E+01 -1.479330E+01 -9.815173E+01 + 4.999998E+00 6.000000E+01 6 2.046443E+03 -1.259009E+01 1.997236E+03 -4.460722E+02 + 4.999998E+00 9.000000E+01 1 9.873493E-06 -1.008077E+02 -1.851404E-06 -9.698359E-06 + 4.999998E+00 9.000000E+01 2 1.367568E+02 7.594843E+01 3.320388E+01 1.326647E+02 + 4.999998E+00 9.000000E+01 3 1.298596E+01 -1.747427E+02 -1.293134E+01 -1.189889E+00 + 4.999998E+00 9.000000E+01 4 7.877038E+02 8.068748E+01 1.274659E+02 7.773221E+02 + 4.999998E+00 9.000000E+01 5 1.751611E-04 -8.334624E+01 2.029577E-05 -1.739813E-04 + 4.999998E+00 9.000000E+01 6 6.508722E-04 1.643833E+02 -6.268446E-04 1.752157E-04 + 5.099998E+00 0.000000E+00 1 1.312804E+02 8.677015E+01 7.396552E+00 1.310719E+02 + 5.099998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.099998E+00 0.000000E+00 3 1.801020E+00 2.839039E+01 1.584408E+00 8.563427E-01 + 5.099998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.099998E+00 0.000000E+00 5 4.830936E+02 -9.984545E+01 -8.260476E+01 -4.759789E+02 + 5.099998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.099998E+00 3.000000E+01 1 2.846573E+01 -9.460564E+01 -2.285713E+00 -2.837381E+01 + 5.099998E+00 3.000000E+01 2 1.517342E+01 1.739700E+02 -1.508947E+01 1.593953E+00 + 5.099998E+00 3.000000E+01 3 4.530262E+00 2.998076E+01 3.924082E+00 2.263813E+00 + 5.099998E+00 3.000000E+01 4 1.063378E+02 1.655567E+02 -1.029770E+02 2.652286E+01 + 5.099998E+00 3.000000E+01 5 7.443301E+01 1.267481E+02 -4.453309E+01 5.964124E+01 + 5.099998E+00 3.000000E+01 6 3.324823E+03 1.663876E+02 -3.231429E+03 7.825051E+02 + 5.099998E+00 6.000000E+01 1 3.106172E+01 -8.046489E+01 5.145436E+00 -3.063258E+01 + 5.099998E+00 6.000000E+01 2 5.653857E+01 -1.046741E+02 -1.432239E+01 -5.469442E+01 + 5.099998E+00 6.000000E+01 3 3.987724E+00 1.300531E+02 -2.566091E+00 3.052396E+00 + 5.099998E+00 6.000000E+01 4 1.457803E+02 -1.327872E+02 -9.902529E+01 -1.069855E+02 + 5.099998E+00 6.000000E+01 5 1.720107E+02 -9.528493E+01 -1.584369E+01 -1.712795E+02 + 5.099998E+00 6.000000E+01 6 2.247497E+03 -1.253841E+01 2.193896E+03 -4.879184E+02 + 5.099998E+00 9.000000E+01 1 1.005404E-05 -1.010651E+02 -1.929613E-06 -9.867133E-06 + 5.099998E+00 9.000000E+01 2 1.478123E+02 7.833849E+01 2.987723E+01 1.447613E+02 + 5.099998E+00 9.000000E+01 3 1.335400E+01 1.780605E+02 -1.334635E+01 4.519591E-01 + 5.099998E+00 9.000000E+01 4 8.430808E+02 8.196151E+01 1.178951E+02 8.347970E+02 + 5.099998E+00 9.000000E+01 5 1.824164E-04 -8.369120E+01 2.004519E-05 -1.813117E-04 + 5.099998E+00 9.000000E+01 6 6.185627E-04 1.642137E+02 -5.952326E-04 1.682797E-04 + 5.199997E+00 0.000000E+00 1 9.872353E+01 8.776910E+01 3.842977E+00 9.864870E+01 + 5.199997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.199997E+00 0.000000E+00 3 1.284143E+00 5.091521E+01 8.096135E-01 9.967697E-01 + 5.199997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.199997E+00 0.000000E+00 5 3.974545E+02 -1.023061E+02 -8.471117E+01 -3.883222E+02 + 5.199997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.199997E+00 3.000000E+01 1 3.130427E+01 -9.179281E+01 -9.793614E-01 -3.128895E+01 + 5.199997E+00 3.000000E+01 2 1.834637E+01 -1.649215E+02 -1.771471E+01 -4.772676E+00 + 5.199997E+00 3.000000E+01 3 3.355320E+00 4.752442E+01 2.265767E+00 2.474767E+00 + 5.199997E+00 3.000000E+01 4 1.111701E+02 -1.790739E+02 -1.111556E+02 -1.796929E+00 + 5.199997E+00 3.000000E+01 5 6.993764E+01 1.462886E+02 -5.817718E+01 3.881610E+01 + 5.199997E+00 3.000000E+01 6 2.903145E+03 1.697889E+02 -2.857164E+03 5.146542E+02 + 5.199997E+00 6.000000E+01 1 1.686113E+01 -7.846501E+01 3.371660E+00 -1.652059E+01 + 5.199997E+00 6.000000E+01 2 3.889046E+01 -1.118502E+02 -1.447432E+01 -3.609656E+01 + 5.199997E+00 6.000000E+01 3 5.714093E+00 1.418495E+02 -4.493509E+00 3.529765E+00 + 5.199997E+00 6.000000E+01 4 1.021020E+02 -1.621298E+02 -9.717603E+01 -3.133125E+01 + 5.199997E+00 6.000000E+01 5 2.306090E+02 -9.358036E+01 -1.440116E+01 -2.301589E+02 + 5.199997E+00 6.000000E+01 6 2.410101E+03 -1.237994E+01 2.354060E+03 -5.167098E+02 + 5.199997E+00 9.000000E+01 1 1.029325E-05 -1.012334E+02 -2.005185E-06 -1.009605E-05 + 5.199997E+00 9.000000E+01 2 1.575495E+02 8.016237E+01 2.691839E+01 1.552329E+02 + 5.199997E+00 9.000000E+01 3 1.436696E+01 1.714826E+02 -1.420850E+01 2.127890E+00 + 5.199997E+00 9.000000E+01 4 8.917733E+02 8.292913E+01 1.097745E+02 8.849910E+02 + 5.199997E+00 9.000000E+01 5 1.891061E-04 -8.411414E+01 1.939230E-05 -1.881092E-04 + 5.199997E+00 9.000000E+01 6 5.892388E-04 1.639931E+02 -5.663932E-04 1.624843E-04 + 5.299997E+00 0.000000E+00 1 7.318203E+01 8.851676E+01 1.894282E+00 7.315751E+01 + 5.299997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.299997E+00 0.000000E+00 3 7.291105E-01 9.409160E+01 -5.202293E-02 7.272522E-01 + 5.299997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.299997E+00 0.000000E+00 5 3.408557E+02 -1.061450E+02 -9.478160E+01 -3.274127E+02 + 5.299997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.299997E+00 3.000000E+01 1 3.183023E+01 -9.126304E+01 -7.016137E-01 -3.182250E+01 + 5.299997E+00 3.000000E+01 2 2.139673E+01 -1.538552E+02 -1.920749E+01 -9.428274E+00 + 5.299997E+00 3.000000E+01 3 2.469082E+00 7.542561E+01 6.213123E-01 2.389631E+00 + 5.299997E+00 3.000000E+01 4 1.172394E+02 -1.684819E+02 -1.148783E+02 -2.341015E+01 + 5.299997E+00 3.000000E+01 5 7.161636E+01 1.724431E+02 -7.099435E+01 9.418367E+00 + 5.299997E+00 3.000000E+01 6 2.469182E+03 1.730642E+02 -2.451113E+03 2.981705E+02 + 5.299997E+00 6.000000E+01 1 5.029590E+00 -7.181719E+01 1.569483E+00 -4.778441E+00 + 5.299997E+00 6.000000E+01 2 2.403101E+01 -1.265989E+02 -1.432751E+01 -1.929280E+01 + 5.299997E+00 6.000000E+01 3 7.550153E+00 1.475927E+02 -6.374292E+00 4.046382E+00 + 5.299997E+00 6.000000E+01 4 1.006784E+02 1.580147E+02 -9.335703E+01 3.769087E+01 + 5.299997E+00 6.000000E+01 5 2.778275E+02 -9.266583E+01 -1.292196E+01 -2.775269E+02 + 5.299997E+00 6.000000E+01 6 2.538895E+03 -1.221761E+01 2.481391E+03 -5.372943E+02 + 5.299997E+00 9.000000E+01 1 1.056448E-05 -1.012218E+02 -2.055921E-06 -1.036250E-05 + 5.299997E+00 9.000000E+01 2 1.661043E+02 8.158524E+01 2.430735E+01 1.643162E+02 + 5.299997E+00 9.000000E+01 3 1.576545E+01 1.668751E+02 -1.535362E+01 3.579932E+00 + 5.299997E+00 9.000000E+01 4 9.343185E+02 8.368379E+01 1.027895E+02 9.286471E+02 + 5.299997E+00 9.000000E+01 5 1.954692E-04 -8.459381E+01 1.841629E-05 -1.945997E-04 + 5.299997E+00 9.000000E+01 6 5.626847E-04 1.637713E+02 -5.402638E-04 1.572549E-04 + 5.399997E+00 0.000000E+00 1 5.320681E+01 8.927164E+01 6.763632E-01 5.320251E+01 + 5.399997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.399997E+00 0.000000E+00 3 8.946602E-01 1.628443E+02 -8.548536E-01 2.638978E-01 + 5.399997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.399997E+00 0.000000E+00 5 3.084848E+02 -1.108280E+02 -1.096860E+02 -2.883259E+02 + 5.399997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.399997E+00 3.000000E+01 1 3.072328E+01 -9.174631E+01 -9.362619E-01 -3.070901E+01 + 5.399997E+00 3.000000E+01 2 2.341204E+01 -1.477095E+02 -1.979138E+01 -1.250700E+01 + 5.399997E+00 3.000000E+01 3 2.390580E+00 1.128374E+02 -9.278246E-01 2.203183E+00 + 5.399997E+00 3.000000E+01 4 1.212354E+02 -1.613960E+02 -1.149004E+02 -3.867727E+01 + 5.399997E+00 3.000000E+01 5 8.786434E+01 -1.629816E+02 -8.401685E+01 -2.571596E+01 + 5.399997E+00 3.000000E+01 6 2.044515E+03 1.763336E+02 -2.040331E+03 1.307424E+02 + 5.399997E+00 6.000000E+01 1 5.211673E+00 8.915567E+01 7.679845E-02 5.211107E+00 + 5.399997E+00 6.000000E+01 2 1.436965E+01 -1.638569E+02 -1.380306E+01 -3.995303E+00 + 5.399997E+00 6.000000E+01 3 9.404319E+00 1.508960E+02 -8.216909E+00 4.574233E+00 + 5.399997E+00 6.000000E+01 4 1.336929E+02 1.309017E+02 -8.753727E+01 1.010495E+02 + 5.399997E+00 6.000000E+01 5 3.157938E+02 -9.220214E+01 -1.213439E+01 -3.155605E+02 + 5.399997E+00 6.000000E+01 6 2.639307E+03 -1.208229E+01 2.580841E+03 -5.524499E+02 + 5.399997E+00 9.000000E+01 1 1.084641E-05 -1.010023E+02 -2.070025E-06 -1.064705E-05 + 5.399997E+00 9.000000E+01 2 1.735647E+02 8.271427E+01 2.201106E+01 1.721633E+02 + 5.399997E+00 9.000000E+01 3 1.724582E+01 1.640994E+02 -1.658596E+01 4.724835E+00 + 5.399997E+00 9.000000E+01 4 9.710290E+02 8.428634E+01 9.667275E+01 9.662048E+02 + 5.399997E+00 9.000000E+01 5 2.016459E-04 -8.508926E+01 1.726162E-05 -2.009057E-04 + 5.399997E+00 9.000000E+01 6 5.385648E-04 1.635914E+02 -5.166297E-04 1.521372E-04 + 5.499997E+00 0.000000E+00 1 3.771612E+01 9.009675E+01 -6.368235E-02 3.771607E+01 + 5.499997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.499997E+00 0.000000E+00 3 1.600938E+00 -1.721058E+02 -1.585767E+00 -2.198788E-01 + 5.499997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.499997E+00 0.000000E+00 5 2.962563E+02 -1.155710E+02 -1.278731E+02 -2.672382E+02 + 5.499997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.499997E+00 3.000000E+01 1 2.840397E+01 -9.256886E+01 -1.273066E+00 -2.837543E+01 + 5.499997E+00 3.000000E+01 2 2.422392E+01 -1.442243E+02 -1.965315E+01 -1.416163E+01 + 5.499997E+00 3.000000E+01 3 3.138138E+00 1.397190E+02 -2.394031E+00 2.028922E+00 + 5.499997E+00 3.000000E+01 4 1.217762E+02 -1.567622E+02 -1.118971E+02 -4.804665E+01 + 5.499997E+00 3.000000E+01 5 1.172373E+02 -1.464309E+02 -9.768437E+01 -6.482551E+01 + 5.499997E+00 3.000000E+01 6 1.642951E+03 1.798269E+02 -1.642944E+03 4.963988E+00 + 5.499997E+00 6.000000E+01 1 1.392469E+01 9.416711E+01 -1.011847E+00 1.388788E+01 + 5.499997E+00 6.000000E+01 2 1.634966E+01 1.422125E+02 -1.292094E+01 1.001801E+01 + 5.499997E+00 6.000000E+01 3 1.121547E+01 1.531807E+02 -1.000906E+01 5.060182E+00 + 5.499997E+00 6.000000E+01 4 1.784242E+02 1.166464E+02 -8.002017E+01 1.594741E+02 + 5.499997E+00 6.000000E+01 5 3.460588E+02 -9.198971E+01 -1.201513E+01 -3.458501E+02 + 5.499997E+00 6.000000E+01 6 2.716236E+03 -1.196644E+01 2.657210E+03 -5.631809E+02 + 5.499997E+00 9.000000E+01 1 1.112227E-05 -1.005776E+02 -2.041689E-06 -1.093327E-05 + 5.499997E+00 9.000000E+01 2 1.800022E+02 8.361764E+01 2.000959E+01 1.788865E+02 + 5.499997E+00 9.000000E+01 3 1.862189E+01 1.626125E+02 -1.777097E+01 5.564838E+00 + 5.499997E+00 9.000000E+01 4 1.002173E+03 8.477409E+01 9.128094E+01 9.980078E+02 + 5.499997E+00 9.000000E+01 5 2.076841E-04 -8.555885E+01 1.608203E-05 -2.070605E-04 + 5.499997E+00 9.000000E+01 6 5.164861E-04 1.634863E+02 -4.951819E-04 1.468086E-04 + 5.599997E+00 0.000000E+00 1 2.592664E+01 9.071744E+01 -3.246363E-01 2.592461E+01 + 5.599997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.599997E+00 0.000000E+00 3 2.360951E+00 -1.646193E+02 -2.276394E+00 -6.261969E-01 + 5.599997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.599997E+00 0.000000E+00 5 3.003529E+02 -1.195644E+02 -1.481948E+02 -2.612473E+02 + 5.599997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.599997E+00 3.000000E+01 1 2.511107E+01 -9.324791E+01 -1.422701E+00 -2.507073E+01 + 5.599997E+00 3.000000E+01 2 2.390110E+01 -1.424890E+02 -1.895922E+01 -1.455372E+01 + 5.599997E+00 3.000000E+01 3 4.252658E+00 1.533592E+02 -3.801176E+00 1.906873E+00 + 5.599997E+00 3.000000E+01 4 1.185494E+02 -1.539626E+02 -1.065176E+02 -5.203813E+01 + 5.599997E+00 3.000000E+01 5 1.546024E+02 -1.363390E+02 -1.118452E+02 -1.067360E+02 + 5.599997E+00 3.000000E+01 6 1.272583E+03 -1.760506E+02 -1.269561E+03 -8.764964E+01 + 5.599997E+00 6.000000E+01 1 2.162773E+01 9.453346E+01 -1.709483E+00 2.156006E+01 + 5.599997E+00 6.000000E+01 2 2.574589E+01 1.171429E+02 -1.174558E+01 2.291052E+01 + 5.599997E+00 6.000000E+01 3 1.292267E+01 1.550454E+02 -1.171624E+01 5.452082E+00 + 5.599997E+00 6.000000E+01 4 2.250487E+02 1.084547E+02 -7.124017E+01 2.134754E+02 + 5.599997E+00 6.000000E+01 5 3.697420E+02 -9.189798E+01 -1.224580E+01 -3.695392E+02 + 5.599997E+00 6.000000E+01 6 2.773529E+03 -1.184790E+01 2.714442E+03 -5.694453E+02 + 5.599997E+00 9.000000E+01 1 1.137850E-05 -9.996614E+01 -1.969235E-06 -1.120680E-05 + 5.599997E+00 9.000000E+01 2 1.854883E+02 8.433888E+01 1.829739E+01 1.845836E+02 + 5.599997E+00 9.000000E+01 3 1.979555E+01 1.619875E+02 -1.882535E+01 6.121271E+00 + 5.599997E+00 9.000000E+01 4 1.028038E+03 8.516866E+01 8.658434E+01 1.024386E+03 + 5.599997E+00 9.000000E+01 5 2.135555E-04 -8.597174E+01 1.500195E-05 -2.130279E-04 + 5.599997E+00 9.000000E+01 6 5.334870E-04 1.735302E+02 -5.300895E-04 6.011270E-05 + 5.699997E+00 0.000000E+00 1 1.728198E+01 9.010542E+01 -3.179745E-02 1.728195E+01 + 5.699997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.699997E+00 0.000000E+00 3 3.096178E+00 -1.628466E+02 -2.958456E+00 -9.131567E-01 + 5.699997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.699997E+00 0.000000E+00 5 3.170832E+02 -1.222886E+02 -1.693808E+02 -2.680520E+02 + 5.699997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.699997E+00 3.000000E+01 1 2.096853E+01 -9.330057E+01 -1.207242E+00 -2.093375E+01 + 5.699997E+00 3.000000E+01 2 2.260131E+01 -1.422039E+02 -1.785948E+01 -1.385128E+01 + 5.699997E+00 3.000000E+01 3 5.475793E+00 1.603896E+02 -5.158177E+00 1.837805E+00 + 5.699997E+00 3.000000E+01 4 1.118138E+02 -1.527302E+02 -9.938672E+01 -5.123090E+01 + 5.699997E+00 3.000000E+01 5 1.962200E+02 -1.298908E+02 -1.258410E+02 -1.505534E+02 + 5.699997E+00 3.000000E+01 6 9.383300E+02 -1.705120E+02 -9.254937E+02 -1.546758E+02 + 5.699997E+00 6.000000E+01 1 2.851969E+01 9.417486E+01 -2.076246E+00 2.844401E+01 + 5.699997E+00 6.000000E+01 2 3.630803E+01 1.065696E+02 -1.035434E+01 3.480030E+01 + 5.699997E+00 6.000000E+01 3 1.446616E+01 1.567466E+02 -1.329104E+01 5.711210E+00 + 5.699997E+00 6.000000E+01 4 2.705252E+02 1.031721E+02 -6.164660E+01 2.634077E+02 + 5.699997E+00 6.000000E+01 5 3.876318E+02 -9.183718E+01 -1.242720E+01 -3.874325E+02 + 5.699997E+00 6.000000E+01 6 2.813971E+03 -1.170341E+01 2.755471E+03 -5.708015E+02 + 5.699997E+00 9.000000E+01 1 1.160414E-05 -9.919559E+01 -1.854404E-06 -1.145501E-05 + 5.699997E+00 9.000000E+01 2 1.901039E+02 8.490704E+01 1.687589E+01 1.893534E+02 + 5.699997E+00 9.000000E+01 3 2.071064E+01 1.619549E+02 -1.969195E+01 6.415437E+00 + 5.699997E+00 9.000000E+01 4 1.048984E+03 8.548279E+01 8.261642E+01 1.045725E+03 + 5.699997E+00 9.000000E+01 5 2.191727E-04 -8.631281E+01 1.409480E-05 -2.187190E-04 + 5.699997E+00 9.000000E+01 6 5.074404E-04 1.735952E+02 -5.042733E-04 5.660590E-05 + 5.799997E+00 0.000000E+00 1 1.144484E+01 8.563708E+01 8.706529E-01 1.141168E+01 + 5.799997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.799997E+00 0.000000E+00 3 3.805194E+00 -1.636273E+02 -3.650888E+00 -1.072621E+00 + 5.799997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.799997E+00 0.000000E+00 5 3.429525E+02 -1.236140E+02 -1.898565E+02 -2.856062E+02 + 5.799997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.799997E+00 3.000000E+01 1 1.604464E+01 -9.196248E+01 -5.494484E-01 -1.603523E+01 + 5.799997E+00 3.000000E+01 2 2.052374E+01 -1.434422E+02 -1.648582E+01 -1.222463E+01 + 5.799997E+00 3.000000E+01 3 6.704503E+00 1.643690E+02 -6.456552E+00 1.806462E+00 + 5.799997E+00 3.000000E+01 4 1.021577E+02 -1.530744E+02 -9.108334E+01 -4.626033E+01 + 5.799997E+00 3.000000E+01 5 2.396104E+02 -1.253522E+02 -1.386386E+02 -1.954289E+02 + 5.799997E+00 3.000000E+01 6 6.452072E+02 -1.617413E+02 -6.127220E+02 -2.021487E+02 + 5.799997E+00 6.000000E+01 1 3.476017E+01 9.361497E+01 -2.191678E+00 3.469101E+01 + 5.799997E+00 6.000000E+01 2 4.661618E+01 1.009082E+02 -8.821434E+00 4.577390E+01 + 5.799997E+00 6.000000E+01 3 1.579199E+01 1.583885E+02 -1.468185E+01 5.816370E+00 + 5.799997E+00 6.000000E+01 4 3.137964E+02 9.947241E+01 -5.164229E+01 3.095178E+02 + 5.799997E+00 6.000000E+01 5 4.002642E+02 -9.174596E+01 -1.219529E+01 -4.000784E+02 + 5.799997E+00 6.000000E+01 6 2.839525E+03 -1.151507E+01 2.782372E+03 -5.668420E+02 + 5.799997E+00 9.000000E+01 1 1.179089E-05 -9.829910E+01 -1.701904E-06 -1.166742E-05 + 5.799997E+00 9.000000E+01 2 1.939394E+02 8.534341E+01 1.574466E+01 1.932993E+02 + 5.799997E+00 9.000000E+01 3 2.133052E+01 1.623423E+02 -2.032555E+01 6.470180E+00 + 5.799997E+00 9.000000E+01 4 1.065437E+03 8.572481E+01 7.942514E+01 1.062473E+03 + 5.799997E+00 9.000000E+01 5 2.244461E-04 -8.658265E+01 1.337895E-05 -2.240470E-04 + 5.799997E+00 9.000000E+01 6 4.829921E-04 1.736989E+02 -4.800743E-04 5.300975E-05 + 5.899997E+00 0.000000E+00 1 8.392694E+00 7.358714E+01 2.371412E+00 8.050696E+00 + 5.899997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.899997E+00 0.000000E+00 3 4.499769E+00 -1.656466E+02 -4.359310E+00 -1.115499E+00 + 5.899997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.899997E+00 0.000000E+00 5 3.747024E+02 -1.236756E+02 -2.077689E+02 -3.118236E+02 + 5.899997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.899997E+00 3.000000E+01 1 1.042408E+01 -8.704988E+01 5.364913E-01 -1.041026E+01 + 5.899997E+00 3.000000E+01 2 1.789810E+01 -1.466397E+02 -1.494902E+01 -9.842196E+00 + 5.899997E+00 3.000000E+01 3 7.883803E+00 1.668464E+02 -7.676961E+00 1.794051E+00 + 5.899997E+00 3.000000E+01 4 9.039412E+01 -1.552851E+02 -8.211400E+01 -3.779402E+01 + 5.899997E+00 3.000000E+01 5 2.828014E+02 -1.217937E+02 -1.489974E+02 -2.403673E+02 + 5.899997E+00 3.000000E+01 6 4.059503E+02 -1.446949E+02 -3.312903E+02 -2.346111E+02 + 5.899997E+00 6.000000E+01 1 4.046095E+01 9.303251E+01 -2.140489E+00 4.040429E+01 + 5.899997E+00 6.000000E+01 2 5.636086E+01 9.735036E+01 -7.210611E+00 5.589771E+01 + 5.899997E+00 6.000000E+01 3 1.685619E+01 1.600059E+02 -1.584023E+01 5.763529E+00 + 5.899997E+00 6.000000E+01 4 3.544296E+02 9.673380E+01 -4.155926E+01 3.519846E+02 + 5.899997E+00 6.000000E+01 5 4.080023E+02 -9.158569E+01 -1.129021E+01 -4.078460E+02 + 5.899997E+00 6.000000E+01 6 2.851611E+03 -1.127238E+01 2.796601E+03 -5.574141E+02 + 5.899997E+00 9.000000E+01 1 1.193312E-05 -9.731239E+01 -1.518836E-06 -1.183606E-05 + 5.899997E+00 9.000000E+01 2 1.970907E+02 8.566570E+01 1.489529E+01 1.965271E+02 + 5.899997E+00 9.000000E+01 3 2.163098E+01 1.630303E+02 -2.068915E+01 6.313335E+00 + 5.899997E+00 9.000000E+01 4 1.077874E+03 8.590173E+01 7.703280E+01 1.075118E+03 + 5.899997E+00 9.000000E+01 5 2.292903E-04 -8.679324E+01 1.282634E-05 -2.289313E-04 + 5.899997E+00 9.000000E+01 6 4.599442E-04 1.738406E+02 -4.572890E-04 4.934994E-05 + 5.999997E+00 0.000000E+00 1 8.249591E+00 5.801945E+01 4.369242E+00 6.997534E+00 + 5.999997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.999997E+00 0.000000E+00 3 5.187577E+00 -1.681797E+02 -5.077574E+00 -1.062639E+00 + 5.999997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.999997E+00 0.000000E+00 5 4.092494E+02 -1.227191E+02 -2.212080E+02 -3.443139E+02 + 5.999997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 5.999997E+00 3.000000E+01 1 4.531404E+00 -6.442155E+01 1.956418E+00 -4.087304E+00 + 5.999997E+00 3.000000E+01 2 1.500057E+01 -1.527637E+02 -1.333741E+01 -6.865170E+00 + 5.999997E+00 3.000000E+01 3 8.973127E+00 1.685330E+02 -8.794018E+00 1.783891E+00 + 5.999997E+00 3.000000E+01 4 7.756216E+01 -1.600227E+02 -7.289507E+01 -2.649899E+01 + 5.999997E+00 3.000000E+01 5 3.239916E+02 -1.187229E+02 -1.557018E+02 -2.841259E+02 + 5.999997E+00 3.000000E+01 6 2.677123E+02 -1.074318E+02 -8.019846E+01 -2.554175E+02 + 5.999997E+00 6.000000E+01 1 4.569069E+01 9.251271E+01 -2.003130E+00 4.564676E+01 + 5.999997E+00 6.000000E+01 2 6.546344E+01 9.488390E+01 -5.573354E+00 6.522576E+01 + 5.999997E+00 6.000000E+01 3 1.762659E+01 1.616013E+02 -1.672557E+01 5.563430E+00 + 5.999997E+00 6.000000E+01 4 3.922416E+02 9.462893E+01 -3.165479E+01 3.909622E+02 + 5.999997E+00 6.000000E+01 5 4.110932E+02 -9.133858E+01 -9.603373E+00 -4.109810E+02 + 5.999997E+00 6.000000E+01 6 2.851342E+03 -1.097183E+01 2.799222E+03 -5.426855E+02 + 5.999997E+00 9.000000E+01 1 1.202753E-05 -9.627190E+01 -1.313971E-06 -1.195555E-05 + 5.999997E+00 9.000000E+01 2 1.996523E+02 8.589021E+01 1.430868E+01 1.991389E+02 + 5.999997E+00 9.000000E+01 3 2.159931E+01 1.639290E+02 -2.075520E+01 5.979290E+00 + 5.999997E+00 9.000000E+01 4 1.086781E+03 8.602073E+01 7.541784E+01 1.084161E+03 + 5.999997E+00 9.000000E+01 5 2.336553E-04 -8.696281E+01 1.238002E-05 -2.333271E-04 + 5.999997E+00 9.000000E+01 6 4.381380E-04 1.740168E+02 -4.357513E-04 4.567037E-05 + 6.099997E+00 0.000000E+00 1 1.046364E+01 5.035596E+01 6.675972E+00 8.057245E+00 + 6.099997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.099997E+00 0.000000E+00 3 5.866732E+00 -1.707883E+02 -5.791072E+00 -9.391614E-01 + 6.099997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.099997E+00 0.000000E+00 5 4.436782E+02 -1.210020E+02 -2.285244E+02 -3.802985E+02 + 6.099997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.099997E+00 3.000000E+01 1 4.574429E+00 3.900104E+01 3.554947E+00 2.878845E+00 + 6.099997E+00 3.000000E+01 2 1.221256E+01 -1.636316E+02 -1.171758E+01 -3.441653E+00 + 6.099997E+00 3.000000E+01 3 9.939134E+00 1.697807E+02 -9.781460E+00 1.763356E+00 + 6.099997E+00 3.000000E+01 4 6.506376E+01 -1.684614E+02 -6.374884E+01 -1.301454E+01 + 6.099997E+00 3.000000E+01 5 3.614323E+02 -1.158878E+02 -1.578053E+02 -3.251627E+02 + 6.099997E+00 3.000000E+01 6 3.025023E+02 -6.198606E+01 1.420812E+02 -2.670591E+02 + 6.099997E+00 6.000000E+01 1 5.048534E+01 9.209763E+01 -1.847879E+00 5.045151E+01 + 6.099997E+00 6.000000E+01 2 7.391103E+01 9.306325E+01 -3.949679E+00 7.380543E+01 + 6.099997E+00 6.000000E+01 3 1.808422E+01 1.631641E+02 -1.730909E+01 5.237776E+00 + 6.099997E+00 6.000000E+01 4 4.271609E+02 9.296829E+01 -2.211983E+01 4.265879E+02 + 6.099997E+00 6.000000E+01 5 4.097423E+02 -9.100600E+01 -7.193880E+00 -4.096792E+02 + 6.099997E+00 6.000000E+01 6 2.839707E+03 -1.061555E+01 2.791107E+03 -5.231253E+02 + 6.099997E+00 9.000000E+01 1 1.207376E-05 -9.521217E+01 -1.096832E-06 -1.202384E-05 + 6.099997E+00 9.000000E+01 2 2.017121E+02 8.603269E+01 1.395591E+01 2.012287E+02 + 6.099997E+00 9.000000E+01 3 2.123364E+01 1.649668E+02 -2.050693E+01 5.507566E+00 + 6.099997E+00 9.000000E+01 4 1.092631E+03 8.608970E+01 7.451158E+01 1.090088E+03 + 6.099997E+00 9.000000E+01 5 2.375192E-04 -8.711062E+01 1.197284E-05 -2.372173E-04 + 6.099997E+00 9.000000E+01 6 4.174509E-04 1.742228E+02 -4.153306E-04 4.202110E-05 + 6.199996E+00 0.000000E+00 1 1.423732E+01 5.055992E+01 9.044558E+00 1.099533E+01 + 6.199996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.199996E+00 0.000000E+00 3 6.524652E+00 -1.732178E+02 -6.478994E+00 -7.705297E-01 + 6.199996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.199996E+00 0.000000E+00 5 4.753039E+02 -1.187623E+02 -2.287052E+02 -4.166626E+02 + 6.199996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.199996E+00 3.000000E+01 1 1.159182E+01 6.364566E+01 5.145857E+00 1.038704E+01 + 6.199996E+00 3.000000E+01 2 1.014111E+01 1.783265E+02 -1.013678E+01 2.961683E-01 + 6.199996E+00 3.000000E+01 3 1.075400E+01 1.707731E+02 -1.061486E+01 1.724348E+00 + 6.199996E+00 3.000000E+01 4 5.494801E+01 1.778411E+02 -5.490900E+01 2.069896E+00 + 6.199996E+00 3.000000E+01 5 3.935418E+02 -1.131767E+02 -1.548857E+02 -3.617812E+02 + 6.199996E+00 3.000000E+01 6 4.329815E+02 -3.882263E+01 3.373317E+02 -2.714411E+02 + 6.199996E+00 6.000000E+01 1 5.485495E+01 9.180088E+01 -1.723876E+00 5.482785E+01 + 6.199996E+00 6.000000E+01 2 8.171471E+01 9.166198E+01 -2.369965E+00 8.168033E+01 + 6.199996E+00 6.000000E+01 3 1.822185E+01 1.646790E+02 -1.757425E+01 4.814692E+00 + 6.199996E+00 6.000000E+01 4 4.591909E+02 9.163345E+01 -1.308932E+01 4.590043E+02 + 6.199996E+00 6.000000E+01 5 4.041983E+02 -9.060629E+01 -4.277046E+00 -4.041757E+02 + 6.199996E+00 6.000000E+01 6 2.817646E+03 -1.020965E+01 2.773031E+03 -4.994294E+02 + 6.199996E+00 9.000000E+01 1 1.207343E-05 -9.416452E+01 -8.767791E-07 -1.204155E-05 + 6.199996E+00 9.000000E+01 2 2.033479E+02 8.610851E+01 1.380067E+01 2.028790E+02 + 6.199996E+00 9.000000E+01 3 2.054312E+01 1.660861E+02 -1.994034E+01 4.939880E+00 + 6.199996E+00 9.000000E+01 4 1.095863E+03 8.611726E+01 7.420622E+01 1.093347E+03 + 6.199996E+00 9.000000E+01 5 2.409031E-04 -8.725345E+01 1.154361E-05 -2.406263E-04 + 6.199996E+00 9.000000E+01 6 3.977880E-04 1.744530E+02 -3.959252E-04 3.845130E-05 + 6.299996E+00 0.000000E+00 1 1.914362E+01 5.413163E+01 1.121673E+01 1.551332E+01 + 6.299996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.299996E+00 0.000000E+00 3 7.141086E+00 -1.753409E+02 -7.117488E+00 -5.800562E-01 + 6.299996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.299996E+00 0.000000E+00 5 5.019013E+02 -1.162051E+02 -2.216324E+02 -4.503155E+02 + 6.299996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.299996E+00 3.000000E+01 1 1.941873E+01 7.028712E+01 6.550072E+00 1.828069E+01 + 6.299996E+00 3.000000E+01 2 9.609566E+00 1.538569E+02 -8.626476E+00 4.234107E+00 + 6.299996E+00 3.000000E+01 3 1.139540E+01 1.716096E+02 -1.127343E+01 1.662793E+00 + 6.299996E+00 3.000000E+01 4 4.997646E+01 1.586054E+02 -4.653260E+01 1.823085E+01 + 6.299996E+00 3.000000E+01 5 4.190488E+02 -1.105592E+02 -1.471591E+02 -3.923597E+02 + 6.299996E+00 3.000000E+01 6 5.748251E+02 -2.802354E+01 5.074295E+02 -2.700725E+02 + 6.299996E+00 6.000000E+01 1 5.879642E+01 9.161513E+01 -1.657208E+00 5.877306E+01 + 6.299996E+00 6.000000E+01 2 8.889552E+01 9.055240E+01 -8.570521E-01 8.889138E+01 + 6.299996E+00 6.000000E+01 3 1.804291E+01 1.661316E+02 -1.751694E+01 4.324758E+00 + 6.299996E+00 6.000000E+01 4 4.883799E+02 9.054623E+01 -4.655920E+00 4.883577E+02 + 6.299996E+00 6.000000E+01 5 3.947912E+02 -9.016973E+01 -1.169526E+00 -3.947895E+02 + 6.299996E+00 6.000000E+01 6 2.786145E+03 -9.762721E+00 2.745798E+03 -4.724420E+02 + 6.299996E+00 9.000000E+01 1 1.203010E-05 -9.315540E+01 -6.621877E-07 -1.201186E-05 + 6.299996E+00 9.000000E+01 2 2.046265E+02 8.613224E+01 1.380285E+01 2.041604E+02 + 6.299996E+00 9.000000E+01 3 1.954493E+01 1.672406E+02 -1.906229E+01 4.316647E+00 + 6.299996E+00 9.000000E+01 4 1.096852E+03 8.611218E+01 7.436994E+01 1.094328E+03 + 6.299996E+00 9.000000E+01 5 2.438480E-04 -8.740331E+01 1.104761E-05 -2.435977E-04 + 6.299996E+00 9.000000E+01 6 3.790760E-04 1.747016E+02 -3.774563E-04 3.500461E-05 + 6.399996E+00 0.000000E+00 1 2.490040E+01 5.859365E+01 1.297570E+01 2.125232E+01 + 6.399996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.399996E+00 0.000000E+00 3 7.690893E+00 -1.771123E+02 -7.681128E+00 -3.874537E-01 + 6.399996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.399996E+00 0.000000E+00 5 5.218397E+02 -1.135057E+02 -2.081304E+02 -4.785378E+02 + 6.399996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.399996E+00 3.000000E+01 1 2.744187E+01 7.385473E+01 7.630864E+00 2.635955E+01 + 6.399996E+00 3.000000E+01 2 1.097380E+01 1.310448E+02 -7.205935E+00 8.276397E+00 + 6.399996E+00 3.000000E+01 3 1.184639E+01 1.723465E+02 -1.174086E+01 1.577718E+00 + 6.399996E+00 3.000000E+01 4 5.220620E+01 1.378680E+02 -3.871618E+01 3.502207E+01 + 6.399996E+00 3.000000E+01 5 4.371505E+02 -1.080518E+02 -1.354627E+02 -4.156325E+02 + 6.399996E+00 3.000000E+01 6 7.056147E+02 -2.198862E+01 6.542870E+02 -2.641980E+02 + 6.399996E+00 6.000000E+01 1 6.230491E+01 9.151879E+01 -1.651382E+00 6.228302E+01 + 6.399996E+00 6.000000E+01 2 9.548029E+01 8.965668E+01 5.721323E-01 9.547857E+01 + 6.399996E+00 6.000000E+01 3 1.755966E+01 1.675099E+02 -1.714409E+01 3.797630E+00 + 6.399996E+00 6.000000E+01 4 5.148070E+02 8.965267E+01 3.120712E+00 5.147975E+02 + 6.399996E+00 6.000000E+01 5 3.819733E+02 -8.973202E+01 1.786511E+00 -3.819691E+02 + 6.399996E+00 6.000000E+01 6 2.746226E+03 -9.284508E+00 2.710248E+03 -4.430677E+02 + 6.399996E+00 9.000000E+01 1 1.194856E-05 -9.220567E+01 -4.598603E-07 -1.193971E-05 + 6.399996E+00 9.000000E+01 2 2.056012E+02 8.611742E+01 1.392169E+01 2.051293E+02 + 6.399996E+00 9.000000E+01 3 1.826296E+01 1.683928E+02 -1.788948E+01 3.674524E+00 + 6.399996E+00 9.000000E+01 4 1.095928E+03 8.608315E+01 7.486142E+01 1.093369E+03 + 6.399996E+00 9.000000E+01 5 2.464013E-04 -8.756695E+01 1.046024E-05 -2.461792E-04 + 6.399996E+00 9.000000E+01 6 3.612580E-04 1.749633E+02 -3.598631E-04 3.171640E-05 + 6.499996E+00 0.000000E+00 1 3.122998E+01 6.298394E+01 1.418592E+01 2.782214E+01 + 6.499996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.499996E+00 0.000000E+00 3 8.148113E+00 -1.785369E+02 -8.145456E+00 -2.080519E-01 + 6.499996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.499996E+00 0.000000E+00 5 5.342173E+02 -1.108041E+02 -1.897402E+02 -4.993865E+02 + 6.499996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.499996E+00 3.000000E+01 1 3.539780E+01 7.641184E+01 8.316403E+00 3.440700E+01 + 6.499996E+00 3.000000E+01 2 1.367614E+01 1.154904E+02 -5.885651E+00 1.234487E+01 + 6.499996E+00 3.000000E+01 3 1.209567E+01 1.730168E+02 -1.200595E+01 1.470577E+00 + 6.499996E+00 3.000000E+01 4 6.085913E+01 1.211826E+02 -3.151083E+01 5.206631E+01 + 6.499996E+00 3.000000E+01 5 4.475864E+02 -1.056898E+02 -1.210405E+02 -4.309092E+02 + 6.499996E+00 3.000000E+01 6 8.204029E+02 -1.809916E+01 7.798096E+02 -2.548684E+02 + 6.499996E+00 6.000000E+01 1 6.538300E+01 9.148339E+01 -1.692576E+00 6.536109E+01 + 6.499996E+00 6.000000E+01 2 1.014976E+02 8.892442E+01 1.905245E+00 1.014797E+02 + 6.499996E+00 6.000000E+01 3 1.678957E+01 1.688050E+02 -1.647010E+01 3.259687E+00 + 6.499996E+00 6.000000E+01 4 5.385770E+02 8.891418E+01 1.020595E+01 5.384803E+02 + 6.499996E+00 6.000000E+01 5 3.662848E+02 -8.932704E+01 4.302074E+00 -3.662596E+02 + 6.499996E+00 6.000000E+01 6 2.698946E+03 -8.785026E+00 2.667282E+03 -4.122033E+02 + 6.499996E+00 9.000000E+01 1 1.183456E-05 -9.133024E+01 -2.747390E-07 -1.183137E-05 + 6.499996E+00 9.000000E+01 2 2.063142E+02 8.607605E+01 1.411855E+01 2.058306E+02 + 6.499996E+00 9.000000E+01 3 1.672458E+01 1.695131E+02 -1.644522E+01 3.044042E+00 + 6.499996E+00 9.000000E+01 4 1.093365E+03 8.603822E+01 7.554176E+01 1.090752E+03 + 6.499996E+00 9.000000E+01 5 2.486224E-04 -8.774632E+01 9.776836E-06 -2.484300E-04 + 6.499996E+00 9.000000E+01 6 3.442881E-04 1.752327E+02 -3.430970E-04 2.861344E-05 + 6.599996E+00 0.000000E+00 1 3.786176E+01 6.697951E+01 1.480623E+01 3.484664E+01 + 6.599996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.599996E+00 0.000000E+00 3 8.487835E+00 -1.796442E+02 -8.487671E+00 -5.270457E-02 + 6.599996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.599996E+00 0.000000E+00 5 5.388351E+02 -1.082077E+02 -1.683661E+02 -5.118555E+02 + 6.599996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.599996E+00 3.000000E+01 1 4.308966E+01 7.848481E+01 8.601892E+00 4.222235E+01 + 6.599996E+00 3.000000E+01 2 1.702968E+01 1.059161E+02 -4.670047E+00 1.637683E+01 + 6.599996E+00 3.000000E+01 3 1.213597E+01 1.736402E+02 -1.206129E+01 1.344316E+00 + 6.599996E+00 3.000000E+01 4 7.342095E+01 1.098535E+02 -2.493490E+01 6.905713E+01 + 6.599996E+00 3.000000E+01 5 4.506039E+02 -1.035107E+02 -1.052731E+02 -4.381340E+02 + 6.599996E+00 3.000000E+01 6 9.185867E+02 -1.533850E+01 8.858665E+02 -2.429855E+02 + 6.599996E+00 6.000000E+01 1 6.804441E+01 9.148019E+01 -1.757680E+00 6.802171E+01 + 6.599996E+00 6.000000E+01 2 1.069763E+02 8.832145E+01 3.133549E+00 1.069304E+02 + 6.599996E+00 6.000000E+01 3 1.575467E+01 1.700105E+02 -1.551582E+01 2.732924E+00 + 6.599996E+00 6.000000E+01 4 5.598049E+02 8.830235E+01 1.658437E+01 5.595591E+02 + 6.599996E+00 6.000000E+01 5 3.483130E+02 -8.898127E+01 6.192752E+00 -3.482580E+02 + 6.599996E+00 6.000000E+01 6 2.645371E+03 -8.273825E+00 2.617837E+03 -3.806798E+02 + 6.599996E+00 9.000000E+01 1 1.169387E-05 -9.053847E+01 -1.098983E-07 -1.169335E-05 + 6.599996E+00 9.000000E+01 2 2.067984E+02 8.601857E+01 1.435866E+01 2.062993E+02 + 6.599996E+00 9.000000E+01 3 1.495983E+01 1.705767E+02 -1.475796E+01 2.449327E+00 + 6.599996E+00 9.000000E+01 4 1.089383E+03 8.598453E+01 7.628492E+01 1.086709E+03 + 6.599996E+00 9.000000E+01 5 2.505603E-04 -8.793982E+01 9.007451E-06 -2.503984E-04 + 6.599996E+00 9.000000E+01 6 3.281282E-04 1.755054E+02 -3.271191E-04 2.571375E-05 + 6.699996E+00 0.000000E+00 1 4.455798E+01 7.049490E+01 1.487750E+01 4.200088E+01 + 6.699996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.699996E+00 0.000000E+00 3 8.688542E+00 1.795257E+02 -8.688245E+00 7.192025E-02 + 6.699996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.699996E+00 0.000000E+00 5 5.360759E+02 -1.057896E+02 -1.458690E+02 -5.158484E+02 + 6.699996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.699996E+00 3.000000E+01 1 5.037367E+01 8.024486E+01 8.535211E+00 4.964531E+01 + 6.699996E+00 3.000000E+01 2 2.063268E+01 9.993425E+01 -3.559507E+00 2.032333E+01 + 6.699996E+00 3.000000E+01 3 1.196493E+01 1.742294E+02 -1.190430E+01 1.203019E+00 + 6.699996E+00 3.000000E+01 4 8.782640E+01 1.024838E+02 -1.898485E+01 8.574994E+01 + 6.699996E+00 3.000000E+01 5 4.468409E+02 -1.015424E+02 -8.940945E+01 -4.378044E+02 + 6.699996E+00 3.000000E+01 6 1.000911E+03 -1.324486E+01 9.742869E+02 -2.293219E+02 + 6.699996E+00 6.000000E+01 1 7.031628E+01 9.148508E+01 -1.822360E+00 7.029266E+01 + 6.699996E+00 6.000000E+01 2 1.119460E+02 8.782357E+01 4.251348E+00 1.118652E+02 + 6.699996E+00 6.000000E+01 3 1.447888E+01 1.711226E+02 -1.430544E+01 2.234383E+00 + 6.699996E+00 6.000000E+01 4 5.786184E+02 8.779576E+01 2.225468E+01 5.781902E+02 + 6.699996E+00 6.000000E+01 5 3.286430E+02 -8.871101E+01 7.392869E+00 -3.285598E+02 + 6.699996E+00 6.000000E+01 6 2.586569E+03 -7.759521E+00 2.562885E+03 -3.492271E+02 + 6.699996E+00 9.000000E+01 1 1.153209E-05 -8.983506E+01 3.319838E-08 -1.153204E-05 + 6.699996E+00 9.000000E+01 2 2.070776E+02 8.595363E+01 1.461220E+01 2.065614E+02 + 6.699996E+00 9.000000E+01 3 1.299832E+01 1.715605E+02 -1.285757E+01 1.907696E+00 + 6.699996E+00 9.000000E+01 4 1.084159E+03 8.592821E+01 7.698219E+01 1.081422E+03 + 6.699996E+00 9.000000E+01 5 2.522556E-04 -8.814351E+01 8.172125E-06 -2.521232E-04 + 6.699996E+00 9.000000E+01 6 3.127473E-04 1.757775E+02 -3.118984E-04 2.302751E-05 + 6.799996E+00 0.000000E+00 1 5.113235E+01 7.353231E+01 1.449473E+01 4.903489E+01 + 6.799996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.799996E+00 0.000000E+00 3 8.732897E+00 1.789313E+02 -8.731378E+00 1.628813E-01 + 6.799996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.799996E+00 0.000000E+00 5 5.266843E+02 -1.035937E+02 -1.237892E+02 -5.119302E+02 + 6.799996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.799996E+00 3.000000E+01 1 5.715731E+01 8.175683E+01 8.194915E+00 5.656678E+01 + 6.799996E+00 3.000000E+01 2 2.428172E+01 9.603278E+01 -2.551944E+00 2.414725E+01 + 6.799996E+00 3.000000E+01 3 1.158336E+01 1.747928E+02 -1.153555E+01 1.051281E+00 + 6.799996E+00 3.000000E+01 4 1.028631E+02 9.762134E+01 -1.364228E+01 1.019544E+02 + 6.799996E+00 3.000000E+01 5 4.371751E+02 -9.979926E+01 -7.440577E+01 -4.307968E+02 + 6.799996E+00 3.000000E+01 6 1.068589E+03 -1.158160E+01 1.046832E+03 -2.145334E+02 + 6.799996E+00 6.000000E+01 1 7.223330E+01 9.148089E+01 -1.866762E+00 7.220918E+01 + 6.799996E+00 6.000000E+01 2 1.164352E+02 8.741300E+01 5.255457E+00 1.163165E+02 + 6.799996E+00 6.000000E+01 3 1.298696E+01 1.721374E+02 -1.286487E+01 1.776593E+00 + 6.799996E+00 6.000000E+01 4 5.951456E+02 8.737786E+01 2.722735E+01 5.945225E+02 + 6.799996E+00 6.000000E+01 5 3.077865E+02 -8.852185E+01 7.939594E+00 -3.076841E+02 + 6.799996E+00 6.000000E+01 6 2.523560E+03 -7.249585E+00 2.503386E+03 -3.184525E+02 + 6.799996E+00 9.000000E+01 1 1.135437E-05 -8.922071E+01 1.544279E-07 -1.135332E-05 + 6.799996E+00 9.000000E+01 2 2.071705E+02 8.588818E+01 1.485480E+01 2.066373E+02 + 6.799996E+00 9.000000E+01 3 1.086942E+01 1.724371E+02 -1.077487E+01 1.430578E+00 + 6.799996E+00 9.000000E+01 4 1.077842E+03 8.587426E+01 7.754592E+01 1.075049E+03 + 6.799996E+00 9.000000E+01 5 2.537453E-04 -8.835240E+01 7.295710E-06 -2.536403E-04 + 6.799996E+00 9.000000E+01 6 2.981145E-04 1.760457E+02 -2.974048E-04 2.055814E-05 + 6.899996E+00 0.000000E+00 1 5.745194E+01 7.612595E+01 1.377632E+01 5.577579E+01 + 6.899996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.899996E+00 0.000000E+00 3 8.607684E+00 1.785334E+02 -8.604864E+00 2.203111E-01 + 6.899996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.899996E+00 0.000000E+00 5 5.116173E+02 -1.016391E+02 -1.032173E+02 -5.010972E+02 + 6.899996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.899996E+00 3.000000E+01 1 6.339461E+01 8.305264E+01 7.668045E+00 6.292915E+01 + 6.899996E+00 3.000000E+01 2 2.786877E+01 9.338131E+01 -1.643719E+00 2.782025E+01 + 6.899996E+00 3.000000E+01 3 1.099518E+01 1.753356E+02 -1.095876E+01 8.941151E-01 + 6.899996E+00 3.000000E+01 4 1.178615E+02 9.432112E+01 -8.880433E+00 1.175264E+02 + 6.899996E+00 3.000000E+01 5 4.225779E+02 -9.828252E+01 -6.087412E+01 -4.181703E+02 + 6.899996E+00 3.000000E+01 6 1.122989E+03 -1.021568E+01 1.105186E+03 -1.991666E+02 + 6.899996E+00 6.000000E+01 1 7.383486E+01 9.145753E+01 -1.878057E+00 7.381097E+01 + 6.899996E+00 6.000000E+01 2 1.204713E+02 8.707623E+01 6.144914E+00 1.203145E+02 + 6.899996E+00 6.000000E+01 3 1.130301E+01 1.730492E+02 -1.121993E+01 1.367863E+00 + 6.899996E+00 6.000000E+01 4 6.095179E+02 8.703556E+01 3.152198E+01 6.087022E+02 + 6.899996E+00 6.000000E+01 5 2.861794E+02 -8.841126E+01 7.934399E+00 -2.860694E+02 + 6.899996E+00 6.000000E+01 6 2.457310E+03 -6.750232E+00 2.440276E+03 -2.888357E+02 + 6.899996E+00 9.000000E+01 1 1.116526E-05 -8.869334E+01 2.546057E-07 -1.116236E-05 + 6.899996E+00 9.000000E+01 2 2.070912E+02 8.582763E+01 1.506740E+01 2.065423E+02 + 6.899996E+00 9.000000E+01 3 8.599986E+00 1.731607E+02 -8.538789E+00 1.024133E+00 + 6.899996E+00 9.000000E+01 4 1.070553E+03 8.582662E+01 7.790929E+01 1.067714E+03 + 6.899996E+00 9.000000E+01 5 2.550481E-04 -8.856126E+01 6.403743E-06 -2.549677E-04 + 6.899996E+00 9.000000E+01 6 2.842032E-04 1.763074E+02 -2.836132E-04 1.830359E-05 + 6.999996E+00 0.000000E+00 1 6.343251E+01 7.832144E+01 1.284006E+01 6.211937E+01 + 6.999996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.999996E+00 0.000000E+00 3 8.304324E+00 1.782966E+02 -8.300654E+00 2.468486E-01 + 6.999996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.999996E+00 0.000000E+00 5 4.918595E+02 -9.992722E+01 -8.479517E+01 -4.844952E+02 + 6.999996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 6.999996E+00 3.000000E+01 1 6.907496E+01 8.415459E+01 7.034931E+00 6.871579E+01 + 6.999996E+00 3.000000E+01 2 3.133360E+01 9.151859E+01 -8.303803E-01 3.132260E+01 + 6.999996E+00 3.000000E+01 3 1.020716E+01 1.758622E+02 -1.018056E+01 7.364960E-01 + 6.999996E+00 3.000000E+01 4 1.324410E+02 9.201951E+01 -4.667178E+00 1.323587E+02 + 6.999996E+00 3.000000E+01 5 4.039922E+02 -9.698272E+01 -4.911329E+01 -4.009958E+02 + 6.999996E+00 3.000000E+01 6 1.165503E+03 -9.066772E+00 1.150941E+03 -1.836663E+02 + 6.999996E+00 6.000000E+01 1 7.516010E+01 9.141090E+01 -1.850616E+00 7.513731E+01 + 6.999996E+00 6.000000E+01 2 1.240806E+02 8.680267E+01 6.920580E+00 1.238875E+02 + 6.999996E+00 6.000000E+01 3 9.450929E+00 1.738460E+02 -9.396466E+00 1.013153E+00 + 6.999996E+00 6.000000E+01 4 6.218619E+02 8.675819E+01 3.516629E+01 6.208668E+02 + 6.999996E+00 6.000000E+01 5 2.641574E+02 -8.837112E+01 7.508770E+00 -2.640507E+02 + 6.999996E+00 6.000000E+01 6 2.388713E+03 -6.266428E+00 2.374440E+03 -2.607325E+02 + 6.999996E+00 9.000000E+01 1 1.096863E-05 -8.824891E+01 3.351755E-07 -1.096351E-05 + 6.999996E+00 9.000000E+01 2 2.068489E+02 8.577593E+01 1.523589E+01 2.062870E+02 + 6.999996E+00 9.000000E+01 3 6.214508E+00 1.736199E+02 -6.176019E+00 6.905746E-01 + 6.999996E+00 9.000000E+01 4 1.062390E+03 8.578819E+01 7.802592E+01 1.059521E+03 + 6.999996E+00 9.000000E+01 5 2.561845E-04 -8.876540E+01 5.519805E-06 -2.561250E-04 + 6.999996E+00 9.000000E+01 6 2.709863E-04 1.765605E+02 -2.704981E-04 1.625756E-05 + 7.099996E+00 0.000000E+00 1 6.902799E+01 8.016754E+01 1.178775E+01 6.801406E+01 + 7.099996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.099996E+00 0.000000E+00 3 7.818867E+00 1.781913E+02 -7.814971E+00 2.467834E-01 + 7.099996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.099996E+00 0.000000E+00 5 4.683553E+02 -9.844705E+01 -6.879926E+01 -4.632746E+02 + 7.099996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.099996E+00 3.000000E+01 1 7.421140E+01 8.508284E+01 6.361053E+00 7.393828E+01 + 7.099996E+00 3.000000E+01 2 3.464056E+01 9.017688E+01 -1.069370E-01 3.464040E+01 + 7.099996E+00 3.000000E+01 3 9.228217E+00 1.763761E+02 -9.209764E+00 5.832899E-01 + 7.099996E+00 3.000000E+01 4 1.463782E+02 9.037870E+01 -9.674802E-01 1.463750E+02 + 7.099996E+00 3.000000E+01 5 3.822705E+02 -9.588326E+01 -3.918346E+01 -3.802570E+02 + 7.099996E+00 3.000000E+01 6 1.197489E+03 -8.083371E+00 1.185591E+03 -1.683836E+02 + 7.099996E+00 6.000000E+01 1 7.624609E+01 9.134110E+01 -1.784504E+00 7.622520E+01 + 7.099996E+00 6.000000E+01 2 1.272887E+02 8.658373E+01 7.585104E+00 1.270625E+02 + 7.099996E+00 6.000000E+01 3 7.452615E+00 1.744976E+02 -7.418275E+00 7.146100E-01 + 7.099996E+00 6.000000E+01 4 6.323093E+02 8.653707E+01 3.819326E+01 6.311547E+02 + 7.099996E+00 6.000000E+01 5 2.420005E+02 -8.839009E+01 6.798873E+00 -2.419050E+02 + 7.099996E+00 6.000000E+01 6 2.318564E+03 -5.801970E+00 2.306687E+03 -2.343848E+02 + 7.099996E+00 9.000000E+01 1 1.076766E-05 -8.788194E+01 3.979592E-07 -1.076031E-05 + 7.099996E+00 9.000000E+01 2 2.064532E+02 8.573586E+01 1.535073E+01 2.058817E+02 + 7.099996E+00 9.000000E+01 3 3.737227E+00 1.734104E+02 -3.712537E+00 4.288726E-01 + 7.099996E+00 9.000000E+01 4 1.053439E+03 8.576096E+01 7.786783E+01 1.050557E+03 + 7.099996E+00 9.000000E+01 5 2.571575E-04 -8.896078E+01 4.663993E-06 -2.571152E-04 + 7.099996E+00 9.000000E+01 6 2.584371E-04 1.768035E+02 -2.580350E-04 1.441059E-05 + 7.199996E+00 0.000000E+00 1 7.421930E+01 8.171126E+01 1.069959E+01 7.344402E+01 + 7.199996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.199996E+00 0.000000E+00 3 7.150705E+00 1.781928E+02 -7.147148E+00 2.255081E-01 + 7.199996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.199996E+00 0.000000E+00 5 4.419293E+02 -9.717999E+01 -5.523533E+01 -4.384639E+02 + 7.199996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.199996E+00 3.000000E+01 1 7.883245E+01 8.585766E+01 5.694427E+00 7.862652E+01 + 7.199996E+00 3.000000E+01 2 3.776899E+01 8.919318E+01 5.318334E-01 3.776524E+01 + 7.199996E+00 3.000000E+01 3 8.068378E+00 1.768814E+02 -8.056430E+00 4.389446E-01 + 7.199996E+00 3.000000E+01 4 1.595447E+02 8.919025E+01 2.254713E+00 1.595288E+02 + 7.199996E+00 3.000000E+01 5 3.581570E+02 -9.496335E+01 -3.098722E+01 -3.568139E+02 + 7.199996E+00 3.000000E+01 6 1.220220E+03 -7.230842E+00 1.210516E+03 -1.535857E+02 + 7.199996E+00 6.000000E+01 1 7.712525E+01 9.125092E+01 -1.683711E+00 7.710687E+01 + 7.199996E+00 6.000000E+01 2 1.301200E+02 8.641229E+01 8.142446E+00 1.298650E+02 + 7.199996E+00 6.000000E+01 3 5.329028E+00 1.749167E+02 -5.308068E+00 4.721779E-01 + 7.199996E+00 6.000000E+01 4 6.409879E+02 8.636476E+01 4.064141E+01 6.396981E+02 + 7.199996E+00 6.000000E+01 5 2.198767E+02 -8.845608E+01 5.924181E+00 -2.197969E+02 + 7.199996E+00 6.000000E+01 6 2.247585E+03 -5.359552E+00 2.237759E+03 -2.099368E+02 + 7.199996E+00 9.000000E+01 1 1.056503E-05 -8.758630E+01 4.449422E-07 -1.055565E-05 + 7.199996E+00 9.000000E+01 2 2.059109E+02 8.570915E+01 1.540616E+01 2.053338E+02 + 7.199996E+00 9.000000E+01 3 1.192611E+00 1.686046E+02 -1.169101E+00 2.356335E-01 + 7.199996E+00 9.000000E+01 4 1.043784E+03 8.574621E+01 7.742220E+01 1.040909E+03 + 7.199996E+00 9.000000E+01 5 2.579798E-04 -8.914448E+01 3.851947E-06 -2.579511E-04 + 7.199996E+00 9.000000E+01 6 2.465296E-04 1.770352E+02 -2.461996E-04 1.275104E-05 + 7.299995E+00 0.000000E+00 1 7.900702E+01 8.299664E+01 9.633142E+00 7.841755E+01 + 7.299995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.299995E+00 0.000000E+00 3 6.303385E+00 1.782814E+02 -6.300550E+00 1.890387E-01 + 7.299995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.299995E+00 0.000000E+00 5 4.132928E+02 -9.610378E+01 -4.394532E+01 -4.109499E+02 + 7.299995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.299995E+00 3.000000E+01 1 8.297503E+01 8.649887E+01 5.067137E+00 8.282017E+01 + 7.299995E+00 3.000000E+01 2 4.070684E+01 8.846386E+01 1.091247E+00 4.069221E+01 + 7.299995E+00 3.000000E+01 3 6.739426E+00 1.773851E+02 -6.732409E+00 3.074704E-01 + 7.299995E+00 3.000000E+01 4 1.718642E+02 8.832094E+01 5.035780E+00 1.717904E+02 + 7.299995E+00 3.000000E+01 5 3.322572E+02 -9.420104E+01 -2.433993E+01 -3.313644E+02 + 7.299995E+00 3.000000E+01 6 1.234887E+03 -6.484753E+00 1.226986E+03 -1.394666E+02 + 7.299995E+00 6.000000E+01 1 7.782559E+01 9.114442E+01 -1.554368E+00 7.781007E+01 + 7.299995E+00 6.000000E+01 2 1.325970E+02 8.628230E+01 8.597677E+00 1.323180E+02 + 7.299995E+00 6.000000E+01 3 3.099323E+00 1.747380E+02 -3.086262E+00 2.842379E-01 + 7.299995E+00 6.000000E+01 4 6.480093E+02 8.623495E+01 4.255168E+01 6.466107E+02 + 7.299995E+00 6.000000E+01 5 1.979331E+02 -8.855743E+01 4.982943E+00 -1.978704E+02 + 7.299995E+00 6.000000E+01 6 2.176386E+03 -4.941000E+00 2.168298E+03 -1.874518E+02 + 7.299995E+00 9.000000E+01 1 1.036275E-05 -8.735548E+01 4.781286E-07 -1.035171E-05 + 7.299995E+00 9.000000E+01 2 2.052295E+02 8.569668E+01 1.539971E+01 2.046509E+02 + 7.299995E+00 9.000000E+01 3 1.438498E+00 4.225457E+00 1.434588E+00 1.059904E-01 + 7.299995E+00 9.000000E+01 4 1.033485E+03 8.574448E+01 7.668940E+01 1.030635E+03 + 7.299995E+00 9.000000E+01 5 2.586495E-04 -8.931433E+01 3.095230E-06 -2.586310E-04 + 7.299995E+00 9.000000E+01 6 2.352377E-04 1.772550E+02 -2.349678E-04 1.126597E-05 + 7.399995E+00 0.000000E+00 1 8.340108E+01 8.406290E+01 8.626729E+00 8.295373E+01 + 7.399995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.399995E+00 0.000000E+00 3 5.281970E+00 1.784444E+02 -5.280023E+00 1.433921E-01 + 7.399995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.399995E+00 0.000000E+00 5 3.830153E+02 -9.519530E+01 -3.468234E+01 -3.814418E+02 + 7.399995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.399995E+00 3.000000E+01 1 8.667696E+01 8.702539E+01 4.497969E+00 8.656017E+01 + 7.399995E+00 3.000000E+01 2 4.344891E+01 8.792039E+01 1.576675E+00 4.342029E+01 + 7.399995E+00 3.000000E+01 3 5.253987E+00 1.779033E+02 -5.250469E+00 1.922214E-01 + 7.399995E+00 3.000000E+01 4 1.832959E+02 8.768266E+01 7.411419E+00 1.831460E+02 + 7.399995E+00 3.000000E+01 5 3.050693E+02 -9.357434E+01 -1.901909E+01 -3.044759E+02 + 7.399995E+00 3.000000E+01 6 1.242579E+03 -5.827247E+00 1.236158E+03 -1.261583E+02 + 7.399995E+00 6.000000E+01 1 7.837060E+01 9.102612E+01 -1.403471E+00 7.835803E+01 + 7.399995E+00 6.000000E+01 2 1.347433E+02 8.618854E+01 8.956859E+00 1.344453E+02 + 7.399995E+00 6.000000E+01 3 7.860215E-01 1.691552E+02 -7.719834E-01 1.478894E-01 + 7.399995E+00 6.000000E+01 4 6.535016E+02 8.614218E+01 4.396807E+01 6.520209E+02 + 7.399995E+00 6.000000E+01 5 1.762595E+02 -8.868392E+01 4.048314E+00 -1.762130E+02 + 7.399995E+00 6.000000E+01 6 2.105494E+03 -4.547356E+00 2.098867E+03 -1.669300E+02 + 7.399995E+00 9.000000E+01 1 1.016247E-05 -8.718291E+01 4.994621E-07 -1.015019E-05 + 7.399995E+00 9.000000E+01 2 2.044150E+02 8.569868E+01 1.533145E+01 2.038392E+02 + 7.399995E+00 9.000000E+01 3 4.082258E+00 4.759538E-01 4.082117E+00 3.391077E-02 + 7.399995E+00 9.000000E+01 4 1.022605E+03 8.575587E+01 7.567914E+01 1.019801E+03 + 7.399995E+00 9.000000E+01 5 2.591698E-04 -8.946914E+01 2.401235E-06 -2.591586E-04 + 7.399995E+00 9.000000E+01 6 2.245352E-04 1.774623E+02 -2.243150E-04 9.941742E-06 + 7.499995E+00 0.000000E+00 1 8.742158E+01 8.494504E+01 7.702832E+00 8.708157E+01 + 7.499995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.499995E+00 0.000000E+00 3 4.095227E+00 1.786794E+02 -4.094140E+00 9.438183E-02 + 7.499995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.499995E+00 0.000000E+00 5 3.515769E+02 -9.443193E+01 -2.716799E+01 -3.505256E+02 + 7.499995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.499995E+00 3.000000E+01 1 8.997755E+01 8.745473E+01 3.995785E+00 8.988879E+01 + 7.499995E+00 3.000000E+01 2 4.599360E+01 8.751589E+01 1.993469E+00 4.595038E+01 + 7.499995E+00 3.000000E+01 3 3.625280E+00 1.784841E+02 -3.624011E+00 9.590188E-02 + 7.499995E+00 3.000000E+01 4 1.938288E+02 8.721533E+01 9.416683E+00 1.935999E+02 + 7.499995E+00 3.000000E+01 5 2.769919E+02 -9.306342E+01 -1.480279E+01 -2.765961E+02 + 7.499995E+00 3.000000E+01 6 1.244277E+03 -5.244829E+00 1.239067E+03 -1.137415E+02 + 7.499995E+00 6.000000E+01 1 7.877998E+01 9.090032E+01 -1.237872E+00 7.877025E+01 + 7.499995E+00 6.000000E+01 2 1.365795E+02 8.612640E+01 9.226720E+00 1.362675E+02 + 7.499995E+00 6.000000E+01 3 1.619560E+00 2.104268E+00 1.618468E+00 5.946723E-02 + 7.499995E+00 6.000000E+01 4 6.575726E+02 8.608166E+01 4.493509E+01 6.560355E+02 + 7.499995E+00 6.000000E+01 5 1.549301E+02 -8.882681E+01 3.172145E+00 -1.548976E+02 + 7.499995E+00 6.000000E+01 6 2.035356E+03 -4.178991E+00 2.029945E+03 -1.483215E+02 + 7.499995E+00 9.000000E+01 1 9.965480E-06 -8.706212E+01 5.107633E-07 -9.952382E-06 + 7.499995E+00 9.000000E+01 2 2.034739E+02 8.571490E+01 1.520344E+01 2.029051E+02 + 7.499995E+00 9.000000E+01 3 6.759169E+00 1.113236E-01 6.759156E+00 1.313281E-02 + 7.499995E+00 9.000000E+01 4 1.011207E+03 8.578003E+01 7.441042E+01 1.008466E+03 + 7.499995E+00 9.000000E+01 5 2.595411E-04 -8.960838E+01 1.773960E-06 -2.595350E-04 + 7.499995E+00 9.000000E+01 6 2.143955E-04 1.776571E+02 -2.142163E-04 8.764559E-06 + 7.599995E+00 0.000000E+00 1 9.108731E+01 8.567310E+01 6.872245E+00 9.082770E+01 + 7.599995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.599995E+00 0.000000E+00 3 2.753061E+00 1.790195E+02 -2.752658E+00 4.711146E-02 + 7.599995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.599995E+00 0.000000E+00 5 3.193669E+02 -9.379190E+01 -2.112063E+01 -3.186677E+02 + 7.599995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.599995E+00 3.000000E+01 1 9.291185E+01 8.780254E+01 3.562552E+00 9.284352E+01 + 7.599995E+00 3.000000E+01 2 4.834269E+01 8.721734E+01 2.346922E+00 4.828569E+01 + 7.599995E+00 3.000000E+01 3 1.866945E+00 1.793741E+02 -1.866833E+00 2.039605E-02 + 7.599995E+00 3.000000E+01 4 2.034649E+02 8.687680E+01 1.108542E+01 2.031627E+02 + 7.599995E+00 3.000000E+01 5 2.483542E+02 -9.264957E+01 -1.148071E+01 -2.480887E+02 + 7.599995E+00 3.000000E+01 6 1.240875E+03 -4.726879E+00 1.236654E+03 -1.022556E+02 + 7.599995E+00 6.000000E+01 1 7.907039E+01 9.077093E+01 -1.063876E+00 7.906323E+01 + 7.599995E+00 6.000000E+01 2 1.381267E+02 8.609180E+01 9.414437E+00 1.378055E+02 + 7.599995E+00 6.000000E+01 3 4.069374E+00 2.072948E-01 4.069347E+00 1.472287E-02 + 7.599995E+00 6.000000E+01 4 6.603373E+02 8.604908E+01 4.549854E+01 6.587679E+02 + 7.599995E+00 6.000000E+01 5 1.340043E+02 -8.897920E+01 2.387324E+00 -1.339831E+02 + 7.599995E+00 6.000000E+01 6 1.966332E+03 -3.835799E+00 1.961927E+03 -1.315424E+02 + 7.599995E+00 9.000000E+01 1 9.772629E-06 -8.698692E+01 5.136886E-07 -9.759118E-06 + 7.599995E+00 9.000000E+01 2 2.024144E+02 8.574466E+01 1.501944E+01 2.018564E+02 + 7.599995E+00 9.000000E+01 3 9.453634E+00 2.233773E-01 9.453563E+00 3.685650E-02 + 7.599995E+00 9.000000E+01 4 9.993538E+02 8.581632E+01 7.290702E+01 9.966908E+02 + 7.599995E+00 9.000000E+01 5 2.597687E-04 -8.973209E+01 1.214688E-06 -2.597658E-04 + 7.599995E+00 9.000000E+01 6 2.047929E-04 1.778394E+02 -2.046473E-04 7.720900E-06 + 7.699995E+00 0.000000E+00 1 9.442255E+01 8.627306E+01 6.137610E+00 9.422286E+01 + 7.699995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.699995E+00 0.000000E+00 3 1.266463E+00 1.797298E+02 -1.266448E+00 5.973011E-03 + 7.699995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.699995E+00 0.000000E+00 5 2.866823E+02 -9.325626E+01 -1.628411E+01 -2.862195E+02 + 7.699995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.699995E+00 3.000000E+01 1 9.551472E+01 8.808272E+01 3.195601E+00 9.546125E+01 + 7.699995E+00 3.000000E+01 2 5.050034E+01 8.700081E+01 2.642276E+00 5.043117E+01 + 7.699995E+00 3.000000E+01 3 3.403573E-02 -7.708894E+01 7.604886E-03 -3.317524E-02 + 7.699995E+00 3.000000E+01 4 2.122245E+02 8.663680E+01 1.245017E+01 2.118590E+02 + 7.699995E+00 3.000000E+01 5 2.194090E+02 -9.231698E+01 -8.870259E+00 -2.192297E+02 + 7.699995E+00 3.000000E+01 6 1.233160E+03 -4.264926E+00 1.229745E+03 -9.170797E+01 + 7.699995E+00 6.000000E+01 1 7.925520E+01 9.064118E+01 -8.868990E-01 7.925024E+01 + 7.699995E+00 6.000000E+01 2 1.394051E+02 8.608114E+01 9.527458E+00 1.390791E+02 + 7.699995E+00 6.000000E+01 3 6.567874E+00 7.875823E-02 6.567868E+00 9.028135E-03 + 7.699995E+00 6.000000E+01 4 6.618986E+02 8.604070E+01 4.570275E+01 6.603188E+02 + 7.699995E+00 6.000000E+01 5 1.135088E+02 -8.913577E+01 1.712074E+00 -1.134959E+02 + 7.699995E+00 6.000000E+01 6 1.898716E+03 -3.517265E+00 1.895140E+03 -1.164849E+02 + 7.699995E+00 9.000000E+01 1 9.584668E-06 -8.695145E+01 5.097324E-07 -9.571104E-06 + 7.699995E+00 9.000000E+01 2 2.012424E+02 8.578704E+01 1.478404E+01 2.006986E+02 + 7.699995E+00 9.000000E+01 3 1.215646E+01 4.643328E-01 1.215606E+01 9.851649E-02 + 7.699995E+00 9.000000E+01 4 9.870933E+02 8.586389E+01 7.119507E+01 9.845224E+02 + 7.699995E+00 9.000000E+01 5 2.598501E-04 -8.984074E+01 7.222630E-07 -2.598492E-04 + 7.699995E+00 9.000000E+01 6 1.957017E-04 1.780094E+02 -1.955836E-04 6.797717E-06 + 7.799995E+00 0.000000E+00 1 9.744762E+01 8.676672E+01 5.496192E+00 9.729250E+01 + 7.799995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.799995E+00 0.000000E+00 3 3.533028E-01 -4.133177E+00 3.523839E-01 -2.546430E-02 + 7.799995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.799995E+00 0.000000E+00 5 2.537789E+02 -9.280707E+01 -1.242832E+01 -2.534744E+02 + 7.799995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.799995E+00 3.000000E+01 1 9.781522E+01 8.830712E+01 2.889658E+00 9.777252E+01 + 7.799995E+00 3.000000E+01 2 5.247171E+01 8.684859E+01 2.884618E+00 5.239236E+01 + 7.799995E+00 3.000000E+01 3 1.986412E+00 -1.854771E+00 1.985371E+00 -6.429262E-02 + 7.799995E+00 3.000000E+01 4 2.201274E+02 8.647298E+01 1.354209E+01 2.197104E+02 + 7.799995E+00 3.000000E+01 5 1.903563E+02 -9.205275E+01 -6.818476E+00 -1.902341E+02 + 7.799995E+00 3.000000E+01 6 1.221833E+03 -3.851990E+00 1.219072E+03 -8.208183E+01 + 7.799995E+00 6.000000E+01 1 7.934649E+01 9.051372E+01 -7.114094E-01 7.934330E+01 + 7.799995E+00 6.000000E+01 2 1.404336E+02 8.609111E+01 9.573378E+00 1.401069E+02 + 7.799995E+00 6.000000E+01 3 9.102118E+00 2.380052E-01 9.102040E+00 3.780986E-02 + 7.799995E+00 6.000000E+01 4 6.623581E+02 8.605309E+01 4.559156E+01 6.607872E+02 + 7.799995E+00 6.000000E+01 5 9.347800E+01 -8.929327E+01 1.153013E+00 -9.347089E+01 + 7.799995E+00 6.000000E+01 6 1.832736E+03 -3.222579E+00 1.829838E+03 -1.030272E+02 + 7.799995E+00 9.000000E+01 1 9.401953E-06 -8.695017E+01 5.002249E-07 -9.388636E-06 + 7.799995E+00 9.000000E+01 2 1.999665E+02 8.584091E+01 1.450279E+01 1.994399E+02 + 7.799995E+00 9.000000E+01 3 1.485886E+01 7.400206E-01 1.485762E+01 1.919087E-01 + 7.799995E+00 9.000000E+01 4 9.744837E+02 8.592172E+01 6.930460E+01 9.720161E+02 + 7.799995E+00 9.000000E+01 5 2.597919E-04 -8.993514E+01 2.940749E-07 -2.597917E-04 + 7.799995E+00 9.000000E+01 6 1.870968E-04 1.781676E+02 -1.870011E-04 5.982688E-06 + 7.899995E+00 0.000000E+00 1 1.001835E+02 8.717259E+01 4.941816E+00 1.000616E+02 + 7.899995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.899995E+00 0.000000E+00 3 2.091449E+00 -1.222346E+00 2.090973E+00 -4.461550E-02 + 7.899995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.899995E+00 0.000000E+00 5 2.208600E+02 -9.242885E+01 -9.359738E+00 -2.206615E+02 + 7.899995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.899995E+00 3.000000E+01 1 9.984132E+01 8.848597E+01 2.637978E+00 9.980646E+01 + 7.899995E+00 3.000000E+01 2 5.426383E+01 8.674731E+01 3.078921E+00 5.417641E+01 + 7.899995E+00 3.000000E+01 3 4.054196E+00 -1.035074E+00 4.053535E+00 -7.323688E-02 + 7.899995E+00 3.000000E+01 4 2.272098E+02 8.636868E+01 1.439062E+01 2.267536E+02 + 7.899995E+00 3.000000E+01 5 1.613735E+02 -9.184579E+01 -5.197766E+00 -1.612898E+02 + 7.899995E+00 3.000000E+01 6 1.207513E+03 -3.482229E+00 1.205284E+03 -7.334307E+01 + 7.899995E+00 6.000000E+01 1 7.935417E+01 9.039056E+01 -5.409049E-01 7.935233E+01 + 7.899995E+00 6.000000E+01 2 1.412311E+02 8.611877E+01 9.559717E+00 1.409072E+02 + 7.899995E+00 6.000000E+01 3 1.166198E+01 4.730663E-01 1.166158E+01 9.628679E-02 + 7.899995E+00 6.000000E+01 4 6.618198E+02 8.608330E+01 4.520630E+01 6.602740E+02 + 7.899995E+00 6.000000E+01 5 7.393465E+01 -8.944995E+01 7.097710E-01 -7.393124E+01 + 7.899995E+00 6.000000E+01 6 1.768568E+03 -2.950732E+00 1.766223E+03 -9.104096E+01 + 7.899995E+00 9.000000E+01 1 9.224881E-06 -8.697808E+01 4.863176E-07 -9.212054E-06 + 7.899995E+00 9.000000E+01 2 1.985938E+02 8.590507E+01 1.418145E+01 1.980869E+02 + 7.899995E+00 9.000000E+01 3 1.755438E+01 1.015346E+00 1.755162E+01 3.110671E-01 + 7.899995E+00 9.000000E+01 4 9.615761E+02 8.598869E+01 6.726544E+01 9.592205E+02 + 7.899995E+00 9.000000E+01 5 2.595977E-04 -9.001629E+01 -7.377717E-08 -2.595977E-04 + 7.899995E+00 9.000000E+01 6 1.789530E-04 1.783143E+02 -1.788755E-04 5.264333E-06 + 7.999995E+00 0.000000E+00 1 1.026511E+02 8.750613E+01 4.466602E+00 1.025539E+02 + 7.999995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.999995E+00 0.000000E+00 3 3.937476E+00 -7.238156E-01 3.937161E+00 -4.974067E-02 + 7.999995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.999995E+00 0.000000E+00 5 1.880801E+02 -9.210726E+01 -6.915757E+00 -1.879529E+02 + 7.999995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 7.999995E+00 3.000000E+01 1 1.016173E+02 8.862783E+01 2.433381E+00 1.015881E+02 + 7.999995E+00 3.000000E+01 2 5.588414E+01 8.668661E+01 3.229963E+00 5.579073E+01 + 7.999995E+00 3.000000E+01 3 6.199816E+00 -5.616584E-01 6.199518E+00 -6.077451E-02 + 7.999995E+00 3.000000E+01 4 2.335099E+02 8.631115E+01 1.502359E+01 2.330261E+02 + 7.999995E+00 3.000000E+01 5 1.325916E+02 -9.168777E+01 -3.905201E+00 -1.325341E+02 + 7.999995E+00 3.000000E+01 6 1.190741E+03 -3.150677E+00 1.188941E+03 -6.544550E+01 + 7.999995E+00 6.000000E+01 1 7.928681E+01 9.027322E+01 -3.780780E-01 7.928591E+01 + 7.999995E+00 6.000000E+01 2 1.418152E+02 8.616150E+01 9.493734E+00 1.414971E+02 + 7.999995E+00 6.000000E+01 3 1.423871E+01 7.244696E-01 1.423757E+01 1.800348E-01 + 7.999995E+00 6.000000E+01 4 6.603688E+02 8.612856E+01 4.458681E+01 6.588619E+02 + 7.999995E+00 6.000000E+01 5 5.490401E+01 -8.960667E+01 3.769139E-01 -5.490271E+01 + 7.999995E+00 6.000000E+01 6 1.706345E+03 -2.700556E+00 1.704450E+03 -8.039639E+01 + 7.999995E+00 9.000000E+01 1 9.053556E-06 -8.703043E+01 4.690244E-07 -9.041399E-06 + 7.999995E+00 9.000000E+01 2 1.971333E+02 8.597823E+01 1.382605E+01 1.966479E+02 + 7.999995E+00 9.000000E+01 3 2.023759E+01 1.275899E+00 2.023257E+01 4.506261E-01 + 7.999995E+00 9.000000E+01 4 9.484269E+02 8.606368E+01 6.510731E+01 9.461896E+02 + 7.999995E+00 9.000000E+01 5 2.592711E-04 -9.008528E+01 -3.859052E-07 -2.592708E-04 + 7.999995E+00 9.000000E+01 6 1.712471E-04 1.784500E+02 -1.711845E-04 4.632054E-06 + 8.099995E+00 0.000000E+00 1 1.048676E+02 8.778030E+01 4.061672E+00 1.047889E+02 + 8.099995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.099995E+00 0.000000E+00 3 5.878958E+00 -3.878740E-01 5.878823E+00 -3.979835E-02 + 8.099995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.099995E+00 0.000000E+00 5 1.555692E+02 -9.182758E+01 -4.961399E+00 -1.554901E+02 + 8.099995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.099995E+00 3.000000E+01 1 1.031647E+02 8.873989E+01 2.268725E+00 1.031398E+02 + 8.099995E+00 3.000000E+01 2 5.734096E+01 8.665842E+01 3.342315E+00 5.724347E+01 + 8.099995E+00 3.000000E+01 3 8.412326E+00 -1.913998E-01 8.412279E+00 -2.810179E-02 + 8.099995E+00 3.000000E+01 4 2.390619E+02 8.629047E+01 1.546689E+01 2.385610E+02 + 8.099995E+00 3.000000E+01 5 1.041119E+02 -9.157516E+01 -2.861869E+00 -1.040726E+02 + 8.099995E+00 3.000000E+01 6 1.171987E+03 -2.853062E+00 1.170535E+03 -5.833537E+01 + 8.099995E+00 6.000000E+01 1 7.915191E+01 9.016277E+01 -2.248562E-01 7.915159E+01 + 8.099995E+00 6.000000E+01 2 1.422033E+02 8.621691E+01 9.382489E+00 1.418934E+02 + 8.099995E+00 6.000000E+01 3 1.682552E+01 9.696588E-01 1.682311E+01 2.847371E-01 + 8.099995E+00 6.000000E+01 4 6.580927E+02 8.618642E+01 4.376996E+01 6.566354E+02 + 8.099995E+00 6.000000E+01 5 3.638227E+01 -8.977335E+01 1.439245E-01 -3.638198E+01 + 8.099995E+00 6.000000E+01 6 1.646148E+03 -2.470806E+00 1.644618E+03 -7.096602E+01 + 8.099995E+00 9.000000E+01 1 8.888026E-06 -8.710305E+01 4.491992E-07 -8.876667E-06 + 8.099995E+00 9.000000E+01 2 1.955928E+02 8.605914E+01 1.344249E+01 1.951303E+02 + 8.099995E+00 9.000000E+01 3 2.290479E+01 1.515339E+00 2.289677E+01 6.057073E-01 + 8.099995E+00 9.000000E+01 4 9.350745E+02 8.614549E+01 6.285859E+01 9.329593E+02 + 8.099995E+00 9.000000E+01 5 2.588207E-04 -9.014330E+01 -6.473321E-07 -2.588199E-04 + 8.099995E+00 9.000000E+01 6 1.639552E-04 1.785754E+02 -1.639046E-04 4.076145E-06 + 8.199995E+00 0.000000E+00 1 1.068520E+02 8.800578E+01 3.718322E+00 1.067873E+02 + 8.199995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.199995E+00 0.000000E+00 3 7.902928E+00 -1.063022E-01 7.902915E+00 -1.466247E-02 + 8.199995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.199995E+00 0.000000E+00 5 1.234563E+02 -9.157329E+01 -3.389571E+00 -1.234097E+02 + 8.199995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.199995E+00 3.000000E+01 1 1.045033E+02 8.882807E+01 2.137357E+00 1.044814E+02 + 8.199995E+00 3.000000E+01 2 5.864267E+01 8.665630E+01 3.420366E+00 5.854284E+01 + 8.199995E+00 3.000000E+01 3 1.068015E+01 1.240289E-01 1.068013E+01 2.311945E-02 + 8.199995E+00 3.000000E+01 4 2.439129E+02 8.629896E+01 1.574469E+01 2.434042E+02 + 8.199995E+00 3.000000E+01 5 7.604199E+01 -9.151055E+01 -2.004550E+00 -7.601556E+01 + 8.199995E+00 3.000000E+01 6 1.151663E+03 -2.585664E+00 1.150490E+03 -5.195500E+01 + 8.199995E+00 6.000000E+01 1 7.895687E+01 9.005986E+01 -8.249161E-02 7.895683E+01 + 8.199995E+00 6.000000E+01 2 1.424118E+02 8.628288E+01 9.232624E+00 1.421122E+02 + 8.199995E+00 6.000000E+01 3 1.941458E+01 1.199059E+00 1.941032E+01 4.062694E-01 + 8.199995E+00 6.000000E+01 4 6.550826E+02 8.625477E+01 4.279003E+01 6.536836E+02 + 8.199995E+00 6.000000E+01 5 1.840337E+01 -8.999612E+01 1.248352E-03 -1.840337E+01 + 8.199995E+00 6.000000E+01 6 1.588037E+03 -2.260185E+00 1.586802E+03 -6.262812E+01 + 8.199995E+00 9.000000E+01 1 8.728281E-06 -8.719205E+01 4.275842E-07 -8.717801E-06 + 8.199995E+00 9.000000E+01 2 1.939802E+02 8.614654E+01 1.303642E+01 1.935417E+02 + 8.199995E+00 9.000000E+01 3 2.555106E+01 1.731206E+00 2.553940E+01 7.719142E-01 + 8.199995E+00 9.000000E+01 4 9.215750E+02 8.623306E+01 6.054570E+01 9.195839E+02 + 8.199995E+00 9.000000E+01 5 2.582526E-04 -9.019151E+01 -8.632314E-07 -2.582512E-04 + 8.199995E+00 9.000000E+01 6 1.570556E-04 1.786910E+02 -1.570146E-04 3.587820E-06 + 8.299995E+00 0.000000E+00 1 1.086188E+02 8.819144E+01 3.428026E+00 1.085647E+02 + 8.299995E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.299995E+00 0.000000E+00 3 9.999021E+00 1.456736E-01 9.998988E+00 2.542233E-02 + 8.299995E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.299995E+00 0.000000E+00 5 9.182286E+01 -9.132073E+01 -2.116430E+00 -9.179847E+01 + 8.299995E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.299995E+00 3.000000E+01 1 1.056509E+02 8.889730E+01 2.033197E+00 1.056313E+02 + 8.299995E+00 3.000000E+01 2 5.979816E+01 8.667507E+01 3.468193E+00 5.969751E+01 + 8.299995E+00 3.000000E+01 3 1.299342E+01 4.014685E-01 1.299310E+01 9.104348E-02 + 8.299995E+00 3.000000E+01 4 2.481039E+02 8.633039E+01 1.587941E+01 2.475952E+02 + 8.299995E+00 3.000000E+01 5 4.845108E+01 -9.152054E+01 -1.285665E+00 -4.843402E+01 + 8.299995E+00 3.000000E+01 6 1.130121E+03 -2.345234E+00 1.129175E+03 -4.624528E+01 + 8.299995E+00 6.000000E+01 1 7.870705E+01 8.996489E+01 4.823263E-02 7.870704E+01 + 8.299995E+00 6.000000E+01 2 1.424557E+02 8.635747E+01 9.050406E+00 1.421679E+02 + 8.299995E+00 6.000000E+01 3 2.200033E+01 1.409368E+00 2.199367E+01 5.411121E-01 + 8.299995E+00 6.000000E+01 4 6.514143E+02 8.633164E+01 4.167820E+01 6.500797E+02 + 8.299995E+00 6.000000E+01 5 9.643353E-01 -9.382101E+01 -6.426318E-02 -9.621917E-01 + 8.299995E+00 6.000000E+01 6 1.532040E+03 -2.067390E+00 1.531042E+03 -5.526822E+01 + 8.299995E+00 9.000000E+01 1 8.574210E-06 -8.729401E+01 4.047953E-07 -8.564650E-06 + 8.299995E+00 9.000000E+01 2 1.923042E+02 8.623924E+01 1.261333E+01 1.918901E+02 + 8.299995E+00 9.000000E+01 3 2.817375E+01 1.923349E+00 2.815788E+01 9.455803E-01 + 8.299995E+00 9.000000E+01 4 9.079691E+02 8.632528E+01 5.819356E+01 9.061024E+02 + 8.299995E+00 9.000000E+01 5 2.575735E-04 -9.023106E+01 -1.038740E-06 -2.575714E-04 + 8.299995E+00 9.000000E+01 6 1.505263E-04 1.787974E+02 -1.504932E-04 3.159157E-06 + 8.399996E+00 0.000000E+00 1 1.101842E+02 8.834463E+01 3.182974E+00 1.101382E+02 + 8.399996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.399996E+00 0.000000E+00 3 1.215627E+01 3.754811E-01 1.215601E+01 7.966411E-02 + 8.399996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.399996E+00 0.000000E+00 5 6.073744E+01 -9.101222E+01 -1.072971E+00 -6.072796E+01 + 8.399996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.399996E+00 3.000000E+01 1 1.066237E+02 8.895159E+01 1.950916E+00 1.066059E+02 + 8.399996E+00 3.000000E+01 2 6.081600E+01 8.671054E+01 3.489645E+00 6.071580E+01 + 8.399996E+00 3.000000E+01 3 1.534336E+01 6.485831E-01 1.534238E+01 1.736817E-01 + 8.399996E+00 3.000000E+01 4 2.516782E+02 8.637983E+01 1.589144E+01 2.511760E+02 + 8.399996E+00 3.000000E+01 5 2.139992E+01 -9.179913E+01 -6.718618E-01 -2.138937E+01 + 8.399996E+00 3.000000E+01 6 1.107667E+03 -2.128899E+00 1.106903E+03 -4.114735E+01 + 8.399996E+00 6.000000E+01 1 7.840784E+01 8.987799E+01 1.669732E-01 7.840767E+01 + 8.399996E+00 6.000000E+01 2 1.423499E+02 8.643902E+01 8.841481E+00 1.420750E+02 + 8.399996E+00 6.000000E+01 3 2.457878E+01 1.598849E+00 2.456922E+01 6.857862E-01 + 8.399996E+00 6.000000E+01 4 6.471569E+02 8.641531E+01 4.046268E+01 6.458907E+02 + 8.399996E+00 6.000000E+01 5 1.593196E+01 9.023058E+01 -6.411661E-02 1.593184E+01 + 8.399996E+00 6.000000E+01 6 1.478153E+03 -1.891146E+00 1.477348E+03 -4.878013E+01 + 8.399996E+00 9.000000E+01 1 8.425674E-06 -8.740590E+01 3.813477E-07 -8.417040E-06 + 8.399996E+00 9.000000E+01 2 1.905720E+02 8.633611E+01 1.217818E+01 1.901825E+02 + 8.399996E+00 9.000000E+01 3 3.077169E+01 2.092187E+00 3.075118E+01 1.123396E+00 + 8.399996E+00 9.000000E+01 4 8.942975E+02 8.642114E+01 5.582407E+01 8.925535E+02 + 8.399996E+00 9.000000E+01 5 2.567888E-04 -9.026302E+01 -1.178763E-06 -2.567861E-04 + 8.399996E+00 9.000000E+01 6 1.443470E-04 1.788952E+02 -1.443201E-04 2.783047E-06 + 8.499996E+00 0.000000E+00 1 1.115610E+02 8.847137E+01 2.976067E+00 1.115213E+02 + 8.499996E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.499996E+00 0.000000E+00 3 1.436424E+01 5.859408E-01 1.436349E+01 1.468947E-01 + 8.499996E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.499996E+00 0.000000E+00 5 3.026838E+01 -9.039252E+01 -2.073547E-01 -3.026767E+01 + 8.499996E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.499996E+00 3.000000E+01 1 1.074365E+02 8.899419E+01 1.885903E+00 1.074199E+02 + 8.499996E+00 3.000000E+01 2 6.170529E+01 8.675925E+01 3.488291E+00 6.160661E+01 + 8.499996E+00 3.000000E+01 3 1.772121E+01 8.693196E-01 1.771917E+01 2.688645E-01 + 8.499996E+00 3.000000E+01 4 2.546799E+02 8.644330E+01 1.579940E+01 2.541894E+02 + 8.499996E+00 3.000000E+01 5 5.062679E+00 9.151420E+01 -1.337793E-01 5.060912E+00 + 8.499996E+00 3.000000E+01 6 1.084562E+03 -1.934128E+00 1.083944E+03 -3.660450E+01 + 8.499996E+00 6.000000E+01 1 7.806481E+01 8.979910E+01 2.737343E-01 7.806433E+01 + 8.499996E+00 6.000000E+01 2 1.421089E+02 8.652599E+01 8.611196E+00 1.418477E+02 + 8.499996E+00 6.000000E+01 3 2.714522E+01 1.767649E+00 2.713231E+01 8.373327E-01 + 8.499996E+00 6.000000E+01 4 6.423845E+02 8.650430E+01 3.916857E+01 6.411893E+02 + 8.499996E+00 6.000000E+01 5 3.227318E+01 9.001779E+01 -1.001967E-02 3.227318E+01 + 8.499996E+00 6.000000E+01 6 1.426372E+03 -1.730191E+00 1.425722E+03 -4.306636E+01 + 8.499996E+00 9.000000E+01 1 1.042746E-05 -8.652386E+01 6.322487E-07 -1.040828E-05 + 8.499996E+00 9.000000E+01 2 1.887924E+02 8.643615E+01 1.173549E+01 1.884273E+02 + 8.499996E+00 9.000000E+01 3 3.334180E+01 2.238865E+00 3.331635E+01 1.302519E+00 + 8.499996E+00 9.000000E+01 4 8.806016E+02 8.651970E+01 5.345721E+01 8.789775E+02 + 8.499996E+00 9.000000E+01 5 3.221859E-04 -8.928722E+01 4.007965E-06 -3.221609E-04 + 8.499996E+00 9.000000E+01 6 1.384979E-04 1.789851E+02 -1.384762E-04 2.453158E-06 + 8.599997E+00 0.000000E+00 1 1.127633E+02 8.857661E+01 2.801085E+00 1.127285E+02 + 8.599997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.599997E+00 0.000000E+00 3 1.661392E+01 7.786490E-01 1.661238E+01 2.257760E-01 + 8.599997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.599997E+00 0.000000E+00 5 7.083997E-01 -4.257503E+01 5.216599E-01 -4.792714E-01 + 8.599997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.599997E+00 3.000000E+01 1 1.081019E+02 8.902776E+01 1.834273E+00 1.080864E+02 + 8.599997E+00 3.000000E+01 2 6.247464E+01 8.681840E+01 3.467401E+00 6.237835E+01 + 8.599997E+00 3.000000E+01 3 2.011938E+01 1.066583E+00 2.011590E+01 3.745086E-01 + 8.599997E+00 3.000000E+01 4 2.571511E+02 8.651755E+01 1.562009E+01 2.566763E+02 + 8.599997E+00 3.000000E+01 5 3.088075E+01 8.935660E+01 3.467661E-01 3.087881E+01 + 8.599997E+00 3.000000E+01 6 1.061029E+03 -1.758672E+00 1.060529E+03 -3.256275E+01 + 8.599997E+00 6.000000E+01 1 7.768225E+01 8.972802E+01 3.687541E-01 7.768137E+01 + 8.599997E+00 6.000000E+01 2 1.417454E+02 8.661707E+01 8.364246E+00 1.414984E+02 + 8.599997E+00 6.000000E+01 3 2.969547E+01 1.916534E+00 2.967886E+01 9.931231E-01 + 8.599997E+00 6.000000E+01 4 6.371637E+02 8.659726E+01 3.781829E+01 6.360403E+02 + 8.599997E+00 6.000000E+01 5 4.805872E+01 8.989476E+01 8.827934E-02 4.805864E+01 + 8.599997E+00 6.000000E+01 6 1.376663E+03 -1.583330E+00 1.376137E+03 -3.803830E+01 + 8.599997E+00 9.000000E+01 1 1.023129E-05 -8.663912E+01 5.998070E-07 -1.021369E-05 + 8.599997E+00 9.000000E+01 2 1.869718E+02 8.653838E+01 1.128936E+01 1.866306E+02 + 8.599997E+00 9.000000E+01 3 3.588227E+01 2.364943E+00 3.585170E+01 1.480657E+00 + 8.599997E+00 9.000000E+01 4 8.669142E+02 8.662012E+01 5.110961E+01 8.654063E+02 + 8.599997E+00 9.000000E+01 5 3.202662E-04 -8.929819E+01 3.922801E-06 -3.202422E-04 + 8.599997E+00 9.000000E+01 6 1.329601E-04 1.790675E+02 -1.329425E-04 2.163852E-06 + 8.699997E+00 0.000000E+00 1 1.138037E+02 8.866444E+01 2.652522E+00 1.137728E+02 + 8.699997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.699997E+00 0.000000E+00 3 1.889723E+01 9.544963E-01 1.889460E+01 3.147963E-01 + 8.699997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.699997E+00 0.000000E+00 5 2.862950E+01 8.771075E+01 1.143582E+00 2.860665E+01 + 8.699997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.699997E+00 3.000000E+01 1 1.086335E+02 8.905442E+01 1.792759E+00 1.086187E+02 + 8.699997E+00 3.000000E+01 2 6.313221E+01 8.688560E+01 3.429956E+00 6.303897E+01 + 8.699997E+00 3.000000E+01 3 2.253175E+01 1.242531E+00 2.252645E+01 4.885909E-01 + 8.699997E+00 3.000000E+01 4 2.591305E+02 8.659990E+01 1.536855E+01 2.586743E+02 + 8.699997E+00 3.000000E+01 5 5.604251E+01 8.920014E+01 7.823366E-01 5.603704E+01 + 8.699997E+00 3.000000E+01 6 1.037252E+03 -1.600515E+00 1.036847E+03 -2.897108E+01 + 8.699997E+00 6.000000E+01 1 7.726470E+01 8.966447E+01 4.524664E-01 7.726337E+01 + 8.699997E+00 6.000000E+01 2 1.412723E+02 8.671111E+01 8.104875E+00 1.410396E+02 + 8.699997E+00 6.000000E+01 3 3.222758E+01 2.046584E+00 3.220703E+01 1.150913E+00 + 8.699997E+00 6.000000E+01 4 6.315511E+02 8.669302E+01 3.643149E+01 6.304995E+02 + 8.699997E+00 6.000000E+01 5 6.329416E+01 8.980098E+01 2.198613E-01 6.329378E+01 + 8.699997E+00 6.000000E+01 6 1.328988E+03 -1.449415E+00 1.328563E+03 -3.361591E+01 + 8.699997E+00 9.000000E+01 1 1.004328E-05 -8.676299E+01 5.671095E-07 -1.002725E-05 + 8.699997E+00 9.000000E+01 2 1.851176E+02 8.664194E+01 1.084338E+01 1.847998E+02 + 8.699997E+00 9.000000E+01 3 3.839290E+01 2.472024E+00 3.835717E+01 1.655946E+00 + 8.699997E+00 9.000000E+01 4 8.532695E+02 8.672157E+01 4.879702E+01 8.518731E+02 + 8.699997E+00 9.000000E+01 5 3.182887E-04 -8.931004E+01 3.832783E-06 -3.182656E-04 + 8.699997E+00 9.000000E+01 6 1.277159E-04 1.791430E+02 -1.277016E-04 1.910145E-06 + 8.799997E+00 0.000000E+00 1 1.146925E+02 8.873815E+01 2.525715E+00 1.146646E+02 + 8.799997E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.799997E+00 0.000000E+00 3 2.120618E+01 1.114105E+00 2.120217E+01 4.123240E-01 + 8.799997E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.799997E+00 0.000000E+00 5 5.696907E+01 8.830740E+01 1.682705E+00 5.694421E+01 + 8.799997E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.799997E+00 3.000000E+01 1 1.090416E+02 8.907587E+01 1.758680E+00 1.090274E+02 + 8.799997E+00 3.000000E+01 2 6.368653E+01 8.695892E+01 3.378690E+00 6.359685E+01 + 8.799997E+00 3.000000E+01 3 2.495154E+01 1.398870E+00 2.494411E+01 6.091287E-01 + 8.799997E+00 3.000000E+01 4 2.606603E+02 8.668817E+01 1.505839E+01 2.602250E+02 + 8.799997E+00 3.000000E+01 5 8.050187E+01 8.915780E+01 1.183269E+00 8.049317E+01 + 8.799997E+00 3.000000E+01 6 1.013393E+03 -1.457878E+00 1.013065E+03 -2.578277E+01 + 8.799997E+00 6.000000E+01 1 7.681592E+01 8.960807E+01 5.254475E-01 7.681412E+01 + 8.799997E+00 6.000000E+01 2 1.407009E+02 8.680706E+01 7.836827E+00 1.404825E+02 + 8.799997E+00 6.000000E+01 3 3.473800E+01 2.159020E+00 3.471334E+01 1.308688E+00 + 8.799997E+00 6.000000E+01 4 6.256008E+02 8.679055E+01 3.502496E+01 6.246196E+02 + 8.799997E+00 6.000000E+01 5 7.797361E+01 8.972295E+01 3.770394E-01 7.797270E+01 + 8.799997E+00 6.000000E+01 6 1.283291E+03 -1.327380E+00 1.282947E+03 -2.972753E+01 + 8.799997E+00 9.000000E+01 1 9.863033E-06 -8.689292E+01 5.345981E-07 -9.848533E-06 + 8.799997E+00 9.000000E+01 2 1.832373E+02 8.674611E+01 1.040067E+01 1.829419E+02 + 8.799997E+00 9.000000E+01 3 4.087251E+01 2.561725E+00 4.083166E+01 1.826823E+00 + 8.799997E+00 9.000000E+01 4 8.397040E+02 8.682341E+01 4.653093E+01 8.384138E+02 + 8.799997E+00 9.000000E+01 5 3.162640E-04 -8.932271E+01 3.738477E-06 -3.162420E-04 + 8.799997E+00 9.000000E+01 6 1.227483E-04 1.792122E+02 -1.227367E-04 1.687626E-06 + 8.899998E+00 0.000000E+00 1 1.154415E+02 8.880047E+01 2.416671E+00 1.154162E+02 + 8.899998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.899998E+00 0.000000E+00 3 2.353365E+01 1.258228E+00 2.352797E+01 5.167626E-01 + 8.899998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.899998E+00 0.000000E+00 5 8.453156E+01 8.853838E+01 2.156168E+00 8.450405E+01 + 8.899998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.899998E+00 3.000000E+01 1 1.093369E+02 8.909344E+01 1.729911E+00 1.093232E+02 + 8.899998E+00 3.000000E+01 2 6.414483E+01 8.703671E+01 3.316039E+00 6.405906E+01 + 8.899998E+00 3.000000E+01 3 2.737386E+01 1.537138E+00 2.736401E+01 7.343010E-01 + 8.899998E+00 3.000000E+01 4 2.617768E+02 8.678060E+01 1.470127E+01 2.613637E+02 + 8.899998E+00 3.000000E+01 5 1.042432E+02 8.914483E+01 1.555832E+00 1.042316E+02 + 8.899998E+00 3.000000E+01 6 9.895847E+02 -1.329165E+00 9.893184E+02 -2.295463E+01 + 8.899998E+00 6.000000E+01 1 7.633929E+01 8.955841E+01 5.883585E-01 7.633702E+01 + 8.899998E+00 6.000000E+01 2 1.400420E+02 8.690406E+01 7.563385E+00 1.398376E+02 + 8.899998E+00 6.000000E+01 3 3.722475E+01 2.255234E+00 3.719592E+01 1.464835E+00 + 8.899998E+00 6.000000E+01 4 6.193709E+02 8.688903E+01 3.361327E+01 6.184581E+02 + 8.899998E+00 6.000000E+01 5 9.210502E+01 8.965668E+01 5.518961E-01 9.210336E+01 + 8.899998E+00 6.000000E+01 6 1.239524E+03 -1.216205E+00 1.239245E+03 -2.630914E+01 + 8.899998E+00 9.000000E+01 1 9.690153E-06 -8.702674E+01 5.026269E-07 -9.677109E-06 + 8.899998E+00 9.000000E+01 2 1.813369E+02 8.685020E+01 9.963889E+00 1.810629E+02 + 8.899998E+00 9.000000E+01 3 4.331962E+01 2.635539E+00 4.327380E+01 1.991950E+00 + 8.899998E+00 9.000000E+01 4 8.262416E+02 8.692502E+01 4.432195E+01 8.250520E+02 + 8.899998E+00 9.000000E+01 5 3.141985E-04 -8.933611E+01 3.640586E-06 -3.141774E-04 + 8.899998E+00 9.000000E+01 6 1.180415E-04 1.792756E+02 -1.180320E-04 1.492417E-06 + 8.999998E+00 0.000000E+00 1 1.160606E+02 8.885361E+01 2.322023E+00 1.160374E+02 + 8.999998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.999998E+00 0.000000E+00 3 2.587355E+01 1.387605E+00 2.586596E+01 6.265516E-01 + 8.999998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.999998E+00 0.000000E+00 5 1.113087E+02 8.867339E+01 2.576969E+00 1.112789E+02 + 8.999998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 8.999998E+00 3.000000E+01 1 1.095290E+02 8.910822E+01 1.704707E+00 1.095157E+02 + 8.999998E+00 3.000000E+01 2 6.451524E+01 8.711766E+01 3.244162E+00 6.443362E+01 + 8.999998E+00 3.000000E+01 3 2.979382E+01 1.658782E+00 2.978134E+01 8.624467E-01 + 8.999998E+00 3.000000E+01 4 2.625165E+02 8.687570E+01 1.430773E+01 2.621263E+02 + 8.999998E+00 3.000000E+01 5 1.272618E+02 8.914267E+01 1.904178E+00 1.272476E+02 + 8.999998E+00 3.000000E+01 6 9.659369E+02 -1.212944E+00 9.657205E+02 -2.044723E+01 + 8.999998E+00 6.000000E+01 1 7.583825E+01 8.951503E+01 6.419079E-01 7.583553E+01 + 8.999998E+00 6.000000E+01 2 1.393056E+02 8.700136E+01 7.287399E+00 1.391148E+02 + 8.999998E+00 6.000000E+01 3 3.968670E+01 2.336427E+00 3.965370E+01 1.617909E+00 + 8.999998E+00 6.000000E+01 4 6.129016E+02 8.698767E+01 3.220852E+01 6.120547E+02 + 8.999998E+00 6.000000E+01 5 1.056942E+02 8.959994E+01 7.379875E-01 1.056916E+02 + 8.999998E+00 6.000000E+01 6 1.197618E+03 -1.114954E+00 1.197392E+03 -2.330372E+01 + 8.999998E+00 9.000000E+01 1 9.524249E-06 -8.716258E+01 4.714704E-07 -9.512573E-06 + 8.999998E+00 9.000000E+01 2 1.794218E+02 8.695363E+01 9.535217E+00 1.791683E+02 + 8.999998E+00 9.000000E+01 3 4.573512E+01 2.695062E+00 4.568454E+01 2.150482E+00 + 8.999998E+00 9.000000E+01 4 8.129009E+02 8.702586E+01 4.217762E+01 8.118060E+02 + 8.999998E+00 9.000000E+01 5 3.121020E-04 -8.935016E+01 3.539742E-06 -3.120819E-04 + 8.999998E+00 9.000000E+01 6 1.135800E-04 1.793336E+02 -1.135724E-04 1.321103E-06 + 9.099998E+00 0.000000E+00 1 1.165594E+02 8.889934E+01 2.238990E+00 1.165379E+02 + 9.099998E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.099998E+00 0.000000E+00 3 2.822002E+01 1.503054E+00 2.821031E+01 7.402175E-01 + 9.099998E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.099998E+00 0.000000E+00 5 1.372598E+02 8.876658E+01 2.954594E+00 1.372280E+02 + 9.099998E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.099998E+00 3.000000E+01 1 1.096270E+02 8.912101E+01 1.681753E+00 1.096141E+02 + 9.099998E+00 3.000000E+01 2 6.480476E+01 8.720060E+01 3.165014E+00 6.472742E+01 + 9.099998E+00 3.000000E+01 3 3.220694E+01 1.765186E+00 3.219166E+01 9.920846E-01 + 9.099998E+00 3.000000E+01 4 2.629136E+02 8.697227E+01 1.388687E+01 2.625466E+02 + 9.099998E+00 3.000000E+01 5 1.495354E+02 8.914532E+01 2.230549E+00 1.495188E+02 + 9.099998E+00 3.000000E+01 6 9.425421E+02 -1.107938E+00 9.423659E+02 -1.822496E+01 + 9.099998E+00 6.000000E+01 1 7.531596E+01 8.947748E+01 6.868495E-01 7.531282E+01 + 9.099998E+00 6.000000E+01 2 1.385013E+02 8.709830E+01 7.011276E+00 1.383237E+02 + 9.099998E+00 6.000000E+01 3 4.212157E+01 2.404099E+00 4.208450E+01 1.766879E+00 + 9.099998E+00 6.000000E+01 4 6.062382E+02 8.708585E+01 3.082088E+01 6.054542E+02 + 9.099998E+00 6.000000E+01 5 1.187472E+02 8.955143E+01 9.296626E-01 1.187436E+02 + 9.099998E+00 6.000000E+01 6 1.157509E+03 -1.022758E+00 1.157325E+03 -2.066101E+01 + 9.099998E+00 9.000000E+01 1 9.364927E-06 -8.729887E+01 4.413322E-07 -9.354522E-06 + 9.099998E+00 9.000000E+01 2 1.774974E+02 8.705589E+01 9.116605E+00 1.772631E+02 + 9.099998E+00 9.000000E+01 3 4.811776E+01 2.741782E+00 4.806268E+01 2.301706E+00 + 9.099998E+00 9.000000E+01 4 7.997100E+02 8.712547E+01 4.010474E+01 7.987038E+02 + 9.099998E+00 9.000000E+01 5 3.099794E-04 -8.936478E+01 3.436606E-06 -3.099604E-04 + 9.099998E+00 9.000000E+01 6 1.093497E-04 1.793866E+02 -1.093434E-04 1.170687E-06 + 9.199999E+00 0.000000E+00 1 1.169471E+02 8.893913E+01 2.165245E+00 1.169271E+02 + 9.199999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.199999E+00 0.000000E+00 3 3.056842E+01 1.605399E+00 3.055642E+01 8.563998E-01 + 9.199999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.199999E+00 0.000000E+00 5 1.623999E+02 8.883729E+01 3.295392E+00 1.623665E+02 + 9.199999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.199999E+00 3.000000E+01 1 1.096390E+02 8.913246E+01 1.660030E+00 1.096264E+02 + 9.199999E+00 3.000000E+01 2 6.502007E+01 8.728464E+01 3.080281E+00 6.494707E+01 + 9.199999E+00 3.000000E+01 3 3.460962E+01 1.857570E+00 3.459143E+01 1.121872E+00 + 9.199999E+00 3.000000E+01 4 2.629997E+02 8.706934E+01 1.344649E+01 2.626557E+02 + 9.199999E+00 3.000000E+01 5 1.710542E+02 8.915020E+01 2.536954E+00 1.710354E+02 + 9.199999E+00 3.000000E+01 6 9.194749E+02 -1.013012E+00 9.193312E+02 -1.625583E+01 + 9.199999E+00 6.000000E+01 1 7.477536E+01 8.944529E+01 7.239272E-01 7.477186E+01 + 9.199999E+00 6.000000E+01 2 1.376372E+02 8.719436E+01 6.737082E+00 1.374722E+02 + 9.199999E+00 6.000000E+01 3 4.452791E+01 2.459471E+00 4.448689E+01 1.910812E+00 + 9.199999E+00 6.000000E+01 4 5.994178E+02 8.718303E+01 2.945880E+01 5.986935E+02 + 9.199999E+00 6.000000E+01 5 1.312729E+02 8.951003E+01 1.122579E+00 1.312681E+02 + 9.199999E+00 6.000000E+01 6 1.119135E+03 -9.388041E-01 1.118985E+03 -1.833646E+01 + 9.199999E+00 9.000000E+01 1 9.211790E-06 -8.743430E+01 4.123651E-07 -9.202556E-06 + 9.199999E+00 9.000000E+01 2 1.755691E+02 8.715659E+01 8.709388E+00 1.753530E+02 + 9.199999E+00 9.000000E+01 3 5.046645E+01 2.777081E+00 5.040718E+01 2.445111E+00 + 9.199999E+00 9.000000E+01 4 7.866900E+02 8.722346E+01 3.810787E+01 7.857665E+02 + 9.199999E+00 9.000000E+01 5 3.078333E-04 -8.937985E+01 3.331829E-06 -3.078153E-04 + 9.199999E+00 9.000000E+01 6 1.053368E-04 1.794351E+02 -1.053317E-04 1.038555E-06 + 9.299999E+00 0.000000E+00 1 1.172321E+02 8.897412E+01 2.098919E+00 1.172133E+02 + 9.299999E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.299999E+00 0.000000E+00 3 3.291422E+01 1.695353E+00 3.289981E+01 9.737731E-01 + 9.299999E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.299999E+00 0.000000E+00 5 1.867091E+02 8.889349E+01 3.605545E+00 1.866742E+02 + 9.299999E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.299999E+00 3.000000E+01 1 1.095727E+02 8.914307E+01 1.638749E+00 1.095604E+02 + 9.299999E+00 3.000000E+01 2 6.516769E+01 8.736900E+01 2.991433E+00 6.509899E+01 + 9.299999E+00 3.000000E+01 3 3.699881E+01 1.936981E+00 3.697767E+01 1.250569E+00 + 9.299999E+00 3.000000E+01 4 2.628047E+02 8.716611E+01 1.299326E+01 2.624833E+02 + 9.299999E+00 3.000000E+01 5 1.918302E+02 8.915633E+01 2.824592E+00 1.918094E+02 + 9.299999E+00 3.000000E+01 6 8.967960E+02 -9.271351E-01 8.966786E+02 -1.451092E+01 + 9.299999E+00 6.000000E+01 1 7.421921E+01 8.941801E+01 7.538694E-01 7.421538E+01 + 9.299999E+00 6.000000E+01 2 1.367218E+02 8.728908E+01 6.466522E+00 1.365688E+02 + 9.299999E+00 6.000000E+01 3 4.690530E+01 2.503586E+00 4.686052E+01 2.048913E+00 + 9.299999E+00 6.000000E+01 4 5.924759E+02 8.727876E+01 2.812886E+01 5.918078E+02 + 9.299999E+00 6.000000E+01 5 1.432829E+02 8.947479E+01 1.313416E+00 1.432769E+02 + 9.299999E+00 6.000000E+01 6 1.082423E+03 -8.623536E-01 1.082300E+03 -1.629083E+01 + 9.299999E+00 9.000000E+01 1 9.064471E-06 -8.756777E+01 3.846747E-07 -9.056304E-06 + 9.299999E+00 9.000000E+01 2 1.736416E+02 8.725536E+01 8.314786E+00 1.734424E+02 + 9.299999E+00 9.000000E+01 3 5.278285E+01 2.802060E+00 5.271974E+01 2.580326E+00 + 9.299999E+00 9.000000E+01 4 7.738512E+02 8.731953E+01 3.618996E+01 7.730045E+02 + 9.299999E+00 9.000000E+01 5 3.056753E-04 -8.939530E+01 3.226063E-06 -3.056583E-04 + 9.299999E+00 9.000000E+01 6 1.015288E-04 1.794794E+02 -1.015247E-04 9.224037E-07 + 9.400000E+00 0.000000E+00 1 1.174227E+02 8.900529E+01 2.038470E+00 1.174050E+02 + 9.400000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.400000E+00 0.000000E+00 3 3.525301E+01 1.773938E+00 3.523611E+01 1.091296E+00 + 9.400000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.400000E+00 0.000000E+00 5 2.101871E+02 8.893999E+01 3.888407E+00 2.101512E+02 + 9.400000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.400000E+00 3.000000E+01 1 1.094354E+02 8.915318E+01 1.617389E+00 1.094234E+02 + 9.400000E+00 3.000000E+01 2 6.525328E+01 8.745300E+01 2.899776E+00 6.518882E+01 + 9.400000E+00 3.000000E+01 3 3.937164E+01 2.004708E+00 3.934754E+01 1.377283E+00 + 9.400000E+00 3.000000E+01 4 2.623578E+02 8.726190E+01 1.253300E+01 2.620582E+02 + 9.400000E+00 3.000000E+01 5 2.118597E+02 8.916341E+01 3.093292E+00 2.118371E+02 + 9.400000E+00 3.000000E+01 6 8.745499E+02 -8.493958E-01 8.744538E+02 -1.296451E+01 + 9.400000E+00 6.000000E+01 1 7.364943E+01 8.939521E+01 7.774000E-01 7.364532E+01 + 9.400000E+00 6.000000E+01 2 1.357621E+02 8.738207E+01 6.201006E+00 1.356204E+02 + 9.400000E+00 6.000000E+01 3 4.925246E+01 2.537764E+00 4.920415E+01 2.180793E+00 + 9.400000E+00 6.000000E+01 4 5.854478E+02 8.737270E+01 2.683640E+01 5.848324E+02 + 9.400000E+00 6.000000E+01 5 1.547827E+02 8.944517E+01 1.498852E+00 1.547754E+02 + 9.400000E+00 6.000000E+01 6 1.047306E+03 -7.927245E-01 1.047206E+03 -1.448970E+01 + 9.400000E+00 9.000000E+01 1 8.922653E-06 -8.769844E+01 3.583247E-07 -8.915456E-06 + 9.400000E+00 9.000000E+01 2 1.717189E+02 8.735191E+01 7.933661E+00 1.715355E+02 + 9.400000E+00 9.000000E+01 3 5.506533E+01 2.818021E+00 5.499874E+01 2.707227E+00 + 9.400000E+00 9.000000E+01 4 7.612180E+02 8.741341E+01 3.435312E+01 7.604424E+02 + 9.400000E+00 9.000000E+01 5 3.035088E-04 -8.941103E+01 3.119849E-06 -3.034928E-04 + 9.400000E+00 9.000000E+01 6 9.791365E-05 1.795200E+02 -9.791021E-05 8.202282E-07 + 9.500000E+00 0.000000E+00 1 1.175263E+02 8.903337E+01 1.982663E+00 1.175095E+02 + 9.500000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.500000E+00 0.000000E+00 3 3.758219E+01 1.841845E+00 3.756277E+01 1.207919E+00 + 9.500000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.500000E+00 0.000000E+00 5 2.328416E+02 8.897963E+01 4.146432E+00 2.328046E+02 + 9.500000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.500000E+00 3.000000E+01 1 1.092334E+02 8.916306E+01 1.595552E+00 1.092217E+02 + 9.500000E+00 3.000000E+01 2 6.528275E+01 8.753620E+01 2.806384E+00 6.522240E+01 + 9.500000E+00 3.000000E+01 3 4.172578E+01 2.061700E+00 4.169877E+01 1.501114E+00 + 9.500000E+00 3.000000E+01 4 2.616840E+02 8.735624E+01 1.207042E+01 2.614055E+02 + 9.500000E+00 3.000000E+01 5 2.311435E+02 8.917111E+01 3.343805E+00 2.311194E+02 + 9.500000E+00 3.000000E+01 6 8.527784E+02 -7.789711E-01 8.526996E+02 -1.159369E+01 + 9.500000E+00 6.000000E+01 1 7.306854E+01 8.937646E+01 7.951841E-01 7.306422E+01 + 9.500000E+00 6.000000E+01 2 1.347647E+02 8.747308E+01 5.941638E+00 1.346337E+02 + 9.500000E+00 6.000000E+01 3 5.156913E+01 2.562895E+00 5.151755E+01 2.305967E+00 + 9.500000E+00 6.000000E+01 4 5.783568E+02 8.746452E+01 2.558543E+01 5.777906E+02 + 9.500000E+00 6.000000E+01 5 1.657898E+02 8.942056E+01 1.676633E+00 1.657813E+02 + 9.500000E+00 6.000000E+01 6 1.013714E+03 -7.292941E-01 1.013632E+03 -1.290279E+01 + 9.500000E+00 9.000000E+01 1 8.785993E-06 -8.782562E+01 3.333497E-07 -8.779667E-06 + 9.500000E+00 9.000000E+01 2 1.698040E+02 8.744601E+01 7.566580E+00 1.696353E+02 + 9.500000E+00 9.000000E+01 3 5.731452E+01 2.825916E+00 5.724482E+01 2.825694E+00 + 9.500000E+00 9.000000E+01 4 7.487892E+02 8.750488E+01 3.259814E+01 7.480793E+02 + 9.500000E+00 9.000000E+01 5 3.013330E-04 -8.942694E+01 3.013811E-06 -3.013179E-04 + 9.500000E+00 9.000000E+01 6 9.447982E-05 1.795571E+02 -9.447700E-05 7.302739E-07 + 9.600000E+00 0.000000E+00 1 1.175499E+02 8.905898E+01 1.930542E+00 1.175340E+02 + 9.600000E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.600000E+00 0.000000E+00 3 3.989761E+01 1.899998E+00 3.987568E+01 1.322811E+00 + 9.600000E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.600000E+00 0.000000E+00 5 2.546638E+02 8.901414E+01 4.381640E+00 2.546261E+02 + 9.600000E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.600000E+00 3.000000E+01 1 1.089727E+02 8.917290E+01 1.573015E+00 1.089613E+02 + 9.600000E+00 3.000000E+01 2 6.526106E+01 8.761814E+01 2.712210E+00 6.520468E+01 + 9.600000E+00 3.000000E+01 3 4.405827E+01 2.109046E+00 4.402843E+01 1.621410E+00 + 9.600000E+00 3.000000E+01 4 2.608084E+02 8.744871E+01 1.160957E+01 2.605499E+02 + 9.600000E+00 3.000000E+01 5 2.496811E+02 8.917929E+01 3.576336E+00 2.496555E+02 + 9.600000E+00 3.000000E+01 6 8.315068E+02 -7.151269E-01 8.314421E+02 -1.037803E+01 + 9.600000E+00 6.000000E+01 1 7.247884E+01 8.936135E+01 8.078730E-01 7.247433E+01 + 9.600000E+00 6.000000E+01 2 1.337359E+02 8.756182E+01 5.689329E+00 1.336148E+02 + 9.600000E+00 6.000000E+01 3 5.385368E+01 2.580039E+00 5.379909E+01 2.424221E+00 + 9.600000E+00 6.000000E+01 4 5.712331E+02 8.755403E+01 2.437869E+01 5.707126E+02 + 9.600000E+00 6.000000E+01 5 1.763068E+02 8.940032E+01 1.845266E+00 1.762971E+02 + 9.600000E+00 6.000000E+01 6 9.815810E+02 -6.714934E-01 9.815136E+02 -1.150364E+01 + 9.600000E+00 9.000000E+01 1 8.654189E-06 -8.794876E+01 3.097618E-07 -8.648643E-06 + 9.600000E+00 9.000000E+01 2 1.679009E+02 8.753750E+01 7.213941E+00 1.677458E+02 + 9.600000E+00 9.000000E+01 3 5.952987E+01 2.826792E+00 5.945744E+01 2.935823E+00 + 9.600000E+00 9.000000E+01 4 7.365856E+02 8.759377E+01 3.092498E+01 7.359361E+02 + 9.600000E+00 9.000000E+01 5 2.991584E-04 -8.944297E+01 2.908380E-06 -2.991442E-04 + 9.600000E+00 9.000000E+01 6 9.121706E-05 1.795911E+02 -9.121474E-05 6.510139E-07 + 9.700001E+00 0.000000E+00 1 1.175001E+02 8.908259E+01 1.881315E+00 1.174850E+02 + 9.700001E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.700001E+00 0.000000E+00 3 4.219749E+01 1.949078E+00 4.217308E+01 1.435190E+00 + 9.700001E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.700001E+00 0.000000E+00 5 2.756729E+02 8.904470E+01 4.596128E+00 2.756346E+02 + 9.700001E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.700001E+00 3.000000E+01 1 1.086600E+02 8.918287E+01 1.549620E+00 1.086490E+02 + 9.700001E+00 3.000000E+01 2 6.519335E+01 8.769851E+01 2.618025E+00 6.514076E+01 + 9.700001E+00 3.000000E+01 3 4.636815E+01 2.147478E+00 4.633559E+01 1.737497E+00 + 9.700001E+00 3.000000E+01 4 2.597520E+02 8.753899E+01 1.115364E+01 2.595125E+02 + 9.700001E+00 3.000000E+01 5 2.675006E+02 8.918803E+01 3.790771E+00 2.674738E+02 + 9.700001E+00 3.000000E+01 6 8.107560E+02 -6.572052E-01 8.107027E+02 -9.299488E+00 + 9.700001E+00 6.000000E+01 1 7.188165E+01 8.934953E+01 8.160516E-01 7.187702E+01 + 9.700001E+00 6.000000E+01 2 1.326802E+02 8.764812E+01 5.444745E+00 1.325684E+02 + 9.700001E+00 6.000000E+01 3 5.610655E+01 2.589999E+00 5.604924E+01 2.535378E+00 + 9.700001E+00 6.000000E+01 4 5.640962E+02 8.764104E+01 2.321823E+01 5.636182E+02 + 9.700001E+00 6.000000E+01 5 1.863526E+02 8.938400E+01 2.003495E+00 1.863418E+02 + 9.700001E+00 6.000000E+01 6 9.508435E+02 -6.188014E-01 9.507880E+02 -1.026903E+01 + 9.700001E+00 9.000000E+01 1 8.526941E-06 -8.806748E+01 2.875491E-07 -8.522092E-06 + 9.700001E+00 9.000000E+01 2 1.660127E+02 8.762624E+01 6.875925E+00 1.658703E+02 + 9.700001E+00 9.000000E+01 3 6.171202E+01 2.821412E+00 6.163721E+01 3.037653E+00 + 9.700001E+00 9.000000E+01 4 7.246121E+02 8.767999E+01 2.933279E+01 7.240182E+02 + 9.700001E+00 9.000000E+01 5 2.969830E-04 -8.945903E+01 2.803997E-06 -2.969697E-04 + 9.700001E+00 9.000000E+01 6 8.811515E-05 1.796221E+02 -8.811324E-05 5.811088E-07 + 9.800001E+00 0.000000E+00 1 1.173830E+02 8.910458E+01 1.834391E+00 1.173687E+02 + 9.800001E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.800001E+00 0.000000E+00 3 4.447944E+01 1.989984E+00 4.445261E+01 1.544539E+00 + 9.800001E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.800001E+00 0.000000E+00 5 2.958734E+02 8.907237E+01 4.790026E+00 2.958347E+02 + 9.800001E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.800001E+00 3.000000E+01 1 1.082990E+02 8.919299E+01 1.525331E+00 1.082883E+02 + 9.800001E+00 3.000000E+01 2 6.508414E+01 8.777704E+01 2.524505E+00 6.503516E+01 + 9.800001E+00 3.000000E+01 3 4.865367E+01 2.177999E+00 4.861852E+01 1.849039E+00 + 9.800001E+00 3.000000E+01 4 2.585378E+02 8.762685E+01 1.070539E+01 2.583160E+02 + 9.800001E+00 3.000000E+01 5 2.846022E+02 8.919722E+01 3.987484E+00 2.845743E+02 + 9.800001E+00 3.000000E+01 6 7.905407E+02 -6.046118E-01 7.904967E+02 -8.342000E+00 + 9.800001E+00 6.000000E+01 1 7.127917E+01 8.934064E+01 8.202709E-01 7.127444E+01 + 9.800001E+00 6.000000E+01 2 1.316037E+02 8.773186E+01 5.208350E+00 1.315005E+02 + 9.800001E+00 6.000000E+01 3 5.832739E+01 2.593717E+00 5.826764E+01 2.639515E+00 + 9.800001E+00 6.000000E+01 4 5.569635E+02 8.772540E+01 2.210526E+01 5.565247E+02 + 9.800001E+00 6.000000E+01 5 1.959448E+02 8.937125E+01 2.150185E+00 1.959330E+02 + 9.800001E+00 6.000000E+01 6 9.214333E+02 -5.707465E-01 9.213876E+02 -9.178619E+00 + 9.800001E+00 9.000000E+01 1 8.404029E-06 -8.818153E+01 2.666843E-07 -8.399797E-06 + 9.800001E+00 9.000000E+01 2 1.641413E+02 8.771213E+01 6.552562E+00 1.640104E+02 + 9.800001E+00 9.000000E+01 3 6.386058E+01 2.810702E+00 6.378376E+01 3.131488E+00 + 9.800001E+00 9.000000E+01 4 7.128737E+02 8.776344E+01 2.782015E+01 7.123307E+02 + 9.800001E+00 9.000000E+01 5 2.948142E-04 -8.947506E+01 2.701058E-06 -2.948018E-04 + 9.800001E+00 9.000000E+01 6 8.516476E-05 1.796506E+02 -8.516318E-05 5.193963E-07 + 9.900002E+00 0.000000E+00 1 1.172050E+02 8.912526E+01 1.789311E+00 1.171914E+02 + 9.900002E+00 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.900002E+00 0.000000E+00 3 4.674041E+01 2.023381E+00 4.671127E+01 1.650278E+00 + 9.900002E+00 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.900002E+00 0.000000E+00 5 3.152844E+02 8.909766E+01 4.965184E+00 3.152453E+02 + 9.900002E+00 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 9.900002E+00 3.000000E+01 1 1.078954E+02 8.920335E+01 1.500136E+00 1.078849E+02 + 9.900002E+00 3.000000E+01 2 6.493745E+01 8.785353E+01 2.432174E+00 6.489188E+01 + 9.900002E+00 3.000000E+01 3 5.091317E+01 2.201357E+00 5.087559E+01 1.955649E+00 + 9.900002E+00 3.000000E+01 4 2.571832E+02 8.771211E+01 1.026689E+01 2.569782E+02 + 9.900002E+00 3.000000E+01 5 3.009960E+02 8.920689E+01 4.166389E+00 3.009671E+02 + 9.900002E+00 3.000000E+01 6 7.708690E+02 -5.568187E-01 7.708326E+02 -7.491434E+00 + 9.900002E+00 6.000000E+01 1 7.067269E+01 8.933435E+01 8.210385E-01 7.066792E+01 + 9.900002E+00 6.000000E+01 2 1.305102E+02 8.781295E+01 4.980528E+00 1.304152E+02 + 9.900002E+00 6.000000E+01 3 6.051537E+01 2.591830E+00 6.045346E+01 2.736538E+00 + 9.900002E+00 6.000000E+01 4 5.498582E+02 8.780705E+01 2.104022E+01 5.494555E+02 + 9.900002E+00 6.000000E+01 5 2.050883E+02 8.936155E+01 2.285264E+00 2.050755E+02 + 9.900002E+00 6.000000E+01 6 8.932906E+02 -5.268963E-01 8.932528E+02 -8.214651E+00 + 9.900002E+00 9.000000E+01 1 8.285133E-06 -8.829071E+01 2.471319E-07 -8.281447E-06 + 9.900002E+00 9.000000E+01 2 1.622894E+02 8.779511E+01 6.243764E+00 1.621692E+02 + 9.900002E+00 9.000000E+01 3 6.597607E+01 2.795250E+00 6.589757E+01 3.217452E+00 + 9.900002E+00 9.000000E+01 4 7.013761E+02 8.784407E+01 2.638522E+01 7.008796E+02 + 9.900002E+00 9.000000E+01 5 2.926507E-04 -8.949097E+01 2.599930E-06 -2.926391E-04 + 9.900002E+00 9.000000E+01 6 8.235678E-05 1.796766E+02 -8.235547E-05 4.648591E-07 + 1.000000E+01 0.000000E+00 1 1.169712E+02 8.914487E+01 1.745720E+00 1.169581E+02 + 1.000000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E+01 0.000000E+00 3 4.897959E+01 2.049965E+00 4.894825E+01 1.752050E+00 + 1.000000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E+01 0.000000E+00 5 3.339042E+02 8.912106E+01 5.122027E+00 3.338649E+02 + 1.000000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.000000E+01 3.000000E+01 1 1.074541E+02 8.921397E+01 1.474098E+00 1.074440E+02 + 1.000000E+01 3.000000E+01 2 6.475717E+01 8.792786E+01 2.341482E+00 6.471483E+01 + 1.000000E+01 3.000000E+01 3 5.314511E+01 2.218310E+00 5.310529E+01 2.057096E+00 + 1.000000E+01 3.000000E+01 4 2.557055E+02 8.779467E+01 9.839749E+00 2.555161E+02 + 1.000000E+01 3.000000E+01 5 3.167002E+02 8.921693E+01 4.328268E+00 3.166707E+02 + 1.000000E+01 3.000000E+01 6 7.517448E+02 -5.133530E-01 7.517147E+02 -6.735319E+00 + 1.000000E+01 6.000000E+01 1 7.006360E+01 8.933038E+01 8.188215E-01 7.005882E+01 + 1.000000E+01 6.000000E+01 2 1.294039E+02 8.789131E+01 4.761447E+00 1.293162E+02 + 1.000000E+01 6.000000E+01 3 6.267030E+01 2.585020E+00 6.260653E+01 2.826543E+00 + 1.000000E+01 6.000000E+01 4 5.427922E+02 8.788593E+01 2.002315E+01 5.424228E+02 + 1.000000E+01 6.000000E+01 5 2.138007E+02 8.935457E+01 2.408391E+00 2.137871E+02 + 1.000000E+01 6.000000E+01 6 8.663563E+02 -4.868632E-01 8.663251E+02 -7.361658E+00 + 1.000000E+01 9.000000E+01 1 8.170079E-06 -8.839492E+01 2.288456E-07 -8.166873E-06 + 1.000000E+01 9.000000E+01 2 1.604586E+02 8.787517E+01 5.949301E+00 1.603483E+02 + 1.000000E+01 9.000000E+01 3 6.805760E+01 2.775809E+00 6.797775E+01 3.295897E+00 + 1.000000E+01 9.000000E+01 4 6.901216E+02 8.792185E+01 2.502566E+01 6.896677E+02 + 1.000000E+01 9.000000E+01 5 2.904943E-04 -8.950674E+01 2.500847E-06 -2.904835E-04 + 1.000000E+01 9.000000E+01 6 7.968334E-05 1.797004E+02 -7.968225E-05 4.166122E-07 + 1.010000E+01 0.000000E+00 1 1.166864E+02 8.916358E+01 1.703356E+00 1.166740E+02 + 1.010000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.010000E+01 0.000000E+00 3 5.119496E+01 2.070443E+00 5.116154E+01 1.849581E+00 + 1.010000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.010000E+01 0.000000E+00 5 3.517633E+02 8.914294E+01 5.261702E+00 3.517239E+02 + 1.010000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.010000E+01 3.000000E+01 1 1.069780E+02 8.922484E+01 1.447280E+00 1.069682E+02 + 1.010000E+01 3.000000E+01 2 6.454665E+01 8.799989E+01 2.252775E+00 6.450732E+01 + 1.010000E+01 3.000000E+01 3 5.534990E+01 2.229496E+00 5.530801E+01 2.153234E+00 + 1.010000E+01 3.000000E+01 4 2.541205E+02 8.787442E+01 9.425289E+00 2.539457E+02 + 1.010000E+01 3.000000E+01 5 3.317360E+02 8.922735E+01 4.473430E+00 3.317058E+02 + 1.010000E+01 3.000000E+01 6 7.331686E+02 -4.737875E-01 7.331436E+02 -6.062614E+00 + 1.010000E+01 6.000000E+01 1 6.945335E+01 8.932846E+01 8.140199E-01 6.944859E+01 + 1.010000E+01 6.000000E+01 2 1.282881E+02 8.796692E+01 4.551222E+00 1.282073E+02 + 1.010000E+01 6.000000E+01 3 6.479252E+01 2.573969E+00 6.472715E+01 2.909775E+00 + 1.010000E+01 6.000000E+01 4 5.357795E+02 8.796202E+01 1.905341E+01 5.354407E+02 + 1.010000E+01 6.000000E+01 5 2.220971E+02 8.935001E+01 2.519507E+00 2.220828E+02 + 1.010000E+01 6.000000E+01 6 8.405726E+02 -4.502915E-01 8.405467E+02 -6.606051E+00 + 1.010000E+01 9.000000E+01 1 8.058648E-06 -8.849416E+01 2.117711E-07 -8.055865E-06 + 1.010000E+01 9.000000E+01 2 1.586507E+02 8.795229E+01 5.668875E+00 1.585494E+02 + 1.010000E+01 9.000000E+01 3 7.010595E+01 2.752871E+00 7.002505E+01 3.367061E+00 + 1.010000E+01 9.000000E+01 4 6.791106E+02 8.799677E+01 2.373888E+01 6.786956E+02 + 1.010000E+01 9.000000E+01 5 2.883523E-04 -8.952231E+01 2.404073E-06 -2.883423E-04 + 1.010000E+01 9.000000E+01 6 7.713650E-05 1.797223E+02 -7.713559E-05 3.738827E-07 + 1.020000E+01 0.000000E+00 1 1.163559E+02 8.918156E+01 1.662029E+00 1.163440E+02 + 1.020000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.020000E+01 0.000000E+00 3 5.338578E+01 2.085252E+00 5.335043E+01 1.942520E+00 + 1.020000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.020000E+01 0.000000E+00 5 3.688779E+02 8.916357E+01 5.384873E+00 3.688386E+02 + 1.020000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.020000E+01 3.000000E+01 1 1.064719E+02 8.923595E+01 1.419788E+00 1.064624E+02 + 1.020000E+01 3.000000E+01 2 6.430946E+01 8.806957E+01 2.166323E+00 6.427296E+01 + 1.020000E+01 3.000000E+01 3 5.752578E+01 2.235494E+00 5.748199E+01 2.243899E+00 + 1.020000E+01 3.000000E+01 4 2.524415E+02 8.795133E+01 9.024391E+00 2.522802E+02 + 1.020000E+01 3.000000E+01 5 3.461152E+02 8.923814E+01 4.602109E+00 3.460846E+02 + 1.020000E+01 3.000000E+01 6 7.151368E+02 -4.377417E-01 7.151159E+02 -5.463615E+00 + 1.020000E+01 6.000000E+01 1 6.884287E+01 8.932832E+01 8.070253E-01 6.883814E+01 + 1.020000E+01 6.000000E+01 2 1.271661E+02 8.803976E+01 4.349825E+00 1.270917E+02 + 1.020000E+01 6.000000E+01 3 6.688241E+01 2.559122E+00 6.681570E+01 2.986316E+00 + 1.020000E+01 6.000000E+01 4 5.288314E+02 8.803529E+01 1.813049E+01 5.285204E+02 + 1.020000E+01 6.000000E+01 5 2.299881E+02 8.934759E+01 2.618761E+00 2.299732E+02 + 1.020000E+01 6.000000E+01 6 8.158806E+02 -4.168615E-01 8.158589E+02 -5.935972E+00 + 1.020000E+01 9.000000E+01 1 7.950614E-06 -8.858845E+01 1.958533E-07 -7.948202E-06 + 1.020000E+01 9.000000E+01 2 1.568666E+02 8.802647E+01 5.402133E+00 1.567735E+02 + 1.020000E+01 9.000000E+01 3 7.212234E+01 2.726942E+00 7.204066E+01 3.431303E+00 + 1.020000E+01 9.000000E+01 4 6.683471E+02 8.806887E+01 2.252207E+01 6.679675E+02 + 1.020000E+01 9.000000E+01 5 2.862214E-04 -8.953762E+01 2.309812E-06 -2.862121E-04 + 1.020000E+01 9.000000E+01 6 7.470902E-05 1.797423E+02 -7.470826E-05 3.359954E-07 + 1.030000E+01 0.000000E+00 1 1.159833E+02 8.919891E+01 1.621601E+00 1.159719E+02 + 1.030000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.030000E+01 0.000000E+00 3 5.555044E+01 2.095102E+00 5.551330E+01 2.030828E+00 + 1.030000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.030000E+01 0.000000E+00 5 3.852576E+02 8.918316E+01 5.492260E+00 3.852184E+02 + 1.030000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.030000E+01 3.000000E+01 1 1.059390E+02 8.924728E+01 1.391723E+00 1.059299E+02 + 1.030000E+01 3.000000E+01 2 6.404846E+01 8.813687E+01 2.082344E+00 6.401460E+01 + 1.030000E+01 3.000000E+01 3 5.967226E+01 2.236973E+00 5.962678E+01 2.329164E+00 + 1.030000E+01 3.000000E+01 4 2.506837E+02 8.802541E+01 8.637652E+00 2.505348E+02 + 1.030000E+01 3.000000E+01 5 3.598548E+02 8.924917E+01 4.715608E+00 3.598239E+02 + 1.030000E+01 3.000000E+01 6 6.976420E+02 -4.048707E-01 6.976246E+02 -4.929726E+00 + 1.030000E+01 6.000000E+01 1 6.823340E+01 8.932977E+01 7.981609E-01 6.822873E+01 + 1.030000E+01 6.000000E+01 2 1.260409E+02 8.810987E+01 4.157207E+00 1.259723E+02 + 1.030000E+01 6.000000E+01 3 6.893880E+01 2.541027E+00 6.887101E+01 3.056384E+00 + 1.030000E+01 6.000000E+01 4 5.219585E+02 8.810577E+01 1.725308E+01 5.216733E+02 + 1.030000E+01 6.000000E+01 5 2.374935E+02 8.934695E+01 2.706846E+00 2.374780E+02 + 1.030000E+01 6.000000E+01 6 7.922292E+02 -3.862822E-01 7.922112E+02 -5.341087E+00 + 1.030000E+01 9.000000E+01 1 7.845823E-06 -8.867785E+01 1.810329E-07 -7.843734E-06 + 1.030000E+01 9.000000E+01 2 1.551079E+02 8.809779E+01 5.148639E+00 1.550224E+02 + 1.030000E+01 9.000000E+01 3 7.410574E+01 2.698485E+00 7.402357E+01 3.488901E+00 + 1.030000E+01 9.000000E+01 4 6.578296E+02 8.813818E+01 2.137241E+01 6.574823E+02 + 1.030000E+01 9.000000E+01 5 2.841064E-04 -8.955265E+01 2.218179E-06 -2.840977E-04 + 1.030000E+01 9.000000E+01 6 7.239411E-05 1.797607E+02 -7.239348E-05 3.023628E-07 + 1.040000E+01 0.000000E+00 1 1.155735E+02 8.921570E+01 1.581993E+00 1.155627E+02 + 1.040000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.040000E+01 0.000000E+00 3 5.768827E+01 2.100430E+00 5.764951E+01 2.114344E+00 + 1.040000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.040000E+01 0.000000E+00 5 4.009281E+02 8.920187E+01 5.584766E+00 4.008892E+02 + 1.040000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.040000E+01 3.000000E+01 1 1.053823E+02 8.925881E+01 1.363213E+00 1.053735E+02 + 1.040000E+01 3.000000E+01 2 6.376615E+01 8.820177E+01 2.000984E+00 6.373475E+01 + 1.040000E+01 3.000000E+01 3 6.178837E+01 2.234376E+00 6.174139E+01 2.408964E+00 + 1.040000E+01 3.000000E+01 4 2.488582E+02 8.809665E+01 8.265490E+00 2.487209E+02 + 1.040000E+01 3.000000E+01 5 3.729734E+02 8.926048E+01 4.813849E+00 3.729423E+02 + 1.040000E+01 3.000000E+01 6 6.806799E+02 -3.748697E-01 6.806653E+02 -4.453459E+00 + 1.040000E+01 6.000000E+01 1 6.762556E+01 8.933258E+01 7.877367E-01 6.762097E+01 + 1.040000E+01 6.000000E+01 2 1.249154E+02 8.817728E+01 3.973207E+00 1.248521E+02 + 1.040000E+01 6.000000E+01 3 7.096295E+01 2.520146E+00 7.089432E+01 3.120288E+00 + 1.040000E+01 6.000000E+01 4 5.151669E+02 8.817352E+01 1.641975E+01 5.149052E+02 + 1.040000E+01 6.000000E+01 5 2.446202E+02 8.934795E+01 2.783833E+00 2.446044E+02 + 1.040000E+01 6.000000E+01 6 7.695685E+02 -3.582901E-01 7.695535E+02 -4.812344E+00 + 1.040000E+01 9.000000E+01 1 7.744115E-06 -8.876249E+01 1.672494E-07 -7.742309E-06 + 1.040000E+01 9.000000E+01 2 1.533754E+02 8.816624E+01 4.907936E+00 1.532968E+02 + 1.040000E+01 9.000000E+01 3 7.605679E+01 2.667913E+00 7.597435E+01 3.540219E+00 + 1.040000E+01 9.000000E+01 4 6.475590E+02 8.820473E+01 2.028681E+01 6.472411E+02 + 1.040000E+01 9.000000E+01 5 2.820044E-04 -8.956738E+01 2.129336E-06 -2.819964E-04 + 1.040000E+01 9.000000E+01 6 7.018534E-05 1.797776E+02 -7.018481E-05 2.724718E-07 + 1.050000E+01 0.000000E+00 1 1.151296E+02 8.923202E+01 1.543128E+00 1.151192E+02 + 1.050000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.050000E+01 0.000000E+00 3 5.979835E+01 2.101754E+00 5.975812E+01 2.193062E+00 + 1.050000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.050000E+01 0.000000E+00 5 4.159096E+02 8.921983E+01 5.663044E+00 4.158711E+02 + 1.050000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.050000E+01 3.000000E+01 1 1.048050E+02 8.927050E+01 1.334369E+00 1.047966E+02 + 1.050000E+01 3.000000E+01 2 6.346526E+01 8.826427E+01 1.922339E+00 6.343614E+01 + 1.050000E+01 3.000000E+01 3 6.387455E+01 2.228186E+00 6.382626E+01 2.483403E+00 + 1.050000E+01 3.000000E+01 4 2.469748E+02 8.816509E+01 7.908054E+00 2.468482E+02 + 1.050000E+01 3.000000E+01 5 3.854914E+02 8.927195E+01 4.898271E+00 3.854603E+02 + 1.050000E+01 3.000000E+01 6 6.642385E+02 -3.474618E-01 6.642263E+02 -4.028152E+00 + 1.050000E+01 6.000000E+01 1 6.702032E+01 8.933657E+01 7.760142E-01 6.701583E+01 + 1.050000E+01 6.000000E+01 2 1.237905E+02 8.824201E+01 3.797640E+00 1.237323E+02 + 1.050000E+01 6.000000E+01 3 7.295372E+01 2.496862E+00 7.288446E+01 3.178205E+00 + 1.050000E+01 6.000000E+01 4 5.084659E+02 8.823856E+01 1.562921E+01 5.082257E+02 + 1.050000E+01 6.000000E+01 5 2.513903E+02 8.935038E+01 2.850223E+00 2.513742E+02 + 1.050000E+01 6.000000E+01 6 7.478476E+02 -3.326485E-01 7.478350E+02 -4.341838E+00 + 1.050000E+01 9.000000E+01 1 7.645333E-06 -8.884250E+01 1.544425E-07 -7.643774E-06 + 1.050000E+01 9.000000E+01 2 1.516699E+02 8.823196E+01 4.679524E+00 1.515977E+02 + 1.050000E+01 9.000000E+01 3 7.797541E+01 2.635607E+00 7.789293E+01 3.585605E+00 + 1.050000E+01 9.000000E+01 4 6.375266E+02 8.826861E+01 1.926221E+01 6.372355E+02 + 1.050000E+01 9.000000E+01 5 2.799223E-04 -8.958176E+01 2.043348E-06 -2.799149E-04 + 1.050000E+01 9.000000E+01 6 6.807659E-05 1.797931E+02 -6.807614E-05 2.458727E-07 + 1.060000E+01 0.000000E+00 1 1.146553E+02 8.924791E+01 1.504978E+00 1.146454E+02 + 1.060000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.060000E+01 0.000000E+00 3 6.187998E+01 2.099505E+00 6.183844E+01 2.266978E+00 + 1.060000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.060000E+01 0.000000E+00 5 4.302150E+02 8.923714E+01 5.727894E+00 4.301769E+02 + 1.060000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.060000E+01 3.000000E+01 1 1.042095E+02 8.928232E+01 1.305299E+00 1.042013E+02 + 1.060000E+01 3.000000E+01 2 6.314794E+01 8.832440E+01 1.846480E+00 6.312094E+01 + 1.060000E+01 3.000000E+01 3 6.592982E+01 2.218868E+00 6.588039E+01 2.552597E+00 + 1.060000E+01 3.000000E+01 4 2.450438E+02 8.823080E+01 7.565379E+00 2.449270E+02 + 1.060000E+01 3.000000E+01 5 3.974218E+02 8.928361E+01 4.969038E+00 3.973907E+02 + 1.060000E+01 3.000000E+01 6 6.483076E+02 -3.223989E-01 6.482973E+02 -3.647957E+00 + 1.060000E+01 6.000000E+01 1 6.641848E+01 8.934158E+01 7.632339E-01 6.641409E+01 + 1.060000E+01 6.000000E+01 2 1.226696E+02 8.830415E+01 3.630279E+00 1.226159E+02 + 1.060000E+01 6.000000E+01 3 7.491222E+01 2.471537E+00 7.484253E+01 3.230445E+00 + 1.060000E+01 6.000000E+01 4 5.018592E+02 8.830099E+01 1.487966E+01 5.016385E+02 + 1.060000E+01 6.000000E+01 5 2.578091E+02 8.935396E+01 2.906878E+00 2.577927E+02 + 1.060000E+01 6.000000E+01 6 7.270218E+02 -3.091397E-01 7.270112E+02 -3.922631E+00 + 1.060000E+01 9.000000E+01 1 7.549281E-06 -8.891802E+01 1.425530E-07 -7.547935E-06 + 1.060000E+01 9.000000E+01 2 1.499921E+02 8.829495E+01 4.462903E+00 1.499257E+02 + 1.060000E+01 9.000000E+01 3 7.986166E+01 2.601855E+00 7.977934E+01 3.625347E+00 + 1.060000E+01 9.000000E+01 4 6.277375E+02 8.832988E+01 1.829544E+01 6.274709E+02 + 1.060000E+01 9.000000E+01 5 2.778549E-04 -8.959577E+01 1.960276E-06 -2.778480E-04 + 1.060000E+01 9.000000E+01 6 6.606242E-05 1.798073E+02 -6.606205E-05 2.221744E-07 + 1.070000E+01 0.000000E+00 1 1.141537E+02 8.926340E+01 1.467511E+00 1.141442E+02 + 1.070000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.070000E+01 0.000000E+00 3 6.393304E+01 2.094086E+00 6.389034E+01 2.336149E+00 + 1.070000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.070000E+01 0.000000E+00 5 4.438734E+02 8.925386E+01 5.780247E+00 4.438358E+02 + 1.070000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.070000E+01 3.000000E+01 1 1.035983E+02 8.929422E+01 1.276119E+00 1.035905E+02 + 1.070000E+01 3.000000E+01 2 6.281622E+01 8.838221E+01 1.773431E+00 6.279118E+01 + 1.070000E+01 3.000000E+01 3 6.795429E+01 2.206761E+00 6.790389E+01 2.616629E+00 + 1.070000E+01 3.000000E+01 4 2.430734E+02 8.829381E+01 7.237322E+00 2.429656E+02 + 1.070000E+01 3.000000E+01 5 4.087933E+02 8.929536E+01 5.027290E+00 4.087624E+02 + 1.070000E+01 3.000000E+01 6 6.328757E+02 -2.994595E-01 6.328670E+02 -3.307744E+00 + 1.070000E+01 6.000000E+01 1 6.582057E+01 8.934747E+01 7.495978E-01 6.581631E+01 + 1.070000E+01 6.000000E+01 2 1.215535E+02 8.836374E+01 3.470883E+00 1.215040E+02 + 1.070000E+01 6.000000E+01 3 7.683866E+01 2.444463E+00 7.676874E+01 3.277245E+00 + 1.070000E+01 6.000000E+01 4 4.953550E+02 8.836084E+01 1.416955E+01 4.951523E+02 + 1.070000E+01 6.000000E+01 5 2.638965E+02 8.935859E+01 2.954202E+00 2.638800E+02 + 1.070000E+01 6.000000E+01 6 7.070473E+02 -2.875706E-01 7.070384E+02 -3.548694E+00 + 1.070000E+01 9.000000E+01 1 7.455899E-06 -8.898923E+01 1.315240E-07 -7.454739E-06 + 1.070000E+01 9.000000E+01 2 1.483416E+02 8.835533E+01 4.257556E+00 1.482805E+02 + 1.070000E+01 9.000000E+01 3 8.171694E+01 2.566934E+00 8.163495E+01 3.659813E+00 + 1.070000E+01 9.000000E+01 4 6.181830E+02 8.838859E+01 1.738377E+01 6.179386E+02 + 1.070000E+01 9.000000E+01 5 2.758073E-04 -8.960943E+01 1.880126E-06 -2.758008E-04 + 1.070000E+01 9.000000E+01 6 6.413752E-05 1.798204E+02 -6.413721E-05 2.010338E-07 + 1.080000E+01 0.000000E+00 1 1.136280E+02 8.927855E+01 1.430734E+00 1.136190E+02 + 1.080000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.080000E+01 0.000000E+00 3 6.595620E+01 2.085848E+00 6.591250E+01 2.400599E+00 + 1.080000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.080000E+01 0.000000E+00 5 4.568948E+02 8.927005E+01 5.820706E+00 4.568578E+02 + 1.080000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.080000E+01 3.000000E+01 1 1.029741E+02 8.930618E+01 1.246922E+00 1.029666E+02 + 1.080000E+01 3.000000E+01 2 6.247221E+01 8.843774E+01 1.703198E+00 6.244899E+01 + 1.080000E+01 3.000000E+01 3 6.994787E+01 2.192204E+00 6.989668E+01 2.675635E+00 + 1.080000E+01 3.000000E+01 4 2.410707E+02 8.835420E+01 6.923707E+00 2.409713E+02 + 1.080000E+01 3.000000E+01 5 4.196074E+02 8.930720E+01 5.073658E+00 4.195768E+02 + 1.080000E+01 3.000000E+01 6 6.179302E+02 -2.784428E-01 6.179229E+02 -3.002970E+00 + 1.080000E+01 6.000000E+01 1 6.522710E+01 8.935410E+01 7.352954E-01 6.522296E+01 + 1.080000E+01 6.000000E+01 2 1.204439E+02 8.842086E+01 3.319156E+00 1.203982E+02 + 1.080000E+01 6.000000E+01 3 7.873296E+01 2.415946E+00 7.866298E+01 3.318888E+00 + 1.080000E+01 6.000000E+01 4 4.889547E+02 8.841821E+01 1.349714E+01 4.887684E+02 + 1.080000E+01 6.000000E+01 5 2.696635E+02 8.936408E+01 2.992888E+00 2.696469E+02 + 1.080000E+01 6.000000E+01 6 6.878823E+02 -2.677642E-01 6.878748E+02 -3.214714E+00 + 1.080000E+01 9.000000E+01 1 7.365016E-06 -8.905633E+01 1.212971E-07 -7.364017E-06 + 1.080000E+01 9.000000E+01 2 1.467195E+02 8.841316E+01 4.062960E+00 1.466632E+02 + 1.080000E+01 9.000000E+01 3 8.354046E+01 2.531108E+00 8.345895E+01 3.689297E+00 + 1.080000E+01 9.000000E+01 4 6.088626E+02 8.844485E+01 1.652410E+01 6.086384E+02 + 1.080000E+01 9.000000E+01 5 2.737784E-04 -8.962268E+01 1.802924E-06 -2.737724E-04 + 1.080000E+01 9.000000E+01 6 6.229666E-05 1.798325E+02 -6.229639E-05 1.821510E-07 + 1.090001E+01 0.000000E+00 1 1.130809E+02 8.929334E+01 1.394639E+00 1.130723E+02 + 1.090001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.090001E+01 0.000000E+00 3 6.795072E+01 2.075143E+00 6.790616E+01 2.460506E+00 + 1.090001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.090001E+01 0.000000E+00 5 4.693108E+02 8.928577E+01 5.850070E+00 4.692743E+02 + 1.090001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.090001E+01 3.000000E+01 1 1.023384E+02 8.931818E+01 1.217809E+00 1.023312E+02 + 1.090001E+01 3.000000E+01 2 6.211732E+01 8.849104E+01 1.635760E+00 6.209578E+01 + 1.090001E+01 3.000000E+01 3 7.191013E+01 2.175603E+00 7.185829E+01 2.729875E+00 + 1.090001E+01 3.000000E+01 4 2.390453E+02 8.841207E+01 6.624189E+00 2.389535E+02 + 1.090001E+01 3.000000E+01 5 4.299111E+02 8.931908E+01 5.109051E+00 4.298808E+02 + 1.090001E+01 3.000000E+01 6 6.034572E+02 -2.591694E-01 6.034510E+02 -2.729645E+00 + 1.090001E+01 6.000000E+01 1 6.463866E+01 8.936135E+01 7.204774E-01 6.463465E+01 + 1.090001E+01 6.000000E+01 2 1.193423E+02 8.847560E+01 3.174819E+00 1.193001E+02 + 1.090001E+01 6.000000E+01 3 8.059480E+01 2.386306E+00 8.052491E+01 3.355714E+00 + 1.090001E+01 6.000000E+01 4 4.826599E+02 8.847315E+01 1.286060E+01 4.824885E+02 + 1.090001E+01 6.000000E+01 5 2.751201E+02 8.937035E+01 3.023324E+00 2.751035E+02 + 1.090001E+01 6.000000E+01 6 6.694854E+02 -2.495624E-01 6.694791E+02 -2.916059E+00 + 1.090001E+01 9.000000E+01 1 7.276533E-06 -8.911949E+01 1.118204E-07 -7.275674E-06 + 1.090001E+01 9.000000E+01 2 1.451256E+02 8.846854E+01 3.878605E+00 1.450737E+02 + 1.090001E+01 9.000000E+01 3 8.533361E+01 2.494587E+00 8.525275E+01 3.714146E+00 + 1.090001E+01 9.000000E+01 4 5.997737E+02 8.849873E+01 1.571356E+01 5.995679E+02 + 1.090001E+01 9.000000E+01 5 2.717693E-04 -8.963556E+01 1.728637E-06 -2.717638E-04 + 1.090001E+01 9.000000E+01 6 6.053559E-05 1.798436E+02 -6.053536E-05 1.652639E-07 + 1.100001E+01 0.000000E+00 1 1.125144E+02 8.930782E+01 1.359243E+00 1.125062E+02 + 1.100001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.100001E+01 0.000000E+00 3 6.991489E+01 2.062274E+00 6.986961E+01 2.515937E+00 + 1.100001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.100001E+01 0.000000E+00 5 4.811365E+02 8.930108E+01 5.869034E+00 4.811007E+02 + 1.100001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.100001E+01 3.000000E+01 1 1.016928E+02 8.933015E+01 1.188864E+00 1.016858E+02 + 1.100001E+01 3.000000E+01 2 6.175324E+01 8.854217E+01 1.571076E+00 6.173325E+01 + 1.100001E+01 3.000000E+01 3 7.384133E+01 2.157180E+00 7.378900E+01 2.779461E+00 + 1.100001E+01 3.000000E+01 4 2.370016E+02 8.846749E+01 6.338412E+00 2.369169E+02 + 1.100001E+01 3.000000E+01 5 4.396971E+02 8.933101E+01 5.133879E+00 4.396672E+02 + 1.100001E+01 3.000000E+01 6 5.894427E+02 -2.414777E-01 5.894375E+02 -2.484246E+00 + 1.100001E+01 6.000000E+01 1 6.405579E+01 8.936913E+01 7.052865E-01 6.405190E+01 + 1.100001E+01 6.000000E+01 2 1.182499E+02 8.852805E+01 3.037569E+00 1.182109E+02 + 1.100001E+01 6.000000E+01 3 8.242564E+01 2.355674E+00 8.235598E+01 3.387915E+00 + 1.100001E+01 6.000000E+01 4 4.764743E+02 8.852579E+01 1.225823E+01 4.763166E+02 + 1.100001E+01 6.000000E+01 5 2.802826E+02 8.937723E+01 3.046450E+00 2.802660E+02 + 1.100001E+01 6.000000E+01 6 6.518202E+02 -2.328204E-01 6.518148E+02 -2.648653E+00 + 1.100001E+01 9.000000E+01 1 7.190376E-06 -8.917889E+01 1.030418E-07 -7.189638E-06 + 1.100001E+01 9.000000E+01 2 1.435599E+02 8.852155E+01 3.703973E+00 1.435121E+02 + 1.100001E+01 9.000000E+01 3 8.709569E+01 2.457584E+00 8.701558E+01 3.734643E+00 + 1.100001E+01 9.000000E+01 4 5.909086E+02 8.855032E+01 1.494944E+01 5.907194E+02 + 1.100001E+01 9.000000E+01 5 2.697787E-04 -8.964803E+01 1.657267E-06 -2.697736E-04 + 1.100001E+01 9.000000E+01 6 5.884979E-05 1.798538E+02 -5.884960E-05 1.501424E-07 + 1.110001E+01 0.000000E+00 1 1.119316E+02 8.932198E+01 1.324538E+00 1.119238E+02 + 1.110001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.110001E+01 0.000000E+00 3 7.184986E+01 2.047471E+00 7.180399E+01 2.567016E+00 + 1.110001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.110001E+01 0.000000E+00 5 4.924015E+02 8.931596E+01 5.878577E+00 4.923664E+02 + 1.110001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.110001E+01 3.000000E+01 1 1.010397E+02 8.934211E+01 1.160147E+00 1.010330E+02 + 1.110001E+01 3.000000E+01 2 6.138131E+01 8.859121E+01 1.509093E+00 6.136276E+01 + 1.110001E+01 3.000000E+01 3 7.574242E+01 2.137134E+00 7.568974E+01 2.824539E+00 + 1.110001E+01 3.000000E+01 4 2.349445E+02 8.852053E+01 6.065991E+00 2.348662E+02 + 1.110001E+01 3.000000E+01 5 4.489980E+02 8.934286E+01 5.149603E+00 4.489685E+02 + 1.110001E+01 3.000000E+01 6 5.758735E+02 -2.252217E-01 5.758691E+02 -2.263673E+00 + 1.110001E+01 6.000000E+01 1 6.347852E+01 8.937733E+01 6.898419E-01 6.347477E+01 + 1.110001E+01 6.000000E+01 2 1.171672E+02 8.857825E+01 2.907109E+00 1.171311E+02 + 1.110001E+01 6.000000E+01 3 8.422581E+01 2.324244E+00 8.415652E+01 3.415742E+00 + 1.110001E+01 6.000000E+01 4 4.703987E+02 8.857618E+01 1.168838E+01 4.702535E+02 + 1.110001E+01 6.000000E+01 5 2.851645E+02 8.938467E+01 3.062518E+00 2.851480E+02 + 1.110001E+01 6.000000E+01 6 6.348505E+02 -2.174072E-01 6.348459E+02 -2.408916E+00 + 1.110001E+01 9.000000E+01 1 7.106396E-06 -8.923474E+01 9.491247E-08 -7.105763E-06 + 1.110001E+01 9.000000E+01 2 1.420220E+02 8.857228E+01 3.538598E+00 1.419779E+02 + 1.110001E+01 9.000000E+01 3 8.882748E+01 2.420229E+00 8.874824E+01 3.751043E+00 + 1.110001E+01 9.000000E+01 4 5.822624E+02 8.859971E+01 1.422893E+01 5.820885E+02 + 1.110001E+01 9.000000E+01 5 2.678100E-04 -8.966010E+01 1.588743E-06 -2.678053E-04 + 1.110001E+01 9.000000E+01 6 5.723511E-05 1.798633E+02 -5.723494E-05 1.365836E-07 + 1.120001E+01 0.000000E+00 1 1.113342E+02 8.933583E+01 1.290555E+00 1.113267E+02 + 1.120001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.120001E+01 0.000000E+00 3 7.375426E+01 2.031043E+00 7.370792E+01 2.613922E+00 + 1.120001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.120001E+01 0.000000E+00 5 5.031029E+02 8.933041E+01 5.879393E+00 5.030686E+02 + 1.120001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.120001E+01 3.000000E+01 1 1.003808E+02 8.935400E+01 1.131748E+00 1.003744E+02 + 1.120001E+01 3.000000E+01 2 6.100290E+01 8.863823E+01 1.449747E+00 6.098566E+01 + 1.120001E+01 3.000000E+01 3 7.761174E+01 2.115768E+00 7.755883E+01 2.865326E+00 + 1.120001E+01 3.000000E+01 4 2.328806E+02 8.857130E+01 5.806410E+00 2.328082E+02 + 1.120001E+01 3.000000E+01 5 4.578250E+02 8.935469E+01 5.156323E+00 4.577959E+02 + 1.120001E+01 3.000000E+01 6 5.627352E+02 -2.102707E-01 5.627314E+02 -2.065186E+00 + 1.120001E+01 6.000000E+01 1 6.290738E+01 8.938589E+01 6.742471E-01 6.290377E+01 + 1.120001E+01 6.000000E+01 2 1.160951E+02 8.862632E+01 2.783134E+00 1.160617E+02 + 1.120001E+01 6.000000E+01 3 8.599400E+01 2.292254E+00 8.592519E+01 3.439478E+00 + 1.120001E+01 6.000000E+01 4 4.644374E+02 8.862442E+01 1.114933E+01 4.643036E+02 + 1.120001E+01 6.000000E+01 5 2.897723E+02 8.939249E+01 3.072418E+00 2.897560E+02 + 1.120001E+01 6.000000E+01 6 6.185414E+02 -2.032062E-01 6.185375E+02 -2.193725E+00 + 1.120001E+01 9.000000E+01 1 7.024513E-06 -8.928721E+01 8.738753E-08 -7.023969E-06 + 1.120001E+01 9.000000E+01 2 1.405123E+02 8.862083E+01 3.381952E+00 1.404716E+02 + 1.120001E+01 9.000000E+01 3 9.052944E+01 2.382656E+00 9.045117E+01 3.763600E+00 + 1.120001E+01 9.000000E+01 4 5.738329E+02 8.864698E+01 1.354965E+01 5.736729E+02 + 1.120001E+01 9.000000E+01 5 2.658614E-04 -8.967177E+01 1.523023E-06 -2.658571E-04 + 1.120001E+01 9.000000E+01 6 5.568777E-05 1.798720E+02 -5.568763E-05 1.244114E-07 + 1.130001E+01 0.000000E+00 1 1.107238E+02 8.934938E+01 1.257293E+00 1.107167E+02 + 1.130001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.130001E+01 0.000000E+00 3 7.562865E+01 2.013171E+00 7.558198E+01 2.656777E+00 + 1.130001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.130001E+01 0.000000E+00 5 5.132776E+02 8.934452E+01 5.871973E+00 5.132441E+02 + 1.130001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.130001E+01 3.000000E+01 1 9.971642E+01 8.936581E+01 1.103706E+00 9.971030E+01 + 1.130001E+01 3.000000E+01 2 6.061891E+01 8.868329E+01 1.392957E+00 6.060290E+01 + 1.130001E+01 3.000000E+01 3 7.945041E+01 2.093302E+00 7.939739E+01 2.902076E+00 + 1.130001E+01 3.000000E+01 4 2.308129E+02 8.861987E+01 5.559219E+00 2.307459E+02 + 1.130001E+01 3.000000E+01 5 4.662014E+02 8.936644E+01 5.154998E+00 4.661729E+02 + 1.130001E+01 3.000000E+01 6 5.500144E+02 -1.965068E-01 5.500112E+02 -1.886376E+00 + 1.130001E+01 6.000000E+01 1 6.234248E+01 8.939471E+01 6.585937E-01 6.233900E+01 + 1.130001E+01 6.000000E+01 2 1.150346E+02 8.867235E+01 2.665341E+00 1.150037E+02 + 1.130001E+01 6.000000E+01 3 8.773208E+01 2.259831E+00 8.766385E+01 3.459388E+00 + 1.130001E+01 6.000000E+01 4 4.585868E+02 8.867059E+01 1.063947E+01 4.584634E+02 + 1.130001E+01 6.000000E+01 5 2.941199E+02 8.940067E+01 3.076541E+00 2.941038E+02 + 1.130001E+01 6.000000E+01 6 6.028621E+02 -1.901099E-01 6.028588E+02 -2.000319E+00 + 1.130001E+01 9.000000E+01 1 6.944631E-06 -8.933647E+01 8.042228E-08 -6.944166E-06 + 1.130001E+01 9.000000E+01 2 1.390304E+02 8.866728E+01 3.233606E+00 1.389928E+02 + 1.130001E+01 9.000000E+01 3 9.220133E+01 2.345079E+00 9.212411E+01 3.772687E+00 + 1.130001E+01 9.000000E+01 4 5.656148E+02 8.869221E+01 1.290913E+01 5.654675E+02 + 1.130001E+01 9.000000E+01 5 2.639317E-04 -8.968305E+01 1.460027E-06 -2.639277E-04 + 1.130001E+01 9.000000E+01 6 5.420435E-05 1.798801E+02 -5.420423E-05 1.134699E-07 + 1.140001E+01 0.000000E+00 1 1.101025E+02 8.936264E+01 1.224765E+00 1.100957E+02 + 1.140001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.140001E+01 0.000000E+00 3 7.747333E+01 1.994088E+00 7.742641E+01 2.695791E+00 + 1.140001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.140001E+01 0.000000E+00 5 5.229449E+02 8.935825E+01 5.857249E+00 5.229121E+02 + 1.140001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.140001E+01 3.000000E+01 1 9.904882E+01 8.937751E+01 1.076087E+00 9.904298E+01 + 1.140001E+01 3.000000E+01 2 6.023065E+01 8.872647E+01 1.338648E+00 6.021577E+01 + 1.140001E+01 3.000000E+01 3 8.125858E+01 2.069893E+00 8.120556E+01 2.934945E+00 + 1.140001E+01 3.000000E+01 4 2.287463E+02 8.866636E+01 5.323910E+00 2.286843E+02 + 1.140001E+01 3.000000E+01 5 4.741358E+02 8.937807E+01 5.146564E+00 4.741078E+02 + 1.140001E+01 3.000000E+01 6 5.376979E+02 -1.838224E-01 5.376951E+02 -1.725097E+00 + 1.140001E+01 6.000000E+01 1 6.178437E+01 8.940375E+01 6.429548E-01 6.178102E+01 + 1.140001E+01 6.000000E+01 2 1.139862E+02 8.871640E+01 2.553433E+00 1.139576E+02 + 1.140001E+01 6.000000E+01 3 8.943973E+01 2.227108E+00 8.937217E+01 3.475679E+00 + 1.140001E+01 6.000000E+01 4 4.528462E+02 8.871477E+01 1.015718E+01 4.527323E+02 + 1.140001E+01 6.000000E+01 5 2.982212E+02 8.940913E+01 3.075377E+00 2.982053E+02 + 1.140001E+01 6.000000E+01 6 5.877830E+02 -1.780215E-01 5.877802E+02 -1.826275E+00 + 1.140001E+01 9.000000E+01 1 6.866730E-06 -8.938273E+01 7.397684E-08 -6.866332E-06 + 1.140001E+01 9.000000E+01 2 1.375760E+02 8.871172E+01 3.093096E+00 1.375413E+02 + 1.140001E+01 9.000000E+01 3 9.384401E+01 2.307541E+00 9.376791E+01 3.778470E+00 + 1.140001E+01 9.000000E+01 4 5.576008E+02 8.873551E+01 1.230498E+01 5.574650E+02 + 1.140001E+01 9.000000E+01 5 2.620240E-04 -8.969394E+01 1.399698E-06 -2.620202E-04 + 1.140001E+01 9.000000E+01 6 5.278120E-05 1.798875E+02 -5.278110E-05 1.036221E-07 + 1.150001E+01 0.000000E+00 1 1.094725E+02 8.937561E+01 1.192975E+00 1.094660E+02 + 1.150001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.150001E+01 0.000000E+00 3 7.928864E+01 1.973968E+00 7.924158E+01 2.731131E+00 + 1.150001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.150001E+01 0.000000E+00 5 5.321284E+02 8.937166E+01 5.835532E+00 5.320964E+02 + 1.150001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.150001E+01 3.000000E+01 1 9.837859E+01 8.938910E+01 1.048917E+00 9.837300E+01 + 1.150001E+01 3.000000E+01 2 5.983892E+01 8.876785E+01 1.286740E+00 5.982508E+01 + 1.150001E+01 3.000000E+01 3 8.303709E+01 2.045689E+00 8.298417E+01 2.964127E+00 + 1.150001E+01 3.000000E+01 4 2.266836E+02 8.871083E+01 5.100006E+00 2.266263E+02 + 1.150001E+01 3.000000E+01 5 4.816543E+02 8.938961E+01 5.131142E+00 4.816269E+02 + 1.150001E+01 3.000000E+01 6 5.257704E+02 -1.721227E-01 5.257680E+02 -1.579469E+00 + 1.150001E+01 6.000000E+01 1 6.123268E+01 8.941293E+01 6.273907E-01 6.122946E+01 + 1.150001E+01 6.000000E+01 2 1.129500E+02 8.875856E+01 2.447115E+00 1.129235E+02 + 1.150001E+01 6.000000E+01 3 9.111797E+01 2.194224E+00 9.105116E+01 3.488640E+00 + 1.150001E+01 6.000000E+01 4 4.472183E+02 8.875706E+01 9.700960E+00 4.471131E+02 + 1.150001E+01 6.000000E+01 5 3.020876E+02 8.941781E+01 3.069503E+00 3.020721E+02 + 1.150001E+01 6.000000E+01 6 5.732735E+02 -1.668540E-01 5.732711E+02 -1.669457E+00 + 1.150001E+01 9.000000E+01 1 6.790643E-06 -8.942614E+01 6.801285E-08 -6.790302E-06 + 1.150001E+01 9.000000E+01 2 1.361487E+02 8.875424E+01 2.959986E+00 1.361165E+02 + 1.150001E+01 9.000000E+01 3 9.545879E+01 2.270139E+00 9.538387E+01 3.781222E+00 + 1.150001E+01 9.000000E+01 4 5.497868E+02 8.877695E+01 1.173502E+01 5.496616E+02 + 1.150001E+01 9.000000E+01 5 2.601389E-04 -8.970444E+01 1.341961E-06 -2.601354E-04 + 1.150001E+01 9.000000E+01 6 5.141528E-05 1.798944E+02 -5.141519E-05 9.474749E-08 + 1.160001E+01 0.000000E+00 1 1.088344E+02 8.938829E+01 1.161933E+00 1.088281E+02 + 1.160001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.160001E+01 0.000000E+00 3 8.107460E+01 1.952964E+00 8.102750E+01 2.762945E+00 + 1.160001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.160001E+01 0.000000E+00 5 5.408304E+02 8.938472E+01 5.807692E+00 5.407993E+02 + 1.160001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.160001E+01 3.000000E+01 1 9.770663E+01 8.940054E+01 1.022247E+00 9.770128E+01 + 1.160001E+01 3.000000E+01 2 5.944448E+01 8.880750E+01 1.237135E+00 5.943161E+01 + 1.160001E+01 3.000000E+01 3 8.478502E+01 2.020885E+00 8.473228E+01 2.989840E+00 + 1.160001E+01 3.000000E+01 4 2.246288E+02 8.875339E+01 4.886991E+00 2.245756E+02 + 1.160001E+01 3.000000E+01 5 4.887805E+02 8.940102E+01 5.109688E+00 4.887538E+02 + 1.160001E+01 3.000000E+01 6 5.142203E+02 -1.613197E-01 5.142183E+02 -1.447816E+00 + 1.160001E+01 6.000000E+01 1 6.068818E+01 8.942224E+01 6.119623E-01 6.068510E+01 + 1.160001E+01 6.000000E+01 2 1.119269E+02 8.879893E+01 2.346122E+00 1.119023E+02 + 1.160001E+01 6.000000E+01 3 9.276630E+01 2.161283E+00 9.270030E+01 3.498454E+00 + 1.160001E+01 6.000000E+01 4 4.417021E+02 8.879754E+01 9.269327E+00 4.416049E+02 + 1.160001E+01 6.000000E+01 5 3.057259E+02 8.942667E+01 3.059182E+00 3.057105E+02 + 1.160001E+01 6.000000E+01 6 5.593065E+02 -1.565280E-01 5.593044E+02 -1.527984E+00 + 1.160001E+01 9.000000E+01 1 6.716354E-06 -8.946687E+01 6.249444E-08 -6.716063E-06 + 1.160001E+01 9.000000E+01 2 1.347481E+02 8.879493E+01 2.833873E+00 1.347183E+02 + 1.160001E+01 9.000000E+01 3 9.704471E+01 2.232968E+00 9.697102E+01 3.781131E+00 + 1.160001E+01 9.000000E+01 4 5.421680E+02 8.881660E+01 1.119728E+01 5.420523E+02 + 1.160001E+01 9.000000E+01 5 2.582736E-04 -8.971455E+01 1.286725E-06 -2.582704E-04 + 1.160001E+01 9.000000E+01 6 5.010374E-05 1.799008E+02 -5.010366E-05 8.673994E-08 + 1.170001E+01 0.000000E+00 1 1.081895E+02 8.940069E+01 1.131644E+00 1.081836E+02 + 1.170001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.170001E+01 0.000000E+00 3 8.283031E+01 1.931236E+00 8.278326E+01 2.791385E+00 + 1.170001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.170001E+01 0.000000E+00 5 5.490875E+02 8.939746E+01 5.774291E+00 5.490571E+02 + 1.170001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.170001E+01 3.000000E+01 1 9.703459E+01 8.941183E+01 9.961008E-01 9.702948E+01 + 1.170001E+01 3.000000E+01 2 5.904829E+01 8.884548E+01 1.189748E+00 5.903631E+01 + 1.170001E+01 3.000000E+01 3 8.650333E+01 1.995570E+00 8.645087E+01 3.012239E+00 + 1.170001E+01 3.000000E+01 4 2.225845E+02 8.879410E+01 4.684371E+00 2.225352E+02 + 1.170001E+01 3.000000E+01 5 4.955051E+02 8.941225E+01 5.082895E+00 4.954790E+02 + 1.170001E+01 3.000000E+01 6 5.030318E+02 -1.513360E-01 5.030301E+02 -1.328662E+00 + 1.170001E+01 6.000000E+01 1 6.015052E+01 8.943160E+01 5.967079E-01 6.014756E+01 + 1.170001E+01 6.000000E+01 2 1.109169E+02 8.883756E+01 2.250171E+00 1.108940E+02 + 1.170001E+01 6.000000E+01 3 9.438599E+01 2.128350E+00 9.432087E+01 3.505323E+00 + 1.170001E+01 6.000000E+01 4 4.362974E+02 8.883627E+01 8.860934E+00 4.362074E+02 + 1.170001E+01 6.000000E+01 5 3.091421E+02 8.943562E+01 3.045091E+00 3.091271E+02 + 1.170001E+01 6.000000E+01 6 5.458569E+02 -1.469714E-01 5.458551E+02 -1.400195E+00 + 1.170001E+01 9.000000E+01 1 6.643791E-06 -8.950507E+01 5.738891E-08 -6.643544E-06 + 1.170001E+01 9.000000E+01 2 1.333739E+02 8.883386E+01 2.714365E+00 1.333463E+02 + 1.170001E+01 9.000000E+01 3 9.860223E+01 2.196118E+00 9.852982E+01 3.778448E+00 + 1.170001E+01 9.000000E+01 4 5.347398E+02 8.885456E+01 1.068966E+01 5.346329E+02 + 1.170001E+01 9.000000E+01 5 2.564288E-04 -8.972430E+01 1.233911E-06 -2.564258E-04 + 1.170001E+01 9.000000E+01 6 4.884357E-05 1.799067E+02 -4.884350E-05 7.950538E-08 + 1.180001E+01 0.000000E+00 1 1.075397E+02 8.941280E+01 1.102103E+00 1.075341E+02 + 1.180001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.180001E+01 0.000000E+00 3 8.455796E+01 1.908912E+00 8.451103E+01 2.816679E+00 + 1.180001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.180001E+01 0.000000E+00 5 5.569067E+02 8.940990E+01 5.735585E+00 5.568771E+02 + 1.180001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.180001E+01 3.000000E+01 1 9.636280E+01 8.942295E+01 9.705013E-01 9.635791E+01 + 1.180001E+01 3.000000E+01 2 5.865092E+01 8.888188E+01 1.144490E+00 5.863975E+01 + 1.180001E+01 3.000000E+01 3 8.819274E+01 1.969882E+00 8.814062E+01 3.031551E+00 + 1.180001E+01 3.000000E+01 4 2.205512E+02 8.883305E+01 4.491670E+00 2.205054E+02 + 1.180001E+01 3.000000E+01 5 5.018663E+02 8.942335E+01 5.050970E+00 5.018409E+02 + 1.180001E+01 3.000000E+01 6 4.921938E+02 -1.421004E-01 4.921923E+02 -1.220698E+00 + 1.180001E+01 6.000000E+01 1 5.961980E+01 8.944099E+01 5.816728E-01 5.961696E+01 + 1.180001E+01 6.000000E+01 2 1.099202E+02 8.887455E+01 2.159002E+00 1.098990E+02 + 1.180001E+01 6.000000E+01 3 9.597688E+01 2.095549E+00 9.591269E+01 3.509498E+00 + 1.180001E+01 6.000000E+01 4 4.309995E+02 8.887337E+01 8.474439E+00 4.309162E+02 + 1.180001E+01 6.000000E+01 5 3.123563E+02 8.944466E+01 3.027450E+00 3.123416E+02 + 1.180001E+01 6.000000E+01 6 5.328994E+02 -1.381192E-01 5.328979E+02 -1.284625E+00 + 1.180001E+01 9.000000E+01 1 6.572867E-06 -8.954091E+01 5.266531E-08 -6.572656E-06 + 1.180001E+01 9.000000E+01 2 1.320260E+02 8.887112E+01 2.601086E+00 1.320003E+02 + 1.180001E+01 9.000000E+01 3 1.001325E+02 2.159629E+00 1.000614E+02 3.773364E+00 + 1.180001E+01 9.000000E+01 4 5.274958E+02 8.889090E+01 1.021038E+01 5.273970E+02 + 1.180001E+01 9.000000E+01 5 2.546061E-04 -8.973369E+01 1.183421E-06 -2.546033E-04 + 1.180001E+01 9.000000E+01 6 4.763217E-05 1.799122E+02 -4.763211E-05 7.296139E-08 + 1.190001E+01 0.000000E+00 1 1.068864E+02 8.942465E+01 1.073315E+00 1.068810E+02 + 1.190001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.190001E+01 0.000000E+00 3 8.625607E+01 1.886070E+00 8.620934E+01 2.838876E+00 + 1.190001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.190001E+01 0.000000E+00 5 5.643052E+02 8.942200E+01 5.692641E+00 5.642765E+02 + 1.190001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.190001E+01 3.000000E+01 1 9.569206E+01 8.943389E+01 9.454651E-01 9.568739E+01 + 1.190001E+01 3.000000E+01 2 5.825286E+01 8.891676E+01 1.101272E+00 5.824245E+01 + 1.190001E+01 3.000000E+01 3 8.985291E+01 1.943876E+00 8.980120E+01 3.047858E+00 + 1.190001E+01 3.000000E+01 4 2.185332E+02 8.887034E+01 4.308407E+00 2.184907E+02 + 1.190001E+01 3.000000E+01 5 5.078765E+02 8.943426E+01 5.014700E+00 5.078517E+02 + 1.190001E+01 3.000000E+01 6 4.816945E+02 -1.335487E-01 4.816932E+02 -1.122764E+00 + 1.190001E+01 6.000000E+01 1 5.909634E+01 8.945039E+01 5.668811E-01 5.909362E+01 + 1.190001E+01 6.000000E+01 2 1.089371E+02 8.890997E+01 2.072361E+00 1.089174E+02 + 1.190001E+01 6.000000E+01 3 9.754016E+01 2.062865E+00 9.747695E+01 3.511057E+00 + 1.190001E+01 6.000000E+01 4 4.258096E+02 8.890886E+01 8.108605E+00 4.257324E+02 + 1.190001E+01 6.000000E+01 5 3.153695E+02 8.945371E+01 3.006876E+00 3.153551E+02 + 1.190001E+01 6.000000E+01 6 5.204125E+02 -1.299123E-01 5.204112E+02 -1.179981E+00 + 1.190001E+01 9.000000E+01 1 6.503536E-06 -8.957452E+01 4.829484E-08 -6.503357E-06 + 1.190001E+01 9.000000E+01 2 1.307033E+02 8.890679E+01 2.493684E+00 1.306795E+02 + 1.190001E+01 9.000000E+01 3 1.016361E+02 2.123506E+00 1.015663E+02 3.765992E+00 + 1.190001E+01 9.000000E+01 4 5.204306E+02 8.892568E+01 9.757710E+00 5.203391E+02 + 1.190001E+01 9.000000E+01 5 2.528031E-04 -8.974271E+01 1.135188E-06 -2.528005E-04 + 1.190001E+01 9.000000E+01 6 4.646727E-05 1.799173E+02 -4.646722E-05 6.703487E-08 + 1.200001E+01 0.000000E+00 1 1.062292E+02 8.943621E+01 1.045279E+00 1.062241E+02 + 1.200001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.200001E+01 0.000000E+00 3 8.792551E+01 1.862878E+00 8.787904E+01 2.858249E+00 + 1.200001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.200001E+01 0.000000E+00 5 5.713010E+02 8.943381E+01 5.645458E+00 5.712731E+02 + 1.200001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.200001E+01 3.000000E+01 1 9.502312E+01 8.944466E+01 9.210083E-01 9.501866E+01 + 1.200001E+01 3.000000E+01 2 5.785476E+01 8.895018E+01 1.059999E+00 5.784505E+01 + 1.200001E+01 3.000000E+01 3 9.148434E+01 1.917713E+00 9.143310E+01 3.061446E+00 + 1.200001E+01 3.000000E+01 4 2.165313E+02 8.890603E+01 4.134084E+00 2.164918E+02 + 1.200001E+01 3.000000E+01 5 5.135402E+02 8.944498E+01 4.974524E+00 5.135161E+02 + 1.200001E+01 3.000000E+01 6 4.715199E+02 -1.256225E-01 4.715188E+02 -1.033819E+00 + 1.200001E+01 6.000000E+01 1 5.857990E+01 8.945974E+01 5.523602E-01 5.857729E+01 + 1.200001E+01 6.000000E+01 2 1.079678E+02 8.894389E+01 1.990017E+00 1.079494E+02 + 1.200001E+01 6.000000E+01 3 9.907504E+01 2.030438E+00 9.901284E+01 3.510269E+00 + 1.200001E+01 6.000000E+01 4 4.207267E+02 8.894286E+01 7.762195E+00 4.206550E+02 + 1.200001E+01 6.000000E+01 5 3.181928E+02 8.946277E+01 2.983491E+00 3.181788E+02 + 1.200001E+01 6.000000E+01 6 5.083714E+02 -1.222968E-01 5.083702E+02 -1.085109E+00 + 1.200001E+01 9.000000E+01 1 6.435780E-06 -8.960605E+01 4.425109E-08 -6.435627E-06 + 1.200001E+01 9.000000E+01 2 1.294058E+02 8.894093E+01 2.391825E+00 1.293837E+02 + 1.200001E+01 9.000000E+01 3 1.031123E+02 2.087878E+00 1.030439E+02 3.756617E+00 + 1.200001E+01 9.000000E+01 4 5.135405E+02 8.895899E+01 9.330029E+00 5.134557E+02 + 1.200001E+01 9.000000E+01 5 2.510214E-04 -8.975141E+01 1.089106E-06 -2.510191E-04 + 1.200001E+01 9.000000E+01 6 4.534634E-05 1.799221E+02 -4.534630E-05 6.166076E-08 + 1.210001E+01 0.000000E+00 1 1.055706E+02 8.944751E+01 1.017983E+00 1.055657E+02 + 1.210001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.210001E+01 0.000000E+00 3 8.956721E+01 1.839370E+00 8.952106E+01 2.874888E+00 + 1.210001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.210001E+01 0.000000E+00 5 5.779141E+02 8.944532E+01 5.594736E+00 5.778870E+02 + 1.210001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.210001E+01 3.000000E+01 1 9.435610E+01 8.945523E+01 8.971375E-01 9.435184E+01 + 1.210001E+01 3.000000E+01 2 5.745713E+01 8.898222E+01 1.020595E+00 5.744807E+01 + 1.210001E+01 3.000000E+01 3 9.308748E+01 1.891421E+00 9.303676E+01 3.072401E+00 + 1.210001E+01 3.000000E+01 4 2.145465E+02 8.894019E+01 3.968291E+00 2.145098E+02 + 1.210001E+01 3.000000E+01 5 5.188732E+02 8.945552E+01 4.930748E+00 5.188497E+02 + 1.210001E+01 3.000000E+01 6 4.616594E+02 -1.182696E-01 4.616584E+02 -9.529539E-01 + 1.210001E+01 6.000000E+01 1 5.807073E+01 8.946905E+01 5.381309E-01 5.806824E+01 + 1.210001E+01 6.000000E+01 2 1.070119E+02 8.897638E+01 1.911727E+00 1.069948E+02 + 1.210001E+01 6.000000E+01 3 1.005827E+02 1.998309E+00 1.005216E+02 3.507320E+00 + 1.210001E+01 6.000000E+01 4 4.157474E+02 8.897543E+01 7.434075E+00 4.156809E+02 + 1.210001E+01 6.000000E+01 5 3.208337E+02 8.947179E+01 2.957735E+00 3.208201E+02 + 1.210001E+01 6.000000E+01 6 4.967585E+02 -1.152239E-01 4.967575E+02 -9.989983E-01 + 1.210001E+01 9.000000E+01 1 6.369472E-06 -8.963560E+01 4.050915E-08 -6.369344E-06 + 1.210001E+01 9.000000E+01 2 1.281328E+02 8.897363E+01 2.295185E+00 1.281122E+02 + 1.210001E+01 9.000000E+01 3 1.045628E+02 2.052713E+00 1.044957E+02 3.745329E+00 + 1.210001E+01 9.000000E+01 4 5.068209E+02 8.899091E+01 8.925686E+00 5.067423E+02 + 1.210001E+01 9.000000E+01 5 2.492595E-04 -8.975977E+01 1.045091E-06 -2.492573E-04 + 1.210001E+01 9.000000E+01 6 4.426733E-05 1.799265E+02 -4.426729E-05 5.678195E-08 + 1.220001E+01 0.000000E+00 1 1.049102E+02 8.945853E+01 9.914271E-01 1.049055E+02 + 1.220001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.220001E+01 0.000000E+00 3 9.118073E+01 1.815689E+00 9.113495E+01 2.889012E+00 + 1.220001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.220001E+01 0.000000E+00 5 5.841580E+02 8.945654E+01 5.540733E+00 5.841317E+02 + 1.220001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.220001E+01 3.000000E+01 1 9.369230E+01 8.946560E+01 8.738610E-01 9.368822E+01 + 1.220001E+01 3.000000E+01 2 5.706032E+01 8.901293E+01 9.829652E-01 5.705185E+01 + 1.220001E+01 3.000000E+01 3 9.466312E+01 1.865110E+00 9.461298E+01 3.080958E+00 + 1.220001E+01 3.000000E+01 4 2.125812E+02 8.897290E+01 3.810581E+00 2.125471E+02 + 1.220001E+01 3.000000E+01 5 5.239091E+02 8.946588E+01 4.883858E+00 5.238863E+02 + 1.220001E+01 3.000000E+01 6 4.521007E+02 -1.114424E-01 4.520999E+02 -8.793516E-01 + 1.220001E+01 6.000000E+01 1 5.756867E+01 8.947827E+01 5.242051E-01 5.756628E+01 + 1.220001E+01 6.000000E+01 2 1.060700E+02 8.900750E+01 1.837288E+00 1.060541E+02 + 1.220001E+01 6.000000E+01 3 1.020632E+02 1.966529E+00 1.020031E+02 3.502366E+00 + 1.220001E+01 6.000000E+01 4 4.108702E+02 8.900661E+01 7.123251E+00 4.108085E+02 + 1.220001E+01 6.000000E+01 5 3.233058E+02 8.948078E+01 2.929794E+00 3.232925E+02 + 1.220001E+01 6.000000E+01 6 4.855527E+02 -1.086493E-01 4.855518E+02 -9.207476E-01 + 1.220001E+01 9.000000E+01 1 6.304601E-06 -8.966332E+01 3.704645E-08 -6.304493E-06 + 1.220001E+01 9.000000E+01 2 1.268837E+02 8.900494E+01 2.203476E+00 1.268646E+02 + 1.220001E+01 9.000000E+01 3 1.059868E+02 2.018099E+00 1.059210E+02 3.732344E+00 + 1.220001E+01 9.000000E+01 4 5.002638E+02 8.902147E+01 8.543369E+00 5.001908E+02 + 1.220001E+01 9.000000E+01 5 2.475191E-04 -8.976781E+01 1.003075E-06 -2.475171E-04 + 1.220001E+01 9.000000E+01 6 4.322813E-05 1.799306E+02 -4.322810E-05 5.234746E-08 + 1.230001E+01 0.000000E+00 1 1.042497E+02 8.946930E+01 9.655973E-01 1.042452E+02 + 1.230001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.230001E+01 0.000000E+00 3 9.276642E+01 1.791852E+00 9.272105E+01 2.900677E+00 + 1.230001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.230001E+01 0.000000E+00 5 5.900499E+02 8.946748E+01 5.483995E+00 5.900244E+02 + 1.230001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.230001E+01 3.000000E+01 1 9.303152E+01 8.947578E+01 8.511832E-01 9.302763E+01 + 1.230001E+01 3.000000E+01 2 5.666471E+01 8.904237E+01 9.470353E-01 5.665679E+01 + 1.230001E+01 3.000000E+01 3 9.621081E+01 1.838820E+00 9.616126E+01 3.087209E+00 + 1.230001E+01 3.000000E+01 4 2.106349E+02 8.900423E+01 3.660543E+00 2.106031E+02 + 1.230001E+01 3.000000E+01 5 5.286344E+02 8.947604E+01 4.834286E+00 5.286123E+02 + 1.230001E+01 3.000000E+01 6 4.428337E+02 -1.050971E-01 4.428329E+02 -8.122854E-01 + 1.230001E+01 6.000000E+01 1 5.707371E+01 8.948741E+01 5.105975E-01 5.707143E+01 + 1.230001E+01 6.000000E+01 2 1.051417E+02 8.903733E+01 1.766484E+00 1.051268E+02 + 1.230001E+01 6.000000E+01 3 1.035178E+02 1.935063E+00 1.034588E+02 3.495465E+00 + 1.230001E+01 6.000000E+01 4 4.060948E+02 8.903651E+01 6.828631E+00 4.060374E+02 + 1.230001E+01 6.000000E+01 5 3.256099E+02 8.948969E+01 2.900049E+00 3.255970E+02 + 1.230001E+01 6.000000E+01 6 4.747352E+02 -1.025328E-01 4.747344E+02 -8.495545E-01 + 1.230001E+01 9.000000E+01 1 6.241133E-06 -8.968932E+01 3.384201E-08 -6.241041E-06 + 1.230001E+01 9.000000E+01 2 1.256580E+02 8.903494E+01 2.116406E+00 1.256402E+02 + 1.230001E+01 9.000000E+01 3 1.073860E+02 1.983983E+00 1.073217E+02 3.717717E+00 + 1.230001E+01 9.000000E+01 4 4.938672E+02 8.905077E+01 8.181700E+00 4.937994E+02 + 1.230001E+01 9.000000E+01 5 2.457996E-04 -8.977554E+01 9.629482E-07 -2.457977E-04 + 1.230001E+01 9.000000E+01 6 4.222679E-05 1.799344E+02 -4.222676E-05 4.831198E-08 + 1.240001E+01 0.000000E+00 1 1.035895E+02 8.947980E+01 9.404937E-01 1.035852E+02 + 1.240001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.240001E+01 0.000000E+00 3 9.432555E+01 1.767963E+00 9.428065E+01 2.910121E+00 + 1.240001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.240001E+01 0.000000E+00 5 5.956002E+02 8.947814E+01 5.424707E+00 5.955754E+02 + 1.240001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.240001E+01 3.000000E+01 1 9.237492E+01 8.948574E+01 8.291031E-01 9.237119E+01 + 1.240001E+01 3.000000E+01 2 5.627071E+01 8.907061E+01 9.127184E-01 5.626330E+01 + 1.240001E+01 3.000000E+01 3 9.773093E+01 1.812637E+00 9.768202E+01 3.091347E+00 + 1.240001E+01 3.000000E+01 4 2.087110E+02 8.903425E+01 3.517780E+00 2.086814E+02 + 1.240001E+01 3.000000E+01 5 5.330732E+02 8.948598E+01 4.782290E+00 5.330518E+02 + 1.240001E+01 3.000000E+01 6 4.338464E+02 -9.919482E-02 4.338457E+02 -7.511076E-01 + 1.240001E+01 6.000000E+01 1 5.658599E+01 8.949644E+01 4.973158E-01 5.658380E+01 + 1.240001E+01 6.000000E+01 2 1.042272E+02 8.906592E+01 1.699119E+00 1.042134E+02 + 1.240001E+01 6.000000E+01 3 1.049463E+02 1.904029E+00 1.048884E+02 3.486890E+00 + 1.240001E+01 6.000000E+01 4 4.014172E+02 8.906515E+01 6.549312E+00 4.013638E+02 + 1.240001E+01 6.000000E+01 5 3.277592E+02 8.949853E+01 2.868647E+00 3.277467E+02 + 1.240001E+01 6.000000E+01 6 4.642887E+02 -9.683754E-02 4.642880E+02 -7.847096E-01 + 1.240001E+01 9.000000E+01 1 6.179006E-06 -8.971370E+01 3.087587E-08 -6.178929E-06 + 1.240001E+01 9.000000E+01 2 1.244558E+02 8.906370E+01 2.033714E+00 1.244392E+02 + 1.240001E+01 9.000000E+01 3 1.087600E+02 1.950470E+00 1.086970E+02 3.701705E+00 + 1.240001E+01 9.000000E+01 4 4.876261E+02 8.907884E+01 7.839365E+00 4.875630E+02 + 1.240001E+01 9.000000E+01 5 2.440982E-04 -8.978297E+01 9.246425E-07 -2.440964E-04 + 1.240001E+01 9.000000E+01 6 4.126145E-05 1.799380E+02 -4.126142E-05 4.463558E-08 + 1.250001E+01 0.000000E+00 1 1.029296E+02 8.949005E+01 9.160917E-01 1.029255E+02 + 1.250001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.250001E+01 0.000000E+00 3 9.585702E+01 1.744084E+00 9.581261E+01 2.917438E+00 + 1.250001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.250001E+01 0.000000E+00 5 6.008287E+02 8.948854E+01 5.363334E+00 6.008048E+02 + 1.250001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.250001E+01 3.000000E+01 1 9.172245E+01 8.949551E+01 8.076090E-01 9.171889E+01 + 1.250001E+01 3.000000E+01 2 5.587859E+01 8.909771E+01 8.799407E-01 5.587166E+01 + 1.250001E+01 3.000000E+01 3 9.922520E+01 1.786535E+00 9.917697E+01 3.093431E+00 + 1.250001E+01 3.000000E+01 4 2.068085E+02 8.906302E+01 3.381885E+00 2.067808E+02 + 1.250001E+01 3.000000E+01 5 5.372525E+02 8.949575E+01 4.728209E+00 5.372317E+02 + 1.250001E+01 3.000000E+01 6 4.251291E+02 -9.369939E-02 4.251285E+02 -6.952400E-01 + 1.250001E+01 6.000000E+01 1 5.610529E+01 8.950536E+01 4.843614E-01 5.610320E+01 + 1.250001E+01 6.000000E+01 2 1.033262E+02 8.909333E+01 1.635004E+00 1.033132E+02 + 1.250001E+01 6.000000E+01 3 1.063493E+02 1.873419E+00 1.062925E+02 3.476720E+00 + 1.250001E+01 6.000000E+01 4 3.968362E+02 8.909261E+01 6.284411E+00 3.967865E+02 + 1.250001E+01 6.000000E+01 5 3.297563E+02 8.950726E+01 2.835852E+00 3.297441E+02 + 1.250001E+01 6.000000E+01 6 4.541964E+02 -9.152967E-02 4.541958E+02 -7.255757E-01 + 1.250001E+01 9.000000E+01 1 6.118162E-06 -8.973656E+01 2.813067E-08 -6.118098E-06 + 1.250001E+01 9.000000E+01 2 1.232759E+02 8.909126E+01 1.955142E+00 1.232604E+02 + 1.250001E+01 9.000000E+01 3 1.101094E+02 1.917527E+00 1.100478E+02 3.684362E+00 + 1.250001E+01 9.000000E+01 4 4.815327E+02 8.910576E+01 7.515173E+00 4.814741E+02 + 1.250001E+01 9.000000E+01 5 2.424188E-04 -8.979011E+01 8.880730E-07 -2.424172E-04 + 1.250001E+01 9.000000E+01 6 4.033050E-05 1.799413E+02 -4.033048E-05 4.128229E-08 + 1.260001E+01 0.000000E+00 1 1.022716E+02 8.950005E+01 8.923918E-01 1.022678E+02 + 1.260001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.260001E+01 0.000000E+00 3 9.736290E+01 1.720210E+00 9.731902E+01 2.922719E+00 + 1.260001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.260001E+01 0.000000E+00 5 6.057446E+02 8.949866E+01 5.300231E+00 6.057214E+02 + 1.260001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.260001E+01 3.000000E+01 1 9.107421E+01 8.950507E+01 7.867076E-01 9.107082E+01 + 1.260001E+01 3.000000E+01 2 5.548875E+01 8.912370E+01 8.486320E-01 5.548226E+01 + 1.260001E+01 3.000000E+01 3 1.006928E+02 1.760619E+00 1.006452E+02 3.093660E+00 + 1.260001E+01 3.000000E+01 4 2.049292E+02 8.909059E+01 3.252542E+00 2.049034E+02 + 1.260001E+01 3.000000E+01 5 5.411503E+02 8.950527E+01 4.672566E+00 5.411301E+02 + 1.260001E+01 3.000000E+01 6 4.166722E+02 -8.857828E-02 4.166717E+02 -6.441677E-01 + 1.260001E+01 6.000000E+01 1 5.563151E+01 8.951414E+01 4.717415E-01 5.562951E+01 + 1.260001E+01 6.000000E+01 2 1.024386E+02 8.911962E+01 1.573968E+00 1.024265E+02 + 1.260001E+01 6.000000E+01 3 1.077271E+02 1.843222E+00 1.076713E+02 3.465012E+00 + 1.260001E+01 6.000000E+01 4 3.923490E+02 8.911895E+01 6.033013E+00 3.923026E+02 + 1.260001E+01 6.000000E+01 5 3.316088E+02 8.951587E+01 2.801925E+00 3.315970E+02 + 1.260001E+01 6.000000E+01 6 4.444436E+02 -8.657908E-02 4.444431E+02 -6.715940E-01 + 1.260001E+01 9.000000E+01 1 6.058593E-06 -8.975800E+01 2.558908E-08 -6.058538E-06 + 1.260001E+01 9.000000E+01 2 1.221181E+02 8.911768E+01 1.880469E+00 1.221036E+02 + 1.260001E+01 9.000000E+01 3 1.114346E+02 1.885134E+00 1.113743E+02 3.665738E+00 + 1.260001E+01 9.000000E+01 4 4.755874E+02 8.913158E+01 7.208121E+00 4.755328E+02 + 1.260001E+01 9.000000E+01 5 2.407573E-04 -8.979696E+01 8.531620E-07 -2.407558E-04 + 1.260001E+01 9.000000E+01 6 3.943224E-05 1.799445E+02 -3.943222E-05 3.822041E-08 + 1.270001E+01 0.000000E+00 1 1.016153E+02 8.950980E+01 8.693728E-01 1.016116E+02 + 1.270001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.270001E+01 0.000000E+00 3 9.884223E+01 1.696432E+00 9.879891E+01 2.926125E+00 + 1.270001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.270001E+01 0.000000E+00 5 6.103551E+02 8.950853E+01 5.235420E+00 6.103326E+02 + 1.270001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.270001E+01 3.000000E+01 1 9.043067E+01 8.951442E+01 7.663884E-01 9.042742E+01 + 1.270001E+01 3.000000E+01 2 5.510102E+01 8.914865E+01 8.187144E-01 5.509494E+01 + 1.270001E+01 3.000000E+01 3 1.021355E+02 1.734906E+00 1.020887E+02 3.092173E+00 + 1.270001E+01 3.000000E+01 4 2.030723E+02 8.911703E+01 3.129369E+00 2.030482E+02 + 1.270001E+01 3.000000E+01 5 5.448085E+02 8.951463E+01 4.615272E+00 5.447889E+02 + 1.270001E+01 3.000000E+01 6 4.084662E+02 -8.380222E-02 4.084658E+02 -5.974325E-01 + 1.270001E+01 6.000000E+01 1 5.516476E+01 8.952279E+01 4.594568E-01 5.516285E+01 + 1.270001E+01 6.000000E+01 2 1.015644E+02 8.914484E+01 1.515838E+00 1.015531E+02 + 1.270001E+01 6.000000E+01 3 1.090804E+02 1.813513E+00 1.090258E+02 3.452014E+00 + 1.270001E+01 6.000000E+01 4 3.879556E+02 8.914421E+01 5.794427E+00 3.879123E+02 + 1.270001E+01 6.000000E+01 5 3.333284E+02 8.952438E+01 2.766979E+00 3.333169E+02 + 1.270001E+01 6.000000E+01 6 4.350145E+02 -8.195766E-02 4.350140E+02 -6.222580E-01 + 1.270001E+01 9.000000E+01 1 6.000205E-06 -8.977811E+01 2.323623E-08 -6.000160E-06 + 1.270001E+01 9.000000E+01 2 1.209816E+02 8.914303E+01 1.809454E+00 1.209680E+02 + 1.270001E+01 9.000000E+01 3 1.127366E+02 1.853378E+00 1.126776E+02 3.646115E+00 + 1.270001E+01 9.000000E+01 4 4.697818E+02 8.915635E+01 6.917041E+00 4.697309E+02 + 1.270001E+01 9.000000E+01 5 2.391163E-04 -8.980356E+01 8.198295E-07 -2.391149E-04 + 1.270001E+01 9.000000E+01 6 3.856514E-05 1.799474E+02 -3.856512E-05 3.542146E-08 + 1.280001E+01 0.000000E+00 1 1.009614E+02 8.951931E+01 8.470231E-01 1.009578E+02 + 1.280001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.280001E+01 0.000000E+00 3 1.002962E+02 1.672778E+00 1.002535E+02 2.927781E+00 + 1.280001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.280001E+01 0.000000E+00 5 6.146942E+02 8.951814E+01 5.169532E+00 6.146724E+02 + 1.280001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.280001E+01 3.000000E+01 1 8.979245E+01 8.952357E+01 7.466415E-01 8.978934E+01 + 1.280001E+01 3.000000E+01 2 5.471620E+01 8.917259E+01 7.901255E-01 5.471049E+01 + 1.280001E+01 3.000000E+01 3 1.035522E+02 1.709448E+00 1.035061E+02 3.089072E+00 + 1.280001E+01 3.000000E+01 4 2.012382E+02 8.914239E+01 3.012062E+00 2.012156E+02 + 1.280001E+01 3.000000E+01 5 5.482299E+02 8.952376E+01 4.556846E+00 5.482110E+02 + 1.280001E+01 3.000000E+01 6 4.005014E+02 -7.934381E-02 4.005010E+02 -5.546184E-01 + 1.280001E+01 6.000000E+01 1 5.470491E+01 8.953130E+01 4.475023E-01 5.470308E+01 + 1.280001E+01 6.000000E+01 2 1.007037E+02 8.916904E+01 1.460459E+00 1.006931E+02 + 1.280001E+01 6.000000E+01 3 1.104098E+02 1.784248E+00 1.103563E+02 3.437717E+00 + 1.280001E+01 6.000000E+01 4 3.836539E+02 8.916846E+01 5.567841E+00 3.836135E+02 + 1.280001E+01 6.000000E+01 5 3.349163E+02 8.953274E+01 2.731304E+00 3.349051E+02 + 1.280001E+01 6.000000E+01 6 4.258942E+02 -7.764024E-02 4.258938E+02 -5.771196E-01 + 1.280001E+01 9.000000E+01 1 5.943022E-06 -8.979699E+01 2.105765E-08 -5.942984E-06 + 1.280001E+01 9.000000E+01 2 1.198662E+02 8.916734E+01 1.741907E+00 1.198535E+02 + 1.280001E+01 9.000000E+01 3 1.140152E+02 1.822179E+00 1.139576E+02 3.625418E+00 + 1.280001E+01 9.000000E+01 4 4.641135E+02 8.918012E+01 6.641050E+00 4.640660E+02 + 1.280001E+01 9.000000E+01 5 2.374954E-04 -8.980989E+01 7.880111E-07 -2.374941E-04 + 1.280001E+01 9.000000E+01 6 3.772786E-05 1.799501E+02 -3.772785E-05 3.286006E-08 + 1.290001E+01 0.000000E+00 1 1.003103E+02 8.952858E+01 8.253285E-01 1.003070E+02 + 1.290001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.290001E+01 0.000000E+00 3 1.017248E+02 1.649289E+00 1.016827E+02 2.927798E+00 + 1.290001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.290001E+01 0.000000E+00 5 6.187474E+02 8.952752E+01 5.102357E+00 6.187264E+02 + 1.290001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.290001E+01 3.000000E+01 1 8.915935E+01 8.953251E+01 7.274616E-01 8.915638E+01 + 1.290001E+01 3.000000E+01 2 5.433393E+01 8.919559E+01 7.627972E-01 5.432858E+01 + 1.290001E+01 3.000000E+01 3 1.049436E+02 1.684247E+00 1.048983E+02 3.084443E+00 + 1.290001E+01 3.000000E+01 4 1.994283E+02 8.916672E+01 2.900286E+00 1.994072E+02 + 1.290001E+01 3.000000E+01 5 5.514082E+02 8.953268E+01 4.497407E+00 5.513898E+02 + 1.290001E+01 3.000000E+01 6 3.927689E+02 -7.517843E-02 3.927686E+02 -5.153563E-01 + 1.290001E+01 6.000000E+01 1 5.425166E+01 8.953966E+01 4.358831E-01 5.424991E+01 + 1.290001E+01 6.000000E+01 2 9.985564E+01 8.919227E+01 1.407678E+00 9.984572E+01 + 1.290001E+01 6.000000E+01 3 1.117153E+02 1.755491E+00 1.116628E+02 3.422320E+00 + 1.290001E+01 6.000000E+01 4 3.794368E+02 8.919173E+01 5.352582E+00 3.793991E+02 + 1.290001E+01 6.000000E+01 5 3.363806E+02 8.954098E+01 2.694847E+00 3.363698E+02 + 1.290001E+01 6.000000E+01 6 4.170709E+02 -7.360327E-02 4.170705E+02 -5.357772E-01 + 1.290001E+01 9.000000E+01 1 5.886964E-06 -8.981469E+01 1.904019E-08 -5.886933E-06 + 1.290001E+01 9.000000E+01 2 1.187717E+02 8.919069E+01 1.677620E+00 1.187598E+02 + 1.290001E+01 9.000000E+01 3 1.152706E+02 1.791620E+00 1.152143E+02 3.603888E+00 + 1.290001E+01 9.000000E+01 4 4.585769E+02 8.920294E+01 6.379220E+00 4.585326E+02 + 1.290001E+01 9.000000E+01 5 2.358923E-04 -8.981598E+01 7.576314E-07 -2.358911E-04 + 1.290001E+01 9.000000E+01 6 3.691895E-05 1.799527E+02 -3.691894E-05 3.051355E-08 + 1.300001E+01 0.000000E+00 1 9.966228E+01 8.953762E+01 8.042725E-01 9.965904E+01 + 1.300001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.300001E+01 0.000000E+00 3 1.031288E+02 1.625988E+00 1.030872E+02 2.926281E+00 + 1.300001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.300001E+01 0.000000E+00 5 6.225383E+02 8.953664E+01 5.034557E+00 6.225179E+02 + 1.300001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.300001E+01 3.000000E+01 1 8.853170E+01 8.954125E+01 7.088355E-01 8.852886E+01 + 1.300001E+01 3.000000E+01 2 5.395467E+01 8.921769E+01 7.366695E-01 5.394965E+01 + 1.300001E+01 3.000000E+01 3 1.063111E+02 1.659326E+00 1.062665E+02 3.078414E+00 + 1.300001E+01 3.000000E+01 4 1.976420E+02 8.919007E+01 2.793766E+00 1.976223E+02 + 1.300001E+01 3.000000E+01 5 5.543762E+02 8.954140E+01 4.437195E+00 5.543584E+02 + 1.300001E+01 3.000000E+01 6 3.852600E+02 -7.128378E-02 3.852597E+02 -4.793159E-01 + 1.300001E+01 6.000000E+01 1 5.380541E+01 8.954787E+01 4.245897E-01 5.380374E+01 + 1.300001E+01 6.000000E+01 2 9.902090E+01 8.921458E+01 1.357359E+00 9.901160E+01 + 1.300001E+01 6.000000E+01 3 1.129971E+02 1.727234E+00 1.129457E+02 3.405884E+00 + 1.300001E+01 6.000000E+01 4 3.753094E+02 8.921407E+01 5.148009E+00 3.752740E+02 + 1.300001E+01 6.000000E+01 5 3.377252E+02 8.954906E+01 2.657947E+00 3.377147E+02 + 1.300001E+01 6.000000E+01 6 4.085299E+02 -6.982595E-02 4.085296E+02 -4.978722E-01 + 1.300001E+01 9.000000E+01 1 5.832023E-06 -8.983130E+01 1.717203E-08 -5.831997E-06 + 1.300001E+01 9.000000E+01 2 1.176967E+02 8.921309E+01 1.616412E+00 1.176856E+02 + 1.300001E+01 9.000000E+01 3 1.165038E+02 1.761626E+00 1.164487E+02 3.581482E+00 + 1.300001E+01 9.000000E+01 4 4.531705E+02 8.922485E+01 6.130694E+00 4.531290E+02 + 1.300001E+01 9.000000E+01 5 2.343102E-04 -8.982183E+01 7.286212E-07 -2.343090E-04 + 1.300001E+01 9.000000E+01 6 3.613716E-05 1.799550E+02 -3.613715E-05 2.836163E-08 + 1.310001E+01 0.000000E+00 1 9.901750E+01 8.954643E+01 7.838416E-01 9.901440E+01 + 1.310001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.310001E+01 0.000000E+00 3 1.045077E+02 1.602922E+00 1.044668E+02 2.923352E+00 + 1.310001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.310001E+01 0.000000E+00 5 6.260788E+02 8.954553E+01 4.966015E+00 6.260591E+02 + 1.310001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.310001E+01 3.000000E+01 1 8.790895E+01 8.954979E+01 6.907496E-01 8.790623E+01 + 1.310001E+01 3.000000E+01 2 5.357861E+01 8.923892E+01 7.116803E-01 5.357389E+01 + 1.310001E+01 3.000000E+01 3 1.076543E+02 1.634723E+00 1.076105E+02 3.071101E+00 + 1.310001E+01 3.000000E+01 4 1.958805E+02 8.921249E+01 2.692211E+00 1.958620E+02 + 1.310001E+01 3.000000E+01 5 5.571302E+02 8.954993E+01 4.376284E+00 5.571130E+02 + 1.310001E+01 3.000000E+01 6 3.779671E+02 -6.763905E-02 3.779669E+02 -4.461991E-01 + 1.310001E+01 6.000000E+01 1 5.336574E+01 8.955592E+01 4.136202E-01 5.336414E+01 + 1.310001E+01 6.000000E+01 2 9.819876E+01 8.923601E+01 1.309368E+00 9.819003E+01 + 1.310001E+01 6.000000E+01 3 1.142560E+02 1.699478E+00 1.142057E+02 3.388506E+00 + 1.310001E+01 6.000000E+01 4 3.712650E+02 8.923553E+01 4.953495E+00 3.712319E+02 + 1.310001E+01 6.000000E+01 5 3.389550E+02 8.955701E+01 2.620605E+00 3.389448E+02 + 1.310001E+01 6.000000E+01 6 4.002613E+02 -6.628826E-02 4.002610E+02 -4.630815E-01 + 1.310001E+01 9.000000E+01 1 5.778136E-06 -8.984689E+01 1.544170E-08 -5.778116E-06 + 1.310001E+01 9.000000E+01 2 1.166413E+02 8.923461E+01 1.558110E+00 1.166309E+02 + 1.310001E+01 9.000000E+01 3 1.177151E+02 1.732256E+00 1.176613E+02 3.558406E+00 + 1.310001E+01 9.000000E+01 4 4.478879E+02 8.924590E+01 5.894688E+00 4.478491E+02 + 1.310001E+01 9.000000E+01 5 2.327449E-04 -8.982745E+01 7.009148E-07 -2.327438E-04 + 1.310001E+01 9.000000E+01 6 3.538123E-05 1.799573E+02 -3.538122E-05 2.638610E-08 + 1.320001E+01 0.000000E+00 1 9.837684E+01 8.955502E+01 7.640185E-01 9.837387E+01 + 1.320001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.320001E+01 0.000000E+00 3 1.058633E+02 1.580071E+00 1.058230E+02 2.919067E+00 + 1.320001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.320001E+01 0.000000E+00 5 6.293903E+02 8.955421E+01 4.897017E+00 6.293712E+02 + 1.320001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.320001E+01 3.000000E+01 1 8.729283E+01 8.955813E+01 6.731992E-01 8.729024E+01 + 1.320001E+01 3.000000E+01 2 5.320554E+01 8.925933E+01 6.877763E-01 5.320110E+01 + 1.320001E+01 3.000000E+01 3 1.089736E+02 1.610426E+00 1.089306E+02 3.062545E+00 + 1.320001E+01 3.000000E+01 4 1.941425E+02 8.923402E+01 2.595366E+00 1.941252E+02 + 1.320001E+01 3.000000E+01 5 5.596900E+02 8.955827E+01 4.314929E+00 5.596733E+02 + 1.320001E+01 3.000000E+01 6 3.708825E+02 -6.422561E-02 3.708823E+02 -4.157401E-01 + 1.320001E+01 6.000000E+01 1 5.293261E+01 8.956381E+01 4.029681E-01 5.293108E+01 + 1.320001E+01 6.000000E+01 2 9.738930E+01 8.925660E+01 1.263577E+00 9.738110E+01 + 1.320001E+01 6.000000E+01 3 1.154934E+02 1.672202E+00 1.154442E+02 3.370245E+00 + 1.320001E+01 6.000000E+01 4 3.673029E+02 8.925615E+01 4.768451E+00 3.672720E+02 + 1.320001E+01 6.000000E+01 5 3.400790E+02 8.956483E+01 2.582965E+00 3.400692E+02 + 1.320001E+01 6.000000E+01 6 3.922525E+02 -6.297272E-02 3.922523E+02 -4.311173E-01 + 1.320001E+01 9.000000E+01 1 5.725295E-06 -8.986151E+01 1.383912E-08 -5.725278E-06 + 1.320001E+01 9.000000E+01 2 1.156054E+02 8.925529E+01 1.502553E+00 1.155956E+02 + 1.320001E+01 9.000000E+01 3 1.189044E+02 1.703483E+00 1.188518E+02 3.534670E+00 + 1.320001E+01 9.000000E+01 4 4.427265E+02 8.926614E+01 5.670448E+00 4.426902E+02 + 1.320001E+01 9.000000E+01 5 2.311977E-04 -8.983286E+01 6.744531E-07 -2.311967E-04 + 1.320001E+01 9.000000E+01 6 3.465001E-05 1.799594E+02 -3.465001E-05 2.457063E-08 + 1.330001E+01 0.000000E+00 1 9.774033E+01 8.956340E+01 7.447913E-01 9.773750E+01 + 1.330001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.330001E+01 0.000000E+00 3 1.071949E+02 1.557480E+00 1.071553E+02 2.913537E+00 + 1.330001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.330001E+01 0.000000E+00 5 6.324617E+02 8.956264E+01 4.827824E+00 6.324432E+02 + 1.330001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.330001E+01 3.000000E+01 1 8.668199E+01 8.956628E+01 6.561638E-01 8.667950E+01 + 1.330001E+01 3.000000E+01 2 5.283584E+01 8.927895E+01 6.649019E-01 5.283165E+01 + 1.330001E+01 3.000000E+01 3 1.102699E+02 1.586484E+00 1.102276E+02 3.052914E+00 + 1.330001E+01 3.000000E+01 4 1.924293E+02 8.925472E+01 2.502980E+00 1.924130E+02 + 1.330001E+01 3.000000E+01 5 5.620496E+02 8.956641E+01 4.253352E+00 5.620335E+02 + 1.330001E+01 3.000000E+01 6 3.639974E+02 -6.102650E-02 3.639972E+02 -3.876984E-01 + 1.330001E+01 6.000000E+01 1 5.250566E+01 8.957155E+01 3.926283E-01 5.250420E+01 + 1.330001E+01 6.000000E+01 2 9.659223E+01 8.927639E+01 1.219870E+00 9.658453E+01 + 1.330001E+01 6.000000E+01 3 1.167076E+02 1.645454E+00 1.166595E+02 3.351216E+00 + 1.330001E+01 6.000000E+01 4 3.634221E+02 8.927597E+01 4.592340E+00 3.633930E+02 + 1.330001E+01 6.000000E+01 5 3.411006E+02 8.957249E+01 2.545118E+00 3.410912E+02 + 1.330001E+01 6.000000E+01 6 3.844919E+02 -5.986314E-02 3.844917E+02 -4.017205E-01 + 1.330001E+01 9.000000E+01 1 5.673464E-06 -8.987523E+01 1.235477E-08 -5.673451E-06 + 1.330001E+01 9.000000E+01 2 1.145877E+02 8.927516E+01 1.449587E+00 1.145785E+02 + 1.330001E+01 9.000000E+01 3 1.200731E+02 1.675291E+00 1.200218E+02 3.510358E+00 + 1.330001E+01 9.000000E+01 4 4.376828E+02 8.928558E+01 5.457304E+00 4.376488E+02 + 1.330001E+01 9.000000E+01 5 2.296706E-04 -8.983805E+01 6.491774E-07 -2.296697E-04 + 1.330001E+01 9.000000E+01 6 3.394248E-05 1.799613E+02 -3.394248E-05 2.290062E-08 + 1.340001E+01 0.000000E+00 1 9.710779E+01 8.957156E+01 7.261354E-01 9.710507E+01 + 1.340001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.340001E+01 0.000000E+00 3 1.085035E+02 1.535164E+00 1.084645E+02 2.906857E+00 + 1.340001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.340001E+01 0.000000E+00 5 6.353191E+02 8.957086E+01 4.758424E+00 6.353013E+02 + 1.340001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.340001E+01 3.000000E+01 1 8.607747E+01 8.957423E+01 6.396378E-01 8.607509E+01 + 1.340001E+01 3.000000E+01 2 5.246952E+01 8.929783E+01 6.430091E-01 5.246558E+01 + 1.340001E+01 3.000000E+01 3 1.115434E+02 1.562870E+00 1.115019E+02 3.042217E+00 + 1.340001E+01 3.000000E+01 4 1.907394E+02 8.927460E+01 2.414806E+00 1.907242E+02 + 1.340001E+01 3.000000E+01 5 5.642354E+02 8.957436E+01 4.191593E+00 5.642198E+02 + 1.340001E+01 3.000000E+01 6 3.573062E+02 -5.802537E-02 3.573061E+02 -3.618560E-01 + 1.340001E+01 6.000000E+01 1 5.208547E+01 8.957913E+01 3.825932E-01 5.208406E+01 + 1.340001E+01 6.000000E+01 2 9.580726E+01 8.929543E+01 1.178136E+00 9.580002E+01 + 1.340001E+01 6.000000E+01 3 1.179009E+02 1.619188E+00 1.178538E+02 3.331455E+00 + 1.340001E+01 6.000000E+01 4 3.596194E+02 8.929503E+01 4.424686E+00 3.595922E+02 + 1.340001E+01 6.000000E+01 5 3.420238E+02 8.957999E+01 2.507203E+00 3.420146E+02 + 1.340001E+01 6.000000E+01 6 3.769714E+02 -5.694431E-02 3.769712E+02 -3.746589E-01 + 1.340001E+01 9.000000E+01 1 5.622613E-06 -8.988811E+01 1.097981E-08 -5.622602E-06 + 1.340001E+01 9.000000E+01 2 1.135885E+02 8.929427E+01 1.399070E+00 1.135799E+02 + 1.340001E+01 9.000000E+01 3 1.212212E+02 1.647668E+00 1.211711E+02 3.485506E+00 + 1.340001E+01 9.000000E+01 4 4.327518E+02 8.930429E+01 5.254560E+00 4.327199E+02 + 1.340001E+01 9.000000E+01 5 2.281604E-04 -8.984305E+01 6.250299E-07 -2.281596E-04 + 1.340001E+01 9.000000E+01 6 3.325758E-05 1.799632E+02 -3.325758E-05 2.136287E-08 + 1.350002E+01 0.000000E+00 1 9.647980E+01 8.957951E+01 7.080393E-01 9.647720E+01 + 1.350002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.350002E+01 0.000000E+00 3 1.097896E+02 1.513120E+00 1.097513E+02 2.899089E+00 + 1.350002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.350002E+01 0.000000E+00 5 6.379564E+02 8.957887E+01 4.689035E+00 6.379391E+02 + 1.350002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.350002E+01 3.000000E+01 1 8.547876E+01 8.958200E+01 6.236005E-01 8.547649E+01 + 1.350002E+01 3.000000E+01 2 5.210656E+01 8.931599E+01 6.220471E-01 5.210284E+01 + 1.350002E+01 3.000000E+01 3 1.127945E+02 1.539611E+00 1.127538E+02 3.030568E+00 + 1.350002E+01 3.000000E+01 4 1.890742E+02 8.929372E+01 2.330631E+00 1.890598E+02 + 1.350002E+01 3.000000E+01 5 5.662357E+02 8.958212E+01 4.129840E+00 5.662206E+02 + 1.350002E+01 3.000000E+01 6 3.508008E+02 -5.520827E-02 3.508006E+02 -3.380197E-01 + 1.350002E+01 6.000000E+01 1 5.167117E+01 8.958656E+01 3.728577E-01 5.166982E+01 + 1.350002E+01 6.000000E+01 2 9.503458E+01 8.931373E+01 1.138269E+00 9.502776E+01 + 1.350002E+01 6.000000E+01 3 1.190729E+02 1.593426E+00 1.190269E+02 3.311053E+00 + 1.350002E+01 6.000000E+01 4 3.558934E+02 8.931335E+01 4.264977E+00 3.558679E+02 + 1.350002E+01 6.000000E+01 5 3.428521E+02 8.958733E+01 2.469314E+00 3.428432E+02 + 1.350002E+01 6.000000E+01 6 3.696781E+02 -5.420265E-02 3.696780E+02 -3.497209E-01 + 1.350002E+01 9.000000E+01 1 5.572710E-06 -8.990021E+01 9.706190E-09 -5.572701E-06 + 1.350002E+01 9.000000E+01 2 1.126070E+02 8.931264E+01 1.350871E+00 1.125989E+02 + 1.350002E+01 9.000000E+01 3 1.223481E+02 1.620644E+00 1.222992E+02 3.460225E+00 + 1.350002E+01 9.000000E+01 4 4.279327E+02 8.932228E+01 5.061672E+00 4.279028E+02 + 1.350002E+01 9.000000E+01 5 2.266682E-04 -8.984784E+01 6.019519E-07 -2.266674E-04 + 1.350002E+01 9.000000E+01 6 3.259435E-05 1.799649E+02 -3.259435E-05 1.994554E-08 + 1.360002E+01 0.000000E+00 1 9.585638E+01 8.958727E+01 6.904913E-01 9.585390E+01 + 1.360002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.360002E+01 0.000000E+00 3 1.110531E+02 1.491375E+00 1.110155E+02 2.890318E+00 + 1.360002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.360002E+01 0.000000E+00 5 6.404005E+02 8.958669E+01 4.619687E+00 6.403839E+02 + 1.360002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.360002E+01 3.000000E+01 1 8.488598E+01 8.958958E+01 6.080474E-01 8.488380E+01 + 1.360002E+01 3.000000E+01 2 5.174720E+01 8.933347E+01 6.019685E-01 5.174369E+01 + 1.360002E+01 3.000000E+01 3 1.140237E+02 1.516720E+00 1.139837E+02 3.018055E+00 + 1.360002E+01 3.000000E+01 4 1.874324E+02 8.931211E+01 2.250251E+00 1.874189E+02 + 1.360002E+01 3.000000E+01 5 5.680785E+02 8.958969E+01 4.068121E+00 5.680639E+02 + 1.360002E+01 3.000000E+01 6 3.444746E+02 -5.256160E-02 3.444745E+02 -3.160116E-01 + 1.360002E+01 6.000000E+01 1 5.126316E+01 8.959382E+01 3.634132E-01 5.126187E+01 + 1.360002E+01 6.000000E+01 2 9.427340E+01 8.933135E+01 1.100167E+00 9.426698E+01 + 1.360002E+01 6.000000E+01 3 1.202243E+02 1.568163E+00 1.201793E+02 3.290081E+00 + 1.360002E+01 6.000000E+01 4 3.522416E+02 8.933100E+01 4.112770E+00 3.522176E+02 + 1.360002E+01 6.000000E+01 5 3.435918E+02 8.959454E+01 2.431463E+00 3.435832E+02 + 1.360002E+01 6.000000E+01 6 3.626053E+02 -5.162517E-02 3.626052E+02 -3.267179E-01 + 1.360002E+01 9.000000E+01 1 5.523750E-06 -8.991156E+01 8.526428E-09 -5.523743E-06 + 1.360002E+01 9.000000E+01 2 1.116428E+02 8.933032E+01 1.304857E+00 1.116352E+02 + 1.360002E+01 9.000000E+01 3 1.234563E+02 1.594159E+00 1.234086E+02 3.434522E+00 + 1.360002E+01 9.000000E+01 4 4.232200E+02 8.933959E+01 4.878055E+00 4.231919E+02 + 1.360002E+01 9.000000E+01 5 2.251913E-04 -8.985246E+01 5.798990E-07 -2.251906E-04 + 1.360002E+01 9.000000E+01 6 3.195180E-05 1.799666E+02 -3.195180E-05 1.863791E-08 + 1.370002E+01 0.000000E+00 1 9.523803E+01 8.959483E+01 6.734699E-01 9.523565E+01 + 1.370002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.370002E+01 0.000000E+00 3 1.122953E+02 1.469924E+00 1.122583E+02 2.880620E+00 + 1.370002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.370002E+01 0.000000E+00 5 6.426550E+02 8.959429E+01 4.550618E+00 6.426389E+02 + 1.370002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.370002E+01 3.000000E+01 1 8.429946E+01 8.959698E+01 5.929583E-01 8.429738E+01 + 1.370002E+01 3.000000E+01 2 5.139131E+01 8.935030E+01 5.827336E-01 5.138801E+01 + 1.370002E+01 3.000000E+01 3 1.152318E+02 1.494177E+00 1.151926E+02 3.004710E+00 + 1.370002E+01 3.000000E+01 4 1.858150E+02 8.932980E+01 2.173457E+00 1.858023E+02 + 1.370002E+01 3.000000E+01 5 5.697527E+02 8.959708E+01 4.006640E+00 5.697386E+02 + 1.370002E+01 3.000000E+01 6 3.383217E+02 -5.007343E-02 3.383216E+02 -2.956749E-01 + 1.370002E+01 6.000000E+01 1 5.086125E+01 8.960093E+01 3.542526E-01 5.086002E+01 + 1.370002E+01 6.000000E+01 2 9.352402E+01 8.934830E+01 1.063745E+00 9.351797E+01 + 1.370002E+01 6.000000E+01 3 1.213550E+02 1.543401E+00 1.213110E+02 3.268597E+00 + 1.370002E+01 6.000000E+01 4 3.486605E+02 8.934798E+01 3.967686E+00 3.486379E+02 + 1.370002E+01 6.000000E+01 5 3.442470E+02 8.960159E+01 2.393731E+00 3.442386E+02 + 1.370002E+01 6.000000E+01 6 3.557429E+02 -4.920064E-02 3.557427E+02 -3.054811E-01 + 1.370002E+01 9.000000E+01 1 5.475670E-06 -8.992222E+01 7.433633E-09 -5.475665E-06 + 1.370002E+01 9.000000E+01 2 1.106953E+02 8.934734E+01 1.260907E+00 1.106881E+02 + 1.370002E+01 9.000000E+01 3 1.245441E+02 1.568268E+00 1.244974E+02 3.408525E+00 + 1.370002E+01 9.000000E+01 4 4.186085E+02 8.935625E+01 4.703158E+00 4.185821E+02 + 1.370002E+01 9.000000E+01 5 2.237349E-04 -8.985690E+01 5.588086E-07 -2.237342E-04 + 1.370002E+01 9.000000E+01 6 3.132915E-05 1.799681E+02 -3.132915E-05 1.743039E-08 + 1.380002E+01 0.000000E+00 1 9.462417E+01 8.960220E+01 6.569591E-01 9.462189E+01 + 1.380002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.380002E+01 0.000000E+00 3 1.135152E+02 1.448807E+00 1.134789E+02 2.870092E+00 + 1.380002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.380002E+01 0.000000E+00 5 6.447154E+02 8.960169E+01 4.481882E+00 6.446998E+02 + 1.380002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.380002E+01 3.000000E+01 1 8.371916E+01 8.960421E+01 5.783236E-01 8.371716E+01 + 1.380002E+01 3.000000E+01 2 5.103907E+01 8.936652E+01 5.642987E-01 5.103595E+01 + 1.380002E+01 3.000000E+01 3 1.164179E+02 1.472036E+00 1.163795E+02 2.990666E+00 + 1.380002E+01 3.000000E+01 4 1.842216E+02 8.934684E+01 2.100059E+00 1.842097E+02 + 1.380002E+01 3.000000E+01 5 5.712762E+02 8.960429E+01 3.945374E+00 5.712626E+02 + 1.380002E+01 3.000000E+01 6 3.323361E+02 -4.773237E-02 3.323359E+02 -2.768648E-01 + 1.380002E+01 6.000000E+01 1 5.046520E+01 8.960788E+01 3.453674E-01 5.046402E+01 + 1.380002E+01 6.000000E+01 2 9.278586E+01 8.936463E+01 1.028909E+00 9.278015E+01 + 1.380002E+01 6.000000E+01 3 1.224657E+02 1.519127E+00 1.224227E+02 3.246646E+00 + 1.380002E+01 6.000000E+01 4 3.451521E+02 8.936433E+01 3.829268E+00 3.451308E+02 + 1.380002E+01 6.000000E+01 5 3.448199E+02 8.960848E+01 2.356209E+00 3.448118E+02 + 1.380002E+01 6.000000E+01 6 3.490835E+02 -4.691823E-02 3.490834E+02 -2.858566E-01 + 1.380002E+01 9.000000E+01 1 5.428473E-06 -8.993223E+01 6.421432E-09 -5.428470E-06 + 1.380002E+01 9.000000E+01 2 1.097644E+02 8.936373E+01 1.218917E+00 1.097577E+02 + 1.380002E+01 9.000000E+01 3 1.256127E+02 1.542922E+00 1.255671E+02 3.382223E+00 + 1.380002E+01 9.000000E+01 4 4.140994E+02 8.937231E+01 4.536509E+00 4.140746E+02 + 1.380002E+01 9.000000E+01 5 2.222941E-04 -8.986117E+01 5.386522E-07 -2.222934E-04 + 1.380002E+01 9.000000E+01 6 3.072555E-05 1.799696E+02 -3.072555E-05 1.631426E-08 + 1.390002E+01 0.000000E+00 1 9.401585E+01 8.960938E+01 6.409466E-01 9.401367E+01 + 1.390002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.390002E+01 0.000000E+00 3 1.147139E+02 1.428002E+00 1.146783E+02 2.858756E+00 + 1.390002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.390002E+01 0.000000E+00 5 6.466078E+02 8.960892E+01 4.413477E+00 6.465928E+02 + 1.390002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.390002E+01 3.000000E+01 1 8.314499E+01 8.961125E+01 5.641295E-01 8.314307E+01 + 1.390002E+01 3.000000E+01 2 5.069037E+01 8.938213E+01 5.466266E-01 5.068742E+01 + 1.390002E+01 3.000000E+01 3 1.175835E+02 1.450251E+00 1.175459E+02 2.975916E+00 + 1.390002E+01 3.000000E+01 4 1.826507E+02 8.936324E+01 2.029879E+00 1.826394E+02 + 1.390002E+01 3.000000E+01 5 5.726527E+02 8.961134E+01 3.884524E+00 5.726395E+02 + 1.390002E+01 3.000000E+01 6 3.265115E+02 -4.552826E-02 3.265114E+02 -2.594519E-01 + 1.390002E+01 6.000000E+01 1 5.007525E+01 8.961469E+01 3.367526E-01 5.007412E+01 + 1.390002E+01 6.000000E+01 2 9.205920E+01 8.938036E+01 9.955786E-01 9.205381E+01 + 1.390002E+01 6.000000E+01 3 1.235569E+02 1.495332E+00 1.235148E+02 3.224281E+00 + 1.390002E+01 6.000000E+01 4 3.417121E+02 8.938007E+01 3.697199E+00 3.416921E+02 + 1.390002E+01 6.000000E+01 5 3.453161E+02 8.961524E+01 2.318897E+00 3.453083E+02 + 1.390002E+01 6.000000E+01 6 3.426181E+02 -4.476813E-02 3.426180E+02 -2.677051E-01 + 1.390002E+01 9.000000E+01 1 5.382105E-06 -8.994162E+01 5.483923E-09 -5.382103E-06 + 1.390002E+01 9.000000E+01 2 1.088496E+02 8.937951E+01 1.178782E+00 1.088432E+02 + 1.390002E+01 9.000000E+01 3 1.266628E+02 1.518117E+00 1.266184E+02 3.355685E+00 + 1.390002E+01 9.000000E+01 4 4.096870E+02 8.938776E+01 4.377617E+00 4.096636E+02 + 1.390002E+01 9.000000E+01 5 2.208703E-04 -8.986527E+01 5.193689E-07 -2.208697E-04 + 1.390002E+01 9.000000E+01 6 3.014010E-05 1.799709E+02 -3.014010E-05 1.528172E-08 + 1.400002E+01 0.000000E+00 1 9.341292E+01 8.961639E+01 6.254156E-01 9.341083E+01 + 1.400002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.400002E+01 0.000000E+00 3 1.158918E+02 1.407507E+00 1.158568E+02 2.846669E+00 + 1.400002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.400002E+01 0.000000E+00 5 6.483340E+02 8.961596E+01 4.345604E+00 6.483194E+02 + 1.400002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.400002E+01 3.000000E+01 1 8.257697E+01 8.961813E+01 5.503611E-01 8.257514E+01 + 1.400002E+01 3.000000E+01 2 5.034540E+01 8.939719E+01 5.296783E-01 5.034261E+01 + 1.400002E+01 3.000000E+01 3 1.187293E+02 1.428819E+00 1.186924E+02 2.960516E+00 + 1.400002E+01 3.000000E+01 4 1.811027E+02 8.937902E+01 1.962768E+00 1.810921E+02 + 1.400002E+01 3.000000E+01 5 5.738928E+02 8.961822E+01 3.824070E+00 5.738800E+02 + 1.400002E+01 3.000000E+01 6 3.208421E+02 -4.345161E-02 3.208420E+02 -2.433182E-01 + 1.400002E+01 6.000000E+01 1 4.969078E+01 8.962134E+01 3.283996E-01 4.968969E+01 + 1.400002E+01 6.000000E+01 2 9.134313E+01 8.939552E+01 9.636754E-01 9.133805E+01 + 1.400002E+01 6.000000E+01 3 1.246293E+02 1.472011E+00 1.245882E+02 3.201554E+00 + 1.400002E+01 6.000000E+01 4 3.383389E+02 8.939524E+01 3.571121E+00 3.383200E+02 + 1.400002E+01 6.000000E+01 5 3.457374E+02 8.962184E+01 2.281882E+00 3.457299E+02 + 1.400002E+01 6.000000E+01 6 3.363388E+02 -4.274136E-02 3.363387E+02 -2.509011E-01 + 1.400002E+01 9.000000E+01 1 5.336591E-06 -8.995045E+01 4.615730E-09 -5.336589E-06 + 1.400002E+01 9.000000E+01 2 1.079504E+02 8.939471E+01 1.140400E+00 1.079444E+02 + 1.400002E+01 9.000000E+01 3 1.276943E+02 1.493816E+00 1.276509E+02 3.328869E+00 + 1.400002E+01 9.000000E+01 4 4.053708E+02 8.940267E+01 4.226071E+00 4.053488E+02 + 1.400002E+01 9.000000E+01 5 2.194629E-04 -8.986922E+01 5.009261E-07 -2.194623E-04 + 1.400002E+01 9.000000E+01 6 2.957223E-05 1.799722E+02 -2.957222E-05 1.432562E-08 + 1.410002E+01 0.000000E+00 1 9.281465E+01 8.962321E+01 6.103522E-01 9.281264E+01 + 1.410002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.410002E+01 0.000000E+00 3 1.170500E+02 1.387336E+00 1.170157E+02 2.833923E+00 + 1.410002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.410002E+01 0.000000E+00 5 6.498899E+02 8.962283E+01 4.278166E+00 6.498758E+02 + 1.410002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.410002E+01 3.000000E+01 1 8.201529E+01 8.962485E+01 5.370075E-01 8.201353E+01 + 1.410002E+01 3.000000E+01 2 5.000404E+01 8.941170E+01 5.134202E-01 5.000141E+01 + 1.410002E+01 3.000000E+01 3 1.198546E+02 1.407775E+00 1.198184E+02 2.944569E+00 + 1.410002E+01 3.000000E+01 4 1.795791E+02 8.939424E+01 1.898557E+00 1.795691E+02 + 1.410002E+01 3.000000E+01 5 5.749977E+02 8.962492E+01 3.764142E+00 5.749854E+02 + 1.410002E+01 3.000000E+01 6 3.153224E+02 -4.149376E-02 3.153224E+02 -2.283574E-01 + 1.410002E+01 6.000000E+01 1 4.931218E+01 8.962784E+01 3.202994E-01 4.931113E+01 + 1.410002E+01 6.000000E+01 2 9.063799E+01 8.941013E+01 9.331260E-01 9.063319E+01 + 1.410002E+01 6.000000E+01 3 1.256827E+02 1.449176E+00 1.256425E+02 3.178539E+00 + 1.410002E+01 6.000000E+01 4 3.350314E+02 8.940987E+01 3.450684E+00 3.350136E+02 + 1.410002E+01 6.000000E+01 5 3.460934E+02 8.962830E+01 2.245189E+00 3.460861E+02 + 1.410002E+01 6.000000E+01 6 3.302390E+02 -4.082947E-02 3.302389E+02 -2.353311E-01 + 1.410002E+01 9.000000E+01 1 5.291866E-06 -8.995872E+01 3.811751E-09 -5.291865E-06 + 1.410002E+01 9.000000E+01 2 1.070666E+02 8.940937E+01 1.103676E+00 1.070609E+02 + 1.410002E+01 9.000000E+01 3 1.287075E+02 1.470075E+00 1.286651E+02 3.301970E+00 + 1.410002E+01 9.000000E+01 4 4.011458E+02 8.941704E+01 4.081447E+00 4.011251E+02 + 1.410002E+01 9.000000E+01 5 2.180719E-04 -8.987302E+01 4.832769E-07 -2.180714E-04 + 1.410002E+01 9.000000E+01 6 2.902108E-05 1.799735E+02 -2.902108E-05 1.343956E-08 + 1.420002E+01 0.000000E+00 1 9.222209E+01 8.962988E+01 5.957394E-01 9.222017E+01 + 1.420002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.420002E+01 0.000000E+00 3 1.181887E+02 1.367490E+00 1.181551E+02 2.820566E+00 + 1.420002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.420002E+01 0.000000E+00 5 6.512989E+02 8.962952E+01 4.211454E+00 6.512853E+02 + 1.420002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.420002E+01 3.000000E+01 1 8.145914E+01 8.963139E+01 5.240567E-01 8.145745E+01 + 1.420002E+01 3.000000E+01 2 4.966637E+01 8.942570E+01 4.978178E-01 4.966388E+01 + 1.420002E+01 3.000000E+01 3 1.209608E+02 1.387103E+00 1.209254E+02 2.928117E+00 + 1.420002E+01 3.000000E+01 4 1.780764E+02 8.940891E+01 1.837086E+00 1.780669E+02 + 1.420002E+01 3.000000E+01 5 5.759803E+02 8.963148E+01 3.704710E+00 5.759684E+02 + 1.420002E+01 3.000000E+01 6 3.099483E+02 -3.964655E-02 3.099482E+02 -2.144727E-01 + 1.420002E+01 6.000000E+01 1 4.893873E+01 8.963420E+01 3.124456E-01 4.893773E+01 + 1.420002E+01 6.000000E+01 2 8.994339E+01 8.942421E+01 9.038602E-01 8.993885E+01 + 1.420002E+01 6.000000E+01 3 1.267177E+02 1.426796E+00 1.266785E+02 3.155236E+00 + 1.420002E+01 6.000000E+01 4 3.317870E+02 8.942397E+01 3.335597E+00 3.317702E+02 + 1.420002E+01 6.000000E+01 5 3.463760E+02 8.963463E+01 2.208806E+00 3.463690E+02 + 1.420002E+01 6.000000E+01 6 3.243127E+02 -3.902475E-02 3.243127E+02 -2.208927E-01 + 1.420002E+01 9.000000E+01 1 5.247934E-06 -8.996651E+01 3.067469E-09 -5.247933E-06 + 1.420002E+01 9.000000E+01 2 1.061972E+02 8.942349E+01 1.068530E+00 1.061918E+02 + 1.420002E+01 9.000000E+01 3 1.297040E+02 1.446820E+00 1.296626E+02 3.274906E+00 + 1.420002E+01 9.000000E+01 4 3.970090E+02 8.943089E+01 3.943370E+00 3.969894E+02 + 1.420002E+01 9.000000E+01 5 2.166960E-04 -8.987669E+01 4.663885E-07 -2.166955E-04 + 1.420002E+01 9.000000E+01 6 2.848610E-05 1.799746E+02 -2.848610E-05 1.261768E-08 + 1.430002E+01 0.000000E+00 1 9.163473E+01 8.963637E+01 5.815630E-01 9.163288E+01 + 1.430002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.430002E+01 0.000000E+00 3 1.193063E+02 1.347985E+00 1.192732E+02 2.806632E+00 + 1.430002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.430002E+01 0.000000E+00 5 6.525556E+02 8.963602E+01 4.145412E+00 6.525424E+02 + 1.430002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.430002E+01 3.000000E+01 1 8.090956E+01 8.963779E+01 5.114934E-01 8.090794E+01 + 1.430002E+01 3.000000E+01 2 4.933223E+01 8.943921E+01 4.828393E-01 4.932987E+01 + 1.430002E+01 3.000000E+01 3 1.220479E+02 1.366797E+00 1.220132E+02 2.911189E+00 + 1.430002E+01 3.000000E+01 4 1.765970E+02 8.942306E+01 1.778233E+00 1.765881E+02 + 1.430002E+01 3.000000E+01 5 5.768289E+02 8.963786E+01 3.645904E+00 5.768173E+02 + 1.430002E+01 3.000000E+01 6 3.047135E+02 -3.790264E-02 3.047134E+02 -2.015758E-01 + 1.430002E+01 6.000000E+01 1 4.857093E+01 8.964041E+01 3.048303E-01 4.856997E+01 + 1.430002E+01 6.000000E+01 2 8.925934E+01 8.943781E+01 8.758137E-01 8.925504E+01 + 1.430002E+01 6.000000E+01 3 1.277345E+02 1.404871E+00 1.276961E+02 3.131686E+00 + 1.430002E+01 6.000000E+01 4 3.286065E+02 8.943757E+01 3.225616E+00 3.285907E+02 + 1.430002E+01 6.000000E+01 5 3.465981E+02 8.964080E+01 2.172868E+00 3.465913E+02 + 1.430002E+01 6.000000E+01 6 3.185517E+02 -3.732009E-02 3.185517E+02 -2.074914E-01 + 1.430002E+01 9.000000E+01 1 5.204746E-06 -8.997382E+01 2.378467E-09 -5.204746E-06 + 1.430002E+01 9.000000E+01 2 1.053429E+02 8.943713E+01 1.034876E+00 1.053378E+02 + 1.430002E+01 9.000000E+01 3 1.306822E+02 1.424090E+00 1.306419E+02 3.247781E+00 + 1.430002E+01 9.000000E+01 4 3.929597E+02 8.944426E+01 3.811475E+00 3.929412E+02 + 1.430002E+01 9.000000E+01 5 2.153368E-04 -8.988021E+01 4.502167E-07 -2.153363E-04 + 1.430002E+01 9.000000E+01 6 2.796662E-05 1.799757E+02 -2.796661E-05 1.185471E-08 + 1.440002E+01 0.000000E+00 1 9.105280E+01 8.964269E+01 5.678107E-01 9.105103E+01 + 1.440002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.440002E+01 0.000000E+00 3 1.204055E+02 1.328791E+00 1.203731E+02 2.792167E+00 + 1.440002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.440002E+01 0.000000E+00 5 6.536740E+02 8.964238E+01 4.079990E+00 6.536613E+02 + 1.440002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.440002E+01 3.000000E+01 1 8.036610E+01 8.964403E+01 4.993050E-01 8.036456E+01 + 1.440002E+01 3.000000E+01 2 4.900182E+01 8.945224E+01 4.684564E-01 4.899958E+01 + 1.440002E+01 3.000000E+01 3 1.231159E+02 1.346855E+00 1.230819E+02 2.893824E+00 + 1.440002E+01 3.000000E+01 4 1.751390E+02 8.943670E+01 1.721862E+00 1.751306E+02 + 1.440002E+01 3.000000E+01 5 5.775671E+02 8.964409E+01 3.587728E+00 5.775560E+02 + 1.440002E+01 3.000000E+01 6 2.996143E+02 -3.625504E-02 2.996142E+02 -1.895868E-01 + 1.440002E+01 6.000000E+01 1 4.820866E+01 8.964648E+01 2.974450E-01 4.820774E+01 + 1.440002E+01 6.000000E+01 2 8.858540E+01 8.945092E+01 8.489271E-01 8.858134E+01 + 1.440002E+01 6.000000E+01 3 1.287342E+02 1.383388E+00 1.286967E+02 3.107944E+00 + 1.440002E+01 6.000000E+01 4 3.254849E+02 8.945070E+01 3.120404E+00 3.254700E+02 + 1.440002E+01 6.000000E+01 5 3.467580E+02 8.964685E+01 2.137307E+00 3.467514E+02 + 1.440002E+01 6.000000E+01 6 3.129503E+02 -3.570894E-02 3.129503E+02 -1.950427E-01 + 1.440002E+01 9.000000E+01 1 5.162310E-06 -8.998068E+01 1.740849E-09 -5.162309E-06 + 1.440002E+01 9.000000E+01 2 1.045026E+02 8.945028E+01 1.002634E+00 1.044978E+02 + 1.440002E+01 9.000000E+01 3 1.316441E+02 1.401820E+00 1.316047E+02 3.220534E+00 + 1.440002E+01 9.000000E+01 4 3.889918E+02 8.945715E+01 3.685435E+00 3.889743E+02 + 1.440002E+01 9.000000E+01 5 2.139940E-04 -8.988361E+01 4.347340E-07 -2.139936E-04 + 1.440002E+01 9.000000E+01 6 2.746197E-05 1.799767E+02 -2.746197E-05 1.114580E-08 + 1.450002E+01 0.000000E+00 1 9.047619E+01 8.964887E+01 5.544686E-01 9.047449E+01 + 1.450002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.450002E+01 0.000000E+00 3 1.214867E+02 1.309920E+00 1.214549E+02 2.777238E+00 + 1.450002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.450002E+01 0.000000E+00 5 6.546560E+02 8.964857E+01 4.015304E+00 6.546437E+02 + 1.450002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.450002E+01 3.000000E+01 1 7.982861E+01 8.965012E+01 4.874841E-01 7.982712E+01 + 1.450002E+01 3.000000E+01 2 4.867495E+01 8.946483E+01 4.546393E-01 4.867282E+01 + 1.450002E+01 3.000000E+01 3 1.241655E+02 1.327266E+00 1.241322E+02 2.876056E+00 + 1.450002E+01 3.000000E+01 4 1.737033E+02 8.944986E+01 1.667834E+00 1.736953E+02 + 1.450002E+01 3.000000E+01 5 5.781986E+02 8.965018E+01 3.530241E+00 5.781878E+02 + 1.450002E+01 3.000000E+01 6 2.946451E+02 -3.469753E-02 2.946450E+02 -1.784330E-01 + 1.450002E+01 6.000000E+01 1 4.785126E+01 8.965242E+01 2.902845E-01 4.785038E+01 + 1.450002E+01 6.000000E+01 2 8.792124E+01 8.946358E+01 8.231394E-01 8.791739E+01 + 1.450002E+01 6.000000E+01 3 1.297157E+02 1.362360E+00 1.296790E+02 3.084047E+00 + 1.450002E+01 6.000000E+01 4 3.224222E+02 8.946337E+01 3.019745E+00 3.224081E+02 + 1.450002E+01 6.000000E+01 5 3.468647E+02 8.965275E+01 2.102222E+00 3.468583E+02 + 1.450002E+01 6.000000E+01 6 3.075024E+02 -3.418531E-02 3.075024E+02 -1.834701E-01 + 1.450002E+01 9.000000E+01 1 5.120589E-06 -8.998712E+01 1.150930E-09 -5.120589E-06 + 1.450002E+01 9.000000E+01 2 1.036764E+02 8.946297E+01 9.717385E-01 1.036719E+02 + 1.450002E+01 9.000000E+01 3 1.325885E+02 1.380049E+00 1.325500E+02 3.193270E+00 + 1.450002E+01 9.000000E+01 4 3.851090E+02 8.946960E+01 3.564947E+00 3.850925E+02 + 1.450002E+01 9.000000E+01 5 2.126657E-04 -8.988687E+01 4.199055E-07 -2.126653E-04 + 1.450002E+01 9.000000E+01 6 2.697163E-05 1.799777E+02 -2.697163E-05 1.048662E-08 + 1.460002E+01 0.000000E+00 1 8.990534E+01 8.965489E+01 5.415218E-01 8.990371E+01 + 1.460002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.460002E+01 0.000000E+00 3 1.225487E+02 1.291372E+00 1.225176E+02 2.761854E+00 + 1.460002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.460002E+01 0.000000E+00 5 6.555183E+02 8.965462E+01 3.951430E+00 6.555064E+02 + 1.460002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.460002E+01 3.000000E+01 1 7.929740E+01 8.965606E+01 4.760134E-01 7.929597E+01 + 1.460002E+01 3.000000E+01 2 4.835192E+01 8.947699E+01 4.413630E-01 4.834990E+01 + 1.460002E+01 3.000000E+01 3 1.251974E+02 1.308041E+00 1.251648E+02 2.857962E+00 + 1.460002E+01 3.000000E+01 4 1.722886E+02 8.946256E+01 1.616053E+00 1.722810E+02 + 1.460002E+01 3.000000E+01 5 5.787271E+02 8.965612E+01 3.473412E+00 5.787167E+02 + 1.460002E+01 3.000000E+01 6 2.898024E+02 -3.322428E-02 2.898023E+02 -1.680486E-01 + 1.460002E+01 6.000000E+01 1 4.749929E+01 8.965822E+01 2.833395E-01 4.749844E+01 + 1.460002E+01 6.000000E+01 2 8.726714E+01 8.947580E+01 7.983971E-01 8.726349E+01 + 1.460002E+01 6.000000E+01 3 1.306810E+02 1.341744E+00 1.306452E+02 3.059990E+00 + 1.460002E+01 6.000000E+01 4 3.194173E+02 8.947560E+01 2.923404E+00 3.194039E+02 + 1.460002E+01 6.000000E+01 5 3.469147E+02 8.965853E+01 2.067532E+00 3.469086E+02 + 1.460002E+01 6.000000E+01 6 3.022028E+02 -3.274328E-02 3.022027E+02 -1.727022E-01 + 1.460002E+01 9.000000E+01 1 5.079569E-06 -8.999317E+01 6.052689E-10 -5.079569E-06 + 1.460002E+01 9.000000E+01 2 1.028633E+02 8.947523E+01 9.421161E-01 1.028589E+02 + 1.460002E+01 9.000000E+01 3 1.335172E+02 1.358744E+00 1.334797E+02 3.166005E+00 + 1.460002E+01 9.000000E+01 4 3.813017E+02 8.948164E+01 3.449689E+00 3.812861E+02 + 1.460002E+01 9.000000E+01 5 2.113527E-04 -8.989001E+01 4.056980E-07 -2.113523E-04 + 1.460002E+01 9.000000E+01 6 2.649499E-05 1.799787E+02 -2.649499E-05 9.873189E-09 + 1.470002E+01 0.000000E+00 1 8.934002E+01 8.966077E+01 5.289591E-01 8.933846E+01 + 1.470002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.470002E+01 0.000000E+00 3 1.235926E+02 1.273147E+00 1.235621E+02 2.746077E+00 + 1.470002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.470002E+01 0.000000E+00 5 6.562511E+02 8.966051E+01 3.888381E+00 6.562396E+02 + 1.470002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.470002E+01 3.000000E+01 1 7.877178E+01 8.966186E+01 4.648857E-01 7.877041E+01 + 1.470002E+01 3.000000E+01 2 4.803225E+01 8.948874E+01 4.285992E-01 4.803034E+01 + 1.470002E+01 3.000000E+01 3 1.262114E+02 1.289177E+00 1.261794E+02 2.839566E+00 + 1.470002E+01 3.000000E+01 4 1.708953E+02 8.947484E+01 1.566375E+00 1.708882E+02 + 1.470002E+01 3.000000E+01 5 5.791414E+02 8.966192E+01 3.417307E+00 5.791313E+02 + 1.470002E+01 3.000000E+01 6 2.850809E+02 -3.182985E-02 2.850809E+02 -1.583726E-01 + 1.470002E+01 6.000000E+01 1 4.715218E+01 8.966389E+01 2.766046E-01 4.715137E+01 + 1.470002E+01 6.000000E+01 2 8.662259E+01 8.948761E+01 7.746499E-01 8.661913E+01 + 1.470002E+01 6.000000E+01 3 1.316294E+02 1.321567E+00 1.315944E+02 3.035854E+00 + 1.470002E+01 6.000000E+01 4 3.164691E+02 8.948743E+01 2.831140E+00 3.164564E+02 + 1.470002E+01 6.000000E+01 5 3.469092E+02 8.966417E+01 2.033355E+00 3.469033E+02 + 1.470002E+01 6.000000E+01 6 2.970460E+02 -3.137781E-02 2.970460E+02 -1.626761E-01 + 1.470002E+01 9.000000E+01 1 5.039243E-06 -8.999886E+01 1.007715E-10 -5.039243E-06 + 1.470002E+01 9.000000E+01 2 1.020634E+02 8.948706E+01 9.137036E-01 1.020593E+02 + 1.470002E+01 9.000000E+01 3 1.344297E+02 1.337892E+00 1.343931E+02 3.138733E+00 + 1.470002E+01 9.000000E+01 4 3.775727E+02 8.949325E+01 3.339386E+00 3.775579E+02 + 1.470002E+01 9.000000E+01 5 2.100547E-04 -8.989306E+01 3.920825E-07 -2.100543E-04 + 1.470002E+01 9.000000E+01 6 2.603161E-05 1.799795E+02 -2.603161E-05 9.301885E-09 + 1.480002E+01 0.000000E+00 1 8.877970E+01 8.966649E+01 5.167668E-01 8.877820E+01 + 1.480002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.480002E+01 0.000000E+00 3 1.246186E+02 1.255260E+00 1.245887E+02 2.729977E+00 + 1.480002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.480002E+01 0.000000E+00 5 6.568660E+02 8.966626E+01 3.826134E+00 6.568548E+02 + 1.480002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.480002E+01 3.000000E+01 1 7.825255E+01 8.966753E+01 4.540872E-01 7.825123E+01 + 1.480002E+01 3.000000E+01 2 4.771630E+01 8.950009E+01 4.163271E-01 4.771449E+01 + 1.480002E+01 3.000000E+01 3 1.272083E+02 1.270658E+00 1.271770E+02 2.820889E+00 + 1.480002E+01 3.000000E+01 4 1.695220E+02 8.948669E+01 1.518737E+00 1.695152E+02 + 1.480002E+01 3.000000E+01 5 5.794677E+02 8.966758E+01 3.361999E+00 5.794579E+02 + 1.480002E+01 3.000000E+01 6 2.804776E+02 -3.050905E-02 2.804776E+02 -1.493496E-01 + 1.480002E+01 6.000000E+01 1 4.681024E+01 8.966943E+01 2.700717E-01 4.680946E+01 + 1.480002E+01 6.000000E+01 2 8.598749E+01 8.949902E+01 7.518459E-01 8.598420E+01 + 1.480002E+01 6.000000E+01 3 1.325615E+02 1.301795E+00 1.325273E+02 3.011619E+00 + 1.480002E+01 6.000000E+01 4 3.135744E+02 8.949885E+01 2.742731E+00 3.135624E+02 + 1.480002E+01 6.000000E+01 5 3.468528E+02 8.966969E+01 1.999662E+00 3.468470E+02 + 1.480002E+01 6.000000E+01 6 2.920262E+02 -3.008408E-02 2.920262E+02 -1.533331E-01 + 1.480002E+01 9.000000E+01 1 4.999580E-06 -9.000419E+01 -3.654768E-10 -4.999580E-06 + 1.480002E+01 9.000000E+01 2 1.012766E+02 8.949850E+01 8.864421E-01 1.012727E+02 + 1.480002E+01 9.000000E+01 3 1.353274E+02 1.317483E+00 1.352916E+02 3.111501E+00 + 1.480002E+01 9.000000E+01 4 3.739180E+02 8.950448E+01 3.233794E+00 3.739040E+02 + 1.480002E+01 9.000000E+01 5 2.087706E-04 -8.989598E+01 3.790296E-07 -2.087702E-04 + 1.480002E+01 9.000000E+01 6 2.558093E-05 1.799804E+02 -2.558093E-05 8.769400E-09 + 1.490002E+01 0.000000E+00 1 8.822519E+01 8.967208E+01 5.049328E-01 8.822375E+01 + 1.490002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.490002E+01 0.000000E+00 3 1.256275E+02 1.237665E+00 1.255981E+02 2.713509E+00 + 1.490002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.490002E+01 0.000000E+00 5 6.573676E+02 8.967187E+01 3.764722E+00 6.573568E+02 + 1.490002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.490002E+01 3.000000E+01 1 7.773914E+01 8.967305E+01 4.436097E-01 7.773788E+01 + 1.490002E+01 3.000000E+01 2 4.740380E+01 8.951105E+01 4.045225E-01 4.740208E+01 + 1.490002E+01 3.000000E+01 3 1.281878E+02 1.252486E+00 1.281572E+02 2.801964E+00 + 1.490002E+01 3.000000E+01 4 1.681700E+02 8.949814E+01 1.473014E+00 1.681635E+02 + 1.490002E+01 3.000000E+01 5 5.797009E+02 8.967310E+01 3.307492E+00 5.796915E+02 + 1.490002E+01 3.000000E+01 6 2.759885E+02 -2.925755E-02 2.759884E+02 -1.409309E-01 + 1.490002E+01 6.000000E+01 1 4.647306E+01 8.967484E+01 2.637374E-01 4.647231E+01 + 1.490002E+01 6.000000E+01 2 8.536143E+01 8.951005E+01 7.299417E-01 8.535831E+01 + 1.490002E+01 6.000000E+01 3 1.334781E+02 1.282427E+00 1.334447E+02 2.987334E+00 + 1.490002E+01 6.000000E+01 4 3.107328E+02 8.950988E+01 2.658035E+00 3.107214E+02 + 1.490002E+01 6.000000E+01 5 3.467537E+02 8.967508E+01 1.966433E+00 3.467481E+02 + 1.490002E+01 6.000000E+01 6 2.871392E+02 -2.885762E-02 2.871392E+02 -1.446207E-01 + 1.490002E+01 9.000000E+01 1 4.960578E-06 -9.000919E+01 -7.961881E-10 -4.960578E-06 + 1.490002E+01 9.000000E+01 2 1.005024E+02 8.950956E+01 8.602720E-01 1.004988E+02 + 1.490002E+01 9.000000E+01 3 1.362085E+02 1.297531E+00 1.361736E+02 3.084341E+00 + 1.490002E+01 9.000000E+01 4 3.703365E+02 8.951534E+01 3.132666E+00 3.703233E+02 + 1.490002E+01 9.000000E+01 5 2.075021E-04 -8.989880E+01 3.665159E-07 -2.075017E-04 + 1.490002E+01 9.000000E+01 6 2.514250E-05 1.799812E+02 -2.514250E-05 8.272731E-09 + 1.500002E+01 0.000000E+00 1 8.767646E+01 8.967754E+01 4.934455E-01 8.767507E+01 + 1.500002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.500002E+01 0.000000E+00 3 1.266190E+02 1.220399E+00 1.265903E+02 2.696779E+00 + 1.500002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.500002E+01 0.000000E+00 5 6.577644E+02 8.967734E+01 3.704196E+00 6.577540E+02 + 1.500002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.500002E+01 3.000000E+01 1 7.723136E+01 8.967844E+01 4.334382E-01 7.723015E+01 + 1.500002E+01 3.000000E+01 2 4.709496E+01 8.952168E+01 3.931641E-01 4.709332E+01 + 1.500002E+01 3.000000E+01 3 1.291510E+02 1.234663E+00 1.291210E+02 2.782850E+00 + 1.500002E+01 3.000000E+01 4 1.668384E+02 8.950921E+01 1.429110E+00 1.668323E+02 + 1.500002E+01 3.000000E+01 5 5.798446E+02 8.967849E+01 3.253777E+00 5.798354E+02 + 1.500002E+01 3.000000E+01 6 2.716092E+02 -2.807072E-02 2.716092E+02 -1.330685E-01 + 1.500002E+01 6.000000E+01 1 4.614055E+01 8.968013E+01 2.575900E-01 4.613984E+01 + 1.500002E+01 6.000000E+01 2 8.474454E+01 8.952071E+01 7.088934E-01 8.474157E+01 + 1.500002E+01 6.000000E+01 3 1.343785E+02 1.263469E+00 1.343458E+02 2.963034E+00 + 1.500002E+01 6.000000E+01 4 3.079449E+02 8.952056E+01 2.576803E+00 3.079342E+02 + 1.500002E+01 6.000000E+01 5 3.466065E+02 8.968035E+01 1.933706E+00 3.466011E+02 + 1.500002E+01 6.000000E+01 6 2.823795E+02 -2.769420E-02 2.823794E+02 -1.364895E-01 + 1.500002E+01 9.000000E+01 1 4.922194E-06 -9.001389E+01 -1.193877E-09 -4.922194E-06 + 1.500002E+01 9.000000E+01 2 9.974036E+01 8.952024E+01 8.351440E-01 9.973687E+01 + 1.500002E+01 9.000000E+01 3 1.370753E+02 1.277996E+00 1.370412E+02 3.057245E+00 + 1.500002E+01 9.000000E+01 4 3.668237E+02 8.952583E+01 3.035752E+00 3.668111E+02 + 1.500002E+01 9.000000E+01 5 2.062474E-04 -8.990152E+01 3.545141E-07 -2.062470E-04 + 1.500002E+01 9.000000E+01 6 2.471590E-05 1.799819E+02 -2.471590E-05 7.809119E-09 + 1.510002E+01 0.000000E+00 1 8.713300E+01 8.968285E+01 4.822934E-01 8.713167E+01 + 1.510002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.510002E+01 0.000000E+00 3 1.275944E+02 1.203435E+00 1.275662E+02 2.679784E+00 + 1.510002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.510002E+01 0.000000E+00 5 6.580576E+02 8.968267E+01 3.644553E+00 6.580475E+02 + 1.510002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.510002E+01 3.000000E+01 1 7.672961E+01 8.968371E+01 4.235687E-01 7.672844E+01 + 1.510002E+01 3.000000E+01 2 4.678942E+01 8.953194E+01 3.822304E-01 4.678786E+01 + 1.510002E+01 3.000000E+01 3 1.300972E+02 1.217184E+00 1.300678E+02 2.763560E+00 + 1.510002E+01 3.000000E+01 4 1.655255E+02 8.951991E+01 1.386959E+00 1.655197E+02 + 1.510002E+01 3.000000E+01 5 5.799040E+02 8.968375E+01 3.200826E+00 5.798951E+02 + 1.510002E+01 3.000000E+01 6 2.673363E+02 -2.694475E-02 2.673362E+02 -1.257215E-01 + 1.510002E+01 6.000000E+01 1 4.581274E+01 8.968530E+01 2.516267E-01 4.581205E+01 + 1.510002E+01 6.000000E+01 2 8.413657E+01 8.953103E+01 6.886593E-01 8.413375E+01 + 1.510002E+01 6.000000E+01 3 1.352637E+02 1.244908E+00 1.352318E+02 2.938744E+00 + 1.510002E+01 6.000000E+01 4 3.052050E+02 8.953088E+01 2.498896E+00 3.051948E+02 + 1.510002E+01 6.000000E+01 5 3.464147E+02 8.968550E+01 1.901496E+00 3.464095E+02 + 1.510002E+01 6.000000E+01 6 2.777427E+02 -2.658994E-02 2.777427E+02 -1.288954E-01 + 1.510002E+01 9.000000E+01 1 4.884440E-06 -9.001831E+01 -1.560826E-09 -4.884439E-06 + 1.510002E+01 9.000000E+01 2 9.899045E+01 8.953059E+01 8.110016E-01 9.898713E+01 + 1.510002E+01 9.000000E+01 3 1.379266E+02 1.258885E+00 1.378933E+02 3.030236E+00 + 1.510002E+01 9.000000E+01 4 3.633807E+02 8.953598E+01 2.942872E+00 3.633688E+02 + 1.510002E+01 9.000000E+01 5 2.050074E-04 -8.990414E+01 3.429994E-07 -2.050071E-04 + 1.510002E+01 9.000000E+01 6 2.430062E-05 1.799826E+02 -2.430062E-05 7.376046E-09 + 1.520002E+01 0.000000E+00 1 8.659521E+01 8.968806E+01 4.714664E-01 8.659393E+01 + 1.520002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.520002E+01 0.000000E+00 3 1.285534E+02 1.186760E+00 1.285259E+02 2.662521E+00 + 1.520002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.520002E+01 0.000000E+00 5 6.582505E+02 8.968787E+01 3.585832E+00 6.582408E+02 + 1.520002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.520002E+01 3.000000E+01 1 7.623369E+01 8.968886E+01 4.139851E-01 7.623257E+01 + 1.520002E+01 3.000000E+01 2 4.648751E+01 8.954188E+01 3.717035E-01 4.648602E+01 + 1.520002E+01 3.000000E+01 3 1.310284E+02 1.199995E+00 1.309997E+02 2.744039E+00 + 1.520002E+01 3.000000E+01 4 1.642324E+02 8.953027E+01 1.346447E+00 1.642269E+02 + 1.520002E+01 3.000000E+01 5 5.798818E+02 8.968889E+01 3.148697E+00 5.798732E+02 + 1.520002E+01 3.000000E+01 6 2.631668E+02 -2.587582E-02 2.631667E+02 -1.188509E-01 + 1.520002E+01 6.000000E+01 1 4.548966E+01 8.969035E+01 2.458408E-01 4.548900E+01 + 1.520002E+01 6.000000E+01 2 8.353723E+01 8.954101E+01 6.692020E-01 8.353455E+01 + 1.520002E+01 6.000000E+01 3 1.361334E+02 1.226707E+00 1.361022E+02 2.914402E+00 + 1.520002E+01 6.000000E+01 4 3.025162E+02 8.954087E+01 2.424147E+00 3.025065E+02 + 1.520002E+01 6.000000E+01 5 3.461852E+02 8.969054E+01 1.869825E+00 3.461802E+02 + 1.520002E+01 6.000000E+01 6 2.732248E+02 -2.554131E-02 2.732248E+02 -1.217982E-01 + 1.520002E+01 9.000000E+01 1 4.847285E-06 -9.002245E+01 -1.899215E-09 -4.847284E-06 + 1.520002E+01 9.000000E+01 2 9.825237E+01 8.954059E+01 7.878018E-01 9.824921E+01 + 1.520002E+01 9.000000E+01 3 1.387645E+02 1.240151E+00 1.387320E+02 3.003283E+00 + 1.520002E+01 9.000000E+01 4 3.600040E+02 8.954581E+01 2.853787E+00 3.599927E+02 + 1.520002E+01 9.000000E+01 5 2.037803E-04 -8.990667E+01 3.319499E-07 -2.037801E-04 + 1.520002E+01 9.000000E+01 6 2.389628E-05 1.799833E+02 -2.389628E-05 6.971225E-09 + 1.530002E+01 0.000000E+00 1 8.606243E+01 8.969312E+01 4.609525E-01 8.606120E+01 + 1.530002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.530002E+01 0.000000E+00 3 1.294955E+02 1.170427E+00 1.294685E+02 2.645124E+00 + 1.530002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.530002E+01 0.000000E+00 5 6.583472E+02 8.969296E+01 3.527977E+00 6.583377E+02 + 1.530002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.530002E+01 3.000000E+01 1 7.574323E+01 8.969388E+01 4.046807E-01 7.574215E+01 + 1.530002E+01 3.000000E+01 2 4.618900E+01 8.955148E+01 3.615649E-01 4.618759E+01 + 1.530002E+01 3.000000E+01 3 1.319434E+02 1.183168E+00 1.319152E+02 2.724460E+00 + 1.530002E+01 3.000000E+01 4 1.629589E+02 8.954028E+01 1.307519E+00 1.629536E+02 + 1.530002E+01 3.000000E+01 5 5.797832E+02 8.969391E+01 3.097349E+00 5.797749E+02 + 1.530002E+01 3.000000E+01 6 2.590969E+02 -2.486056E-02 2.590969E+02 -1.124218E-01 + 1.530002E+01 6.000000E+01 1 4.517104E+01 8.969530E+01 2.402260E-01 4.517040E+01 + 1.530002E+01 6.000000E+01 2 8.294641E+01 8.955067E+01 6.504865E-01 8.294386E+01 + 1.530002E+01 6.000000E+01 3 1.369893E+02 1.208894E+00 1.369588E+02 2.890149E+00 + 1.530002E+01 6.000000E+01 4 2.998741E+02 8.955054E+01 2.352382E+00 2.998648E+02 + 1.530002E+01 6.000000E+01 5 3.459137E+02 8.969545E+01 1.838653E+00 3.459088E+02 + 1.530002E+01 6.000000E+01 6 2.688218E+02 -2.454494E-02 2.688217E+02 -1.151606E-01 + 1.530002E+01 9.000000E+01 1 4.810727E-06 -9.002634E+01 -2.211027E-09 -4.810727E-06 + 1.530002E+01 9.000000E+01 2 9.752534E+01 8.955027E+01 7.654933E-01 9.752234E+01 + 1.530002E+01 9.000000E+01 3 1.395885E+02 1.221842E+00 1.395568E+02 2.976523E+00 + 1.530002E+01 9.000000E+01 4 3.566913E+02 8.955532E+01 2.768331E+00 3.566806E+02 + 1.530002E+01 9.000000E+01 5 2.025673E-04 -8.990911E+01 3.213458E-07 -2.025671E-04 + 1.530002E+01 9.000000E+01 6 2.350250E-05 1.799839E+02 -2.350250E-05 6.592542E-09 + 1.540002E+01 0.000000E+00 1 8.553530E+01 8.969807E+01 4.507416E-01 8.553411E+01 + 1.540002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.540002E+01 0.000000E+00 3 1.304226E+02 1.154364E+00 1.303961E+02 2.627505E+00 + 1.540002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.540002E+01 0.000000E+00 5 6.583620E+02 8.969792E+01 3.470994E+00 6.583528E+02 + 1.540002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.540002E+01 3.000000E+01 1 7.525835E+01 8.969878E+01 3.956480E-01 7.525731E+01 + 1.540002E+01 3.000000E+01 2 4.589386E+01 8.956080E+01 3.517953E-01 4.589251E+01 + 1.540002E+01 3.000000E+01 3 1.328431E+02 1.166649E+00 1.328155E+02 2.704745E+00 + 1.540002E+01 3.000000E+01 4 1.617028E+02 8.954997E+01 1.270088E+00 1.616978E+02 + 1.540002E+01 3.000000E+01 5 5.796142E+02 8.969881E+01 3.046833E+00 5.796062E+02 + 1.540002E+01 3.000000E+01 6 2.551239E+02 -2.389564E-02 2.551238E+02 -1.064014E-01 + 1.540002E+01 6.000000E+01 1 4.485680E+01 8.970012E+01 2.347775E-01 4.485618E+01 + 1.540002E+01 6.000000E+01 2 8.236400E+01 8.956002E+01 6.324736E-01 8.236157E+01 + 1.540002E+01 6.000000E+01 3 1.378305E+02 1.191440E+00 1.378007E+02 2.865917E+00 + 1.540002E+01 6.000000E+01 4 2.972792E+02 8.955989E+01 2.283461E+00 2.972704E+02 + 1.540002E+01 6.000000E+01 5 3.456057E+02 8.970026E+01 1.807986E+00 3.456010E+02 + 1.540002E+01 6.000000E+01 6 2.645298E+02 -2.359766E-02 2.645297E+02 -1.089484E-01 + 1.540002E+01 9.000000E+01 1 4.774732E-06 -9.002998E+01 -2.498079E-09 -4.774731E-06 + 1.540002E+01 9.000000E+01 2 9.680955E+01 8.955964E+01 7.440415E-01 9.680669E+01 + 1.540002E+01 9.000000E+01 3 1.403971E+02 1.203922E+00 1.403661E+02 2.949863E+00 + 1.540002E+01 9.000000E+01 4 3.534423E+02 8.956452E+01 2.686297E+00 3.534321E+02 + 1.540002E+01 9.000000E+01 5 2.013682E-04 -8.991146E+01 3.111631E-07 -2.013679E-04 + 1.540002E+01 9.000000E+01 6 2.311891E-05 1.799845E+02 -2.311891E-05 6.238065E-09 + 1.550002E+01 0.000000E+00 1 8.501358E+01 8.970290E+01 4.408222E-01 8.501244E+01 + 1.550002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.550002E+01 0.000000E+00 3 1.313343E+02 1.138597E+00 1.313084E+02 2.609739E+00 + 1.550002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.550002E+01 0.000000E+00 5 6.582881E+02 8.970277E+01 3.414966E+00 6.582793E+02 + 1.550002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.550002E+01 3.000000E+01 1 7.477923E+01 8.970358E+01 3.868747E-01 7.477823E+01 + 1.550002E+01 3.000000E+01 2 4.560212E+01 8.956982E+01 3.423804E-01 4.560084E+01 + 1.550002E+01 3.000000E+01 3 1.337283E+02 1.150445E+00 1.337013E+02 2.684956E+00 + 1.550002E+01 3.000000E+01 4 1.604662E+02 8.955936E+01 1.234099E+00 1.604614E+02 + 1.550002E+01 3.000000E+01 5 5.793742E+02 8.970361E+01 2.997118E+00 5.793665E+02 + 1.550002E+01 3.000000E+01 6 2.512444E+02 -2.297812E-02 2.512443E+02 -1.007600E-01 + 1.550002E+01 6.000000E+01 1 4.454686E+01 8.970483E+01 2.294877E-01 4.454627E+01 + 1.550002E+01 6.000000E+01 2 8.178957E+01 8.956908E+01 6.151325E-01 8.178726E+01 + 1.550002E+01 6.000000E+01 3 1.386578E+02 1.174335E+00 1.386287E+02 2.841734E+00 + 1.550002E+01 6.000000E+01 4 2.947299E+02 8.956896E+01 2.217250E+00 2.947216E+02 + 1.550002E+01 6.000000E+01 5 3.452635E+02 8.970497E+01 1.777822E+00 3.452590E+02 + 1.550002E+01 6.000000E+01 6 2.603443E+02 -2.269665E-02 2.603442E+02 -1.031305E-01 + 1.550002E+01 9.000000E+01 1 4.739297E-06 -9.003339E+01 -2.762163E-09 -4.739296E-06 + 1.550002E+01 9.000000E+01 2 9.610486E+01 8.956872E+01 7.234001E-01 9.610213E+01 + 1.550002E+01 9.000000E+01 3 1.411937E+02 1.186374E+00 1.411634E+02 2.923365E+00 + 1.550002E+01 9.000000E+01 4 3.502533E+02 8.957345E+01 2.607532E+00 3.502436E+02 + 1.550002E+01 9.000000E+01 5 2.001821E-04 -8.991374E+01 3.013827E-07 -2.001819E-04 + 1.550002E+01 9.000000E+01 6 2.274516E-05 1.799851E+02 -2.274516E-05 5.906017E-09 + 1.560002E+01 0.000000E+00 1 8.449736E+01 8.970763E+01 4.311863E-01 8.449626E+01 + 1.560002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.560002E+01 0.000000E+00 3 1.322307E+02 1.123103E+00 1.322053E+02 2.591802E+00 + 1.560002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.560002E+01 0.000000E+00 5 6.581295E+02 8.970750E+01 3.359847E+00 6.581208E+02 + 1.560002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.560002E+01 3.000000E+01 1 7.430541E+01 8.970826E+01 3.783545E-01 7.430445E+01 + 1.560002E+01 3.000000E+01 2 4.531374E+01 8.957856E+01 3.333023E-01 4.531251E+01 + 1.560002E+01 3.000000E+01 3 1.345982E+02 1.134543E+00 1.345718E+02 2.665074E+00 + 1.560002E+01 3.000000E+01 4 1.592472E+02 8.956844E+01 1.199459E+00 1.592427E+02 + 1.560002E+01 3.000000E+01 5 5.790646E+02 8.970828E+01 2.948259E+00 5.790571E+02 + 1.560002E+01 3.000000E+01 6 2.474553E+02 -2.210524E-02 2.474553E+02 -9.547052E-02 + 1.560002E+01 6.000000E+01 1 4.424113E+01 8.970945E+01 2.243525E-01 4.424057E+01 + 1.560002E+01 6.000000E+01 2 8.122330E+01 8.957786E+01 5.984322E-01 8.122110E+01 + 1.560002E+01 6.000000E+01 3 1.394710E+02 1.157583E+00 1.394425E+02 2.817630E+00 + 1.560002E+01 6.000000E+01 4 2.922254E+02 8.957774E+01 2.153616E+00 2.922175E+02 + 1.560002E+01 6.000000E+01 5 3.448848E+02 8.970957E+01 1.748207E+00 3.448803E+02 + 1.560002E+01 6.000000E+01 6 2.562623E+02 -2.183915E-02 2.562622E+02 -9.767821E-02 + 1.560002E+01 9.000000E+01 1 4.704414E-06 -9.003660E+01 -3.004812E-09 -4.704413E-06 + 1.560002E+01 9.000000E+01 2 9.541071E+01 8.957751E+01 7.035336E-01 9.540811E+01 + 1.560002E+01 9.000000E+01 3 1.419765E+02 1.169180E+00 1.419470E+02 2.896977E+00 + 1.560002E+01 9.000000E+01 4 3.471267E+02 8.958209E+01 2.531875E+00 3.471174E+02 + 1.560002E+01 9.000000E+01 5 1.990087E-04 -8.991594E+01 2.919870E-07 -1.990085E-04 + 1.560002E+01 9.000000E+01 6 2.238082E-05 1.799857E+02 -2.238082E-05 5.594784E-09 + 1.570002E+01 0.000000E+00 1 8.398630E+01 8.971223E+01 4.218252E-01 8.398524E+01 + 1.570002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.570002E+01 0.000000E+00 3 1.331126E+02 1.107914E+00 1.330877E+02 2.573803E+00 + 1.570002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.570002E+01 0.000000E+00 5 6.578960E+02 8.971211E+01 3.305639E+00 6.578877E+02 + 1.570002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.570002E+01 3.000000E+01 1 7.383731E+01 8.971283E+01 3.700774E-01 7.383638E+01 + 1.570002E+01 3.000000E+01 2 4.502851E+01 8.958703E+01 3.245486E-01 4.502734E+01 + 1.570002E+01 3.000000E+01 3 1.354543E+02 1.118935E+00 1.354284E+02 2.645133E+00 + 1.570002E+01 3.000000E+01 4 1.580459E+02 8.957725E+01 1.166122E+00 1.580416E+02 + 1.570002E+01 3.000000E+01 5 5.786974E+02 8.971285E+01 2.900206E+00 5.786901E+02 + 1.570002E+01 3.000000E+01 6 2.437544E+02 -2.127433E-02 2.437544E+02 -9.050775E-02 + 1.570002E+01 6.000000E+01 1 4.393958E+01 8.971396E+01 2.193666E-01 4.393903E+01 + 1.570002E+01 6.000000E+01 2 8.066491E+01 8.958636E+01 5.823464E-01 8.066280E+01 + 1.570002E+01 6.000000E+01 3 1.402710E+02 1.141168E+00 1.402432E+02 2.793614E+00 + 1.570002E+01 6.000000E+01 4 2.897626E+02 8.958625E+01 2.092440E+00 2.897550E+02 + 1.570002E+01 6.000000E+01 5 3.444773E+02 8.971407E+01 1.719118E+00 3.444730E+02 + 1.570002E+01 6.000000E+01 6 2.522802E+02 -2.102265E-02 2.522801E+02 -9.256525E-02 + 1.570002E+01 9.000000E+01 1 4.670068E-06 -9.003960E+01 -3.227515E-09 -4.670067E-06 + 1.570002E+01 9.000000E+01 2 9.472731E+01 8.958603E+01 6.844041E-01 9.472484E+01 + 1.570002E+01 9.000000E+01 3 1.427458E+02 1.152369E+00 1.427170E+02 2.870800E+00 + 1.570002E+01 9.000000E+01 4 3.440529E+02 8.959046E+01 2.459167E+00 3.440441E+02 + 1.570002E+01 9.000000E+01 5 1.978478E-04 -8.991805E+01 2.829585E-07 -1.978476E-04 + 1.570002E+01 9.000000E+01 6 2.202568E-05 1.799862E+02 -2.202568E-05 5.302874E-09 + 1.580002E+01 0.000000E+00 1 8.348027E+01 8.971673E+01 4.127260E-01 8.347925E+01 + 1.580002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.580002E+01 0.000000E+00 3 1.339804E+02 1.092994E+00 1.339560E+02 2.555701E+00 + 1.580002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.580002E+01 0.000000E+00 5 6.575893E+02 8.971663E+01 3.252314E+00 6.575812E+02 + 1.580002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.580002E+01 3.000000E+01 1 7.337444E+01 8.971729E+01 3.620350E-01 7.337354E+01 + 1.580002E+01 3.000000E+01 2 4.474663E+01 8.959525E+01 3.161027E-01 4.474551E+01 + 1.580002E+01 3.000000E+01 3 1.362958E+02 1.103642E+00 1.362705E+02 2.625192E+00 + 1.580002E+01 3.000000E+01 4 1.568627E+02 8.958578E+01 1.134036E+00 1.568586E+02 + 1.580002E+01 3.000000E+01 5 5.782645E+02 8.971732E+01 2.852954E+00 5.782575E+02 + 1.580002E+01 3.000000E+01 6 2.401385E+02 -2.048301E-02 2.401385E+02 -8.584853E-02 + 1.580002E+01 6.000000E+01 1 4.364219E+01 8.971836E+01 2.145253E-01 4.364167E+01 + 1.580002E+01 6.000000E+01 2 8.011423E+01 8.959460E+01 5.668424E-01 8.011222E+01 + 1.580002E+01 6.000000E+01 3 1.410566E+02 1.125105E+00 1.410294E+02 2.769721E+00 + 1.580002E+01 6.000000E+01 4 2.873427E+02 8.959451E+01 2.033598E+00 2.873354E+02 + 1.580002E+01 6.000000E+01 5 3.440365E+02 8.971846E+01 1.690512E+00 3.440323E+02 + 1.580002E+01 6.000000E+01 6 2.483942E+02 -2.024484E-02 2.483942E+02 -8.776741E-02 + 1.580002E+01 9.000000E+01 1 4.636241E-06 -9.004241E+01 -3.431655E-09 -4.636240E-06 + 1.580002E+01 9.000000E+01 2 9.405357E+01 8.959430E+01 6.659787E-01 9.405122E+01 + 1.580002E+01 9.000000E+01 3 1.435032E+02 1.135892E+00 1.434750E+02 2.844773E+00 + 1.580002E+01 9.000000E+01 4 3.410387E+02 8.959859E+01 2.389280E+00 3.410303E+02 + 1.580002E+01 9.000000E+01 5 1.967006E-04 -8.992011E+01 2.742790E-07 -1.967004E-04 + 1.580002E+01 9.000000E+01 6 2.167934E-05 1.799867E+02 -2.167934E-05 5.028896E-09 + 1.590002E+01 0.000000E+00 1 8.298023E+01 8.972113E+01 4.038826E-01 8.297925E+01 + 1.590002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.590002E+01 0.000000E+00 3 1.348329E+02 1.078353E+00 1.348090E+02 2.537514E+00 + 1.590002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.590002E+01 0.000000E+00 5 6.572054E+02 8.972102E+01 3.199937E+00 6.571976E+02 + 1.590002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.590002E+01 3.000000E+01 1 7.291677E+01 8.972166E+01 3.542206E-01 7.291591E+01 + 1.590002E+01 3.000000E+01 2 4.446796E+01 8.960321E+01 3.079539E-01 4.446689E+01 + 1.590002E+01 3.000000E+01 3 1.371233E+02 1.088633E+00 1.370986E+02 2.605219E+00 + 1.590002E+01 3.000000E+01 4 1.556960E+02 8.959405E+01 1.103129E+00 1.556920E+02 + 1.590002E+01 3.000000E+01 5 5.777761E+02 8.972169E+01 2.806556E+00 5.777693E+02 + 1.590002E+01 3.000000E+01 6 2.366047E+02 -1.972905E-02 2.366047E+02 -8.147172E-02 + 1.590002E+01 6.000000E+01 1 4.334882E+01 8.972267E+01 2.098231E-01 4.334831E+01 + 1.590002E+01 6.000000E+01 2 7.957107E+01 8.960260E+01 5.518972E-01 7.956915E+01 + 1.590002E+01 6.000000E+01 3 1.418307E+02 1.109341E+00 1.418042E+02 2.745907E+00 + 1.590002E+01 6.000000E+01 4 2.849661E+02 8.960250E+01 1.976981E+00 2.849593E+02 + 1.590002E+01 6.000000E+01 5 3.435679E+02 8.972276E+01 1.662444E+00 3.435639E+02 + 1.590002E+01 6.000000E+01 6 2.446023E+02 -1.950350E-02 2.446022E+02 -8.326268E-02 + 1.590002E+01 9.000000E+01 1 4.602926E-06 -9.004504E+01 -3.618515E-09 -4.602924E-06 + 1.590002E+01 9.000000E+01 2 9.338999E+01 8.960230E+01 6.482276E-01 9.338774E+01 + 1.590002E+01 9.000000E+01 3 1.442480E+02 1.119761E+00 1.442204E+02 2.818933E+00 + 1.590002E+01 9.000000E+01 4 3.380776E+02 8.960646E+01 2.322075E+00 3.380696E+02 + 1.590002E+01 9.000000E+01 5 1.955658E-04 -8.992209E+01 2.659353E-07 -1.955656E-04 + 1.590002E+01 9.000000E+01 6 2.134156E-05 1.799872E+02 -2.134156E-05 4.771601E-09 + 1.600002E+01 0.000000E+00 1 8.248469E+01 8.972543E+01 3.952885E-01 8.248374E+01 + 1.600002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.600002E+01 0.000000E+00 3 1.356718E+02 1.063973E+00 1.356484E+02 2.519257E+00 + 1.600002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.600002E+01 0.000000E+00 5 6.567580E+02 8.972533E+01 3.148412E+00 6.567504E+02 + 1.600002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.600002E+01 3.000000E+01 1 7.246449E+01 8.972593E+01 3.466277E-01 7.246365E+01 + 1.600002E+01 3.000000E+01 2 4.419244E+01 8.961094E+01 3.000866E-01 4.419143E+01 + 1.600002E+01 3.000000E+01 3 1.379379E+02 1.073897E+00 1.379137E+02 2.585224E+00 + 1.600002E+01 3.000000E+01 4 1.545462E+02 8.960207E+01 1.073349E+00 1.545425E+02 + 1.600002E+01 3.000000E+01 5 5.772315E+02 8.972595E+01 2.760939E+00 5.772249E+02 + 1.600002E+01 3.000000E+01 6 2.331511E+02 -1.901023E-02 2.331510E+02 -7.735745E-02 + 1.600002E+01 6.000000E+01 1 4.305938E+01 8.972688E+01 2.052545E-01 4.305889E+01 + 1.600002E+01 6.000000E+01 2 7.903542E+01 8.961035E+01 5.374856E-01 7.903358E+01 + 1.600002E+01 6.000000E+01 3 1.425912E+02 1.093902E+00 1.425652E+02 2.722215E+00 + 1.600002E+01 6.000000E+01 4 2.826280E+02 8.961026E+01 1.922494E+00 2.826215E+02 + 1.600002E+01 6.000000E+01 5 3.430718E+02 8.972696E+01 1.634872E+00 3.430679E+02 + 1.600002E+01 6.000000E+01 6 2.409003E+02 -1.879655E-02 2.409003E+02 -7.903018E-02 + 1.600002E+01 9.000000E+01 1 4.570110E-06 -9.004751E+01 -3.789268E-09 -4.570109E-06 + 1.600002E+01 9.000000E+01 2 9.273631E+01 8.961008E+01 6.311160E-01 9.273416E+01 + 1.600002E+01 9.000000E+01 3 1.449802E+02 1.103963E+00 1.449532E+02 2.793275E+00 + 1.600002E+01 9.000000E+01 4 3.351709E+02 8.961411E+01 2.257408E+00 3.351633E+02 + 1.600002E+01 9.000000E+01 5 1.944421E-04 -8.992400E+01 2.579107E-07 -1.944419E-04 + 1.600002E+01 9.000000E+01 6 2.101203E-05 1.799876E+02 -2.101203E-05 4.529813E-09 + 1.610003E+01 0.000000E+00 1 8.199458E+01 8.972961E+01 3.869341E-01 8.199367E+01 + 1.610003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.610003E+01 0.000000E+00 3 1.364973E+02 1.049858E+00 1.364744E+02 2.500965E+00 + 1.610003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.610003E+01 0.000000E+00 5 6.562446E+02 8.972954E+01 3.097819E+00 6.562373E+02 + 1.610003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.610003E+01 3.000000E+01 1 7.201734E+01 8.973010E+01 3.392474E-01 7.201654E+01 + 1.610003E+01 3.000000E+01 2 4.392006E+01 8.961843E+01 2.924908E-01 4.391909E+01 + 1.610003E+01 3.000000E+01 3 1.387381E+02 1.059451E+00 1.387144E+02 2.565246E+00 + 1.610003E+01 3.000000E+01 4 1.534126E+02 8.960985E+01 1.044645E+00 1.534091E+02 + 1.610003E+01 3.000000E+01 5 5.766322E+02 8.973013E+01 2.716109E+00 5.766258E+02 + 1.610003E+01 3.000000E+01 6 2.297751E+02 -1.832469E-02 2.297751E+02 -7.348808E-02 + 1.610003E+01 6.000000E+01 1 4.277364E+01 8.973100E+01 2.008175E-01 4.277316E+01 + 1.610003E+01 6.000000E+01 2 7.850677E+01 8.961787E+01 5.235832E-01 7.850502E+01 + 1.610003E+01 6.000000E+01 3 1.433391E+02 1.078775E+00 1.433137E+02 2.698655E+00 + 1.610003E+01 6.000000E+01 4 2.803295E+02 8.961778E+01 1.870026E+00 2.803232E+02 + 1.610003E+01 6.000000E+01 5 3.425508E+02 8.973108E+01 1.607805E+00 3.425470E+02 + 1.610003E+01 6.000000E+01 6 2.372856E+02 -1.812215E-02 2.372856E+02 -7.505134E-02 + 1.610003E+01 9.000000E+01 1 4.537772E-06 -9.004981E+01 -3.945039E-09 -4.537770E-06 + 1.610003E+01 9.000000E+01 2 9.209183E+01 8.961761E+01 6.146173E-01 9.208978E+01 + 1.610003E+01 9.000000E+01 3 1.457000E+02 1.088498E+00 1.456738E+02 2.767825E+00 + 1.610003E+01 9.000000E+01 4 3.323153E+02 8.962151E+01 2.195188E+00 3.323080E+02 + 1.610003E+01 9.000000E+01 5 1.933317E-04 -8.992586E+01 2.501906E-07 -1.933316E-04 + 1.610003E+01 9.000000E+01 6 2.069044E-05 1.799881E+02 -2.069044E-05 4.302473E-09 + 1.620003E+01 0.000000E+00 1 8.150962E+01 8.973372E+01 3.788093E-01 8.150874E+01 + 1.620003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.620003E+01 0.000000E+00 3 1.373093E+02 1.036007E+00 1.372869E+02 2.482654E+00 + 1.620003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.620003E+01 0.000000E+00 5 6.556716E+02 8.973365E+01 3.048084E+00 6.556645E+02 + 1.620003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.620003E+01 3.000000E+01 1 7.157527E+01 8.973418E+01 3.320727E-01 7.157450E+01 + 1.620003E+01 3.000000E+01 2 4.365086E+01 8.962571E+01 2.851542E-01 4.364993E+01 + 1.620003E+01 3.000000E+01 3 1.395263E+02 1.045278E+00 1.395030E+02 2.545311E+00 + 1.620003E+01 3.000000E+01 4 1.522952E+02 8.961739E+01 1.016979E+00 1.522918E+02 + 1.620003E+01 3.000000E+01 5 5.759805E+02 8.973420E+01 2.672055E+00 5.759743E+02 + 1.620003E+01 3.000000E+01 6 2.264742E+02 -1.767052E-02 2.264742E+02 -6.984662E-02 + 1.620003E+01 6.000000E+01 1 4.249178E+01 8.973503E+01 1.965063E-01 4.249132E+01 + 1.620003E+01 6.000000E+01 2 7.798560E+01 8.962518E+01 5.101681E-01 7.798392E+01 + 1.620003E+01 6.000000E+01 3 1.440754E+02 1.063956E+00 1.440506E+02 2.675261E+00 + 1.620003E+01 6.000000E+01 4 2.780690E+02 8.962509E+01 1.819491E+00 2.780630E+02 + 1.620003E+01 6.000000E+01 5 3.420031E+02 8.973509E+01 1.581232E+00 3.419995E+02 + 1.620003E+01 6.000000E+01 6 2.337555E+02 -1.747839E-02 2.337555E+02 -7.130837E-02 + 1.620003E+01 9.000000E+01 1 4.505927E-06 -9.005197E+01 -4.086868E-09 -4.505926E-06 + 1.620003E+01 9.000000E+01 2 9.145695E+01 8.962492E+01 5.987044E-01 9.145499E+01 + 1.620003E+01 9.000000E+01 3 1.464088E+02 1.073344E+00 1.463831E+02 2.742572E+00 + 1.620003E+01 9.000000E+01 4 3.295114E+02 8.962872E+01 2.135277E+00 3.295044E+02 + 1.620003E+01 9.000000E+01 5 1.922324E-04 -8.992764E+01 2.427637E-07 -1.922322E-04 + 1.620003E+01 9.000000E+01 6 2.037656E-05 1.799885E+02 -2.037656E-05 4.088583E-09 + 1.630003E+01 0.000000E+00 1 8.102962E+01 8.973773E+01 3.709082E-01 8.102878E+01 + 1.630003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.630003E+01 0.000000E+00 3 1.381084E+02 1.022408E+00 1.380864E+02 2.464328E+00 + 1.630003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.630003E+01 0.000000E+00 5 6.550367E+02 8.973766E+01 2.999223E+00 6.550299E+02 + 1.630003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.630003E+01 3.000000E+01 1 7.113800E+01 8.973816E+01 3.250960E-01 7.113726E+01 + 1.630003E+01 3.000000E+01 2 4.338460E+01 8.963277E+01 2.780656E-01 4.338371E+01 + 1.630003E+01 3.000000E+01 3 1.403013E+02 1.031371E+00 1.402785E+02 2.525403E+00 + 1.630003E+01 3.000000E+01 4 1.511939E+02 8.962472E+01 9.902994E-01 1.511906E+02 + 1.630003E+01 3.000000E+01 5 5.752880E+02 8.973818E+01 2.628852E+00 5.752820E+02 + 1.630003E+01 3.000000E+01 6 2.232461E+02 -1.704601E-02 2.232461E+02 -6.641772E-02 + 1.630003E+01 6.000000E+01 1 4.221375E+01 8.973898E+01 1.923163E-01 4.221331E+01 + 1.630003E+01 6.000000E+01 2 7.747129E+01 8.963226E+01 4.972187E-01 7.746970E+01 + 1.630003E+01 6.000000E+01 3 1.448003E+02 1.049418E+00 1.447760E+02 2.651986E+00 + 1.630003E+01 6.000000E+01 4 2.758463E+02 8.963219E+01 1.770804E+00 2.758407E+02 + 1.630003E+01 6.000000E+01 5 3.414315E+02 8.973903E+01 1.555139E+00 3.414279E+02 + 1.630003E+01 6.000000E+01 6 2.303071E+02 -1.686371E-02 2.303071E+02 -6.778567E-02 + 1.630003E+01 9.000000E+01 1 4.474533E-06 -9.005399E+01 -4.215642E-09 -4.474531E-06 + 1.630003E+01 9.000000E+01 2 9.083119E+01 8.963202E+01 5.833520E-01 9.082932E+01 + 1.630003E+01 9.000000E+01 3 1.471063E+02 1.058501E+00 1.470812E+02 2.717536E+00 + 1.630003E+01 9.000000E+01 4 3.267547E+02 8.963570E+01 2.077567E+00 3.267481E+02 + 1.630003E+01 9.000000E+01 5 1.911456E-04 -8.992938E+01 2.356130E-07 -1.911455E-04 + 1.630003E+01 9.000000E+01 6 2.007018E-05 1.799889E+02 -2.007018E-05 3.887227E-09 + 1.640003E+01 0.000000E+00 1 8.055461E+01 8.974165E+01 3.632233E-01 8.055379E+01 + 1.640003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.640003E+01 0.000000E+00 3 1.388940E+02 1.009062E+00 1.388724E+02 2.445999E+00 + 1.640003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.640003E+01 0.000000E+00 5 6.543459E+02 8.974158E+01 2.951299E+00 6.543393E+02 + 1.640003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.640003E+01 3.000000E+01 1 7.070606E+01 8.974206E+01 3.183130E-01 7.070535E+01 + 1.640003E+01 3.000000E+01 2 4.312134E+01 8.963963E+01 2.712153E-01 4.312048E+01 + 1.640003E+01 3.000000E+01 3 1.410633E+02 1.017727E+00 1.410411E+02 2.505533E+00 + 1.640003E+01 3.000000E+01 4 1.501079E+02 8.963183E+01 9.645554E-01 1.501048E+02 + 1.640003E+01 3.000000E+01 5 5.745479E+02 8.974207E+01 2.586395E+00 5.745421E+02 + 1.640003E+01 3.000000E+01 6 2.200888E+02 -1.644952E-02 2.200888E+02 -6.318712E-02 + 1.640003E+01 6.000000E+01 1 4.193920E+01 8.974283E+01 1.882436E-01 4.193877E+01 + 1.640003E+01 6.000000E+01 2 7.696369E+01 8.963915E+01 4.847154E-01 7.696217E+01 + 1.640003E+01 6.000000E+01 3 1.455114E+02 1.035188E+00 1.454877E+02 2.628876E+00 + 1.640003E+01 6.000000E+01 4 2.736604E+02 8.963908E+01 1.723872E+00 2.736549E+02 + 1.640003E+01 6.000000E+01 5 3.408386E+02 8.974288E+01 1.529532E+00 3.408352E+02 + 1.640003E+01 6.000000E+01 6 2.269384E+02 -1.627640E-02 2.269384E+02 -6.446794E-02 + 1.640003E+01 9.000000E+01 1 4.443601E-06 -9.005586E+01 -4.332325E-09 -4.443599E-06 + 1.640003E+01 9.000000E+01 2 9.021398E+01 8.963892E+01 5.685329E-01 9.021219E+01 + 1.640003E+01 9.000000E+01 3 1.477919E+02 1.043959E+00 1.477673E+02 2.692695E+00 + 1.640003E+01 9.000000E+01 4 3.240478E+02 8.964249E+01 2.021979E+00 3.240415E+02 + 1.640003E+01 9.000000E+01 5 1.900700E-04 -8.993105E+01 2.287292E-07 -1.900699E-04 + 1.640003E+01 9.000000E+01 6 1.977098E-05 1.799893E+02 -1.977098E-05 3.697572E-09 + 1.650003E+01 0.000000E+00 1 8.008446E+01 8.974548E+01 3.557478E-01 8.008366E+01 + 1.650003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.650003E+01 0.000000E+00 3 1.396676E+02 9.959418E-01 1.396465E+02 2.427645E+00 + 1.650003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.650003E+01 0.000000E+00 5 6.536002E+02 8.974541E+01 2.904176E+00 6.535938E+02 + 1.650003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.650003E+01 3.000000E+01 1 7.027889E+01 8.974587E+01 3.117142E-01 7.027820E+01 + 1.650003E+01 3.000000E+01 2 4.286112E+01 8.964629E+01 2.645930E-01 4.286031E+01 + 1.650003E+01 3.000000E+01 3 1.418136E+02 1.004334E+00 1.417918E+02 2.485714E+00 + 1.650003E+01 3.000000E+01 4 1.490375E+02 8.963873E+01 9.397214E-01 1.490346E+02 + 1.650003E+01 3.000000E+01 5 5.737659E+02 8.974589E+01 2.544692E+00 5.737603E+02 + 1.650003E+01 3.000000E+01 6 2.170004E+02 -1.587954E-02 2.170004E+02 -6.014171E-02 + 1.650003E+01 6.000000E+01 1 4.166819E+01 8.974660E+01 1.842842E-01 4.166778E+01 + 1.650003E+01 6.000000E+01 2 7.646296E+01 8.964584E+01 4.726377E-01 7.646150E+01 + 1.650003E+01 6.000000E+01 3 1.462129E+02 1.021221E+00 1.461897E+02 2.605911E+00 + 1.650003E+01 6.000000E+01 4 2.715097E+02 8.964576E+01 1.678620E+00 2.715045E+02 + 1.650003E+01 6.000000E+01 5 3.402256E+02 8.974664E+01 1.504421E+00 3.402223E+02 + 1.650003E+01 6.000000E+01 6 2.236460E+02 -1.571510E-02 2.236460E+02 -6.134169E-02 + 1.650003E+01 9.000000E+01 1 4.413116E-06 -9.005762E+01 -4.437728E-09 -4.413114E-06 + 1.650003E+01 9.000000E+01 2 8.960568E+01 8.964561E+01 5.542263E-01 8.960397E+01 + 1.650003E+01 9.000000E+01 3 1.484664E+02 1.029708E+00 1.484424E+02 2.668064E+00 + 1.650003E+01 9.000000E+01 4 3.213871E+02 8.964908E+01 1.968395E+00 3.213810E+02 + 1.650003E+01 9.000000E+01 5 1.890061E-04 -8.993267E+01 2.220995E-07 -1.890059E-04 + 1.650003E+01 9.000000E+01 6 1.947877E-05 1.799897E+02 -1.947877E-05 3.518819E-09 + 1.660003E+01 0.000000E+00 1 7.961937E+01 8.974923E+01 3.484754E-01 7.961861E+01 + 1.660003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.660003E+01 0.000000E+00 3 1.404284E+02 9.830716E-01 1.404077E+02 2.409329E+00 + 1.660003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.660003E+01 0.000000E+00 5 6.528055E+02 8.974917E+01 2.857936E+00 6.527993E+02 + 1.660003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.660003E+01 3.000000E+01 1 6.985648E+01 8.974960E+01 3.052970E-01 6.985582E+01 + 1.660003E+01 3.000000E+01 2 4.260384E+01 8.965277E+01 2.581891E-01 4.260305E+01 + 1.660003E+01 3.000000E+01 3 1.425518E+02 9.911868E-01 1.425305E+02 2.465948E+00 + 1.660003E+01 3.000000E+01 4 1.479819E+02 8.964544E+01 9.157410E-01 1.479791E+02 + 1.660003E+01 3.000000E+01 5 5.729396E+02 8.974961E+01 2.503804E+00 5.729341E+02 + 1.660003E+01 3.000000E+01 6 2.139779E+02 -1.533474E-02 2.139779E+02 -5.726939E-02 + 1.660003E+01 6.000000E+01 1 4.140081E+01 8.975029E+01 1.804350E-01 4.140041E+01 + 1.660003E+01 6.000000E+01 2 7.596867E+01 8.965234E+01 4.609694E-01 7.596728E+01 + 1.660003E+01 6.000000E+01 3 1.469029E+02 1.007521E+00 1.468802E+02 2.583089E+00 + 1.660003E+01 6.000000E+01 4 2.693941E+02 8.965227E+01 1.634977E+00 2.693891E+02 + 1.660003E+01 6.000000E+01 5 3.395906E+02 8.975034E+01 1.479773E+00 3.395873E+02 + 1.660003E+01 6.000000E+01 6 2.204283E+02 -1.517843E-02 2.204282E+02 -5.839444E-02 + 1.660003E+01 9.000000E+01 1 4.383061E-06 -9.005925E+01 -4.532602E-09 -4.383058E-06 + 1.660003E+01 9.000000E+01 2 8.900592E+01 8.965212E+01 5.404093E-01 8.900428E+01 + 1.660003E+01 9.000000E+01 3 1.491305E+02 1.015738E+00 1.491071E+02 2.643642E+00 + 1.660003E+01 9.000000E+01 4 3.187715E+02 8.965548E+01 1.916744E+00 3.187658E+02 + 1.660003E+01 9.000000E+01 5 1.879531E-04 -8.993424E+01 2.157135E-07 -1.879529E-04 + 1.660003E+01 9.000000E+01 6 1.919333E-05 1.799900E+02 -1.919333E-05 3.350276E-09 + 1.670003E+01 0.000000E+00 1 7.915928E+01 8.975289E+01 3.413980E-01 7.915855E+01 + 1.670003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.670003E+01 0.000000E+00 3 1.411773E+02 9.704314E-01 1.411570E+02 2.391037E+00 + 1.670003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.670003E+01 0.000000E+00 5 6.519617E+02 8.975283E+01 2.812466E+00 6.519557E+02 + 1.670003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.670003E+01 3.000000E+01 1 6.943875E+01 8.975324E+01 2.990534E-01 6.943811E+01 + 1.670003E+01 3.000000E+01 2 4.234944E+01 8.965907E+01 2.519954E-01 4.234869E+01 + 1.670003E+01 3.000000E+01 3 1.432779E+02 9.782935E-01 1.432570E+02 2.446272E+00 + 1.670003E+01 3.000000E+01 4 1.469415E+02 8.965195E+01 8.925918E-01 1.469388E+02 + 1.670003E+01 3.000000E+01 5 5.720788E+02 8.975326E+01 2.463653E+00 5.720735E+02 + 1.670003E+01 3.000000E+01 6 2.110209E+02 -1.481364E-02 2.110209E+02 -5.455877E-02 + 1.670003E+01 6.000000E+01 1 4.113696E+01 8.975391E+01 1.766920E-01 4.113658E+01 + 1.670003E+01 6.000000E+01 2 7.548108E+01 8.965865E+01 4.496918E-01 7.547974E+01 + 1.670003E+01 6.000000E+01 3 1.475816E+02 9.941030E-01 1.475593E+02 2.560466E+00 + 1.670003E+01 6.000000E+01 4 2.673114E+02 8.965858E+01 1.592865E+00 2.673066E+02 + 1.670003E+01 6.000000E+01 5 3.389381E+02 8.975394E+01 1.455589E+00 3.389350E+02 + 1.670003E+01 6.000000E+01 6 2.172823E+02 -1.466502E-02 2.172823E+02 -5.561403E-02 + 1.670003E+01 9.000000E+01 1 4.353434E-06 -9.006077E+01 -4.617680E-09 -4.353431E-06 + 1.670003E+01 9.000000E+01 2 8.841442E+01 8.965845E+01 5.270610E-01 8.841285E+01 + 1.670003E+01 9.000000E+01 3 1.497841E+02 1.002045E+00 1.497612E+02 2.619438E+00 + 1.670003E+01 9.000000E+01 4 3.162005E+02 8.966171E+01 1.866930E+00 3.161950E+02 + 1.670003E+01 9.000000E+01 5 1.869116E-04 -8.993577E+01 2.095604E-07 -1.869115E-04 + 1.670003E+01 9.000000E+01 6 1.891439E-05 1.799903E+02 -1.891439E-05 3.191249E-09 + 1.680003E+01 0.000000E+00 1 7.870379E+01 8.975648E+01 3.345112E-01 7.870308E+01 + 1.680003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.680003E+01 0.000000E+00 3 1.419147E+02 9.580268E-01 1.418949E+02 2.372806E+00 + 1.680003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.680003E+01 0.000000E+00 5 6.510717E+02 8.975642E+01 2.767807E+00 6.510659E+02 + 1.680003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.680003E+01 3.000000E+01 1 6.902589E+01 8.975681E+01 2.929785E-01 6.902527E+01 + 1.680003E+01 3.000000E+01 2 4.209784E+01 8.966518E+01 2.460019E-01 4.209712E+01 + 1.680003E+01 3.000000E+01 3 1.439933E+02 9.656351E-01 1.439729E+02 2.426679E+00 + 1.680003E+01 3.000000E+01 4 1.459150E+02 8.965829E+01 8.702304E-01 1.459124E+02 + 1.680003E+01 3.000000E+01 5 5.711770E+02 8.975683E+01 2.424177E+00 5.711719E+02 + 1.680003E+01 3.000000E+01 6 2.081268E+02 -1.431505E-02 2.081268E+02 -5.199940E-02 + 1.680003E+01 6.000000E+01 1 4.087637E+01 8.975744E+01 1.730514E-01 4.087600E+01 + 1.680003E+01 6.000000E+01 2 7.499953E+01 8.966479E+01 4.387893E-01 7.499825E+01 + 1.680003E+01 6.000000E+01 3 1.482493E+02 9.809484E-01 1.482275E+02 2.538019E+00 + 1.680003E+01 6.000000E+01 4 2.652624E+02 8.966473E+01 1.552231E+00 2.652578E+02 + 1.680003E+01 6.000000E+01 5 3.382650E+02 8.975747E+01 1.431869E+00 3.382619E+02 + 1.680003E+01 6.000000E+01 6 2.142068E+02 -1.417367E-02 2.142068E+02 -5.298986E-02 + 1.680003E+01 9.000000E+01 1 4.324208E-06 -9.006219E+01 -4.693642E-09 -4.324205E-06 + 1.680003E+01 9.000000E+01 2 8.783129E+01 8.966460E+01 5.141620E-01 8.782979E+01 + 1.680003E+01 9.000000E+01 3 1.504268E+02 9.886392E-01 1.504044E+02 2.595487E+00 + 1.680003E+01 9.000000E+01 4 3.136725E+02 8.966776E+01 1.818861E+00 3.136672E+02 + 1.680003E+01 9.000000E+01 5 1.858807E-04 -8.993723E+01 2.036307E-07 -1.858806E-04 + 1.680003E+01 9.000000E+01 6 1.864179E-05 1.799906E+02 -1.864179E-05 3.041129E-09 + 1.690003E+01 0.000000E+00 1 7.825299E+01 8.975999E+01 3.278065E-01 7.825230E+01 + 1.690003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.690003E+01 0.000000E+00 3 1.426401E+02 9.458489E-01 1.426206E+02 2.354621E+00 + 1.690003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.690003E+01 0.000000E+00 5 6.501360E+02 8.975993E+01 2.724063E+00 6.501302E+02 + 1.690003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.690003E+01 3.000000E+01 1 6.861776E+01 8.976030E+01 2.870665E-01 6.861716E+01 + 1.690003E+01 3.000000E+01 2 4.184914E+01 8.967113E+01 2.402019E-01 4.184845E+01 + 1.690003E+01 3.000000E+01 3 1.446970E+02 9.532170E-01 1.446770E+02 2.407180E+00 + 1.690003E+01 3.000000E+01 4 1.449025E+02 8.966444E+01 8.486223E-01 1.449000E+02 + 1.690003E+01 3.000000E+01 5 5.702377E+02 8.976031E+01 2.385506E+00 5.702327E+02 + 1.690003E+01 3.000000E+01 6 2.052938E+02 -1.383781E-02 2.052938E+02 -4.958160E-02 + 1.690003E+01 6.000000E+01 1 4.061907E+01 8.976090E+01 1.695097E-01 4.061872E+01 + 1.690003E+01 6.000000E+01 2 7.452441E+01 8.967075E+01 4.282461E-01 7.452318E+01 + 1.690003E+01 6.000000E+01 3 1.489065E+02 9.680391E-01 1.488852E+02 2.515725E+00 + 1.690003E+01 6.000000E+01 4 2.632462E+02 8.967069E+01 1.512990E+00 2.632419E+02 + 1.690003E+01 6.000000E+01 5 3.375758E+02 8.976092E+01 1.408611E+00 3.375729E+02 + 1.690003E+01 6.000000E+01 6 2.111987E+02 -1.370325E-02 2.111987E+02 -5.051173E-02 + 1.690003E+01 9.000000E+01 1 4.295412E-06 -9.006351E+01 -4.761101E-09 -4.295409E-06 + 1.690003E+01 9.000000E+01 2 8.725597E+01 8.967057E+01 5.016919E-01 8.725453E+01 + 1.690003E+01 9.000000E+01 3 1.510592E+02 9.754964E-01 1.510374E+02 2.571754E+00 + 1.690003E+01 9.000000E+01 4 3.111864E+02 8.967365E+01 1.772481E+00 3.111813E+02 + 1.690003E+01 9.000000E+01 5 1.848607E-04 -8.993866E+01 1.979136E-07 -1.848606E-04 + 1.690003E+01 9.000000E+01 6 1.837537E-05 1.799910E+02 -1.837537E-05 2.899343E-09 + 1.700003E+01 0.000000E+00 1 7.780700E+01 8.976341E+01 3.212808E-01 7.780634E+01 + 1.700003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.700003E+01 0.000000E+00 3 1.433537E+02 9.338885E-01 1.433346E+02 2.336479E+00 + 1.700003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.700003E+01 0.000000E+00 5 6.491511E+02 8.976337E+01 2.681012E+00 6.491456E+02 + 1.700003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.700003E+01 3.000000E+01 1 6.821416E+01 8.976371E+01 2.813120E-01 6.821358E+01 + 1.700003E+01 3.000000E+01 2 4.160308E+01 8.967693E+01 2.345867E-01 4.160242E+01 + 1.700003E+01 3.000000E+01 3 1.453886E+02 9.410301E-01 1.453690E+02 2.387765E+00 + 1.700003E+01 3.000000E+01 4 1.439045E+02 8.967043E+01 8.277432E-01 1.439021E+02 + 1.700003E+01 3.000000E+01 5 5.692606E+02 8.976373E+01 2.347507E+00 5.692558E+02 + 1.700003E+01 3.000000E+01 6 2.025197E+02 -1.338084E-02 2.025197E+02 -4.729638E-02 + 1.700003E+01 6.000000E+01 1 4.036497E+01 8.976428E+01 1.660650E-01 4.036462E+01 + 1.700003E+01 6.000000E+01 2 7.405534E+01 8.967656E+01 4.180475E-01 7.405415E+01 + 1.700003E+01 6.000000E+01 3 1.495526E+02 9.553865E-01 1.495318E+02 2.493621E+00 + 1.700003E+01 6.000000E+01 4 2.612618E+02 8.967651E+01 1.475102E+00 2.612577E+02 + 1.700003E+01 6.000000E+01 5 3.368707E+02 8.976430E+01 1.385798E+00 3.368678E+02 + 1.700003E+01 6.000000E+01 6 2.082564E+02 -1.325271E-02 2.082564E+02 -4.817042E-02 + 1.700003E+01 9.000000E+01 1 4.267002E-06 -9.006474E+01 -4.820654E-09 -4.266999E-06 + 1.700003E+01 9.000000E+01 2 8.668875E+01 8.967638E+01 4.896342E-01 8.668737E+01 + 1.700003E+01 9.000000E+01 3 1.516819E+02 9.626111E-01 1.516604E+02 2.548246E+00 + 1.700003E+01 9.000000E+01 4 3.087421E+02 8.967937E+01 1.727703E+00 3.087373E+02 + 1.700003E+01 9.000000E+01 5 1.838514E-04 -8.994004E+01 1.924002E-07 -1.838513E-04 + 1.700003E+01 9.000000E+01 6 1.811487E-05 1.799913E+02 -1.811487E-05 2.765362E-09 + 1.710003E+01 0.000000E+00 1 7.736562E+01 8.976677E+01 3.149246E-01 7.736497E+01 + 1.710003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.710003E+01 0.000000E+00 3 1.440564E+02 9.221410E-01 1.440378E+02 2.318401E+00 + 1.710003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.710003E+01 0.000000E+00 5 6.481404E+02 8.976672E+01 2.638818E+00 6.481351E+02 + 1.710003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.710003E+01 3.000000E+01 1 6.781467E+01 8.976705E+01 2.757103E-01 6.781411E+01 + 1.710003E+01 3.000000E+01 2 4.135986E+01 8.968256E+01 2.291498E-01 4.135922E+01 + 1.710003E+01 3.000000E+01 3 1.460704E+02 9.290562E-01 1.460512E+02 2.368441E+00 + 1.710003E+01 3.000000E+01 4 1.429198E+02 8.967625E+01 8.075590E-01 1.429175E+02 + 1.710003E+01 3.000000E+01 5 5.682650E+02 8.976707E+01 2.310235E+00 5.682603E+02 + 1.710003E+01 3.000000E+01 6 1.998033E+02 -1.294307E-02 1.998033E+02 -4.513539E-02 + 1.710003E+01 6.000000E+01 1 4.011433E+01 8.976760E+01 1.627119E-01 4.011400E+01 + 1.710003E+01 6.000000E+01 2 7.359230E+01 8.968221E+01 4.081792E-01 7.359117E+01 + 1.710003E+01 6.000000E+01 3 1.501896E+02 9.429771E-01 1.501692E+02 2.471717E+00 + 1.710003E+01 6.000000E+01 4 2.593072E+02 8.968215E+01 1.438494E+00 2.593032E+02 + 1.710003E+01 6.000000E+01 5 3.361512E+02 8.976762E+01 1.363393E+00 3.361484E+02 + 1.710003E+01 6.000000E+01 6 2.053779E+02 -1.282100E-02 2.053779E+02 -4.595713E-02 + 1.710003E+01 9.000000E+01 1 4.238977E-06 -9.006586E+01 -4.872835E-09 -4.238974E-06 + 1.710003E+01 9.000000E+01 2 8.612893E+01 8.968204E+01 4.779708E-01 8.612760E+01 + 1.710003E+01 9.000000E+01 3 1.522950E+02 9.499663E-01 1.522740E+02 2.524941E+00 + 1.710003E+01 9.000000E+01 4 3.063377E+02 8.968494E+01 1.684460E+00 3.063331E+02 + 1.710003E+01 9.000000E+01 5 1.828522E-04 -8.994138E+01 1.870827E-07 -1.828521E-04 + 1.710003E+01 9.000000E+01 6 1.786016E-05 1.799915E+02 -1.786016E-05 2.638687E-09 + 1.720003E+01 0.000000E+00 1 7.692882E+01 8.977006E+01 3.087362E-01 7.692820E+01 + 1.720003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.720003E+01 0.000000E+00 3 1.447481E+02 9.106072E-01 1.447298E+02 2.300398E+00 + 1.720003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.720003E+01 0.000000E+00 5 6.470827E+02 8.977002E+01 2.597396E+00 6.470775E+02 + 1.720003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.720003E+01 3.000000E+01 1 6.742007E+01 8.977033E+01 2.702556E-01 6.741953E+01 + 1.720003E+01 3.000000E+01 2 4.111934E+01 8.968804E+01 2.238836E-01 4.111873E+01 + 1.720003E+01 3.000000E+01 3 1.467415E+02 9.173130E-01 1.467227E+02 2.349250E+00 + 1.720003E+01 3.000000E+01 4 1.419483E+02 8.968192E+01 7.880372E-01 1.419461E+02 + 1.720003E+01 3.000000E+01 5 5.672308E+02 8.977034E+01 2.273669E+00 5.672262E+02 + 1.720003E+01 3.000000E+01 6 1.971432E+02 -1.252353E-02 1.971432E+02 -4.309093E-02 + 1.720003E+01 6.000000E+01 1 3.986652E+01 8.977084E+01 1.594489E-01 3.986620E+01 + 1.720003E+01 6.000000E+01 2 7.313503E+01 8.968771E+01 3.986283E-01 7.313394E+01 + 1.720003E+01 6.000000E+01 3 1.508159E+02 9.308029E-01 1.507961E+02 2.449984E+00 + 1.720003E+01 6.000000E+01 4 2.573831E+02 8.968765E+01 1.403127E+00 2.573793E+02 + 1.720003E+01 6.000000E+01 5 3.354142E+02 8.977086E+01 1.341441E+00 3.354116E+02 + 1.720003E+01 6.000000E+01 6 2.025613E+02 -1.240717E-02 2.025613E+02 -4.386384E-02 + 1.720003E+01 9.000000E+01 1 4.211352E-06 -9.006691E+01 -4.918130E-09 -4.211350E-06 + 1.720003E+01 9.000000E+01 2 8.557645E+01 8.968754E+01 4.666883E-01 8.557518E+01 + 1.720003E+01 9.000000E+01 3 1.528981E+02 9.375727E-01 1.528776E+02 2.501872E+00 + 1.720003E+01 9.000000E+01 4 3.039721E+02 8.969037E+01 1.642692E+00 3.039677E+02 + 1.720003E+01 9.000000E+01 5 1.818636E-04 -8.994268E+01 1.819528E-07 -1.818635E-04 + 1.720003E+01 9.000000E+01 6 1.761103E-05 1.799918E+02 -1.761103E-05 2.518862E-09 + 1.730003E+01 0.000000E+00 1 7.649648E+01 8.977328E+01 3.027084E-01 7.649587E+01 + 1.730003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.730003E+01 0.000000E+00 3 1.454297E+02 8.992753E-01 1.454118E+02 2.282471E+00 + 1.730003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.730003E+01 0.000000E+00 5 6.459941E+02 8.977323E+01 2.556705E+00 6.459890E+02 + 1.730003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.730003E+01 3.000000E+01 1 6.702960E+01 8.977353E+01 2.649444E-01 6.702908E+01 + 1.730003E+01 3.000000E+01 2 4.088143E+01 8.969337E+01 2.187814E-01 4.088085E+01 + 1.730003E+01 3.000000E+01 3 1.474021E+02 9.057806E-01 1.473837E+02 2.330162E+00 + 1.730003E+01 3.000000E+01 4 1.409897E+02 8.968742E+01 7.691571E-01 1.409876E+02 + 1.730003E+01 3.000000E+01 5 5.661701E+02 8.977354E+01 2.237766E+00 5.661657E+02 + 1.730003E+01 3.000000E+01 6 1.945372E+02 -1.212130E-02 1.945372E+02 -4.115565E-02 + 1.730003E+01 6.000000E+01 1 3.962185E+01 8.977402E+01 1.562728E-01 3.962154E+01 + 1.730003E+01 6.000000E+01 2 7.268350E+01 8.969305E+01 3.893808E-01 7.268246E+01 + 1.730003E+01 6.000000E+01 3 1.514333E+02 9.188576E-01 1.514138E+02 2.428445E+00 + 1.730003E+01 6.000000E+01 4 2.554887E+02 8.969300E+01 1.368935E+00 2.554850E+02 + 1.730003E+01 6.000000E+01 5 3.346673E+02 8.977402E+01 1.319904E+00 3.346647E+02 + 1.730003E+01 6.000000E+01 6 1.998048E+02 -1.201034E-02 1.998048E+02 -4.188307E-02 + 1.730003E+01 9.000000E+01 1 4.184083E-06 -9.006788E+01 -4.957047E-09 -4.184080E-06 + 1.730003E+01 9.000000E+01 2 8.503168E+01 8.969289E+01 4.557677E-01 8.503046E+01 + 1.730003E+01 9.000000E+01 3 1.534927E+02 9.254283E-01 1.534726E+02 2.479070E+00 + 1.730003E+01 9.000000E+01 4 3.016447E+02 8.969564E+01 1.602325E+00 3.016405E+02 + 1.730003E+01 9.000000E+01 5 1.808851E-04 -8.994393E+01 1.770024E-07 -1.808850E-04 + 1.730003E+01 9.000000E+01 6 1.736735E-05 1.799921E+02 -1.736735E-05 2.405464E-09 + 1.740003E+01 0.000000E+00 1 7.606857E+01 8.977642E+01 2.968370E-01 7.606799E+01 + 1.740003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.740003E+01 0.000000E+00 3 1.461000E+02 8.881522E-01 1.460824E+02 2.264631E+00 + 1.740003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.740003E+01 0.000000E+00 5 6.448622E+02 8.977638E+01 2.516809E+00 6.448573E+02 + 1.740003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.740003E+01 3.000000E+01 1 6.664342E+01 8.977666E+01 2.597717E-01 6.664291E+01 + 1.740003E+01 3.000000E+01 2 4.064622E+01 8.969857E+01 2.138377E-01 4.064566E+01 + 1.740003E+01 3.000000E+01 3 1.480520E+02 8.944587E-01 1.480340E+02 2.311183E+00 + 1.740003E+01 3.000000E+01 4 1.400447E+02 8.969279E+01 7.508884E-01 1.400427E+02 + 1.740003E+01 3.000000E+01 5 5.650781E+02 8.977668E+01 2.202544E+00 5.650739E+02 + 1.740003E+01 3.000000E+01 6 1.919844E+02 -1.173553E-02 1.919844E+02 -3.932295E-02 + 1.740003E+01 6.000000E+01 1 3.938031E+01 8.977714E+01 1.531806E-01 3.938001E+01 + 1.740003E+01 6.000000E+01 2 7.223764E+01 8.969826E+01 3.804266E-01 7.223664E+01 + 1.740003E+01 6.000000E+01 3 1.520408E+02 9.071378E-01 1.520217E+02 2.407091E+00 + 1.740003E+01 6.000000E+01 4 2.536234E+02 8.969821E+01 1.335878E+00 2.536199E+02 + 1.740003E+01 6.000000E+01 5 3.339070E+02 8.977714E+01 1.298781E+00 3.339045E+02 + 1.740003E+01 6.000000E+01 6 1.971064E+02 -1.162970E-02 1.971064E+02 -4.000797E-02 + 1.740003E+01 9.000000E+01 1 4.157188E-06 -9.006878E+01 -4.990004E-09 -4.157185E-06 + 1.740003E+01 9.000000E+01 2 8.449390E+01 8.969811E+01 4.451937E-01 8.449272E+01 + 1.740003E+01 9.000000E+01 3 1.540770E+02 9.135116E-01 1.540574E+02 2.456466E+00 + 1.740003E+01 9.000000E+01 4 2.993548E+02 8.970079E+01 1.563310E+00 2.993507E+02 + 1.740003E+01 9.000000E+01 5 1.799171E-04 -8.994516E+01 1.722229E-07 -1.799170E-04 + 1.740003E+01 9.000000E+01 6 1.712890E-05 1.799923E+02 -1.712890E-05 2.298087E-09 + 1.750003E+01 0.000000E+00 1 7.564523E+01 8.977950E+01 2.911168E-01 7.564468E+01 + 1.750003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.750003E+01 0.000000E+00 3 1.467605E+02 8.772206E-01 1.467433E+02 2.246873E+00 + 1.750003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.750003E+01 0.000000E+00 5 6.437031E+02 8.977946E+01 2.477639E+00 6.436983E+02 + 1.750003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.750003E+01 3.000000E+01 1 6.626160E+01 8.977974E+01 2.547330E-01 6.626112E+01 + 1.750003E+01 3.000000E+01 2 4.041354E+01 8.970363E+01 2.090445E-01 4.041300E+01 + 1.750003E+01 3.000000E+01 3 1.486924E+02 8.833405E-01 1.486747E+02 2.292330E+00 + 1.750003E+01 3.000000E+01 4 1.391121E+02 8.969801E+01 7.332051E-01 1.391102E+02 + 1.750003E+01 3.000000E+01 5 5.639617E+02 8.977975E+01 2.167981E+00 5.639575E+02 + 1.750003E+01 3.000000E+01 6 1.894836E+02 -1.136537E-02 1.894836E+02 -3.758655E-02 + 1.750003E+01 6.000000E+01 1 3.914173E+01 8.978018E+01 1.501700E-01 3.914144E+01 + 1.750003E+01 6.000000E+01 2 7.179738E+01 8.970333E+01 3.717521E-01 7.179642E+01 + 1.750003E+01 6.000000E+01 3 1.526384E+02 8.956429E-01 1.526198E+02 2.385934E+00 + 1.750003E+01 6.000000E+01 4 2.517860E+02 8.970329E+01 1.303899E+00 2.517826E+02 + 1.750003E+01 6.000000E+01 5 3.331340E+02 8.978019E+01 1.278064E+00 3.331315E+02 + 1.750003E+01 6.000000E+01 6 1.944650E+02 -1.126439E-02 1.944650E+02 -3.823193E-02 + 1.750003E+01 9.000000E+01 1 4.130654E-06 -9.006960E+01 -5.017452E-09 -4.130651E-06 + 1.750003E+01 9.000000E+01 2 8.396326E+01 8.970319E+01 4.349561E-01 8.396214E+01 + 1.750003E+01 9.000000E+01 3 1.546528E+02 9.018231E-01 1.546337E+02 2.434101E+00 + 1.750003E+01 9.000000E+01 4 2.971018E+02 8.970580E+01 1.525586E+00 2.970979E+02 + 1.750003E+01 9.000000E+01 5 1.789581E-04 -8.994634E+01 1.676095E-07 -1.789580E-04 + 1.750003E+01 9.000000E+01 6 1.689559E-05 1.799926E+02 -1.689559E-05 2.196375E-09 + 1.760003E+01 0.000000E+00 1 7.522603E+01 8.978252E+01 2.855424E-01 7.522549E+01 + 1.760003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.760003E+01 0.000000E+00 3 1.474105E+02 8.664895E-01 1.473936E+02 2.229218E+00 + 1.760003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.760003E+01 0.000000E+00 5 6.425116E+02 8.978249E+01 2.439182E+00 6.425070E+02 + 1.760003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.760003E+01 3.000000E+01 1 6.588400E+01 8.978275E+01 2.498240E-01 6.588353E+01 + 1.760003E+01 3.000000E+01 2 4.018336E+01 8.970856E+01 2.043981E-01 4.018284E+01 + 1.760003E+01 3.000000E+01 3 1.493228E+02 8.724263E-01 1.493055E+02 2.273607E+00 + 1.760003E+01 3.000000E+01 4 1.381915E+02 8.970310E+01 7.160906E-01 1.381896E+02 + 1.760003E+01 3.000000E+01 5 5.628223E+02 8.978275E+01 2.134067E+00 5.628182E+02 + 1.760003E+01 3.000000E+01 6 1.870322E+02 -1.101012E-02 1.870322E+02 -3.594062E-02 + 1.760003E+01 6.000000E+01 1 3.890599E+01 8.978316E+01 1.472380E-01 3.890571E+01 + 1.760003E+01 6.000000E+01 2 7.136261E+01 8.970827E+01 3.633476E-01 7.136169E+01 + 1.760003E+01 6.000000E+01 3 1.532270E+02 8.843609E-01 1.532087E+02 2.364966E+00 + 1.760003E+01 6.000000E+01 4 2.499757E+02 8.970823E+01 1.272962E+00 2.499725E+02 + 1.760003E+01 6.000000E+01 5 3.323467E+02 8.978316E+01 1.257752E+00 3.323443E+02 + 1.760003E+01 6.000000E+01 6 1.918781E+02 -1.091368E-02 1.918781E+02 -3.654889E-02 + 1.760003E+01 9.000000E+01 1 4.104470E-06 -9.007036E+01 -5.039729E-09 -4.104467E-06 + 1.760003E+01 9.000000E+01 2 8.343951E+01 8.970814E+01 4.250399E-01 8.343843E+01 + 1.760003E+01 9.000000E+01 3 1.552197E+02 8.903571E-01 1.552009E+02 2.411964E+00 + 1.760003E+01 9.000000E+01 4 2.948824E+02 8.971067E+01 1.489102E+00 2.948787E+02 + 1.760003E+01 9.000000E+01 5 1.780100E-04 -8.994749E+01 1.631530E-07 -1.780099E-04 + 1.760003E+01 9.000000E+01 6 1.666724E-05 1.799928E+02 -1.666724E-05 2.099976E-09 + 1.770003E+01 0.000000E+00 1 7.481139E+01 8.978548E+01 2.801100E-01 7.481087E+01 + 1.770003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.770003E+01 0.000000E+00 3 1.480506E+02 8.559459E-01 1.480341E+02 2.211657E+00 + 1.770003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.770003E+01 0.000000E+00 5 6.412889E+02 8.978545E+01 2.401450E+00 6.412844E+02 + 1.770003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.770003E+01 3.000000E+01 1 6.551038E+01 8.978568E+01 2.450408E-01 6.550993E+01 + 1.770003E+01 3.000000E+01 2 3.995592E+01 8.971336E+01 1.998918E-01 3.995542E+01 + 1.770003E+01 3.000000E+01 3 1.499435E+02 8.617072E-01 1.499266E+02 2.255009E+00 + 1.770003E+01 3.000000E+01 4 1.372833E+02 8.970805E+01 6.995165E-01 1.372816E+02 + 1.770003E+01 3.000000E+01 5 5.616598E+02 8.978569E+01 2.100796E+00 5.616559E+02 + 1.770003E+01 3.000000E+01 6 1.846298E+02 -1.066901E-02 1.846298E+02 -3.437980E-02 + 1.770003E+01 6.000000E+01 1 3.867310E+01 8.978609E+01 1.443823E-01 3.867283E+01 + 1.770003E+01 6.000000E+01 2 7.093285E+01 8.971309E+01 3.552011E-01 7.093196E+01 + 1.770003E+01 6.000000E+01 3 1.538070E+02 8.732904E-01 1.537892E+02 2.344204E+00 + 1.770003E+01 6.000000E+01 4 2.481922E+02 8.971304E+01 1.243022E+00 2.481891E+02 + 1.770003E+01 6.000000E+01 5 3.315513E+02 8.978609E+01 1.237825E+00 3.315490E+02 + 1.770003E+01 6.000000E+01 6 1.893453E+02 -1.057689E-02 1.893453E+02 -3.495344E-02 + 1.770003E+01 9.000000E+01 1 4.078627E-06 -9.007104E+01 -5.057224E-09 -4.078624E-06 + 1.770003E+01 9.000000E+01 2 8.292255E+01 8.971296E+01 4.154316E-01 8.292151E+01 + 1.770003E+01 9.000000E+01 3 1.557786E+02 8.791062E-01 1.557602E+02 2.390063E+00 + 1.770003E+01 9.000000E+01 4 2.926987E+02 8.971542E+01 1.453803E+00 2.926951E+02 + 1.770003E+01 9.000000E+01 5 1.770701E-04 -8.994860E+01 1.588489E-07 -1.770701E-04 + 1.770003E+01 9.000000E+01 6 1.644369E-05 1.799930E+02 -1.644369E-05 2.008577E-09 + 1.780003E+01 0.000000E+00 1 7.440078E+01 8.978837E+01 2.748142E-01 7.440027E+01 + 1.780003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.780003E+01 0.000000E+00 3 1.486817E+02 8.455824E-01 1.486656E+02 2.194195E+00 + 1.780003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.780003E+01 0.000000E+00 5 6.400364E+02 8.978835E+01 2.364407E+00 6.400320E+02 + 1.780003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.780003E+01 3.000000E+01 1 6.514104E+01 8.978857E+01 2.403791E-01 6.514060E+01 + 1.780003E+01 3.000000E+01 2 3.973069E+01 8.971804E+01 1.955202E-01 3.973021E+01 + 1.780003E+01 3.000000E+01 3 1.505547E+02 8.511811E-01 1.505381E+02 2.236545E+00 + 1.780003E+01 3.000000E+01 4 1.363872E+02 8.971288E+01 6.834597E-01 1.363855E+02 + 1.780003E+01 3.000000E+01 5 5.604759E+02 8.978858E+01 2.068119E+00 5.604720E+02 + 1.780003E+01 3.000000E+01 6 1.822750E+02 -1.034134E-02 1.822750E+02 -3.289888E-02 + 1.780003E+01 6.000000E+01 1 3.844302E+01 8.978896E+01 1.416005E-01 3.844276E+01 + 1.780003E+01 6.000000E+01 2 7.050869E+01 8.971778E+01 3.473049E-01 7.050784E+01 + 1.780003E+01 6.000000E+01 3 1.543772E+02 8.624300E-01 1.543597E+02 2.323635E+00 + 1.780003E+01 6.000000E+01 4 2.464359E+02 8.971774E+01 1.214041E+00 2.464330E+02 + 1.780003E+01 6.000000E+01 5 3.307463E+02 8.978896E+01 1.218282E+00 3.307440E+02 + 1.780003E+01 6.000000E+01 6 1.868641E+02 -1.025334E-02 1.868641E+02 -3.344018E-02 + 1.780003E+01 9.000000E+01 1 4.053125E-06 -9.007167E+01 -5.070256E-09 -4.053122E-06 + 1.780003E+01 9.000000E+01 2 8.241228E+01 8.971765E+01 4.061211E-01 8.241128E+01 + 1.780003E+01 9.000000E+01 3 1.563274E+02 8.680727E-01 1.563095E+02 2.368384E+00 + 1.780003E+01 9.000000E+01 4 2.905500E+02 8.972005E+01 1.419651E+00 2.905465E+02 + 1.780003E+01 9.000000E+01 5 1.761400E-04 -8.994968E+01 1.546902E-07 -1.761399E-04 + 1.780003E+01 9.000000E+01 6 1.622480E-05 1.799932E+02 -1.622480E-05 1.921874E-09 + 1.790003E+01 0.000000E+00 1 7.399467E+01 8.979121E+01 2.696534E-01 7.399419E+01 + 1.790003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.790003E+01 0.000000E+00 3 1.493023E+02 8.354082E-01 1.492865E+02 2.176844E+00 + 1.790003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.790003E+01 0.000000E+00 5 6.387642E+02 8.979118E+01 2.328068E+00 6.387599E+02 + 1.790003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.790003E+01 3.000000E+01 1 6.477534E+01 8.979140E+01 2.358356E-01 6.477492E+01 + 1.790003E+01 3.000000E+01 2 3.950798E+01 8.972260E+01 1.912789E-01 3.950752E+01 + 1.790003E+01 3.000000E+01 3 1.511558E+02 8.408459E-01 1.511395E+02 2.218212E+00 + 1.790003E+01 3.000000E+01 4 1.355029E+02 8.971758E+01 6.679081E-01 1.355012E+02 + 1.790003E+01 3.000000E+01 5 5.592638E+02 8.979140E+01 2.036119E+00 5.592601E+02 + 1.790003E+01 3.000000E+01 6 1.799663E+02 -1.002654E-02 1.799663E+02 -3.149339E-02 + 1.790003E+01 6.000000E+01 1 3.821576E+01 8.979176E+01 1.388902E-01 3.821550E+01 + 1.790003E+01 6.000000E+01 2 7.008968E+01 8.972235E+01 3.396469E-01 7.008885E+01 + 1.790003E+01 6.000000E+01 3 1.549396E+02 8.517636E-01 1.549225E+02 2.303259E+00 + 1.790003E+01 6.000000E+01 4 2.447059E+02 8.972231E+01 1.185986E+00 2.447030E+02 + 1.790003E+01 6.000000E+01 5 3.299292E+02 8.979176E+01 1.199113E+00 3.299270E+02 + 1.790003E+01 6.000000E+01 6 1.844336E+02 -9.942386E-03 1.844336E+02 -3.200428E-02 + 1.790003E+01 9.000000E+01 1 4.027956E-06 -9.007224E+01 -5.079143E-09 -4.027953E-06 + 1.790003E+01 9.000000E+01 2 8.190853E+01 8.972223E+01 3.970944E-01 8.190757E+01 + 1.790003E+01 9.000000E+01 3 1.568689E+02 8.572463E-01 1.568513E+02 2.346948E+00 + 1.790003E+01 9.000000E+01 4 2.884336E+02 8.972456E+01 1.386583E+00 2.884302E+02 + 1.790003E+01 9.000000E+01 5 1.752189E-04 -8.995073E+01 1.506712E-07 -1.752189E-04 + 1.790003E+01 9.000000E+01 6 1.601048E-05 1.799934E+02 -1.601048E-05 1.839592E-09 + 1.800003E+01 0.000000E+00 1 7.359242E+01 8.979398E+01 2.646198E-01 7.359195E+01 + 1.800003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.800003E+01 0.000000E+00 3 1.499134E+02 8.254050E-01 1.498979E+02 2.159583E+00 + 1.800003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.800003E+01 0.000000E+00 5 6.374623E+02 8.979396E+01 2.292387E+00 6.374581E+02 + 1.800003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.800003E+01 3.000000E+01 1 6.441399E+01 8.979417E+01 2.314064E-01 6.441357E+01 + 1.800003E+01 3.000000E+01 2 3.928770E+01 8.972705E+01 1.871628E-01 3.928726E+01 + 1.800003E+01 3.000000E+01 3 1.517487E+02 8.306831E-01 1.517327E+02 2.199999E+00 + 1.800003E+01 3.000000E+01 4 1.346301E+02 8.972217E+01 6.528330E-01 1.346285E+02 + 1.800003E+01 3.000000E+01 5 5.580375E+02 8.979417E+01 2.004682E+00 5.580339E+02 + 1.800003E+01 3.000000E+01 6 1.777027E+02 -9.723916E-03 1.777027E+02 -3.015869E-02 + 1.800003E+01 6.000000E+01 1 3.799120E+01 8.979452E+01 1.362488E-01 3.799096E+01 + 1.800003E+01 6.000000E+01 2 6.967571E+01 8.972681E+01 3.322195E-01 6.967492E+01 + 1.800003E+01 6.000000E+01 3 1.554927E+02 8.412932E-01 1.554759E+02 2.283069E+00 + 1.800003E+01 6.000000E+01 4 2.430007E+02 8.972678E+01 1.158802E+00 2.429979E+02 + 1.800003E+01 6.000000E+01 5 3.291052E+02 8.979451E+01 1.180315E+00 3.291031E+02 + 1.800003E+01 6.000000E+01 6 1.820520E+02 -9.643480E-03 1.820520E+02 -3.064126E-02 + 1.800003E+01 9.000000E+01 1 4.003104E-06 -9.007277E+01 -5.084192E-09 -4.003100E-06 + 1.800003E+01 9.000000E+01 2 8.141106E+01 8.972669E+01 3.883424E-01 8.141014E+01 + 1.800003E+01 9.000000E+01 3 1.574014E+02 8.466154E-01 1.573842E+02 2.325713E+00 + 1.800003E+01 9.000000E+01 4 2.863488E+02 8.972896E+01 1.354571E+00 2.863456E+02 + 1.800003E+01 9.000000E+01 5 1.743079E-04 -8.995175E+01 1.467860E-07 -1.743078E-04 + 1.800003E+01 9.000000E+01 6 1.580057E-05 1.799936E+02 -1.580057E-05 1.761472E-09 + 1.810003E+01 0.000000E+00 1 7.319434E+01 8.979670E+01 2.597115E-01 7.319389E+01 + 1.810003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.810003E+01 0.000000E+00 3 1.505152E+02 8.155890E-01 1.505000E+02 2.142469E+00 + 1.810003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.810003E+01 0.000000E+00 5 6.361327E+02 8.979668E+01 2.257386E+00 6.361287E+02 + 1.810003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.810003E+01 3.000000E+01 1 6.405619E+01 8.979688E+01 2.270879E-01 6.405579E+01 + 1.810003E+01 3.000000E+01 2 3.906975E+01 8.973138E+01 1.831671E-01 3.906932E+01 + 1.810003E+01 3.000000E+01 3 1.523327E+02 8.207114E-01 1.523171E+02 2.181957E+00 + 1.810003E+01 3.000000E+01 4 1.337683E+02 8.972664E+01 6.382182E-01 1.337668E+02 + 1.810003E+01 3.000000E+01 5 5.567880E+02 8.979689E+01 1.973825E+00 5.567845E+02 + 1.810003E+01 3.000000E+01 6 1.754824E+02 -9.432958E-03 1.754824E+02 -2.889074E-02 + 1.810003E+01 6.000000E+01 1 3.776931E+01 8.979722E+01 1.336748E-01 3.776907E+01 + 1.810003E+01 6.000000E+01 2 6.926653E+01 8.973116E+01 3.250135E-01 6.926576E+01 + 1.810003E+01 6.000000E+01 3 1.560380E+02 8.310156E-01 1.560216E+02 2.263090E+00 + 1.810003E+01 6.000000E+01 4 2.413194E+02 8.973112E+01 1.132469E+00 2.413167E+02 + 1.810003E+01 6.000000E+01 5 3.282740E+02 8.979721E+01 1.161875E+00 3.282720E+02 + 1.810003E+01 6.000000E+01 6 1.797184E+02 -9.355979E-03 1.797184E+02 -2.934668E-02 + 1.810003E+01 9.000000E+01 1 3.978574E-06 -9.007323E+01 -5.085662E-09 -3.978570E-06 + 1.810003E+01 9.000000E+01 2 8.091991E+01 8.973104E+01 3.798544E-01 8.091902E+01 + 1.810003E+01 9.000000E+01 3 1.579263E+02 8.361931E-01 1.579095E+02 2.304746E+00 + 1.810003E+01 9.000000E+01 4 2.842980E+02 8.973326E+01 1.323563E+00 2.842949E+02 + 1.810003E+01 9.000000E+01 5 1.734056E-04 -8.995274E+01 1.430287E-07 -1.734055E-04 + 1.810003E+01 9.000000E+01 6 1.559493E-05 1.799938E+02 -1.559493E-05 1.687267E-09 + 1.820003E+01 0.000000E+00 1 7.280035E+01 8.979937E+01 2.549250E-01 7.279990E+01 + 1.820003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.820003E+01 0.000000E+00 3 1.511089E+02 8.059275E-01 1.510940E+02 2.125441E+00 + 1.820003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.820003E+01 0.000000E+00 5 6.347894E+02 8.979935E+01 2.223038E+00 6.347855E+02 + 1.820003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.820003E+01 3.000000E+01 1 6.370239E+01 8.979954E+01 2.228774E-01 6.370200E+01 + 1.820003E+01 3.000000E+01 2 3.885412E+01 8.973561E+01 1.792869E-01 3.885371E+01 + 1.820003E+01 3.000000E+01 3 1.529076E+02 8.109112E-01 1.528923E+02 2.164040E+00 + 1.820003E+01 3.000000E+01 4 1.329179E+02 8.973100E+01 6.240516E-01 1.329165E+02 + 1.820003E+01 3.000000E+01 5 5.555248E+02 8.979955E+01 1.943584E+00 5.555214E+02 + 1.820003E+01 3.000000E+01 6 1.733053E+02 -9.153094E-03 1.733053E+02 -2.768579E-02 + 1.820003E+01 6.000000E+01 1 3.754996E+01 8.979986E+01 1.311652E-01 3.754973E+01 + 1.820003E+01 6.000000E+01 2 6.886234E+01 8.973540E+01 3.180218E-01 6.886160E+01 + 1.820003E+01 6.000000E+01 3 1.565751E+02 8.209197E-01 1.565590E+02 2.243292E+00 + 1.820003E+01 6.000000E+01 4 2.396626E+02 8.973536E+01 1.106960E+00 2.396601E+02 + 1.820003E+01 6.000000E+01 5 3.274324E+02 8.979985E+01 1.143814E+00 3.274304E+02 + 1.820003E+01 6.000000E+01 6 1.774308E+02 -9.079442E-03 1.774308E+02 -2.811678E-02 + 1.820003E+01 9.000000E+01 1 3.954354E-06 -9.007366E+01 -5.083816E-09 -3.954351E-06 + 1.820003E+01 9.000000E+01 2 8.043484E+01 8.973528E+01 3.716185E-01 8.043398E+01 + 1.820003E+01 9.000000E+01 3 1.584439E+02 8.259460E-01 1.584274E+02 2.283965E+00 + 1.820003E+01 9.000000E+01 4 2.822743E+02 8.973744E+01 1.293522E+00 2.822714E+02 + 1.820003E+01 9.000000E+01 5 1.725127E-04 -8.995370E+01 1.393963E-07 -1.725126E-04 + 1.820003E+01 9.000000E+01 6 1.539349E-05 1.799940E+02 -1.539349E-05 1.616758E-09 + 1.830003E+01 0.000000E+00 1 7.241020E+01 8.980198E+01 2.502557E-01 7.240977E+01 + 1.830003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.830003E+01 0.000000E+00 3 1.516930E+02 7.964388E-01 1.516783E+02 2.108537E+00 + 1.830003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.830003E+01 0.000000E+00 5 6.334097E+02 8.980196E+01 2.189332E+00 6.334059E+02 + 1.830003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.830003E+01 3.000000E+01 1 6.335241E+01 8.980215E+01 2.187716E-01 6.335203E+01 + 1.830003E+01 3.000000E+01 2 3.864079E+01 8.973975E+01 1.755189E-01 3.864039E+01 + 1.830003E+01 3.000000E+01 3 1.534740E+02 8.012852E-01 1.534589E+02 2.146273E+00 + 1.830003E+01 3.000000E+01 4 1.320782E+02 8.973524E+01 6.103086E-01 1.320768E+02 + 1.830003E+01 3.000000E+01 5 5.542449E+02 8.980215E+01 1.913880E+00 5.542416E+02 + 1.830003E+01 3.000000E+01 6 1.711694E+02 -8.883815E-03 1.711694E+02 -2.654013E-02 + 1.830003E+01 6.000000E+01 1 3.733328E+01 8.980245E+01 1.287194E-01 3.733306E+01 + 1.830003E+01 6.000000E+01 2 6.846301E+01 8.973953E+01 3.112344E-01 6.846230E+01 + 1.830003E+01 6.000000E+01 3 1.571040E+02 8.110126E-01 1.570883E+02 2.223709E+00 + 1.830003E+01 6.000000E+01 4 2.380298E+02 8.973950E+01 1.082225E+00 2.380274E+02 + 1.830003E+01 6.000000E+01 5 3.265837E+02 8.980244E+01 1.126073E+00 3.265818E+02 + 1.830003E+01 6.000000E+01 6 1.751885E+02 -8.813322E-03 1.751885E+02 -2.694776E-02 + 1.830003E+01 9.000000E+01 1 3.930443E-06 -9.007404E+01 -5.078886E-09 -3.930440E-06 + 1.830003E+01 9.000000E+01 2 7.995577E+01 8.973943E+01 3.636277E-01 7.995495E+01 + 1.830003E+01 9.000000E+01 3 1.589527E+02 8.159044E-01 1.589366E+02 2.263445E+00 + 1.830003E+01 9.000000E+01 4 2.802824E+02 8.974153E+01 1.264404E+00 2.802796E+02 + 1.830003E+01 9.000000E+01 5 1.716281E-04 -8.995464E+01 1.358817E-07 -1.716281E-04 + 1.830003E+01 9.000000E+01 6 1.519608E-05 1.799942E+02 -1.519608E-05 1.549729E-09 + 1.840003E+01 0.000000E+00 1 7.202413E+01 8.980454E+01 2.457006E-01 7.202371E+01 + 1.840003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.840003E+01 0.000000E+00 3 1.522688E+02 7.871171E-01 1.522544E+02 2.091770E+00 + 1.840003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.840003E+01 0.000000E+00 5 6.320253E+02 8.980453E+01 2.156214E+00 6.320217E+02 + 1.840003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.840003E+01 3.000000E+01 1 6.300617E+01 8.980470E+01 2.147653E-01 6.300580E+01 + 1.840003E+01 3.000000E+01 2 3.842981E+01 8.974377E+01 1.718586E-01 3.842942E+01 + 1.840003E+01 3.000000E+01 3 1.540321E+02 7.918285E-01 1.540174E+02 2.128659E+00 + 1.840003E+01 3.000000E+01 4 1.312489E+02 8.973939E+01 5.969814E-01 1.312476E+02 + 1.840003E+01 3.000000E+01 5 5.529463E+02 8.980471E+01 1.884742E+00 5.529431E+02 + 1.840003E+01 3.000000E+01 6 1.690739E+02 -8.624646E-03 1.690739E+02 -2.545044E-02 + 1.840003E+01 6.000000E+01 1 3.711906E+01 8.980499E+01 1.263339E-01 3.711884E+01 + 1.840003E+01 6.000000E+01 2 6.806809E+01 8.974357E+01 3.046451E-01 6.806741E+01 + 1.840003E+01 6.000000E+01 3 1.576254E+02 8.012876E-01 1.576100E+02 2.204337E+00 + 1.840003E+01 6.000000E+01 4 2.364193E+02 8.974354E+01 1.058241E+00 2.364169E+02 + 1.840003E+01 6.000000E+01 5 3.257329E+02 8.980498E+01 1.108688E+00 3.257310E+02 + 1.840003E+01 6.000000E+01 6 1.729902E+02 -8.557120E-03 1.729902E+02 -2.583607E-02 + 1.840003E+01 9.000000E+01 1 3.906815E-06 -9.007437E+01 -5.071096E-09 -3.906812E-06 + 1.840003E+01 9.000000E+01 2 7.948264E+01 8.974347E+01 3.558712E-01 7.948185E+01 + 1.840003E+01 9.000000E+01 3 1.594551E+02 8.060344E-01 1.594393E+02 2.243133E+00 + 1.840003E+01 9.000000E+01 4 2.783203E+02 8.974551E+01 1.236186E+00 2.783175E+02 + 1.840003E+01 9.000000E+01 5 1.707521E-04 -8.995554E+01 1.324810E-07 -1.707521E-04 + 1.840003E+01 9.000000E+01 6 1.500261E-05 1.799943E+02 -1.500261E-05 1.485979E-09 + 1.850003E+01 0.000000E+00 1 7.164205E+01 8.980706E+01 2.412556E-01 7.164165E+01 + 1.850003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.850003E+01 0.000000E+00 3 1.528361E+02 7.779517E-01 1.528220E+02 2.075117E+00 + 1.850003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.850003E+01 0.000000E+00 5 6.306125E+02 8.980704E+01 2.123773E+00 6.306089E+02 + 1.850003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.850003E+01 3.000000E+01 1 6.266346E+01 8.980721E+01 2.108573E-01 6.266311E+01 + 1.850003E+01 3.000000E+01 2 3.822110E+01 8.974770E+01 1.683022E-01 3.822073E+01 + 1.850003E+01 3.000000E+01 3 1.545818E+02 7.825297E-01 1.545674E+02 2.111169E+00 + 1.850003E+01 3.000000E+01 4 1.304306E+02 8.974344E+01 5.840477E-01 1.304293E+02 + 1.850003E+01 3.000000E+01 5 5.516334E+02 8.980721E+01 1.856169E+00 5.516302E+02 + 1.850003E+01 3.000000E+01 6 1.670181E+02 -8.375099E-03 1.670181E+02 -2.441354E-02 + 1.850003E+01 6.000000E+01 1 3.690732E+01 8.980749E+01 1.240075E-01 3.690711E+01 + 1.850003E+01 6.000000E+01 2 6.767809E+01 8.974751E+01 2.982456E-01 6.767743E+01 + 1.850003E+01 6.000000E+01 3 1.581387E+02 7.917254E-01 1.581236E+02 2.185125E+00 + 1.850003E+01 6.000000E+01 4 2.348323E+02 8.974747E+01 1.034985E+00 2.348300E+02 + 1.850003E+01 6.000000E+01 5 3.248682E+02 8.980747E+01 1.091634E+00 3.248664E+02 + 1.850003E+01 6.000000E+01 6 1.708347E+02 -8.310426E-03 1.708347E+02 -2.477859E-02 + 1.850003E+01 9.000000E+01 1 3.883495E-06 -9.007466E+01 -5.060660E-09 -3.883492E-06 + 1.850003E+01 9.000000E+01 2 7.901544E+01 8.974741E+01 3.483408E-01 7.901467E+01 + 1.850003E+01 9.000000E+01 3 1.599494E+02 7.963436E-01 1.599340E+02 2.223036E+00 + 1.850003E+01 9.000000E+01 4 2.763865E+02 8.974940E+01 1.208826E+00 2.763838E+02 + 1.850003E+01 9.000000E+01 5 1.698839E-04 -8.995643E+01 1.291906E-07 -1.698839E-04 + 1.850003E+01 9.000000E+01 6 1.481295E-05 1.799945E+02 -1.481295E-05 1.425329E-09 + 1.860003E+01 0.000000E+00 1 7.126378E+01 8.980952E+01 2.369186E-01 7.126338E+01 + 1.860003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.860003E+01 0.000000E+00 3 1.533943E+02 7.689454E-01 1.533805E+02 2.058587E+00 + 1.860003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.860003E+01 0.000000E+00 5 6.291846E+02 8.980950E+01 2.091887E+00 6.291811E+02 + 1.860003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.860003E+01 3.000000E+01 1 6.232437E+01 8.980966E+01 2.070444E-01 6.232403E+01 + 1.860003E+01 3.000000E+01 2 3.801441E+01 8.975154E+01 1.648460E-01 3.801405E+01 + 1.860003E+01 3.000000E+01 3 1.551238E+02 7.734011E-01 1.551096E+02 2.093859E+00 + 1.860003E+01 3.000000E+01 4 1.296225E+02 8.974739E+01 5.714963E-01 1.296213E+02 + 1.860003E+01 3.000000E+01 5 5.503102E+02 8.980967E+01 1.828118E+00 5.503071E+02 + 1.860003E+01 3.000000E+01 6 1.650007E+02 -8.134776E-03 1.650007E+02 -2.342656E-02 + 1.860003E+01 6.000000E+01 1 3.669810E+01 8.980994E+01 1.217389E-01 3.669790E+01 + 1.860003E+01 6.000000E+01 2 6.729265E+01 8.975135E+01 2.920308E-01 6.729202E+01 + 1.860003E+01 6.000000E+01 3 1.586445E+02 7.823420E-01 1.586297E+02 2.166135E+00 + 1.860003E+01 6.000000E+01 4 2.332667E+02 8.975132E+01 1.012429E+00 2.332645E+02 + 1.860003E+01 6.000000E+01 5 3.240025E+02 8.980992E+01 1.074895E+00 3.240008E+02 + 1.860003E+01 6.000000E+01 6 1.687207E+02 -8.072804E-03 1.687207E+02 -2.377225E-02 + 1.860003E+01 9.000000E+01 1 3.860472E-06 -9.007492E+01 -5.047793E-09 -3.860469E-06 + 1.860003E+01 9.000000E+01 2 7.855367E+01 8.975126E+01 3.410285E-01 7.855293E+01 + 1.860003E+01 9.000000E+01 3 1.604366E+02 7.868304E-01 1.604214E+02 2.203171E+00 + 1.860003E+01 9.000000E+01 4 2.744805E+02 8.975320E+01 1.182297E+00 2.744779E+02 + 1.860003E+01 9.000000E+01 5 1.690257E-04 -8.995729E+01 1.260047E-07 -1.690256E-04 + 1.860003E+01 9.000000E+01 6 1.462706E-05 1.799946E+02 -1.462706E-05 1.367605E-09 + 1.870004E+01 0.000000E+00 1 7.088927E+01 8.981194E+01 2.326851E-01 7.088889E+01 + 1.870004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.870004E+01 0.000000E+00 3 1.539454E+02 7.600883E-01 1.539318E+02 2.042186E+00 + 1.870004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.870004E+01 0.000000E+00 5 6.277385E+02 8.981192E+01 2.060601E+00 6.277351E+02 + 1.870004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.870004E+01 3.000000E+01 1 6.198892E+01 8.981207E+01 2.033236E-01 6.198859E+01 + 1.870004E+01 3.000000E+01 2 3.780996E+01 8.975529E+01 1.614865E-01 3.780961E+01 + 1.870004E+01 3.000000E+01 3 1.556573E+02 7.644194E-01 1.556434E+02 2.076661E+00 + 1.870004E+01 3.000000E+01 4 1.288244E+02 8.975124E+01 5.593082E-01 1.288232E+02 + 1.870004E+01 3.000000E+01 5 5.489734E+02 8.981208E+01 1.800582E+00 5.489705E+02 + 1.870004E+01 3.000000E+01 6 1.630204E+02 -7.903268E-03 1.630204E+02 -2.248672E-02 + 1.870004E+01 6.000000E+01 1 3.649121E+01 8.981233E+01 1.195254E-01 3.649101E+01 + 1.870004E+01 6.000000E+01 2 6.691158E+01 8.975510E+01 2.859918E-01 6.691096E+01 + 1.870004E+01 6.000000E+01 3 1.591425E+02 7.731164E-01 1.591281E+02 2.147313E+00 + 1.870004E+01 6.000000E+01 4 2.317234E+02 8.975508E+01 9.905398E-01 2.317213E+02 + 1.870004E+01 6.000000E+01 5 3.231285E+02 8.981232E+01 1.058487E+00 3.231268E+02 + 1.870004E+01 6.000000E+01 6 1.666478E+02 -7.843827E-03 1.666478E+02 -2.281418E-02 + 1.870004E+01 9.000000E+01 1 3.837726E-06 -9.007513E+01 -5.032650E-09 -3.837723E-06 + 1.870004E+01 9.000000E+01 2 7.809767E+01 8.975502E+01 3.339256E-01 7.809695E+01 + 1.870004E+01 9.000000E+01 3 1.609160E+02 7.774919E-01 1.609012E+02 2.183530E+00 + 1.870004E+01 9.000000E+01 4 2.726035E+02 8.975692E+01 1.156559E+00 2.726011E+02 + 1.870004E+01 9.000000E+01 5 1.681753E-04 -8.995812E+01 1.229208E-07 -1.681752E-04 + 1.870004E+01 9.000000E+01 6 1.444477E-05 1.799948E+02 -1.444477E-05 1.312643E-09 + 1.880004E+01 0.000000E+00 1 7.051838E+01 8.981431E+01 2.285529E-01 7.051801E+01 + 1.880004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.880004E+01 0.000000E+00 3 1.544878E+02 7.513816E-01 1.544745E+02 2.025908E+00 + 1.880004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.880004E+01 0.000000E+00 5 6.262758E+02 8.981429E+01 2.029913E+00 6.262725E+02 + 1.880004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.880004E+01 3.000000E+01 1 6.165702E+01 8.981444E+01 1.996926E-01 6.165670E+01 + 1.880004E+01 3.000000E+01 2 3.760765E+01 8.975895E+01 1.582202E-01 3.760732E+01 + 1.880004E+01 3.000000E+01 3 1.561836E+02 7.555948E-01 1.561700E+02 2.059630E+00 + 1.880004E+01 3.000000E+01 4 1.280360E+02 8.975500E+01 5.474756E-01 1.280349E+02 + 1.880004E+01 3.000000E+01 5 5.476246E+02 8.981444E+01 1.773582E+00 5.476217E+02 + 1.880004E+01 3.000000E+01 6 1.610770E+02 -7.680135E-03 1.610770E+02 -2.159135E-02 + 1.880004E+01 6.000000E+01 1 3.628674E+01 8.981468E+01 1.173662E-01 3.628654E+01 + 1.880004E+01 6.000000E+01 2 6.653476E+01 8.975877E+01 2.801238E-01 6.653417E+01 + 1.880004E+01 6.000000E+01 3 1.596335E+02 7.640691E-01 1.596193E+02 2.128733E+00 + 1.880004E+01 6.000000E+01 4 2.301998E+02 8.975875E+01 9.692938E-01 2.301978E+02 + 1.880004E+01 6.000000E+01 5 3.222533E+02 8.981467E+01 1.042398E+00 3.222516E+02 + 1.880004E+01 6.000000E+01 6 1.646141E+02 -7.623150E-03 1.646141E+02 -2.190175E-02 + 1.880004E+01 9.000000E+01 1 3.815251E-06 -9.007532E+01 -5.015422E-09 -3.815248E-06 + 1.880004E+01 9.000000E+01 2 7.764704E+01 8.975869E+01 3.270249E-01 7.764635E+01 + 1.880004E+01 9.000000E+01 3 1.613897E+02 7.683160E-01 1.613752E+02 2.164113E+00 + 1.880004E+01 9.000000E+01 4 2.707519E+02 8.976054E+01 1.131587E+00 2.707496E+02 + 1.880004E+01 9.000000E+01 5 1.673326E-04 -8.995893E+01 1.199335E-07 -1.673326E-04 + 1.880004E+01 9.000000E+01 6 1.426603E-05 1.799949E+02 -1.426603E-05 1.260288E-09 + 1.890004E+01 0.000000E+00 1 7.015113E+01 8.981663E+01 2.245188E-01 7.015077E+01 + 1.890004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.890004E+01 0.000000E+00 3 1.550225E+02 7.428225E-01 1.550094E+02 2.009763E+00 + 1.890004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.890004E+01 0.000000E+00 5 6.247957E+02 8.981661E+01 1.999770E+00 6.247925E+02 + 1.890004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.890004E+01 3.000000E+01 1 6.132856E+01 8.981675E+01 1.961475E-01 6.132825E+01 + 1.890004E+01 3.000000E+01 2 3.740742E+01 8.976253E+01 1.550437E-01 3.740710E+01 + 1.890004E+01 3.000000E+01 3 1.567010E+02 7.469233E-01 1.566877E+02 2.042739E+00 + 1.890004E+01 3.000000E+01 4 1.272576E+02 8.975868E+01 5.359846E-01 1.272565E+02 + 1.890004E+01 3.000000E+01 5 5.462592E+02 8.981675E+01 1.747093E+00 5.462563E+02 + 1.890004E+01 3.000000E+01 6 1.591689E+02 -7.465058E-03 1.591689E+02 -2.073810E-02 + 1.890004E+01 6.000000E+01 1 3.608452E+01 8.981699E+01 1.152586E-01 3.608434E+01 + 1.890004E+01 6.000000E+01 2 6.616258E+01 8.976235E+01 2.744199E-01 6.616201E+01 + 1.890004E+01 6.000000E+01 3 1.601171E+02 7.551630E-01 1.601032E+02 2.110296E+00 + 1.890004E+01 6.000000E+01 4 2.286984E+02 8.976233E+01 9.486709E-01 2.286964E+02 + 1.890004E+01 6.000000E+01 5 3.213707E+02 8.981698E+01 1.026604E+00 3.213691E+02 + 1.890004E+01 6.000000E+01 6 1.626183E+02 -7.410386E-03 1.626183E+02 -2.103234E-02 + 1.890004E+01 9.000000E+01 1 3.793045E-06 -9.007547E+01 -4.996249E-09 -3.793042E-06 + 1.890004E+01 9.000000E+01 2 7.720198E+01 8.976228E+01 3.203201E-01 7.720132E+01 + 1.890004E+01 9.000000E+01 3 1.618545E+02 7.593017E-01 1.618403E+02 2.144884E+00 + 1.890004E+01 9.000000E+01 4 2.689290E+02 8.976408E+01 1.107348E+00 2.689268E+02 + 1.890004E+01 9.000000E+01 5 1.664985E-04 -8.995972E+01 1.170405E-07 -1.664984E-04 + 1.890004E+01 9.000000E+01 6 1.409072E-05 1.799951E+02 -1.409072E-05 1.210402E-09 + 1.900004E+01 0.000000E+00 1 6.978777E+01 8.981891E+01 2.205790E-01 6.978741E+01 + 1.900004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.900004E+01 0.000000E+00 3 1.555495E+02 7.344062E-01 1.555367E+02 1.993748E+00 + 1.900004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.900004E+01 0.000000E+00 5 6.233063E+02 8.981889E+01 1.970198E+00 6.233032E+02 + 1.900004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.900004E+01 3.000000E+01 1 6.100338E+01 8.981902E+01 1.926873E-01 6.100307E+01 + 1.900004E+01 3.000000E+01 2 3.720937E+01 8.976602E+01 1.519540E-01 3.720906E+01 + 1.900004E+01 3.000000E+01 3 1.572115E+02 7.384052E-01 1.571984E+02 2.026023E+00 + 1.900004E+01 3.000000E+01 4 1.264887E+02 8.976228E+01 5.248197E-01 1.264876E+02 + 1.900004E+01 3.000000E+01 5 5.448878E+02 8.981903E+01 1.721063E+00 5.448850E+02 + 1.900004E+01 3.000000E+01 6 1.572953E+02 -7.257670E-03 1.572953E+02 -1.992464E-02 + 1.900004E+01 6.000000E+01 1 3.588451E+01 8.981926E+01 1.132025E-01 3.588433E+01 + 1.900004E+01 6.000000E+01 2 6.579439E+01 8.976586E+01 2.688755E-01 6.579384E+01 + 1.900004E+01 6.000000E+01 3 1.605941E+02 7.464270E-01 1.605805E+02 2.092098E+00 + 1.900004E+01 6.000000E+01 4 2.272180E+02 8.976583E+01 9.286466E-01 2.272161E+02 + 1.900004E+01 6.000000E+01 5 3.204846E+02 8.981924E+01 1.011113E+00 3.204830E+02 + 1.900004E+01 6.000000E+01 6 1.606605E+02 -7.205190E-03 1.606605E+02 -2.020374E-02 + 1.900004E+01 9.000000E+01 1 3.771110E-06 -9.007559E+01 -4.975303E-09 -3.771107E-06 + 1.900004E+01 9.000000E+01 2 7.676212E+01 8.976578E+01 3.138021E-01 7.676148E+01 + 1.900004E+01 9.000000E+01 3 1.623144E+02 7.504477E-01 1.623005E+02 2.125898E+00 + 1.900004E+01 9.000000E+01 4 2.671296E+02 8.976754E+01 1.083821E+00 2.671274E+02 + 1.900004E+01 9.000000E+01 5 1.656728E-04 -8.996049E+01 1.142378E-07 -1.656728E-04 + 1.900004E+01 9.000000E+01 6 1.391878E-05 1.799952E+02 -1.391878E-05 1.162848E-09 + 1.910004E+01 0.000000E+00 1 6.942786E+01 8.982114E+01 2.167330E-01 6.942752E+01 + 1.910004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.910004E+01 0.000000E+00 3 1.560689E+02 7.261311E-01 1.560564E+02 1.977868E+00 + 1.910004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.910004E+01 0.000000E+00 5 6.218000E+02 8.982114E+01 1.941159E+00 6.217969E+02 + 1.910004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.910004E+01 3.000000E+01 1 6.068158E+01 8.982126E+01 1.893084E-01 6.068128E+01 + 1.910004E+01 3.000000E+01 2 3.701323E+01 8.976943E+01 1.489489E-01 3.701293E+01 + 1.910004E+01 3.000000E+01 3 1.577154E+02 7.300221E-01 1.577026E+02 2.009443E+00 + 1.910004E+01 3.000000E+01 4 1.257294E+02 8.976578E+01 5.139754E-01 1.257283E+02 + 1.910004E+01 3.000000E+01 5 5.435054E+02 8.982126E+01 1.695528E+00 5.435027E+02 + 1.910004E+01 3.000000E+01 6 1.554560E+02 -7.057612E-03 1.554560E+02 -1.914885E-02 + 1.910004E+01 6.000000E+01 1 3.568686E+01 8.982148E+01 1.111949E-01 3.568669E+01 + 1.910004E+01 6.000000E+01 2 6.543037E+01 8.976927E+01 2.634829E-01 6.542984E+01 + 1.910004E+01 6.000000E+01 3 1.610642E+02 7.378352E-01 1.610508E+02 2.074071E+00 + 1.910004E+01 6.000000E+01 4 2.257564E+02 8.976925E+01 9.091973E-01 2.257546E+02 + 1.910004E+01 6.000000E+01 5 3.195949E+02 8.982146E+01 9.959189E-01 3.195933E+02 + 1.910004E+01 6.000000E+01 6 1.587390E+02 -7.007251E-03 1.587390E+02 -1.941372E-02 + 1.910004E+01 9.000000E+01 1 3.749427E-06 -9.007568E+01 -4.952720E-09 -3.749424E-06 + 1.910004E+01 9.000000E+01 2 7.632726E+01 8.976920E+01 3.074666E-01 7.632664E+01 + 1.910004E+01 9.000000E+01 3 1.627665E+02 7.417550E-01 1.627528E+02 2.107127E+00 + 1.910004E+01 9.000000E+01 4 2.653554E+02 8.977091E+01 1.060974E+00 2.653533E+02 + 1.910004E+01 9.000000E+01 5 1.648544E-04 -8.996124E+01 1.115214E-07 -1.648543E-04 + 1.910004E+01 9.000000E+01 6 1.375006E-05 1.799953E+02 -1.375006E-05 1.117500E-09 + 1.920004E+01 0.000000E+00 1 6.907115E+01 8.982333E+01 2.129757E-01 6.907082E+01 + 1.920004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.920004E+01 0.000000E+00 3 1.565803E+02 7.179950E-01 1.565680E+02 1.962116E+00 + 1.920004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.920004E+01 0.000000E+00 5 6.202828E+02 8.982333E+01 1.912669E+00 6.202799E+02 + 1.920004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.920004E+01 3.000000E+01 1 6.036312E+01 8.982344E+01 1.860089E-01 6.036284E+01 + 1.920004E+01 3.000000E+01 2 3.681923E+01 8.977277E+01 1.460243E-01 3.681894E+01 + 1.920004E+01 3.000000E+01 3 1.582106E+02 7.217817E-01 1.581981E+02 1.993000E+00 + 1.920004E+01 3.000000E+01 4 1.249795E+02 8.976920E+01 5.034329E-01 1.249784E+02 + 1.920004E+01 3.000000E+01 5 5.421082E+02 8.982345E+01 1.670478E+00 5.421056E+02 + 1.920004E+01 3.000000E+01 6 1.536496E+02 -6.864610E-03 1.536496E+02 -1.840876E-02 + 1.920004E+01 6.000000E+01 1 3.549138E+01 8.982365E+01 1.092358E-01 3.549121E+01 + 1.920004E+01 6.000000E+01 2 6.507050E+01 8.977261E+01 2.582391E-01 6.506998E+01 + 1.920004E+01 6.000000E+01 3 1.615269E+02 7.293875E-01 1.615138E+02 2.056216E+00 + 1.920004E+01 6.000000E+01 4 2.243149E+02 8.977259E+01 8.903069E-01 2.243131E+02 + 1.920004E+01 6.000000E+01 5 3.186985E+02 8.982363E+01 9.810125E-01 3.186970E+02 + 1.920004E+01 6.000000E+01 6 1.568531E+02 -6.816230E-03 1.568531E+02 -1.866014E-02 + 1.920004E+01 9.000000E+01 1 3.728017E-06 -9.007575E+01 -4.928615E-09 -3.728014E-06 + 1.920004E+01 9.000000E+01 2 7.589767E+01 8.977254E+01 3.013060E-01 7.589707E+01 + 1.920004E+01 9.000000E+01 3 1.632128E+02 7.332022E-01 1.631994E+02 2.088543E+00 + 1.920004E+01 9.000000E+01 4 2.636079E+02 8.977422E+01 1.038785E+00 2.636059E+02 + 1.920004E+01 9.000000E+01 5 1.640436E-04 -8.996197E+01 1.088889E-07 -1.640436E-04 + 1.920004E+01 9.000000E+01 6 1.358456E-05 1.799955E+02 -1.358456E-05 1.074242E-09 + 1.930004E+01 0.000000E+00 1 6.871840E+01 8.982549E+01 2.093058E-01 6.871808E+01 + 1.930004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.930004E+01 0.000000E+00 3 1.570845E+02 7.099943E-01 1.570725E+02 1.946501E+00 + 1.930004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.930004E+01 0.000000E+00 5 6.187471E+02 8.982548E+01 1.884677E+00 6.187443E+02 + 1.930004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.930004E+01 3.000000E+01 1 6.004795E+01 8.982559E+01 1.827856E-01 6.004767E+01 + 1.930004E+01 3.000000E+01 2 3.662716E+01 8.977603E+01 1.431779E-01 3.662688E+01 + 1.930004E+01 3.000000E+01 3 1.586995E+02 7.136821E-01 1.586872E+02 1.976727E+00 + 1.930004E+01 3.000000E+01 4 1.242382E+02 8.977256E+01 4.931839E-01 1.242372E+02 + 1.930004E+01 3.000000E+01 5 5.407071E+02 8.982559E+01 1.645885E+00 5.407046E+02 + 1.930004E+01 3.000000E+01 6 1.518755E+02 -6.678335E-03 1.518755E+02 -1.770245E-02 + 1.930004E+01 6.000000E+01 1 3.529807E+01 8.982579E+01 1.073225E-01 3.529791E+01 + 1.930004E+01 6.000000E+01 2 6.471467E+01 8.977589E+01 2.531377E-01 6.471417E+01 + 1.930004E+01 6.000000E+01 3 1.619833E+02 7.210882E-01 1.619704E+02 2.038564E+00 + 1.930004E+01 6.000000E+01 4 2.228919E+02 8.977586E+01 8.719522E-01 2.228902E+02 + 1.930004E+01 6.000000E+01 5 3.178018E+02 8.982578E+01 9.663804E-01 3.178004E+02 + 1.930004E+01 6.000000E+01 6 1.550019E+02 -6.631880E-03 1.550019E+02 -1.794118E-02 + 1.930004E+01 9.000000E+01 1 3.706853E-06 -9.007578E+01 -4.903121E-09 -3.706850E-06 + 1.930004E+01 9.000000E+01 2 7.547302E+01 8.977581E+01 2.953140E-01 7.547244E+01 + 1.930004E+01 9.000000E+01 3 1.636519E+02 7.248065E-01 1.636389E+02 2.070184E+00 + 1.930004E+01 9.000000E+01 4 2.618840E+02 8.977745E+01 1.017237E+00 2.618820E+02 + 1.930004E+01 9.000000E+01 5 1.632413E-04 -8.996268E+01 1.063370E-07 -1.632413E-04 + 1.930004E+01 9.000000E+01 6 1.342214E-05 1.799956E+02 -1.342214E-05 1.032962E-09 + 1.940004E+01 0.000000E+00 1 6.836884E+01 8.982761E+01 2.057198E-01 6.836853E+01 + 1.940004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.940004E+01 0.000000E+00 3 1.575827E+02 7.021175E-01 1.575708E+02 1.931011E+00 + 1.940004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.940004E+01 0.000000E+00 5 6.172117E+02 8.982760E+01 1.857207E+00 6.172089E+02 + 1.940004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.940004E+01 3.000000E+01 1 5.973589E+01 8.982770E+01 1.796385E-01 5.973562E+01 + 1.940004E+01 3.000000E+01 2 3.643702E+01 8.977922E+01 1.404070E-01 3.643675E+01 + 1.940004E+01 3.000000E+01 3 1.591822E+02 7.057143E-01 1.591701E+02 1.960603E+00 + 1.940004E+01 3.000000E+01 4 1.235057E+02 8.977583E+01 4.832211E-01 1.235048E+02 + 1.940004E+01 3.000000E+01 5 5.392993E+02 8.982771E+01 1.621748E+00 5.392968E+02 + 1.940004E+01 3.000000E+01 6 1.501328E+02 -6.498507E-03 1.501328E+02 -1.702811E-02 + 1.940004E+01 6.000000E+01 1 3.510679E+01 8.982790E+01 1.054539E-01 3.510663E+01 + 1.940004E+01 6.000000E+01 2 6.436284E+01 8.977908E+01 2.481732E-01 6.436236E+01 + 1.940004E+01 6.000000E+01 3 1.624339E+02 7.129310E-01 1.624213E+02 2.021111E+00 + 1.940004E+01 6.000000E+01 4 2.214881E+02 8.977905E+01 8.541104E-01 2.214865E+02 + 1.940004E+01 6.000000E+01 5 3.169031E+02 8.982787E+01 9.520346E-01 3.169017E+02 + 1.940004E+01 6.000000E+01 6 1.531846E+02 -6.453868E-03 1.531846E+02 -1.725490E-02 + 1.940004E+01 9.000000E+01 1 3.685946E-06 -9.007580E+01 -4.876348E-09 -3.685942E-06 + 1.940004E+01 9.000000E+01 2 7.505329E+01 8.977901E+01 2.894852E-01 7.505273E+01 + 1.940004E+01 9.000000E+01 3 1.640857E+02 7.165560E-01 1.640729E+02 2.052046E+00 + 1.940004E+01 9.000000E+01 4 2.601810E+02 8.978060E+01 9.962885E-01 2.601790E+02 + 1.940004E+01 9.000000E+01 5 1.624452E-04 -8.996336E+01 1.038618E-07 -1.624452E-04 + 1.940004E+01 9.000000E+01 6 1.326271E-05 1.799957E+02 -1.326271E-05 9.935558E-10 + 1.950004E+01 0.000000E+00 1 6.802279E+01 8.982967E+01 2.022174E-01 6.802249E+01 + 1.950004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.950004E+01 0.000000E+00 3 1.580724E+02 6.943756E-01 1.580608E+02 1.915655E+00 + 1.950004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.950004E+01 0.000000E+00 5 6.156529E+02 8.982967E+01 1.830267E+00 6.156501E+02 + 1.950004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.950004E+01 3.000000E+01 1 5.942714E+01 8.982977E+01 1.765630E-01 5.942687E+01 + 1.950004E+01 3.000000E+01 2 3.624876E+01 8.978233E+01 1.377095E-01 3.624850E+01 + 1.950004E+01 3.000000E+01 3 1.596567E+02 6.978816E-01 1.596449E+02 1.944623E+00 + 1.950004E+01 3.000000E+01 4 1.227823E+02 8.977903E+01 4.735329E-01 1.227813E+02 + 1.950004E+01 3.000000E+01 5 5.378788E+02 8.982977E+01 1.598069E+00 5.378764E+02 + 1.950004E+01 3.000000E+01 6 1.484208E+02 -6.324852E-03 1.484208E+02 -1.638410E-02 + 1.950004E+01 6.000000E+01 1 3.491772E+01 8.982996E+01 1.036295E-01 3.491757E+01 + 1.950004E+01 6.000000E+01 2 6.401466E+01 8.978220E+01 2.433422E-01 6.401420E+01 + 1.950004E+01 6.000000E+01 3 1.628769E+02 7.049140E-01 1.628646E+02 2.003836E+00 + 1.950004E+01 6.000000E+01 4 2.201030E+02 8.978217E+01 8.367677E-01 2.201014E+02 + 1.950004E+01 6.000000E+01 5 3.159998E+02 8.982993E+01 9.379523E-01 3.159984E+02 + 1.950004E+01 6.000000E+01 6 1.514002E+02 -6.281951E-03 1.514002E+02 -1.659963E-02 + 1.950004E+01 9.000000E+01 1 3.665270E-06 -9.007579E+01 -4.848439E-09 -3.665266E-06 + 1.950004E+01 9.000000E+01 2 7.463833E+01 8.978214E+01 2.838138E-01 7.463779E+01 + 1.950004E+01 9.000000E+01 3 1.645125E+02 7.084419E-01 1.644999E+02 2.034086E+00 + 1.950004E+01 9.000000E+01 4 2.585056E+02 8.978369E+01 9.759369E-01 2.585038E+02 + 1.950004E+01 9.000000E+01 5 1.616570E-04 -8.996404E+01 1.014617E-07 -1.616569E-04 + 1.950004E+01 9.000000E+01 6 1.310622E-05 1.799958E+02 -1.310622E-05 9.559269E-10 + 1.960004E+01 0.000000E+00 1 6.768022E+01 8.983171E+01 1.987937E-01 6.767993E+01 + 1.960004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.960004E+01 0.000000E+00 3 1.585559E+02 6.867648E-01 1.585445E+02 1.900454E+00 + 1.960004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.960004E+01 0.000000E+00 5 6.140935E+02 8.983170E+01 1.803811E+00 6.140909E+02 + 1.960004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.960004E+01 3.000000E+01 1 5.912159E+01 8.983180E+01 1.735587E-01 5.912133E+01 + 1.960004E+01 3.000000E+01 2 3.606258E+01 8.978539E+01 1.350825E-01 3.606233E+01 + 1.960004E+01 3.000000E+01 3 1.601251E+02 6.901776E-01 1.601135E+02 1.928800E+00 + 1.960004E+01 3.000000E+01 4 1.220670E+02 8.978216E+01 4.641080E-01 1.220661E+02 + 1.960004E+01 3.000000E+01 5 5.364617E+02 8.983181E+01 1.574792E+00 5.364594E+02 + 1.960004E+01 3.000000E+01 6 1.467386E+02 -6.157144E-03 1.467386E+02 -1.576889E-02 + 1.960004E+01 6.000000E+01 1 3.473074E+01 8.983198E+01 1.018475E-01 3.473059E+01 + 1.960004E+01 6.000000E+01 2 6.367042E+01 8.978526E+01 2.386403E-01 6.366998E+01 + 1.960004E+01 6.000000E+01 3 1.633143E+02 6.970323E-01 1.633022E+02 1.986753E+00 + 1.960004E+01 6.000000E+01 4 2.187356E+02 8.978523E+01 8.199068E-01 2.187341E+02 + 1.960004E+01 6.000000E+01 5 3.150946E+02 8.983196E+01 9.241250E-01 3.150932E+02 + 1.960004E+01 6.000000E+01 6 1.496480E+02 -6.115883E-03 1.496480E+02 -1.597377E-02 + 1.960004E+01 9.000000E+01 1 3.644839E-06 -9.007577E+01 -4.819454E-09 -3.644836E-06 + 1.960004E+01 9.000000E+01 2 7.422815E+01 8.978519E+01 2.782941E-01 7.422763E+01 + 1.960004E+01 9.000000E+01 3 1.649340E+02 7.004694E-01 1.649216E+02 2.016349E+00 + 1.960004E+01 9.000000E+01 4 2.568502E+02 8.978671E+01 9.561508E-01 2.568484E+02 + 1.960004E+01 9.000000E+01 5 1.608771E-04 -8.996470E+01 9.913363E-08 -1.608770E-04 + 1.960004E+01 9.000000E+01 6 1.295262E-05 1.799959E+02 -1.295262E-05 9.199813E-10 + 1.970004E+01 0.000000E+00 1 6.734092E+01 8.983371E+01 1.954481E-01 6.734064E+01 + 1.970004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.970004E+01 0.000000E+00 3 1.590327E+02 6.792712E-01 1.590215E+02 1.885371E+00 + 1.970004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.970004E+01 0.000000E+00 5 6.125246E+02 8.983370E+01 1.777803E+00 6.125220E+02 + 1.970004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.970004E+01 3.000000E+01 1 5.881894E+01 8.983380E+01 1.706220E-01 5.881870E+01 + 1.970004E+01 3.000000E+01 2 3.587813E+01 8.978836E+01 1.325237E-01 3.587788E+01 + 1.970004E+01 3.000000E+01 3 1.605865E+02 6.826011E-01 1.605751E+02 1.913124E+00 + 1.970004E+01 3.000000E+01 4 1.213605E+02 8.978522E+01 4.549405E-01 1.213596E+02 + 1.970004E+01 3.000000E+01 5 5.350274E+02 8.983380E+01 1.551983E+00 5.350251E+02 + 1.970004E+01 3.000000E+01 6 1.450856E+02 -5.995097E-03 1.450856E+02 -1.518091E-02 + 1.970004E+01 6.000000E+01 1 3.454567E+01 8.983397E+01 1.001060E-01 3.454552E+01 + 1.970004E+01 6.000000E+01 2 6.332985E+01 8.978824E+01 2.340613E-01 6.332942E+01 + 1.970004E+01 6.000000E+01 3 1.637459E+02 6.892782E-01 1.637341E+02 1.969845E+00 + 1.970004E+01 6.000000E+01 4 2.173860E+02 8.978822E+01 8.035110E-01 2.173845E+02 + 1.970004E+01 6.000000E+01 5 3.141878E+02 8.983395E+01 9.105613E-01 3.141865E+02 + 1.970004E+01 6.000000E+01 6 1.479271E+02 -5.955416E-03 1.479271E+02 -1.537578E-02 + 1.970004E+01 9.000000E+01 1 3.624643E-06 -9.007571E+01 -4.789501E-09 -3.624640E-06 + 1.970004E+01 9.000000E+01 2 7.382257E+01 8.978818E+01 2.729210E-01 7.382207E+01 + 1.970004E+01 9.000000E+01 3 1.653496E+02 6.926309E-01 1.653375E+02 1.998811E+00 + 1.970004E+01 9.000000E+01 4 2.552161E+02 8.978967E+01 9.369106E-01 2.552144E+02 + 1.970004E+01 9.000000E+01 5 1.601036E-04 -8.996533E+01 9.687469E-08 -1.601036E-04 + 1.970004E+01 9.000000E+01 6 1.280180E-05 1.799960E+02 -1.280180E-05 8.856320E-10 + 1.980004E+01 0.000000E+00 1 6.700471E+01 8.983567E+01 1.921776E-01 6.700443E+01 + 1.980004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.980004E+01 0.000000E+00 3 1.595020E+02 6.718988E-01 1.594910E+02 1.870412E+00 + 1.980004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.980004E+01 0.000000E+00 5 6.109462E+02 8.983567E+01 1.752289E+00 6.109437E+02 + 1.980004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.980004E+01 3.000000E+01 1 5.851933E+01 8.983575E+01 1.677530E-01 5.851908E+01 + 1.980004E+01 3.000000E+01 2 3.569559E+01 8.979129E+01 1.300312E-01 3.569535E+01 + 1.980004E+01 3.000000E+01 3 1.610419E+02 6.751460E-01 1.610307E+02 1.897596E+00 + 1.980004E+01 3.000000E+01 4 1.206626E+02 8.978822E+01 4.460172E-01 1.206618E+02 + 1.980004E+01 3.000000E+01 5 5.335878E+02 8.983575E+01 1.529572E+00 5.335856E+02 + 1.980004E+01 3.000000E+01 6 1.434617E+02 -5.838491E-03 1.434617E+02 -1.461887E-02 + 1.980004E+01 6.000000E+01 1 3.436272E+01 8.983592E+01 9.840482E-02 3.436258E+01 + 1.980004E+01 6.000000E+01 2 6.299330E+01 8.979116E+01 2.296038E-01 6.299288E+01 + 1.980004E+01 6.000000E+01 3 1.641703E+02 6.816542E-01 1.641586E+02 1.953106E+00 + 1.980004E+01 6.000000E+01 4 2.160534E+02 8.979115E+01 7.875615E-01 2.160520E+02 + 1.980004E+01 6.000000E+01 5 3.132790E+02 8.983590E+01 8.972627E-01 3.132777E+02 + 1.980004E+01 6.000000E+01 6 1.462366E+02 -5.800338E-03 1.462366E+02 -1.480426E-02 + 1.980004E+01 9.000000E+01 1 3.604679E-06 -9.007564E+01 -4.758652E-09 -3.604676E-06 + 1.980004E+01 9.000000E+01 2 7.342159E+01 8.979110E+01 2.676905E-01 7.342110E+01 + 1.980004E+01 9.000000E+01 3 1.657582E+02 6.849240E-01 1.657464E+02 1.981456E+00 + 1.980004E+01 9.000000E+01 4 2.536058E+02 8.979256E+01 9.182081E-01 2.536041E+02 + 1.980004E+01 9.000000E+01 5 1.593371E-04 -8.996596E+01 9.468278E-08 -1.593371E-04 + 1.980004E+01 9.000000E+01 6 1.265372E-05 1.799961E+02 -1.265372E-05 8.527974E-10 + 1.990004E+01 0.000000E+00 1 6.667184E+01 8.983759E+01 1.889807E-01 6.667157E+01 + 1.990004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.990004E+01 0.000000E+00 3 1.599651E+02 6.646500E-01 1.599543E+02 1.855606E+00 + 1.990004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.990004E+01 0.000000E+00 5 6.093580E+02 8.983759E+01 1.727242E+00 6.093556E+02 + 1.990004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 1.990004E+01 3.000000E+01 1 5.822293E+01 8.983768E+01 1.649476E-01 5.822269E+01 + 1.990004E+01 3.000000E+01 2 3.551482E+01 8.979414E+01 1.276025E-01 3.551460E+01 + 1.990004E+01 3.000000E+01 3 1.614907E+02 6.678128E-01 1.614797E+02 1.882217E+00 + 1.990004E+01 3.000000E+01 4 1.199726E+02 8.979115E+01 4.373339E-01 1.199718E+02 + 1.990004E+01 3.000000E+01 5 5.321520E+02 8.983768E+01 1.507587E+00 5.321498E+02 + 1.990004E+01 3.000000E+01 6 1.418652E+02 -5.687098E-03 1.418652E+02 -1.408134E-02 + 1.990004E+01 6.000000E+01 1 3.418168E+01 8.983784E+01 9.674253E-02 3.418155E+01 + 1.990004E+01 6.000000E+01 2 6.266013E+01 8.979403E+01 2.252613E-01 6.265973E+01 + 1.990004E+01 6.000000E+01 3 1.645891E+02 6.741656E-01 1.645777E+02 1.936578E+00 + 1.990004E+01 6.000000E+01 4 2.147379E+02 8.979401E+01 7.720474E-01 2.147365E+02 + 1.990004E+01 6.000000E+01 5 3.123662E+02 8.983781E+01 8.842103E-01 3.123649E+02 + 1.990004E+01 6.000000E+01 6 1.445764E+02 -5.650376E-03 1.445764E+02 -1.425779E-02 + 1.990004E+01 9.000000E+01 1 3.584934E-06 -9.007555E+01 -4.727026E-09 -3.584930E-06 + 1.990004E+01 9.000000E+01 2 7.302515E+01 8.979396E+01 2.625970E-01 7.302467E+01 + 1.990004E+01 9.000000E+01 3 1.661619E+02 6.773497E-01 1.661503E+02 1.964318E+00 + 1.990004E+01 9.000000E+01 4 2.520165E+02 8.979539E+01 9.000081E-01 2.520149E+02 + 1.990004E+01 9.000000E+01 5 1.585784E-04 -8.996656E+01 9.255515E-08 -1.585784E-04 + 1.990004E+01 9.000000E+01 6 1.250827E-05 1.799962E+02 -1.250827E-05 8.214012E-10 + 2.000004E+01 0.000000E+00 1 6.634226E+01 8.983949E+01 1.858546E-01 6.634200E+01 + 2.000004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000004E+01 0.000000E+00 3 1.604220E+02 6.575137E-01 1.604115E+02 1.840927E+00 + 2.000004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000004E+01 0.000000E+00 5 6.077615E+02 8.983949E+01 1.702645E+00 6.077592E+02 + 2.000004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.000004E+01 3.000000E+01 1 5.792927E+01 8.983957E+01 1.622059E-01 5.792904E+01 + 2.000004E+01 3.000000E+01 2 3.533589E+01 8.979694E+01 1.252355E-01 3.533567E+01 + 2.000004E+01 3.000000E+01 3 1.619333E+02 6.605989E-01 1.619226E+02 1.866989E+00 + 2.000004E+01 3.000000E+01 4 1.192906E+02 8.979401E+01 4.288814E-01 1.192898E+02 + 2.000004E+01 3.000000E+01 5 5.307010E+02 8.983957E+01 1.485988E+00 5.306990E+02 + 2.000004E+01 3.000000E+01 6 1.402961E+02 -5.540731E-03 1.402961E+02 -1.356720E-02 + 2.000004E+01 6.000000E+01 1 3.400243E+01 8.983972E+01 9.511802E-02 3.400230E+01 + 2.000004E+01 6.000000E+01 2 6.233058E+01 8.979683E+01 2.210312E-01 6.233019E+01 + 2.000004E+01 6.000000E+01 3 1.650017E+02 6.667956E-01 1.649906E+02 1.920210E+00 + 2.000004E+01 6.000000E+01 4 2.134400E+02 8.979681E+01 7.569461E-01 2.134387E+02 + 2.000004E+01 6.000000E+01 5 3.114556E+02 8.983970E+01 8.713866E-01 3.114543E+02 + 2.000004E+01 6.000000E+01 6 1.429450E+02 -5.505381E-03 1.429450E+02 -1.373516E-02 + 2.000004E+01 9.000000E+01 1 3.565423E-06 -9.007544E+01 -4.694682E-09 -3.565420E-06 + 2.000004E+01 9.000000E+01 2 7.263313E+01 8.979677E+01 2.576355E-01 7.263268E+01 + 2.000004E+01 9.000000E+01 3 1.665602E+02 6.698995E-01 1.665488E+02 1.947369E+00 + 2.000004E+01 9.000000E+01 4 2.504476E+02 8.979815E+01 8.823016E-01 2.504461E+02 + 2.000004E+01 9.000000E+01 5 1.578268E-04 -8.996715E+01 9.048949E-08 -1.578268E-04 + 2.000004E+01 9.000000E+01 6 1.236541E-05 1.799963E+02 -1.236541E-05 7.913703E-10 + 2.010004E+01 0.000000E+00 1 6.601561E+01 8.984135E+01 1.827983E-01 6.601536E+01 + 2.010004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.010004E+01 0.000000E+00 3 1.608723E+02 6.504965E-01 1.608620E+02 1.826393E+00 + 2.010004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.010004E+01 0.000000E+00 5 6.061603E+02 8.984135E+01 1.678491E+00 6.061580E+02 + 2.010004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.010004E+01 3.000000E+01 1 5.763844E+01 8.984143E+01 1.595245E-01 5.763822E+01 + 2.010004E+01 3.000000E+01 2 3.515861E+01 8.979967E+01 1.229283E-01 3.515839E+01 + 2.010004E+01 3.000000E+01 3 1.623705E+02 6.535022E-01 1.623599E+02 1.851919E+00 + 2.010004E+01 3.000000E+01 4 1.186168E+02 8.979681E+01 4.206497E-01 1.186160E+02 + 2.010004E+01 3.000000E+01 5 5.292515E+02 8.984143E+01 1.464780E+00 5.292495E+02 + 2.010004E+01 3.000000E+01 6 1.387538E+02 -5.399149E-03 1.387538E+02 -1.307518E-02 + 2.010004E+01 6.000000E+01 1 3.382521E+01 8.984157E+01 9.352974E-02 3.382508E+01 + 2.010004E+01 6.000000E+01 2 6.200449E+01 8.979957E+01 2.169100E-01 6.200412E+01 + 2.010004E+01 6.000000E+01 3 1.654107E+02 6.595407E-01 1.653997E+02 1.904026E+00 + 2.010004E+01 6.000000E+01 4 2.121576E+02 8.979955E+01 7.422479E-01 2.121563E+02 + 2.010004E+01 6.000000E+01 5 3.105449E+02 8.984155E+01 8.588048E-01 3.105437E+02 + 2.010004E+01 6.000000E+01 6 1.413419E+02 -5.365128E-03 1.413419E+02 -1.323513E-02 + 2.010004E+01 9.000000E+01 1 3.546126E-06 -9.007532E+01 -4.661665E-09 -3.546123E-06 + 2.010004E+01 9.000000E+01 2 7.224520E+01 8.979951E+01 2.528028E-01 7.224476E+01 + 2.010004E+01 9.000000E+01 3 1.669528E+02 6.625724E-01 1.669416E+02 1.930611E+00 + 2.010004E+01 9.000000E+01 4 2.488997E+02 8.980087E+01 8.650754E-01 2.488982E+02 + 2.010004E+01 9.000000E+01 5 1.570815E-04 -8.996773E+01 8.848377E-08 -1.570815E-04 + 2.010004E+01 9.000000E+01 6 1.222509E-05 1.799964E+02 -1.222509E-05 7.626365E-10 + 2.020004E+01 0.000000E+00 1 6.569223E+01 8.984318E+01 1.798095E-01 6.569199E+01 + 2.020004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.020004E+01 0.000000E+00 3 1.613166E+02 6.435845E-01 1.613064E+02 1.811978E+00 + 2.020004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.020004E+01 0.000000E+00 5 6.045582E+02 8.984318E+01 1.654773E+00 6.045560E+02 + 2.020004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.020004E+01 3.000000E+01 1 5.735064E+01 8.984325E+01 1.569035E-01 5.735043E+01 + 2.020004E+01 3.000000E+01 2 3.498322E+01 8.980235E+01 1.206792E-01 3.498301E+01 + 2.020004E+01 3.000000E+01 3 1.628003E+02 6.465209E-01 1.627899E+02 1.836986E+00 + 2.020004E+01 3.000000E+01 4 1.179500E+02 8.979956E+01 4.126361E-01 1.179493E+02 + 2.020004E+01 3.000000E+01 5 5.278019E+02 8.984325E+01 1.443964E+00 5.278000E+02 + 2.020004E+01 3.000000E+01 6 1.372371E+02 -5.262219E-03 1.372371E+02 -1.260427E-02 + 2.020004E+01 6.000000E+01 1 3.364986E+01 8.984338E+01 9.197762E-02 3.364973E+01 + 2.020004E+01 6.000000E+01 2 6.168205E+01 8.980224E+01 2.128942E-01 6.168168E+01 + 2.020004E+01 6.000000E+01 3 1.658120E+02 6.524107E-01 1.658013E+02 1.888013E+00 + 2.020004E+01 6.000000E+01 4 2.108919E+02 8.980223E+01 7.279456E-01 2.108907E+02 + 2.020004E+01 6.000000E+01 5 3.096325E+02 8.984337E+01 8.464613E-01 3.096313E+02 + 2.020004E+01 6.000000E+01 6 1.397670E+02 -5.229436E-03 1.397670E+02 -1.275665E-02 + 2.020004E+01 9.000000E+01 1 3.527041E-06 -9.007518E+01 -4.628080E-09 -3.527038E-06 + 2.020004E+01 9.000000E+01 2 7.186182E+01 8.980219E+01 2.480940E-01 7.186139E+01 + 2.020004E+01 9.000000E+01 3 1.673397E+02 6.553698E-01 1.673287E+02 1.914050E+00 + 2.020004E+01 9.000000E+01 4 2.473715E+02 8.980352E+01 8.483040E-01 2.473701E+02 + 2.020004E+01 9.000000E+01 5 1.563432E-04 -8.996829E+01 8.653625E-08 -1.563432E-04 + 2.020004E+01 9.000000E+01 6 1.208725E-05 1.799965E+02 -1.208725E-05 7.351357E-10 + 2.030004E+01 0.000000E+00 1 6.537163E+01 8.984496E+01 1.768856E-01 6.537139E+01 + 2.030004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.030004E+01 0.000000E+00 3 1.617542E+02 6.367794E-01 1.617442E+02 1.797682E+00 + 2.030004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.030004E+01 0.000000E+00 5 6.029449E+02 8.984496E+01 1.631472E+00 6.029427E+02 + 2.030004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.030004E+01 3.000000E+01 1 5.706572E+01 8.984504E+01 1.543395E-01 5.706551E+01 + 2.030004E+01 3.000000E+01 2 3.480951E+01 8.980498E+01 1.184862E-01 3.480930E+01 + 2.030004E+01 3.000000E+01 3 1.632244E+02 6.396463E-01 1.632142E+02 1.822188E+00 + 2.030004E+01 3.000000E+01 4 1.172912E+02 8.980224E+01 4.048288E-01 1.172905E+02 + 2.030004E+01 3.000000E+01 5 5.263376E+02 8.984504E+01 1.423520E+00 5.263356E+02 + 2.030004E+01 3.000000E+01 6 1.357458E+02 -5.129692E-03 1.357458E+02 -1.215333E-02 + 2.030004E+01 6.000000E+01 1 3.347633E+01 8.984518E+01 9.046014E-02 3.347621E+01 + 2.030004E+01 6.000000E+01 2 6.136294E+01 8.980487E+01 2.089788E-01 6.136259E+01 + 2.030004E+01 6.000000E+01 3 1.662077E+02 6.453947E-01 1.661971E+02 1.872167E+00 + 2.030004E+01 6.000000E+01 4 2.096410E+02 8.980486E+01 7.140174E-01 2.096398E+02 + 2.030004E+01 6.000000E+01 5 3.087147E+02 8.984515E+01 8.343419E-01 3.087136E+02 + 2.030004E+01 6.000000E+01 6 1.382186E+02 -5.098135E-03 1.382186E+02 -1.229859E-02 + 2.030004E+01 9.000000E+01 1 3.508177E-06 -9.007504E+01 -4.593992E-09 -3.508174E-06 + 2.030004E+01 9.000000E+01 2 7.148273E+01 8.980482E+01 2.435053E-01 7.148232E+01 + 2.030004E+01 9.000000E+01 3 1.677212E+02 6.482777E-01 1.677105E+02 1.897655E+00 + 2.030004E+01 9.000000E+01 4 2.458635E+02 8.980611E+01 8.319848E-01 2.458621E+02 + 2.030004E+01 9.000000E+01 5 1.556109E-04 -8.996883E+01 8.464443E-08 -1.556108E-04 + 2.030004E+01 9.000000E+01 6 1.195181E-05 1.799966E+02 -1.195181E-05 7.088051E-10 + 2.040004E+01 0.000000E+00 1 6.505441E+01 8.984673E+01 1.740260E-01 6.505418E+01 + 2.040004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.040004E+01 0.000000E+00 3 1.621866E+02 6.300892E-01 1.621768E+02 1.783551E+00 + 2.040004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.040004E+01 0.000000E+00 5 6.013277E+02 8.984673E+01 1.608596E+00 6.013256E+02 + 2.040004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.040004E+01 3.000000E+01 1 5.678340E+01 8.984679E+01 1.518325E-01 5.678320E+01 + 2.040004E+01 3.000000E+01 2 3.463754E+01 8.980754E+01 1.163479E-01 3.463734E+01 + 2.040004E+01 3.000000E+01 3 1.636433E+02 6.328843E-01 1.636333E+02 1.807553E+00 + 2.040004E+01 3.000000E+01 4 1.166399E+02 8.980488E+01 3.972221E-01 1.166392E+02 + 2.040004E+01 3.000000E+01 5 5.248781E+02 8.984680E+01 1.403457E+00 5.248762E+02 + 2.040004E+01 3.000000E+01 6 1.342797E+02 -5.001434E-03 1.342797E+02 -1.172147E-02 + 2.040004E+01 6.000000E+01 1 3.330465E+01 8.984693E+01 8.897616E-02 3.330453E+01 + 2.040004E+01 6.000000E+01 2 6.104716E+01 8.980745E+01 2.051624E-01 6.104681E+01 + 2.040004E+01 6.000000E+01 3 1.665987E+02 6.384989E-01 1.665884E+02 1.856522E+00 + 2.040004E+01 6.000000E+01 4 2.084066E+02 8.980743E+01 7.004500E-01 2.084054E+02 + 2.040004E+01 6.000000E+01 5 3.078017E+02 8.984691E+01 8.224401E-01 3.078006E+02 + 2.040004E+01 6.000000E+01 6 1.366971E+02 -4.971014E-03 1.366971E+02 -1.185991E-02 + 2.040004E+01 9.000000E+01 1 3.489508E-06 -9.007486E+01 -4.559416E-09 -3.489505E-06 + 2.040004E+01 9.000000E+01 2 7.110738E+01 8.980740E+01 2.390324E-01 7.110697E+01 + 2.040004E+01 9.000000E+01 3 1.680971E+02 6.413115E-01 1.680865E+02 1.881471E+00 + 2.040004E+01 9.000000E+01 4 2.443733E+02 8.980866E+01 8.160858E-01 2.443720E+02 + 2.040004E+01 9.000000E+01 5 1.548858E-04 -8.996937E+01 8.280615E-08 -1.548858E-04 + 2.040004E+01 9.000000E+01 6 1.181870E-05 1.799967E+02 -1.181870E-05 6.835885E-10 + 2.050004E+01 0.000000E+00 1 6.474009E+01 8.984846E+01 1.712274E-01 6.473986E+01 + 2.050004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.050004E+01 0.000000E+00 3 1.626125E+02 6.234991E-01 1.626029E+02 1.769532E+00 + 2.050004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.050004E+01 0.000000E+00 5 5.997079E+02 8.984846E+01 1.586125E+00 5.997059E+02 + 2.050004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.050004E+01 3.000000E+01 1 5.650393E+01 8.984853E+01 1.493797E-01 5.650373E+01 + 2.050004E+01 3.000000E+01 2 3.446715E+01 8.981007E+01 1.142618E-01 3.446696E+01 + 2.050004E+01 3.000000E+01 3 1.640561E+02 6.262299E-01 1.640463E+02 1.793061E+00 + 2.050004E+01 3.000000E+01 4 1.159960E+02 8.980746E+01 3.898126E-01 1.159953E+02 + 2.050004E+01 3.000000E+01 5 5.234153E+02 8.984853E+01 1.383736E+00 5.234135E+02 + 2.050004E+01 3.000000E+01 6 1.328376E+02 -4.877278E-03 1.328376E+02 -1.130774E-02 + 2.050004E+01 6.000000E+01 1 3.313467E+01 8.984866E+01 8.752491E-02 3.313456E+01 + 2.050004E+01 6.000000E+01 2 6.073477E+01 8.980997E+01 2.014418E-01 6.073443E+01 + 2.050004E+01 6.000000E+01 3 1.669841E+02 6.317062E-01 1.669740E+02 1.841022E+00 + 2.050004E+01 6.000000E+01 4 2.071870E+02 8.980995E+01 6.872378E-01 2.071858E+02 + 2.050004E+01 6.000000E+01 5 3.068885E+02 8.984863E+01 8.107663E-01 3.068875E+02 + 2.050004E+01 6.000000E+01 6 1.352013E+02 -4.847961E-03 1.352013E+02 -1.143977E-02 + 2.050004E+01 9.000000E+01 1 3.471049E-06 -9.007468E+01 -4.524483E-09 -3.471046E-06 + 2.050004E+01 9.000000E+01 2 7.073632E+01 8.980992E+01 2.346719E-01 7.073593E+01 + 2.050004E+01 9.000000E+01 3 1.684690E+02 6.344550E-01 1.684587E+02 1.865475E+00 + 2.050004E+01 9.000000E+01 4 2.429040E+02 8.981116E+01 8.006036E-01 2.429027E+02 + 2.050004E+01 9.000000E+01 5 1.541678E-04 -8.996989E+01 8.102046E-08 -1.541678E-04 + 2.050004E+01 9.000000E+01 6 1.168791E-05 1.799968E+02 -1.168791E-05 6.594332E-10 + 2.060004E+01 0.000000E+00 1 6.442854E+01 8.985017E+01 1.684904E-01 6.442831E+01 + 2.060004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.060004E+01 0.000000E+00 3 1.630331E+02 6.170130E-01 1.630237E+02 1.755655E+00 + 2.060004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.060004E+01 0.000000E+00 5 5.980828E+02 8.985017E+01 1.564067E+00 5.980807E+02 + 2.060004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.060004E+01 3.000000E+01 1 5.622699E+01 8.985023E+01 1.469798E-01 5.622680E+01 + 2.060004E+01 3.000000E+01 2 3.429849E+01 8.981253E+01 1.122268E-01 3.429831E+01 + 2.060004E+01 3.000000E+01 3 1.644636E+02 6.196801E-01 1.644540E+02 1.778714E+00 + 2.060004E+01 3.000000E+01 4 1.153591E+02 8.980998E+01 3.825918E-01 1.153585E+02 + 2.060004E+01 3.000000E+01 5 5.219458E+02 8.985023E+01 1.364384E+00 5.219440E+02 + 2.060004E+01 3.000000E+01 6 1.314194E+02 -4.757043E-03 1.314194E+02 -1.091124E-02 + 2.060004E+01 6.000000E+01 1 3.296656E+01 8.985035E+01 8.610546E-02 3.296645E+01 + 2.060004E+01 6.000000E+01 2 6.042552E+01 8.981243E+01 1.978129E-01 6.042519E+01 + 2.060004E+01 6.000000E+01 3 1.673642E+02 6.250291E-01 1.673542E+02 1.825709E+00 + 2.060004E+01 6.000000E+01 4 2.059819E+02 8.981242E+01 6.743651E-01 2.059808E+02 + 2.060004E+01 6.000000E+01 5 3.059727E+02 8.985033E+01 7.992912E-01 3.059717E+02 + 2.060004E+01 6.000000E+01 6 1.337309E+02 -4.728779E-03 1.337309E+02 -1.103718E-02 + 2.060004E+01 9.000000E+01 1 3.452798E-06 -9.007449E+01 -4.489176E-09 -3.452795E-06 + 2.060004E+01 9.000000E+01 2 7.036932E+01 8.981239E+01 2.304207E-01 7.036894E+01 + 2.060004E+01 9.000000E+01 3 1.688353E+02 6.277081E-01 1.688251E+02 1.849650E+00 + 2.060004E+01 9.000000E+01 4 2.414518E+02 8.981360E+01 7.855271E-01 2.414505E+02 + 2.060004E+01 9.000000E+01 5 1.534564E-04 -8.997040E+01 7.928448E-08 -1.534564E-04 + 2.060004E+01 9.000000E+01 6 1.155933E-05 1.799969E+02 -1.155933E-05 6.362832E-10 + 2.070004E+01 0.000000E+00 1 6.412022E+01 8.985184E+01 1.658124E-01 6.412000E+01 + 2.070004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.070004E+01 0.000000E+00 3 1.634482E+02 6.106256E-01 1.634389E+02 1.741905E+00 + 2.070004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.070004E+01 0.000000E+00 5 5.964514E+02 8.985184E+01 1.542398E+00 5.964493E+02 + 2.070004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.070004E+01 3.000000E+01 1 5.595306E+01 8.985190E+01 1.446317E-01 5.595288E+01 + 2.070004E+01 3.000000E+01 2 3.413142E+01 8.981494E+01 1.102414E-01 3.413124E+01 + 2.070004E+01 3.000000E+01 3 1.648655E+02 6.132323E-01 1.648561E+02 1.764509E+00 + 2.070004E+01 3.000000E+01 4 1.147300E+02 8.981245E+01 3.755530E-01 1.147294E+02 + 2.070004E+01 3.000000E+01 5 5.204780E+02 8.985190E+01 1.345384E+00 5.204763E+02 + 2.070004E+01 3.000000E+01 6 1.300244E+02 -4.640601E-03 1.300244E+02 -1.053116E-02 + 2.070004E+01 6.000000E+01 1 3.280011E+01 8.985201E+01 8.471688E-02 3.280000E+01 + 2.070004E+01 6.000000E+01 2 6.011945E+01 8.981485E+01 1.942734E-01 6.011913E+01 + 2.070004E+01 6.000000E+01 3 1.677389E+02 6.184556E-01 1.677292E+02 1.810553E+00 + 2.070004E+01 6.000000E+01 4 2.047917E+02 8.981483E+01 6.618194E-01 2.047907E+02 + 2.070004E+01 6.000000E+01 5 3.050566E+02 8.985199E+01 7.880349E-01 3.050556E+02 + 2.070004E+01 6.000000E+01 6 1.322850E+02 -4.613339E-03 1.322850E+02 -1.065131E-02 + 2.070004E+01 9.000000E+01 1 3.434739E-06 -9.007429E+01 -4.453538E-09 -3.434736E-06 + 2.070004E+01 9.000000E+01 2 7.000589E+01 8.981481E+01 2.262746E-01 7.000552E+01 + 2.070004E+01 9.000000E+01 3 1.691965E+02 6.210708E-01 1.691866E+02 1.834009E+00 + 2.070004E+01 9.000000E+01 4 2.400188E+02 8.981599E+01 7.708381E-01 2.400176E+02 + 2.070004E+01 9.000000E+01 5 1.527502E-04 -8.997089E+01 7.759730E-08 -1.527502E-04 + 2.070004E+01 9.000000E+01 6 1.143296E-05 1.799969E+02 -1.143296E-05 6.140952E-10 + 2.080004E+01 0.000000E+00 1 6.381456E+01 8.985349E+01 1.631899E-01 6.381435E+01 + 2.080004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.080004E+01 0.000000E+00 3 1.638572E+02 6.043389E-01 1.638481E+02 1.728285E+00 + 2.080004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.080004E+01 0.000000E+00 5 5.948220E+02 8.985349E+01 1.521102E+00 5.948200E+02 + 2.080004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.080004E+01 3.000000E+01 1 5.568153E+01 8.985354E+01 1.423347E-01 5.568134E+01 + 2.080004E+01 3.000000E+01 2 3.396597E+01 8.981731E+01 1.083039E-01 3.396580E+01 + 2.080004E+01 3.000000E+01 3 1.652620E+02 6.068804E-01 1.652527E+02 1.750433E+00 + 2.080004E+01 3.000000E+01 4 1.141076E+02 8.981487E+01 3.686909E-01 1.141070E+02 + 2.080004E+01 3.000000E+01 5 5.190084E+02 8.985354E+01 1.326702E+00 5.190067E+02 + 2.080004E+01 3.000000E+01 6 1.286520E+02 -4.527792E-03 1.286520E+02 -1.016671E-02 + 2.080004E+01 6.000000E+01 1 3.263537E+01 8.985365E+01 8.335859E-02 3.263527E+01 + 2.080004E+01 6.000000E+01 2 5.981660E+01 8.981722E+01 1.908207E-01 5.981630E+01 + 2.080004E+01 6.000000E+01 3 1.681095E+02 6.119814E-01 1.680999E+02 1.795558E+00 + 2.080004E+01 6.000000E+01 4 2.036151E+02 8.981721E+01 6.495958E-01 2.036141E+02 + 2.080004E+01 6.000000E+01 5 3.041458E+02 8.985363E+01 7.769811E-01 3.041448E+02 + 2.080004E+01 6.000000E+01 6 1.308632E+02 -4.501495E-03 1.308632E+02 -1.028139E-02 + 2.080004E+01 9.000000E+01 1 3.416880E-06 -9.007407E+01 -4.417677E-09 -3.416877E-06 + 2.080004E+01 9.000000E+01 2 6.964664E+01 8.981718E+01 2.222306E-01 6.964629E+01 + 2.080004E+01 9.000000E+01 3 1.695526E+02 6.145399E-01 1.695428E+02 1.818543E+00 + 2.080004E+01 9.000000E+01 4 2.386036E+02 8.981834E+01 7.565217E-01 2.386024E+02 + 2.080004E+01 9.000000E+01 5 1.520502E-04 -8.997137E+01 7.595667E-08 -1.520501E-04 + 2.080004E+01 9.000000E+01 6 1.130872E-05 1.799970E+02 -1.130872E-05 5.928200E-10 + 2.090004E+01 0.000000E+00 1 6.351139E+01 8.985509E+01 1.606237E-01 6.351119E+01 + 2.090004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.090004E+01 0.000000E+00 3 1.642611E+02 5.981480E-01 1.642521E+02 1.714797E+00 + 2.090004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.090004E+01 0.000000E+00 5 5.931834E+02 8.985510E+01 1.500171E+00 5.931815E+02 + 2.090004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.090004E+01 3.000000E+01 1 5.541267E+01 8.985516E+01 1.400858E-01 5.541249E+01 + 2.090004E+01 3.000000E+01 2 3.380206E+01 8.981963E+01 1.064127E-01 3.380189E+01 + 2.090004E+01 3.000000E+01 3 1.656524E+02 6.006361E-01 1.656433E+02 1.736515E+00 + 2.090004E+01 3.000000E+01 4 1.134919E+02 8.981725E+01 3.619986E-01 1.134913E+02 + 2.090004E+01 3.000000E+01 5 5.175372E+02 8.985516E+01 1.308356E+00 5.175355E+02 + 2.090004E+01 3.000000E+01 6 1.273019E+02 -4.418476E-03 1.273019E+02 -9.817134E-03 + 2.090004E+01 6.000000E+01 1 3.247225E+01 8.985526E+01 8.202945E-02 3.247215E+01 + 2.090004E+01 6.000000E+01 2 5.951677E+01 8.981954E+01 1.874512E-01 5.951647E+01 + 2.090004E+01 6.000000E+01 3 1.684745E+02 6.056167E-01 1.684651E+02 1.780743E+00 + 2.090004E+01 6.000000E+01 4 2.024531E+02 8.981953E+01 6.376822E-01 2.024521E+02 + 2.090004E+01 6.000000E+01 5 3.032299E+02 8.985524E+01 7.661338E-01 3.032289E+02 + 2.090004E+01 6.000000E+01 6 1.294651E+02 -4.393109E-03 1.294651E+02 -9.926637E-03 + 2.090004E+01 9.000000E+01 1 3.399201E-06 -9.007386E+01 -4.381584E-09 -3.399198E-06 + 2.090004E+01 9.000000E+01 2 6.929110E+01 8.981950E+01 2.182860E-01 6.929076E+01 + 2.090004E+01 9.000000E+01 3 1.699045E+02 6.081139E-01 1.698949E+02 1.803263E+00 + 2.090004E+01 9.000000E+01 4 2.372046E+02 8.982063E+01 7.425726E-01 2.372035E+02 + 2.090004E+01 9.000000E+01 5 1.513574E-04 -8.997185E+01 7.436127E-08 -1.513574E-04 + 2.090004E+01 9.000000E+01 6 1.118656E-05 1.799971E+02 -1.118656E-05 5.724159E-10 + 2.100004E+01 0.000000E+00 1 6.321159E+01 8.985669E+01 1.581123E-01 6.321140E+01 + 2.100004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.100004E+01 0.000000E+00 3 1.646583E+02 5.920571E-01 1.646495E+02 1.701441E+00 + 2.100004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.100004E+01 0.000000E+00 5 5.915450E+02 8.985669E+01 1.479630E+00 5.915432E+02 + 2.100004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.100004E+01 3.000000E+01 1 5.514629E+01 8.985674E+01 1.378856E-01 5.514612E+01 + 2.100004E+01 3.000000E+01 2 3.363964E+01 8.982190E+01 1.045666E-01 3.363948E+01 + 2.100004E+01 3.000000E+01 3 1.660384E+02 5.944797E-01 1.660295E+02 1.722722E+00 + 2.100004E+01 3.000000E+01 4 1.128829E+02 8.981958E+01 3.554713E-01 1.128823E+02 + 2.100004E+01 3.000000E+01 5 5.160685E+02 8.985674E+01 1.290331E+00 5.160669E+02 + 2.100004E+01 3.000000E+01 6 1.259733E+02 -4.312538E-03 1.259733E+02 -9.481760E-03 + 2.100004E+01 6.000000E+01 1 3.231078E+01 8.985685E+01 8.072911E-02 3.231068E+01 + 2.100004E+01 6.000000E+01 2 5.922005E+01 8.982182E+01 1.841640E-01 5.921976E+01 + 2.100004E+01 6.000000E+01 3 1.688344E+02 5.993465E-01 1.688251E+02 1.766071E+00 + 2.100004E+01 6.000000E+01 4 2.013048E+02 8.982181E+01 6.260641E-01 2.013038E+02 + 2.100004E+01 6.000000E+01 5 3.023165E+02 8.985682E+01 7.554740E-01 3.023156E+02 + 2.100004E+01 6.000000E+01 6 1.280900E+02 -4.288050E-03 1.280900E+02 -9.586333E-03 + 2.100004E+01 9.000000E+01 1 3.381708E-06 -9.007362E+01 -4.345329E-09 -3.381705E-06 + 2.100004E+01 9.000000E+01 2 6.893932E+01 8.982178E+01 2.144361E-01 6.893898E+01 + 2.100004E+01 9.000000E+01 3 1.702522E+02 6.017843E-01 1.702428E+02 1.788146E+00 + 2.100004E+01 9.000000E+01 4 2.358240E+02 8.982289E+01 7.289737E-01 2.358228E+02 + 2.100004E+01 9.000000E+01 5 1.506705E-04 -8.997231E+01 7.281010E-08 -1.506704E-04 + 2.100004E+01 9.000000E+01 6 1.106645E-05 1.799971E+02 -1.106645E-05 5.528405E-10 + 2.110004E+01 0.000000E+00 1 6.291412E+01 8.985825E+01 1.556526E-01 6.291393E+01 + 2.110004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.110004E+01 0.000000E+00 3 1.650519E+02 5.860521E-01 1.650433E+02 1.688211E+00 + 2.110004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.110004E+01 0.000000E+00 5 5.899127E+02 8.985825E+01 1.459441E+00 5.899108E+02 + 2.110004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.110004E+01 3.000000E+01 1 5.488240E+01 8.985831E+01 1.357310E-01 5.488223E+01 + 2.110004E+01 3.000000E+01 2 3.347894E+01 8.982413E+01 1.027637E-01 3.347878E+01 + 2.110004E+01 3.000000E+01 3 1.664191E+02 5.884231E-01 1.664103E+02 1.709080E+00 + 2.110004E+01 3.000000E+01 4 1.122806E+02 8.982185E+01 3.491066E-01 1.122801E+02 + 2.110004E+01 3.000000E+01 5 5.145932E+02 8.985831E+01 1.272644E+00 5.145916E+02 + 2.110004E+01 3.000000E+01 6 1.246663E+02 -4.209812E-03 1.246663E+02 -9.159866E-03 + 2.110004E+01 6.000000E+01 1 3.215103E+01 8.985840E+01 7.945626E-02 3.215093E+01 + 2.110004E+01 6.000000E+01 2 5.892637E+01 8.982405E+01 1.809549E-01 5.892609E+01 + 2.110004E+01 6.000000E+01 3 1.691900E+02 5.931741E-01 1.691809E+02 1.751566E+00 + 2.110004E+01 6.000000E+01 4 2.001701E+02 8.982404E+01 6.147355E-01 2.001692E+02 + 2.110004E+01 6.000000E+01 5 3.014066E+02 8.985838E+01 7.450023E-01 3.014057E+02 + 2.110004E+01 6.000000E+01 6 1.267374E+02 -4.186208E-03 1.267374E+02 -9.259829E-03 + 2.110004E+01 9.000000E+01 1 3.364417E-06 -9.007338E+01 -4.308923E-09 -3.364414E-06 + 2.110004E+01 9.000000E+01 2 6.859097E+01 8.982402E+01 2.106795E-01 6.859065E+01 + 2.110004E+01 9.000000E+01 3 1.705944E+02 5.955566E-01 1.705852E+02 1.773198E+00 + 2.110004E+01 9.000000E+01 4 2.344595E+02 8.982510E+01 7.157160E-01 2.344584E+02 + 2.110004E+01 9.000000E+01 5 1.499893E-04 -8.997276E+01 7.130098E-08 -1.499893E-04 + 2.110004E+01 9.000000E+01 6 1.094833E-05 1.799972E+02 -1.094833E-05 5.340559E-10 + 2.120004E+01 0.000000E+00 1 6.261952E+01 8.985979E+01 1.532447E-01 6.261933E+01 + 2.120004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.120004E+01 0.000000E+00 3 1.654395E+02 5.801370E-01 1.654310E+02 1.675096E+00 + 2.120004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.120004E+01 0.000000E+00 5 5.882706E+02 8.985979E+01 1.439604E+00 5.882689E+02 + 2.120004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.120004E+01 3.000000E+01 1 5.462117E+01 8.985983E+01 1.336218E-01 5.462101E+01 + 2.120004E+01 3.000000E+01 2 3.331966E+01 8.982632E+01 1.010039E-01 3.331951E+01 + 2.120004E+01 3.000000E+01 3 1.667948E+02 5.824519E-01 1.667862E+02 1.695557E+00 + 2.120004E+01 3.000000E+01 4 1.116853E+02 8.982409E+01 3.428971E-01 1.116847E+02 + 2.120004E+01 3.000000E+01 5 5.131204E+02 8.985983E+01 1.255259E+00 5.131188E+02 + 2.120004E+01 3.000000E+01 6 1.233801E+02 -4.110220E-03 1.233801E+02 -8.850900E-03 + 2.120004E+01 6.000000E+01 1 3.199291E+01 8.985994E+01 7.821047E-02 3.199281E+01 + 2.120004E+01 6.000000E+01 2 5.863548E+01 8.982624E+01 1.778218E-01 5.863521E+01 + 2.120004E+01 6.000000E+01 3 1.695406E+02 5.871015E-01 1.695318E+02 1.737228E+00 + 2.120004E+01 6.000000E+01 4 1.990490E+02 8.982623E+01 6.036870E-01 1.990481E+02 + 2.120004E+01 6.000000E+01 5 3.004943E+02 8.985991E+01 7.347198E-01 3.004934E+02 + 2.120004E+01 6.000000E+01 6 1.254070E+02 -4.087419E-03 1.254070E+02 -8.946401E-03 + 2.120004E+01 9.000000E+01 1 3.347297E-06 -9.007314E+01 -4.272425E-09 -3.347295E-06 + 2.120004E+01 9.000000E+01 2 6.824651E+01 8.982620E+01 2.070131E-01 6.824620E+01 + 2.120004E+01 9.000000E+01 3 1.709321E+02 5.894273E-01 1.709230E+02 1.758423E+00 + 2.120004E+01 9.000000E+01 4 2.331120E+02 8.982727E+01 7.027883E-01 2.331109E+02 + 2.120004E+01 9.000000E+01 5 1.493142E-04 -8.997321E+01 6.983249E-08 -1.493142E-04 + 2.120004E+01 9.000000E+01 6 1.083215E-05 1.799973E+02 -1.083215E-05 5.160244E-10 + 2.130005E+01 0.000000E+00 1 6.232783E+01 8.986130E+01 1.508870E-01 6.232764E+01 + 2.130005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.130005E+01 0.000000E+00 3 1.658223E+02 5.743163E-01 1.658140E+02 1.662127E+00 + 2.130005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.130005E+01 0.000000E+00 5 5.866271E+02 8.986130E+01 1.420107E+00 5.866254E+02 + 2.130005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.130005E+01 3.000000E+01 1 5.436221E+01 8.986134E+01 1.315567E-01 5.436205E+01 + 2.130005E+01 3.000000E+01 2 3.316186E+01 8.982846E+01 9.928485E-02 3.316171E+01 + 2.130005E+01 3.000000E+01 3 1.671654E+02 5.765816E-01 1.671569E+02 1.682198E+00 + 2.130005E+01 3.000000E+01 4 1.110960E+02 8.982629E+01 3.368384E-01 1.110955E+02 + 2.130005E+01 3.000000E+01 5 5.116482E+02 8.986134E+01 1.238179E+00 5.116467E+02 + 2.130005E+01 3.000000E+01 6 1.221137E+02 -4.013660E-03 1.221137E+02 -8.554257E-03 + 2.130005E+01 6.000000E+01 1 3.183622E+01 8.986144E+01 7.699062E-02 3.183612E+01 + 2.130005E+01 6.000000E+01 2 5.834761E+01 8.982839E+01 1.747638E-01 5.834734E+01 + 2.130005E+01 6.000000E+01 3 1.698870E+02 5.811199E-01 1.698782E+02 1.723041E+00 + 2.130005E+01 6.000000E+01 4 1.979413E+02 8.982838E+01 5.929118E-01 1.979405E+02 + 2.130005E+01 6.000000E+01 5 2.995831E+02 8.986142E+01 7.246204E-01 2.995822E+02 + 2.130005E+01 6.000000E+01 6 1.240979E+02 -3.991625E-03 1.240979E+02 -8.645531E-03 + 2.130005E+01 9.000000E+01 1 3.330355E-06 -9.007288E+01 -4.235849E-09 -3.330353E-06 + 2.130005E+01 9.000000E+01 2 6.790550E+01 8.982835E+01 2.034333E-01 6.790520E+01 + 2.130005E+01 9.000000E+01 3 1.712655E+02 5.833960E-01 1.712566E+02 1.743826E+00 + 2.130005E+01 9.000000E+01 4 2.317809E+02 8.982939E+01 6.901794E-01 2.317798E+02 + 2.130005E+01 9.000000E+01 5 1.486448E-04 -8.997363E+01 6.840413E-08 -1.486447E-04 + 2.130005E+01 9.000000E+01 6 1.071788E-05 1.799973E+02 -1.071788E-05 4.987119E-10 + 2.140005E+01 0.000000E+00 1 6.203843E+01 8.986279E+01 1.485775E-01 6.203825E+01 + 2.140005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.140005E+01 0.000000E+00 3 1.662000E+02 5.685813E-01 1.661918E+02 1.649278E+00 + 2.140005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.140005E+01 0.000000E+00 5 5.849853E+02 8.986279E+01 1.400969E+00 5.849836E+02 + 2.140005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.140005E+01 3.000000E+01 1 5.410566E+01 8.986282E+01 1.295345E-01 5.410550E+01 + 2.140005E+01 3.000000E+01 2 3.300554E+01 8.983056E+01 9.760576E-02 3.300539E+01 + 2.140005E+01 3.000000E+01 3 1.675312E+02 5.707949E-01 1.675228E+02 1.668960E+00 + 2.140005E+01 3.000000E+01 4 1.105131E+02 8.982843E+01 3.309246E-01 1.105126E+02 + 2.140005E+01 3.000000E+01 5 5.101770E+02 8.986283E+01 1.221408E+00 5.101755E+02 + 2.140005E+01 3.000000E+01 6 1.208675E+02 -3.919979E-03 1.208675E+02 -8.269336E-03 + 2.140005E+01 6.000000E+01 1 3.168116E+01 8.986292E+01 7.579711E-02 3.168107E+01 + 2.140005E+01 6.000000E+01 2 5.806268E+01 8.983049E+01 1.717770E-01 5.806242E+01 + 2.140005E+01 6.000000E+01 3 1.702287E+02 5.752325E-01 1.702201E+02 1.709016E+00 + 2.140005E+01 6.000000E+01 4 1.968455E+02 8.983048E+01 5.823973E-01 1.968446E+02 + 2.140005E+01 6.000000E+01 5 2.986749E+02 8.986290E+01 7.146987E-01 2.986740E+02 + 2.140005E+01 6.000000E+01 6 1.228098E+02 -3.898692E-03 1.228098E+02 -8.356597E-03 + 2.140005E+01 9.000000E+01 1 3.313598E-06 -9.007261E+01 -4.199223E-09 -3.313595E-06 + 2.140005E+01 9.000000E+01 2 6.756801E+01 8.983046E+01 1.999397E-01 6.756771E+01 + 2.140005E+01 9.000000E+01 3 1.715948E+02 5.774541E-01 1.715860E+02 1.729384E+00 + 2.140005E+01 9.000000E+01 4 2.304656E+02 8.983147E+01 6.778837E-01 2.304646E+02 + 2.140005E+01 9.000000E+01 5 1.479810E-04 -8.997405E+01 6.701373E-08 -1.479809E-04 + 2.140005E+01 9.000000E+01 6 1.060548E-05 1.799974E+02 -1.060548E-05 4.820866E-10 + 2.150005E+01 0.000000E+00 1 6.175196E+01 8.986425E+01 1.463160E-01 6.175179E+01 + 2.150005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.150005E+01 0.000000E+00 3 1.665725E+02 5.629305E-01 1.665645E+02 1.636547E+00 + 2.150005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.150005E+01 0.000000E+00 5 5.833430E+02 8.986425E+01 1.382147E+00 5.833413E+02 + 2.150005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.150005E+01 3.000000E+01 1 5.385172E+01 8.986429E+01 1.275541E-01 5.385157E+01 + 2.150005E+01 3.000000E+01 2 3.285075E+01 8.983263E+01 9.596533E-02 3.285061E+01 + 2.150005E+01 3.000000E+01 3 1.678927E+02 5.650940E-01 1.678846E+02 1.655857E+00 + 2.150005E+01 3.000000E+01 4 1.099366E+02 8.983054E+01 3.251544E-01 1.099361E+02 + 2.150005E+01 3.000000E+01 5 5.087033E+02 8.986429E+01 1.204916E+00 5.087019E+02 + 2.150005E+01 3.000000E+01 6 1.196407E+02 -3.829093E-03 1.196407E+02 -7.995619E-03 + 2.150005E+01 6.000000E+01 1 3.152754E+01 8.986438E+01 7.462784E-02 3.152746E+01 + 2.150005E+01 6.000000E+01 2 5.778044E+01 8.983256E+01 1.688604E-01 5.778019E+01 + 2.150005E+01 6.000000E+01 3 1.705653E+02 5.694318E-01 1.705569E+02 1.695129E+00 + 2.150005E+01 6.000000E+01 4 1.957619E+02 8.983255E+01 5.721402E-01 1.957611E+02 + 2.150005E+01 6.000000E+01 5 2.977689E+02 8.986436E+01 7.049621E-01 2.977680E+02 + 2.150005E+01 6.000000E+01 6 1.215423E+02 -3.808532E-03 1.215423E+02 -8.079089E-03 + 2.150005E+01 9.000000E+01 1 3.297014E-06 -9.007234E+01 -4.162584E-09 -3.297011E-06 + 2.150005E+01 9.000000E+01 2 6.723403E+01 8.983252E+01 1.965273E-01 6.723374E+01 + 2.150005E+01 9.000000E+01 3 1.719196E+02 5.716041E-01 1.719111E+02 1.715106E+00 + 2.150005E+01 9.000000E+01 4 2.291658E+02 8.983352E+01 6.658836E-01 2.291648E+02 + 2.150005E+01 9.000000E+01 5 1.473238E-04 -8.997446E+01 6.566022E-08 -1.473238E-04 + 2.150005E+01 9.000000E+01 6 1.049490E-05 1.799975E+02 -1.049490E-05 4.661145E-10 + 2.160005E+01 0.000000E+00 1 6.146769E+01 8.986568E+01 1.441004E-01 6.146752E+01 + 2.160005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.160005E+01 0.000000E+00 3 1.669404E+02 5.573655E-01 1.669325E+02 1.623948E+00 + 2.160005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.160005E+01 0.000000E+00 5 5.816965E+02 8.986568E+01 1.363655E+00 5.816949E+02 + 2.160005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.160005E+01 3.000000E+01 1 5.359994E+01 8.986572E+01 1.256144E-01 5.359979E+01 + 2.160005E+01 3.000000E+01 2 3.269737E+01 8.983465E+01 9.436276E-02 3.269723E+01 + 2.160005E+01 3.000000E+01 3 1.682483E+02 5.594834E-01 1.682403E+02 1.642890E+00 + 2.160005E+01 3.000000E+01 4 1.093665E+02 8.983261E+01 3.195192E-01 1.093660E+02 + 2.160005E+01 3.000000E+01 5 5.072311E+02 8.986572E+01 1.188723E+00 5.072297E+02 + 2.160005E+01 3.000000E+01 6 1.184330E+02 -3.740890E-03 1.184330E+02 -7.732589E-03 + 2.160005E+01 6.000000E+01 1 3.137555E+01 8.986581E+01 7.348310E-02 3.137546E+01 + 2.160005E+01 6.000000E+01 2 5.750114E+01 8.983458E+01 1.660112E-01 5.750090E+01 + 2.160005E+01 6.000000E+01 3 1.708976E+02 5.637235E-01 1.708893E+02 1.681405E+00 + 2.160005E+01 6.000000E+01 4 1.946926E+02 8.983457E+01 5.621283E-01 1.946917E+02 + 2.160005E+01 6.000000E+01 5 2.968618E+02 8.986579E+01 6.953874E-01 2.968609E+02 + 2.160005E+01 6.000000E+01 6 1.202948E+02 -3.721021E-03 1.202948E+02 -7.812435E-03 + 2.160005E+01 9.000000E+01 1 3.280595E-06 -9.007206E+01 -4.125944E-09 -3.280593E-06 + 2.160005E+01 9.000000E+01 2 6.690331E+01 8.983455E+01 1.931945E-01 6.690302E+01 + 2.160005E+01 9.000000E+01 3 1.722387E+02 5.658488E-01 1.722303E+02 1.700989E+00 + 2.160005E+01 9.000000E+01 4 2.278819E+02 8.983553E+01 6.541724E-01 2.278809E+02 + 2.160005E+01 9.000000E+01 5 1.466718E-04 -8.997487E+01 6.434252E-08 -1.466718E-04 + 2.160005E+01 9.000000E+01 6 1.038609E-05 1.799975E+02 -1.038609E-05 4.507669E-10 + 2.170005E+01 0.000000E+00 1 6.118621E+01 8.986710E+01 1.419300E-01 6.118605E+01 + 2.170005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.170005E+01 0.000000E+00 3 1.673034E+02 5.518878E-01 1.672957E+02 1.611485E+00 + 2.170005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.170005E+01 0.000000E+00 5 5.800552E+02 8.986710E+01 1.345487E+00 5.800536E+02 + 2.170005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.170005E+01 3.000000E+01 1 5.335066E+01 8.986713E+01 1.237141E-01 5.335051E+01 + 2.170005E+01 3.000000E+01 2 3.254532E+01 8.983663E+01 9.279647E-02 3.254519E+01 + 2.170005E+01 3.000000E+01 3 1.686000E+02 5.539546E-01 1.685921E+02 1.630056E+00 + 2.170005E+01 3.000000E+01 4 1.088019E+02 8.983464E+01 3.140184E-01 1.088015E+02 + 2.170005E+01 3.000000E+01 5 5.057626E+02 8.986714E+01 1.172791E+00 5.057612E+02 + 2.170005E+01 3.000000E+01 6 1.172439E+02 -3.655281E-03 1.172439E+02 -7.479773E-03 + 2.170005E+01 6.000000E+01 1 3.122495E+01 8.986722E+01 7.236214E-02 3.122487E+01 + 2.170005E+01 6.000000E+01 2 5.722442E+01 8.983657E+01 1.632275E-01 5.722419E+01 + 2.170005E+01 6.000000E+01 3 1.712260E+02 5.581045E-01 1.712178E+02 1.667845E+00 + 2.170005E+01 6.000000E+01 4 1.936340E+02 8.983656E+01 5.523558E-01 1.936332E+02 + 2.170005E+01 6.000000E+01 5 2.959577E+02 8.986720E+01 6.859781E-01 2.959569E+02 + 2.170005E+01 6.000000E+01 6 1.190674E+02 -3.636078E-03 1.190674E+02 -7.556202E-03 + 2.170005E+01 9.000000E+01 1 3.264335E-06 -9.007178E+01 -4.089379E-09 -3.264332E-06 + 2.170005E+01 9.000000E+01 2 6.657600E+01 8.983654E+01 1.899386E-01 6.657572E+01 + 2.170005E+01 9.000000E+01 3 1.725552E+02 5.601832E-01 1.725470E+02 1.687053E+00 + 2.170005E+01 9.000000E+01 4 2.266125E+02 8.983749E+01 6.427448E-01 2.266116E+02 + 2.170005E+01 9.000000E+01 5 1.460258E-04 -8.997526E+01 6.305931E-08 -1.460258E-04 + 2.170005E+01 9.000000E+01 6 1.027902E-05 1.799976E+02 -1.027902E-05 4.360170E-10 + 2.180005E+01 0.000000E+00 1 6.090726E+01 8.986848E+01 1.398032E-01 6.090710E+01 + 2.180005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.180005E+01 0.000000E+00 3 1.676612E+02 5.464816E-01 1.676535E+02 1.599112E+00 + 2.180005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.180005E+01 0.000000E+00 5 5.784138E+02 8.986848E+01 1.327620E+00 5.784122E+02 + 2.180005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.180005E+01 3.000000E+01 1 5.310334E+01 8.986853E+01 1.218527E-01 5.310320E+01 + 2.180005E+01 3.000000E+01 2 3.239473E+01 8.983858E+01 9.126551E-02 3.239460E+01 + 2.180005E+01 3.000000E+01 3 1.689474E+02 5.485032E-01 1.689396E+02 1.617340E+00 + 2.180005E+01 3.000000E+01 4 1.082436E+02 8.983662E+01 3.086476E-01 1.082431E+02 + 2.180005E+01 3.000000E+01 5 5.042939E+02 8.986853E+01 1.157151E+00 5.042926E+02 + 2.180005E+01 3.000000E+01 6 1.160730E+02 -3.572175E-03 1.160730E+02 -7.236714E-03 + 2.180005E+01 6.000000E+01 1 3.107590E+01 8.986861E+01 7.126382E-02 3.107582E+01 + 2.180005E+01 6.000000E+01 2 5.695058E+01 8.983852E+01 1.605081E-01 5.695035E+01 + 2.180005E+01 6.000000E+01 3 1.715500E+02 5.525618E-01 1.715420E+02 1.654407E+00 + 2.180005E+01 6.000000E+01 4 1.925879E+02 8.983851E+01 5.428147E-01 1.925871E+02 + 2.180005E+01 6.000000E+01 5 2.950564E+02 8.986858E+01 6.767493E-01 2.950557E+02 + 2.180005E+01 6.000000E+01 6 1.178590E+02 -3.553607E-03 1.178590E+02 -7.309865E-03 + 2.180005E+01 9.000000E+01 1 3.248258E-06 -9.007149E+01 -4.052839E-09 -3.248256E-06 + 2.180005E+01 9.000000E+01 2 6.625190E+01 8.983849E+01 1.867585E-01 6.625163E+01 + 2.180005E+01 9.000000E+01 3 1.728678E+02 5.545917E-01 1.728596E+02 1.673239E+00 + 2.180005E+01 9.000000E+01 4 2.253576E+02 8.983942E+01 6.315912E-01 2.253568E+02 + 2.180005E+01 9.000000E+01 5 1.453838E-04 -8.997564E+01 6.181024E-08 -1.453838E-04 + 2.180005E+01 9.000000E+01 6 1.017367E-05 1.799976E+02 -1.017367E-05 4.218362E-10 + 2.190005E+01 0.000000E+00 1 6.063079E+01 8.986986E+01 1.377197E-01 6.063063E+01 + 2.190005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.190005E+01 0.000000E+00 3 1.680152E+02 5.411572E-01 1.680077E+02 1.586875E+00 + 2.190005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.190005E+01 0.000000E+00 5 5.767661E+02 8.986986E+01 1.310061E+00 5.767646E+02 + 2.190005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.190005E+01 3.000000E+01 1 5.285872E+01 8.986990E+01 1.200289E-01 5.285858E+01 + 2.190005E+01 3.000000E+01 2 3.224557E+01 8.984049E+01 8.976915E-02 3.224544E+01 + 2.190005E+01 3.000000E+01 3 1.692900E+02 5.431344E-01 1.692824E+02 1.604757E+00 + 2.190005E+01 3.000000E+01 4 1.076909E+02 8.983858E+01 3.034011E-01 1.076905E+02 + 2.190005E+01 3.000000E+01 5 5.028245E+02 8.986990E+01 1.141775E+00 5.028232E+02 + 2.190005E+01 3.000000E+01 6 1.149203E+02 -3.491472E-03 1.149203E+02 -7.002978E-03 + 2.190005E+01 6.000000E+01 1 3.092817E+01 8.986998E+01 7.018826E-02 3.092809E+01 + 2.190005E+01 6.000000E+01 2 5.667926E+01 8.984044E+01 1.578502E-01 5.667904E+01 + 2.190005E+01 6.000000E+01 3 1.718700E+02 5.471047E-01 1.718622E+02 1.641123E+00 + 2.190005E+01 6.000000E+01 4 1.915538E+02 8.984042E+01 5.335016E-01 1.915531E+02 + 2.190005E+01 6.000000E+01 5 2.941549E+02 8.986995E+01 6.676727E-01 2.941541E+02 + 2.190005E+01 6.000000E+01 6 1.166695E+02 -3.473520E-03 1.166695E+02 -7.073014E-03 + 2.190005E+01 9.000000E+01 1 3.232331E-06 -9.007120E+01 -4.016376E-09 -3.232328E-06 + 2.190005E+01 9.000000E+01 2 6.593121E+01 8.984040E+01 1.836506E-01 6.593095E+01 + 2.190005E+01 9.000000E+01 3 1.731751E+02 5.490936E-01 1.731672E+02 1.659597E+00 + 2.190005E+01 9.000000E+01 4 2.241180E+02 8.984132E+01 6.207018E-01 2.241171E+02 + 2.190005E+01 9.000000E+01 5 1.447487E-04 -8.997601E+01 6.059328E-08 -1.447486E-04 + 2.190005E+01 9.000000E+01 6 1.006997E-05 1.799977E+02 -1.006997E-05 4.081997E-10 + 2.200005E+01 0.000000E+00 1 6.035680E+01 8.987121E+01 1.356777E-01 6.035665E+01 + 2.200005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.200005E+01 0.000000E+00 3 1.683641E+02 5.359118E-01 1.683568E+02 1.574758E+00 + 2.200005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.200005E+01 0.000000E+00 5 5.751278E+02 8.987121E+01 1.292816E+00 5.751263E+02 + 2.200005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.200005E+01 3.000000E+01 1 5.261614E+01 8.987124E+01 1.182418E-01 5.261601E+01 + 2.200005E+01 3.000000E+01 2 3.209763E+01 8.984237E+01 8.830625E-02 3.209751E+01 + 2.200005E+01 3.000000E+01 3 1.696278E+02 5.378510E-01 1.696203E+02 1.592319E+00 + 2.200005E+01 3.000000E+01 4 1.071438E+02 8.984050E+01 2.982757E-01 1.071434E+02 + 2.200005E+01 3.000000E+01 5 5.013560E+02 8.987124E+01 1.126672E+00 5.013547E+02 + 2.200005E+01 3.000000E+01 6 1.137848E+02 -3.413100E-03 1.137848E+02 -6.778141E-03 + 2.200005E+01 6.000000E+01 1 3.078190E+01 8.987132E+01 6.913461E-02 3.078182E+01 + 2.200005E+01 6.000000E+01 2 5.641064E+01 8.984232E+01 1.552524E-01 5.641043E+01 + 2.200005E+01 6.000000E+01 3 1.721860E+02 5.417319E-01 1.721783E+02 1.627995E+00 + 2.200005E+01 6.000000E+01 4 1.905308E+02 8.984230E+01 5.244043E-01 1.905301E+02 + 2.200005E+01 6.000000E+01 5 2.932545E+02 8.987129E+01 6.587522E-01 2.932538E+02 + 2.200005E+01 6.000000E+01 6 1.154984E+02 -3.395742E-03 1.154984E+02 -6.845228E-03 + 2.200005E+01 9.000000E+01 1 3.216569E-06 -9.007089E+01 -3.980032E-09 -3.216566E-06 + 2.200005E+01 9.000000E+01 2 6.561368E+01 8.984228E+01 1.806138E-01 6.561343E+01 + 2.200005E+01 9.000000E+01 3 1.734805E+02 5.436727E-01 1.734727E+02 1.646111E+00 + 2.200005E+01 9.000000E+01 4 2.228934E+02 8.984319E+01 6.100681E-01 2.228926E+02 + 2.200005E+01 9.000000E+01 5 1.441191E-04 -8.997639E+01 5.940745E-08 -1.441191E-04 + 2.200005E+01 9.000000E+01 6 9.967895E-06 1.799977E+02 -9.967895E-06 3.950835E-10 + 2.210005E+01 0.000000E+00 1 6.008511E+01 8.987253E+01 1.336762E-01 6.008496E+01 + 2.210005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.210005E+01 0.000000E+00 3 1.687092E+02 5.307443E-01 1.687020E+02 1.562771E+00 + 2.210005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.210005E+01 0.000000E+00 5 5.734885E+02 8.987254E+01 1.275833E+00 5.734871E+02 + 2.210005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.210005E+01 3.000000E+01 1 5.237580E+01 8.987257E+01 1.164903E-01 5.237568E+01 + 2.210005E+01 3.000000E+01 2 3.195111E+01 8.984422E+01 8.687587E-02 3.195099E+01 + 2.210005E+01 3.000000E+01 3 1.699618E+02 5.326432E-01 1.699544E+02 1.580006E+00 + 2.210005E+01 3.000000E+01 4 1.066027E+02 8.984238E+01 2.932694E-01 1.066023E+02 + 2.210005E+01 3.000000E+01 5 4.998937E+02 8.987257E+01 1.111814E+00 4.998925E+02 + 2.210005E+01 3.000000E+01 6 1.126665E+02 -3.336977E-03 1.126665E+02 -6.561836E-03 + 2.210005E+01 6.000000E+01 1 3.063708E+01 8.987264E+01 6.810214E-02 3.063701E+01 + 2.210005E+01 6.000000E+01 2 5.614452E+01 8.984416E+01 1.527131E-01 5.614431E+01 + 2.210005E+01 6.000000E+01 3 1.724972E+02 5.364386E-01 1.724897E+02 1.615003E+00 + 2.210005E+01 6.000000E+01 4 1.895200E+02 8.984415E+01 5.155184E-01 1.895193E+02 + 2.210005E+01 6.000000E+01 5 2.923587E+02 8.987262E+01 6.499888E-01 2.923580E+02 + 2.210005E+01 6.000000E+01 6 1.143454E+02 -3.320177E-03 1.143454E+02 -6.626091E-03 + 2.210005E+01 9.000000E+01 1 3.200958E-06 -9.007059E+01 -3.943783E-09 -3.200955E-06 + 2.210005E+01 9.000000E+01 2 6.529917E+01 8.984413E+01 1.776451E-01 6.529893E+01 + 2.210005E+01 9.000000E+01 3 1.737801E+02 5.383422E-01 1.737724E+02 1.632786E+00 + 2.210005E+01 9.000000E+01 4 2.216816E+02 8.984501E+01 5.996847E-01 2.216808E+02 + 2.210005E+01 9.000000E+01 5 1.434940E-04 -8.997674E+01 5.825240E-08 -1.434940E-04 + 2.210005E+01 9.000000E+01 6 9.867438E-06 1.799978E+02 -9.867438E-06 3.824653E-10 + 2.220005E+01 0.000000E+00 1 5.981580E+01 8.987383E+01 1.317142E-01 5.981566E+01 + 2.220005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.220005E+01 0.000000E+00 3 1.690494E+02 5.256490E-01 1.690423E+02 1.550889E+00 + 2.220005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.220005E+01 0.000000E+00 5 5.718513E+02 8.987384E+01 1.259161E+00 5.718499E+02 + 2.220005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.220005E+01 3.000000E+01 1 5.213771E+01 8.987387E+01 1.147740E-01 5.213758E+01 + 2.220005E+01 3.000000E+01 2 3.180588E+01 8.984602E+01 8.547690E-02 3.180576E+01 + 2.220005E+01 3.000000E+01 3 1.702915E+02 5.275040E-01 1.702843E+02 1.567797E+00 + 2.220005E+01 3.000000E+01 4 1.060671E+02 8.984422E+01 2.883778E-01 1.060667E+02 + 2.220005E+01 3.000000E+01 5 4.984298E+02 8.987387E+01 1.097223E+00 4.984286E+02 + 2.220005E+01 3.000000E+01 6 1.115650E+02 -3.263013E-03 1.115650E+02 -6.353665E-03 + 2.220005E+01 6.000000E+01 1 3.049358E+01 8.987394E+01 6.709035E-02 3.049351E+01 + 2.220005E+01 6.000000E+01 2 5.588098E+01 8.984597E+01 1.502306E-01 5.588078E+01 + 2.220005E+01 6.000000E+01 3 1.728050E+02 5.312185E-01 1.727976E+02 1.602141E+00 + 2.220005E+01 6.000000E+01 4 1.885188E+02 8.984595E+01 5.068418E-01 1.885181E+02 + 2.220005E+01 6.000000E+01 5 2.914639E+02 8.987392E+01 6.413736E-01 2.914632E+02 + 2.220005E+01 6.000000E+01 6 1.132102E+02 -3.246761E-03 1.132102E+02 -6.415244E-03 + 2.220005E+01 9.000000E+01 1 3.185517E-06 -9.007029E+01 -3.907673E-09 -3.185514E-06 + 2.220005E+01 9.000000E+01 2 6.498784E+01 8.984594E+01 1.747441E-01 6.498760E+01 + 2.220005E+01 9.000000E+01 3 1.740767E+02 5.330843E-01 1.740692E+02 1.619599E+00 + 2.220005E+01 9.000000E+01 4 2.204834E+02 8.984680E+01 5.895447E-01 2.204826E+02 + 2.220005E+01 9.000000E+01 5 1.428752E-04 -8.997710E+01 5.712690E-08 -1.428752E-04 + 2.220005E+01 9.000000E+01 6 9.768516E-06 1.799978E+02 -9.768516E-06 3.703224E-10 + 2.230005E+01 0.000000E+00 1 5.954891E+01 8.987512E+01 1.297910E-01 5.954877E+01 + 2.230005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.230005E+01 0.000000E+00 3 1.693851E+02 5.206265E-01 1.693782E+02 1.539122E+00 + 2.230005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.230005E+01 0.000000E+00 5 5.702155E+02 8.987513E+01 1.242772E+00 5.702141E+02 + 2.230005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.230005E+01 3.000000E+01 1 5.190144E+01 8.987515E+01 1.130914E-01 5.190132E+01 + 2.230005E+01 3.000000E+01 2 3.166203E+01 8.984780E+01 8.410879E-02 3.166191E+01 + 2.230005E+01 3.000000E+01 3 1.706168E+02 5.224418E-01 1.706097E+02 1.555719E+00 + 2.230005E+01 3.000000E+01 4 1.055370E+02 8.984604E+01 2.835975E-01 1.055366E+02 + 2.230005E+01 3.000000E+01 5 4.969723E+02 8.987515E+01 1.082875E+00 4.969711E+02 + 2.230005E+01 3.000000E+01 6 1.104799E+02 -3.191143E-03 1.104799E+02 -6.153282E-03 + 2.230005E+01 6.000000E+01 1 3.035161E+01 8.987522E+01 6.609912E-02 3.035154E+01 + 2.230005E+01 6.000000E+01 2 5.561997E+01 8.984775E+01 1.478033E-01 5.561978E+01 + 2.230005E+01 6.000000E+01 3 1.731088E+02 5.260794E-01 1.731015E+02 1.589431E+00 + 2.230005E+01 6.000000E+01 4 1.875295E+02 8.984774E+01 4.983612E-01 1.875289E+02 + 2.230005E+01 6.000000E+01 5 2.905703E+02 8.987521E+01 6.329147E-01 2.905696E+02 + 2.230005E+01 6.000000E+01 6 1.120922E+02 -3.175411E-03 1.120922E+02 -6.212304E-03 + 2.230005E+01 9.000000E+01 1 3.170218E-06 -9.006997E+01 -3.871713E-09 -3.170216E-06 + 2.230005E+01 9.000000E+01 2 6.467928E+01 8.984772E+01 1.719072E-01 6.467905E+01 + 2.230005E+01 9.000000E+01 3 1.743694E+02 5.279021E-01 1.743620E+02 1.606552E+00 + 2.230005E+01 9.000000E+01 4 2.193003E+02 8.984856E+01 5.796371E-01 2.192995E+02 + 2.230005E+01 9.000000E+01 5 1.422606E-04 -8.997744E+01 5.602987E-08 -1.422606E-04 + 2.230005E+01 9.000000E+01 6 9.671127E-06 1.799979E+02 -9.671127E-06 3.586343E-10 + 2.240005E+01 0.000000E+00 1 5.928447E+01 8.987638E+01 1.279064E-01 5.928434E+01 + 2.240005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.240005E+01 0.000000E+00 3 1.697171E+02 5.156795E-01 1.697102E+02 1.527485E+00 + 2.240005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.240005E+01 0.000000E+00 5 5.685760E+02 8.987639E+01 1.226670E+00 5.685746E+02 + 2.240005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.240005E+01 3.000000E+01 1 5.166759E+01 8.987642E+01 1.114418E-01 5.166747E+01 + 2.240005E+01 3.000000E+01 2 3.151941E+01 8.984954E+01 8.277039E-02 3.151930E+01 + 2.240005E+01 3.000000E+01 3 1.709379E+02 5.174570E-01 1.709310E+02 1.543776E+00 + 2.240005E+01 3.000000E+01 4 1.050123E+02 8.984782E+01 2.789247E-01 1.050119E+02 + 2.240005E+01 3.000000E+01 5 4.955127E+02 8.987642E+01 1.068766E+00 4.955115E+02 + 2.240005E+01 3.000000E+01 6 1.094111E+02 -3.121288E-03 1.094111E+02 -5.960361E-03 + 2.240005E+01 6.000000E+01 1 3.021082E+01 8.987649E+01 6.512718E-02 3.021075E+01 + 2.240005E+01 6.000000E+01 2 5.536131E+01 8.984949E+01 1.454293E-01 5.536111E+01 + 2.240005E+01 6.000000E+01 3 1.734088E+02 5.210173E-01 1.734016E+02 1.576865E+00 + 2.240005E+01 6.000000E+01 4 1.865516E+02 8.984948E+01 4.900765E-01 1.865509E+02 + 2.240005E+01 6.000000E+01 5 2.896793E+02 8.987646E+01 6.245902E-01 2.896786E+02 + 2.240005E+01 6.000000E+01 6 1.109913E+02 -3.106060E-03 1.109913E+02 -6.016947E-03 + 2.240005E+01 9.000000E+01 1 3.155059E-06 -9.006966E+01 -3.835916E-09 -3.155057E-06 + 2.240005E+01 9.000000E+01 2 6.437397E+01 8.984946E+01 1.691330E-01 6.437375E+01 + 2.240005E+01 9.000000E+01 3 1.746581E+02 5.228024E-01 1.746509E+02 1.593668E+00 + 2.240005E+01 9.000000E+01 4 2.181295E+02 8.985030E+01 5.699567E-01 2.181288E+02 + 2.240005E+01 9.000000E+01 5 1.416516E-04 -8.997777E+01 5.496045E-08 -1.416516E-04 + 2.240005E+01 9.000000E+01 6 9.575243E-06 1.799979E+02 -9.575243E-06 3.473817E-10 + 2.250005E+01 0.000000E+00 1 5.902221E+01 8.987763E+01 1.260573E-01 5.902208E+01 + 2.250005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.250005E+01 0.000000E+00 3 1.700447E+02 5.108026E-01 1.700380E+02 1.515961E+00 + 2.250005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.250005E+01 0.000000E+00 5 5.669478E+02 8.987763E+01 1.210813E+00 5.669465E+02 + 2.250005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.250005E+01 3.000000E+01 1 5.143571E+01 8.987766E+01 1.098251E-01 5.143559E+01 + 2.250005E+01 3.000000E+01 2 3.137811E+01 8.985126E+01 8.146127E-02 3.137801E+01 + 2.250005E+01 3.000000E+01 3 1.712562E+02 5.125394E-01 1.712494E+02 1.531952E+00 + 2.250005E+01 3.000000E+01 4 1.044927E+02 8.984956E+01 2.743582E-01 1.044923E+02 + 2.250005E+01 3.000000E+01 5 4.940579E+02 8.987766E+01 1.054901E+00 4.940568E+02 + 2.250005E+01 3.000000E+01 6 1.083581E+02 -3.053386E-03 1.083581E+02 -5.774582E-03 + 2.250005E+01 6.000000E+01 1 3.007125E+01 8.987773E+01 6.417476E-02 3.007118E+01 + 2.250005E+01 6.000000E+01 2 5.510530E+01 8.985121E+01 1.431075E-01 5.510511E+01 + 2.250005E+01 6.000000E+01 3 1.737053E+02 5.160235E-01 1.736983E+02 1.564422E+00 + 2.250005E+01 6.000000E+01 4 1.855834E+02 8.985120E+01 4.819798E-01 1.855828E+02 + 2.250005E+01 6.000000E+01 5 2.887914E+02 8.987770E+01 6.164166E-01 2.887907E+02 + 2.250005E+01 6.000000E+01 6 1.099068E+02 -3.038650E-03 1.099068E+02 -5.828848E-03 + 2.250005E+01 9.000000E+01 1 3.140078E-06 -9.006934E+01 -3.800280E-09 -3.140075E-06 + 2.250005E+01 9.000000E+01 2 6.407160E+01 8.985118E+01 1.664205E-01 6.407139E+01 + 2.250005E+01 9.000000E+01 3 1.749439E+02 5.177726E-01 1.749368E+02 1.580918E+00 + 2.250005E+01 9.000000E+01 4 2.169711E+02 8.985199E+01 5.605000E-01 2.169704E+02 + 2.250005E+01 9.000000E+01 5 1.410474E-04 -8.997810E+01 5.391795E-08 -1.410474E-04 + 2.250005E+01 9.000000E+01 6 9.480822E-06 1.799980E+02 -9.480822E-06 3.365462E-10 + 2.260005E+01 0.000000E+00 1 5.876220E+01 8.987885E+01 1.242446E-01 5.876207E+01 + 2.260005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.260005E+01 0.000000E+00 3 1.703676E+02 5.059933E-01 1.703610E+02 1.504540E+00 + 2.260005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.260005E+01 0.000000E+00 5 5.653150E+02 8.987886E+01 1.195239E+00 5.653137E+02 + 2.260005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.260005E+01 3.000000E+01 1 5.120598E+01 8.987889E+01 1.082396E-01 5.120586E+01 + 2.260005E+01 3.000000E+01 2 3.123807E+01 8.985294E+01 8.018006E-02 3.123797E+01 + 2.260005E+01 3.000000E+01 3 1.715686E+02 5.076953E-01 1.715618E+02 1.520242E+00 + 2.260005E+01 3.000000E+01 4 1.039790E+02 8.985128E+01 2.698922E-01 1.039787E+02 + 2.260005E+01 3.000000E+01 5 4.926046E+02 8.987889E+01 1.041268E+00 4.926035E+02 + 2.260005E+01 3.000000E+01 6 1.073204E+02 -2.987368E-03 1.073204E+02 -5.595624E-03 + 2.260005E+01 6.000000E+01 1 2.993316E+01 8.987895E+01 6.324082E-02 2.993309E+01 + 2.260005E+01 6.000000E+01 2 5.485150E+01 8.985289E+01 1.408364E-01 5.485132E+01 + 2.260005E+01 6.000000E+01 3 1.739983E+02 5.111058E-01 1.739913E+02 1.552127E+00 + 2.260005E+01 6.000000E+01 4 1.846258E+02 8.985288E+01 4.740637E-01 1.846252E+02 + 2.260005E+01 6.000000E+01 5 2.879061E+02 8.987892E+01 6.083838E-01 2.879054E+02 + 2.260005E+01 6.000000E+01 6 1.088388E+02 -2.973096E-03 1.088388E+02 -5.647680E-03 + 2.260005E+01 9.000000E+01 1 3.125226E-06 -9.006902E+01 -3.764844E-09 -3.125224E-06 + 2.260005E+01 9.000000E+01 2 6.377199E+01 8.985287E+01 1.637671E-01 6.377178E+01 + 2.260005E+01 9.000000E+01 3 1.752252E+02 5.128179E-01 1.752182E+02 1.568308E+00 + 2.260005E+01 9.000000E+01 4 2.158263E+02 8.985366E+01 5.512557E-01 2.158256E+02 + 2.260005E+01 9.000000E+01 5 1.404487E-04 -8.997842E+01 5.290142E-08 -1.404487E-04 + 2.260005E+01 9.000000E+01 6 9.387832E-06 1.799980E+02 -9.387832E-06 3.261088E-10 + 2.270005E+01 0.000000E+00 1 5.850466E+01 8.988007E+01 1.224671E-01 5.850453E+01 + 2.270005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.270005E+01 0.000000E+00 3 1.706876E+02 5.012506E-01 1.706811E+02 1.493237E+00 + 2.270005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.270005E+01 0.000000E+00 5 5.636855E+02 8.988007E+01 1.179917E+00 5.636843E+02 + 2.270005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.270005E+01 3.000000E+01 1 5.097813E+01 8.988010E+01 1.066849E-01 5.097802E+01 + 2.270005E+01 3.000000E+01 2 3.109923E+01 8.985459E+01 7.892652E-02 3.109913E+01 + 2.270005E+01 3.000000E+01 3 1.718788E+02 5.029147E-01 1.718722E+02 1.508650E+00 + 2.270005E+01 3.000000E+01 4 1.034701E+02 8.985297E+01 2.655265E-01 1.034698E+02 + 2.270005E+01 3.000000E+01 5 4.911523E+02 8.988010E+01 1.027858E+00 4.911512E+02 + 2.270005E+01 3.000000E+01 6 1.062980E+02 -2.923173E-03 1.062980E+02 -5.423216E-03 + 2.270005E+01 6.000000E+01 1 2.979630E+01 8.988016E+01 6.232551E-02 2.979623E+01 + 2.270005E+01 6.000000E+01 2 5.460021E+01 8.985454E+01 1.386141E-01 5.460003E+01 + 2.270005E+01 6.000000E+01 3 1.742867E+02 5.062580E-01 1.742799E+02 1.539954E+00 + 2.270005E+01 6.000000E+01 4 1.836797E+02 8.985454E+01 4.663287E-01 1.836791E+02 + 2.270005E+01 6.000000E+01 5 2.870220E+02 8.988013E+01 6.004782E-01 2.870213E+02 + 2.270005E+01 6.000000E+01 6 1.077867E+02 -2.909345E-03 1.077867E+02 -5.473155E-03 + 2.270005E+01 9.000000E+01 1 3.110519E-06 -9.006870E+01 -3.729598E-09 -3.110516E-06 + 2.270005E+01 9.000000E+01 2 6.347538E+01 8.985452E+01 1.611714E-01 6.347517E+01 + 2.270005E+01 9.000000E+01 3 1.755040E+02 5.079331E-01 1.754971E+02 1.555841E+00 + 2.270005E+01 9.000000E+01 4 2.146954E+02 8.985530E+01 5.422186E-01 2.146947E+02 + 2.270005E+01 9.000000E+01 5 1.398552E-04 -8.997874E+01 5.191003E-08 -1.398552E-04 + 2.270005E+01 9.000000E+01 6 9.296253E-06 1.799980E+02 -9.296253E-06 3.160540E-10 + 2.280005E+01 0.000000E+00 1 5.824918E+01 8.988126E+01 1.207237E-01 5.824906E+01 + 2.280005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.280005E+01 0.000000E+00 3 1.710032E+02 4.965749E-01 1.709967E+02 1.482043E+00 + 2.280005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.280005E+01 0.000000E+00 5 5.620590E+02 8.988126E+01 1.164852E+00 5.620577E+02 + 2.280005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.280005E+01 3.000000E+01 1 5.075246E+01 8.988128E+01 1.051603E-01 5.075235E+01 + 2.280005E+01 3.000000E+01 2 3.096159E+01 8.985622E+01 7.769980E-02 3.096150E+01 + 2.280005E+01 3.000000E+01 3 1.721832E+02 4.982095E-01 1.721766E+02 1.497182E+00 + 2.280005E+01 3.000000E+01 4 1.029662E+02 8.985462E+01 2.612569E-01 1.029658E+02 + 2.280005E+01 3.000000E+01 5 4.897064E+02 8.988128E+01 1.014680E+00 4.897053E+02 + 2.280005E+01 3.000000E+01 6 1.052905E+02 -2.860733E-03 1.052905E+02 -5.257073E-03 + 2.280005E+01 6.000000E+01 1 2.966075E+01 8.988134E+01 6.142784E-02 2.966069E+01 + 2.280005E+01 6.000000E+01 2 5.435117E+01 8.985616E+01 1.364400E-01 5.435100E+01 + 2.280005E+01 6.000000E+01 3 1.745713E+02 5.014826E-01 1.745646E+02 1.527920E+00 + 2.280005E+01 6.000000E+01 4 1.827427E+02 8.985616E+01 4.587638E-01 1.827421E+02 + 2.280005E+01 6.000000E+01 5 2.861421E+02 8.988132E+01 5.927127E-01 2.861415E+02 + 2.280005E+01 6.000000E+01 6 1.067502E+02 -2.847337E-03 1.067502E+02 -5.304995E-03 + 2.280005E+01 9.000000E+01 1 3.095955E-06 -9.006837E+01 -3.694568E-09 -3.095952E-06 + 2.280005E+01 9.000000E+01 2 6.318153E+01 8.985615E+01 1.586325E-01 6.318133E+01 + 2.280005E+01 9.000000E+01 3 1.757789E+02 5.031202E-01 1.757721E+02 1.543513E+00 + 2.280005E+01 9.000000E+01 4 2.135760E+02 8.985691E+01 5.333858E-01 2.135753E+02 + 2.280005E+01 9.000000E+01 5 1.392646E-04 -8.997904E+01 5.094318E-08 -1.392646E-04 + 2.280005E+01 9.000000E+01 6 9.206043E-06 1.799981E+02 -9.206043E-06 3.063649E-10 + 2.290005E+01 0.000000E+00 1 5.799576E+01 8.988242E+01 1.190134E-01 5.799564E+01 + 2.290005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.290005E+01 0.000000E+00 3 1.713144E+02 4.919704E-01 1.713081E+02 1.470973E+00 + 2.290005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.290005E+01 0.000000E+00 5 5.604406E+02 8.988243E+01 1.150034E+00 5.604395E+02 + 2.290005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.290005E+01 3.000000E+01 1 5.052847E+01 8.988245E+01 1.036647E-01 5.052836E+01 + 2.290005E+01 3.000000E+01 2 3.082521E+01 8.985781E+01 7.649886E-02 3.082512E+01 + 2.290005E+01 3.000000E+01 3 1.724854E+02 4.935687E-01 1.724790E+02 1.485840E+00 + 2.290005E+01 3.000000E+01 4 1.024670E+02 8.985625E+01 2.570813E-01 1.024667E+02 + 2.290005E+01 3.000000E+01 5 4.882610E+02 8.988245E+01 1.001710E+00 4.882599E+02 + 2.290005E+01 3.000000E+01 6 1.042977E+02 -2.799999E-03 1.042977E+02 -5.096943E-03 + 2.290005E+01 6.000000E+01 1 2.952635E+01 8.988251E+01 6.054788E-02 2.952629E+01 + 2.290005E+01 6.000000E+01 2 5.410443E+01 8.985777E+01 1.343129E-01 5.410426E+01 + 2.290005E+01 6.000000E+01 3 1.748531E+02 4.967713E-01 1.748465E+02 1.516009E+00 + 2.290005E+01 6.000000E+01 4 1.818155E+02 8.985776E+01 4.513689E-01 1.818149E+02 + 2.290005E+01 6.000000E+01 5 2.852617E+02 8.988248E+01 5.850755E-01 2.852611E+02 + 2.290005E+01 6.000000E+01 6 1.057289E+02 -2.787019E-03 1.057289E+02 -5.142936E-03 + 2.290005E+01 9.000000E+01 1 3.081531E-06 -9.006805E+01 -3.659745E-09 -3.081529E-06 + 2.290005E+01 9.000000E+01 2 6.289063E+01 8.985774E+01 1.561481E-01 6.289043E+01 + 2.290005E+01 9.000000E+01 3 1.760497E+02 4.983768E-01 1.760430E+02 1.531317E+00 + 2.290005E+01 9.000000E+01 4 2.124675E+02 8.985850E+01 5.247492E-01 2.124668E+02 + 2.290005E+01 9.000000E+01 5 1.386812E-04 -8.997934E+01 5.000005E-08 -1.386812E-04 + 2.290005E+01 9.000000E+01 6 9.117193E-06 1.799981E+02 -9.117193E-06 2.970265E-10 + 2.300005E+01 0.000000E+00 1 5.774446E+01 8.988358E+01 1.173359E-01 5.774434E+01 + 2.300005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.300005E+01 0.000000E+00 3 1.716221E+02 4.874241E-01 1.716158E+02 1.459998E+00 + 2.300005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.300005E+01 0.000000E+00 5 5.588184E+02 8.988358E+01 1.135463E+00 5.588173E+02 + 2.300005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.300005E+01 3.000000E+01 1 5.030678E+01 8.988361E+01 1.021980E-01 5.030668E+01 + 2.300005E+01 3.000000E+01 2 3.069005E+01 8.985938E+01 7.532332E-02 3.068996E+01 + 2.300005E+01 3.000000E+01 3 1.727834E+02 4.889895E-01 1.727771E+02 1.474598E+00 + 2.300005E+01 3.000000E+01 4 1.019732E+02 8.985785E+01 2.529953E-01 1.019728E+02 + 2.300005E+01 3.000000E+01 5 4.868222E+02 8.988361E+01 9.889663E-01 4.868212E+02 + 2.300005E+01 3.000000E+01 6 1.033190E+02 -2.740901E-03 1.033190E+02 -4.942546E-03 + 2.300005E+01 6.000000E+01 1 2.939326E+01 8.988366E+01 5.968458E-02 2.939320E+01 + 2.300005E+01 6.000000E+01 2 5.385995E+01 8.985934E+01 1.322304E-01 5.385979E+01 + 2.300005E+01 6.000000E+01 3 1.751313E+02 4.921286E-01 1.751248E+02 1.504230E+00 + 2.300005E+01 6.000000E+01 4 1.808982E+02 8.985933E+01 4.441353E-01 1.808977E+02 + 2.300005E+01 6.000000E+01 5 2.843881E+02 8.988364E+01 5.775701E-01 2.843875E+02 + 2.300005E+01 6.000000E+01 6 1.047226E+02 -2.728326E-03 1.047226E+02 -4.986711E-03 + 2.300005E+01 9.000000E+01 1 3.067234E-06 -9.006772E+01 -3.625147E-09 -3.067232E-06 + 2.300005E+01 9.000000E+01 2 6.260244E+01 8.985931E+01 1.537165E-01 6.260226E+01 + 2.300005E+01 9.000000E+01 3 1.763179E+02 4.936996E-01 1.763113E+02 1.519257E+00 + 2.300005E+01 9.000000E+01 4 2.113725E+02 8.986005E+01 5.163049E-01 2.113719E+02 + 2.300005E+01 9.000000E+01 5 1.381013E-04 -8.997964E+01 4.907984E-08 -1.381013E-04 + 2.300005E+01 9.000000E+01 6 9.029641E-06 1.799982E+02 -9.029641E-06 2.880232E-10 + 2.310005E+01 0.000000E+00 1 5.749552E+01 8.988471E+01 1.156901E-01 5.749540E+01 + 2.310005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.310005E+01 0.000000E+00 3 1.719264E+02 4.829415E-01 1.719203E+02 1.449137E+00 + 2.310005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.310005E+01 0.000000E+00 5 5.572003E+02 8.988472E+01 1.121129E+00 5.571992E+02 + 2.310005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.310005E+01 3.000000E+01 1 5.008691E+01 8.988474E+01 1.007595E-01 5.008681E+01 + 2.310005E+01 3.000000E+01 2 3.055601E+01 8.986092E+01 7.417223E-02 3.055592E+01 + 2.310005E+01 3.000000E+01 3 1.730778E+02 4.844745E-01 1.730717E+02 1.463472E+00 + 2.310005E+01 3.000000E+01 4 1.014840E+02 8.985942E+01 2.489998E-01 1.014837E+02 + 2.310005E+01 3.000000E+01 5 4.853862E+02 8.988474E+01 9.764374E-01 4.853852E+02 + 2.310005E+01 3.000000E+01 6 1.023544E+02 -2.683394E-03 1.023544E+02 -4.793673E-03 + 2.310005E+01 6.000000E+01 1 2.926138E+01 8.988479E+01 5.883796E-02 2.926132E+01 + 2.310005E+01 6.000000E+01 2 5.361773E+01 8.986088E+01 1.301921E-01 5.361758E+01 + 2.310005E+01 6.000000E+01 3 1.754065E+02 4.875498E-01 1.754002E+02 1.492577E+00 + 2.310005E+01 6.000000E+01 4 1.799904E+02 8.986087E+01 4.370606E-01 1.799899E+02 + 2.310005E+01 6.000000E+01 5 2.835160E+02 8.988477E+01 5.701879E-01 2.835154E+02 + 2.310005E+01 6.000000E+01 6 1.037312E+02 -2.671204E-03 1.037312E+02 -4.836084E-03 + 2.310005E+01 9.000000E+01 1 3.053080E-06 -9.006739E+01 -3.590793E-09 -3.053078E-06 + 2.310005E+01 9.000000E+01 2 6.231676E+01 8.986086E+01 1.513368E-01 6.231658E+01 + 2.310005E+01 9.000000E+01 3 1.765828E+02 4.890909E-01 1.765764E+02 1.507336E+00 + 2.310005E+01 9.000000E+01 4 2.102881E+02 8.986158E+01 5.080464E-01 2.102875E+02 + 2.310005E+01 9.000000E+01 5 1.375266E-04 -8.997993E+01 4.818189E-08 -1.375266E-04 + 2.310005E+01 9.000000E+01 6 8.943385E-06 1.799982E+02 -8.943385E-06 2.793419E-10 + 2.320005E+01 0.000000E+00 1 5.724863E+01 8.988583E+01 1.140751E-01 5.724851E+01 + 2.320005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.320005E+01 0.000000E+00 3 1.722262E+02 4.785225E-01 1.722202E+02 1.438381E+00 + 2.320005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.320005E+01 0.000000E+00 5 5.555858E+02 8.988583E+01 1.107037E+00 5.555847E+02 + 2.320005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.320005E+01 3.000000E+01 1 4.986903E+01 8.988586E+01 9.934754E-02 4.986893E+01 + 2.320005E+01 3.000000E+01 2 3.042311E+01 8.986243E+01 7.304538E-02 3.042302E+01 + 2.320005E+01 3.000000E+01 3 1.733679E+02 4.800298E-01 1.733618E+02 1.452477E+00 + 2.320005E+01 3.000000E+01 4 1.010003E+02 8.986097E+01 2.450888E-01 1.010000E+02 + 2.320005E+01 3.000000E+01 5 4.839494E+02 8.988586E+01 9.641139E-01 4.839485E+02 + 2.320005E+01 3.000000E+01 6 1.014036E+02 -2.627429E-03 1.014036E+02 -4.650094E-03 + 2.320005E+01 6.000000E+01 1 2.913063E+01 8.988590E+01 5.800764E-02 2.913058E+01 + 2.320005E+01 6.000000E+01 2 5.337780E+01 8.986240E+01 1.281967E-01 5.337764E+01 + 2.320005E+01 6.000000E+01 3 1.756773E+02 4.830391E-01 1.756711E+02 1.481052E+00 + 2.320005E+01 6.000000E+01 4 1.790919E+02 8.986239E+01 4.301402E-01 1.790914E+02 + 2.320005E+01 6.000000E+01 5 2.826436E+02 8.988589E+01 5.629311E-01 2.826431E+02 + 2.320005E+01 6.000000E+01 6 1.027541E+02 -2.615610E-03 1.027541E+02 -4.690829E-03 + 2.320005E+01 9.000000E+01 1 3.039066E-06 -9.006705E+01 -3.556683E-09 -3.039064E-06 + 2.320005E+01 9.000000E+01 2 6.203386E+01 8.986237E+01 1.490075E-01 6.203368E+01 + 2.320005E+01 9.000000E+01 3 1.768442E+02 4.845468E-01 1.768379E+02 1.495543E+00 + 2.320005E+01 9.000000E+01 4 2.092164E+02 8.986308E+01 4.999671E-01 2.092158E+02 + 2.320005E+01 9.000000E+01 5 1.369564E-04 -8.998021E+01 4.730575E-08 -1.369564E-04 + 2.320005E+01 9.000000E+01 6 8.858414E-06 1.799982E+02 -8.858414E-06 2.709699E-10 + 2.330005E+01 0.000000E+00 1 5.700379E+01 8.988694E+01 1.124909E-01 5.700368E+01 + 2.330005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.330005E+01 0.000000E+00 3 1.725218E+02 4.741654E-01 1.725159E+02 1.427730E+00 + 2.330005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.330005E+01 0.000000E+00 5 5.539759E+02 8.988694E+01 1.093164E+00 5.539748E+02 + 2.330005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.330005E+01 3.000000E+01 1 4.965289E+01 8.988696E+01 9.796271E-02 4.965280E+01 + 2.330005E+01 3.000000E+01 2 3.029145E+01 8.986392E+01 7.194176E-02 3.029136E+01 + 2.330005E+01 3.000000E+01 3 1.736550E+02 4.756360E-01 1.736491E+02 1.441566E+00 + 2.330005E+01 3.000000E+01 4 1.005208E+02 8.986249E+01 2.412628E-01 1.005205E+02 + 2.330005E+01 3.000000E+01 5 4.825190E+02 8.988696E+01 9.519819E-01 4.825180E+02 + 2.330005E+01 3.000000E+01 6 1.004662E+02 -2.572953E-03 1.004662E+02 -4.511584E-03 + 2.330005E+01 6.000000E+01 1 2.900108E+01 8.988701E+01 5.719278E-02 2.900102E+01 + 2.330005E+01 6.000000E+01 2 5.314001E+01 8.986388E+01 1.262435E-01 5.313987E+01 + 2.330005E+01 6.000000E+01 3 1.759453E+02 4.785885E-01 1.759391E+02 1.469644E+00 + 2.330005E+01 6.000000E+01 4 1.782030E+02 8.986388E+01 4.233695E-01 1.782025E+02 + 2.330005E+01 6.000000E+01 5 2.817781E+02 8.988699E+01 5.557917E-01 2.817776E+02 + 2.330005E+01 6.000000E+01 6 1.017911E+02 -2.561494E-03 1.017911E+02 -4.550726E-03 + 2.330005E+01 9.000000E+01 1 3.025175E-06 -9.006672E+01 -3.522809E-09 -3.025173E-06 + 2.330005E+01 9.000000E+01 2 6.175347E+01 8.986386E+01 1.467271E-01 6.175330E+01 + 2.330005E+01 9.000000E+01 3 1.771024E+02 4.800657E-01 1.770962E+02 1.483875E+00 + 2.330005E+01 9.000000E+01 4 2.081564E+02 8.986456E+01 4.920636E-01 2.081558E+02 + 2.330005E+01 9.000000E+01 5 1.363912E-04 -8.998049E+01 4.645045E-08 -1.363912E-04 + 2.330005E+01 9.000000E+01 6 8.774668E-06 1.799983E+02 -8.774668E-06 2.628938E-10 + 2.340005E+01 0.000000E+00 1 5.676098E+01 8.988802E+01 1.109356E-01 5.676088E+01 + 2.340005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.340005E+01 0.000000E+00 3 1.728155E+02 4.698642E-01 1.728097E+02 1.417188E+00 + 2.340005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.340005E+01 0.000000E+00 5 5.523732E+02 8.988802E+01 1.079528E+00 5.523721E+02 + 2.340005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.340005E+01 3.000000E+01 1 4.943872E+01 8.988805E+01 9.660371E-02 4.943862E+01 + 2.340005E+01 3.000000E+01 2 3.016082E+01 8.986539E+01 7.086073E-02 3.016074E+01 + 2.340005E+01 3.000000E+01 3 1.739397E+02 4.713049E-01 1.739338E+02 1.430781E+00 + 2.340005E+01 3.000000E+01 4 1.000457E+02 8.986398E+01 2.375182E-01 1.000454E+02 + 2.340005E+01 3.000000E+01 5 4.810920E+02 8.988805E+01 9.400615E-01 4.810911E+02 + 2.340005E+01 3.000000E+01 6 9.954193E+01 -2.519920E-03 9.954193E+01 -4.377943E-03 + 2.340005E+01 6.000000E+01 1 2.887272E+01 8.988809E+01 5.639353E-02 2.887266E+01 + 2.340005E+01 6.000000E+01 2 5.290430E+01 8.986536E+01 1.243302E-01 5.290416E+01 + 2.340005E+01 6.000000E+01 3 1.762097E+02 4.742000E-01 1.762036E+02 1.458357E+00 + 2.340005E+01 6.000000E+01 4 1.773237E+02 8.986535E+01 4.167439E-01 1.773232E+02 + 2.340005E+01 6.000000E+01 5 2.809125E+02 8.988807E+01 5.487711E-01 2.809119E+02 + 2.340005E+01 6.000000E+01 6 1.008419E+02 -2.508803E-03 1.008419E+02 -4.415549E-03 + 2.340005E+01 9.000000E+01 1 3.011427E-06 -9.006638E+01 -3.489197E-09 -3.011425E-06 + 2.340005E+01 9.000000E+01 2 6.147582E+01 8.986533E+01 1.444942E-01 6.147565E+01 + 2.340005E+01 9.000000E+01 3 1.773578E+02 4.756498E-01 1.773517E+02 1.472347E+00 + 2.340005E+01 9.000000E+01 4 2.071072E+02 8.986601E+01 4.843317E-01 2.071067E+02 + 2.340005E+01 9.000000E+01 5 1.358298E-04 -8.998076E+01 4.561563E-08 -1.358298E-04 + 2.340005E+01 9.000000E+01 6 8.692145E-06 1.799983E+02 -8.692145E-06 2.551012E-10 + 2.350005E+01 0.000000E+00 1 5.652029E+01 8.988909E+01 1.094099E-01 5.652018E+01 + 2.350005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.350005E+01 0.000000E+00 3 1.731049E+02 4.656200E-01 1.730992E+02 1.406739E+00 + 2.350005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.350005E+01 0.000000E+00 5 5.507627E+02 8.988909E+01 1.066108E+00 5.507617E+02 + 2.350005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.350005E+01 3.000000E+01 1 4.922615E+01 8.988911E+01 9.526986E-02 4.922606E+01 + 2.350005E+01 3.000000E+01 2 3.003135E+01 8.986683E+01 6.980192E-02 3.003127E+01 + 2.350005E+01 3.000000E+01 3 1.742183E+02 4.670392E-01 1.742125E+02 1.420103E+00 + 2.350005E+01 3.000000E+01 4 9.957614E+01 8.986544E+01 2.338523E-01 9.957587E+01 + 2.350005E+01 3.000000E+01 5 4.796705E+02 8.988911E+01 9.283333E-01 4.796696E+02 + 2.350005E+01 3.000000E+01 6 9.863074E+01 -2.468276E-03 9.863074E+01 -4.248967E-03 + 2.350005E+01 6.000000E+01 1 2.874556E+01 8.988916E+01 5.560928E-02 2.874551E+01 + 2.350005E+01 6.000000E+01 2 5.267070E+01 8.986679E+01 1.224572E-01 5.267056E+01 + 2.350005E+01 6.000000E+01 3 1.764716E+02 4.698740E-01 1.764656E+02 1.447200E+00 + 2.350005E+01 6.000000E+01 4 1.764534E+02 8.986679E+01 4.102605E-01 1.764529E+02 + 2.350005E+01 6.000000E+01 5 2.800497E+02 8.988914E+01 5.418662E-01 2.800492E+02 + 2.350005E+01 6.000000E+01 6 9.990620E+01 -2.457497E-03 9.990620E+01 -4.285118E-03 + 2.350005E+01 9.000000E+01 1 2.997795E-06 -9.006606E+01 -3.455841E-09 -2.997793E-06 + 2.350005E+01 9.000000E+01 2 6.120066E+01 8.986678E+01 1.423084E-01 6.120050E+01 + 2.350005E+01 9.000000E+01 3 1.776091E+02 4.712927E-01 1.776031E+02 1.460926E+00 + 2.350005E+01 9.000000E+01 4 2.060689E+02 8.986745E+01 4.767658E-01 2.060684E+02 + 2.350005E+01 9.000000E+01 5 1.352738E-04 -8.998103E+01 4.480063E-08 -1.352738E-04 + 2.350005E+01 9.000000E+01 6 8.610819E-06 1.799984E+02 -8.610819E-06 2.475814E-10 + 2.360005E+01 0.000000E+00 1 5.628149E+01 8.989014E+01 1.079119E-01 5.628139E+01 + 2.360005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.360005E+01 0.000000E+00 3 1.733906E+02 4.614415E-01 1.733849E+02 1.396416E+00 + 2.360005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.360005E+01 0.000000E+00 5 5.491675E+02 8.989014E+01 1.052917E+00 5.491665E+02 + 2.360005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.360005E+01 3.000000E+01 1 4.901573E+01 8.989017E+01 9.396078E-02 4.901564E+01 + 2.360005E+01 3.000000E+01 2 2.990297E+01 8.986824E+01 6.876475E-02 2.990289E+01 + 2.360005E+01 3.000000E+01 3 1.744954E+02 4.628298E-01 1.744897E+02 1.409542E+00 + 2.360005E+01 3.000000E+01 4 9.911015E+01 8.986688E+01 2.302644E-01 9.910988E+01 + 2.360005E+01 3.000000E+01 5 4.782509E+02 8.989017E+01 9.167892E-01 4.782500E+02 + 2.360005E+01 3.000000E+01 6 9.773241E+01 -2.417973E-03 9.773241E+01 -4.124463E-03 + 2.360005E+01 6.000000E+01 1 2.861949E+01 8.989021E+01 5.483994E-02 2.861944E+01 + 2.360005E+01 6.000000E+01 2 5.243935E+01 8.986821E+01 1.206222E-01 5.243922E+01 + 2.360005E+01 6.000000E+01 3 1.767299E+02 4.656098E-01 1.767241E+02 1.436167E+00 + 2.360005E+01 6.000000E+01 4 1.755913E+02 8.986820E+01 4.039136E-01 1.755909E+02 + 2.360005E+01 6.000000E+01 5 2.791902E+02 8.989020E+01 5.350783E-01 2.791897E+02 + 2.360005E+01 6.000000E+01 6 9.898397E+01 -2.407515E-03 9.898397E+01 -4.159214E-03 + 2.360005E+01 9.000000E+01 1 2.984292E-06 -9.006572E+01 -3.422742E-09 -2.984290E-06 + 2.360005E+01 9.000000E+01 2 6.092810E+01 8.986819E+01 1.401669E-01 6.092794E+01 + 2.360005E+01 9.000000E+01 3 1.778585E+02 4.669997E-01 1.778526E+02 1.449652E+00 + 2.360005E+01 9.000000E+01 4 2.050410E+02 8.986884E+01 4.693612E-01 2.050404E+02 + 2.360005E+01 9.000000E+01 5 1.347215E-04 -8.998129E+01 4.400496E-08 -1.347215E-04 + 2.360005E+01 9.000000E+01 6 8.530661E-06 1.799984E+02 -8.530661E-06 2.403228E-10 + 2.370005E+01 0.000000E+00 1 5.604475E+01 8.989118E+01 1.064415E-01 5.604465E+01 + 2.370005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.370005E+01 0.000000E+00 3 1.736726E+02 4.573165E-01 1.736671E+02 1.386184E+00 + 2.370005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.370005E+01 0.000000E+00 5 5.475739E+02 8.989118E+01 1.039919E+00 5.475729E+02 + 2.370005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.370005E+01 3.000000E+01 1 4.880688E+01 8.989120E+01 9.267645E-02 4.880679E+01 + 2.370005E+01 3.000000E+01 2 2.977571E+01 8.986964E+01 6.774839E-02 2.977563E+01 + 2.370005E+01 3.000000E+01 3 1.747689E+02 4.586752E-01 1.747633E+02 1.399079E+00 + 2.370005E+01 3.000000E+01 4 9.864913E+01 8.986830E+01 2.267505E-01 9.864887E+01 + 2.370005E+01 3.000000E+01 5 4.768365E+02 8.989120E+01 9.054314E-01 4.768357E+02 + 2.370005E+01 3.000000E+01 6 9.684645E+01 -2.368985E-03 9.684645E+01 -4.004271E-03 + 2.370005E+01 6.000000E+01 1 2.849452E+01 8.989124E+01 5.408464E-02 2.849447E+01 + 2.370005E+01 6.000000E+01 2 5.220984E+01 8.986960E+01 1.188247E-01 5.220970E+01 + 2.370005E+01 6.000000E+01 3 1.769851E+02 4.614007E-01 1.769794E+02 1.425239E+00 + 2.370005E+01 6.000000E+01 4 1.747380E+02 8.986960E+01 3.977008E-01 1.747376E+02 + 2.370005E+01 6.000000E+01 5 2.783364E+02 8.989124E+01 5.283985E-01 2.783359E+02 + 2.370005E+01 6.000000E+01 6 9.807465E+01 -2.358844E-03 9.807465E+01 -4.037693E-03 + 2.370005E+01 9.000000E+01 1 2.970911E-06 -9.006538E+01 -3.389921E-09 -2.970909E-06 + 2.370005E+01 9.000000E+01 2 6.065782E+01 8.986958E+01 1.380700E-01 6.065766E+01 + 2.370005E+01 9.000000E+01 3 1.781040E+02 4.627653E-01 1.780982E+02 1.438491E+00 + 2.370005E+01 9.000000E+01 4 2.040250E+02 8.987022E+01 4.621148E-01 2.040245E+02 + 2.370005E+01 9.000000E+01 5 1.341733E-04 -8.998154E+01 4.322765E-08 -1.341733E-04 + 2.370005E+01 9.000000E+01 6 8.451640E-06 1.799984E+02 -8.451640E-06 2.333156E-10 + 2.380005E+01 0.000000E+00 1 5.580989E+01 8.989221E+01 1.049980E-01 5.580980E+01 + 2.380005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.380005E+01 0.000000E+00 3 1.739525E+02 4.532427E-01 1.739470E+02 1.376050E+00 + 2.380005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.380005E+01 0.000000E+00 5 5.459833E+02 8.989221E+01 1.027143E+00 5.459824E+02 + 2.380005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.380005E+01 3.000000E+01 1 4.859989E+01 8.989223E+01 9.141497E-02 4.859980E+01 + 2.380005E+01 3.000000E+01 2 2.964947E+01 8.987101E+01 6.675254E-02 2.964939E+01 + 2.380005E+01 3.000000E+01 3 1.750398E+02 4.545767E-01 1.750343E+02 1.388727E+00 + 2.380005E+01 3.000000E+01 4 9.819201E+01 8.986970E+01 2.233101E-01 9.819176E+01 + 2.380005E+01 3.000000E+01 5 4.754251E+02 8.989223E+01 8.942596E-01 4.754243E+02 + 2.380005E+01 3.000000E+01 6 9.597267E+01 -2.321265E-03 9.597267E+01 -3.888210E-03 + 2.380005E+01 6.000000E+01 1 2.837053E+01 8.989227E+01 5.334353E-02 2.837048E+01 + 2.380005E+01 6.000000E+01 2 5.198251E+01 8.987097E+01 1.170637E-01 5.198238E+01 + 2.380005E+01 6.000000E+01 3 1.772378E+02 4.572474E-01 1.772321E+02 1.414426E+00 + 2.380005E+01 6.000000E+01 4 1.738934E+02 8.987096E+01 3.916194E-01 1.738930E+02 + 2.380005E+01 6.000000E+01 5 2.774833E+02 8.989225E+01 5.218289E-01 2.774828E+02 + 2.380005E+01 6.000000E+01 6 9.717832E+01 -2.311415E-03 9.717832E+01 -3.920348E-03 + 2.380005E+01 9.000000E+01 1 2.957657E-06 -9.006504E+01 -3.357362E-09 -2.957655E-06 + 2.380005E+01 9.000000E+01 2 6.039014E+01 8.987096E+01 1.360155E-01 6.038999E+01 + 2.380005E+01 9.000000E+01 3 1.783479E+02 4.585855E-01 1.783422E+02 1.427451E+00 + 2.380005E+01 9.000000E+01 4 2.030182E+02 8.987159E+01 4.550181E-01 2.030177E+02 + 2.380005E+01 9.000000E+01 5 1.336310E-04 -8.998180E+01 4.246865E-08 -1.336310E-04 + 2.380005E+01 9.000000E+01 6 8.373747E-06 1.799984E+02 -8.373747E-06 2.265489E-10 + 2.390005E+01 0.000000E+00 1 5.557702E+01 8.989321E+01 1.035810E-01 5.557692E+01 + 2.390005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.390005E+01 0.000000E+00 3 1.742278E+02 4.492277E-01 1.742224E+02 1.366019E+00 + 2.390005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.390005E+01 0.000000E+00 5 5.443948E+02 8.989322E+01 1.014572E+00 5.443939E+02 + 2.390005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.390005E+01 3.000000E+01 1 4.839457E+01 8.989324E+01 9.017714E-02 4.839449E+01 + 2.390005E+01 3.000000E+01 2 2.952438E+01 8.987235E+01 6.577675E-02 2.952431E+01 + 2.390005E+01 3.000000E+01 3 1.753066E+02 4.505365E-01 1.753012E+02 1.378483E+00 + 2.390005E+01 3.000000E+01 4 9.773938E+01 8.987107E+01 2.199414E-01 9.773914E+01 + 2.390005E+01 3.000000E+01 5 4.740217E+02 8.989324E+01 8.832666E-01 4.740209E+02 + 2.390005E+01 3.000000E+01 6 9.511114E+01 -2.274766E-03 9.511114E+01 -3.776117E-03 + 2.390005E+01 6.000000E+01 1 2.824776E+01 8.989327E+01 5.261603E-02 2.824771E+01 + 2.390005E+01 6.000000E+01 2 5.175714E+01 8.987232E+01 1.153386E-01 5.175701E+01 + 2.390005E+01 6.000000E+01 3 1.774868E+02 4.531532E-01 1.774813E+02 1.403731E+00 + 2.390005E+01 6.000000E+01 4 1.730580E+02 8.987231E+01 3.856652E-01 1.730576E+02 + 2.390005E+01 6.000000E+01 5 2.766343E+02 8.989326E+01 5.153677E-01 2.766338E+02 + 2.390005E+01 6.000000E+01 6 9.629453E+01 -2.265204E-03 9.629453E+01 -3.807030E-03 + 2.390005E+01 9.000000E+01 1 2.944529E-06 -9.006470E+01 -3.325086E-09 -2.944527E-06 + 2.390005E+01 9.000000E+01 2 6.012493E+01 8.987231E+01 1.340033E-01 6.012478E+01 + 2.390005E+01 9.000000E+01 3 1.785874E+02 4.544663E-01 1.785818E+02 1.416529E+00 + 2.390005E+01 9.000000E+01 4 2.020221E+02 8.987292E+01 4.480752E-01 2.020216E+02 + 2.390005E+01 9.000000E+01 5 1.330919E-04 -8.998204E+01 4.172722E-08 -1.330919E-04 + 2.390005E+01 9.000000E+01 6 8.296965E-06 1.799985E+02 -8.296965E-06 2.200141E-10 + 2.400006E+01 0.000000E+00 1 5.534610E+01 8.989421E+01 1.021894E-01 5.534601E+01 + 2.400006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.400006E+01 0.000000E+00 3 1.744997E+02 4.452660E-01 1.744944E+02 1.356086E+00 + 2.400006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.400006E+01 0.000000E+00 5 5.428163E+02 8.989422E+01 1.002187E+00 5.428154E+02 + 2.400006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.400006E+01 3.000000E+01 1 4.819088E+01 8.989423E+01 8.896141E-02 4.819080E+01 + 2.400006E+01 3.000000E+01 2 2.940030E+01 8.987368E+01 6.482036E-02 2.940022E+01 + 2.400006E+01 3.000000E+01 3 1.755704E+02 4.465468E-01 1.755651E+02 1.368332E+00 + 2.400006E+01 3.000000E+01 4 9.729131E+01 8.987241E+01 2.166428E-01 9.729107E+01 + 2.400006E+01 3.000000E+01 5 4.726164E+02 8.989423E+01 8.724545E-01 4.726156E+02 + 2.400006E+01 3.000000E+01 6 9.426125E+01 -2.229446E-03 9.426125E+01 -3.667816E-03 + 2.400006E+01 6.000000E+01 1 2.812609E+01 8.989427E+01 5.190174E-02 2.812604E+01 + 2.400006E+01 6.000000E+01 2 5.153378E+01 8.987364E+01 1.136480E-01 5.153366E+01 + 2.400006E+01 6.000000E+01 3 1.777336E+02 4.491123E-01 1.777282E+02 1.393149E+00 + 2.400006E+01 6.000000E+01 4 1.722303E+02 8.987364E+01 3.798343E-01 1.722299E+02 + 2.400006E+01 6.000000E+01 5 2.757869E+02 8.989425E+01 5.090078E-01 2.757864E+02 + 2.400006E+01 6.000000E+01 6 9.542294E+01 -2.220166E-03 9.542294E+01 -3.697563E-03 + 2.400006E+01 9.000000E+01 1 2.931508E-06 -9.006436E+01 -3.293080E-09 -2.931506E-06 + 2.400006E+01 9.000000E+01 2 5.986201E+01 8.987363E+01 1.320310E-01 5.986186E+01 + 2.400006E+01 9.000000E+01 3 1.788251E+02 4.504021E-01 1.788195E+02 1.405729E+00 + 2.400006E+01 9.000000E+01 4 2.010370E+02 8.987424E+01 4.412749E-01 2.010365E+02 + 2.400006E+01 9.000000E+01 5 1.325567E-04 -8.998228E+01 4.100292E-08 -1.325567E-04 + 2.400006E+01 9.000000E+01 6 8.221267E-06 1.799985E+02 -8.221267E-06 2.137008E-10 + 2.410006E+01 0.000000E+00 1 5.511711E+01 8.989520E+01 1.008234E-01 5.511702E+01 + 2.410006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.410006E+01 0.000000E+00 3 1.747693E+02 4.413574E-01 1.747641E+02 1.346259E+00 + 2.410006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.410006E+01 0.000000E+00 5 5.412387E+02 8.989520E+01 9.900017E-01 5.412378E+02 + 2.410006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.410006E+01 3.000000E+01 1 4.798917E+01 8.989522E+01 8.776800E-02 4.798909E+01 + 2.410006E+01 3.000000E+01 2 2.927723E+01 8.987498E+01 6.388288E-02 2.927716E+01 + 2.410006E+01 3.000000E+01 3 1.758313E+02 4.426152E-01 1.758261E+02 1.358300E+00 + 2.410006E+01 3.000000E+01 4 9.684742E+01 8.987375E+01 2.134103E-01 9.684718E+01 + 2.410006E+01 3.000000E+01 5 4.712179E+02 8.989522E+01 8.618144E-01 4.712171E+02 + 2.410006E+01 3.000000E+01 6 9.342292E+01 -2.185286E-03 9.342292E+01 -3.563191E-03 + 2.410006E+01 6.000000E+01 1 2.800544E+01 8.989525E+01 5.120069E-02 2.800540E+01 + 2.410006E+01 6.000000E+01 2 5.131229E+01 8.987495E+01 1.119914E-01 5.131217E+01 + 2.410006E+01 6.000000E+01 3 1.779765E+02 4.451326E-01 1.779711E+02 1.382691E+00 + 2.410006E+01 6.000000E+01 4 1.714108E+02 8.987495E+01 3.741245E-01 1.714104E+02 + 2.410006E+01 6.000000E+01 5 2.749439E+02 8.989523E+01 5.027539E-01 2.749435E+02 + 2.410006E+01 6.000000E+01 6 9.456345E+01 -2.176280E-03 9.456345E+01 -3.591827E-03 + 2.410006E+01 9.000000E+01 1 2.918614E-06 -9.006403E+01 -3.261367E-09 -2.918612E-06 + 2.410006E+01 9.000000E+01 2 5.960152E+01 8.987494E+01 1.300989E-01 5.960138E+01 + 2.410006E+01 9.000000E+01 3 1.790594E+02 4.463964E-01 1.790540E+02 1.395054E+00 + 2.410006E+01 9.000000E+01 4 2.000620E+02 8.987553E+01 4.346154E-01 2.000615E+02 + 2.410006E+01 9.000000E+01 5 1.320264E-04 -8.998251E+01 4.029528E-08 -1.320264E-04 + 2.410006E+01 9.000000E+01 6 8.146621E-06 1.799986E+02 -8.146621E-06 2.076021E-10 + 2.420006E+01 0.000000E+00 1 5.488992E+01 8.989616E+01 9.948167E-02 5.488983E+01 + 2.420006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.420006E+01 0.000000E+00 3 1.750341E+02 4.374979E-01 1.750291E+02 1.336509E+00 + 2.420006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.420006E+01 0.000000E+00 5 5.396603E+02 8.989616E+01 9.780313E-01 5.396594E+02 + 2.420006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.420006E+01 3.000000E+01 1 4.778897E+01 8.989618E+01 8.659603E-02 4.778889E+01 + 2.420006E+01 3.000000E+01 2 2.915520E+01 8.987626E+01 6.296390E-02 2.915514E+01 + 2.420006E+01 3.000000E+01 3 1.760889E+02 4.387318E-01 1.760838E+02 1.348355E+00 + 2.420006E+01 3.000000E+01 4 9.640749E+01 8.987505E+01 2.102454E-01 9.640726E+01 + 2.420006E+01 3.000000E+01 5 4.698246E+02 8.989618E+01 8.513460E-01 4.698238E+02 + 2.420006E+01 3.000000E+01 6 9.259603E+01 -2.142239E-03 9.259603E+01 -3.462085E-03 + 2.420006E+01 6.000000E+01 1 2.788586E+01 8.989622E+01 5.051244E-02 2.788581E+01 + 2.420006E+01 6.000000E+01 2 5.109282E+01 8.987624E+01 1.103676E-01 5.109270E+01 + 2.420006E+01 6.000000E+01 3 1.782167E+02 4.412003E-01 1.782114E+02 1.372326E+00 + 2.420006E+01 6.000000E+01 4 1.705998E+02 8.987624E+01 3.685305E-01 1.705994E+02 + 2.420006E+01 6.000000E+01 5 2.741026E+02 8.989620E+01 4.965967E-01 2.741021E+02 + 2.420006E+01 6.000000E+01 6 9.371589E+01 -2.133490E-03 9.371589E+01 -3.489644E-03 + 2.420006E+01 9.000000E+01 1 2.905833E-06 -9.006369E+01 -3.229919E-09 -2.905831E-06 + 2.420006E+01 9.000000E+01 2 5.934311E+01 8.987622E+01 1.282050E-01 5.934298E+01 + 2.420006E+01 9.000000E+01 3 1.792914E+02 4.424344E-01 1.792861E+02 1.384463E+00 + 2.420006E+01 9.000000E+01 4 1.990962E+02 8.987681E+01 4.280929E-01 1.990957E+02 + 2.420006E+01 9.000000E+01 5 1.314999E-04 -8.998274E+01 3.960369E-08 -1.314999E-04 + 2.420006E+01 9.000000E+01 6 8.073012E-06 1.799986E+02 -8.073012E-06 2.017078E-10 + 2.430006E+01 0.000000E+00 1 5.466449E+01 8.989711E+01 9.816404E-02 5.466441E+01 + 2.430006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.430006E+01 0.000000E+00 3 1.752979E+02 4.336909E-01 1.752929E+02 1.326876E+00 + 2.430006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.430006E+01 0.000000E+00 5 5.380936E+02 8.989712E+01 9.662327E-01 5.380928E+02 + 2.430006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.430006E+01 3.000000E+01 1 4.759039E+01 8.989713E+01 8.544528E-02 4.759032E+01 + 2.430006E+01 3.000000E+01 2 2.903419E+01 8.987753E+01 6.206277E-02 2.903412E+01 + 2.430006E+01 3.000000E+01 3 1.763440E+02 4.348980E-01 1.763389E+02 1.338509E+00 + 2.430006E+01 3.000000E+01 4 9.597160E+01 8.987634E+01 2.071419E-01 9.597138E+01 + 2.430006E+01 3.000000E+01 5 4.684349E+02 8.989713E+01 8.410389E-01 4.684341E+02 + 2.430006E+01 3.000000E+01 6 9.178020E+01 -2.100270E-03 9.178020E+01 -3.364352E-03 + 2.430006E+01 6.000000E+01 1 2.776723E+01 8.989717E+01 4.983657E-02 2.776718E+01 + 2.430006E+01 6.000000E+01 2 5.087517E+01 8.987749E+01 1.087756E-01 5.087505E+01 + 2.430006E+01 6.000000E+01 3 1.784546E+02 4.373234E-01 1.784494E+02 1.362083E+00 + 2.430006E+01 6.000000E+01 4 1.697960E+02 8.987749E+01 3.630520E-01 1.697956E+02 + 2.430006E+01 6.000000E+01 5 2.732666E+02 8.989715E+01 4.905472E-01 2.732661E+02 + 2.430006E+01 6.000000E+01 6 9.287992E+01 -2.091775E-03 9.287992E+01 -3.390893E-03 + 2.430006E+01 9.000000E+01 1 2.893164E-06 -9.006335E+01 -3.198767E-09 -2.893162E-06 + 2.430006E+01 9.000000E+01 2 5.908727E+01 8.987749E+01 1.263492E-01 5.908714E+01 + 2.430006E+01 9.000000E+01 3 1.795202E+02 4.385376E-01 1.795150E+02 1.374021E+00 + 2.430006E+01 9.000000E+01 4 1.981402E+02 8.987806E+01 4.217054E-01 1.981397E+02 + 2.430006E+01 9.000000E+01 5 1.309774E-04 -8.998297E+01 3.892789E-08 -1.309774E-04 + 2.430006E+01 9.000000E+01 6 8.000432E-06 1.799986E+02 -8.000432E-06 1.960112E-10 + 2.440006E+01 0.000000E+00 1 5.444105E+01 8.989805E+01 9.686979E-02 5.444096E+01 + 2.440006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.440006E+01 0.000000E+00 3 1.755571E+02 4.299337E-01 1.755522E+02 1.317326E+00 + 2.440006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.440006E+01 0.000000E+00 5 5.365279E+02 8.989806E+01 9.546290E-01 5.365270E+02 + 2.440006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.440006E+01 3.000000E+01 1 4.739366E+01 8.989807E+01 8.431499E-02 4.739359E+01 + 2.440006E+01 3.000000E+01 2 2.891417E+01 8.987877E+01 6.117931E-02 2.891411E+01 + 2.440006E+01 3.000000E+01 3 1.765949E+02 4.311201E-01 1.765899E+02 1.328769E+00 + 2.440006E+01 3.000000E+01 4 9.553999E+01 8.987760E+01 2.041023E-01 9.553976E+01 + 2.440006E+01 3.000000E+01 5 4.670530E+02 8.989807E+01 8.308989E-01 4.670522E+02 + 2.440006E+01 3.000000E+01 6 9.097534E+01 -2.059355E-03 9.097534E+01 -3.269884E-03 + 2.440006E+01 6.000000E+01 1 2.764974E+01 8.989810E+01 4.917292E-02 2.764970E+01 + 2.440006E+01 6.000000E+01 2 5.065941E+01 8.987874E+01 1.072153E-01 5.065929E+01 + 2.440006E+01 6.000000E+01 3 1.786896E+02 4.334970E-01 1.786844E+02 1.351943E+00 + 2.440006E+01 6.000000E+01 4 1.690008E+02 8.987873E+01 3.576838E-01 1.690005E+02 + 2.440006E+01 6.000000E+01 5 2.724322E+02 8.989809E+01 4.845830E-01 2.724317E+02 + 2.440006E+01 6.000000E+01 6 9.205544E+01 -2.051094E-03 9.205544E+01 -3.295432E-03 + 2.440006E+01 9.000000E+01 1 2.880607E-06 -9.006301E+01 -3.167894E-09 -2.880605E-06 + 2.440006E+01 9.000000E+01 2 5.883351E+01 8.987872E+01 1.245295E-01 5.883337E+01 + 2.440006E+01 9.000000E+01 3 1.797462E+02 4.346892E-01 1.797410E+02 1.363678E+00 + 2.440006E+01 9.000000E+01 4 1.971942E+02 8.987930E+01 4.154466E-01 1.971937E+02 + 2.440006E+01 9.000000E+01 5 1.304596E-04 -8.998319E+01 3.826728E-08 -1.304596E-04 + 2.440006E+01 9.000000E+01 6 7.928846E-06 1.799986E+02 -7.928846E-06 1.905042E-10 + 2.450006E+01 0.000000E+00 1 5.421926E+01 8.989898E+01 9.559872E-02 5.421917E+01 + 2.450006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.450006E+01 0.000000E+00 3 1.758142E+02 4.262261E-01 1.758094E+02 1.307878E+00 + 2.450006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.450006E+01 0.000000E+00 5 5.349677E+02 8.989899E+01 9.431933E-01 5.349668E+02 + 2.450006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.450006E+01 3.000000E+01 1 4.719819E+01 8.989900E+01 8.320457E-02 4.719812E+01 + 2.450006E+01 3.000000E+01 2 2.879515E+01 8.987999E+01 6.031291E-02 2.879509E+01 + 2.450006E+01 3.000000E+01 3 1.768436E+02 4.273906E-01 1.768386E+02 1.319130E+00 + 2.450006E+01 3.000000E+01 4 9.511223E+01 8.987885E+01 2.011238E-01 9.511201E+01 + 2.450006E+01 3.000000E+01 5 4.656710E+02 8.989900E+01 8.209152E-01 4.656702E+02 + 2.450006E+01 3.000000E+01 6 9.018147E+01 -2.019447E-03 9.018147E+01 -3.178535E-03 + 2.450006E+01 6.000000E+01 1 2.753310E+01 8.989903E+01 4.852091E-02 2.753306E+01 + 2.450006E+01 6.000000E+01 2 5.044561E+01 8.987997E+01 1.056854E-01 5.044550E+01 + 2.450006E+01 6.000000E+01 3 1.789222E+02 4.297256E-01 1.789172E+02 1.341926E+00 + 2.450006E+01 6.000000E+01 4 1.682136E+02 8.987997E+01 3.524255E-01 1.682132E+02 + 2.450006E+01 6.000000E+01 5 2.716010E+02 8.989901E+01 4.787209E-01 2.716006E+02 + 2.450006E+01 6.000000E+01 6 9.124196E+01 -2.011430E-03 9.124196E+01 -3.203146E-03 + 2.450006E+01 9.000000E+01 1 2.868165E-06 -9.006267E+01 -3.137320E-09 -2.868163E-06 + 2.450006E+01 9.000000E+01 2 5.858204E+01 8.987995E+01 1.227459E-01 5.858191E+01 + 2.450006E+01 9.000000E+01 3 1.799697E+02 4.308933E-01 1.799646E+02 1.353451E+00 + 2.450006E+01 9.000000E+01 4 1.962583E+02 8.988050E+01 4.093162E-01 1.962579E+02 + 2.450006E+01 9.000000E+01 5 1.299453E-04 -8.998341E+01 3.762150E-08 -1.299453E-04 + 2.450006E+01 9.000000E+01 6 7.858253E-06 1.799987E+02 -7.858253E-06 1.851799E-10 + 2.460006E+01 0.000000E+00 1 5.399934E+01 8.989989E+01 9.434960E-02 5.399926E+01 + 2.460006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.460006E+01 0.000000E+00 3 1.760677E+02 4.225669E-01 1.760629E+02 1.298520E+00 + 2.460006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.460006E+01 0.000000E+00 5 5.334150E+02 8.989990E+01 9.319467E-01 5.334142E+02 + 2.460006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.460006E+01 3.000000E+01 1 4.700480E+01 8.989991E+01 8.211408E-02 4.700473E+01 + 2.460006E+01 3.000000E+01 2 2.867704E+01 8.988120E+01 5.946324E-02 2.867698E+01 + 2.460006E+01 3.000000E+01 3 1.770899E+02 4.237058E-01 1.770851E+02 1.309579E+00 + 2.460006E+01 3.000000E+01 4 9.468811E+01 8.988007E+01 1.982032E-01 9.468790E+01 + 2.460006E+01 3.000000E+01 5 4.642968E+02 8.989991E+01 8.110967E-01 4.642961E+02 + 2.460006E+01 3.000000E+01 6 8.939787E+01 -1.980525E-03 8.939787E+01 -3.090188E-03 + 2.460006E+01 6.000000E+01 1 2.741760E+01 8.989994E+01 4.788094E-02 2.741756E+01 + 2.460006E+01 6.000000E+01 2 5.023351E+01 8.988116E+01 1.041852E-01 5.023340E+01 + 2.460006E+01 6.000000E+01 3 1.791508E+02 4.259996E-01 1.791459E+02 1.331991E+00 + 2.460006E+01 6.000000E+01 4 1.674326E+02 8.988116E+01 3.472713E-01 1.674323E+02 + 2.460006E+01 6.000000E+01 5 2.707739E+02 8.989993E+01 4.729458E-01 2.707735E+02 + 2.460006E+01 6.000000E+01 6 9.043964E+01 -1.972735E-03 9.043964E+01 -3.113902E-03 + 2.460006E+01 9.000000E+01 1 2.855832E-06 -9.006233E+01 -3.107019E-09 -2.855830E-06 + 2.460006E+01 9.000000E+01 2 5.833270E+01 8.988116E+01 1.209969E-01 5.833257E+01 + 2.460006E+01 9.000000E+01 3 1.801916E+02 4.271433E-01 1.801866E+02 1.343326E+00 + 2.460006E+01 9.000000E+01 4 1.953301E+02 8.988170E+01 4.033084E-01 1.953297E+02 + 2.460006E+01 9.000000E+01 5 1.294351E-04 -8.998363E+01 3.699022E-08 -1.294351E-04 + 2.460006E+01 9.000000E+01 6 7.788616E-06 1.799987E+02 -7.788616E-06 1.800306E-10 + 2.470006E+01 0.000000E+00 1 5.378117E+01 8.990079E+01 9.312256E-02 5.378109E+01 + 2.470006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.470006E+01 0.000000E+00 3 1.763189E+02 4.189522E-01 1.763141E+02 1.289249E+00 + 2.470006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.470006E+01 0.000000E+00 5 5.318651E+02 8.990079E+01 9.208829E-01 5.318643E+02 + 2.470006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.470006E+01 3.000000E+01 1 4.681253E+01 8.990081E+01 8.104297E-02 4.681247E+01 + 2.470006E+01 3.000000E+01 2 2.856001E+01 8.988238E+01 5.862991E-02 2.855994E+01 + 2.470006E+01 3.000000E+01 3 1.773324E+02 4.200728E-01 1.773277E+02 1.300128E+00 + 2.470006E+01 3.000000E+01 4 9.426814E+01 8.988127E+01 1.953418E-01 9.426794E+01 + 2.470006E+01 3.000000E+01 5 4.629255E+02 8.990081E+01 8.014228E-01 4.629248E+02 + 2.470006E+01 3.000000E+01 6 8.862480E+01 -1.942562E-03 8.862480E+01 -3.004744E-03 + 2.470006E+01 6.000000E+01 1 2.730299E+01 8.990084E+01 4.725219E-02 2.730295E+01 + 2.470006E+01 6.000000E+01 2 5.002332E+01 8.988235E+01 1.027142E-01 5.002321E+01 + 2.470006E+01 6.000000E+01 3 1.793775E+02 4.223199E-01 1.793727E+02 1.322157E+00 + 2.470006E+01 6.000000E+01 4 1.666603E+02 8.988235E+01 3.422202E-01 1.666600E+02 + 2.470006E+01 6.000000E+01 5 2.699490E+02 8.990083E+01 4.672738E-01 2.699486E+02 + 2.470006E+01 6.000000E+01 6 8.964802E+01 -1.934987E-03 8.964802E+01 -3.027584E-03 + 2.470006E+01 9.000000E+01 1 2.843609E-06 -9.006200E+01 -3.077015E-09 -2.843607E-06 + 2.470006E+01 9.000000E+01 2 5.808551E+01 8.988234E+01 1.192822E-01 5.808539E+01 + 2.470006E+01 9.000000E+01 3 1.804100E+02 4.234435E-01 1.804051E+02 1.333305E+00 + 2.470006E+01 9.000000E+01 4 1.944115E+02 8.988287E+01 3.974206E-01 1.944111E+02 + 2.470006E+01 9.000000E+01 5 1.289278E-04 -8.998383E+01 3.637289E-08 -1.289278E-04 + 2.470006E+01 9.000000E+01 6 7.719932E-06 1.799987E+02 -7.719932E-06 1.750500E-10 + 2.480006E+01 0.000000E+00 1 5.356469E+01 8.990168E+01 9.191687E-02 5.356461E+01 + 2.480006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.480006E+01 0.000000E+00 3 1.765668E+02 4.153858E-01 1.765622E+02 1.280072E+00 + 2.480006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.480006E+01 0.000000E+00 5 5.303159E+02 8.990168E+01 9.099780E-01 5.303151E+02 + 2.480006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.480006E+01 3.000000E+01 1 4.662207E+01 8.990170E+01 7.999029E-02 4.662200E+01 + 2.480006E+01 3.000000E+01 2 2.844382E+01 8.988355E+01 5.781246E-02 2.844377E+01 + 2.480006E+01 3.000000E+01 3 1.775724E+02 4.164839E-01 1.775677E+02 1.290765E+00 + 2.480006E+01 3.000000E+01 4 9.385210E+01 8.988245E+01 1.925367E-01 9.385190E+01 + 2.480006E+01 3.000000E+01 5 4.615573E+02 8.990170E+01 7.919074E-01 4.615566E+02 + 2.480006E+01 3.000000E+01 6 8.786177E+01 -1.905528E-03 8.786177E+01 -2.922084E-03 + 2.480006E+01 6.000000E+01 1 2.718941E+01 8.990173E+01 4.663461E-02 2.718937E+01 + 2.480006E+01 6.000000E+01 2 4.981487E+01 8.988352E+01 1.012714E-01 4.981477E+01 + 2.480006E+01 6.000000E+01 3 1.796018E+02 4.186890E-01 1.795970E+02 1.312429E+00 + 2.480006E+01 6.000000E+01 4 1.658963E+02 8.988352E+01 3.372680E-01 1.658959E+02 + 2.480006E+01 6.000000E+01 5 2.691268E+02 8.990171E+01 4.616813E-01 2.691264E+02 + 2.480006E+01 6.000000E+01 6 8.886719E+01 -1.898159E-03 8.886719E+01 -2.944092E-03 + 2.480006E+01 9.000000E+01 1 2.831491E-06 -9.006167E+01 -3.047292E-09 -2.831489E-06 + 2.480006E+01 9.000000E+01 2 5.784065E+01 8.988351E+01 1.176006E-01 5.784053E+01 + 2.480006E+01 9.000000E+01 3 1.806254E+02 4.197936E-01 1.806206E+02 1.323391E+00 + 2.480006E+01 9.000000E+01 4 1.935027E+02 8.988403E+01 3.916526E-01 1.935023E+02 + 2.480006E+01 9.000000E+01 5 1.284257E-04 -8.998404E+01 3.576919E-08 -1.284257E-04 + 2.480006E+01 9.000000E+01 6 7.652169E-06 1.799987E+02 -7.652169E-06 1.702321E-10 + 2.490006E+01 0.000000E+00 1 5.335005E+01 8.990256E+01 9.073237E-02 5.334998E+01 + 2.490006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.490006E+01 0.000000E+00 3 1.768118E+02 4.118660E-01 1.768072E+02 1.270986E+00 + 2.490006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.490006E+01 0.000000E+00 5 5.287761E+02 8.990257E+01 8.992478E-01 5.287753E+02 + 2.490006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.490006E+01 3.000000E+01 1 4.643299E+01 8.990257E+01 7.895582E-02 4.643292E+01 + 2.490006E+01 3.000000E+01 2 2.832863E+01 8.988470E+01 5.701044E-02 2.832857E+01 + 2.490006E+01 3.000000E+01 3 1.778103E+02 4.129422E-01 1.778057E+02 1.281503E+00 + 2.490006E+01 3.000000E+01 4 9.343965E+01 8.988363E+01 1.897852E-01 9.343946E+01 + 2.490006E+01 3.000000E+01 5 4.601959E+02 8.990257E+01 7.825330E-01 4.601952E+02 + 2.490006E+01 3.000000E+01 6 8.710892E+01 -1.869385E-03 8.710892E+01 -2.842095E-03 + 2.490006E+01 6.000000E+01 1 2.707679E+01 8.990260E+01 4.602775E-02 2.707675E+01 + 2.490006E+01 6.000000E+01 2 4.960810E+01 8.988467E+01 9.985618E-02 4.960800E+01 + 2.490006E+01 6.000000E+01 3 1.798236E+02 4.151099E-01 1.798188E+02 1.302817E+00 + 2.490006E+01 6.000000E+01 4 1.651373E+02 8.988467E+01 3.324157E-01 1.651370E+02 + 2.490006E+01 6.000000E+01 5 2.683115E+02 8.990259E+01 4.561692E-01 2.683111E+02 + 2.490006E+01 6.000000E+01 6 8.809652E+01 -1.862227E-03 8.809652E+01 -2.863312E-03 + 2.490006E+01 9.000000E+01 1 2.819473E-06 -9.006133E+01 -3.017858E-09 -2.819471E-06 + 2.490006E+01 9.000000E+01 2 5.759768E+01 8.988466E+01 1.159510E-01 5.759756E+01 + 2.490006E+01 9.000000E+01 3 1.808393E+02 4.161923E-01 1.808345E+02 1.313591E+00 + 2.490006E+01 9.000000E+01 4 1.926020E+02 8.988518E+01 3.859954E-01 1.926016E+02 + 2.490006E+01 9.000000E+01 5 1.279273E-04 -8.998425E+01 3.517875E-08 -1.279273E-04 + 2.490006E+01 9.000000E+01 6 7.585311E-06 1.799987E+02 -7.585311E-06 1.655704E-10 + 2.500006E+01 0.000000E+00 1 5.313704E+01 8.990343E+01 8.956819E-02 5.313696E+01 + 2.500006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.500006E+01 0.000000E+00 3 1.770543E+02 4.083896E-01 1.770498E+02 1.261987E+00 + 2.500006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.500006E+01 0.000000E+00 5 5.272414E+02 8.990343E+01 8.886803E-01 5.272407E+02 + 2.500006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.500006E+01 3.000000E+01 1 4.624553E+01 8.990343E+01 7.794006E-02 4.624546E+01 + 2.500006E+01 3.000000E+01 2 2.821434E+01 8.988583E+01 5.622368E-02 2.821428E+01 + 2.500006E+01 3.000000E+01 3 1.780443E+02 4.094484E-01 1.780397E+02 1.272333E+00 + 2.500006E+01 3.000000E+01 4 9.303102E+01 8.988478E+01 1.870886E-01 9.303083E+01 + 2.500006E+01 3.000000E+01 5 4.588366E+02 8.990343E+01 7.733034E-01 4.588360E+02 + 2.500006E+01 3.000000E+01 6 8.636576E+01 -1.834118E-03 8.636576E+01 -2.764689E-03 + 2.500006E+01 6.000000E+01 1 2.696503E+01 8.990347E+01 4.543158E-02 2.696499E+01 + 2.500006E+01 6.000000E+01 2 4.940303E+01 8.988580E+01 9.846783E-02 4.940293E+01 + 2.500006E+01 6.000000E+01 3 1.800412E+02 4.115758E-01 1.800365E+02 1.293288E+00 + 2.500006E+01 6.000000E+01 4 1.643874E+02 8.988580E+01 3.276581E-01 1.643871E+02 + 2.500006E+01 6.000000E+01 5 2.674931E+02 8.990345E+01 4.507528E-01 2.674927E+02 + 2.500006E+01 6.000000E+01 6 8.733630E+01 -1.827158E-03 8.733630E+01 -2.785148E-03 + 2.500006E+01 9.000000E+01 1 2.807568E-06 -9.006100E+01 -2.988725E-09 -2.807566E-06 + 2.500006E+01 9.000000E+01 2 5.735681E+01 8.988579E+01 1.143331E-01 5.735670E+01 + 2.500006E+01 9.000000E+01 3 1.810499E+02 4.126362E-01 1.810452E+02 1.303885E+00 + 2.500006E+01 9.000000E+01 4 1.917110E+02 8.988629E+01 3.804510E-01 1.917106E+02 + 2.500006E+01 9.000000E+01 5 1.274322E-04 -8.998444E+01 3.460135E-08 -1.274322E-04 + 2.500006E+01 9.000000E+01 6 7.519363E-06 1.799988E+02 -7.519363E-06 1.610591E-10 + 2.510006E+01 0.000000E+00 1 5.292557E+01 8.990427E+01 8.842468E-02 5.292550E+01 + 2.510006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.510006E+01 0.000000E+00 3 1.772938E+02 4.049586E-01 1.772893E+02 1.253077E+00 + 2.510006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.510006E+01 0.000000E+00 5 5.257103E+02 8.990428E+01 8.782778E-01 5.257095E+02 + 2.510006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.510006E+01 3.000000E+01 1 4.605963E+01 8.990429E+01 7.694146E-02 4.605957E+01 + 2.510006E+01 3.000000E+01 2 2.810098E+01 8.988694E+01 5.545168E-02 2.810092E+01 + 2.510006E+01 3.000000E+01 3 1.782761E+02 4.060007E-01 1.782716E+02 1.263263E+00 + 2.510006E+01 3.000000E+01 4 9.262593E+01 8.988591E+01 1.844436E-01 9.262575E+01 + 2.510006E+01 3.000000E+01 5 4.574836E+02 8.990428E+01 7.642243E-01 4.574829E+02 + 2.510006E+01 3.000000E+01 6 8.563242E+01 -1.799699E-03 8.563242E+01 -2.689772E-03 + 2.510006E+01 6.000000E+01 1 2.685440E+01 8.990432E+01 4.484583E-02 2.685436E+01 + 2.510006E+01 6.000000E+01 2 4.919981E+01 8.988692E+01 9.710602E-02 4.919972E+01 + 2.510006E+01 6.000000E+01 3 1.802585E+02 4.080828E-01 1.802540E+02 1.283860E+00 + 2.510006E+01 6.000000E+01 4 1.636436E+02 8.988691E+01 3.229948E-01 1.636433E+02 + 2.510006E+01 6.000000E+01 5 2.666844E+02 8.990430E+01 4.454191E-01 2.666840E+02 + 2.510006E+01 6.000000E+01 6 8.658608E+01 -1.792929E-03 8.658608E+01 -2.709497E-03 + 2.510006E+01 9.000000E+01 1 2.795762E-06 -9.006066E+01 -2.959867E-09 -2.795760E-06 + 2.510006E+01 9.000000E+01 2 5.711811E+01 8.988690E+01 1.127463E-01 5.711800E+01 + 2.510006E+01 9.000000E+01 3 1.812591E+02 4.091276E-01 1.812544E+02 1.294292E+00 + 2.510006E+01 9.000000E+01 4 1.908277E+02 8.988740E+01 3.750165E-01 1.908274E+02 + 2.510006E+01 9.000000E+01 5 1.269409E-04 -8.998463E+01 3.403653E-08 -1.269409E-04 + 2.510006E+01 9.000000E+01 6 7.454297E-06 1.799988E+02 -7.454297E-06 1.566928E-10 + 2.520006E+01 0.000000E+00 1 5.271600E+01 8.990512E+01 8.730014E-02 5.271592E+01 + 2.520006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.520006E+01 0.000000E+00 3 1.775309E+02 4.015695E-01 1.775265E+02 1.244252E+00 + 2.520006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.520006E+01 0.000000E+00 5 5.241855E+02 8.990512E+01 8.680288E-01 5.241848E+02 + 2.520006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.520006E+01 3.000000E+01 1 4.587526E+01 8.990513E+01 7.595998E-02 4.587519E+01 + 2.520006E+01 3.000000E+01 2 2.798850E+01 8.988804E+01 5.469400E-02 2.798845E+01 + 2.520006E+01 3.000000E+01 3 1.785062E+02 4.025902E-01 1.785018E+02 1.254268E+00 + 2.520006E+01 3.000000E+01 4 9.222443E+01 8.988702E+01 1.818499E-01 9.222426E+01 + 2.520006E+01 3.000000E+01 5 4.561398E+02 8.990513E+01 7.552798E-01 4.561392E+02 + 2.520006E+01 3.000000E+01 6 8.490846E+01 -1.766103E-03 8.490846E+01 -2.617246E-03 + 2.520006E+01 6.000000E+01 1 2.674450E+01 8.990516E+01 4.427037E-02 2.674446E+01 + 2.520006E+01 6.000000E+01 2 4.899820E+01 8.988802E+01 9.576986E-02 4.899810E+01 + 2.520006E+01 6.000000E+01 3 1.804727E+02 4.046407E-01 1.804682E+02 1.274544E+00 + 2.520006E+01 6.000000E+01 4 1.629073E+02 8.988801E+01 3.184209E-01 1.629070E+02 + 2.520006E+01 6.000000E+01 5 2.658757E+02 8.990514E+01 4.401714E-01 2.658753E+02 + 2.520006E+01 6.000000E+01 6 8.584565E+01 -1.759518E-03 8.584565E+01 -2.636266E-03 + 2.520006E+01 9.000000E+01 1 2.784061E-06 -9.006033E+01 -2.931307E-09 -2.784060E-06 + 2.520006E+01 9.000000E+01 2 5.688136E+01 8.988800E+01 1.111894E-01 5.688126E+01 + 2.520006E+01 9.000000E+01 3 1.814655E+02 4.056632E-01 1.814610E+02 1.284794E+00 + 2.520006E+01 9.000000E+01 4 1.899537E+02 8.988850E+01 3.696886E-01 1.899533E+02 + 2.520006E+01 9.000000E+01 5 1.264529E-04 -8.998483E+01 3.348378E-08 -1.264529E-04 + 2.520006E+01 9.000000E+01 6 7.390084E-06 1.799988E+02 -7.390084E-06 1.524657E-10 + 2.530006E+01 0.000000E+00 1 5.250806E+01 8.990594E+01 8.619491E-02 5.250799E+01 + 2.530006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.530006E+01 0.000000E+00 3 1.777646E+02 3.982247E-01 1.777604E+02 1.235514E+00 + 2.530006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.530006E+01 0.000000E+00 5 5.226671E+02 8.990595E+01 8.579420E-01 5.226663E+02 + 2.530006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.530006E+01 3.000000E+01 1 4.569215E+01 8.990596E+01 7.499533E-02 4.569209E+01 + 2.530006E+01 3.000000E+01 2 2.787701E+01 8.988911E+01 5.395045E-02 2.787696E+01 + 2.530006E+01 3.000000E+01 3 1.787324E+02 3.992268E-01 1.787280E+02 1.245365E+00 + 2.530006E+01 3.000000E+01 4 9.182629E+01 8.988811E+01 1.793063E-01 9.182612E+01 + 2.530006E+01 3.000000E+01 5 4.547971E+02 8.990596E+01 7.464731E-01 4.547965E+02 + 2.530006E+01 3.000000E+01 6 8.419390E+01 -1.733304E-03 8.419390E+01 -2.547023E-03 + 2.530006E+01 6.000000E+01 1 2.663543E+01 8.990598E+01 4.370455E-02 2.663539E+01 + 2.530006E+01 6.000000E+01 2 4.879833E+01 8.988909E+01 9.445865E-02 4.879824E+01 + 2.530006E+01 6.000000E+01 3 1.806845E+02 4.012356E-01 1.806801E+02 1.265302E+00 + 2.530006E+01 6.000000E+01 4 1.621776E+02 8.988909E+01 3.139356E-01 1.621773E+02 + 2.530006E+01 6.000000E+01 5 2.650708E+02 8.990598E+01 4.350087E-01 2.650704E+02 + 2.530006E+01 6.000000E+01 6 8.511478E+01 -1.726902E-03 8.511478E+01 -2.565370E-03 + 2.530006E+01 9.000000E+01 1 2.772455E-06 -9.005999E+01 -2.903029E-09 -2.772453E-06 + 2.530006E+01 9.000000E+01 2 5.664659E+01 8.988908E+01 1.096615E-01 5.664648E+01 + 2.530006E+01 9.000000E+01 3 1.816694E+02 4.022422E-01 1.816649E+02 1.275391E+00 + 2.530006E+01 9.000000E+01 4 1.890861E+02 8.988956E+01 3.644627E-01 1.890857E+02 + 2.530006E+01 9.000000E+01 5 1.259696E-04 -8.998502E+01 3.294310E-08 -1.259696E-04 + 2.530006E+01 9.000000E+01 6 7.326716E-06 1.799988E+02 -7.326716E-06 1.483733E-10 + 2.540006E+01 0.000000E+00 1 5.230154E+01 8.990676E+01 8.510897E-02 5.230147E+01 + 2.540006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.540006E+01 0.000000E+00 3 1.779963E+02 3.949230E-01 1.779921E+02 1.226866E+00 + 2.540006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.540006E+01 0.000000E+00 5 5.211514E+02 8.990677E+01 8.480092E-01 5.211507E+02 + 2.540006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.540006E+01 3.000000E+01 1 4.551067E+01 8.990678E+01 7.404727E-02 4.551060E+01 + 2.540006E+01 3.000000E+01 2 2.776632E+01 8.989018E+01 5.322068E-02 2.776627E+01 + 2.540006E+01 3.000000E+01 3 1.789560E+02 3.959090E-01 1.789518E+02 1.236561E+00 + 2.540006E+01 3.000000E+01 4 9.143183E+01 8.988921E+01 1.768100E-01 9.143166E+01 + 2.540006E+01 3.000000E+01 5 4.534624E+02 8.990678E+01 7.377992E-01 4.534618E+02 + 2.540006E+01 3.000000E+01 6 8.348849E+01 -1.701282E-03 8.348849E+01 -2.479021E-03 + 2.540006E+01 6.000000E+01 1 2.652739E+01 8.990681E+01 4.314886E-02 2.652736E+01 + 2.540006E+01 6.000000E+01 2 4.860004E+01 8.989016E+01 9.317198E-02 4.859996E+01 + 2.540006E+01 6.000000E+01 3 1.808939E+02 3.978804E-01 1.808895E+02 1.256175E+00 + 2.540006E+01 6.000000E+01 4 1.614544E+02 8.989015E+01 3.095352E-01 1.614541E+02 + 2.540006E+01 6.000000E+01 5 2.642698E+02 8.990679E+01 4.299184E-01 2.642694E+02 + 2.540006E+01 6.000000E+01 6 8.439370E+01 -1.695051E-03 8.439370E+01 -2.496722E-03 + 2.540006E+01 9.000000E+01 1 2.760949E-06 -9.005966E+01 -2.875039E-09 -2.760948E-06 + 2.540006E+01 9.000000E+01 2 5.641391E+01 8.989014E+01 1.081625E-01 5.641381E+01 + 2.540006E+01 9.000000E+01 3 1.818706E+02 3.988698E-01 1.818662E+02 1.266098E+00 + 2.540006E+01 9.000000E+01 4 1.882291E+02 8.989062E+01 3.593362E-01 1.882288E+02 + 2.540006E+01 9.000000E+01 5 1.254894E-04 -8.998520E+01 3.241390E-08 -1.254894E-04 + 2.540006E+01 9.000000E+01 6 7.264190E-06 1.799989E+02 -7.264190E-06 1.444104E-10 + 2.550006E+01 0.000000E+00 1 5.209661E+01 8.990757E+01 8.404067E-02 5.209655E+01 + 2.550006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.550006E+01 0.000000E+00 3 1.782248E+02 3.916592E-01 1.782206E+02 1.218289E+00 + 2.550006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.550006E+01 0.000000E+00 5 5.196445E+02 8.990758E+01 8.382323E-01 5.196438E+02 + 2.550006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.550006E+01 3.000000E+01 1 4.533051E+01 8.990759E+01 7.311536E-02 4.533046E+01 + 2.550006E+01 3.000000E+01 2 2.765651E+01 8.989123E+01 5.250428E-02 2.765646E+01 + 2.550006E+01 3.000000E+01 3 1.791780E+02 3.926268E-01 1.791738E+02 1.227831E+00 + 2.550006E+01 3.000000E+01 4 9.104112E+01 8.989027E+01 1.743610E-01 9.104095E+01 + 2.550006E+01 3.000000E+01 5 4.521271E+02 8.990759E+01 7.292583E-01 4.521265E+02 + 2.550006E+01 3.000000E+01 6 8.279195E+01 -1.670009E-03 8.279195E+01 -2.413150E-03 + 2.550006E+01 6.000000E+01 1 2.642026E+01 8.990761E+01 4.260239E-02 2.642022E+01 + 2.550006E+01 6.000000E+01 2 4.840344E+01 8.989120E+01 9.190919E-02 4.840335E+01 + 2.550006E+01 6.000000E+01 3 1.811003E+02 3.945653E-01 1.810961E+02 1.247131E+00 + 2.550006E+01 6.000000E+01 4 1.607382E+02 8.989120E+01 3.052194E-01 1.607379E+02 + 2.550006E+01 6.000000E+01 5 2.634714E+02 8.990760E+01 4.249104E-01 2.634711E+02 + 2.550006E+01 6.000000E+01 6 8.368171E+01 -1.663949E-03 8.368171E+01 -2.430232E-03 + 2.550006E+01 9.000000E+01 1 2.749541E-06 -9.005933E+01 -2.847323E-09 -2.749540E-06 + 2.550006E+01 9.000000E+01 2 5.618304E+01 8.989120E+01 1.066911E-01 5.618293E+01 + 2.550006E+01 9.000000E+01 3 1.820701E+02 3.955380E-01 1.820657E+02 1.256900E+00 + 2.550006E+01 9.000000E+01 4 1.873790E+02 8.989166E+01 3.543107E-01 1.873787E+02 + 2.550006E+01 9.000000E+01 5 1.250131E-04 -8.998538E+01 3.189593E-08 -1.250131E-04 + 2.550006E+01 9.000000E+01 6 7.202465E-06 1.799989E+02 -7.202465E-06 1.405721E-10 + 2.560006E+01 0.000000E+00 1 5.189355E+01 8.990837E+01 8.299110E-02 5.189349E+01 + 2.560006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.560006E+01 0.000000E+00 3 1.784516E+02 3.884348E-01 1.784475E+02 1.209798E+00 + 2.560006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.560006E+01 0.000000E+00 5 5.181401E+02 8.990838E+01 8.285958E-01 5.181395E+02 + 2.560006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.560006E+01 3.000000E+01 1 4.515197E+01 8.990839E+01 7.219904E-02 4.515192E+01 + 2.560006E+01 3.000000E+01 2 2.754763E+01 8.989227E+01 5.180098E-02 2.754758E+01 + 2.560006E+01 3.000000E+01 3 1.793979E+02 3.893873E-01 1.793937E+02 1.219195E+00 + 2.560006E+01 3.000000E+01 4 9.065352E+01 8.989131E+01 1.719588E-01 9.065336E+01 + 2.560006E+01 3.000000E+01 5 4.508022E+02 8.990839E+01 7.208501E-01 4.508016E+02 + 2.560006E+01 3.000000E+01 6 8.210437E+01 -1.639471E-03 8.210437E+01 -2.349349E-03 + 2.560006E+01 6.000000E+01 1 2.631397E+01 8.990841E+01 4.206533E-02 2.631394E+01 + 2.560006E+01 6.000000E+01 2 4.820838E+01 8.989223E+01 9.066956E-02 4.820830E+01 + 2.560006E+01 6.000000E+01 3 1.813056E+02 3.912900E-01 1.813014E+02 1.238181E+00 + 2.560006E+01 6.000000E+01 4 1.600283E+02 8.989223E+01 3.009848E-01 1.600280E+02 + 2.560006E+01 6.000000E+01 5 2.626792E+02 8.990839E+01 4.199771E-01 2.626789E+02 + 2.560006E+01 6.000000E+01 6 8.297894E+01 -1.633574E-03 8.297894E+01 -2.365833E-03 + 2.560006E+01 9.000000E+01 1 2.738228E-06 -9.005901E+01 -2.819910E-09 -2.738226E-06 + 2.560006E+01 9.000000E+01 2 5.595417E+01 8.989223E+01 1.052474E-01 5.595407E+01 + 2.560006E+01 9.000000E+01 3 1.822680E+02 3.922426E-01 1.822638E+02 1.247784E+00 + 2.560006E+01 9.000000E+01 4 1.865367E+02 8.989268E+01 3.493795E-01 1.865363E+02 + 2.560006E+01 9.000000E+01 5 1.245393E-04 -8.998556E+01 3.138911E-08 -1.245393E-04 + 2.560006E+01 9.000000E+01 6 7.141562E-06 1.799989E+02 -7.141562E-06 1.368536E-10 + 2.570006E+01 0.000000E+00 1 5.169181E+01 8.990916E+01 8.195859E-02 5.169174E+01 + 2.570006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.570006E+01 0.000000E+00 3 1.786752E+02 3.852565E-01 1.786711E+02 1.201402E+00 + 2.570006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.570006E+01 0.000000E+00 5 5.166389E+02 8.990916E+01 8.191053E-01 5.166382E+02 + 2.570006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.570006E+01 3.000000E+01 1 4.497443E+01 8.990917E+01 7.129841E-02 4.497437E+01 + 2.570006E+01 3.000000E+01 2 2.743947E+01 8.989327E+01 5.111049E-02 2.743943E+01 + 2.570006E+01 3.000000E+01 3 1.796143E+02 3.861879E-01 1.796102E+02 1.210636E+00 + 2.570006E+01 3.000000E+01 4 9.026964E+01 8.989235E+01 1.696022E-01 9.026948E+01 + 2.570006E+01 3.000000E+01 5 4.494815E+02 8.990917E+01 7.125678E-01 4.494809E+02 + 2.570006E+01 3.000000E+01 6 8.142542E+01 -1.609643E-03 8.142542E+01 -2.287530E-03 + 2.570006E+01 6.000000E+01 1 2.620855E+01 8.990919E+01 4.153742E-02 2.620851E+01 + 2.570006E+01 6.000000E+01 2 4.801499E+01 8.989326E+01 8.945265E-02 4.801491E+01 + 2.570006E+01 6.000000E+01 3 1.815072E+02 3.880599E-01 1.815030E+02 1.229325E+00 + 2.570006E+01 6.000000E+01 4 1.593258E+02 8.989326E+01 2.968335E-01 1.593255E+02 + 2.570006E+01 6.000000E+01 5 2.618866E+02 8.990918E+01 4.151195E-01 2.618863E+02 + 2.570006E+01 6.000000E+01 6 8.228532E+01 -1.603900E-03 8.228532E+01 -2.303440E-03 + 2.570006E+01 9.000000E+01 1 2.727010E-06 -9.005869E+01 -2.792771E-09 -2.727008E-06 + 2.570006E+01 9.000000E+01 2 5.572707E+01 8.989325E+01 1.038303E-01 5.572697E+01 + 2.570006E+01 9.000000E+01 3 1.824620E+02 3.889971E-01 1.824578E+02 1.238776E+00 + 2.570006E+01 9.000000E+01 4 1.857030E+02 8.989370E+01 3.445441E-01 1.857027E+02 + 2.570006E+01 9.000000E+01 5 1.240707E-04 -8.998573E+01 3.089279E-08 -1.240707E-04 + 2.570006E+01 9.000000E+01 6 7.081438E-06 1.799989E+02 -7.081438E-06 1.332513E-10 + 2.580006E+01 0.000000E+00 1 5.149174E+01 8.990993E+01 8.094350E-02 5.149168E+01 + 2.580006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.580006E+01 0.000000E+00 3 1.788970E+02 3.821118E-01 1.788931E+02 1.193075E+00 + 2.580006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.580006E+01 0.000000E+00 5 5.151501E+02 8.990994E+01 8.097555E-01 5.151495E+02 + 2.580006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.580006E+01 3.000000E+01 1 4.479865E+01 8.990995E+01 7.041294E-02 4.479859E+01 + 2.580006E+01 3.000000E+01 2 2.733228E+01 8.989428E+01 5.043266E-02 2.733224E+01 + 2.580006E+01 3.000000E+01 3 1.798286E+02 3.830300E-01 1.798246E+02 1.202170E+00 + 2.580006E+01 3.000000E+01 4 8.988863E+01 8.989337E+01 1.672889E-01 8.988848E+01 + 2.580006E+01 3.000000E+01 5 4.481632E+02 8.990995E+01 7.044100E-01 4.481627E+02 + 2.580006E+01 3.000000E+01 6 8.075513E+01 -1.580509E-03 8.075513E+01 -2.227637E-03 + 2.580006E+01 6.000000E+01 1 2.610392E+01 8.990997E+01 4.101842E-02 2.610389E+01 + 2.580006E+01 6.000000E+01 2 4.782318E+01 8.989426E+01 8.825807E-02 4.782310E+01 + 2.580006E+01 6.000000E+01 3 1.817074E+02 3.848689E-01 1.817033E+02 1.220561E+00 + 2.580006E+01 6.000000E+01 4 1.586282E+02 8.989426E+01 2.927581E-01 1.586279E+02 + 2.580006E+01 6.000000E+01 5 2.610994E+02 8.990996E+01 4.103387E-01 2.610991E+02 + 2.580006E+01 6.000000E+01 6 8.160052E+01 -1.574919E-03 8.160052E+01 -2.242996E-03 + 2.580006E+01 9.000000E+01 1 2.715886E-06 -9.005836E+01 -2.765918E-09 -2.715885E-06 + 2.580006E+01 9.000000E+01 2 5.550196E+01 8.989425E+01 1.024391E-01 5.550187E+01 + 2.580006E+01 9.000000E+01 3 1.826550E+02 3.857875E-01 1.826509E+02 1.229855E+00 + 2.580006E+01 9.000000E+01 4 1.848768E+02 8.989470E+01 3.397984E-01 1.848765E+02 + 2.580006E+01 9.000000E+01 5 1.236045E-04 -8.998591E+01 3.040703E-08 -1.236045E-04 + 2.580006E+01 9.000000E+01 6 7.022090E-06 1.799989E+02 -7.022090E-06 1.297610E-10 + 2.590006E+01 0.000000E+00 1 5.129295E+01 8.991070E+01 7.994528E-02 5.129289E+01 + 2.590006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.590006E+01 0.000000E+00 3 1.791144E+02 3.790093E-01 1.791105E+02 1.184826E+00 + 2.590006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.590006E+01 0.000000E+00 5 5.136596E+02 8.991071E+01 8.005537E-01 5.136590E+02 + 2.590006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.590006E+01 3.000000E+01 1 4.462414E+01 8.991071E+01 6.954189E-02 4.462409E+01 + 2.590006E+01 3.000000E+01 2 2.722587E+01 8.989527E+01 4.976699E-02 2.722582E+01 + 2.590006E+01 3.000000E+01 3 1.800397E+02 3.799113E-01 1.800357E+02 1.193781E+00 + 2.590006E+01 3.000000E+01 4 8.951101E+01 8.989437E+01 1.650197E-01 8.951086E+01 + 2.590006E+01 3.000000E+01 5 4.468538E+02 8.991071E+01 6.963717E-01 4.468533E+02 + 2.590006E+01 3.000000E+01 6 8.009295E+01 -1.552043E-03 8.009295E+01 -2.169579E-03 + 2.590006E+01 6.000000E+01 1 2.600018E+01 8.991074E+01 4.050803E-02 2.600015E+01 + 2.590006E+01 6.000000E+01 2 4.763277E+01 8.989525E+01 8.708522E-02 4.763269E+01 + 2.590006E+01 6.000000E+01 3 1.819051E+02 3.817146E-01 1.819011E+02 1.211875E+00 + 2.590006E+01 6.000000E+01 4 1.579380E+02 8.989525E+01 2.887590E-01 1.579378E+02 + 2.590006E+01 6.000000E+01 5 2.603143E+02 8.991072E+01 4.056258E-01 2.603140E+02 + 2.590006E+01 6.000000E+01 6 8.092432E+01 -1.546603E-03 8.092432E+01 -2.184416E-03 + 2.590006E+01 9.000000E+01 1 2.704857E-06 -9.005803E+01 -2.739347E-09 -2.704856E-06 + 2.590006E+01 9.000000E+01 2 5.527861E+01 8.989524E+01 1.010732E-01 5.527851E+01 + 2.590006E+01 9.000000E+01 3 1.828451E+02 3.826203E-01 1.828410E+02 1.221027E+00 + 2.590006E+01 9.000000E+01 4 1.840587E+02 8.989568E+01 3.351416E-01 1.840584E+02 + 2.590006E+01 9.000000E+01 5 1.231414E-04 -8.998608E+01 2.993141E-08 -1.231414E-04 + 2.590006E+01 9.000000E+01 6 6.963511E-06 1.799990E+02 -6.963511E-06 1.263779E-10 + 2.600006E+01 0.000000E+00 1 5.109602E+01 8.991145E+01 7.896393E-02 5.109596E+01 + 2.600006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.600006E+01 0.000000E+00 3 1.793311E+02 3.759445E-01 1.793272E+02 1.176667E+00 + 2.600006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.600006E+01 0.000000E+00 5 5.121817E+02 8.991146E+01 7.914839E-01 5.121811E+02 + 2.600006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.600006E+01 3.000000E+01 1 4.445098E+01 8.991147E+01 6.868564E-02 4.445093E+01 + 2.600006E+01 3.000000E+01 2 2.712029E+01 8.989624E+01 4.911324E-02 2.712024E+01 + 2.600006E+01 3.000000E+01 3 1.802490E+02 3.768303E-01 1.802451E+02 1.185476E+00 + 2.600006E+01 3.000000E+01 4 8.913700E+01 8.989536E+01 1.627916E-01 8.913686E+01 + 2.600006E+01 3.000000E+01 5 4.455464E+02 8.991146E+01 6.884615E-01 4.455459E+02 + 2.600006E+01 3.000000E+01 6 7.943929E+01 -1.524229E-03 7.943929E+01 -2.113309E-03 + 2.600006E+01 6.000000E+01 1 2.589724E+01 8.991149E+01 4.000637E-02 2.589721E+01 + 2.600006E+01 6.000000E+01 2 4.744403E+01 8.989622E+01 8.593361E-02 4.744396E+01 + 2.600006E+01 6.000000E+01 3 1.820998E+02 3.786066E-01 1.820958E+02 1.203294E+00 + 2.600006E+01 6.000000E+01 4 1.572541E+02 8.989622E+01 2.848348E-01 1.572538E+02 + 2.600006E+01 6.000000E+01 5 2.595318E+02 8.991148E+01 4.009877E-01 2.595315E+02 + 2.600006E+01 6.000000E+01 6 8.025684E+01 -1.518931E-03 8.025684E+01 -2.127636E-03 + 2.600006E+01 9.000000E+01 1 2.693912E-06 -9.005771E+01 -2.713053E-09 -2.693911E-06 + 2.600006E+01 9.000000E+01 2 5.505724E+01 8.989621E+01 9.973222E-02 5.505715E+01 + 2.600006E+01 9.000000E+01 3 1.830339E+02 3.794927E-01 1.830299E+02 1.212297E+00 + 2.600006E+01 9.000000E+01 4 1.832482E+02 8.989664E+01 3.305736E-01 1.832479E+02 + 2.600006E+01 9.000000E+01 5 1.226827E-04 -8.998624E+01 2.946566E-08 -1.226827E-04 + 2.600006E+01 9.000000E+01 6 6.905673E-06 1.799990E+02 -6.905673E-06 1.230990E-10 + 2.610006E+01 0.000000E+00 1 5.090041E+01 8.991220E+01 7.799821E-02 5.090035E+01 + 2.610006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.610006E+01 0.000000E+00 3 1.795460E+02 3.729165E-01 1.795422E+02 1.168588E+00 + 2.610006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.610006E+01 0.000000E+00 5 5.107065E+02 8.991221E+01 7.825466E-01 5.107059E+02 + 2.610006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.610006E+01 3.000000E+01 1 4.427908E+01 8.991222E+01 6.784350E-02 4.427903E+01 + 2.610006E+01 3.000000E+01 2 2.701556E+01 8.989720E+01 4.847119E-02 2.701551E+01 + 2.610006E+01 3.000000E+01 3 1.804570E+02 3.737855E-01 1.804531E+02 1.177255E+00 + 2.610006E+01 3.000000E+01 4 8.876540E+01 8.989633E+01 1.606045E-01 8.876526E+01 + 2.610006E+01 3.000000E+01 5 4.442437E+02 8.991222E+01 6.806616E-01 4.442431E+02 + 2.610006E+01 3.000000E+01 6 7.879364E+01 -1.497048E-03 7.879364E+01 -2.058754E-03 + 2.610006E+01 6.000000E+01 1 2.579519E+01 8.991224E+01 3.951291E-02 2.579516E+01 + 2.610006E+01 6.000000E+01 2 4.725676E+01 8.989718E+01 8.480272E-02 4.725668E+01 + 2.610006E+01 6.000000E+01 3 1.822945E+02 3.755299E-01 1.822906E+02 1.194792E+00 + 2.610006E+01 6.000000E+01 4 1.565759E+02 8.989718E+01 2.809838E-01 1.565756E+02 + 2.610006E+01 6.000000E+01 5 2.587555E+02 8.991222E+01 3.964159E-01 2.587552E+02 + 2.610006E+01 6.000000E+01 6 7.959760E+01 -1.491891E-03 7.959760E+01 -2.072594E-03 + 2.610006E+01 9.000000E+01 1 2.683070E-06 -9.005738E+01 -2.687030E-09 -2.683068E-06 + 2.610006E+01 9.000000E+01 2 5.483751E+01 8.989718E+01 9.841555E-02 5.483743E+01 + 2.610006E+01 9.000000E+01 3 1.832212E+02 3.764021E-01 1.832172E+02 1.203655E+00 + 2.610006E+01 9.000000E+01 4 1.824440E+02 8.989759E+01 3.260891E-01 1.824437E+02 + 2.610006E+01 9.000000E+01 5 1.222264E-04 -8.998640E+01 2.900953E-08 -1.222264E-04 + 2.610006E+01 9.000000E+01 6 6.848570E-06 1.799990E+02 -6.848570E-06 1.199204E-10 + 2.620006E+01 0.000000E+00 1 5.070644E+01 8.991294E+01 7.704881E-02 5.070638E+01 + 2.620006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.620006E+01 0.000000E+00 3 1.797571E+02 3.699245E-01 1.797534E+02 1.160576E+00 + 2.620006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.620006E+01 0.000000E+00 5 5.092314E+02 8.991295E+01 7.737415E-01 5.092308E+02 + 2.620006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.620006E+01 3.000000E+01 1 4.410872E+01 8.991296E+01 6.701516E-02 4.410867E+01 + 2.620006E+01 3.000000E+01 2 2.691160E+01 8.989815E+01 4.784046E-02 2.691155E+01 + 2.620006E+01 3.000000E+01 3 1.806618E+02 3.707798E-01 1.806580E+02 1.169114E+00 + 2.620006E+01 3.000000E+01 4 8.839765E+01 8.989730E+01 1.584572E-01 8.839751E+01 + 2.620006E+01 3.000000E+01 5 4.429486E+02 8.991296E+01 6.729875E-01 4.429481E+02 + 2.620006E+01 3.000000E+01 6 7.815615E+01 -1.470482E-03 7.815615E+01 -2.005859E-03 + 2.620006E+01 6.000000E+01 1 2.569386E+01 8.991297E+01 3.902771E-02 2.569383E+01 + 2.620006E+01 6.000000E+01 2 4.707100E+01 8.989813E+01 8.369195E-02 4.707092E+01 + 2.620006E+01 6.000000E+01 3 1.824854E+02 3.724924E-01 1.824815E+02 1.186369E+00 + 2.620006E+01 6.000000E+01 4 1.559037E+02 8.989812E+01 2.772022E-01 1.559034E+02 + 2.620006E+01 6.000000E+01 5 2.579809E+02 8.991296E+01 3.919181E-01 2.579806E+02 + 2.620006E+01 6.000000E+01 6 7.894678E+01 -1.465459E-03 7.894678E+01 -2.019228E-03 + 2.620006E+01 9.000000E+01 1 2.672306E-06 -9.005706E+01 -2.661287E-09 -2.672305E-06 + 2.620006E+01 9.000000E+01 2 5.461969E+01 8.989812E+01 9.712229E-02 5.461960E+01 + 2.620006E+01 9.000000E+01 3 1.834053E+02 3.733473E-01 1.834014E+02 1.195086E+00 + 2.620006E+01 9.000000E+01 4 1.816475E+02 8.989854E+01 3.216880E-01 1.816472E+02 + 2.620006E+01 9.000000E+01 5 1.217739E-04 -8.998656E+01 2.856275E-08 -1.217739E-04 + 2.620006E+01 9.000000E+01 6 6.792188E-06 1.799990E+02 -6.792188E-06 1.168381E-10 + 2.630006E+01 0.000000E+00 1 5.051381E+01 8.991367E+01 7.611477E-02 5.051376E+01 + 2.630006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.630006E+01 0.000000E+00 3 1.799664E+02 3.669711E-01 1.799627E+02 1.152651E+00 + 2.630006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.630006E+01 0.000000E+00 5 5.077678E+02 8.991367E+01 7.650717E-01 5.077672E+02 + 2.630006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.630006E+01 3.000000E+01 1 4.393940E+01 8.991367E+01 6.620029E-02 4.393935E+01 + 2.630006E+01 3.000000E+01 2 2.680844E+01 8.989908E+01 4.722099E-02 2.680840E+01 + 2.630006E+01 3.000000E+01 3 1.808641E+02 3.678109E-01 1.808603E+02 1.161051E+00 + 2.630006E+01 3.000000E+01 4 8.803287E+01 8.989824E+01 1.563495E-01 8.803273E+01 + 2.630006E+01 3.000000E+01 5 4.416592E+02 8.991367E+01 6.654167E-01 4.416587E+02 + 2.630006E+01 3.000000E+01 6 7.752633E+01 -1.444522E-03 7.752633E+01 -1.954567E-03 + 2.630006E+01 6.000000E+01 1 2.559350E+01 8.991370E+01 3.855051E-02 2.559347E+01 + 2.630006E+01 6.000000E+01 2 4.688665E+01 8.989906E+01 8.260126E-02 4.688658E+01 + 2.630006E+01 6.000000E+01 3 1.826747E+02 3.694938E-01 1.826709E+02 1.178040E+00 + 2.630006E+01 6.000000E+01 4 1.552378E+02 8.989906E+01 2.734921E-01 1.552376E+02 + 2.630006E+01 6.000000E+01 5 2.572104E+02 8.991368E+01 3.874862E-01 2.572101E+02 + 2.630006E+01 6.000000E+01 6 7.830399E+01 -1.439627E-03 7.830399E+01 -1.967484E-03 + 2.630006E+01 9.000000E+01 1 2.661636E-06 -9.005674E+01 -2.635820E-09 -2.661635E-06 + 2.630006E+01 9.000000E+01 2 5.440361E+01 8.989906E+01 9.585236E-02 5.440353E+01 + 2.630006E+01 9.000000E+01 3 1.835871E+02 3.703380E-01 1.835832E+02 1.186628E+00 + 2.630006E+01 9.000000E+01 4 1.808585E+02 8.989946E+01 3.173669E-01 1.808582E+02 + 2.630006E+01 9.000000E+01 5 1.213248E-04 -8.998672E+01 2.812506E-08 -1.213248E-04 + 2.630006E+01 9.000000E+01 6 6.736523E-06 1.799990E+02 -6.736523E-06 1.138494E-10 + 2.640006E+01 0.000000E+00 1 5.032254E+01 8.991439E+01 7.519586E-02 5.032248E+01 + 2.640006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.640006E+01 0.000000E+00 3 1.801734E+02 3.640529E-01 1.801698E+02 1.144800E+00 + 2.640006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.640006E+01 0.000000E+00 5 5.063096E+02 8.991439E+01 7.565247E-01 5.063090E+02 + 2.640006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.640006E+01 3.000000E+01 1 4.377151E+01 8.991439E+01 6.539898E-02 4.377147E+01 + 2.640006E+01 3.000000E+01 2 2.670610E+01 8.989999E+01 4.661248E-02 2.670606E+01 + 2.640006E+01 3.000000E+01 3 1.810648E+02 3.648795E-01 1.810612E+02 1.153076E+00 + 2.640006E+01 3.000000E+01 4 8.767094E+01 8.989918E+01 1.542793E-01 8.767080E+01 + 2.640006E+01 3.000000E+01 5 4.403716E+02 8.991439E+01 6.579621E-01 4.403712E+02 + 2.640006E+01 3.000000E+01 6 7.690427E+01 -1.419140E-03 7.690427E+01 -1.904816E-03 + 2.640006E+01 6.000000E+01 1 2.549375E+01 8.991441E+01 3.808119E-02 2.549372E+01 + 2.640006E+01 6.000000E+01 2 4.670385E+01 8.989998E+01 8.152983E-02 4.670377E+01 + 2.640006E+01 6.000000E+01 3 1.828615E+02 3.665332E-01 1.828577E+02 1.169795E+00 + 2.640006E+01 6.000000E+01 4 1.545782E+02 8.989998E+01 2.698491E-01 1.545780E+02 + 2.640006E+01 6.000000E+01 5 2.564434E+02 8.991440E+01 3.831136E-01 2.564431E+02 + 2.640006E+01 6.000000E+01 6 7.766911E+01 -1.414375E-03 7.766911E+01 -1.917301E-03 + 2.640006E+01 9.000000E+01 1 2.651050E-06 -9.005642E+01 -2.610633E-09 -2.651049E-06 + 2.640006E+01 9.000000E+01 2 5.418918E+01 8.989998E+01 9.460504E-02 5.418909E+01 + 2.640006E+01 9.000000E+01 3 1.837673E+02 3.673604E-01 1.837635E+02 1.178243E+00 + 2.640006E+01 9.000000E+01 4 1.800775E+02 8.990038E+01 3.131272E-01 1.800772E+02 + 2.640006E+01 9.000000E+01 5 1.208786E-04 -8.998688E+01 2.769650E-08 -1.208786E-04 + 2.640006E+01 9.000000E+01 6 6.681551E-06 1.799991E+02 -6.681551E-06 1.109505E-10 + 2.650006E+01 0.000000E+00 1 5.013262E+01 8.991509E+01 7.429196E-02 5.013257E+01 + 2.650006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.650006E+01 0.000000E+00 3 1.803780E+02 3.611699E-01 1.803744E+02 1.137024E+00 + 2.650006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.650006E+01 0.000000E+00 5 5.048548E+02 8.991510E+01 7.481000E-01 5.048543E+02 + 2.650006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.650006E+01 3.000000E+01 1 4.360493E+01 8.991511E+01 6.461056E-02 4.360489E+01 + 2.650006E+01 3.000000E+01 2 2.660445E+01 8.990090E+01 4.601443E-02 2.660441E+01 + 2.650006E+01 3.000000E+01 3 1.812630E+02 3.619791E-01 1.812593E+02 1.145162E+00 + 2.650006E+01 3.000000E+01 4 8.731237E+01 8.990009E+01 1.522471E-01 8.731224E+01 + 2.650006E+01 3.000000E+01 5 4.390908E+02 8.991511E+01 6.506217E-01 4.390903E+02 + 2.650006E+01 3.000000E+01 6 7.628987E+01 -1.394326E-03 7.628987E+01 -1.856558E-03 + 2.650006E+01 6.000000E+01 1 2.539485E+01 8.991512E+01 3.761959E-02 2.539482E+01 + 2.650006E+01 6.000000E+01 2 4.652246E+01 8.990089E+01 8.047722E-02 4.652239E+01 + 2.650006E+01 6.000000E+01 3 1.830477E+02 3.636064E-01 1.830440E+02 1.161637E+00 + 2.650006E+01 6.000000E+01 4 1.539234E+02 8.990089E+01 2.662709E-01 1.539231E+02 + 2.650006E+01 6.000000E+01 5 2.556804E+02 8.991511E+01 3.788157E-01 2.556801E+02 + 2.650006E+01 6.000000E+01 6 7.704235E+01 -1.389681E-03 7.704235E+01 -1.868624E-03 + 2.650006E+01 9.000000E+01 1 2.640545E-06 -9.005611E+01 -2.585707E-09 -2.640544E-06 + 2.650006E+01 9.000000E+01 2 5.397648E+01 8.990088E+01 9.337966E-02 5.397640E+01 + 2.650006E+01 9.000000E+01 3 1.839465E+02 3.644179E-01 1.839428E+02 1.169946E+00 + 2.650006E+01 9.000000E+01 4 1.793023E+02 8.990128E+01 3.089624E-01 1.793020E+02 + 2.650006E+01 9.000000E+01 5 1.204361E-04 -8.998702E+01 2.727646E-08 -1.204361E-04 + 2.650006E+01 9.000000E+01 6 6.627258E-06 1.799991E+02 -6.627258E-06 1.081387E-10 + 2.660007E+01 0.000000E+00 1 4.994437E+01 8.991579E+01 7.340250E-02 4.994431E+01 + 2.660007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.660007E+01 0.000000E+00 3 1.805811E+02 3.583170E-01 1.805776E+02 1.129313E+00 + 2.660007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.660007E+01 0.000000E+00 5 5.034080E+02 8.991580E+01 7.398058E-01 5.034074E+02 + 2.660007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.660007E+01 3.000000E+01 1 4.343951E+01 8.991580E+01 6.383497E-02 4.343946E+01 + 2.660007E+01 3.000000E+01 2 2.650364E+01 8.990180E+01 4.542688E-02 2.650360E+01 + 2.660007E+01 3.000000E+01 3 1.814593E+02 3.591148E-01 1.814557E+02 1.137331E+00 + 2.660007E+01 3.000000E+01 4 8.695663E+01 8.990100E+01 1.502510E-01 8.695650E+01 + 2.660007E+01 3.000000E+01 5 4.378155E+02 8.991580E+01 6.433796E-01 4.378150E+02 + 2.660007E+01 3.000000E+01 6 7.568286E+01 -1.370062E-03 7.568286E+01 -1.809736E-03 + 2.660007E+01 6.000000E+01 1 2.529667E+01 8.991582E+01 3.716544E-02 2.529665E+01 + 2.660007E+01 6.000000E+01 2 4.634241E+01 8.990178E+01 7.944313E-02 4.634234E+01 + 2.660007E+01 6.000000E+01 3 1.832295E+02 3.607149E-01 1.832259E+02 1.153543E+00 + 2.660007E+01 6.000000E+01 4 1.532749E+02 8.990178E+01 2.627592E-01 1.532746E+02 + 2.660007E+01 6.000000E+01 5 2.549184E+02 8.991581E+01 3.745768E-01 2.549181E+02 + 2.660007E+01 6.000000E+01 6 7.642311E+01 -1.365538E-03 7.642311E+01 -1.821402E-03 + 2.660007E+01 9.000000E+01 1 2.630131E-06 -9.005579E+01 -2.561041E-09 -2.630130E-06 + 2.660007E+01 9.000000E+01 2 5.376562E+01 8.990177E+01 9.217608E-02 5.376554E+01 + 2.660007E+01 9.000000E+01 3 1.841226E+02 3.615143E-01 1.841189E+02 1.161735E+00 + 2.660007E+01 9.000000E+01 4 1.785347E+02 8.990216E+01 3.048739E-01 1.785345E+02 + 2.660007E+01 9.000000E+01 5 1.199960E-04 -8.998717E+01 2.686492E-08 -1.199960E-04 + 2.660007E+01 9.000000E+01 6 6.573651E-06 1.799991E+02 -6.573651E-06 1.054108E-10 + 2.670007E+01 0.000000E+00 1 4.975744E+01 8.991648E+01 7.252754E-02 4.975739E+01 + 2.670007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.670007E+01 0.000000E+00 3 1.807815E+02 3.555000E-01 1.807780E+02 1.121678E+00 + 2.670007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.670007E+01 0.000000E+00 5 5.019677E+02 8.991649E+01 7.316379E-01 5.019671E+02 + 2.670007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.670007E+01 3.000000E+01 1 4.327540E+01 8.991650E+01 6.307177E-02 4.327536E+01 + 2.670007E+01 3.000000E+01 2 2.640359E+01 8.990268E+01 4.484951E-02 2.640355E+01 + 2.670007E+01 3.000000E+01 3 1.816536E+02 3.562858E-01 1.816501E+02 1.129580E+00 + 2.670007E+01 3.000000E+01 4 8.660397E+01 8.990189E+01 1.482904E-01 8.660384E+01 + 2.670007E+01 3.000000E+01 5 4.365475E+02 8.991649E+01 6.362560E-01 4.365471E+02 + 2.670007E+01 3.000000E+01 6 7.508324E+01 -1.346339E-03 7.508324E+01 -1.764310E-03 + 2.670007E+01 6.000000E+01 1 2.519938E+01 8.991651E+01 3.671863E-02 2.519935E+01 + 2.670007E+01 6.000000E+01 2 4.616380E+01 8.990266E+01 7.842716E-02 4.616373E+01 + 2.670007E+01 6.000000E+01 3 1.834113E+02 3.578544E-01 1.834077E+02 1.145531E+00 + 2.670007E+01 6.000000E+01 4 1.526322E+02 8.990266E+01 2.593098E-01 1.526319E+02 + 2.670007E+01 6.000000E+01 5 2.541618E+02 8.991650E+01 3.703984E-01 2.541615E+02 + 2.670007E+01 6.000000E+01 6 7.581155E+01 -1.341930E-03 7.581155E+01 -1.775589E-03 + 2.670007E+01 9.000000E+01 1 2.619800E-06 -9.005548E+01 -2.536655E-09 -2.619799E-06 + 2.670007E+01 9.000000E+01 2 5.355633E+01 8.990266E+01 9.099358E-02 5.355625E+01 + 2.670007E+01 9.000000E+01 3 1.842975E+02 3.586431E-01 1.842939E+02 1.153603E+00 + 2.670007E+01 9.000000E+01 4 1.777730E+02 8.990304E+01 3.008603E-01 1.777727E+02 + 2.670007E+01 9.000000E+01 5 1.195592E-04 -8.998732E+01 2.646168E-08 -1.195592E-04 + 2.670007E+01 9.000000E+01 6 6.520702E-06 1.799991E+02 -6.520702E-06 1.027639E-10 + 2.680007E+01 0.000000E+00 1 4.957199E+01 8.991717E+01 7.166658E-02 4.957193E+01 + 2.680007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.680007E+01 0.000000E+00 3 1.809795E+02 3.527180E-01 1.809761E+02 1.114119E+00 + 2.680007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.680007E+01 0.000000E+00 5 5.005284E+02 8.991718E+01 7.235785E-01 5.005278E+02 + 2.680007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.680007E+01 3.000000E+01 1 4.311250E+01 8.991718E+01 6.232109E-02 4.311246E+01 + 2.680007E+01 3.000000E+01 2 2.630436E+01 8.990355E+01 4.428224E-02 2.630432E+01 + 2.680007E+01 3.000000E+01 3 1.818457E+02 3.534885E-01 1.818422E+02 1.121897E+00 + 2.680007E+01 3.000000E+01 4 8.625410E+01 8.990278E+01 1.463647E-01 8.625397E+01 + 2.680007E+01 3.000000E+01 5 4.352836E+02 8.991718E+01 6.292251E-01 4.352831E+02 + 2.680007E+01 3.000000E+01 6 7.449078E+01 -1.323138E-03 7.449078E+01 -1.720224E-03 + 2.680007E+01 6.000000E+01 1 2.510277E+01 8.991719E+01 3.627928E-02 2.510275E+01 + 2.680007E+01 6.000000E+01 2 4.598661E+01 8.990353E+01 7.742900E-02 4.598655E+01 + 2.680007E+01 6.000000E+01 3 1.835903E+02 3.550344E-01 1.835868E+02 1.137614E+00 + 2.680007E+01 6.000000E+01 4 1.519946E+02 8.990353E+01 2.559225E-01 1.519944E+02 + 2.680007E+01 6.000000E+01 5 2.534075E+02 8.991718E+01 3.662858E-01 2.534072E+02 + 2.680007E+01 6.000000E+01 6 7.520734E+01 -1.318840E-03 7.520734E+01 -1.731130E-03 + 2.680007E+01 9.000000E+01 1 2.609547E-06 -9.005516E+01 -2.512525E-09 -2.609546E-06 + 2.680007E+01 9.000000E+01 2 5.334876E+01 8.990352E+01 8.983179E-02 5.334868E+01 + 2.680007E+01 9.000000E+01 3 1.844700E+02 3.558068E-01 1.844665E+02 1.145552E+00 + 2.680007E+01 9.000000E+01 4 1.770188E+02 8.990389E+01 2.969182E-01 1.770186E+02 + 2.680007E+01 9.000000E+01 5 1.191260E-04 -8.998746E+01 2.606647E-08 -1.191260E-04 + 2.680007E+01 9.000000E+01 6 6.468401E-06 1.799991E+02 -6.468401E-06 1.001952E-10 + 2.690007E+01 0.000000E+00 1 4.938780E+01 8.991785E+01 7.081942E-02 4.938775E+01 + 2.690007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.690007E+01 0.000000E+00 3 1.811754E+02 3.499687E-01 1.811720E+02 1.106632E+00 + 2.690007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.690007E+01 0.000000E+00 5 4.990980E+02 8.991785E+01 7.156407E-01 4.990975E+02 + 2.690007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.690007E+01 3.000000E+01 1 4.295082E+01 8.991785E+01 6.158246E-02 4.295078E+01 + 2.690007E+01 3.000000E+01 2 2.620577E+01 8.990440E+01 4.372468E-02 2.620573E+01 + 2.690007E+01 3.000000E+01 3 1.820351E+02 3.507273E-01 1.820317E+02 1.114293E+00 + 2.690007E+01 3.000000E+01 4 8.590702E+01 8.990364E+01 1.444738E-01 8.590690E+01 + 2.690007E+01 3.000000E+01 5 4.340239E+02 8.991785E+01 6.222978E-01 4.340234E+02 + 2.690007E+01 3.000000E+01 6 7.390546E+01 -1.300444E-03 7.390546E+01 -1.677434E-03 + 2.690007E+01 6.000000E+01 1 2.500688E+01 8.991787E+01 3.584683E-02 2.500686E+01 + 2.690007E+01 6.000000E+01 2 4.581085E+01 8.990439E+01 7.644784E-02 4.581078E+01 + 2.690007E+01 6.000000E+01 3 1.837681E+02 3.522452E-01 1.837646E+02 1.129770E+00 + 2.690007E+01 6.000000E+01 4 1.513629E+02 8.990439E+01 2.525952E-01 1.513627E+02 + 2.690007E+01 6.000000E+01 5 2.526579E+02 8.991785E+01 3.622274E-01 2.526577E+02 + 2.690007E+01 6.000000E+01 6 7.461059E+01 -1.296254E-03 7.461059E+01 -1.687982E-03 + 2.690007E+01 9.000000E+01 1 2.599385E-06 -9.005486E+01 -2.488661E-09 -2.599384E-06 + 2.690007E+01 9.000000E+01 2 5.314262E+01 8.990438E+01 8.869006E-02 5.314255E+01 + 2.690007E+01 9.000000E+01 3 1.846405E+02 3.530075E-01 1.846369E+02 1.137589E+00 + 2.690007E+01 9.000000E+01 4 1.762712E+02 8.990475E+01 2.930458E-01 1.762710E+02 + 2.690007E+01 9.000000E+01 5 1.186961E-04 -8.998761E+01 2.567913E-08 -1.186961E-04 + 2.690007E+01 9.000000E+01 6 6.416746E-06 1.799991E+02 -6.416746E-06 9.770214E-11 + 2.700007E+01 0.000000E+00 1 4.920490E+01 8.991850E+01 6.998554E-02 4.920485E+01 + 2.700007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.700007E+01 0.000000E+00 3 1.813689E+02 3.472509E-01 1.813656E+02 1.099211E+00 + 2.700007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.700007E+01 0.000000E+00 5 4.976733E+02 8.991851E+01 7.078170E-01 4.976729E+02 + 2.700007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.700007E+01 3.000000E+01 1 4.279038E+01 8.991852E+01 6.085530E-02 4.279034E+01 + 2.700007E+01 3.000000E+01 2 2.610797E+01 8.990525E+01 4.317663E-02 2.610794E+01 + 2.700007E+01 3.000000E+01 3 1.822231E+02 3.479971E-01 1.822197E+02 1.106760E+00 + 2.700007E+01 3.000000E+01 4 8.556313E+01 8.990450E+01 1.426155E-01 8.556300E+01 + 2.700007E+01 3.000000E+01 5 4.327675E+02 8.991851E+01 6.154766E-01 4.327670E+02 + 2.700007E+01 3.000000E+01 6 7.332723E+01 -1.278245E-03 7.332723E+01 -1.635900E-03 + 2.700007E+01 6.000000E+01 1 2.491184E+01 8.991853E+01 3.542138E-02 2.491181E+01 + 2.700007E+01 6.000000E+01 2 4.563639E+01 8.990524E+01 7.548375E-02 4.563633E+01 + 2.700007E+01 6.000000E+01 3 1.839427E+02 3.494898E-01 1.839393E+02 1.121997E+00 + 2.700007E+01 6.000000E+01 4 1.507368E+02 8.990523E+01 2.493267E-01 1.507366E+02 + 2.700007E+01 6.000000E+01 5 2.519093E+02 8.991852E+01 3.582369E-01 2.519090E+02 + 2.700007E+01 6.000000E+01 6 7.402103E+01 -1.274159E-03 7.402103E+01 -1.646100E-03 + 2.700007E+01 9.000000E+01 1 2.589300E-06 -9.005455E+01 -2.465060E-09 -2.589299E-06 + 2.700007E+01 9.000000E+01 2 5.293827E+01 8.990523E+01 8.756818E-02 5.293820E+01 + 2.700007E+01 9.000000E+01 3 1.848093E+02 3.502394E-01 1.848058E+02 1.129701E+00 + 2.700007E+01 9.000000E+01 4 1.755305E+02 8.990559E+01 2.892429E-01 1.755303E+02 + 2.700007E+01 9.000000E+01 5 1.182691E-04 -8.998774E+01 2.529955E-08 -1.182691E-04 + 2.700007E+01 9.000000E+01 6 6.365723E-06 1.799991E+02 -6.365723E-06 9.528219E-11 + 2.710007E+01 0.000000E+00 1 4.902344E+01 8.991917E+01 6.916495E-02 4.902339E+01 + 2.710007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.710007E+01 0.000000E+00 3 1.815618E+02 3.445647E-01 1.815585E+02 1.091867E+00 + 2.710007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.710007E+01 0.000000E+00 5 4.962538E+02 8.991917E+01 7.001016E-01 4.962533E+02 + 2.710007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.710007E+01 3.000000E+01 1 4.263114E+01 8.991917E+01 6.013989E-02 4.263110E+01 + 2.710007E+01 3.000000E+01 2 2.601083E+01 8.990608E+01 4.263784E-02 2.601079E+01 + 2.710007E+01 3.000000E+01 3 1.824096E+02 3.452974E-01 1.824062E+02 1.099298E+00 + 2.710007E+01 3.000000E+01 4 8.522180E+01 8.990534E+01 1.407893E-01 8.522169E+01 + 2.710007E+01 3.000000E+01 5 4.315216E+02 8.991917E+01 6.087543E-01 4.315212E+02 + 2.710007E+01 3.000000E+01 6 7.275581E+01 -1.256524E-03 7.275581E+01 -1.595569E-03 + 2.710007E+01 6.000000E+01 1 2.481732E+01 8.991919E+01 3.500267E-02 2.481729E+01 + 2.710007E+01 6.000000E+01 2 4.546335E+01 8.990607E+01 7.453614E-02 4.546329E+01 + 2.710007E+01 6.000000E+01 3 1.841169E+02 3.467660E-01 1.841135E+02 1.114307E+00 + 2.710007E+01 6.000000E+01 4 1.501154E+02 8.990606E+01 2.461157E-01 1.501152E+02 + 2.710007E+01 6.000000E+01 5 2.511670E+02 8.991918E+01 3.542949E-01 2.511668E+02 + 2.710007E+01 6.000000E+01 6 7.343852E+01 -1.252542E-03 7.343852E+01 -1.605438E-03 + 2.710007E+01 9.000000E+01 1 2.579291E-06 -9.005424E+01 -2.441710E-09 -2.579290E-06 + 2.710007E+01 9.000000E+01 2 5.273567E+01 8.990606E+01 8.646568E-02 5.273560E+01 + 2.710007E+01 9.000000E+01 3 1.849767E+02 3.475021E-01 1.849733E+02 1.121887E+00 + 2.710007E+01 9.000000E+01 4 1.747955E+02 8.990642E+01 2.855069E-01 1.747953E+02 + 2.710007E+01 9.000000E+01 5 1.178443E-04 -8.998788E+01 2.492732E-08 -1.178443E-04 + 2.710007E+01 9.000000E+01 6 6.315318E-06 1.799992E+02 -6.315318E-06 9.293270E-11 + 2.720007E+01 0.000000E+00 1 4.884344E+01 8.991982E+01 6.835720E-02 4.884339E+01 + 2.720007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.720007E+01 0.000000E+00 3 1.817517E+02 3.419110E-01 1.817485E+02 1.084592E+00 + 2.720007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.720007E+01 0.000000E+00 5 4.948399E+02 8.991982E+01 6.925036E-01 4.948394E+02 + 2.720007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.720007E+01 3.000000E+01 1 4.247307E+01 8.991982E+01 5.943553E-02 4.247303E+01 + 2.720007E+01 3.000000E+01 2 2.591444E+01 8.990690E+01 4.210823E-02 2.591440E+01 + 2.720007E+01 3.000000E+01 3 1.825933E+02 3.426316E-01 1.825900E+02 1.091911E+00 + 2.720007E+01 3.000000E+01 4 8.488303E+01 8.990617E+01 1.389956E-01 8.488292E+01 + 2.720007E+01 3.000000E+01 5 4.302785E+02 8.991982E+01 6.021183E-01 4.302781E+02 + 2.720007E+01 3.000000E+01 6 7.219109E+01 -1.235276E-03 7.219109E+01 -1.556413E-03 + 2.720007E+01 6.000000E+01 1 2.472375E+01 8.991984E+01 3.459062E-02 2.472373E+01 + 2.720007E+01 6.000000E+01 2 4.529155E+01 8.990689E+01 7.360472E-02 4.529148E+01 + 2.720007E+01 6.000000E+01 3 1.842882E+02 3.440768E-01 1.842848E+02 1.106694E+00 + 2.720007E+01 6.000000E+01 4 1.494998E+02 8.990689E+01 2.429615E-01 1.494996E+02 + 2.720007E+01 6.000000E+01 5 2.504262E+02 8.991983E+01 3.504170E-01 2.504259E+02 + 2.720007E+01 6.000000E+01 6 7.286304E+01 -1.231394E-03 7.286304E+01 -1.565964E-03 + 2.720007E+01 9.000000E+01 1 2.569363E-06 -9.005393E+01 -2.418613E-09 -2.569362E-06 + 2.720007E+01 9.000000E+01 2 5.253433E+01 8.990688E+01 8.538185E-02 5.253426E+01 + 2.720007E+01 9.000000E+01 3 1.851433E+02 3.447990E-01 1.851400E+02 1.114163E+00 + 2.720007E+01 9.000000E+01 4 1.740674E+02 8.990723E+01 2.818376E-01 1.740672E+02 + 2.720007E+01 9.000000E+01 5 1.174236E-04 -8.998801E+01 2.456243E-08 -1.174236E-04 + 2.720007E+01 9.000000E+01 6 6.265522E-06 1.799992E+02 -6.265522E-06 9.065138E-11 + 2.730007E+01 0.000000E+00 1 4.866451E+01 8.992046E+01 6.756207E-02 4.866446E+01 + 2.730007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.730007E+01 0.000000E+00 3 1.819394E+02 3.392879E-01 1.819362E+02 1.077383E+00 + 2.730007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.730007E+01 0.000000E+00 5 4.934328E+02 8.992046E+01 6.850067E-01 4.934323E+02 + 2.730007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.730007E+01 3.000000E+01 1 4.231627E+01 8.992046E+01 5.874249E-02 4.231622E+01 + 2.730007E+01 3.000000E+01 2 2.581881E+01 8.990771E+01 4.158749E-02 2.581878E+01 + 2.730007E+01 3.000000E+01 3 1.827751E+02 3.399976E-01 1.827719E+02 1.084595E+00 + 2.730007E+01 3.000000E+01 4 8.454766E+01 8.990701E+01 1.372326E-01 8.454755E+01 + 2.730007E+01 3.000000E+01 5 4.290386E+02 8.992046E+01 5.955858E-01 4.290382E+02 + 2.730007E+01 3.000000E+01 6 7.163303E+01 -1.214485E-03 7.163303E+01 -1.518388E-03 + 2.730007E+01 6.000000E+01 1 2.463076E+01 8.992048E+01 3.418513E-02 2.463073E+01 + 2.730007E+01 6.000000E+01 2 4.512109E+01 8.990770E+01 7.268921E-02 4.512103E+01 + 2.730007E+01 6.000000E+01 3 1.844582E+02 3.414169E-01 1.844549E+02 1.099152E+00 + 2.730007E+01 6.000000E+01 4 1.488900E+02 8.990770E+01 2.398632E-01 1.488898E+02 + 2.730007E+01 6.000000E+01 5 2.496882E+02 8.992046E+01 3.465922E-01 2.496879E+02 + 2.730007E+01 6.000000E+01 6 7.229449E+01 -1.210696E-03 7.229449E+01 -1.527628E-03 + 2.730007E+01 9.000000E+01 1 2.559514E-06 -9.005363E+01 -2.395775E-09 -2.559513E-06 + 2.730007E+01 9.000000E+01 2 5.233474E+01 8.990769E+01 8.431654E-02 5.233467E+01 + 2.730007E+01 9.000000E+01 3 1.853064E+02 3.421285E-01 1.853031E+02 1.106508E+00 + 2.730007E+01 9.000000E+01 4 1.733455E+02 8.990804E+01 2.782318E-01 1.733453E+02 + 2.730007E+01 9.000000E+01 5 1.170052E-04 -8.998814E+01 2.420465E-08 -1.170052E-04 + 2.730007E+01 9.000000E+01 6 6.216318E-06 1.799992E+02 -6.216318E-06 8.843600E-11 + 2.740007E+01 0.000000E+00 1 4.848690E+01 8.992109E+01 6.677949E-02 4.848685E+01 + 2.740007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.740007E+01 0.000000E+00 3 1.821252E+02 3.366948E-01 1.821221E+02 1.070241E+00 + 2.740007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.740007E+01 0.000000E+00 5 4.920308E+02 8.992110E+01 6.776208E-01 4.920303E+02 + 2.740007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.740007E+01 3.000000E+01 1 4.216036E+01 8.992110E+01 5.806039E-02 4.216032E+01 + 2.740007E+01 3.000000E+01 2 2.572382E+01 8.990852E+01 4.107559E-02 2.572379E+01 + 2.740007E+01 3.000000E+01 3 1.829552E+02 3.373922E-01 1.829521E+02 1.077345E+00 + 2.740007E+01 3.000000E+01 4 8.421449E+01 8.990781E+01 1.355001E-01 8.421438E+01 + 2.740007E+01 3.000000E+01 5 4.278035E+02 8.992110E+01 5.891410E-01 4.278031E+02 + 2.740007E+01 3.000000E+01 6 7.108159E+01 -1.194137E-03 7.108159E+01 -1.481456E-03 + 2.740007E+01 6.000000E+01 1 2.453847E+01 8.992111E+01 3.378597E-02 2.453845E+01 + 2.740007E+01 6.000000E+01 2 4.495183E+01 8.990850E+01 7.178903E-02 4.495177E+01 + 2.740007E+01 6.000000E+01 3 1.846259E+02 3.387916E-01 1.846227E+02 1.091692E+00 + 2.740007E+01 6.000000E+01 4 1.482844E+02 8.990850E+01 2.368169E-01 1.482843E+02 + 2.740007E+01 6.000000E+01 5 2.489519E+02 8.992110E+01 3.428245E-01 2.489516E+02 + 2.740007E+01 6.000000E+01 6 7.173272E+01 -1.190445E-03 7.173272E+01 -1.490404E-03 + 2.740007E+01 9.000000E+01 1 2.549738E-06 -9.005333E+01 -2.373185E-09 -2.549737E-06 + 2.740007E+01 9.000000E+01 2 5.213666E+01 8.990849E+01 8.326934E-02 5.213660E+01 + 2.740007E+01 9.000000E+01 3 1.854675E+02 3.394896E-01 1.854642E+02 1.098928E+00 + 2.740007E+01 9.000000E+01 4 1.726298E+02 8.990884E+01 2.746894E-01 1.726296E+02 + 2.740007E+01 9.000000E+01 5 1.165900E-04 -8.998827E+01 2.385390E-08 -1.165900E-04 + 2.740007E+01 9.000000E+01 6 6.167719E-06 1.799992E+02 -6.167719E-06 8.628445E-11 + 2.750007E+01 0.000000E+00 1 4.831063E+01 8.992171E+01 6.600901E-02 4.831059E+01 + 2.750007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.750007E+01 0.000000E+00 3 1.823094E+02 3.341334E-01 1.823063E+02 1.063173E+00 + 2.750007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.750007E+01 0.000000E+00 5 4.906328E+02 8.992171E+01 6.703410E-01 4.906323E+02 + 2.750007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.750007E+01 3.000000E+01 1 4.200584E+01 8.992172E+01 5.738883E-02 4.200580E+01 + 2.750007E+01 3.000000E+01 2 2.562960E+01 8.990930E+01 4.057218E-02 2.562957E+01 + 2.750007E+01 3.000000E+01 3 1.831329E+02 3.348190E-01 1.831297E+02 1.070166E+00 + 2.750007E+01 3.000000E+01 4 8.388406E+01 8.990862E+01 1.337978E-01 8.388396E+01 + 2.750007E+01 3.000000E+01 5 4.265785E+02 8.992172E+01 5.827969E-01 4.265781E+02 + 2.750007E+01 3.000000E+01 6 7.053657E+01 -1.174226E-03 7.053657E+01 -1.445584E-03 + 2.750007E+01 6.000000E+01 1 2.444687E+01 8.992174E+01 3.339313E-02 2.444685E+01 + 2.750007E+01 6.000000E+01 2 4.478394E+01 8.990929E+01 7.090422E-02 4.478388E+01 + 2.750007E+01 6.000000E+01 3 1.847924E+02 3.361934E-01 1.847893E+02 1.084297E+00 + 2.750007E+01 6.000000E+01 4 1.476844E+02 8.990929E+01 2.338234E-01 1.476842E+02 + 2.750007E+01 6.000000E+01 5 2.482252E+02 8.992173E+01 3.391076E-01 2.482250E+02 + 2.750007E+01 6.000000E+01 6 7.117751E+01 -1.170623E-03 7.117751E+01 -1.454244E-03 + 2.750007E+01 9.000000E+01 1 2.540039E-06 -9.005302E+01 -2.350846E-09 -2.540038E-06 + 2.750007E+01 9.000000E+01 2 5.194011E+01 8.990928E+01 8.223996E-02 5.194005E+01 + 2.750007E+01 9.000000E+01 3 1.856278E+02 3.368838E-01 1.856246E+02 1.091435E+00 + 2.750007E+01 9.000000E+01 4 1.719206E+02 8.990961E+01 2.712083E-01 1.719204E+02 + 2.750007E+01 9.000000E+01 5 1.161768E-04 -8.998840E+01 2.350978E-08 -1.161768E-04 + 2.750007E+01 9.000000E+01 6 6.119692E-06 1.799992E+02 -6.119692E-06 8.419448E-11 + 2.760007E+01 0.000000E+00 1 4.813564E+01 8.992233E+01 6.525052E-02 4.813560E+01 + 2.760007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.760007E+01 0.000000E+00 3 1.824921E+02 3.315973E-01 1.824891E+02 1.056161E+00 + 2.760007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.760007E+01 0.000000E+00 5 4.892461E+02 8.992234E+01 6.631604E-01 4.892456E+02 + 2.760007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.760007E+01 3.000000E+01 1 4.185225E+01 8.992235E+01 5.672759E-02 4.185221E+01 + 2.760007E+01 3.000000E+01 2 2.553599E+01 8.991008E+01 4.007721E-02 2.553596E+01 + 2.760007E+01 3.000000E+01 3 1.833097E+02 3.322738E-01 1.833067E+02 1.063057E+00 + 2.760007E+01 3.000000E+01 4 8.355618E+01 8.990940E+01 1.321238E-01 8.355607E+01 + 2.760007E+01 3.000000E+01 5 4.253565E+02 8.992234E+01 5.765409E-01 4.253561E+02 + 2.760007E+01 3.000000E+01 6 6.999789E+01 -1.154733E-03 6.999789E+01 -1.410730E-03 + 2.760007E+01 6.000000E+01 1 2.435611E+01 8.992236E+01 3.300640E-02 2.435608E+01 + 2.760007E+01 6.000000E+01 2 4.461734E+01 8.991006E+01 7.003406E-02 4.461728E+01 + 2.760007E+01 6.000000E+01 3 1.849570E+02 3.336269E-01 1.849538E+02 1.076977E+00 + 2.760007E+01 6.000000E+01 4 1.470889E+02 8.991006E+01 2.308832E-01 1.470887E+02 + 2.760007E+01 6.000000E+01 5 2.474967E+02 8.992235E+01 3.354477E-01 2.474964E+02 + 2.760007E+01 6.000000E+01 6 7.062881E+01 -1.151217E-03 7.062881E+01 -1.419111E-03 + 2.760007E+01 9.000000E+01 1 2.530414E-06 -9.005273E+01 -2.328743E-09 -2.530413E-06 + 2.760007E+01 9.000000E+01 2 5.174487E+01 8.991006E+01 8.122753E-02 5.174480E+01 + 2.760007E+01 9.000000E+01 3 1.857875E+02 3.343015E-01 1.857844E+02 1.084001E+00 + 2.760007E+01 9.000000E+01 4 1.712166E+02 8.991039E+01 2.677870E-01 1.712164E+02 + 2.760007E+01 9.000000E+01 5 1.157683E-04 -8.998853E+01 2.317238E-08 -1.157683E-04 + 2.760007E+01 9.000000E+01 6 6.072243E-06 1.799992E+02 -6.072243E-06 8.216394E-11 + 2.770007E+01 0.000000E+00 1 4.796184E+01 8.992294E+01 6.450374E-02 4.796180E+01 + 2.770007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.770007E+01 0.000000E+00 3 1.826720E+02 3.290921E-01 1.826689E+02 1.049214E+00 + 2.770007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.770007E+01 0.000000E+00 5 4.878579E+02 8.992294E+01 6.560824E-01 4.878575E+02 + 2.770007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.770007E+01 3.000000E+01 1 4.170002E+01 8.992295E+01 5.607668E-02 4.169999E+01 + 2.770007E+01 3.000000E+01 2 2.544310E+01 8.991085E+01 3.959041E-02 2.544307E+01 + 2.770007E+01 3.000000E+01 3 1.834834E+02 3.297578E-01 1.834803E+02 1.056007E+00 + 2.770007E+01 3.000000E+01 4 8.323134E+01 8.991018E+01 1.304788E-01 8.323124E+01 + 2.770007E+01 3.000000E+01 5 4.241356E+02 8.992295E+01 5.703716E-01 4.241352E+02 + 2.770007E+01 3.000000E+01 6 6.946550E+01 -1.135652E-03 6.946550E+01 -1.376866E-03 + 2.770007E+01 6.000000E+01 1 2.426589E+01 8.992297E+01 3.262576E-02 2.426587E+01 + 2.770007E+01 6.000000E+01 2 4.445199E+01 8.991084E+01 6.917854E-02 4.445193E+01 + 2.770007E+01 6.000000E+01 3 1.851198E+02 3.310885E-01 1.851167E+02 1.069724E+00 + 2.770007E+01 6.000000E+01 4 1.464987E+02 8.991084E+01 2.279924E-01 1.464985E+02 + 2.770007E+01 6.000000E+01 5 2.467748E+02 8.992295E+01 3.318392E-01 2.467746E+02 + 2.770007E+01 6.000000E+01 6 7.008666E+01 -1.132223E-03 7.008666E+01 -1.384983E-03 + 2.770007E+01 9.000000E+01 1 2.520866E-06 -9.005243E+01 -2.306889E-09 -2.520865E-06 + 2.770007E+01 9.000000E+01 2 5.155136E+01 8.991083E+01 8.023254E-02 5.155130E+01 + 2.770007E+01 9.000000E+01 3 1.859445E+02 3.317517E-01 1.859414E+02 1.076642E+00 + 2.770007E+01 9.000000E+01 4 1.705203E+02 8.991116E+01 2.644240E-01 1.705201E+02 + 2.770007E+01 9.000000E+01 5 1.153612E-04 -8.998866E+01 2.284139E-08 -1.153612E-04 + 2.770007E+01 9.000000E+01 6 6.025352E-06 1.799992E+02 -6.025352E-06 8.019128E-11 + 2.780007E+01 0.000000E+00 1 4.778943E+01 8.992355E+01 6.376842E-02 4.778939E+01 + 2.780007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.780007E+01 0.000000E+00 3 1.828498E+02 3.266193E-01 1.828468E+02 1.042345E+00 + 2.780007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.780007E+01 0.000000E+00 5 4.864798E+02 8.992355E+01 6.491061E-01 4.864794E+02 + 2.780007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.780007E+01 3.000000E+01 1 4.154868E+01 8.992355E+01 5.543589E-02 4.154864E+01 + 2.780007E+01 3.000000E+01 2 2.535089E+01 8.991161E+01 3.911167E-02 2.535086E+01 + 2.780007E+01 3.000000E+01 3 1.836570E+02 3.272706E-01 1.836540E+02 1.049034E+00 + 2.780007E+01 3.000000E+01 4 8.290870E+01 8.991094E+01 1.288622E-01 8.290860E+01 + 2.780007E+01 3.000000E+01 5 4.229265E+02 8.992355E+01 5.642854E-01 4.229261E+02 + 2.780007E+01 3.000000E+01 6 6.893920E+01 -1.116972E-03 6.893920E+01 -1.343959E-03 + 2.780007E+01 6.000000E+01 1 2.417634E+01 8.992357E+01 3.225103E-02 2.417632E+01 + 2.780007E+01 6.000000E+01 2 4.428777E+01 8.991159E+01 6.833703E-02 4.428772E+01 + 2.780007E+01 6.000000E+01 3 1.852806E+02 3.285831E-01 1.852776E+02 1.062552E+00 + 2.780007E+01 6.000000E+01 4 1.459133E+02 8.991159E+01 2.251514E-01 1.459132E+02 + 2.780007E+01 6.000000E+01 5 2.460548E+02 8.992356E+01 3.282776E-01 2.460546E+02 + 2.780007E+01 6.000000E+01 6 6.955079E+01 -1.113628E-03 6.955079E+01 -1.351822E-03 + 2.780007E+01 9.000000E+01 1 2.511394E-06 -9.005214E+01 -2.285283E-09 -2.511393E-06 + 2.780007E+01 9.000000E+01 2 5.135925E+01 8.991158E+01 7.925393E-02 5.135918E+01 + 2.780007E+01 9.000000E+01 3 1.860998E+02 3.292342E-01 1.860967E+02 1.069365E+00 + 2.780007E+01 9.000000E+01 4 1.698282E+02 8.991191E+01 2.611189E-01 1.698280E+02 + 2.780007E+01 9.000000E+01 5 1.149569E-04 -8.998878E+01 2.251673E-08 -1.149569E-04 + 2.780007E+01 9.000000E+01 6 5.979010E-06 1.799993E+02 -5.979010E-06 7.827420E-11 + 2.790007E+01 0.000000E+00 1 4.761823E+01 8.992414E+01 6.304449E-02 4.761819E+01 + 2.790007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.790007E+01 0.000000E+00 3 1.830271E+02 3.241700E-01 1.830242E+02 1.035532E+00 + 2.790007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.790007E+01 0.000000E+00 5 4.851045E+02 8.992415E+01 6.422254E-01 4.851041E+02 + 2.790007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.790007E+01 3.000000E+01 1 4.139865E+01 8.992416E+01 5.480478E-02 4.139861E+01 + 2.790007E+01 3.000000E+01 2 2.525932E+01 8.991235E+01 3.864074E-02 2.525929E+01 + 2.790007E+01 3.000000E+01 3 1.838277E+02 3.248135E-01 1.838247E+02 1.042126E+00 + 2.790007E+01 3.000000E+01 4 8.258921E+01 8.991171E+01 1.272726E-01 8.258911E+01 + 2.790007E+01 3.000000E+01 5 4.217174E+02 8.992415E+01 5.582868E-01 4.217170E+02 + 2.790007E+01 3.000000E+01 6 6.841891E+01 -1.098685E-03 6.841891E+01 -1.311978E-03 + 2.790007E+01 6.000000E+01 1 2.408754E+01 8.992417E+01 3.188213E-02 2.408752E+01 + 2.790007E+01 6.000000E+01 2 4.412487E+01 8.991234E+01 6.750953E-02 4.412482E+01 + 2.790007E+01 6.000000E+01 3 1.854400E+02 3.261012E-01 1.854370E+02 1.055433E+00 + 2.790007E+01 6.000000E+01 4 1.453328E+02 8.991234E+01 2.223575E-01 1.453327E+02 + 2.790007E+01 6.000000E+01 5 2.453364E+02 8.992416E+01 3.247714E-01 2.453362E+02 + 2.790007E+01 6.000000E+01 6 6.902113E+01 -1.095419E-03 6.902113E+01 -1.319592E-03 + 2.790007E+01 9.000000E+01 1 2.501991E-06 -9.005184E+01 -2.263919E-09 -2.501990E-06 + 2.790007E+01 9.000000E+01 2 5.116870E+01 8.991233E+01 7.829168E-02 5.116864E+01 + 2.790007E+01 9.000000E+01 3 1.862526E+02 3.267466E-01 1.862496E+02 1.062156E+00 + 2.790007E+01 9.000000E+01 4 1.691419E+02 8.991265E+01 2.578705E-01 1.691417E+02 + 2.790007E+01 9.000000E+01 5 1.145557E-04 -8.998890E+01 2.219828E-08 -1.145557E-04 + 2.790007E+01 9.000000E+01 6 5.933215E-06 1.799993E+02 -5.933215E-06 7.641110E-11 + 2.800007E+01 0.000000E+00 1 4.744809E+01 8.992474E+01 6.233130E-02 4.744805E+01 + 2.800007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.800007E+01 0.000000E+00 3 1.832010E+02 3.217495E-01 1.831982E+02 1.028776E+00 + 2.800007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.800007E+01 0.000000E+00 5 4.837372E+02 8.992474E+01 6.354414E-01 4.837368E+02 + 2.800007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.800007E+01 3.000000E+01 1 4.124949E+01 8.992474E+01 5.418339E-02 4.124946E+01 + 2.800007E+01 3.000000E+01 2 2.516845E+01 8.991309E+01 3.817756E-02 2.516842E+01 + 2.800007E+01 3.000000E+01 3 1.839966E+02 3.223823E-01 1.839937E+02 1.035276E+00 + 2.800007E+01 3.000000E+01 4 8.227146E+01 8.991245E+01 1.257093E-01 8.227136E+01 + 2.800007E+01 3.000000E+01 5 4.205184E+02 8.992474E+01 5.523752E-01 4.205181E+02 + 2.800007E+01 3.000000E+01 6 6.790480E+01 -1.080773E-03 6.790480E+01 -1.280892E-03 + 2.800007E+01 6.000000E+01 1 2.399938E+01 8.992476E+01 3.151871E-02 2.399936E+01 + 2.800007E+01 6.000000E+01 2 4.396320E+01 8.991308E+01 6.669591E-02 4.396315E+01 + 2.800007E+01 6.000000E+01 3 1.855984E+02 3.236502E-01 1.855955E+02 1.048396E+00 + 2.800007E+01 6.000000E+01 4 1.447571E+02 8.991308E+01 2.196120E-01 1.447570E+02 + 2.800007E+01 6.000000E+01 5 2.446227E+02 8.992474E+01 3.213120E-01 2.446225E+02 + 2.800007E+01 6.000000E+01 6 6.849780E+01 -1.077585E-03 6.849780E+01 -1.288266E-03 + 2.800007E+01 9.000000E+01 1 2.492656E-06 -9.005155E+01 -2.242774E-09 -2.492656E-06 + 2.800007E+01 9.000000E+01 2 5.097934E+01 8.991308E+01 7.734487E-02 5.097928E+01 + 2.800007E+01 9.000000E+01 3 1.864052E+02 3.242849E-01 1.864023E+02 1.055018E+00 + 2.800007E+01 9.000000E+01 4 1.684627E+02 8.991338E+01 2.546772E-01 1.684625E+02 + 2.800007E+01 9.000000E+01 5 1.141573E-04 -8.998901E+01 2.188575E-08 -1.141573E-04 + 2.800007E+01 9.000000E+01 6 5.887949E-06 1.799993E+02 -5.887949E-06 7.460020E-11 + 2.810007E+01 0.000000E+00 1 4.727943E+01 8.992532E+01 6.162915E-02 4.727939E+01 + 2.810007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.810007E+01 0.000000E+00 3 1.833738E+02 3.193567E-01 1.833709E+02 1.022088E+00 + 2.810007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.810007E+01 0.000000E+00 5 4.823730E+02 8.992532E+01 6.287509E-01 4.823727E+02 + 2.810007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.810007E+01 3.000000E+01 1 4.110149E+01 8.992532E+01 5.357149E-02 4.110145E+01 + 2.810007E+01 3.000000E+01 2 2.507817E+01 8.991382E+01 3.772182E-02 2.507814E+01 + 2.810007E+01 3.000000E+01 3 1.841638E+02 3.199789E-01 1.841610E+02 1.028492E+00 + 2.810007E+01 3.000000E+01 4 8.195668E+01 8.991319E+01 1.241722E-01 8.195659E+01 + 2.810007E+01 3.000000E+01 5 4.193215E+02 8.992532E+01 5.465394E-01 4.193211E+02 + 2.810007E+01 3.000000E+01 6 6.739633E+01 -1.063236E-03 6.739633E+01 -1.250672E-03 + 2.810007E+01 6.000000E+01 1 2.391177E+01 8.992534E+01 3.116108E-02 2.391175E+01 + 2.810007E+01 6.000000E+01 2 4.380273E+01 8.991380E+01 6.589521E-02 4.380268E+01 + 2.810007E+01 6.000000E+01 3 1.857555E+02 3.212252E-01 1.857526E+02 1.041421E+00 + 2.810007E+01 6.000000E+01 4 1.441860E+02 8.991380E+01 2.169119E-01 1.441858E+02 + 2.810007E+01 6.000000E+01 5 2.439112E+02 8.992532E+01 3.179022E-01 2.439110E+02 + 2.810007E+01 6.000000E+01 6 6.798024E+01 -1.060128E-03 6.798024E+01 -1.257820E-03 + 2.810007E+01 9.000000E+01 1 2.483399E-06 -9.005126E+01 -2.221880E-09 -2.483398E-06 + 2.810007E+01 9.000000E+01 2 5.079157E+01 8.991380E+01 7.641418E-02 5.079152E+01 + 2.810007E+01 9.000000E+01 3 1.865555E+02 3.218505E-01 1.865526E+02 1.047943E+00 + 2.810007E+01 9.000000E+01 4 1.677881E+02 8.991411E+01 2.515384E-01 1.677879E+02 + 2.810007E+01 9.000000E+01 5 1.137617E-04 -8.998913E+01 2.157909E-08 -1.137617E-04 + 2.810007E+01 9.000000E+01 6 5.843222E-06 1.799993E+02 -5.843222E-06 7.283976E-11 + 2.820007E+01 0.000000E+00 1 4.711179E+01 8.992589E+01 6.093765E-02 4.711176E+01 + 2.820007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.820007E+01 0.000000E+00 3 1.835450E+02 3.169907E-01 1.835422E+02 1.015463E+00 + 2.820007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.820007E+01 0.000000E+00 5 4.810190E+02 8.992590E+01 6.221502E-01 4.810186E+02 + 2.820007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.820007E+01 3.000000E+01 1 4.095451E+01 8.992590E+01 5.296883E-02 4.095447E+01 + 2.820007E+01 3.000000E+01 2 2.498859E+01 8.991454E+01 3.727363E-02 2.498856E+01 + 2.820007E+01 3.000000E+01 3 1.843295E+02 3.176023E-01 1.843267E+02 1.021771E+00 + 2.820007E+01 3.000000E+01 4 8.164420E+01 8.991393E+01 1.226603E-01 8.164410E+01 + 2.820007E+01 3.000000E+01 5 4.181278E+02 8.992590E+01 5.407942E-01 4.181275E+02 + 2.820007E+01 3.000000E+01 6 6.689375E+01 -1.046059E-03 6.689375E+01 -1.221291E-03 + 2.820007E+01 6.000000E+01 1 2.382490E+01 8.992591E+01 3.080876E-02 2.382488E+01 + 2.820007E+01 6.000000E+01 2 4.364328E+01 8.991452E+01 6.510767E-02 4.364323E+01 + 2.820007E+01 6.000000E+01 3 1.859091E+02 3.188306E-01 1.859062E+02 1.034512E+00 + 2.820007E+01 6.000000E+01 4 1.436199E+02 8.991452E+01 2.142572E-01 1.436198E+02 + 2.820007E+01 6.000000E+01 5 2.432052E+02 8.992590E+01 3.145411E-01 2.432050E+02 + 2.820007E+01 6.000000E+01 6 6.746886E+01 -1.043021E-03 6.746886E+01 -1.228213E-03 + 2.820007E+01 9.000000E+01 1 2.474212E-06 -9.005098E+01 -2.201207E-09 -2.474211E-06 + 2.820007E+01 9.000000E+01 2 5.060510E+01 8.991452E+01 7.549848E-02 5.060505E+01 + 2.820007E+01 9.000000E+01 3 1.867050E+02 3.194449E-01 1.867021E+02 1.040943E+00 + 2.820007E+01 9.000000E+01 4 1.671197E+02 8.991483E+01 2.484505E-01 1.671196E+02 + 2.820007E+01 9.000000E+01 5 1.133686E-04 -8.998924E+01 2.127823E-08 -1.133686E-04 + 2.820007E+01 9.000000E+01 6 5.799000E-06 1.799993E+02 -5.799000E-06 7.112817E-11 + 2.830007E+01 0.000000E+00 1 4.694517E+01 8.992645E+01 6.025654E-02 4.694513E+01 + 2.830007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.830007E+01 0.000000E+00 3 1.837143E+02 3.146522E-01 1.837115E+02 1.008901E+00 + 2.830007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.830007E+01 0.000000E+00 5 4.796661E+02 8.992646E+01 6.156455E-01 4.796657E+02 + 2.830007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.830007E+01 3.000000E+01 1 4.080869E+01 8.992646E+01 5.237546E-02 4.080865E+01 + 2.830007E+01 3.000000E+01 2 2.489963E+01 8.991525E+01 3.683248E-02 2.489960E+01 + 2.830007E+01 3.000000E+01 3 1.844937E+02 3.152546E-01 1.844909E+02 1.015122E+00 + 2.830007E+01 3.000000E+01 4 8.133396E+01 8.991464E+01 1.211739E-01 8.133387E+01 + 2.830007E+01 3.000000E+01 5 4.169438E+02 8.992646E+01 5.351219E-01 4.169435E+02 + 2.830007E+01 3.000000E+01 6 6.639690E+01 -1.029236E-03 6.639690E+01 -1.192724E-03 + 2.830007E+01 6.000000E+01 1 2.373865E+01 8.992648E+01 3.046190E-02 2.373863E+01 + 2.830007E+01 6.000000E+01 2 4.348512E+01 8.991524E+01 6.433313E-02 4.348507E+01 + 2.830007E+01 6.000000E+01 3 1.860634E+02 3.164616E-01 1.860605E+02 1.027678E+00 + 2.830007E+01 6.000000E+01 4 1.430579E+02 8.991524E+01 2.116471E-01 1.430577E+02 + 2.830007E+01 6.000000E+01 5 2.425011E+02 8.992647E+01 3.112257E-01 2.425009E+02 + 2.830007E+01 6.000000E+01 6 6.696328E+01 -1.026270E-03 6.696328E+01 -1.199433E-03 + 2.830007E+01 9.000000E+01 1 2.465086E-06 -9.005069E+01 -2.180761E-09 -2.465085E-06 + 2.830007E+01 9.000000E+01 2 5.042012E+01 8.991524E+01 7.459762E-02 5.042007E+01 + 2.830007E+01 9.000000E+01 3 1.868528E+02 3.170685E-01 1.868499E+02 1.034017E+00 + 2.830007E+01 9.000000E+01 4 1.664560E+02 8.991553E+01 2.454160E-01 1.664558E+02 + 2.830007E+01 9.000000E+01 5 1.129783E-04 -8.998936E+01 2.098303E-08 -1.129783E-04 + 2.830007E+01 9.000000E+01 6 5.755298E-06 1.799993E+02 -5.755298E-06 6.946392E-11 + 2.840007E+01 0.000000E+00 1 4.677987E+01 8.992702E+01 5.958563E-02 4.677983E+01 + 2.840007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.840007E+01 0.000000E+00 3 1.838813E+02 3.123398E-01 1.838786E+02 1.002398E+00 + 2.840007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.840007E+01 0.000000E+00 5 4.783223E+02 8.992702E+01 6.092303E-01 4.783219E+02 + 2.840007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.840007E+01 3.000000E+01 1 4.066379E+01 8.992703E+01 5.179086E-02 4.066375E+01 + 2.840007E+01 3.000000E+01 2 2.481134E+01 8.991595E+01 3.639850E-02 2.481132E+01 + 2.840007E+01 3.000000E+01 3 1.846556E+02 3.129305E-01 1.846528E+02 1.008522E+00 + 2.840007E+01 3.000000E+01 4 8.102666E+01 8.991535E+01 1.197123E-01 8.102657E+01 + 2.840007E+01 3.000000E+01 5 4.157625E+02 8.992703E+01 5.295332E-01 4.157622E+02 + 2.840007E+01 3.000000E+01 6 6.590559E+01 -1.012755E-03 6.590559E+01 -1.164941E-03 + 2.840007E+01 6.000000E+01 1 2.365303E+01 8.992704E+01 3.012023E-02 2.365301E+01 + 2.840007E+01 6.000000E+01 2 4.332825E+01 8.991594E+01 6.357099E-02 4.332820E+01 + 2.840007E+01 6.000000E+01 3 1.862146E+02 3.141187E-01 1.862118E+02 1.020899E+00 + 2.840007E+01 6.000000E+01 4 1.425012E+02 8.991594E+01 2.090798E-01 1.425010E+02 + 2.840007E+01 6.000000E+01 5 2.418004E+02 8.992703E+01 3.079569E-01 2.418002E+02 + 2.840007E+01 6.000000E+01 6 6.646344E+01 -1.009861E-03 6.646344E+01 -1.171445E-03 + 2.840007E+01 9.000000E+01 1 2.456037E-06 -9.005040E+01 -2.160548E-09 -2.456036E-06 + 2.840007E+01 9.000000E+01 2 5.023649E+01 8.991593E+01 7.371149E-02 5.023643E+01 + 2.840007E+01 9.000000E+01 3 1.869987E+02 3.147150E-01 1.869958E+02 1.027143E+00 + 2.840007E+01 9.000000E+01 4 1.657985E+02 8.991622E+01 2.424307E-01 1.657984E+02 + 2.840007E+01 9.000000E+01 5 1.125906E-04 -8.998947E+01 2.069316E-08 -1.125906E-04 + 2.840007E+01 9.000000E+01 6 5.712103E-06 1.799993E+02 -5.712103E-06 6.784557E-11 + 2.850007E+01 0.000000E+00 1 4.661565E+01 8.992757E+01 5.892463E-02 4.661562E+01 + 2.850007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.850007E+01 0.000000E+00 3 1.840484E+02 3.100492E-01 1.840457E+02 9.959512E-01 + 2.850007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.850007E+01 0.000000E+00 5 4.769853E+02 8.992758E+01 6.029006E-01 4.769849E+02 + 2.850007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.850007E+01 3.000000E+01 1 4.051995E+01 8.992758E+01 5.121486E-02 4.051992E+01 + 2.850007E+01 3.000000E+01 2 2.472359E+01 8.991664E+01 3.597154E-02 2.472357E+01 + 2.850007E+01 3.000000E+01 3 1.848165E+02 3.106342E-01 1.848137E+02 1.001994E+00 + 2.850007E+01 3.000000E+01 4 8.072145E+01 8.991605E+01 1.182747E-01 8.072137E+01 + 2.850007E+01 3.000000E+01 5 4.145861E+02 8.992758E+01 5.240204E-01 4.145857E+02 + 2.850007E+01 3.000000E+01 6 6.541982E+01 -9.966095E-04 6.541982E+01 -1.137920E-03 + 2.850007E+01 6.000000E+01 1 2.356802E+01 8.992760E+01 2.978378E-02 2.356800E+01 + 2.850007E+01 6.000000E+01 2 4.317225E+01 8.991663E+01 6.282101E-02 4.317220E+01 + 2.850007E+01 6.000000E+01 3 1.863645E+02 3.118035E-01 1.863618E+02 1.014191E+00 + 2.850007E+01 6.000000E+01 4 1.419480E+02 8.991663E+01 2.065548E-01 1.419479E+02 + 2.850007E+01 6.000000E+01 5 2.411035E+02 8.992758E+01 3.047306E-01 2.411033E+02 + 2.850007E+01 6.000000E+01 6 6.596940E+01 -9.937821E-04 6.596940E+01 -1.144224E-03 + 2.850007E+01 9.000000E+01 1 2.447048E-06 -9.005013E+01 -2.140565E-09 -2.447047E-06 + 2.850007E+01 9.000000E+01 2 5.005430E+01 8.991662E+01 7.283960E-02 5.005425E+01 + 2.850007E+01 9.000000E+01 3 1.871428E+02 3.123914E-01 1.871401E+02 1.020346E+00 + 2.850007E+01 9.000000E+01 4 1.651463E+02 8.991691E+01 2.394964E-01 1.651462E+02 + 2.850007E+01 9.000000E+01 5 1.122053E-04 -8.998958E+01 2.040873E-08 -1.122053E-04 + 2.850007E+01 9.000000E+01 6 5.669390E-06 1.799993E+02 -5.669390E-06 6.627149E-11 + 2.860007E+01 0.000000E+00 1 4.645269E+01 8.992812E+01 5.827371E-02 4.645265E+01 + 2.860007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.860007E+01 0.000000E+00 3 1.842122E+02 3.077878E-01 1.842095E+02 9.895664E-01 + 2.860007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.860007E+01 0.000000E+00 5 4.756524E+02 8.992813E+01 5.966589E-01 4.756520E+02 + 2.860007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.860007E+01 3.000000E+01 1 4.037712E+01 8.992813E+01 5.064785E-02 4.037709E+01 + 2.860007E+01 3.000000E+01 2 2.463656E+01 8.991733E+01 3.555132E-02 2.463653E+01 + 2.860007E+01 3.000000E+01 3 1.849752E+02 3.083637E-01 1.849725E+02 9.955246E-01 + 2.860007E+01 3.000000E+01 4 8.041879E+01 8.991674E+01 1.168599E-01 8.041870E+01 + 2.860007E+01 3.000000E+01 5 4.134140E+02 8.992813E+01 5.185757E-01 4.134136E+02 + 2.860007E+01 3.000000E+01 6 6.493947E+01 -9.807913E-04 6.493947E+01 -1.111636E-03 + 2.860007E+01 6.000000E+01 1 2.348356E+01 8.992815E+01 2.945225E-02 2.348354E+01 + 2.860007E+01 6.000000E+01 2 4.301755E+01 8.991731E+01 6.208301E-02 4.301750E+01 + 2.860007E+01 6.000000E+01 3 1.865120E+02 3.095161E-01 1.865093E+02 1.007547E+00 + 2.860007E+01 6.000000E+01 4 1.413996E+02 8.991731E+01 2.040714E-01 1.413995E+02 + 2.860007E+01 6.000000E+01 5 2.404083E+02 8.992814E+01 3.015527E-01 2.404081E+02 + 2.860007E+01 6.000000E+01 6 6.548082E+01 -9.780284E-04 6.548082E+01 -1.117745E-03 + 2.860007E+01 9.000000E+01 1 2.438129E-06 -9.004984E+01 -2.120792E-09 -2.438128E-06 + 2.860007E+01 9.000000E+01 2 4.987325E+01 8.991730E+01 7.198154E-02 4.987319E+01 + 2.860007E+01 9.000000E+01 3 1.872858E+02 3.100912E-01 1.872831E+02 1.013607E+00 + 2.860007E+01 9.000000E+01 4 1.644998E+02 8.991759E+01 2.366087E-01 1.644997E+02 + 2.860007E+01 9.000000E+01 5 1.118234E-04 -8.998969E+01 2.012946E-08 -1.118234E-04 + 2.860007E+01 9.000000E+01 6 5.627169E-06 1.799993E+02 -5.627169E-06 6.474039E-11 + 2.870007E+01 0.000000E+00 1 4.629090E+01 8.992867E+01 5.763241E-02 4.629087E+01 + 2.870007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.870007E+01 0.000000E+00 3 1.843742E+02 3.055500E-01 1.843716E+02 9.832358E-01 + 2.870007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.870007E+01 0.000000E+00 5 4.743232E+02 8.992867E+01 5.905062E-01 4.743228E+02 + 2.870007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.870007E+01 3.000000E+01 1 4.023531E+01 8.992867E+01 5.008899E-02 4.023528E+01 + 2.870007E+01 3.000000E+01 2 2.455005E+01 8.991799E+01 3.513776E-02 2.455002E+01 + 2.870007E+01 3.000000E+01 3 1.851326E+02 3.061164E-01 1.851300E+02 9.891106E-01 + 2.870007E+01 3.000000E+01 4 8.011801E+01 8.991743E+01 1.154684E-01 8.011793E+01 + 2.870007E+01 3.000000E+01 5 4.122494E+02 8.992867E+01 5.132151E-01 4.122491E+02 + 2.870007E+01 3.000000E+01 6 6.446452E+01 -9.652921E-04 6.446452E+01 -1.086068E-03 + 2.870007E+01 6.000000E+01 1 2.339984E+01 8.992868E+01 2.912585E-02 2.339982E+01 + 2.870007E+01 6.000000E+01 2 4.286395E+01 8.991798E+01 6.135697E-02 4.286390E+01 + 2.870007E+01 6.000000E+01 3 1.866599E+02 3.072492E-01 1.866572E+02 1.000961E+00 + 2.870007E+01 6.000000E+01 4 1.408558E+02 8.991798E+01 2.016285E-01 1.408556E+02 + 2.870007E+01 6.000000E+01 5 2.397190E+02 8.992867E+01 2.984205E-01 2.397188E+02 + 2.870007E+01 6.000000E+01 6 6.499773E+01 -9.625954E-04 6.499773E+01 -1.091992E-03 + 2.870007E+01 9.000000E+01 1 2.429276E-06 -9.004955E+01 -2.101240E-09 -2.429275E-06 + 2.870007E+01 9.000000E+01 2 4.969361E+01 8.991798E+01 7.113768E-02 4.969356E+01 + 2.870007E+01 9.000000E+01 3 1.874273E+02 3.078184E-01 1.874246E+02 1.006938E+00 + 2.870007E+01 9.000000E+01 4 1.638578E+02 8.991826E+01 2.337690E-01 1.638577E+02 + 2.870007E+01 9.000000E+01 5 1.114432E-04 -8.998979E+01 1.985536E-08 -1.114432E-04 + 2.870007E+01 9.000000E+01 6 5.585436E-06 1.799993E+02 -5.585436E-06 6.325095E-11 + 2.880007E+01 0.000000E+00 1 4.613022E+01 8.992920E+01 5.700032E-02 4.613018E+01 + 2.880007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.880007E+01 0.000000E+00 3 1.845348E+02 3.033354E-01 1.845323E+02 9.769601E-01 + 2.880007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.880007E+01 0.000000E+00 5 4.730033E+02 8.992921E+01 5.844322E-01 4.730029E+02 + 2.880007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.880007E+01 3.000000E+01 1 4.009457E+01 8.992921E+01 4.953853E-02 4.009454E+01 + 2.880007E+01 3.000000E+01 2 2.446420E+01 8.991866E+01 3.473059E-02 2.446418E+01 + 2.880007E+01 3.000000E+01 3 1.852882E+02 3.038919E-01 1.852856E+02 9.827483E-01 + 2.880007E+01 3.000000E+01 4 7.981991E+01 8.991810E+01 1.140992E-01 7.981982E+01 + 2.880007E+01 3.000000E+01 5 4.110927E+02 8.992921E+01 5.079241E-01 4.110923E+02 + 2.880007E+01 3.000000E+01 6 6.399482E+01 -9.501004E-04 6.399482E+01 -1.061186E-03 + 2.880007E+01 6.000000E+01 1 2.331664E+01 8.992922E+01 2.880419E-02 2.331662E+01 + 2.880007E+01 6.000000E+01 2 4.271136E+01 8.991865E+01 6.064233E-02 4.271132E+01 + 2.880007E+01 6.000000E+01 3 1.868046E+02 3.050091E-01 1.868019E+02 9.944332E-01 + 2.880007E+01 6.000000E+01 4 1.403165E+02 8.991865E+01 1.992254E-01 1.403164E+02 + 2.880007E+01 6.000000E+01 5 2.390303E+02 8.992921E+01 2.953278E-01 2.390302E+02 + 2.880007E+01 6.000000E+01 6 6.452022E+01 -9.474657E-04 6.452022E+01 -1.066932E-03 + 2.880007E+01 9.000000E+01 1 2.420488E-06 -9.004929E+01 -2.081912E-09 -2.420487E-06 + 2.880007E+01 9.000000E+01 2 4.951539E+01 8.991865E+01 7.030696E-02 4.951534E+01 + 2.880007E+01 9.000000E+01 3 1.875682E+02 3.055684E-01 1.875655E+02 1.000329E+00 + 2.880007E+01 9.000000E+01 4 1.632213E+02 8.991892E+01 2.309761E-01 1.632211E+02 + 2.880007E+01 9.000000E+01 5 1.110659E-04 -8.998990E+01 1.958618E-08 -1.110659E-04 + 2.880007E+01 9.000000E+01 6 5.544158E-06 1.799994E+02 -5.544158E-06 6.180179E-11 + 2.890007E+01 0.000000E+00 1 4.597051E+01 8.992973E+01 5.637762E-02 4.597048E+01 + 2.890007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.890007E+01 0.000000E+00 3 1.846951E+02 3.011470E-01 1.846926E+02 9.707543E-01 + 2.890007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.890007E+01 0.000000E+00 5 4.716823E+02 8.992973E+01 5.784411E-01 4.716820E+02 + 2.890007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.890007E+01 3.000000E+01 1 3.995467E+01 8.992974E+01 4.899608E-02 3.995464E+01 + 2.890007E+01 3.000000E+01 2 2.437893E+01 8.991932E+01 3.433002E-02 2.437890E+01 + 2.890007E+01 3.000000E+01 3 1.854426E+02 3.016971E-01 1.854400E+02 9.764636E-01 + 2.890007E+01 3.000000E+01 4 7.952345E+01 8.991876E+01 1.127526E-01 7.952338E+01 + 2.890007E+01 3.000000E+01 5 4.099373E+02 8.992974E+01 5.027046E-01 4.099370E+02 + 2.890007E+01 3.000000E+01 6 6.353027E+01 -9.352144E-04 6.353027E+01 -1.036977E-03 + 2.890007E+01 6.000000E+01 1 2.323405E+01 8.992975E+01 2.848738E-02 2.323404E+01 + 2.890007E+01 6.000000E+01 2 4.255993E+01 8.991931E+01 5.993906E-02 4.255989E+01 + 2.890007E+01 6.000000E+01 3 1.869487E+02 3.027964E-01 1.869461E+02 9.879808E-01 + 2.890007E+01 6.000000E+01 4 1.397805E+02 8.991930E+01 1.968617E-01 1.397803E+02 + 2.890007E+01 6.000000E+01 5 2.383465E+02 8.992974E+01 2.922797E-01 2.383463E+02 + 2.890007E+01 6.000000E+01 6 6.404784E+01 -9.326427E-04 6.404784E+01 -1.042551E-03 + 2.890007E+01 9.000000E+01 1 2.411764E-06 -9.004900E+01 -2.062795E-09 -2.411763E-06 + 2.890007E+01 9.000000E+01 2 4.933831E+01 8.991930E+01 6.948937E-02 4.933826E+01 + 2.890007E+01 9.000000E+01 3 1.877075E+02 3.033449E-01 1.877048E+02 9.937877E-01 + 2.890007E+01 9.000000E+01 4 1.625896E+02 8.991957E+01 2.282291E-01 1.625895E+02 + 2.890007E+01 9.000000E+01 5 1.106909E-04 -8.999000E+01 1.932194E-08 -1.106909E-04 + 2.890007E+01 9.000000E+01 6 5.503363E-06 1.799994E+02 -5.503363E-06 6.039165E-11 + 2.900007E+01 0.000000E+00 1 4.581194E+01 8.993026E+01 5.576444E-02 4.581190E+01 + 2.900007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.900007E+01 0.000000E+00 3 1.848529E+02 2.989812E-01 1.848504E+02 9.645963E-01 + 2.900007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.900007E+01 0.000000E+00 5 4.703759E+02 8.993026E+01 5.725312E-01 4.703756E+02 + 2.900007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.900007E+01 3.000000E+01 1 3.981580E+01 8.993026E+01 4.846161E-02 3.981577E+01 + 2.900007E+01 3.000000E+01 2 2.429428E+01 8.991997E+01 3.393558E-02 2.429426E+01 + 2.900007E+01 3.000000E+01 3 1.855956E+02 2.995215E-01 1.855931E+02 9.702220E-01 + 2.900007E+01 3.000000E+01 4 7.922995E+01 8.991942E+01 1.114271E-01 7.922987E+01 + 2.900007E+01 3.000000E+01 5 4.087864E+02 8.993026E+01 4.975584E-01 4.087861E+02 + 2.900007E+01 3.000000E+01 6 6.307088E+01 -9.206262E-04 6.307088E+01 -1.013420E-03 + 2.900007E+01 6.000000E+01 1 2.315207E+01 8.993027E+01 2.817525E-02 2.315206E+01 + 2.900007E+01 6.000000E+01 2 4.240964E+01 8.991996E+01 5.924690E-02 4.240960E+01 + 2.900007E+01 6.000000E+01 3 1.870907E+02 3.006066E-01 1.870882E+02 9.815809E-01 + 2.900007E+01 6.000000E+01 4 1.392496E+02 8.991995E+01 1.945360E-01 1.392495E+02 + 2.900007E+01 6.000000E+01 5 2.376660E+02 8.993027E+01 2.892712E-01 2.376659E+02 + 2.900007E+01 6.000000E+01 6 6.358087E+01 -9.181129E-04 6.358087E+01 -1.018826E-03 + 2.900007E+01 9.000000E+01 1 2.403105E-06 -9.004873E+01 -2.043889E-09 -2.403104E-06 + 2.900007E+01 9.000000E+01 2 4.916262E+01 8.991995E+01 6.868486E-02 4.916257E+01 + 2.900007E+01 9.000000E+01 3 1.878439E+02 3.011484E-01 1.878413E+02 9.873088E-01 + 2.900007E+01 9.000000E+01 4 1.619632E+02 8.992022E+01 2.255255E-01 1.619631E+02 + 2.900007E+01 9.000000E+01 5 1.103186E-04 -8.999010E+01 1.906248E-08 -1.103186E-04 + 2.900007E+01 9.000000E+01 6 5.463011E-06 1.799994E+02 -5.463011E-06 5.901934E-11 + 2.910007E+01 0.000000E+00 1 4.565451E+01 8.993078E+01 5.515980E-02 4.565447E+01 + 2.910007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.910007E+01 0.000000E+00 3 1.850083E+02 2.968405E-01 1.850058E+02 9.584949E-01 + 2.910007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.910007E+01 0.000000E+00 5 4.690703E+02 8.993078E+01 5.667050E-01 4.690700E+02 + 2.910007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.910007E+01 3.000000E+01 1 3.967776E+01 8.993078E+01 4.793527E-02 3.967773E+01 + 2.910007E+01 3.000000E+01 2 2.421017E+01 8.992061E+01 3.354733E-02 2.421014E+01 + 2.910007E+01 3.000000E+01 3 1.857465E+02 2.973713E-01 1.857440E+02 9.640398E-01 + 2.910007E+01 3.000000E+01 4 7.893834E+01 8.992007E+01 1.101233E-01 7.893826E+01 + 2.910007E+01 3.000000E+01 5 4.076400E+02 8.993078E+01 4.924771E-01 4.076396E+02 + 2.910007E+01 3.000000E+01 6 6.261650E+01 -9.063248E-04 6.261650E+01 -9.904898E-04 + 2.910007E+01 6.000000E+01 1 2.307065E+01 8.993079E+01 2.786764E-02 2.307064E+01 + 2.910007E+01 6.000000E+01 2 4.226030E+01 8.992059E+01 5.856558E-02 4.226025E+01 + 2.910007E+01 6.000000E+01 3 1.872321E+02 2.984377E-01 1.872296E+02 9.752351E-01 + 2.910007E+01 6.000000E+01 4 1.387225E+02 8.992059E+01 1.922476E-01 1.387224E+02 + 2.910007E+01 6.000000E+01 5 2.369875E+02 8.993078E+01 2.863030E-01 2.369873E+02 + 2.910007E+01 6.000000E+01 6 6.311901E+01 -9.038706E-04 6.311901E+01 -9.957352E-04 + 2.910007E+01 9.000000E+01 1 2.394512E-06 -9.004845E+01 -2.025197E-09 -2.394511E-06 + 2.910007E+01 9.000000E+01 2 4.898807E+01 8.992059E+01 6.789295E-02 4.898802E+01 + 2.910007E+01 9.000000E+01 3 1.879809E+02 2.989702E-01 1.879783E+02 9.808823E-01 + 2.910007E+01 9.000000E+01 4 1.613429E+02 8.992085E+01 2.228654E-01 1.613427E+02 + 2.910007E+01 9.000000E+01 5 1.099485E-04 -8.999020E+01 1.880766E-08 -1.099485E-04 + 2.910007E+01 9.000000E+01 6 5.423113E-06 1.799994E+02 -5.423113E-06 5.768371E-11 + 2.920008E+01 0.000000E+00 1 4.549806E+01 8.993128E+01 5.456414E-02 4.549802E+01 + 2.920008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.920008E+01 0.000000E+00 3 1.851628E+02 2.947226E-01 1.851604E+02 9.524513E-01 + 2.920008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.920008E+01 0.000000E+00 5 4.677693E+02 8.993129E+01 5.609504E-01 4.677689E+02 + 2.920008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.920008E+01 3.000000E+01 1 3.954085E+01 8.993129E+01 4.741634E-02 3.954082E+01 + 2.920008E+01 3.000000E+01 2 2.412669E+01 8.992123E+01 3.316514E-02 2.412667E+01 + 2.920008E+01 3.000000E+01 3 1.858962E+02 2.952467E-01 1.858938E+02 9.579241E-01 + 2.920008E+01 3.000000E+01 4 7.864951E+01 8.992072E+01 1.088400E-01 7.864943E+01 + 2.920008E+01 3.000000E+01 5 4.065047E+02 8.993129E+01 4.874707E-01 4.065044E+02 + 2.920008E+01 3.000000E+01 6 6.216718E+01 -8.923067E-04 6.216718E+01 -9.681724E-04 + 2.920008E+01 6.000000E+01 1 2.298986E+01 8.993130E+01 2.756465E-02 2.298984E+01 + 2.920008E+01 6.000000E+01 2 4.211215E+01 8.992123E+01 5.789485E-02 4.211211E+01 + 2.920008E+01 6.000000E+01 3 1.873722E+02 2.962984E-01 1.873697E+02 9.689689E-01 + 2.920008E+01 6.000000E+01 4 1.382000E+02 8.992123E+01 1.899966E-01 1.381999E+02 + 2.920008E+01 6.000000E+01 5 2.363138E+02 8.993129E+01 2.833776E-01 2.363137E+02 + 2.920008E+01 6.000000E+01 6 6.266233E+01 -8.899080E-04 6.266233E+01 -9.732604E-04 + 2.920008E+01 9.000000E+01 1 2.385977E-06 -9.004819E+01 -2.006705E-09 -2.385976E-06 + 2.920008E+01 9.000000E+01 2 4.881489E+01 8.992123E+01 6.711344E-02 4.881485E+01 + 2.920008E+01 9.000000E+01 3 1.881146E+02 2.968224E-01 1.881121E+02 9.745286E-01 + 2.920008E+01 9.000000E+01 4 1.607267E+02 8.992149E+01 2.202494E-01 1.607265E+02 + 2.920008E+01 9.000000E+01 5 1.095814E-04 -8.999030E+01 1.855737E-08 -1.095814E-04 + 2.920008E+01 9.000000E+01 6 5.383661E-06 1.799994E+02 -5.383661E-06 5.638373E-11 + 2.930008E+01 0.000000E+00 1 4.534274E+01 8.993180E+01 5.397703E-02 4.534271E+01 + 2.930008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.930008E+01 0.000000E+00 3 1.853160E+02 2.926262E-01 1.853136E+02 9.464585E-01 + 2.930008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.930008E+01 0.000000E+00 5 4.664778E+02 8.993180E+01 5.552765E-01 4.664775E+02 + 2.930008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.930008E+01 3.000000E+01 1 3.940488E+01 8.993180E+01 4.690501E-02 3.940486E+01 + 2.930008E+01 3.000000E+01 2 2.404375E+01 8.992187E+01 3.278877E-02 2.404373E+01 + 2.930008E+01 3.000000E+01 3 1.860446E+02 2.931412E-01 1.860421E+02 9.518520E-01 + 2.930008E+01 3.000000E+01 4 7.836202E+01 8.992135E+01 1.075768E-01 7.836195E+01 + 2.930008E+01 3.000000E+01 5 4.053678E+02 8.993180E+01 4.825287E-01 4.053676E+02 + 2.930008E+01 3.000000E+01 6 6.172264E+01 -8.785634E-04 6.172264E+01 -9.464441E-04 + 2.930008E+01 6.000000E+01 1 2.290953E+01 8.993181E+01 2.726608E-02 2.290951E+01 + 2.930008E+01 6.000000E+01 2 4.196497E+01 8.992186E+01 5.723463E-02 4.196493E+01 + 2.930008E+01 6.000000E+01 3 1.875102E+02 2.941777E-01 1.875077E+02 9.627420E-01 + 2.930008E+01 6.000000E+01 4 1.376808E+02 8.992186E+01 1.877802E-01 1.376807E+02 + 2.930008E+01 6.000000E+01 5 2.356416E+02 8.993180E+01 2.804900E-01 2.356414E+02 + 2.930008E+01 6.000000E+01 6 6.221064E+01 -8.762188E-04 6.221064E+01 -9.513813E-04 + 2.930008E+01 9.000000E+01 1 2.377505E-06 -9.004792E+01 -1.988428E-09 -2.377504E-06 + 2.930008E+01 9.000000E+01 2 4.864286E+01 8.992185E+01 6.634599E-02 4.864281E+01 + 2.930008E+01 9.000000E+01 3 1.882483E+02 2.946921E-01 1.882458E+02 9.682223E-01 + 2.930008E+01 9.000000E+01 4 1.601145E+02 8.992210E+01 2.176737E-01 1.601144E+02 + 2.930008E+01 9.000000E+01 5 1.092160E-04 -8.999039E+01 1.831153E-08 -1.092160E-04 + 2.930008E+01 9.000000E+01 6 5.344647E-06 1.799994E+02 -5.344647E-06 5.511807E-11 + 2.940008E+01 0.000000E+00 1 4.518850E+01 8.993230E+01 5.339843E-02 4.518847E+01 + 2.940008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.940008E+01 0.000000E+00 3 1.854676E+02 2.905528E-01 1.854652E+02 9.405209E-01 + 2.940008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.940008E+01 0.000000E+00 5 4.651899E+02 8.993230E+01 5.496780E-01 4.651896E+02 + 2.940008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.940008E+01 3.000000E+01 1 3.926988E+01 8.993230E+01 4.640102E-02 3.926986E+01 + 2.940008E+01 3.000000E+01 2 2.396139E+01 8.992248E+01 3.241828E-02 2.396137E+01 + 2.940008E+01 3.000000E+01 3 1.861911E+02 2.910613E-01 1.861888E+02 9.458427E-01 + 2.940008E+01 3.000000E+01 4 7.807688E+01 8.992197E+01 1.063335E-01 7.807681E+01 + 2.940008E+01 3.000000E+01 5 4.042377E+02 8.993230E+01 4.776469E-01 4.042374E+02 + 2.940008E+01 3.000000E+01 6 6.128293E+01 -8.650887E-04 6.128293E+01 -9.252893E-04 + 2.940008E+01 6.000000E+01 1 2.282981E+01 8.993231E+01 2.697182E-02 2.282980E+01 + 2.940008E+01 6.000000E+01 2 4.181889E+01 8.992248E+01 5.658454E-02 4.181886E+01 + 2.940008E+01 6.000000E+01 3 1.876475E+02 2.920804E-01 1.876450E+02 9.565786E-01 + 2.940008E+01 6.000000E+01 4 1.371663E+02 8.992248E+01 1.855994E-01 1.371662E+02 + 2.940008E+01 6.000000E+01 5 2.349724E+02 8.993230E+01 2.776411E-01 2.349723E+02 + 2.940008E+01 6.000000E+01 6 6.176389E+01 -8.627969E-04 6.176389E+01 -9.300805E-04 + 2.940008E+01 9.000000E+01 1 2.369096E-06 -9.004765E+01 -1.970345E-09 -2.369095E-06 + 2.940008E+01 9.000000E+01 2 4.847226E+01 8.992248E+01 6.559054E-02 4.847221E+01 + 2.940008E+01 9.000000E+01 3 1.883794E+02 2.925909E-01 1.883770E+02 9.619884E-01 + 2.940008E+01 9.000000E+01 4 1.595086E+02 8.992272E+01 2.151389E-01 1.595084E+02 + 2.940008E+01 9.000000E+01 5 1.088531E-04 -8.999049E+01 1.807004E-08 -1.088531E-04 + 2.940008E+01 9.000000E+01 6 5.306068E-06 1.799994E+02 -5.306068E-06 5.388587E-11 + 2.950008E+01 0.000000E+00 1 4.503524E+01 8.993279E+01 5.282796E-02 4.503521E+01 + 2.950008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.950008E+01 0.000000E+00 3 1.856178E+02 2.885004E-01 1.856155E+02 9.346341E-01 + 2.950008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.950008E+01 0.000000E+00 5 4.639080E+02 8.993279E+01 5.441520E-01 4.639077E+02 + 2.950008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.950008E+01 3.000000E+01 1 3.913564E+01 8.993279E+01 4.590441E-02 3.913562E+01 + 2.950008E+01 3.000000E+01 2 2.387957E+01 8.992310E+01 3.205346E-02 2.387955E+01 + 2.950008E+01 3.000000E+01 3 1.863369E+02 2.890021E-01 1.863346E+02 9.398865E-01 + 2.950008E+01 3.000000E+01 4 7.779379E+01 8.992258E+01 1.051103E-01 7.779372E+01 + 2.950008E+01 3.000000E+01 5 4.031126E+02 8.993279E+01 4.728397E-01 4.031123E+02 + 2.950008E+01 3.000000E+01 6 6.084794E+01 -8.518766E-04 6.084794E+01 -9.046903E-04 + 2.950008E+01 6.000000E+01 1 2.275075E+01 8.993281E+01 2.668183E-02 2.275074E+01 + 2.950008E+01 6.000000E+01 2 4.167384E+01 8.992308E+01 5.594446E-02 4.167380E+01 + 2.950008E+01 6.000000E+01 3 1.877826E+02 2.900069E-01 1.877802E+02 9.504718E-01 + 2.950008E+01 6.000000E+01 4 1.366552E+02 8.992308E+01 1.834532E-01 1.366551E+02 + 2.950008E+01 6.000000E+01 5 2.343090E+02 8.993279E+01 2.748291E-01 2.343089E+02 + 2.950008E+01 6.000000E+01 6 6.132202E+01 -8.496349E-04 6.132202E+01 -9.093396E-04 + 2.950008E+01 9.000000E+01 1 2.360742E-06 -9.004739E+01 -1.952473E-09 -2.360742E-06 + 2.950008E+01 9.000000E+01 2 4.830267E+01 8.992308E+01 6.484669E-02 4.830262E+01 + 2.950008E+01 9.000000E+01 3 1.885108E+02 2.905099E-01 1.885083E+02 9.558124E-01 + 2.950008E+01 9.000000E+01 4 1.589058E+02 8.992332E+01 2.126458E-01 1.589057E+02 + 2.950008E+01 9.000000E+01 5 1.084931E-04 -8.999059E+01 1.783283E-08 -1.084931E-04 + 2.950008E+01 9.000000E+01 6 5.267908E-06 1.799994E+02 -5.267908E-06 5.268607E-11 + 2.960008E+01 0.000000E+00 1 4.488310E+01 8.993328E+01 5.226607E-02 4.488307E+01 + 2.960008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.960008E+01 0.000000E+00 3 1.857660E+02 2.864744E-01 1.857637E+02 9.288118E-01 + 2.960008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.960008E+01 0.000000E+00 5 4.626335E+02 8.993329E+01 5.387046E-01 4.626332E+02 + 2.960008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.960008E+01 3.000000E+01 1 3.900241E+01 8.993329E+01 4.541489E-02 3.900238E+01 + 2.960008E+01 3.000000E+01 2 2.379830E+01 8.992370E+01 3.169409E-02 2.379828E+01 + 2.960008E+01 3.000000E+01 3 1.864805E+02 2.869669E-01 1.864781E+02 9.339865E-01 + 2.960008E+01 3.000000E+01 4 7.751311E+01 8.992319E+01 1.039054E-01 7.751304E+01 + 2.960008E+01 3.000000E+01 5 4.019959E+02 8.993329E+01 4.680890E-01 4.019956E+02 + 2.960008E+01 3.000000E+01 6 6.041780E+01 -8.389194E-04 6.041780E+01 -8.846318E-04 + 2.960008E+01 6.000000E+01 1 2.267214E+01 8.993330E+01 2.639602E-02 2.267212E+01 + 2.960008E+01 6.000000E+01 2 4.152969E+01 8.992369E+01 5.531419E-02 4.152965E+01 + 2.960008E+01 6.000000E+01 3 1.879169E+02 2.879573E-01 1.879145E+02 9.444292E-01 + 2.960008E+01 6.000000E+01 4 1.361490E+02 8.992369E+01 1.813403E-01 1.361488E+02 + 2.960008E+01 6.000000E+01 5 2.336446E+02 8.993329E+01 2.720580E-01 2.336444E+02 + 2.960008E+01 6.000000E+01 6 6.088495E+01 -8.367306E-04 6.088495E+01 -8.891458E-04 + 2.960008E+01 9.000000E+01 1 2.352451E-06 -9.004713E+01 -1.934784E-09 -2.352450E-06 + 2.960008E+01 9.000000E+01 2 4.813428E+01 8.992368E+01 6.411441E-02 4.813424E+01 + 2.960008E+01 9.000000E+01 3 1.886402E+02 2.884483E-01 1.886378E+02 9.496808E-01 + 2.960008E+01 9.000000E+01 4 1.583091E+02 8.992393E+01 2.101913E-01 1.583089E+02 + 2.960008E+01 9.000000E+01 5 1.081352E-04 -8.999068E+01 1.759984E-08 -1.081352E-04 + 2.960008E+01 9.000000E+01 6 5.230166E-06 1.799994E+02 -5.230166E-06 5.151773E-11 + 2.970008E+01 0.000000E+00 1 4.473183E+01 8.993376E+01 5.171188E-02 4.473180E+01 + 2.970008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.970008E+01 0.000000E+00 3 1.859136E+02 2.844649E-01 1.859113E+02 9.230294E-01 + 2.970008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.970008E+01 0.000000E+00 5 4.613603E+02 8.993376E+01 5.333279E-01 4.613600E+02 + 2.970008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.970008E+01 3.000000E+01 1 3.887003E+01 8.993377E+01 4.493246E-02 3.887001E+01 + 2.970008E+01 3.000000E+01 2 2.371763E+01 8.992429E+01 3.134031E-02 2.371761E+01 + 2.970008E+01 3.000000E+01 3 1.866223E+02 2.849506E-01 1.866200E+02 9.281297E-01 + 2.970008E+01 3.000000E+01 4 7.723470E+01 8.992380E+01 1.027199E-01 7.723463E+01 + 2.970008E+01 3.000000E+01 5 4.008798E+02 8.993377E+01 4.634041E-01 4.008795E+02 + 2.970008E+01 3.000000E+01 6 5.999210E+01 -8.262128E-04 5.999210E+01 -8.650940E-04 + 2.970008E+01 6.000000E+01 1 2.259411E+01 8.993378E+01 2.611432E-02 2.259409E+01 + 2.970008E+01 6.000000E+01 2 4.138663E+01 8.992429E+01 5.469355E-02 4.138660E+01 + 2.970008E+01 6.000000E+01 3 1.880501E+02 2.859252E-01 1.880478E+02 9.384295E-01 + 2.970008E+01 6.000000E+01 4 1.356459E+02 8.992429E+01 1.792611E-01 1.356457E+02 + 2.970008E+01 6.000000E+01 5 2.329868E+02 8.993377E+01 2.693222E-01 2.329866E+02 + 2.970008E+01 6.000000E+01 6 6.045265E+01 -8.240722E-04 6.045265E+01 -8.694767E-04 + 2.970008E+01 9.000000E+01 1 2.344221E-06 -9.004687E+01 -1.917299E-09 -2.344220E-06 + 2.970008E+01 9.000000E+01 2 4.796714E+01 8.992428E+01 6.339323E-02 4.796710E+01 + 2.970008E+01 9.000000E+01 3 1.887684E+02 2.864132E-01 1.887661E+02 9.436218E-01 + 2.970008E+01 9.000000E+01 4 1.577163E+02 8.992452E+01 2.077747E-01 1.577162E+02 + 2.970008E+01 9.000000E+01 5 1.077796E-04 -8.999077E+01 1.737087E-08 -1.077796E-04 + 2.970008E+01 9.000000E+01 6 5.192836E-06 1.799995E+02 -5.192836E-06 5.037978E-11 + 2.980008E+01 0.000000E+00 1 4.458161E+01 8.993424E+01 5.116573E-02 4.458158E+01 + 2.980008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.980008E+01 0.000000E+00 3 1.860588E+02 2.824788E-01 1.860565E+02 9.173005E-01 + 2.980008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.980008E+01 0.000000E+00 5 4.600951E+02 8.993425E+01 5.280202E-01 4.600948E+02 + 2.980008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.980008E+01 3.000000E+01 1 3.873870E+01 8.993425E+01 4.445663E-02 3.873868E+01 + 2.980008E+01 3.000000E+01 2 2.363745E+01 8.992488E+01 3.099185E-02 2.363742E+01 + 2.980008E+01 3.000000E+01 3 1.867638E+02 2.829582E-01 1.867615E+02 9.223391E-01 + 2.980008E+01 3.000000E+01 4 7.695767E+01 8.992439E+01 1.015526E-01 7.695760E+01 + 2.980008E+01 3.000000E+01 5 3.997693E+02 8.993425E+01 4.587857E-01 3.997691E+02 + 2.980008E+01 3.000000E+01 6 5.957100E+01 -8.137521E-04 5.957100E+01 -8.460662E-04 + 2.980008E+01 6.000000E+01 1 2.251657E+01 8.993426E+01 2.583669E-02 2.251655E+01 + 2.980008E+01 6.000000E+01 2 4.124451E+01 8.992487E+01 5.408248E-02 4.124448E+01 + 2.980008E+01 6.000000E+01 3 1.881823E+02 2.839167E-01 1.881800E+02 9.324922E-01 + 2.980008E+01 6.000000E+01 4 1.351464E+02 8.992487E+01 1.772145E-01 1.351463E+02 + 2.980008E+01 6.000000E+01 5 2.323321E+02 8.993425E+01 2.666237E-01 2.323319E+02 + 2.980008E+01 6.000000E+01 6 6.002500E+01 -8.116572E-04 6.002500E+01 -8.503196E-04 + 2.980008E+01 9.000000E+01 1 2.336046E-06 -9.004660E+01 -1.900011E-09 -2.336046E-06 + 2.980008E+01 9.000000E+01 2 4.780128E+01 8.992487E+01 6.268329E-02 4.780124E+01 + 2.980008E+01 9.000000E+01 3 1.888957E+02 2.843975E-01 1.888934E+02 9.376126E-01 + 2.980008E+01 9.000000E+01 4 1.571293E+02 8.992510E+01 2.053965E-01 1.571291E+02 + 2.980008E+01 9.000000E+01 5 1.074264E-04 -8.999086E+01 1.714589E-08 -1.074264E-04 + 2.980008E+01 9.000000E+01 6 5.155914E-06 1.799995E+02 -5.155914E-06 4.927143E-11 + 2.990008E+01 0.000000E+00 1 4.443261E+01 8.993472E+01 5.062736E-02 4.443258E+01 + 2.990008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.990008E+01 0.000000E+00 3 1.862035E+02 2.805118E-01 1.862012E+02 9.116213E-01 + 2.990008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.990008E+01 0.000000E+00 5 4.588384E+02 8.993472E+01 5.227810E-01 4.588381E+02 + 2.990008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 2.990008E+01 3.000000E+01 1 3.860804E+01 8.993472E+01 4.398783E-02 3.860802E+01 + 2.990008E+01 3.000000E+01 2 2.355785E+01 8.992546E+01 3.064860E-02 2.355783E+01 + 2.990008E+01 3.000000E+01 3 1.869043E+02 2.809834E-01 1.869021E+02 9.165912E-01 + 2.990008E+01 3.000000E+01 4 7.668298E+01 8.992498E+01 1.004033E-01 7.668291E+01 + 2.990008E+01 3.000000E+01 5 3.986673E+02 8.993472E+01 4.542212E-01 3.986671E+02 + 2.990008E+01 3.000000E+01 6 5.915438E+01 -8.015265E-04 5.915438E+01 -8.275269E-04 + 2.990008E+01 6.000000E+01 1 2.243959E+01 8.993473E+01 2.556304E-02 2.243958E+01 + 2.990008E+01 6.000000E+01 2 4.110343E+01 8.992545E+01 5.348057E-02 4.110339E+01 + 2.990008E+01 6.000000E+01 3 1.883131E+02 2.819290E-01 1.883108E+02 9.266077E-01 + 2.990008E+01 6.000000E+01 4 1.346508E+02 8.992545E+01 1.751986E-01 1.346507E+02 + 2.990008E+01 6.000000E+01 5 2.316790E+02 8.993472E+01 2.639591E-01 2.316788E+02 + 2.990008E+01 6.000000E+01 6 5.960191E+01 -7.994796E-04 5.960191E+01 -8.316583E-04 + 2.990008E+01 9.000000E+01 1 2.327931E-06 -9.004635E+01 -1.882912E-09 -2.327931E-06 + 2.990008E+01 9.000000E+01 2 4.763644E+01 8.992545E+01 6.198391E-02 4.763639E+01 + 2.990008E+01 9.000000E+01 3 1.890210E+02 2.824030E-01 1.890187E+02 9.316548E-01 + 2.990008E+01 9.000000E+01 4 1.565448E+02 8.992568E+01 2.030558E-01 1.565446E+02 + 2.990008E+01 9.000000E+01 5 1.070752E-04 -8.999094E+01 1.692479E-08 -1.070752E-04 + 2.990008E+01 9.000000E+01 6 5.119384E-06 1.799995E+02 -5.119384E-06 4.819163E-11 + 3.000008E+01 0.000000E+00 1 4.428444E+01 8.993519E+01 5.009654E-02 4.428441E+01 + 3.000008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.000008E+01 0.000000E+00 3 1.863466E+02 2.785688E-01 1.863445E+02 9.060031E-01 + 3.000008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.000008E+01 0.000000E+00 5 4.575834E+02 8.993519E+01 5.176095E-01 4.575831E+02 + 3.000008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.000008E+01 3.000000E+01 1 3.847847E+01 8.993519E+01 4.352576E-02 3.847845E+01 + 3.000008E+01 3.000000E+01 2 2.347882E+01 8.992603E+01 3.031052E-02 2.347880E+01 + 3.000008E+01 3.000000E+01 3 1.870421E+02 2.790350E-01 1.870399E+02 9.109065E-01 + 3.000008E+01 3.000000E+01 4 7.640999E+01 8.992556E+01 9.927158E-02 7.640993E+01 + 3.000008E+01 3.000000E+01 5 3.975689E+02 8.993519E+01 4.497190E-01 3.975686E+02 + 3.000008E+01 3.000000E+01 6 5.874228E+01 -7.895360E-04 5.874228E+01 -8.094688E-04 + 3.000008E+01 6.000000E+01 1 2.236315E+01 8.993520E+01 2.529320E-02 2.236314E+01 + 3.000008E+01 6.000000E+01 2 4.096333E+01 8.992603E+01 5.288776E-02 4.096329E+01 + 3.000008E+01 6.000000E+01 3 1.884412E+02 2.799668E-01 1.884389E+02 9.207846E-01 + 3.000008E+01 6.000000E+01 4 1.341592E+02 8.992603E+01 1.732149E-01 1.341591E+02 + 3.000008E+01 6.000000E+01 5 2.310289E+02 8.993519E+01 2.613340E-01 2.310288E+02 + 3.000008E+01 6.000000E+01 6 5.918349E+01 -7.875339E-04 5.918349E+01 -8.134806E-04 + 3.000008E+01 9.000000E+01 1 2.319874E-06 -9.004609E+01 -1.866006E-09 -2.319874E-06 + 3.000008E+01 9.000000E+01 2 4.747283E+01 8.992603E+01 6.129526E-02 4.747279E+01 + 3.000008E+01 9.000000E+01 3 1.891457E+02 2.804316E-01 1.891434E+02 9.257614E-01 + 3.000008E+01 9.000000E+01 4 1.559664E+02 8.992625E+01 2.007503E-01 1.559662E+02 + 3.000008E+01 9.000000E+01 5 1.067263E-04 -8.999103E+01 1.670759E-08 -1.067263E-04 + 3.000008E+01 9.000000E+01 6 5.083257E-06 1.799995E+02 -5.083257E-06 4.713976E-11 + 3.010008E+01 0.000000E+00 1 4.413715E+01 8.993565E+01 4.957308E-02 4.413712E+01 + 3.010008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.010008E+01 0.000000E+00 3 1.864881E+02 2.766453E-01 1.864859E+02 9.004302E-01 + 3.010008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.010008E+01 0.000000E+00 5 4.563321E+02 8.993565E+01 5.125093E-01 4.563318E+02 + 3.010008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.010008E+01 3.000000E+01 1 3.834960E+01 8.993565E+01 4.307000E-02 3.834958E+01 + 3.010008E+01 3.000000E+01 2 2.340023E+01 8.992660E+01 2.997750E-02 2.340022E+01 + 3.010008E+01 3.000000E+01 3 1.871787E+02 2.771035E-01 1.871766E+02 9.052616E-01 + 3.010008E+01 3.000000E+01 4 7.613928E+01 8.992613E+01 9.815692E-02 7.613922E+01 + 3.010008E+01 3.000000E+01 5 3.964720E+02 8.993565E+01 4.452759E-01 3.964718E+02 + 3.010008E+01 3.000000E+01 6 5.833445E+01 -7.777730E-04 5.833445E+01 -7.918726E-04 + 3.010008E+01 6.000000E+01 1 2.228726E+01 8.993566E+01 2.502731E-02 2.228725E+01 + 3.010008E+01 6.000000E+01 2 4.082419E+01 8.992659E+01 5.230393E-02 4.082416E+01 + 3.010008E+01 6.000000E+01 3 1.885693E+02 2.780216E-01 1.885671E+02 9.150085E-01 + 3.010008E+01 6.000000E+01 4 1.336717E+02 8.992659E+01 1.712611E-01 1.336716E+02 + 3.010008E+01 6.000000E+01 5 2.303822E+02 8.993565E+01 2.587382E-01 2.303821E+02 + 3.010008E+01 6.000000E+01 6 5.876945E+01 -7.758149E-04 5.876945E+01 -7.957692E-04 + 3.010008E+01 9.000000E+01 1 2.311875E-06 -9.004584E+01 -1.849279E-09 -2.311875E-06 + 3.010008E+01 9.000000E+01 2 4.731023E+01 8.992659E+01 6.061680E-02 4.731019E+01 + 3.010008E+01 9.000000E+01 3 1.892687E+02 2.784809E-01 1.892664E+02 9.199195E-01 + 3.010008E+01 9.000000E+01 4 1.553916E+02 8.992682E+01 1.984811E-01 1.553914E+02 + 3.010008E+01 9.000000E+01 5 1.063797E-04 -8.999112E+01 1.649406E-08 -1.063797E-04 + 3.010008E+01 9.000000E+01 6 5.047520E-06 1.799995E+02 -5.047520E-06 4.611490E-11 + 3.020008E+01 0.000000E+00 1 4.399104E+01 8.993610E+01 4.905705E-02 4.399102E+01 + 3.020008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.020008E+01 0.000000E+00 3 1.866277E+02 2.747404E-01 1.866255E+02 8.948994E-01 + 3.020008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.020008E+01 0.000000E+00 5 4.550890E+02 8.993610E+01 5.074785E-01 4.550887E+02 + 3.020008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.020008E+01 3.000000E+01 1 3.822173E+01 8.993611E+01 4.262054E-02 3.822170E+01 + 3.020008E+01 3.000000E+01 2 2.332226E+01 8.992716E+01 2.964941E-02 2.332224E+01 + 3.020008E+01 3.000000E+01 3 1.873143E+02 2.751917E-01 1.873121E+02 8.996674E-01 + 3.020008E+01 3.000000E+01 4 7.587064E+01 8.992670E+01 9.705951E-02 7.587057E+01 + 3.020008E+01 3.000000E+01 5 3.953836E+02 8.993610E+01 4.408927E-01 3.953834E+02 + 3.020008E+01 3.000000E+01 6 5.793094E+01 -7.662302E-04 5.793094E+01 -7.747244E-04 + 3.020008E+01 6.000000E+01 1 2.221184E+01 8.993612E+01 2.476502E-02 2.221183E+01 + 3.020008E+01 6.000000E+01 2 4.068599E+01 8.992715E+01 5.172871E-02 4.068595E+01 + 3.020008E+01 6.000000E+01 3 1.886955E+02 2.760973E-01 1.886933E+02 9.092838E-01 + 3.020008E+01 6.000000E+01 4 1.331873E+02 8.992715E+01 1.693382E-01 1.331871E+02 + 3.020008E+01 6.000000E+01 5 2.297372E+02 8.993611E+01 2.561796E-01 2.297370E+02 + 3.020008E+01 6.000000E+01 6 5.835978E+01 -7.643160E-04 5.835978E+01 -7.785096E-04 + 3.020008E+01 9.000000E+01 1 2.303925E-06 -9.004558E+01 -1.832743E-09 -2.303924E-06 + 3.020008E+01 9.000000E+01 2 4.714886E+01 8.992715E+01 5.994865E-02 4.714883E+01 + 3.020008E+01 9.000000E+01 3 1.893911E+02 2.765493E-01 1.893889E+02 9.141296E-01 + 3.020008E+01 9.000000E+01 4 1.548217E+02 8.992738E+01 1.962462E-01 1.548215E+02 + 3.020008E+01 9.000000E+01 5 1.060351E-04 -8.999120E+01 1.628421E-08 -1.060351E-04 + 3.020008E+01 9.000000E+01 6 5.012160E-06 1.799995E+02 -5.012160E-06 4.511613E-11 + 3.030008E+01 0.000000E+00 1 4.384571E+01 8.993656E+01 4.854807E-02 4.384568E+01 + 3.030008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.030008E+01 0.000000E+00 3 1.867672E+02 2.728531E-01 1.867651E+02 8.894166E-01 + 3.030008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.030008E+01 0.000000E+00 5 4.538535E+02 8.993656E+01 5.025070E-01 4.538533E+02 + 3.030008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.030008E+01 3.000000E+01 1 3.809455E+01 8.993656E+01 4.217757E-02 3.809453E+01 + 3.030008E+01 3.000000E+01 2 2.324474E+01 8.992771E+01 2.932620E-02 2.324472E+01 + 3.030008E+01 3.000000E+01 3 1.874488E+02 2.733010E-01 1.874466E+02 8.941275E-01 + 3.030008E+01 3.000000E+01 4 7.560383E+01 8.992726E+01 9.597894E-02 7.560377E+01 + 3.030008E+01 3.000000E+01 5 3.942994E+02 8.993656E+01 4.365642E-01 3.942992E+02 + 3.030008E+01 3.000000E+01 6 5.753164E+01 -7.549060E-04 5.753164E+01 -7.580137E-04 + 3.030008E+01 6.000000E+01 1 2.213692E+01 8.993657E+01 2.450664E-02 2.213691E+01 + 3.030008E+01 6.000000E+01 2 4.054869E+01 8.992770E+01 5.116217E-02 4.054866E+01 + 3.030008E+01 6.000000E+01 3 1.888214E+02 2.741920E-01 1.888193E+02 9.036114E-01 + 3.030008E+01 6.000000E+01 4 1.327063E+02 8.992770E+01 1.674437E-01 1.327062E+02 + 3.030008E+01 6.000000E+01 5 2.290964E+02 8.993656E+01 2.536536E-01 2.290963E+02 + 3.030008E+01 6.000000E+01 6 5.795443E+01 -7.530344E-04 5.795443E+01 -7.616910E-04 + 3.030008E+01 9.000000E+01 1 2.296035E-06 -9.004533E+01 -1.816389E-09 -2.296034E-06 + 3.030008E+01 9.000000E+01 2 4.698862E+01 8.992770E+01 5.929046E-02 4.698859E+01 + 3.030008E+01 9.000000E+01 3 1.895123E+02 2.746371E-01 1.895101E+02 9.083899E-01 + 3.030008E+01 9.000000E+01 4 1.542555E+02 8.992793E+01 1.940461E-01 1.542554E+02 + 3.030008E+01 9.000000E+01 5 1.056931E-04 -8.999129E+01 1.607786E-08 -1.056931E-04 + 3.030008E+01 9.000000E+01 6 4.977173E-06 1.799995E+02 -4.977173E-06 4.414284E-11 + 3.040008E+01 0.000000E+00 1 4.370139E+01 8.993701E+01 4.804649E-02 4.370137E+01 + 3.040008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.040008E+01 0.000000E+00 3 1.869051E+02 2.709897E-01 1.869030E+02 8.839947E-01 + 3.040008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.040008E+01 0.000000E+00 5 4.526188E+02 8.993701E+01 4.975999E-01 4.526185E+02 + 3.040008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.040008E+01 3.000000E+01 1 3.796838E+01 8.993702E+01 4.174079E-02 3.796835E+01 + 3.040008E+01 3.000000E+01 2 2.316777E+01 8.992826E+01 2.900782E-02 2.316776E+01 + 3.040008E+01 3.000000E+01 3 1.875829E+02 2.714281E-01 1.875808E+02 8.886361E-01 + 3.040008E+01 3.000000E+01 4 7.533876E+01 8.992782E+01 9.491497E-02 7.533870E+01 + 3.040008E+01 3.000000E+01 5 3.932216E+02 8.993701E+01 4.322958E-01 3.932214E+02 + 3.040008E+01 3.000000E+01 6 5.713646E+01 -7.437957E-04 5.713646E+01 -7.417274E-04 + 3.040008E+01 6.000000E+01 1 2.206254E+01 8.993702E+01 2.425172E-02 2.206253E+01 + 3.040008E+01 6.000000E+01 2 4.041239E+01 8.992825E+01 5.060411E-02 4.041236E+01 + 3.040008E+01 6.000000E+01 3 1.889464E+02 2.723086E-01 1.889442E+02 8.979985E-01 + 3.040008E+01 6.000000E+01 4 1.322292E+02 8.992825E+01 1.655786E-01 1.322291E+02 + 3.040008E+01 6.000000E+01 5 2.284614E+02 8.993702E+01 2.511606E-01 2.284613E+02 + 3.040008E+01 6.000000E+01 6 5.755345E+01 -7.419637E-04 5.755345E+01 -7.453004E-04 + 3.040008E+01 9.000000E+01 1 2.288200E-06 -9.004507E+01 -1.800219E-09 -2.288199E-06 + 3.040008E+01 9.000000E+01 2 4.682941E+01 8.992825E+01 5.864220E-02 4.682937E+01 + 3.040008E+01 9.000000E+01 3 1.896316E+02 2.727475E-01 1.896294E+02 9.027076E-01 + 3.040008E+01 9.000000E+01 4 1.536942E+02 8.992847E+01 1.918793E-01 1.536940E+02 + 3.040008E+01 9.000000E+01 5 1.053537E-04 -8.999137E+01 1.587513E-08 -1.053537E-04 + 3.040008E+01 9.000000E+01 6 4.942566E-06 1.799995E+02 -4.942566E-06 4.319428E-11 + 3.050008E+01 0.000000E+00 1 4.355813E+01 8.993745E+01 4.755162E-02 4.355810E+01 + 3.050008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.050008E+01 0.000000E+00 3 1.870413E+02 2.691429E-01 1.870393E+02 8.786101E-01 + 3.050008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.050008E+01 0.000000E+00 5 4.513942E+02 8.993745E+01 4.927564E-01 4.513939E+02 + 3.050008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.050008E+01 3.000000E+01 1 3.784296E+01 8.993745E+01 4.131014E-02 3.784294E+01 + 3.050008E+01 3.000000E+01 2 2.309130E+01 8.992880E+01 2.869410E-02 2.309128E+01 + 3.050008E+01 3.000000E+01 3 1.877141E+02 2.695771E-01 1.877121E+02 8.831933E-01 + 3.050008E+01 3.000000E+01 4 7.507595E+01 8.992836E+01 9.386633E-02 7.507589E+01 + 3.050008E+01 3.000000E+01 5 3.921465E+02 8.993745E+01 4.280784E-01 3.921463E+02 + 3.050008E+01 3.000000E+01 6 5.674545E+01 -7.328924E-04 5.674545E+01 -7.258530E-04 + 3.050008E+01 6.000000E+01 1 2.198871E+01 8.993747E+01 2.400045E-02 2.198870E+01 + 3.050008E+01 6.000000E+01 2 4.027695E+01 8.992880E+01 5.005425E-02 4.027692E+01 + 3.050008E+01 6.000000E+01 3 1.890693E+02 2.704426E-01 1.890672E+02 8.924252E-01 + 3.050008E+01 6.000000E+01 4 1.317560E+02 8.992880E+01 1.637411E-01 1.317559E+02 + 3.050008E+01 6.000000E+01 5 2.278264E+02 8.993745E+01 2.487008E-01 2.278262E+02 + 3.050008E+01 6.000000E+01 6 5.715665E+01 -7.310992E-04 5.715665E+01 -7.293238E-04 + 3.050008E+01 9.000000E+01 1 2.280426E-06 -9.004483E+01 -1.784220E-09 -2.280425E-06 + 3.050008E+01 9.000000E+01 2 4.667132E+01 8.992879E+01 5.800344E-02 4.667128E+01 + 3.050008E+01 9.000000E+01 3 1.897509E+02 2.708740E-01 1.897488E+02 8.970714E-01 + 3.050008E+01 9.000000E+01 4 1.531367E+02 8.992901E+01 1.897454E-01 1.531366E+02 + 3.050008E+01 9.000000E+01 5 1.050156E-04 -8.999145E+01 1.567574E-08 -1.050156E-04 + 3.050008E+01 9.000000E+01 6 4.908320E-06 1.799995E+02 -4.908320E-06 4.226957E-11 + 3.060008E+01 0.000000E+00 1 4.341547E+01 8.993789E+01 4.706380E-02 4.341545E+01 + 3.060008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.060008E+01 0.000000E+00 3 1.871758E+02 2.673157E-01 1.871738E+02 8.732731E-01 + 3.060008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.060008E+01 0.000000E+00 5 4.501742E+02 8.993790E+01 4.879782E-01 4.501739E+02 + 3.060008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.060008E+01 3.000000E+01 1 3.771829E+01 8.993790E+01 4.088533E-02 3.771827E+01 + 3.060008E+01 3.000000E+01 2 2.301533E+01 8.992934E+01 2.838496E-02 2.301531E+01 + 3.060008E+01 3.000000E+01 3 1.878450E+02 2.677438E-01 1.878429E+02 8.777985E-01 + 3.060008E+01 3.000000E+01 4 7.481495E+01 8.992891E+01 9.283397E-02 7.481489E+01 + 3.060008E+01 3.000000E+01 5 3.910774E+02 8.993790E+01 4.239163E-01 3.910772E+02 + 3.060008E+01 3.000000E+01 6 5.635844E+01 -7.221899E-04 5.635844E+01 -7.103751E-04 + 3.060008E+01 6.000000E+01 1 2.191535E+01 8.993790E+01 2.375261E-02 2.191534E+01 + 3.060008E+01 6.000000E+01 2 4.014241E+01 8.992933E+01 4.951235E-02 4.014238E+01 + 3.060008E+01 6.000000E+01 3 1.891911E+02 2.685968E-01 1.891890E+02 8.869054E-01 + 3.060008E+01 6.000000E+01 4 1.312857E+02 8.992933E+01 1.619315E-01 1.312856E+02 + 3.060008E+01 6.000000E+01 5 2.271952E+02 8.993790E+01 2.462717E-01 2.271951E+02 + 3.060008E+01 6.000000E+01 6 5.676398E+01 -7.204352E-04 5.676398E+01 -7.137483E-04 + 3.060008E+01 9.000000E+01 1 2.272691E-06 -9.004459E+01 -1.768402E-09 -2.272690E-06 + 3.060008E+01 9.000000E+01 2 4.651435E+01 8.992933E+01 5.737413E-02 4.651432E+01 + 3.060008E+01 9.000000E+01 3 1.898685E+02 2.690236E-01 1.898664E+02 8.914955E-01 + 3.060008E+01 9.000000E+01 4 1.525838E+02 8.992954E+01 1.876438E-01 1.525837E+02 + 3.060008E+01 9.000000E+01 5 1.046796E-04 -8.999152E+01 1.547975E-08 -1.046796E-04 + 3.060008E+01 9.000000E+01 6 4.874436E-06 1.799995E+02 -4.874436E-06 4.136818E-11 + 3.070008E+01 0.000000E+00 1 4.327412E+01 8.993832E+01 4.658252E-02 4.327409E+01 + 3.070008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.070008E+01 0.000000E+00 3 1.873088E+02 2.655096E-01 1.873068E+02 8.679889E-01 + 3.070008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.070008E+01 0.000000E+00 5 4.489539E+02 8.993832E+01 4.832589E-01 4.489536E+02 + 3.070008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.070008E+01 3.000000E+01 1 3.759457E+01 8.993832E+01 4.046637E-02 3.759455E+01 + 3.070008E+01 3.000000E+01 2 2.293990E+01 8.992986E+01 2.808030E-02 2.293988E+01 + 3.070008E+01 3.000000E+01 3 1.879740E+02 2.659305E-01 1.879720E+02 8.724524E-01 + 3.070008E+01 3.000000E+01 4 7.455549E+01 8.992944E+01 9.181644E-02 7.455544E+01 + 3.070008E+01 3.000000E+01 5 3.900139E+02 8.993832E+01 4.198111E-01 3.900136E+02 + 3.070008E+01 3.000000E+01 6 5.597549E+01 -7.116874E-04 5.597549E+01 -6.952877E-04 + 3.070008E+01 6.000000E+01 1 2.184251E+01 8.993833E+01 2.350826E-02 2.184250E+01 + 3.070008E+01 6.000000E+01 2 4.000882E+01 8.992986E+01 4.897862E-02 4.000879E+01 + 3.070008E+01 6.000000E+01 3 1.893117E+02 2.667704E-01 1.893097E+02 8.814362E-01 + 3.070008E+01 6.000000E+01 4 1.308191E+02 8.992986E+01 1.601499E-01 1.308190E+02 + 3.070008E+01 6.000000E+01 5 2.265663E+02 8.993832E+01 2.438751E-01 2.265661E+02 + 3.070008E+01 6.000000E+01 6 5.637542E+01 -7.099709E-04 5.637542E+01 -6.985664E-04 + 3.070008E+01 9.000000E+01 1 2.265018E-06 -9.004434E+01 -1.752754E-09 -2.265018E-06 + 3.070008E+01 9.000000E+01 2 4.635834E+01 8.992986E+01 5.675413E-02 4.635830E+01 + 3.070008E+01 9.000000E+01 3 1.899848E+02 2.671911E-01 1.899827E+02 8.859651E-01 + 3.070008E+01 9.000000E+01 4 1.520348E+02 8.993006E+01 1.855742E-01 1.520347E+02 + 3.070008E+01 9.000000E+01 5 1.043465E-04 -8.999161E+01 1.528707E-08 -1.043465E-04 + 3.070008E+01 9.000000E+01 6 4.840912E-06 1.799995E+02 -4.840912E-06 4.048949E-11 + 3.080008E+01 0.000000E+00 1 4.313348E+01 8.993876E+01 4.610780E-02 4.313346E+01 + 3.080008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.080008E+01 0.000000E+00 3 1.874410E+02 2.637186E-01 1.874390E+02 8.627427E-01 + 3.080008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.080008E+01 0.000000E+00 5 4.477463E+02 8.993876E+01 4.785979E-01 4.477460E+02 + 3.080008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.080008E+01 3.000000E+01 1 3.747162E+01 8.993876E+01 4.005323E-02 3.747160E+01 + 3.080008E+01 3.000000E+01 2 2.286489E+01 8.993039E+01 2.778010E-02 2.286487E+01 + 3.080008E+01 3.000000E+01 3 1.881021E+02 2.641324E-01 1.881001E+02 8.671439E-01 + 3.080008E+01 3.000000E+01 4 7.429823E+01 8.992997E+01 9.081502E-02 7.429818E+01 + 3.080008E+01 3.000000E+01 5 3.889516E+02 8.993876E+01 4.157513E-01 3.889514E+02 + 3.080008E+01 3.000000E+01 6 5.559647E+01 -7.013758E-04 5.559647E+01 -6.805740E-04 + 3.080008E+01 6.000000E+01 1 2.177006E+01 8.993877E+01 2.326731E-02 2.177005E+01 + 3.080008E+01 6.000000E+01 2 3.987618E+01 8.993038E+01 4.845255E-02 3.987615E+01 + 3.080008E+01 6.000000E+01 3 1.894314E+02 2.649621E-01 1.894293E+02 8.760148E-01 + 3.080008E+01 6.000000E+01 4 1.303561E+02 8.993038E+01 1.583941E-01 1.303560E+02 + 3.080008E+01 6.000000E+01 5 2.259407E+02 8.993876E+01 2.415084E-01 2.259406E+02 + 3.080008E+01 6.000000E+01 6 5.599092E+01 -6.996971E-04 5.599092E+01 -6.837621E-04 + 3.080008E+01 9.000000E+01 1 2.257399E-06 -9.004409E+01 -1.737281E-09 -2.257398E-06 + 3.080008E+01 9.000000E+01 2 4.620346E+01 8.993037E+01 5.614324E-02 4.620343E+01 + 3.080008E+01 9.000000E+01 3 1.901001E+02 2.653768E-01 1.900981E+02 8.804832E-01 + 3.080008E+01 9.000000E+01 4 1.514902E+02 8.993059E+01 1.835350E-01 1.514901E+02 + 3.080008E+01 9.000000E+01 5 1.040144E-04 -8.999168E+01 1.509754E-08 -1.040144E-04 + 3.080008E+01 9.000000E+01 6 4.807736E-06 1.799995E+02 -4.807736E-06 3.963256E-11 + 3.090008E+01 0.000000E+00 1 4.299379E+01 8.993918E+01 4.563982E-02 4.299377E+01 + 3.090008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.090008E+01 0.000000E+00 3 1.875726E+02 2.619484E-01 1.875706E+02 8.575530E-01 + 3.090008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.090008E+01 0.000000E+00 5 4.465399E+02 8.993918E+01 4.739981E-01 4.465397E+02 + 3.090008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.090008E+01 3.000000E+01 1 3.734951E+01 8.993918E+01 3.964584E-02 3.734948E+01 + 3.090008E+01 3.000000E+01 2 2.279037E+01 8.993090E+01 2.748421E-02 2.279035E+01 + 3.090008E+01 3.000000E+01 3 1.882289E+02 2.623577E-01 1.882269E+02 8.618982E-01 + 3.090008E+01 3.000000E+01 4 7.404259E+01 8.993050E+01 8.982762E-02 7.404254E+01 + 3.090008E+01 3.000000E+01 5 3.878961E+02 8.993918E+01 4.117511E-01 3.878959E+02 + 3.090008E+01 3.000000E+01 6 5.522128E+01 -6.912568E-04 5.522128E+01 -6.662285E-04 + 3.090008E+01 6.000000E+01 1 2.169816E+01 8.993919E+01 2.302962E-02 2.169815E+01 + 3.090008E+01 6.000000E+01 2 3.974430E+01 8.993089E+01 4.793413E-02 3.974427E+01 + 3.090008E+01 6.000000E+01 3 1.895503E+02 2.631741E-01 1.895483E+02 8.706501E-01 + 3.090008E+01 6.000000E+01 4 1.298961E+02 8.993089E+01 1.566642E-01 1.298960E+02 + 3.090008E+01 6.000000E+01 5 2.253170E+02 8.993918E+01 2.391713E-01 2.253169E+02 + 3.090008E+01 6.000000E+01 6 5.561031E+01 -6.896126E-04 5.561031E+01 -6.693262E-04 + 3.090008E+01 9.000000E+01 1 2.249829E-06 -9.004385E+01 -1.721973E-09 -2.249828E-06 + 3.090008E+01 9.000000E+01 2 4.604965E+01 8.993089E+01 5.554111E-02 4.604961E+01 + 3.090008E+01 9.000000E+01 3 1.902134E+02 2.635837E-01 1.902114E+02 8.750553E-01 + 3.090008E+01 9.000000E+01 4 1.509488E+02 8.993110E+01 1.815263E-01 1.509487E+02 + 3.090008E+01 9.000000E+01 5 1.036849E-04 -8.999176E+01 1.491125E-08 -1.036849E-04 + 3.090008E+01 9.000000E+01 6 4.774903E-06 1.799995E+02 -4.774903E-06 3.879698E-11 + 3.100008E+01 0.000000E+00 1 4.285502E+01 8.993960E+01 4.517803E-02 4.285500E+01 + 3.100008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.100008E+01 0.000000E+00 3 1.877029E+02 2.601949E-01 1.877009E+02 8.524042E-01 + 3.100008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.100008E+01 0.000000E+00 5 4.453406E+02 8.993961E+01 4.694585E-01 4.453404E+02 + 3.100008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.100008E+01 3.000000E+01 1 3.722807E+01 8.993961E+01 3.924388E-02 3.722805E+01 + 3.100008E+01 3.000000E+01 2 2.271643E+01 8.993141E+01 2.719263E-02 2.271642E+01 + 3.100008E+01 3.000000E+01 3 1.883554E+02 2.605982E-01 1.883535E+02 8.566936E-01 + 3.100008E+01 3.000000E+01 4 7.378862E+01 8.993101E+01 8.885553E-02 7.378857E+01 + 3.100008E+01 3.000000E+01 5 3.868489E+02 8.993961E+01 4.077967E-01 3.868487E+02 + 3.100008E+01 3.000000E+01 6 5.485001E+01 -6.813236E-04 5.485001E+01 -6.522401E-04 + 3.100008E+01 6.000000E+01 1 2.162674E+01 8.993961E+01 2.279516E-02 2.162673E+01 + 3.100008E+01 6.000000E+01 2 3.961340E+01 8.993141E+01 4.742325E-02 3.961337E+01 + 3.100008E+01 6.000000E+01 3 1.896681E+02 2.614026E-01 1.896662E+02 8.653268E-01 + 3.100008E+01 6.000000E+01 4 1.294397E+02 8.993141E+01 1.549607E-01 1.294396E+02 + 3.100008E+01 6.000000E+01 5 2.246980E+02 8.993961E+01 2.368684E-01 2.246979E+02 + 3.100008E+01 6.000000E+01 6 5.523374E+01 -6.797137E-04 5.523374E+01 -6.552512E-04 + 3.100008E+01 9.000000E+01 1 2.242310E-06 -9.004362E+01 -1.706840E-09 -2.242310E-06 + 3.100008E+01 9.000000E+01 2 4.589690E+01 8.993141E+01 5.494807E-02 4.589687E+01 + 3.100008E+01 9.000000E+01 3 1.903277E+02 2.618063E-01 1.903257E+02 8.696770E-01 + 3.100008E+01 9.000000E+01 4 1.504123E+02 8.993160E+01 1.795485E-01 1.504122E+02 + 3.100008E+01 9.000000E+01 5 1.033579E-04 -8.999184E+01 1.472793E-08 -1.033579E-04 + 3.100008E+01 9.000000E+01 6 4.742417E-06 1.799995E+02 -4.742417E-06 3.798223E-11 + 3.110008E+01 0.000000E+00 1 4.271725E+01 8.994002E+01 4.472252E-02 4.271722E+01 + 3.110008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.110008E+01 0.000000E+00 3 1.878313E+02 2.584578E-01 1.878293E+02 8.472925E-01 + 3.110008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.110008E+01 0.000000E+00 5 4.441506E+02 8.994002E+01 4.649782E-01 4.441503E+02 + 3.110008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.110008E+01 3.000000E+01 1 3.710766E+01 8.994002E+01 3.884733E-02 3.710764E+01 + 3.110008E+01 3.000000E+01 2 2.264285E+01 8.993192E+01 2.690524E-02 2.264283E+01 + 3.110008E+01 3.000000E+01 3 1.884795E+02 2.588557E-01 1.884776E+02 8.515257E-01 + 3.110008E+01 3.000000E+01 4 7.353658E+01 8.993152E+01 8.789667E-02 7.353653E+01 + 3.110008E+01 3.000000E+01 5 3.858040E+02 8.994002E+01 4.038925E-01 3.858038E+02 + 3.110008E+01 3.000000E+01 6 5.448254E+01 -6.715673E-04 5.448254E+01 -6.385931E-04 + 3.110008E+01 6.000000E+01 1 2.155575E+01 8.994003E+01 2.256396E-02 2.155574E+01 + 3.110008E+01 6.000000E+01 2 3.948326E+01 8.993192E+01 4.691983E-02 3.948323E+01 + 3.110008E+01 6.000000E+01 3 1.897842E+02 2.596489E-01 1.897823E+02 8.600475E-01 + 3.110008E+01 6.000000E+01 4 1.289867E+02 8.993192E+01 1.532820E-01 1.289866E+02 + 3.110008E+01 6.000000E+01 5 2.240822E+02 8.994002E+01 2.345902E-01 2.240821E+02 + 3.110008E+01 6.000000E+01 6 5.486097E+01 -6.699933E-04 5.486097E+01 -6.415217E-04 + 3.110008E+01 9.000000E+01 1 2.234839E-06 -9.004337E+01 -1.691864E-09 -2.234839E-06 + 3.110008E+01 9.000000E+01 2 4.574520E+01 8.993192E+01 5.436330E-02 4.574517E+01 + 3.110008E+01 9.000000E+01 3 1.904401E+02 2.600465E-01 1.904381E+02 8.643413E-01 + 3.110008E+01 9.000000E+01 4 1.498793E+02 8.993211E+01 1.775985E-01 1.498792E+02 + 3.110008E+01 9.000000E+01 5 1.030330E-04 -8.999191E+01 1.454769E-08 -1.030330E-04 + 3.110008E+01 9.000000E+01 6 4.710264E-06 1.799996E+02 -4.710264E-06 3.718752E-11 + 3.120008E+01 0.000000E+00 1 4.258026E+01 8.994042E+01 4.427331E-02 4.258024E+01 + 3.120008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.120008E+01 0.000000E+00 3 1.879590E+02 2.567396E-01 1.879572E+02 8.422326E-01 + 3.120008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.120008E+01 0.000000E+00 5 4.429591E+02 8.994043E+01 4.605506E-01 4.429588E+02 + 3.120008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.120008E+01 3.000000E+01 1 3.698774E+01 8.994043E+01 3.845636E-02 3.698772E+01 + 3.120008E+01 3.000000E+01 2 2.256986E+01 8.993242E+01 2.662198E-02 2.256985E+01 + 3.120008E+01 3.000000E+01 3 1.886033E+02 2.571312E-01 1.886014E+02 8.464085E-01 + 3.120008E+01 3.000000E+01 4 7.328609E+01 8.993202E+01 8.695251E-02 7.328603E+01 + 3.120008E+01 3.000000E+01 5 3.847628E+02 8.994043E+01 4.000409E-01 3.847626E+02 + 3.120008E+01 3.000000E+01 6 5.411873E+01 -6.619911E-04 5.411873E+01 -6.252836E-04 + 3.120008E+01 6.000000E+01 1 2.148526E+01 8.994044E+01 2.233585E-02 2.148524E+01 + 3.120008E+01 6.000000E+01 2 3.935412E+01 8.993241E+01 4.642364E-02 3.935410E+01 + 3.120008E+01 6.000000E+01 3 1.898994E+02 2.579163E-01 1.898975E+02 8.548273E-01 + 3.120008E+01 6.000000E+01 4 1.285365E+02 8.993241E+01 1.516277E-01 1.285364E+02 + 3.120008E+01 6.000000E+01 5 2.234675E+02 8.994043E+01 2.323439E-01 2.234673E+02 + 3.120008E+01 6.000000E+01 6 5.449213E+01 -6.604489E-04 5.449213E+01 -6.281313E-04 + 3.120008E+01 9.000000E+01 1 2.227424E-06 -9.004314E+01 -1.677062E-09 -2.227424E-06 + 3.120008E+01 9.000000E+01 2 4.559439E+01 8.993241E+01 5.378699E-02 4.559436E+01 + 3.120008E+01 9.000000E+01 3 1.905505E+02 2.583078E-01 1.905486E+02 8.590598E-01 + 3.120008E+01 9.000000E+01 4 1.493502E+02 8.993260E+01 1.756782E-01 1.493501E+02 + 3.120008E+01 9.000000E+01 5 1.027095E-04 -8.999198E+01 1.437044E-08 -1.027095E-04 + 3.120008E+01 9.000000E+01 6 4.678442E-06 1.799996E+02 -4.678442E-06 3.641232E-11 + 3.130008E+01 0.000000E+00 1 4.244415E+01 8.994083E+01 4.383010E-02 4.244413E+01 + 3.130008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.130008E+01 0.000000E+00 3 1.880849E+02 2.550395E-01 1.880830E+02 8.372157E-01 + 3.130008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.130008E+01 0.000000E+00 5 4.417768E+02 8.994083E+01 4.561822E-01 4.417766E+02 + 3.130008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.130008E+01 3.000000E+01 1 3.686876E+01 8.994084E+01 3.807050E-02 3.686874E+01 + 3.130008E+01 3.000000E+01 2 2.249725E+01 8.993291E+01 2.634262E-02 2.249723E+01 + 3.130008E+01 3.000000E+01 3 1.887257E+02 2.554244E-01 1.887238E+02 8.413358E-01 + 3.130008E+01 3.000000E+01 4 7.303760E+01 8.993252E+01 8.602200E-02 7.303754E+01 + 3.130008E+01 3.000000E+01 5 3.837261E+02 8.994084E+01 3.962370E-01 3.837259E+02 + 3.130008E+01 3.000000E+01 6 5.375858E+01 -6.525866E-04 5.375858E+01 -6.122987E-04 + 3.130008E+01 6.000000E+01 1 2.141525E+01 8.994085E+01 2.211093E-02 2.141524E+01 + 3.130008E+01 6.000000E+01 2 3.922577E+01 8.993291E+01 4.593449E-02 3.922575E+01 + 3.130008E+01 6.000000E+01 3 1.900133E+02 2.561975E-01 1.900114E+02 8.496398E-01 + 3.130008E+01 6.000000E+01 4 1.280902E+02 8.993291E+01 1.499988E-01 1.280901E+02 + 3.130008E+01 6.000000E+01 5 2.228578E+02 8.994083E+01 2.301247E-01 2.228577E+02 + 3.130008E+01 6.000000E+01 6 5.412697E+01 -6.510770E-04 5.412697E+01 -6.150684E-04 + 3.130008E+01 9.000000E+01 1 2.220058E-06 -9.004291E+01 -1.662420E-09 -2.220057E-06 + 3.130008E+01 9.000000E+01 2 4.544458E+01 8.993291E+01 5.321904E-02 4.544455E+01 + 3.130008E+01 9.000000E+01 3 1.906605E+02 2.565849E-01 1.906586E+02 8.538228E-01 + 3.130008E+01 9.000000E+01 4 1.488255E+02 8.993310E+01 1.737858E-01 1.488254E+02 + 3.130008E+01 9.000000E+01 5 1.023886E-04 -8.999206E+01 1.419605E-08 -1.023886E-04 + 3.130008E+01 9.000000E+01 6 4.646949E-06 1.799996E+02 -4.646949E-06 3.565608E-11 + 3.140008E+01 0.000000E+00 1 4.230868E+01 8.994124E+01 4.339260E-02 4.230866E+01 + 3.140008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.140008E+01 0.000000E+00 3 1.882101E+02 2.533561E-01 1.882083E+02 8.322434E-01 + 3.140008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.140008E+01 0.000000E+00 5 4.405977E+02 8.994125E+01 4.518622E-01 4.405974E+02 + 3.140008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.140008E+01 3.000000E+01 1 3.675054E+01 8.994125E+01 3.768987E-02 3.675052E+01 + 3.140008E+01 3.000000E+01 2 2.242517E+01 8.993340E+01 2.606731E-02 2.242516E+01 + 3.140008E+01 3.000000E+01 3 1.888465E+02 2.537359E-01 1.888446E+02 8.363090E-01 + 3.140008E+01 3.000000E+01 4 7.279086E+01 8.993301E+01 8.510463E-02 7.279081E+01 + 3.140008E+01 3.000000E+01 5 3.826943E+02 8.994125E+01 3.924760E-01 3.826941E+02 + 3.140008E+01 3.000000E+01 6 5.340209E+01 -6.433519E-04 5.340209E+01 -5.996312E-04 + 3.140008E+01 6.000000E+01 1 2.134567E+01 8.994125E+01 2.188901E-02 2.134566E+01 + 3.140008E+01 6.000000E+01 2 3.909828E+01 8.993340E+01 4.545228E-02 3.909825E+01 + 3.140008E+01 6.000000E+01 3 1.901261E+02 2.544982E-01 1.901242E+02 8.445050E-01 + 3.140008E+01 6.000000E+01 4 1.276465E+02 8.993340E+01 1.483917E-01 1.276465E+02 + 3.140008E+01 6.000000E+01 5 2.222494E+02 8.994124E+01 2.279338E-01 2.222492E+02 + 3.140008E+01 6.000000E+01 6 5.376556E+01 -6.418732E-04 5.376556E+01 -6.023248E-04 + 3.140008E+01 9.000000E+01 1 2.212740E-06 -9.004267E+01 -1.647934E-09 -2.212739E-06 + 3.140008E+01 9.000000E+01 2 4.529589E+01 8.993339E+01 5.265917E-02 4.529586E+01 + 3.140008E+01 9.000000E+01 3 1.907693E+02 2.548800E-01 1.907674E+02 8.486333E-01 + 3.140008E+01 9.000000E+01 4 1.483038E+02 8.993358E+01 1.719213E-01 1.483037E+02 + 3.140008E+01 9.000000E+01 5 1.020689E-04 -8.999213E+01 1.402449E-08 -1.020689E-04 + 3.140008E+01 9.000000E+01 6 4.615771E-06 1.799996E+02 -4.615771E-06 3.491831E-11 + 3.150008E+01 0.000000E+00 1 4.217438E+01 8.994164E+01 4.296125E-02 4.217436E+01 + 3.150008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.150008E+01 0.000000E+00 3 1.883341E+02 2.516885E-01 1.883323E+02 8.273101E-01 + 3.150008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.150008E+01 0.000000E+00 5 4.394270E+02 8.994164E+01 4.476003E-01 4.394268E+02 + 3.150008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.150008E+01 3.000000E+01 1 3.663300E+01 8.994164E+01 3.731441E-02 3.663298E+01 + 3.150008E+01 3.000000E+01 2 2.235349E+01 8.993388E+01 2.579601E-02 2.235347E+01 + 3.150008E+01 3.000000E+01 3 1.889663E+02 2.520641E-01 1.889645E+02 8.313261E-01 + 3.150008E+01 3.000000E+01 4 7.254544E+01 8.993349E+01 8.420121E-02 7.254539E+01 + 3.150008E+01 3.000000E+01 5 3.816672E+02 8.994164E+01 3.887678E-01 3.816670E+02 + 3.150008E+01 3.000000E+01 6 5.304921E+01 -6.342840E-04 5.304921E+01 -5.872730E-04 + 3.150008E+01 6.000000E+01 1 2.127658E+01 8.994164E+01 2.167005E-02 2.127657E+01 + 3.150008E+01 6.000000E+01 2 3.897163E+01 8.993388E+01 4.497702E-02 3.897160E+01 + 3.150008E+01 6.000000E+01 3 1.902381E+02 2.528161E-01 1.902362E+02 8.394178E-01 + 3.150008E+01 6.000000E+01 4 1.272065E+02 8.993388E+01 1.468103E-01 1.272064E+02 + 3.150008E+01 6.000000E+01 5 2.216435E+02 8.994164E+01 2.257711E-01 2.216434E+02 + 3.150008E+01 6.000000E+01 6 5.340778E+01 -6.328357E-04 5.340778E+01 -5.898924E-04 + 3.150008E+01 9.000000E+01 1 2.205470E-06 -9.004244E+01 -1.633608E-09 -2.205469E-06 + 3.150008E+01 9.000000E+01 2 4.514809E+01 8.993388E+01 5.210731E-02 4.514806E+01 + 3.150008E+01 9.000000E+01 3 1.908779E+02 2.531905E-01 1.908760E+02 8.434882E-01 + 3.150008E+01 9.000000E+01 4 1.477864E+02 8.993406E+01 1.700838E-01 1.477863E+02 + 3.150008E+01 9.000000E+01 5 1.017515E-04 -8.999220E+01 1.385574E-08 -1.017515E-04 + 3.150008E+01 9.000000E+01 6 4.584919E-06 1.799996E+02 -4.584919E-06 3.419857E-11 + 3.160008E+01 0.000000E+00 1 4.204083E+01 8.994203E+01 4.253544E-02 4.204081E+01 + 3.160008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.160008E+01 0.000000E+00 3 1.884562E+02 2.500386E-01 1.884544E+02 8.224198E-01 + 3.160008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.160008E+01 0.000000E+00 5 4.382549E+02 8.994204E+01 4.433883E-01 4.382547E+02 + 3.160008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.160008E+01 3.000000E+01 1 3.651622E+01 8.994204E+01 3.694400E-02 3.651620E+01 + 3.160008E+01 3.000000E+01 2 2.228225E+01 8.993436E+01 2.552840E-02 2.228224E+01 + 3.160008E+01 3.000000E+01 3 1.890855E+02 2.504062E-01 1.890837E+02 8.263793E-01 + 3.160008E+01 3.000000E+01 4 7.230212E+01 8.993398E+01 8.331058E-02 7.230207E+01 + 3.160008E+01 3.000000E+01 5 3.806456E+02 8.994204E+01 3.851067E-01 3.806454E+02 + 3.160008E+01 3.000000E+01 6 5.269993E+01 -6.253745E-04 5.269993E+01 -5.752115E-04 + 3.160008E+01 6.000000E+01 1 2.120787E+01 8.994204E+01 2.145409E-02 2.120786E+01 + 3.160008E+01 6.000000E+01 2 3.884573E+01 8.993435E+01 4.450839E-02 3.884570E+01 + 3.160008E+01 6.000000E+01 3 1.903499E+02 2.511452E-01 1.903480E+02 8.343601E-01 + 3.160008E+01 6.000000E+01 4 1.267692E+02 8.993435E+01 1.452493E-01 1.267691E+02 + 3.160008E+01 6.000000E+01 5 2.210407E+02 8.994204E+01 2.236348E-01 2.210406E+02 + 3.160008E+01 6.000000E+01 6 5.305369E+01 -6.239574E-04 5.305369E+01 -5.777606E-04 + 3.160008E+01 9.000000E+01 1 2.198246E-06 -9.004221E+01 -1.619432E-09 -2.198245E-06 + 3.160008E+01 9.000000E+01 2 4.500122E+01 8.993435E+01 5.156337E-02 4.500119E+01 + 3.160008E+01 9.000000E+01 3 1.909846E+02 2.515182E-01 1.909828E+02 8.383856E-01 + 3.160008E+01 9.000000E+01 4 1.472733E+02 8.993454E+01 1.682731E-01 1.472732E+02 + 3.160008E+01 9.000000E+01 5 1.014360E-04 -8.999227E+01 1.368970E-08 -1.014360E-04 + 3.160008E+01 9.000000E+01 6 4.554380E-06 1.799996E+02 -4.554380E-06 3.349617E-11 + 3.170008E+01 0.000000E+00 1 4.190809E+01 8.994243E+01 4.211542E-02 4.190807E+01 + 3.170008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.170008E+01 0.000000E+00 3 1.885789E+02 2.484026E-01 1.885771E+02 8.175706E-01 + 3.170008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.170008E+01 0.000000E+00 5 4.370938E+02 8.994243E+01 4.392354E-01 4.370936E+02 + 3.170008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.170008E+01 3.000000E+01 1 3.640022E+01 8.994243E+01 3.657847E-02 3.640020E+01 + 3.170008E+01 3.000000E+01 2 2.221152E+01 8.993483E+01 2.526463E-02 2.221151E+01 + 3.170008E+01 3.000000E+01 3 1.892030E+02 2.487685E-01 1.892012E+02 8.214847E-01 + 3.170008E+01 3.000000E+01 4 7.206001E+01 8.993446E+01 8.243237E-02 7.205997E+01 + 3.170008E+01 3.000000E+01 5 3.796264E+02 8.994243E+01 3.814907E-01 3.796263E+02 + 3.170008E+01 3.000000E+01 6 5.235402E+01 -6.166263E-04 5.235402E+01 -5.634424E-04 + 3.170008E+01 6.000000E+01 1 2.113974E+01 8.994243E+01 2.124105E-02 2.113973E+01 + 3.170008E+01 6.000000E+01 2 3.872069E+01 8.993482E+01 4.404656E-02 3.872066E+01 + 3.170008E+01 6.000000E+01 3 1.904602E+02 2.494981E-01 1.904584E+02 8.293681E-01 + 3.170008E+01 6.000000E+01 4 1.263347E+02 8.993482E+01 1.437122E-01 1.263346E+02 + 3.170008E+01 6.000000E+01 5 2.204412E+02 8.994243E+01 2.215249E-01 2.204411E+02 + 3.170008E+01 6.000000E+01 6 5.270306E+01 -6.152387E-04 5.270306E+01 -5.659224E-04 + 3.170008E+01 9.000000E+01 1 2.191076E-06 -9.004198E+01 -1.605421E-09 -2.191076E-06 + 3.170008E+01 9.000000E+01 2 4.485546E+01 8.993482E+01 5.102707E-02 4.485543E+01 + 3.170008E+01 9.000000E+01 3 1.910912E+02 2.498643E-01 1.910894E+02 8.333375E-01 + 3.170008E+01 9.000000E+01 4 1.467623E+02 8.993501E+01 1.664887E-01 1.467622E+02 + 3.170008E+01 9.000000E+01 5 1.011228E-04 -8.999234E+01 1.352632E-08 -1.011228E-04 + 3.170008E+01 9.000000E+01 6 4.524147E-06 1.799996E+02 -4.524147E-06 3.281071E-11 + 3.180009E+01 0.000000E+00 1 4.177626E+01 8.994281E+01 4.170094E-02 4.177624E+01 + 3.180009E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.180009E+01 0.000000E+00 3 1.886985E+02 2.467859E-01 1.886967E+02 8.127648E-01 + 3.180009E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.180009E+01 0.000000E+00 5 4.359382E+02 8.994282E+01 4.351280E-01 4.359380E+02 + 3.180009E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.180009E+01 3.000000E+01 1 3.628497E+01 8.994282E+01 3.621782E-02 3.628495E+01 + 3.180009E+01 3.000000E+01 2 2.214123E+01 8.993530E+01 2.500446E-02 2.214121E+01 + 3.180009E+01 3.000000E+01 3 1.893201E+02 2.471441E-01 1.893183E+02 8.166255E-01 + 3.180009E+01 3.000000E+01 4 7.182027E+01 8.993493E+01 8.156680E-02 7.182023E+01 + 3.180009E+01 3.000000E+01 5 3.786160E+02 8.994282E+01 3.779165E-01 3.786158E+02 + 3.180009E+01 3.000000E+01 6 5.201163E+01 -6.080327E-04 5.201163E+01 -5.519564E-04 + 3.180009E+01 6.000000E+01 1 2.107197E+01 8.994282E+01 2.103077E-02 2.107196E+01 + 3.180009E+01 6.000000E+01 2 3.859646E+01 8.993529E+01 4.359111E-02 3.859644E+01 + 3.180009E+01 6.000000E+01 3 1.905677E+02 2.478663E-01 1.905659E+02 8.244089E-01 + 3.180009E+01 6.000000E+01 4 1.259037E+02 8.993529E+01 1.421973E-01 1.259036E+02 + 3.180009E+01 6.000000E+01 5 2.198459E+02 8.994281E+01 2.194431E-01 2.198458E+02 + 3.180009E+01 6.000000E+01 6 5.235597E+01 -6.066744E-04 5.235597E+01 -5.543694E-04 + 3.180009E+01 9.000000E+01 1 2.183949E-06 -9.004176E+01 -1.591557E-09 -2.183949E-06 + 3.180009E+01 9.000000E+01 2 4.471059E+01 8.993529E+01 5.049825E-02 4.471057E+01 + 3.180009E+01 9.000000E+01 3 1.911960E+02 2.482258E-01 1.911942E+02 8.283267E-01 + 3.180009E+01 9.000000E+01 4 1.462562E+02 8.993546E+01 1.647293E-01 1.462561E+02 + 3.180009E+01 9.000000E+01 5 1.008110E-04 -8.999240E+01 1.336559E-08 -1.008110E-04 + 3.180009E+01 9.000000E+01 6 4.494217E-06 1.799996E+02 -4.494217E-06 3.214170E-11 + 3.190009E+01 0.000000E+00 1 4.164527E+01 8.994319E+01 4.129188E-02 4.164525E+01 + 3.190009E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.190009E+01 0.000000E+00 3 1.888182E+02 2.451834E-01 1.888164E+02 8.079990E-01 + 3.190009E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.190009E+01 0.000000E+00 5 4.347829E+02 8.994320E+01 4.310761E-01 4.347827E+02 + 3.190009E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.190009E+01 3.000000E+01 1 3.617052E+01 8.994320E+01 3.586186E-02 3.617050E+01 + 3.190009E+01 3.000000E+01 2 2.207140E+01 8.993576E+01 2.474802E-02 2.207138E+01 + 3.190009E+01 3.000000E+01 3 1.894362E+02 2.455358E-01 1.894345E+02 8.118090E-01 + 3.190009E+01 3.000000E+01 4 7.158137E+01 8.993539E+01 8.071379E-02 7.158132E+01 + 3.190009E+01 3.000000E+01 5 3.776061E+02 8.994320E+01 3.743875E-01 3.776059E+02 + 3.190009E+01 3.000000E+01 6 5.167256E+01 -5.995906E-04 5.167256E+01 -5.407446E-04 + 3.190009E+01 6.000000E+01 1 2.100459E+01 8.994320E+01 2.082334E-02 2.100458E+01 + 3.190009E+01 6.000000E+01 2 3.847307E+01 8.993575E+01 4.314199E-02 3.847305E+01 + 3.190009E+01 6.000000E+01 3 1.906760E+02 2.462474E-01 1.906742E+02 8.194901E-01 + 3.190009E+01 6.000000E+01 4 1.254759E+02 8.993575E+01 1.407038E-01 1.254758E+02 + 3.190009E+01 6.000000E+01 5 2.192515E+02 8.994319E+01 2.173868E-01 2.192514E+02 + 3.190009E+01 6.000000E+01 6 5.201238E+01 -5.982598E-04 5.201238E+01 -5.430927E-04 + 3.190009E+01 9.000000E+01 1 2.176870E-06 -9.004153E+01 -1.577846E-09 -2.176870E-06 + 3.190009E+01 9.000000E+01 2 4.456656E+01 8.993575E+01 4.997700E-02 4.456654E+01 + 3.190009E+01 9.000000E+01 3 1.912997E+02 2.466044E-01 1.912979E+02 8.233623E-01 + 3.190009E+01 9.000000E+01 4 1.457529E+02 8.993593E+01 1.629959E-01 1.457528E+02 + 3.190009E+01 9.000000E+01 5 1.005013E-04 -8.999247E+01 1.320738E-08 -1.005013E-04 + 3.190009E+01 9.000000E+01 6 4.464596E-06 1.799996E+02 -4.464596E-06 3.148874E-11 + 3.200008E+01 0.000000E+00 1 4.151496E+01 8.994357E+01 4.088827E-02 4.151494E+01 + 3.200008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.200008E+01 0.000000E+00 3 1.889369E+02 2.435945E-01 1.889352E+02 8.032676E-01 + 3.200008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.200008E+01 0.000000E+00 5 4.336381E+02 8.994357E+01 4.270725E-01 4.336379E+02 + 3.200008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.200008E+01 3.000000E+01 1 3.605668E+01 8.994357E+01 3.551064E-02 3.605666E+01 + 3.200008E+01 3.000000E+01 2 2.200198E+01 8.993621E+01 2.449506E-02 2.200197E+01 + 3.200008E+01 3.000000E+01 3 1.895500E+02 2.439445E-01 1.895483E+02 8.070324E-01 + 3.200008E+01 3.000000E+01 4 7.134460E+01 8.993585E+01 7.987279E-02 7.134456E+01 + 3.200008E+01 3.000000E+01 5 3.766031E+02 8.994357E+01 3.709035E-01 3.766029E+02 + 3.200008E+01 3.000000E+01 6 5.133684E+01 -5.912976E-04 5.133684E+01 -5.298008E-04 + 3.200008E+01 6.000000E+01 1 2.093769E+01 8.994358E+01 2.061860E-02 2.093768E+01 + 3.200008E+01 6.000000E+01 2 3.835047E+01 8.993621E+01 4.269923E-02 3.835044E+01 + 3.200008E+01 6.000000E+01 3 1.907836E+02 2.446454E-01 1.907819E+02 8.146182E-01 + 3.200008E+01 6.000000E+01 4 1.250506E+02 8.993621E+01 1.392321E-01 1.250505E+02 + 3.200008E+01 6.000000E+01 5 2.186613E+02 8.994357E+01 2.153551E-01 2.186612E+02 + 3.200008E+01 6.000000E+01 6 5.167227E+01 -5.899935E-04 5.167227E+01 -5.320864E-04 + 3.200008E+01 9.000000E+01 1 2.169839E-06 -9.004131E+01 -1.564281E-09 -2.169839E-06 + 3.200008E+01 9.000000E+01 2 4.442363E+01 8.993620E+01 4.946293E-02 4.442361E+01 + 3.200008E+01 9.000000E+01 3 1.914030E+02 2.449974E-01 1.914012E+02 8.184388E-01 + 3.200008E+01 9.000000E+01 4 1.452537E+02 8.993638E+01 1.612873E-01 1.452536E+02 + 3.200008E+01 9.000000E+01 5 1.001939E-04 -8.999254E+01 1.305173E-08 -1.001939E-04 + 3.200008E+01 9.000000E+01 6 4.435266E-06 1.799996E+02 -4.435266E-06 3.085144E-11 + 3.210008E+01 0.000000E+00 1 4.138552E+01 8.994395E+01 4.049001E-02 4.138551E+01 + 3.210008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.210008E+01 0.000000E+00 3 1.890545E+02 2.420243E-01 1.890528E+02 7.985864E-01 + 3.210008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.210008E+01 0.000000E+00 5 4.324951E+02 8.994395E+01 4.231172E-01 4.324949E+02 + 3.210008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.210008E+01 3.000000E+01 1 3.594356E+01 8.994395E+01 3.516399E-02 3.594354E+01 + 3.210008E+01 3.000000E+01 2 2.193302E+01 8.993667E+01 2.424563E-02 2.193301E+01 + 3.210008E+01 3.000000E+01 3 1.896640E+02 2.423693E-01 1.896624E+02 8.023036E-01 + 3.210008E+01 3.000000E+01 4 7.110902E+01 8.993631E+01 7.904386E-02 7.110898E+01 + 3.210008E+01 3.000000E+01 5 3.756074E+02 8.994395E+01 3.674622E-01 3.756072E+02 + 3.210008E+01 3.000000E+01 6 5.100443E+01 -5.831493E-04 5.100443E+01 -5.191167E-04 + 3.210008E+01 6.000000E+01 1 2.087120E+01 8.994395E+01 2.041666E-02 2.087119E+01 + 3.210008E+01 6.000000E+01 2 3.822867E+01 8.993666E+01 4.226264E-02 3.822865E+01 + 3.210008E+01 6.000000E+01 3 1.908896E+02 2.430616E-01 1.908879E+02 8.097945E-01 + 3.210008E+01 6.000000E+01 4 1.246291E+02 8.993666E+01 1.377807E-01 1.246290E+02 + 3.210008E+01 6.000000E+01 5 2.180737E+02 8.994395E+01 2.133478E-01 2.180736E+02 + 3.210008E+01 6.000000E+01 6 5.133543E+01 -5.818719E-04 5.133543E+01 -5.213410E-04 + 3.210008E+01 9.000000E+01 1 2.162853E-06 -9.004108E+01 -1.550861E-09 -2.162853E-06 + 3.210008E+01 9.000000E+01 2 4.428160E+01 8.993665E+01 4.895616E-02 4.428158E+01 + 3.210008E+01 9.000000E+01 3 1.915062E+02 2.434063E-01 1.915045E+02 8.135623E-01 + 3.210008E+01 9.000000E+01 4 1.447575E+02 8.993683E+01 1.596025E-01 1.447574E+02 + 3.210008E+01 9.000000E+01 5 9.988794E-05 -8.999260E+01 1.289854E-08 -9.988794E-05 + 3.210008E+01 9.000000E+01 6 4.406237E-06 1.799996E+02 -4.406237E-06 3.022927E-11 + 3.220008E+01 0.000000E+00 1 4.125680E+01 8.994432E+01 4.009678E-02 4.125678E+01 + 3.220008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.220008E+01 0.000000E+00 3 1.891709E+02 2.404694E-01 1.891692E+02 7.939445E-01 + 3.220008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.220008E+01 0.000000E+00 5 4.313605E+02 8.994432E+01 4.192114E-01 4.313603E+02 + 3.220008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.220008E+01 3.000000E+01 1 3.583120E+01 8.994432E+01 3.482202E-02 3.583118E+01 + 3.220008E+01 3.000000E+01 2 2.186450E+01 8.993711E+01 2.399961E-02 2.186448E+01 + 3.220008E+01 3.000000E+01 3 1.897765E+02 2.408099E-01 1.897748E+02 7.976139E-01 + 3.220008E+01 3.000000E+01 4 7.087527E+01 8.993676E+01 7.822643E-02 7.087522E+01 + 3.220008E+01 3.000000E+01 5 3.746130E+02 8.994432E+01 3.640628E-01 3.746128E+02 + 3.220008E+01 3.000000E+01 6 5.067528E+01 -5.751448E-04 5.067528E+01 -5.086872E-04 + 3.220008E+01 6.000000E+01 1 2.080516E+01 8.994432E+01 2.021730E-02 2.080515E+01 + 3.220008E+01 6.000000E+01 2 3.810759E+01 8.993710E+01 4.183198E-02 3.810756E+01 + 3.220008E+01 6.000000E+01 3 1.909952E+02 2.414915E-01 1.909935E+02 8.050085E-01 + 3.220008E+01 6.000000E+01 4 1.242095E+02 8.993710E+01 1.363501E-01 1.242094E+02 + 3.220008E+01 6.000000E+01 5 2.174872E+02 8.994432E+01 2.113664E-01 2.174871E+02 + 3.220008E+01 6.000000E+01 6 5.100198E+01 -5.738919E-04 5.100198E+01 -5.108513E-04 + 3.220008E+01 9.000000E+01 1 2.155913E-06 -9.004086E+01 -1.537593E-09 -2.155913E-06 + 3.220008E+01 9.000000E+01 2 4.414053E+01 8.993710E+01 4.845633E-02 4.414050E+01 + 3.220008E+01 9.000000E+01 3 1.916070E+02 2.418338E-01 1.916053E+02 8.087315E-01 + 3.220008E+01 9.000000E+01 4 1.442664E+02 8.993728E+01 1.579417E-01 1.442663E+02 + 3.220008E+01 9.000000E+01 5 9.958397E-05 -8.999267E+01 1.274775E-08 -9.958397E-05 + 3.220008E+01 9.000000E+01 6 4.377488E-06 1.799996E+02 -4.377488E-06 2.962181E-11 + 3.230008E+01 0.000000E+00 1 4.112895E+01 8.994469E+01 3.970887E-02 4.112893E+01 + 3.230008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.230008E+01 0.000000E+00 3 1.892857E+02 2.389284E-01 1.892840E+02 7.893355E-01 + 3.230008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.230008E+01 0.000000E+00 5 4.302268E+02 8.994469E+01 4.153519E-01 4.302266E+02 + 3.230008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.230008E+01 3.000000E+01 1 3.571948E+01 8.994469E+01 3.448439E-02 3.571946E+01 + 3.230008E+01 3.000000E+01 2 2.179637E+01 8.993755E+01 2.375698E-02 2.179636E+01 + 3.230008E+01 3.000000E+01 3 1.898883E+02 2.392633E-01 1.898867E+02 7.929583E-01 + 3.230008E+01 3.000000E+01 4 7.064333E+01 8.993721E+01 7.742055E-02 7.064329E+01 + 3.230008E+01 3.000000E+01 5 3.736209E+02 8.994469E+01 3.607068E-01 3.736207E+02 + 3.230008E+01 3.000000E+01 6 5.034934E+01 -5.672779E-04 5.034934E+01 -4.985021E-04 + 3.230008E+01 6.000000E+01 1 2.073949E+01 8.994469E+01 2.002059E-02 2.073948E+01 + 3.230008E+01 6.000000E+01 2 3.798725E+01 8.993755E+01 4.140727E-02 3.798723E+01 + 3.230008E+01 6.000000E+01 3 1.910985E+02 2.399381E-01 1.910968E+02 8.002629E-01 + 3.230008E+01 6.000000E+01 4 1.237939E+02 8.993755E+01 1.349392E-01 1.237938E+02 + 3.230008E+01 6.000000E+01 5 2.169046E+02 8.994469E+01 2.094097E-01 2.169044E+02 + 3.230008E+01 6.000000E+01 6 5.067178E+01 -5.660514E-04 5.067178E+01 -5.006098E-04 + 3.230008E+01 9.000000E+01 1 2.149018E-06 -9.004064E+01 -1.524460E-09 -2.149018E-06 + 3.230008E+01 9.000000E+01 2 4.400010E+01 8.993754E+01 4.796338E-02 4.400007E+01 + 3.230008E+01 9.000000E+01 3 1.917073E+02 2.402732E-01 1.917056E+02 8.039336E-01 + 3.230008E+01 9.000000E+01 4 1.437770E+02 8.993771E+01 1.563048E-01 1.437769E+02 + 3.230008E+01 9.000000E+01 5 9.928187E-05 -8.999273E+01 1.259932E-08 -9.928187E-05 + 3.230008E+01 9.000000E+01 6 4.349024E-06 1.799996E+02 -4.349024E-06 2.902866E-11 + 3.240008E+01 0.000000E+00 1 4.100199E+01 8.994505E+01 3.932587E-02 4.100197E+01 + 3.240008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.240008E+01 0.000000E+00 3 1.894001E+02 2.374020E-01 1.893985E+02 7.847670E-01 + 3.240008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.240008E+01 0.000000E+00 5 4.291011E+02 8.994505E+01 4.115402E-01 4.291009E+02 + 3.240008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.240008E+01 3.000000E+01 1 3.560848E+01 8.994505E+01 3.415127E-02 3.560846E+01 + 3.240008E+01 3.000000E+01 2 2.172871E+01 8.993799E+01 2.351772E-02 2.172870E+01 + 3.240008E+01 3.000000E+01 3 1.899988E+02 2.377335E-01 1.899972E+02 7.883469E-01 + 3.240008E+01 3.000000E+01 4 7.041291E+01 8.993765E+01 7.662544E-02 7.041287E+01 + 3.240008E+01 3.000000E+01 5 3.726361E+02 8.994505E+01 3.573909E-01 3.726360E+02 + 3.240008E+01 3.000000E+01 6 5.002665E+01 -5.595473E-04 5.002665E+01 -4.885573E-04 + 3.240008E+01 6.000000E+01 1 2.067430E+01 8.994505E+01 1.982643E-02 2.067429E+01 + 3.240008E+01 6.000000E+01 2 3.786776E+01 8.993799E+01 4.098853E-02 3.786774E+01 + 3.240008E+01 6.000000E+01 3 1.912020E+02 2.383991E-01 1.912004E+02 7.955605E-01 + 3.240008E+01 6.000000E+01 4 1.233801E+02 8.993799E+01 1.335490E-01 1.233801E+02 + 3.240008E+01 6.000000E+01 5 2.163262E+02 8.994505E+01 2.074770E-01 2.163261E+02 + 3.240008E+01 6.000000E+01 6 5.034487E+01 -5.583456E-04 5.034487E+01 -4.906092E-04 + 3.240008E+01 9.000000E+01 1 2.142163E-06 -9.004043E+01 -1.511472E-09 -2.142163E-06 + 3.240008E+01 9.000000E+01 2 4.386096E+01 8.993798E+01 4.747720E-02 4.386093E+01 + 3.240008E+01 9.000000E+01 3 1.918069E+02 2.387314E-01 1.918052E+02 7.991897E-01 + 3.240008E+01 9.000000E+01 4 1.432912E+02 8.993815E+01 1.546903E-01 1.432911E+02 + 3.240008E+01 9.000000E+01 5 9.898109E-05 -8.999279E+01 1.245321E-08 -9.898109E-05 + 3.240008E+01 9.000000E+01 6 4.320847E-06 1.799996E+02 -4.320847E-06 2.844953E-11 + 3.250008E+01 0.000000E+00 1 4.087568E+01 8.994541E+01 3.894788E-02 4.087566E+01 + 3.250008E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.250008E+01 0.000000E+00 3 1.895135E+02 2.358895E-01 1.895119E+02 7.802342E-01 + 3.250008E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.250008E+01 0.000000E+00 5 4.279817E+02 8.994541E+01 4.077779E-01 4.279815E+02 + 3.250008E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.250008E+01 3.000000E+01 1 3.549810E+01 8.994541E+01 3.382239E-02 3.549809E+01 + 3.250008E+01 3.000000E+01 2 2.166137E+01 8.993842E+01 2.328165E-02 2.166136E+01 + 3.250008E+01 3.000000E+01 3 1.901080E+02 2.362162E-01 1.901064E+02 7.837657E-01 + 3.250008E+01 3.000000E+01 4 7.018360E+01 8.993809E+01 7.584215E-02 7.018356E+01 + 3.250008E+01 3.000000E+01 5 3.716557E+02 8.994541E+01 3.541102E-01 3.716555E+02 + 3.250008E+01 3.000000E+01 6 4.970701E+01 -5.519501E-04 4.970701E+01 -4.788449E-04 + 3.250008E+01 6.000000E+01 1 2.060950E+01 8.994542E+01 1.963478E-02 2.060949E+01 + 3.250008E+01 6.000000E+01 2 3.774897E+01 8.993842E+01 4.057537E-02 3.774894E+01 + 3.250008E+01 6.000000E+01 3 1.913042E+02 2.368745E-01 1.913026E+02 7.908953E-01 + 3.250008E+01 6.000000E+01 4 1.229697E+02 8.993842E+01 1.321773E-01 1.229697E+02 + 3.250008E+01 6.000000E+01 5 2.157487E+02 8.994541E+01 2.055700E-01 2.157487E+02 + 3.250008E+01 6.000000E+01 6 5.002107E+01 -5.507733E-04 5.002107E+01 -4.808429E-04 + 3.250008E+01 9.000000E+01 1 2.135361E-06 -9.004021E+01 -1.498625E-09 -2.135360E-06 + 3.250008E+01 9.000000E+01 2 4.372243E+01 8.993842E+01 4.699778E-02 4.372240E+01 + 3.250008E+01 9.000000E+01 3 1.919054E+02 2.372008E-01 1.919038E+02 7.944735E-01 + 3.250008E+01 9.000000E+01 4 1.428095E+02 8.993858E+01 1.530993E-01 1.428094E+02 + 3.250008E+01 9.000000E+01 5 9.868251E-05 -8.999285E+01 1.230938E-08 -9.868251E-05 + 3.250008E+01 9.000000E+01 6 4.292944E-06 1.799996E+02 -4.292944E-06 2.788391E-11 + 3.260007E+01 0.000000E+00 1 4.075017E+01 8.994576E+01 3.857466E-02 4.075015E+01 + 3.260007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.260007E+01 0.000000E+00 3 1.896254E+02 2.343947E-01 1.896239E+02 7.757479E-01 + 3.260007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.260007E+01 0.000000E+00 5 4.268635E+02 8.994576E+01 4.040548E-01 4.268633E+02 + 3.260007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.260007E+01 3.000000E+01 1 3.538857E+01 8.994576E+01 3.349778E-02 3.538855E+01 + 3.260007E+01 3.000000E+01 2 2.159455E+01 8.993884E+01 2.304880E-02 2.159454E+01 + 3.260007E+01 3.000000E+01 3 1.902169E+02 2.347176E-01 1.902153E+02 7.792391E-01 + 3.260007E+01 3.000000E+01 4 6.995581E+01 8.993851E+01 7.506908E-02 6.995577E+01 + 3.260007E+01 3.000000E+01 5 3.706799E+02 8.994576E+01 3.508785E-01 3.706798E+02 + 3.260007E+01 3.000000E+01 6 4.939045E+01 -5.444839E-04 4.939045E+01 -4.693592E-04 + 3.260007E+01 6.000000E+01 1 2.054506E+01 8.994577E+01 1.944564E-02 2.054505E+01 + 3.260007E+01 6.000000E+01 2 3.763100E+01 8.993884E+01 4.016798E-02 3.763098E+01 + 3.260007E+01 6.000000E+01 3 1.914061E+02 2.353635E-01 1.914045E+02 7.862688E-01 + 3.260007E+01 6.000000E+01 4 1.225619E+02 8.993884E+01 1.308252E-01 1.225618E+02 + 3.260007E+01 6.000000E+01 5 2.151736E+02 8.994576E+01 2.036822E-01 2.151735E+02 + 3.260007E+01 6.000000E+01 6 4.970055E+01 -5.433299E-04 4.970055E+01 -4.713051E-04 + 3.260007E+01 9.000000E+01 1 2.128597E-06 -9.003999E+01 -1.485917E-09 -2.128596E-06 + 3.260007E+01 9.000000E+01 2 4.358488E+01 8.993884E+01 4.652485E-02 4.358485E+01 + 3.260007E+01 9.000000E+01 3 1.920032E+02 2.356875E-01 1.920016E+02 7.898074E-01 + 3.260007E+01 9.000000E+01 4 1.423310E+02 8.993900E+01 1.515296E-01 1.423309E+02 + 3.260007E+01 9.000000E+01 5 9.838604E-05 -8.999291E+01 1.216779E-08 -9.838604E-05 + 3.260007E+01 9.000000E+01 6 4.265306E-06 1.799996E+02 -4.265306E-06 2.733150E-11 + 3.270007E+01 0.000000E+00 1 4.062551E+01 8.994612E+01 3.820643E-02 4.062550E+01 + 3.270007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.270007E+01 0.000000E+00 3 1.897361E+02 2.329117E-01 1.897345E+02 7.712896E-01 + 3.270007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.270007E+01 0.000000E+00 5 4.257521E+02 8.994612E+01 4.003795E-01 4.257519E+02 + 3.270007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.270007E+01 3.000000E+01 1 3.527961E+01 8.994612E+01 3.317728E-02 3.527960E+01 + 3.270007E+01 3.000000E+01 2 2.152806E+01 8.993927E+01 2.281912E-02 2.152805E+01 + 3.270007E+01 3.000000E+01 3 1.903243E+02 2.332301E-01 1.903228E+02 7.747384E-01 + 3.270007E+01 3.000000E+01 4 6.972990E+01 8.993894E+01 7.430685E-02 6.972986E+01 + 3.270007E+01 3.000000E+01 5 3.697094E+02 8.994612E+01 3.476809E-01 3.697092E+02 + 3.270007E+01 3.000000E+01 6 4.907703E+01 -5.371456E-04 4.907703E+01 -4.600952E-04 + 3.270007E+01 6.000000E+01 1 2.048114E+01 8.994613E+01 1.925889E-02 2.048113E+01 + 3.270007E+01 6.000000E+01 2 3.751371E+01 8.993926E+01 3.976609E-02 3.751369E+01 + 3.270007E+01 6.000000E+01 3 1.915064E+02 2.338690E-01 1.915048E+02 7.816854E-01 + 3.270007E+01 6.000000E+01 4 1.221573E+02 8.993926E+01 1.294923E-01 1.221572E+02 + 3.270007E+01 6.000000E+01 5 2.146027E+02 8.994612E+01 2.018178E-01 2.146026E+02 + 3.270007E+01 6.000000E+01 6 4.938311E+01 -5.360143E-04 4.938311E+01 -4.619896E-04 + 3.270007E+01 9.000000E+01 1 2.121884E-06 -9.003978E+01 -1.473344E-09 -2.121883E-06 + 3.270007E+01 9.000000E+01 2 4.344816E+01 8.993926E+01 4.605846E-02 4.344814E+01 + 3.270007E+01 9.000000E+01 3 1.921006E+02 2.341865E-01 1.920990E+02 7.851754E-01 + 3.270007E+01 9.000000E+01 4 1.418556E+02 8.993942E+01 1.499822E-01 1.418555E+02 + 3.270007E+01 9.000000E+01 5 9.809092E-05 -8.999297E+01 1.202839E-08 -9.809092E-05 + 3.270007E+01 9.000000E+01 6 4.237947E-06 1.799996E+02 -4.237947E-06 2.679195E-11 + 3.280007E+01 0.000000E+00 1 4.050157E+01 8.994647E+01 3.784274E-02 4.050155E+01 + 3.280007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.280007E+01 0.000000E+00 3 1.898468E+02 2.314430E-01 1.898453E+02 7.668732E-01 + 3.280007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.280007E+01 0.000000E+00 5 4.246447E+02 8.994647E+01 3.967502E-01 4.246445E+02 + 3.280007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.280007E+01 3.000000E+01 1 3.517133E+01 8.994647E+01 3.286090E-02 3.517131E+01 + 3.280007E+01 3.000000E+01 2 2.146205E+01 8.993969E+01 2.259255E-02 2.146204E+01 + 3.280007E+01 3.000000E+01 3 1.904306E+02 2.317582E-01 1.904290E+02 7.702790E-01 + 3.280007E+01 3.000000E+01 4 6.950526E+01 8.993936E+01 7.355542E-02 6.950522E+01 + 3.280007E+01 3.000000E+01 5 3.687395E+02 8.994647E+01 3.445204E-01 3.687393E+02 + 3.280007E+01 3.000000E+01 6 4.876656E+01 -5.299335E-04 4.876656E+01 -4.510460E-04 + 3.280007E+01 6.000000E+01 1 2.041751E+01 8.994647E+01 1.907471E-02 2.041751E+01 + 3.280007E+01 6.000000E+01 2 3.739711E+01 8.993969E+01 3.936956E-02 3.739709E+01 + 3.280007E+01 6.000000E+01 3 1.916055E+02 2.323883E-01 1.916039E+02 7.771385E-01 + 3.280007E+01 6.000000E+01 4 1.217550E+02 8.993969E+01 1.281774E-01 1.217549E+02 + 3.280007E+01 6.000000E+01 5 2.140330E+02 8.994647E+01 1.999796E-01 2.140329E+02 + 3.280007E+01 6.000000E+01 6 4.906877E+01 -5.288246E-04 4.906877E+01 -4.528915E-04 + 3.280007E+01 9.000000E+01 1 2.115198E-06 -9.003957E+01 -1.460903E-09 -2.115197E-06 + 3.280007E+01 9.000000E+01 2 4.331230E+01 8.993968E+01 4.559829E-02 4.331228E+01 + 3.280007E+01 9.000000E+01 3 1.921956E+02 2.327027E-01 1.921940E+02 7.805864E-01 + 3.280007E+01 9.000000E+01 4 1.413835E+02 8.993983E+01 1.484559E-01 1.413834E+02 + 3.280007E+01 9.000000E+01 5 9.779726E-05 -8.999303E+01 1.189116E-08 -9.779726E-05 + 3.280007E+01 9.000000E+01 6 4.210858E-06 1.799996E+02 -4.210858E-06 2.626491E-11 + 3.290007E+01 0.000000E+00 1 4.037837E+01 8.994681E+01 3.748371E-02 4.037835E+01 + 3.290007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.290007E+01 0.000000E+00 3 1.899555E+02 2.299896E-01 1.899539E+02 7.624938E-01 + 3.290007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.290007E+01 0.000000E+00 5 4.235428E+02 8.994682E+01 3.931653E-01 4.235426E+02 + 3.290007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.290007E+01 3.000000E+01 1 3.506364E+01 8.994682E+01 3.254865E-02 3.506363E+01 + 3.290007E+01 3.000000E+01 2 2.139643E+01 8.994010E+01 2.236903E-02 2.139642E+01 + 3.290007E+01 3.000000E+01 3 1.905367E+02 2.302989E-01 1.905351E+02 7.658550E-01 + 3.290007E+01 3.000000E+01 4 6.928204E+01 8.993978E+01 7.281420E-02 6.928200E+01 + 3.290007E+01 3.000000E+01 5 3.677775E+02 8.994682E+01 3.413959E-01 3.677773E+02 + 3.290007E+01 3.000000E+01 6 4.845910E+01 -5.228421E-04 4.845910E+01 -4.422046E-04 + 3.290007E+01 6.000000E+01 1 2.035437E+01 8.994682E+01 1.889274E-02 2.035436E+01 + 3.290007E+01 6.000000E+01 2 3.728128E+01 8.994009E+01 3.897846E-02 3.728126E+01 + 3.290007E+01 6.000000E+01 3 1.917040E+02 2.309203E-01 1.917024E+02 7.726262E-01 + 3.290007E+01 6.000000E+01 4 1.213558E+02 8.994009E+01 1.268805E-01 1.213557E+02 + 3.290007E+01 6.000000E+01 5 2.134662E+02 8.994681E+01 1.981611E-01 2.134661E+02 + 3.290007E+01 6.000000E+01 6 4.875742E+01 -5.217555E-04 4.875742E+01 -4.440022E-04 + 3.290007E+01 9.000000E+01 1 2.108570E-06 -9.003937E+01 -1.448598E-09 -2.108569E-06 + 3.290007E+01 9.000000E+01 2 4.317736E+01 8.994009E+01 4.514453E-02 4.317733E+01 + 3.290007E+01 9.000000E+01 3 1.922909E+02 2.312311E-01 1.922893E+02 7.760345E-01 + 3.290007E+01 9.000000E+01 4 1.409151E+02 8.994025E+01 1.469510E-01 1.409151E+02 + 3.290007E+01 9.000000E+01 5 9.750568E-05 -8.999309E+01 1.175602E-08 -9.750568E-05 + 3.290007E+01 9.000000E+01 6 4.184036E-06 1.799996E+02 -4.184036E-06 2.575009E-11 + 3.300007E+01 0.000000E+00 1 4.025585E+01 8.994716E+01 3.712926E-02 4.025583E+01 + 3.300007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.300007E+01 0.000000E+00 3 1.900640E+02 2.285481E-01 1.900625E+02 7.581477E-01 + 3.300007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.300007E+01 0.000000E+00 5 4.224463E+02 8.994716E+01 3.896166E-01 4.224461E+02 + 3.300007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.300007E+01 3.000000E+01 1 3.495679E+01 8.994716E+01 3.224034E-02 3.495678E+01 + 3.300007E+01 3.000000E+01 2 2.133117E+01 8.994051E+01 2.214840E-02 2.133116E+01 + 3.300007E+01 3.000000E+01 3 1.906416E+02 2.288531E-01 1.906401E+02 7.614663E-01 + 3.300007E+01 3.000000E+01 4 6.906031E+01 8.994020E+01 7.208294E-02 6.906027E+01 + 3.300007E+01 3.000000E+01 5 3.668197E+02 8.994716E+01 3.383159E-01 3.668195E+02 + 3.300007E+01 3.000000E+01 6 4.815453E+01 -5.158705E-04 4.815453E+01 -4.335660E-04 + 3.300007E+01 6.000000E+01 1 2.029157E+01 8.994717E+01 1.871317E-02 2.029156E+01 + 3.300007E+01 6.000000E+01 2 3.716633E+01 8.994051E+01 3.859261E-02 3.716631E+01 + 3.300007E+01 6.000000E+01 3 1.918021E+02 2.294670E-01 1.918006E+02 7.681569E-01 + 3.300007E+01 6.000000E+01 4 1.209585E+02 8.994051E+01 1.256014E-01 1.209585E+02 + 3.300007E+01 6.000000E+01 5 2.129026E+02 8.994716E+01 1.963649E-01 2.129025E+02 + 3.300007E+01 6.000000E+01 6 4.844903E+01 -5.148064E-04 4.844903E+01 -4.353177E-04 + 3.300007E+01 9.000000E+01 1 2.101973E-06 -9.003915E+01 -1.436424E-09 -2.101973E-06 + 3.300007E+01 9.000000E+01 2 4.304322E+01 8.994051E+01 4.469663E-02 4.304320E+01 + 3.300007E+01 9.000000E+01 3 1.923854E+02 2.297733E-01 1.923839E+02 7.715214E-01 + 3.300007E+01 9.000000E+01 4 1.404492E+02 8.994066E+01 1.454666E-01 1.404491E+02 + 3.300007E+01 9.000000E+01 5 9.721555E-05 -8.999316E+01 1.162294E-08 -9.721555E-05 + 3.300007E+01 9.000000E+01 6 4.157459E-06 1.799996E+02 -4.157459E-06 2.524701E-11 + 3.310007E+01 0.000000E+00 1 4.013415E+01 8.994749E+01 3.677930E-02 4.013413E+01 + 3.310007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.310007E+01 0.000000E+00 3 1.901713E+02 2.271214E-01 1.901698E+02 7.538400E-01 + 3.310007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.310007E+01 0.000000E+00 5 4.213561E+02 8.994750E+01 3.861173E-01 4.213559E+02 + 3.310007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.310007E+01 3.000000E+01 1 3.485051E+01 8.994750E+01 3.193597E-02 3.485050E+01 + 3.310007E+01 3.000000E+01 2 2.126639E+01 8.994092E+01 2.193080E-02 2.126638E+01 + 3.310007E+01 3.000000E+01 3 1.907446E+02 2.274259E-01 1.907431E+02 7.571262E-01 + 3.310007E+01 3.000000E+01 4 6.884032E+01 8.994061E+01 7.136160E-02 6.884028E+01 + 3.310007E+01 3.000000E+01 5 3.658636E+02 8.994749E+01 3.352709E-01 3.658634E+02 + 3.310007E+01 3.000000E+01 6 4.785292E+01 -5.090184E-04 4.785292E+01 -4.251276E-04 + 3.310007E+01 6.000000E+01 1 2.022916E+01 8.994750E+01 1.853587E-02 2.022915E+01 + 3.310007E+01 6.000000E+01 2 3.705191E+01 8.994091E+01 3.821192E-02 3.705189E+01 + 3.310007E+01 6.000000E+01 3 1.918990E+02 2.280288E-01 1.918974E+02 7.637275E-01 + 3.310007E+01 6.000000E+01 4 1.205647E+02 8.994091E+01 1.243399E-01 1.205647E+02 + 3.310007E+01 6.000000E+01 5 2.123428E+02 8.994749E+01 1.945905E-01 2.123427E+02 + 3.310007E+01 6.000000E+01 6 4.814366E+01 -5.079747E-04 4.814366E+01 -4.268336E-04 + 3.310007E+01 9.000000E+01 1 2.095427E-06 -9.003895E+01 -1.424380E-09 -2.095426E-06 + 3.310007E+01 9.000000E+01 2 4.290991E+01 8.994091E+01 4.425495E-02 4.290989E+01 + 3.310007E+01 9.000000E+01 3 1.924789E+02 2.283318E-01 1.924774E+02 7.670537E-01 + 3.310007E+01 9.000000E+01 4 1.399865E+02 8.994106E+01 1.440035E-01 1.399864E+02 + 3.310007E+01 9.000000E+01 5 9.692730E-05 -8.999321E+01 1.149185E-08 -9.692730E-05 + 3.310007E+01 9.000000E+01 6 4.131145E-06 1.799996E+02 -4.131145E-06 2.475558E-11 + 3.320007E+01 0.000000E+00 1 4.001321E+01 8.994783E+01 3.643377E-02 4.001320E+01 + 3.320007E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.320007E+01 0.000000E+00 3 1.902766E+02 2.257106E-01 1.902751E+02 7.495722E-01 + 3.320007E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.320007E+01 0.000000E+00 5 4.202658E+02 8.994784E+01 3.826576E-01 4.202656E+02 + 3.320007E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.320007E+01 3.000000E+01 1 3.474481E+01 8.994784E+01 3.163544E-02 3.474479E+01 + 3.320007E+01 3.000000E+01 2 2.120192E+01 8.994132E+01 2.171606E-02 2.120191E+01 + 3.320007E+01 3.000000E+01 3 1.908476E+02 2.260078E-01 1.908461E+02 7.528118E-01 + 3.320007E+01 3.000000E+01 4 6.862160E+01 8.994101E+01 7.065042E-02 6.862156E+01 + 3.320007E+01 3.000000E+01 5 3.649148E+02 8.994784E+01 3.322608E-01 3.649147E+02 + 3.320007E+01 3.000000E+01 6 4.755409E+01 -5.022815E-04 4.755409E+01 -4.168813E-04 + 3.320007E+01 6.000000E+01 1 2.016714E+01 8.994784E+01 1.836078E-02 2.016713E+01 + 3.320007E+01 6.000000E+01 2 3.693820E+01 8.994131E+01 3.783626E-02 3.693818E+01 + 3.320007E+01 6.000000E+01 3 1.919947E+02 2.266037E-01 1.919932E+02 7.593333E-01 + 3.320007E+01 6.000000E+01 4 1.201731E+02 8.994131E+01 1.230952E-01 1.201731E+02 + 3.320007E+01 6.000000E+01 5 2.117833E+02 8.994784E+01 1.928348E-01 2.117832E+02 + 3.320007E+01 6.000000E+01 6 4.784115E+01 -5.012579E-04 4.784115E+01 -4.185432E-04 + 3.320007E+01 9.000000E+01 1 2.088918E-06 -9.003874E+01 -1.412462E-09 -2.088917E-06 + 3.320007E+01 9.000000E+01 2 4.277749E+01 8.994131E+01 4.381904E-02 4.277747E+01 + 3.320007E+01 9.000000E+01 3 1.925713E+02 2.269027E-01 1.925698E+02 7.626185E-01 + 3.320007E+01 9.000000E+01 4 1.395276E+02 8.994146E+01 1.425587E-01 1.395276E+02 + 3.320007E+01 9.000000E+01 5 9.664099E-05 -8.999326E+01 1.136279E-08 -9.664099E-05 + 3.320007E+01 9.000000E+01 6 4.105087E-06 1.799997E+02 -4.105087E-06 2.427533E-11 + 3.330006E+01 0.000000E+00 1 3.989290E+01 8.994817E+01 3.609265E-02 3.989289E+01 + 3.330006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.330006E+01 0.000000E+00 3 1.903828E+02 2.243082E-01 1.903813E+02 7.453308E-01 + 3.330006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.330006E+01 0.000000E+00 5 4.191859E+02 8.994817E+01 3.792374E-01 4.191858E+02 + 3.330006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.330006E+01 3.000000E+01 1 3.463985E+01 8.994817E+01 3.133862E-02 3.463984E+01 + 3.330006E+01 3.000000E+01 2 2.113789E+01 8.994171E+01 2.150420E-02 2.113788E+01 + 3.330006E+01 3.000000E+01 3 1.909505E+02 2.246025E-01 1.909490E+02 7.485340E-01 + 3.330006E+01 3.000000E+01 4 6.840399E+01 8.994141E+01 6.994873E-02 6.840395E+01 + 3.330006E+01 3.000000E+01 5 3.639682E+02 8.994817E+01 3.292862E-01 3.639681E+02 + 3.330006E+01 3.000000E+01 6 4.725818E+01 -4.956563E-04 4.725818E+01 -4.088227E-04 + 3.330006E+01 6.000000E+01 1 2.010546E+01 8.994817E+01 1.818799E-02 2.010545E+01 + 3.330006E+01 6.000000E+01 2 3.682528E+01 8.994171E+01 3.746574E-02 3.682526E+01 + 3.330006E+01 6.000000E+01 3 1.920908E+02 2.251912E-01 1.920893E+02 7.549779E-01 + 3.330006E+01 6.000000E+01 4 1.197841E+02 8.994171E+01 1.218680E-01 1.197840E+02 + 3.330006E+01 6.000000E+01 5 2.112272E+02 8.994817E+01 1.911036E-01 2.112271E+02 + 3.330006E+01 6.000000E+01 6 4.754157E+01 -4.946532E-04 4.754157E+01 -4.104419E-04 + 3.330006E+01 9.000000E+01 1 2.082450E-06 -9.003854E+01 -1.400675E-09 -2.082449E-06 + 3.330006E+01 9.000000E+01 2 4.264584E+01 8.994171E+01 4.338904E-02 4.264582E+01 + 3.330006E+01 9.000000E+01 3 1.926637E+02 2.254867E-01 1.926622E+02 7.582231E-01 + 3.330006E+01 9.000000E+01 4 1.390710E+02 8.994186E+01 1.411347E-01 1.390710E+02 + 3.330006E+01 9.000000E+01 5 9.635598E-05 -8.999332E+01 1.123567E-08 -9.635598E-05 + 3.330006E+01 9.000000E+01 6 4.079272E-06 1.799997E+02 -4.079272E-06 2.380602E-11 + 3.340006E+01 0.000000E+00 1 3.977332E+01 8.994849E+01 3.575583E-02 3.977330E+01 + 3.340006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.340006E+01 0.000000E+00 3 1.904877E+02 2.229205E-01 1.904863E+02 7.411280E-01 + 3.340006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.340006E+01 0.000000E+00 5 4.181083E+02 8.994849E+01 3.758605E-01 4.181081E+02 + 3.340006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.340006E+01 3.000000E+01 1 3.453543E+01 8.994849E+01 3.104566E-02 3.453542E+01 + 3.340006E+01 3.000000E+01 2 2.107421E+01 8.994210E+01 2.129508E-02 2.107420E+01 + 3.340006E+01 3.000000E+01 3 1.910508E+02 2.232130E-01 1.910493E+02 7.442940E-01 + 3.340006E+01 3.000000E+01 4 6.818805E+01 8.994181E+01 6.925596E-02 6.818801E+01 + 3.340006E+01 3.000000E+01 5 3.630287E+02 8.994849E+01 3.263490E-01 3.630285E+02 + 3.340006E+01 3.000000E+01 6 4.696491E+01 -4.891424E-04 4.696491E+01 -4.009463E-04 + 3.340006E+01 6.000000E+01 1 2.004414E+01 8.994849E+01 1.801731E-02 2.004414E+01 + 3.340006E+01 6.000000E+01 2 3.671303E+01 8.994210E+01 3.709995E-02 3.671301E+01 + 3.340006E+01 6.000000E+01 3 1.921849E+02 2.237944E-01 1.921834E+02 7.506623E-01 + 3.340006E+01 6.000000E+01 4 1.193978E+02 8.994210E+01 1.206570E-01 1.193977E+02 + 3.340006E+01 6.000000E+01 5 2.106739E+02 8.994849E+01 1.893928E-01 2.106738E+02 + 3.340006E+01 6.000000E+01 6 4.724491E+01 -4.881580E-04 4.724491E+01 -4.025249E-04 + 3.340006E+01 9.000000E+01 1 2.076021E-06 -9.003834E+01 -1.389009E-09 -2.076020E-06 + 3.340006E+01 9.000000E+01 2 4.251513E+01 8.994210E+01 4.296470E-02 4.251511E+01 + 3.340006E+01 9.000000E+01 3 1.927546E+02 2.240849E-01 1.927531E+02 7.538652E-01 + 3.340006E+01 9.000000E+01 4 1.386183E+02 8.994225E+01 1.397293E-01 1.386183E+02 + 3.340006E+01 9.000000E+01 5 9.607337E-05 -8.999338E+01 1.111041E-08 -9.607337E-05 + 3.340006E+01 9.000000E+01 6 4.053707E-06 1.799997E+02 -4.053707E-06 2.334736E-11 + 3.350006E+01 0.000000E+00 1 3.965461E+01 8.994881E+01 3.542322E-02 3.965459E+01 + 3.350006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.350006E+01 0.000000E+00 3 1.905910E+02 2.215475E-01 1.905896E+02 7.369626E-01 + 3.350006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.350006E+01 0.000000E+00 5 4.170345E+02 8.994881E+01 3.725198E-01 4.170343E+02 + 3.350006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.350006E+01 3.000000E+01 1 3.443173E+01 8.994881E+01 3.075631E-02 3.443172E+01 + 3.350006E+01 3.000000E+01 2 2.101094E+01 8.994249E+01 2.108870E-02 2.101093E+01 + 3.350006E+01 3.000000E+01 3 1.911513E+02 2.218343E-01 1.911499E+02 7.400862E-01 + 3.350006E+01 3.000000E+01 4 6.797367E+01 8.994220E+01 6.857287E-02 6.797363E+01 + 3.350006E+01 3.000000E+01 5 3.620924E+02 8.994881E+01 3.234438E-01 3.620922E+02 + 3.350006E+01 3.000000E+01 6 4.667448E+01 -4.827369E-04 4.667448E+01 -3.932487E-04 + 3.350006E+01 6.000000E+01 1 1.998332E+01 8.994882E+01 1.784883E-02 1.998331E+01 + 3.350006E+01 6.000000E+01 2 3.660141E+01 8.994249E+01 3.673913E-02 3.660139E+01 + 3.350006E+01 6.000000E+01 3 1.922785E+02 2.224091E-01 1.922771E+02 7.463794E-01 + 3.350006E+01 6.000000E+01 4 1.190141E+02 8.994249E+01 1.194625E-01 1.190140E+02 + 3.350006E+01 6.000000E+01 5 2.101224E+02 8.994881E+01 1.877010E-01 2.101223E+02 + 3.350006E+01 6.000000E+01 6 4.695098E+01 -4.817709E-04 4.695098E+01 -3.947868E-04 + 3.350006E+01 9.000000E+01 1 2.069632E-06 -9.003814E+01 -1.377468E-09 -2.069631E-06 + 3.350006E+01 9.000000E+01 2 4.238506E+01 8.994249E+01 4.254586E-02 4.238503E+01 + 3.350006E+01 9.000000E+01 3 1.928446E+02 2.226968E-01 1.928431E+02 7.495451E-01 + 3.350006E+01 9.000000E+01 4 1.381679E+02 8.994263E+01 1.383440E-01 1.381678E+02 + 3.350006E+01 9.000000E+01 5 9.579137E-05 -8.999342E+01 1.098708E-08 -9.579137E-05 + 3.350006E+01 9.000000E+01 6 4.028387E-06 1.799997E+02 -4.028387E-06 2.289907E-11 + 3.360006E+01 0.000000E+00 1 3.953648E+01 8.994914E+01 3.509463E-02 3.953646E+01 + 3.360006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.360006E+01 0.000000E+00 3 1.906935E+02 2.201875E-01 1.906921E+02 7.328328E-01 + 3.360006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.360006E+01 0.000000E+00 5 4.159681E+02 8.994914E+01 3.692213E-01 4.159680E+02 + 3.360006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.360006E+01 3.000000E+01 1 3.432856E+01 8.994914E+01 3.047062E-02 3.432855E+01 + 3.360006E+01 3.000000E+01 2 2.094806E+01 8.994288E+01 2.088508E-02 2.094805E+01 + 3.360006E+01 3.000000E+01 3 1.912510E+02 2.204702E-01 1.912496E+02 7.359189E-01 + 3.360006E+01 3.000000E+01 4 6.776035E+01 8.994259E+01 6.789912E-02 6.776032E+01 + 3.360006E+01 3.000000E+01 5 3.611580E+02 8.994914E+01 3.205728E-01 3.611579E+02 + 3.360006E+01 3.000000E+01 6 4.638676E+01 -4.764366E-04 4.638676E+01 -3.857239E-04 + 3.360006E+01 6.000000E+01 1 1.992280E+01 8.994914E+01 1.768249E-02 1.992279E+01 + 3.360006E+01 6.000000E+01 2 3.649052E+01 8.994288E+01 3.638297E-02 3.649050E+01 + 3.360006E+01 6.000000E+01 3 1.923710E+02 2.210367E-01 1.923696E+02 7.421306E-01 + 3.360006E+01 6.000000E+01 4 1.186326E+02 8.994288E+01 1.182837E-01 1.186326E+02 + 3.360006E+01 6.000000E+01 5 2.095754E+02 8.994914E+01 1.860294E-01 2.095753E+02 + 3.360006E+01 6.000000E+01 6 4.665978E+01 -4.754898E-04 4.665978E+01 -3.872231E-04 + 3.360006E+01 9.000000E+01 1 2.063289E-06 -9.003794E+01 -1.366047E-09 -2.063289E-06 + 3.360006E+01 9.000000E+01 2 4.225586E+01 8.994287E+01 4.213268E-02 4.225583E+01 + 3.360006E+01 9.000000E+01 3 1.929343E+02 2.213204E-01 1.929328E+02 7.452589E-01 + 3.360006E+01 9.000000E+01 4 1.377205E+02 8.994302E+01 1.369766E-01 1.377205E+02 + 3.360006E+01 9.000000E+01 5 9.551140E-05 -8.999348E+01 1.086559E-08 -9.551140E-05 + 3.360006E+01 9.000000E+01 6 4.003303E-06 1.799997E+02 -4.003303E-06 2.246091E-11 + 3.370006E+01 0.000000E+00 1 3.941903E+01 8.994946E+01 3.477030E-02 3.941902E+01 + 3.370006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.370006E+01 0.000000E+00 3 1.907948E+02 2.188378E-01 1.907935E+02 7.287277E-01 + 3.370006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.370006E+01 0.000000E+00 5 4.149079E+02 8.994947E+01 3.659608E-01 4.149077E+02 + 3.370006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.370006E+01 3.000000E+01 1 3.422599E+01 8.994947E+01 3.018847E-02 3.422598E+01 + 3.370006E+01 3.000000E+01 2 2.088553E+01 8.994326E+01 2.068408E-02 2.088552E+01 + 3.370006E+01 3.000000E+01 3 1.913493E+02 2.191173E-01 1.913479E+02 7.317789E-01 + 3.370006E+01 3.000000E+01 4 6.754848E+01 8.994297E+01 6.723402E-02 6.754845E+01 + 3.370006E+01 3.000000E+01 5 3.602292E+02 8.994947E+01 3.177367E-01 3.602291E+02 + 3.370006E+01 3.000000E+01 6 4.610175E+01 -4.702416E-04 4.610175E+01 -3.783692E-04 + 3.370006E+01 6.000000E+01 1 1.986265E+01 8.994947E+01 1.751814E-02 1.986264E+01 + 3.370006E+01 6.000000E+01 2 3.638029E+01 8.994325E+01 3.603162E-02 3.638027E+01 + 3.370006E+01 6.000000E+01 3 1.924628E+02 2.196764E-01 1.924614E+02 7.379153E-01 + 3.370006E+01 6.000000E+01 4 1.182544E+02 8.994325E+01 1.171209E-01 1.182544E+02 + 3.370006E+01 6.000000E+01 5 2.090304E+02 8.994946E+01 1.843785E-01 2.090303E+02 + 3.370006E+01 6.000000E+01 6 4.637133E+01 -4.693134E-04 4.637133E+01 -3.798305E-04 + 3.370006E+01 9.000000E+01 1 2.056978E-06 -9.003773E+01 -1.354751E-09 -2.056977E-06 + 3.370006E+01 9.000000E+01 2 4.212744E+01 8.994325E+01 4.172492E-02 4.212742E+01 + 3.370006E+01 9.000000E+01 3 1.930227E+02 2.199568E-01 1.930213E+02 7.410066E-01 + 3.370006E+01 9.000000E+01 4 1.372767E+02 8.994340E+01 1.356272E-01 1.372766E+02 + 3.370006E+01 9.000000E+01 5 9.523307E-05 -8.999354E+01 1.074594E-08 -9.523307E-05 + 3.370006E+01 9.000000E+01 6 3.978461E-06 1.799997E+02 -3.978461E-06 2.203259E-11 + 3.380006E+01 0.000000E+00 1 3.930218E+01 8.994978E+01 3.444978E-02 3.930216E+01 + 3.380006E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.380006E+01 0.000000E+00 3 1.908964E+02 2.174999E-01 1.908950E+02 7.246583E-01 + 3.380006E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.380006E+01 0.000000E+00 5 4.138488E+02 8.994978E+01 3.627357E-01 4.138487E+02 + 3.380006E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.380006E+01 3.000000E+01 1 3.412407E+01 8.994978E+01 2.990977E-02 3.412405E+01 + 3.380006E+01 3.000000E+01 2 2.082336E+01 8.994363E+01 2.048573E-02 2.082335E+01 + 3.380006E+01 3.000000E+01 3 1.914473E+02 2.177773E-01 1.914459E+02 7.276760E-01 + 3.380006E+01 3.000000E+01 4 6.733807E+01 8.994335E+01 6.657772E-02 6.733804E+01 + 3.380006E+01 3.000000E+01 5 3.593055E+02 8.994978E+01 3.149348E-01 3.593054E+02 + 3.380006E+01 3.000000E+01 6 4.581934E+01 -4.641483E-04 4.581934E+01 -3.711787E-04 + 3.380006E+01 6.000000E+01 1 1.980288E+01 8.994979E+01 1.735591E-02 1.980288E+01 + 3.380006E+01 6.000000E+01 2 3.627076E+01 8.994363E+01 3.568467E-02 3.627074E+01 + 3.380006E+01 6.000000E+01 3 1.925543E+02 2.183298E-01 1.925529E+02 7.337406E-01 + 3.380006E+01 6.000000E+01 4 1.178778E+02 8.994363E+01 1.159738E-01 1.178778E+02 + 3.380006E+01 6.000000E+01 5 2.084864E+02 8.994978E+01 1.827458E-01 2.084863E+02 + 3.380006E+01 6.000000E+01 6 4.608560E+01 -4.632380E-04 4.608560E+01 -3.726034E-04 + 3.380006E+01 9.000000E+01 1 2.050707E-06 -9.003754E+01 -1.343575E-09 -2.050706E-06 + 3.380006E+01 9.000000E+01 2 4.199990E+01 8.994363E+01 4.132249E-02 4.199989E+01 + 3.380006E+01 9.000000E+01 3 1.931105E+02 2.186055E-01 1.931091E+02 7.367893E-01 + 3.380006E+01 9.000000E+01 4 1.368353E+02 8.994377E+01 1.342966E-01 1.368352E+02 + 3.380006E+01 9.000000E+01 5 9.495654E-05 -8.999359E+01 1.062802E-08 -9.495654E-05 + 3.380006E+01 9.000000E+01 6 3.953850E-06 1.799997E+02 -3.953850E-06 2.161383E-11 + 3.390005E+01 0.000000E+00 1 3.918617E+01 8.995010E+01 3.413335E-02 3.918615E+01 + 3.390005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.390005E+01 0.000000E+00 3 1.909960E+02 2.161779E-01 1.909947E+02 7.206295E-01 + 3.390005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.390005E+01 0.000000E+00 5 4.127961E+02 8.995010E+01 3.595535E-01 4.127960E+02 + 3.390005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.390005E+01 3.000000E+01 1 3.402280E+01 8.995010E+01 2.963470E-02 3.402279E+01 + 3.390005E+01 3.000000E+01 2 2.076159E+01 8.994401E+01 2.028989E-02 2.076159E+01 + 3.390005E+01 3.000000E+01 3 1.915440E+02 2.164503E-01 1.915426E+02 7.236077E-01 + 3.390005E+01 3.000000E+01 4 6.712875E+01 8.994373E+01 6.593039E-02 6.712872E+01 + 3.390005E+01 3.000000E+01 5 3.583869E+02 8.995010E+01 3.121656E-01 3.583867E+02 + 3.390005E+01 3.000000E+01 6 4.553960E+01 -4.581544E-04 4.553960E+01 -3.641484E-04 + 3.390005E+01 6.000000E+01 1 1.974346E+01 8.995010E+01 1.719568E-02 1.974345E+01 + 3.390005E+01 6.000000E+01 2 3.616187E+01 8.994400E+01 3.534235E-02 3.616185E+01 + 3.390005E+01 6.000000E+01 3 1.926449E+02 2.169954E-01 1.926435E+02 7.295989E-01 + 3.390005E+01 6.000000E+01 4 1.175042E+02 8.994400E+01 1.148419E-01 1.175042E+02 + 3.390005E+01 6.000000E+01 5 2.079469E+02 8.995010E+01 1.811315E-01 2.079469E+02 + 3.390005E+01 6.000000E+01 6 4.580251E+01 -4.572622E-04 4.580251E+01 -3.655375E-04 + 3.390005E+01 9.000000E+01 1 2.044483E-06 -9.003735E+01 -1.332509E-09 -2.044482E-06 + 3.390005E+01 9.000000E+01 2 4.187303E+01 8.994400E+01 4.092541E-02 4.187301E+01 + 3.390005E+01 9.000000E+01 3 1.931985E+02 2.172666E-01 1.931971E+02 7.326102E-01 + 3.390005E+01 9.000000E+01 4 1.363971E+02 8.994414E+01 1.329831E-01 1.363971E+02 + 3.390005E+01 9.000000E+01 5 9.468116E-05 -8.999364E+01 1.051181E-08 -9.468116E-05 + 3.390005E+01 9.000000E+01 6 3.929469E-06 1.799997E+02 -3.929469E-06 2.120445E-11 + 3.400005E+01 0.000000E+00 1 3.907083E+01 8.995040E+01 3.382083E-02 3.907082E+01 + 3.400005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.400005E+01 0.000000E+00 3 1.910952E+02 2.148654E-01 1.910939E+02 7.166262E-01 + 3.400005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.400005E+01 0.000000E+00 5 4.117466E+02 8.995041E+01 3.564029E-01 4.117465E+02 + 3.400005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.400005E+01 3.000000E+01 1 3.392203E+01 8.995040E+01 2.936275E-02 3.392202E+01 + 3.400005E+01 3.000000E+01 2 2.070027E+01 8.994438E+01 2.009663E-02 2.070026E+01 + 3.400005E+01 3.000000E+01 3 1.916397E+02 2.151350E-01 1.916384E+02 7.195699E-01 + 3.400005E+01 3.000000E+01 4 6.692104E+01 8.994410E+01 6.529147E-02 6.692101E+01 + 3.400005E+01 3.000000E+01 5 3.574666E+02 8.995040E+01 3.094259E-01 3.574665E+02 + 3.400005E+01 3.000000E+01 6 4.526242E+01 -4.522591E-04 4.526242E+01 -3.572749E-04 + 3.400005E+01 6.000000E+01 1 1.968440E+01 8.995041E+01 1.703744E-02 1.968439E+01 + 3.400005E+01 6.000000E+01 2 3.605368E+01 8.994437E+01 3.500450E-02 3.605367E+01 + 3.400005E+01 6.000000E+01 3 1.927338E+02 2.156741E-01 1.927324E+02 7.254912E-01 + 3.400005E+01 6.000000E+01 4 1.171330E+02 8.994437E+01 1.137248E-01 1.171329E+02 + 3.400005E+01 6.000000E+01 5 2.074086E+02 8.995040E+01 1.795366E-01 2.074086E+02 + 3.400005E+01 6.000000E+01 6 4.552207E+01 -4.513839E-04 4.552207E+01 -3.586290E-04 + 3.400005E+01 9.000000E+01 1 2.038288E-06 -9.003716E+01 -1.321565E-09 -2.038288E-06 + 3.400005E+01 9.000000E+01 2 4.174704E+01 8.994437E+01 4.053334E-02 4.174702E+01 + 3.400005E+01 9.000000E+01 3 1.932842E+02 2.159432E-01 1.932829E+02 7.284712E-01 + 3.400005E+01 9.000000E+01 4 1.359620E+02 8.994451E+01 1.316872E-01 1.359619E+02 + 3.400005E+01 9.000000E+01 5 9.440799E-05 -8.999369E+01 1.039739E-08 -9.440799E-05 + 3.400005E+01 9.000000E+01 6 3.905322E-06 1.799997E+02 -3.905322E-06 2.080413E-11 + 3.410005E+01 0.000000E+00 1 3.895607E+01 8.995071E+01 3.351206E-02 3.895606E+01 + 3.410005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.410005E+01 0.000000E+00 3 1.911934E+02 2.135657E-01 1.911921E+02 7.126575E-01 + 3.410005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.410005E+01 0.000000E+00 5 4.107012E+02 8.995071E+01 3.532951E-01 4.107010E+02 + 3.410005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.410005E+01 3.000000E+01 1 3.382191E+01 8.995071E+01 2.909433E-02 3.382190E+01 + 3.410005E+01 3.000000E+01 2 2.063913E+01 8.994474E+01 1.990585E-02 2.063912E+01 + 3.410005E+01 3.000000E+01 3 1.917356E+02 2.138311E-01 1.917343E+02 7.155666E-01 + 3.410005E+01 3.000000E+01 4 6.671435E+01 8.994447E+01 6.466094E-02 6.671432E+01 + 3.410005E+01 3.000000E+01 5 3.565597E+02 8.995071E+01 3.067199E-01 3.565596E+02 + 3.410005E+01 3.000000E+01 6 4.498774E+01 -4.464596E-04 4.498774E+01 -3.505531E-04 + 3.410005E+01 6.000000E+01 1 1.962566E+01 8.995071E+01 1.688116E-02 1.962565E+01 + 3.410005E+01 6.000000E+01 2 3.594605E+01 8.994474E+01 3.467092E-02 3.594604E+01 + 3.410005E+01 6.000000E+01 3 1.928227E+02 2.143649E-01 1.928214E+02 7.214200E-01 + 3.410005E+01 6.000000E+01 4 1.167640E+02 8.994474E+01 1.126223E-01 1.167640E+02 + 3.410005E+01 6.000000E+01 5 2.068734E+02 8.995071E+01 1.779629E-01 2.068734E+02 + 3.410005E+01 6.000000E+01 6 4.524427E+01 -4.456003E-04 4.524427E+01 -3.518733E-04 + 3.410005E+01 9.000000E+01 1 2.032130E-06 -9.003696E+01 -1.310731E-09 -2.032130E-06 + 3.410005E+01 9.000000E+01 2 4.162177E+01 8.994473E+01 4.014638E-02 4.162175E+01 + 3.410005E+01 9.000000E+01 3 1.933700E+02 2.146287E-01 1.933686E+02 7.243579E-01 + 3.410005E+01 9.000000E+01 4 1.355293E+02 8.994487E+01 1.304089E-01 1.355293E+02 + 3.410005E+01 9.000000E+01 5 9.413626E-05 -8.999374E+01 1.028458E-08 -9.413626E-05 + 3.410005E+01 9.000000E+01 6 3.881387E-06 1.799997E+02 -3.881387E-06 2.041273E-11 + 3.420005E+01 0.000000E+00 1 3.884214E+01 8.995102E+01 3.320713E-02 3.884213E+01 + 3.420005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.420005E+01 0.000000E+00 3 1.912910E+02 2.122780E-01 1.912897E+02 7.087221E-01 + 3.420005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.420005E+01 0.000000E+00 5 4.096624E+02 8.995102E+01 3.502164E-01 4.096622E+02 + 3.420005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.420005E+01 3.000000E+01 1 3.372246E+01 8.995102E+01 2.882922E-02 3.372245E+01 + 3.420005E+01 3.000000E+01 2 2.057844E+01 8.994510E+01 1.971754E-02 2.057843E+01 + 3.420005E+01 3.000000E+01 3 1.918292E+02 2.125403E-01 1.918279E+02 7.115940E-01 + 3.420005E+01 3.000000E+01 4 6.650908E+01 8.994484E+01 6.403850E-02 6.650905E+01 + 3.420005E+01 3.000000E+01 5 3.556488E+02 8.995102E+01 3.040474E-01 3.556487E+02 + 3.420005E+01 3.000000E+01 6 4.471568E+01 -4.407538E-04 4.471568E+01 -3.439801E-04 + 3.420005E+01 6.000000E+01 1 1.956731E+01 8.995103E+01 1.672681E-02 1.956731E+01 + 3.420005E+01 6.000000E+01 2 3.583922E+01 8.994510E+01 3.434163E-02 3.583920E+01 + 3.420005E+01 6.000000E+01 3 1.929110E+02 2.130659E-01 1.929097E+02 7.173767E-01 + 3.420005E+01 6.000000E+01 4 1.163975E+02 8.994510E+01 1.115347E-01 1.163975E+02 + 3.420005E+01 6.000000E+01 5 2.063403E+02 8.995102E+01 1.764052E-01 2.063403E+02 + 3.420005E+01 6.000000E+01 6 4.496900E+01 -4.399107E-04 4.496900E+01 -3.452670E-04 + 3.420005E+01 9.000000E+01 1 2.026014E-06 -9.003677E+01 -1.300017E-09 -2.026014E-06 + 3.420005E+01 9.000000E+01 2 4.149716E+01 8.994510E+01 3.976450E-02 4.149714E+01 + 3.420005E+01 9.000000E+01 3 1.934550E+02 2.133281E-01 1.934536E+02 7.202849E-01 + 3.420005E+01 9.000000E+01 4 1.350997E+02 8.994523E+01 1.291466E-01 1.350996E+02 + 3.420005E+01 9.000000E+01 5 9.386538E-05 -8.999379E+01 1.017344E-08 -9.386538E-05 + 3.420005E+01 9.000000E+01 6 3.857687E-06 1.799997E+02 -3.857687E-06 2.002991E-11 + 3.430005E+01 0.000000E+00 1 3.872882E+01 8.995132E+01 3.290593E-02 3.872881E+01 + 3.430005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.430005E+01 0.000000E+00 3 1.913871E+02 2.110021E-01 1.913858E+02 7.048159E-01 + 3.430005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.430005E+01 0.000000E+00 5 4.086259E+02 8.995132E+01 3.471771E-01 4.086258E+02 + 3.430005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.430005E+01 3.000000E+01 1 3.362355E+01 8.995132E+01 2.856727E-02 3.362354E+01 + 3.430005E+01 3.000000E+01 2 2.051813E+01 8.994546E+01 1.953158E-02 2.051812E+01 + 3.430005E+01 3.000000E+01 3 1.919223E+02 2.112613E-01 1.919209E+02 7.076553E-01 + 3.430005E+01 3.000000E+01 4 6.630528E+01 8.994520E+01 6.342429E-02 6.630525E+01 + 3.430005E+01 3.000000E+01 5 3.547445E+02 8.995132E+01 3.014019E-01 3.547444E+02 + 3.430005E+01 3.000000E+01 6 4.444604E+01 -4.351407E-04 4.444604E+01 -3.375516E-04 + 3.430005E+01 6.000000E+01 1 1.950934E+01 8.995132E+01 1.657432E-02 1.950933E+01 + 3.430005E+01 6.000000E+01 2 3.573286E+01 8.994546E+01 3.401675E-02 3.573285E+01 + 3.430005E+01 6.000000E+01 3 1.929984E+02 2.117788E-01 1.929971E+02 7.133664E-01 + 3.430005E+01 6.000000E+01 4 1.160334E+02 8.994546E+01 1.104610E-01 1.160334E+02 + 3.430005E+01 6.000000E+01 5 2.058100E+02 8.995132E+01 1.748671E-01 2.058099E+02 + 3.430005E+01 6.000000E+01 6 4.469635E+01 -4.343129E-04 4.469635E+01 -3.388068E-04 + 3.430005E+01 9.000000E+01 1 2.019941E-06 -9.003658E+01 -1.289411E-09 -2.019940E-06 + 3.430005E+01 9.000000E+01 2 4.137342E+01 8.994546E+01 3.938750E-02 4.137340E+01 + 3.430005E+01 9.000000E+01 3 1.935388E+02 2.120385E-01 1.935375E+02 7.162409E-01 + 3.430005E+01 9.000000E+01 4 1.346734E+02 8.994559E+01 1.279012E-01 1.346734E+02 + 3.430005E+01 9.000000E+01 5 9.359654E-05 -8.999384E+01 1.006393E-08 -9.359654E-05 + 3.430005E+01 9.000000E+01 6 3.834203E-06 1.799997E+02 -3.834203E-06 1.965557E-11 + 3.440005E+01 0.000000E+00 1 3.861600E+01 8.995162E+01 3.260842E-02 3.861599E+01 + 3.440005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.440005E+01 0.000000E+00 3 1.914837E+02 2.097367E-01 1.914825E+02 7.009432E-01 + 3.440005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.440005E+01 0.000000E+00 5 4.076013E+02 8.995162E+01 3.441715E-01 4.076011E+02 + 3.440005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.440005E+01 3.000000E+01 1 3.352515E+01 8.995162E+01 2.830854E-02 3.352514E+01 + 3.440005E+01 3.000000E+01 2 2.045809E+01 8.994582E+01 1.934802E-02 2.045808E+01 + 3.440005E+01 3.000000E+01 3 1.920156E+02 2.099940E-01 1.920143E+02 7.037520E-01 + 3.440005E+01 3.000000E+01 4 6.610255E+01 8.994556E+01 6.281795E-02 6.610252E+01 + 3.440005E+01 3.000000E+01 5 3.538477E+02 8.995162E+01 2.987881E-01 3.538476E+02 + 3.440005E+01 3.000000E+01 6 4.417879E+01 -4.296174E-04 4.417879E+01 -3.312631E-04 + 3.440005E+01 6.000000E+01 1 1.945168E+01 8.995162E+01 1.642371E-02 1.945168E+01 + 3.440005E+01 6.000000E+01 2 3.562713E+01 8.994582E+01 3.369583E-02 3.562711E+01 + 3.440005E+01 6.000000E+01 3 1.930847E+02 2.105051E-01 1.930835E+02 7.093930E-01 + 3.440005E+01 6.000000E+01 4 1.156715E+02 8.994582E+01 1.094015E-01 1.156714E+02 + 3.440005E+01 6.000000E+01 5 2.052818E+02 8.995162E+01 1.733446E-01 2.052818E+02 + 3.440005E+01 6.000000E+01 6 4.442604E+01 -4.288058E-04 4.442604E+01 -3.324877E-04 + 3.440005E+01 9.000000E+01 1 2.013890E-06 -9.003638E+01 -1.278914E-09 -2.013890E-06 + 3.440005E+01 9.000000E+01 2 4.125039E+01 8.994582E+01 3.901527E-02 4.125037E+01 + 3.440005E+01 9.000000E+01 3 1.936228E+02 2.107600E-01 1.936215E+02 7.122312E-01 + 3.440005E+01 9.000000E+01 4 1.342484E+02 8.994594E+01 1.266718E-01 1.342483E+02 + 3.440005E+01 9.000000E+01 5 9.332901E-05 -8.999389E+01 9.955983E-09 -9.332901E-05 + 3.440005E+01 9.000000E+01 6 3.810930E-06 1.799997E+02 -3.810930E-06 1.928943E-11 + 3.450005E+01 0.000000E+00 1 3.850412E+01 8.995192E+01 3.231448E-02 3.850410E+01 + 3.450005E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.450005E+01 0.000000E+00 3 1.915782E+02 2.084854E-01 1.915769E+02 6.971048E-01 + 3.450005E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.450005E+01 0.000000E+00 5 4.065757E+02 8.995192E+01 3.412012E-01 4.065756E+02 + 3.450005E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.450005E+01 3.000000E+01 1 3.342742E+01 8.995192E+01 2.805291E-02 3.342741E+01 + 3.450005E+01 3.000000E+01 2 2.039851E+01 8.994617E+01 1.916681E-02 2.039850E+01 + 3.450005E+01 3.000000E+01 3 1.921078E+02 2.087367E-01 1.921066E+02 6.998748E-01 + 3.450005E+01 3.000000E+01 4 6.590118E+01 8.994591E+01 6.221944E-02 6.590115E+01 + 3.450005E+01 3.000000E+01 5 3.529504E+02 8.995192E+01 2.962039E-01 3.529503E+02 + 3.450005E+01 3.000000E+01 6 4.391412E+01 -4.241830E-04 4.391412E+01 -3.251134E-04 + 3.450005E+01 6.000000E+01 1 1.939433E+01 8.995192E+01 1.627497E-02 1.939432E+01 + 3.450005E+01 6.000000E+01 2 3.552214E+01 8.994616E+01 3.337909E-02 3.552212E+01 + 3.450005E+01 6.000000E+01 3 1.931709E+02 2.092436E-01 1.931696E+02 7.054566E-01 + 3.450005E+01 6.000000E+01 4 1.153121E+02 8.994616E+01 1.083552E-01 1.153121E+02 + 3.450005E+01 6.000000E+01 5 2.047556E+02 8.995192E+01 1.718409E-01 2.047555E+02 + 3.450005E+01 6.000000E+01 6 4.415838E+01 -4.233874E-04 4.415838E+01 -3.263085E-04 + 3.450005E+01 9.000000E+01 1 2.007891E-06 -9.003619E+01 -1.268531E-09 -2.007891E-06 + 3.450005E+01 9.000000E+01 2 4.112812E+01 8.994616E+01 3.864783E-02 4.112811E+01 + 3.450005E+01 9.000000E+01 3 1.937057E+02 2.094953E-01 1.937044E+02 7.082606E-01 + 3.450005E+01 9.000000E+01 4 1.338276E+02 8.994629E+01 1.254597E-01 1.338276E+02 + 3.450005E+01 9.000000E+01 5 9.306328E-05 -8.999393E+01 9.849639E-09 -9.306328E-05 + 3.450005E+01 9.000000E+01 6 3.787876E-06 1.799997E+02 -3.787876E-06 1.893127E-11 + 3.460004E+01 0.000000E+00 1 3.839270E+01 8.995221E+01 3.202403E-02 3.839268E+01 + 3.460004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.460004E+01 0.000000E+00 3 1.916720E+02 2.072441E-01 1.916708E+02 6.932938E-01 + 3.460004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.460004E+01 0.000000E+00 5 4.055526E+02 8.995221E+01 3.382632E-01 4.055524E+02 + 3.460004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.460004E+01 3.000000E+01 1 3.333018E+01 8.995221E+01 2.780049E-02 3.333017E+01 + 3.460004E+01 3.000000E+01 2 2.033922E+01 8.994651E+01 1.898784E-02 2.033921E+01 + 3.460004E+01 3.000000E+01 3 1.921990E+02 2.074935E-01 1.921977E+02 6.960364E-01 + 3.460004E+01 3.000000E+01 4 6.570105E+01 8.994626E+01 6.162897E-02 6.570102E+01 + 3.460004E+01 3.000000E+01 5 3.520589E+02 8.995221E+01 2.936520E-01 3.520588E+02 + 3.460004E+01 3.000000E+01 6 4.365172E+01 -4.188360E-04 4.365172E+01 -3.190970E-04 + 3.460004E+01 6.000000E+01 1 1.933741E+01 8.995221E+01 1.612801E-02 1.933740E+01 + 3.460004E+01 6.000000E+01 2 3.541766E+01 8.994651E+01 3.306628E-02 3.541765E+01 + 3.460004E+01 6.000000E+01 3 1.932563E+02 2.079926E-01 1.932550E+02 7.015489E-01 + 3.460004E+01 6.000000E+01 4 1.149547E+02 8.994651E+01 1.073231E-01 1.149546E+02 + 3.460004E+01 6.000000E+01 5 2.042325E+02 8.995221E+01 1.703553E-01 2.042324E+02 + 3.460004E+01 6.000000E+01 6 4.389307E+01 -4.180543E-04 4.389307E+01 -3.202625E-04 + 3.460004E+01 9.000000E+01 1 2.001920E-06 -9.003601E+01 -1.258253E-09 -2.001919E-06 + 3.460004E+01 9.000000E+01 2 4.100655E+01 8.994651E+01 3.828514E-02 4.100653E+01 + 3.460004E+01 9.000000E+01 3 1.937877E+02 2.082420E-01 1.937864E+02 7.043214E-01 + 3.460004E+01 9.000000E+01 4 1.334088E+02 8.994663E+01 1.242620E-01 1.334087E+02 + 3.460004E+01 9.000000E+01 5 9.279925E-05 -8.999399E+01 9.744760E-09 -9.279925E-05 + 3.460004E+01 9.000000E+01 6 3.765038E-06 1.799997E+02 -3.765038E-06 1.858096E-11 + 3.470004E+01 0.000000E+00 1 3.828198E+01 8.995250E+01 3.173710E-02 3.828197E+01 + 3.470004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.470004E+01 0.000000E+00 3 1.917661E+02 2.060119E-01 1.917648E+02 6.895097E-01 + 3.470004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.470004E+01 0.000000E+00 5 4.045352E+02 8.995250E+01 3.353630E-01 4.045350E+02 + 3.470004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.470004E+01 3.000000E+01 1 3.323360E+01 8.995250E+01 2.755093E-02 3.323359E+01 + 3.470004E+01 3.000000E+01 2 2.028024E+01 8.994686E+01 1.881117E-02 2.028024E+01 + 3.470004E+01 3.000000E+01 3 1.922891E+02 2.062576E-01 1.922878E+02 6.922148E-01 + 3.470004E+01 3.000000E+01 4 6.550204E+01 8.994660E+01 6.104593E-02 6.550201E+01 + 3.470004E+01 3.000000E+01 5 3.511710E+02 8.995250E+01 2.911268E-01 3.511709E+02 + 3.470004E+01 3.000000E+01 6 4.339181E+01 -4.135736E-04 4.339181E+01 -3.132117E-04 + 3.470004E+01 6.000000E+01 1 1.928073E+01 8.995251E+01 1.598278E-02 1.928073E+01 + 3.470004E+01 6.000000E+01 2 3.531391E+01 8.994685E+01 3.275752E-02 3.531390E+01 + 3.470004E+01 6.000000E+01 3 1.933406E+02 2.067509E-01 1.933394E+02 6.976652E-01 + 3.470004E+01 6.000000E+01 4 1.145994E+02 8.994685E+01 1.063041E-01 1.145993E+02 + 3.470004E+01 6.000000E+01 5 2.037125E+02 8.995250E+01 1.688858E-01 2.037124E+02 + 3.470004E+01 6.000000E+01 6 4.363018E+01 -4.128074E-04 4.363018E+01 -3.143488E-04 + 3.470004E+01 9.000000E+01 1 1.995988E-06 -9.003583E+01 -1.248082E-09 -1.995987E-06 + 3.470004E+01 9.000000E+01 2 4.088573E+01 8.994685E+01 3.792702E-02 4.088572E+01 + 3.470004E+01 9.000000E+01 3 1.938689E+02 2.069982E-01 1.938677E+02 7.004082E-01 + 3.470004E+01 9.000000E+01 4 1.329931E+02 8.994698E+01 1.230801E-01 1.329930E+02 + 3.470004E+01 9.000000E+01 5 9.253614E-05 -8.999403E+01 9.641385E-09 -9.253614E-05 + 3.470004E+01 9.000000E+01 6 3.742401E-06 1.799997E+02 -3.742401E-06 1.823821E-11 + 3.480004E+01 0.000000E+00 1 3.817182E+01 8.995279E+01 3.145370E-02 3.817181E+01 + 3.480004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.480004E+01 0.000000E+00 3 1.918590E+02 2.047918E-01 1.918578E+02 6.857587E-01 + 3.480004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.480004E+01 0.000000E+00 5 4.035247E+02 8.995280E+01 3.324912E-01 4.035246E+02 + 3.480004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.480004E+01 3.000000E+01 1 3.313750E+01 8.995280E+01 2.730451E-02 3.313749E+01 + 3.480004E+01 3.000000E+01 2 2.022166E+01 8.994720E+01 1.863669E-02 2.022165E+01 + 3.480004E+01 3.000000E+01 3 1.923790E+02 2.050359E-01 1.923777E+02 6.884367E-01 + 3.480004E+01 3.000000E+01 4 6.530428E+01 8.994695E+01 6.047025E-02 6.530425E+01 + 3.480004E+01 3.000000E+01 5 3.502878E+02 8.995280E+01 2.886325E-01 3.502877E+02 + 3.480004E+01 3.000000E+01 6 4.313417E+01 -4.083954E-04 4.313417E+01 -3.074537E-04 + 3.480004E+01 6.000000E+01 1 1.922439E+01 8.995280E+01 1.583939E-02 1.922439E+01 + 3.480004E+01 6.000000E+01 2 3.521078E+01 8.994719E+01 3.245264E-02 3.521076E+01 + 3.480004E+01 6.000000E+01 3 1.934247E+02 2.055226E-01 1.934235E+02 6.938217E-01 + 3.480004E+01 6.000000E+01 4 1.142474E+02 8.994719E+01 1.052982E-01 1.142474E+02 + 3.480004E+01 6.000000E+01 5 2.031938E+02 8.995279E+01 1.674338E-01 2.031937E+02 + 3.480004E+01 6.000000E+01 6 4.336976E+01 -4.076424E-04 4.336976E+01 -3.085629E-04 + 3.480004E+01 9.000000E+01 1 1.990087E-06 -9.003564E+01 -1.238019E-09 -1.990086E-06 + 3.480004E+01 9.000000E+01 2 4.076549E+01 8.994719E+01 3.757337E-02 4.076547E+01 + 3.480004E+01 9.000000E+01 3 1.939492E+02 2.057671E-01 1.939480E+02 6.965309E-01 + 3.480004E+01 9.000000E+01 4 1.325797E+02 8.994732E+01 1.219134E-01 1.325796E+02 + 3.480004E+01 9.000000E+01 5 9.227471E-05 -8.999407E+01 9.539542E-09 -9.227471E-05 + 3.480004E+01 9.000000E+01 6 3.719979E-06 1.799997E+02 -3.719979E-06 1.790291E-11 + 3.490004E+01 0.000000E+00 1 3.806224E+01 8.995307E+01 3.117362E-02 3.806223E+01 + 3.490004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.490004E+01 0.000000E+00 3 1.919511E+02 2.035830E-01 1.919499E+02 6.820379E-01 + 3.490004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.490004E+01 0.000000E+00 5 4.025160E+02 8.995307E+01 3.296574E-01 4.025159E+02 + 3.490004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.490004E+01 3.000000E+01 1 3.304195E+01 8.995307E+01 2.706098E-02 3.304194E+01 + 3.490004E+01 3.000000E+01 2 2.016346E+01 8.994753E+01 1.846446E-02 2.016346E+01 + 3.490004E+01 3.000000E+01 3 1.924683E+02 2.038238E-01 1.924671E+02 6.846845E-01 + 3.490004E+01 3.000000E+01 4 6.510779E+01 8.994729E+01 5.990160E-02 6.510776E+01 + 3.490004E+01 3.000000E+01 5 3.494085E+02 8.995307E+01 2.861628E-01 3.494084E+02 + 3.490004E+01 3.000000E+01 6 4.287885E+01 -4.032986E-04 4.287885E+01 -3.018194E-04 + 3.490004E+01 6.000000E+01 1 1.916846E+01 8.995308E+01 1.569767E-02 1.916845E+01 + 3.490004E+01 6.000000E+01 2 3.510817E+01 8.994753E+01 3.215162E-02 3.510815E+01 + 3.490004E+01 6.000000E+01 3 1.935076E+02 2.043044E-01 1.935064E+02 6.900049E-01 + 3.490004E+01 6.000000E+01 4 1.138965E+02 8.994753E+01 1.043052E-01 1.138964E+02 + 3.490004E+01 6.000000E+01 5 2.026765E+02 8.995307E+01 1.659977E-01 2.026764E+02 + 3.490004E+01 6.000000E+01 6 4.311163E+01 -4.025592E-04 4.311163E+01 -3.029016E-04 + 3.490004E+01 9.000000E+01 1 1.984223E-06 -9.003546E+01 -1.228055E-09 -1.984222E-06 + 3.490004E+01 9.000000E+01 2 4.064616E+01 8.994753E+01 3.722418E-02 4.064615E+01 + 3.490004E+01 9.000000E+01 3 1.940294E+02 2.045455E-01 1.940282E+02 6.926820E-01 + 3.490004E+01 9.000000E+01 4 1.321692E+02 8.994765E+01 1.207615E-01 1.321692E+02 + 3.490004E+01 9.000000E+01 5 9.201452E-05 -8.999413E+01 9.439129E-09 -9.201452E-05 + 3.490004E+01 9.000000E+01 6 3.697755E-06 1.799997E+02 -3.697755E-06 1.757481E-11 + 3.500004E+01 0.000000E+00 1 3.795351E+01 8.995336E+01 3.089688E-02 3.795350E+01 + 3.500004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.500004E+01 0.000000E+00 3 1.920423E+02 2.023840E-01 1.920411E+02 6.783434E-01 + 3.500004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.500004E+01 0.000000E+00 5 4.015163E+02 8.995336E+01 3.268485E-01 4.015162E+02 + 3.500004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.500004E+01 3.000000E+01 1 3.294705E+01 8.995336E+01 2.682038E-02 3.294704E+01 + 3.500004E+01 3.000000E+01 2 2.010550E+01 8.994787E+01 1.829428E-02 2.010549E+01 + 3.500004E+01 3.000000E+01 3 1.925567E+02 2.026219E-01 1.925555E+02 6.809596E-01 + 3.500004E+01 3.000000E+01 4 6.491261E+01 8.994762E+01 5.934080E-02 6.491257E+01 + 3.500004E+01 3.000000E+01 5 3.485332E+02 8.995336E+01 2.837231E-01 3.485331E+02 + 3.500004E+01 3.000000E+01 6 4.262578E+01 -3.982828E-04 4.262578E+01 -2.963066E-04 + 3.500004E+01 6.000000E+01 1 1.911280E+01 8.995336E+01 1.555773E-02 1.911280E+01 + 3.500004E+01 6.000000E+01 2 3.500626E+01 8.994786E+01 3.185429E-02 3.500624E+01 + 3.500004E+01 6.000000E+01 3 1.935907E+02 2.030970E-01 1.935895E+02 6.862218E-01 + 3.500004E+01 6.000000E+01 4 1.135478E+02 8.994786E+01 1.033246E-01 1.135478E+02 + 3.500004E+01 6.000000E+01 5 2.021646E+02 8.995336E+01 1.645771E-01 2.021646E+02 + 3.500004E+01 6.000000E+01 6 4.285572E+01 -3.975577E-04 4.285572E+01 -2.973626E-04 + 3.500004E+01 9.000000E+01 1 1.978392E-06 -9.003528E+01 -1.218199E-09 -1.978391E-06 + 3.500004E+01 9.000000E+01 2 4.052742E+01 8.994786E+01 3.687941E-02 4.052741E+01 + 3.500004E+01 9.000000E+01 3 1.941088E+02 2.033347E-01 1.941076E+02 6.888635E-01 + 3.500004E+01 9.000000E+01 4 1.317611E+02 8.994798E+01 1.196246E-01 1.317610E+02 + 3.500004E+01 9.000000E+01 5 9.175624E-05 -8.999417E+01 9.340133E-09 -9.175624E-05 + 3.500004E+01 9.000000E+01 6 3.675732E-06 1.799997E+02 -3.675732E-06 1.725378E-11 + 3.510004E+01 0.000000E+00 1 3.784522E+01 8.995364E+01 3.062340E-02 3.784521E+01 + 3.510004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.510004E+01 0.000000E+00 3 1.921323E+02 2.011986E-01 1.921311E+02 6.746861E-01 + 3.510004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.510004E+01 0.000000E+00 5 4.005159E+02 8.995364E+01 3.240772E-01 4.005157E+02 + 3.510004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.510004E+01 3.000000E+01 1 3.285258E+01 8.995364E+01 2.658270E-02 3.285257E+01 + 3.510004E+01 3.000000E+01 2 2.004789E+01 8.994820E+01 1.812631E-02 2.004788E+01 + 3.510004E+01 3.000000E+01 3 1.926437E+02 2.014320E-01 1.926425E+02 6.772668E-01 + 3.510004E+01 3.000000E+01 4 6.471822E+01 8.994796E+01 5.878688E-02 6.471820E+01 + 3.510004E+01 3.000000E+01 5 3.476617E+02 8.995364E+01 2.813121E-01 3.476616E+02 + 3.510004E+01 3.000000E+01 6 4.237505E+01 -3.933454E-04 4.237505E+01 -2.909121E-04 + 3.510004E+01 6.000000E+01 1 1.905746E+01 8.995364E+01 1.541935E-02 1.905745E+01 + 3.510004E+01 6.000000E+01 2 3.490485E+01 8.994820E+01 3.156079E-02 3.490484E+01 + 3.510004E+01 6.000000E+01 3 1.936721E+02 2.019015E-01 1.936709E+02 6.824692E-01 + 3.510004E+01 6.000000E+01 4 1.132020E+02 8.994820E+01 1.023572E-01 1.132019E+02 + 3.510004E+01 6.000000E+01 5 2.016539E+02 8.995364E+01 1.631736E-01 2.016539E+02 + 3.510004E+01 6.000000E+01 6 4.260228E+01 -3.926331E-04 4.260228E+01 -2.919424E-04 + 3.510004E+01 9.000000E+01 1 1.972597E-06 -9.003510E+01 -1.208441E-09 -1.972596E-06 + 3.510004E+01 9.000000E+01 2 4.040936E+01 8.994819E+01 3.653902E-02 4.040934E+01 + 3.510004E+01 9.000000E+01 3 1.941877E+02 2.021375E-01 1.941865E+02 6.850861E-01 + 3.510004E+01 9.000000E+01 4 1.313557E+02 8.994831E+01 1.185021E-01 1.313557E+02 + 3.510004E+01 9.000000E+01 5 9.149918E-05 -8.999421E+01 9.242510E-09 -9.149918E-05 + 3.510004E+01 9.000000E+01 6 3.653911E-06 1.799997E+02 -3.653911E-06 1.693964E-11 + 3.520004E+01 0.000000E+00 1 3.773761E+01 8.995391E+01 3.035335E-02 3.773759E+01 + 3.520004E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.520004E+01 0.000000E+00 3 1.922220E+02 2.000209E-01 1.922208E+02 6.710501E-01 + 3.520004E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.520004E+01 0.000000E+00 5 3.995221E+02 8.995392E+01 3.213328E-01 3.995220E+02 + 3.520004E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.520004E+01 3.000000E+01 1 3.275866E+01 8.995392E+01 2.634779E-02 3.275865E+01 + 3.520004E+01 3.000000E+01 2 1.999064E+01 8.994852E+01 1.796036E-02 1.999063E+01 + 3.520004E+01 3.000000E+01 3 1.927310E+02 2.002532E-01 1.927299E+02 6.736085E-01 + 3.520004E+01 3.000000E+01 4 6.452542E+01 8.994829E+01 5.823993E-02 6.452540E+01 + 3.520004E+01 3.000000E+01 5 3.467957E+02 8.995392E+01 2.789291E-01 3.467956E+02 + 3.520004E+01 3.000000E+01 6 4.212649E+01 -3.884865E-04 4.212649E+01 -2.856331E-04 + 3.520004E+01 6.000000E+01 1 1.900245E+01 8.995392E+01 1.528268E-02 1.900244E+01 + 3.520004E+01 6.000000E+01 2 3.480407E+01 8.994852E+01 3.127093E-02 3.480406E+01 + 3.520004E+01 6.000000E+01 3 1.937533E+02 2.007143E-01 1.937521E+02 6.787407E-01 + 3.520004E+01 6.000000E+01 4 1.128584E+02 8.994852E+01 1.014013E-01 1.128583E+02 + 3.520004E+01 6.000000E+01 5 2.011441E+02 8.995391E+01 1.617859E-01 2.011441E+02 + 3.520004E+01 6.000000E+01 6 4.235104E+01 -3.877869E-04 4.235104E+01 -2.866386E-04 + 3.520004E+01 9.000000E+01 1 1.966843E-06 -9.003492E+01 -1.198787E-09 -1.966843E-06 + 3.520004E+01 9.000000E+01 2 4.029213E+01 8.994852E+01 3.620280E-02 4.029211E+01 + 3.520004E+01 9.000000E+01 3 1.942664E+02 2.009482E-01 1.942653E+02 6.813314E-01 + 3.520004E+01 9.000000E+01 4 1.309527E+02 8.994864E+01 1.173940E-01 1.309526E+02 + 3.520004E+01 9.000000E+01 5 9.124355E-05 -8.999426E+01 9.146307E-09 -9.124355E-05 + 3.520004E+01 9.000000E+01 6 3.632280E-06 1.799997E+02 -3.632280E-06 1.663220E-11 + 3.530003E+01 0.000000E+00 1 3.763055E+01 8.995419E+01 3.008623E-02 3.763054E+01 + 3.530003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.530003E+01 0.000000E+00 3 1.923106E+02 1.988533E-01 1.923095E+02 6.674405E-01 + 3.530003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.530003E+01 0.000000E+00 5 3.985317E+02 8.995419E+01 3.186210E-01 3.985316E+02 + 3.530003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.530003E+01 3.000000E+01 1 3.266527E+01 8.995419E+01 2.611567E-02 3.266526E+01 + 3.530003E+01 3.000000E+01 2 1.993369E+01 8.994884E+01 1.779652E-02 1.993368E+01 + 3.530003E+01 3.000000E+01 3 1.928163E+02 1.990832E-01 1.928151E+02 6.699691E-01 + 3.530003E+01 3.000000E+01 4 6.433378E+01 8.994862E+01 5.769991E-02 6.433376E+01 + 3.530003E+01 3.000000E+01 5 3.459283E+02 8.995419E+01 2.765716E-01 3.459282E+02 + 3.530003E+01 3.000000E+01 6 4.188017E+01 -3.837014E-04 4.188017E+01 -2.804653E-04 + 3.530003E+01 6.000000E+01 1 1.894780E+01 8.995419E+01 1.514764E-02 1.894779E+01 + 3.530003E+01 6.000000E+01 2 3.470378E+01 8.994884E+01 3.098455E-02 3.470377E+01 + 3.530003E+01 6.000000E+01 3 1.938325E+02 1.995412E-01 1.938313E+02 6.750494E-01 + 3.530003E+01 6.000000E+01 4 1.125162E+02 8.994884E+01 1.004579E-01 1.125162E+02 + 3.530003E+01 6.000000E+01 5 2.006375E+02 8.995419E+01 1.604136E-01 2.006374E+02 + 3.530003E+01 6.000000E+01 6 4.210201E+01 -3.830161E-04 4.210201E+01 -2.814473E-04 + 3.530003E+01 9.000000E+01 1 1.961117E-06 -9.003475E+01 -1.189225E-09 -1.961117E-06 + 3.530003E+01 9.000000E+01 2 4.017547E+01 8.994884E+01 3.587072E-02 4.017545E+01 + 3.530003E+01 9.000000E+01 3 1.943434E+02 1.997693E-01 1.943422E+02 6.776026E-01 + 3.530003E+01 9.000000E+01 4 1.305525E+02 8.994896E+01 1.162998E-01 1.305525E+02 + 3.530003E+01 9.000000E+01 5 9.098926E-05 -8.999430E+01 9.051415E-09 -9.098926E-05 + 3.530003E+01 9.000000E+01 6 3.610850E-06 1.799997E+02 -3.610850E-06 1.633129E-11 + 3.540003E+01 0.000000E+00 1 3.752418E+01 8.995447E+01 2.982253E-02 3.752417E+01 + 3.540003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.540003E+01 0.000000E+00 3 1.923982E+02 1.976994E-01 1.923971E+02 6.638698E-01 + 3.540003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.540003E+01 0.000000E+00 5 3.975461E+02 8.995447E+01 3.159379E-01 3.975459E+02 + 3.540003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.540003E+01 3.000000E+01 1 3.257248E+01 8.995447E+01 2.588621E-02 3.257247E+01 + 3.540003E+01 3.000000E+01 2 1.987711E+01 8.994917E+01 1.763467E-02 1.987710E+01 + 3.540003E+01 3.000000E+01 3 1.929014E+02 1.979246E-01 1.929002E+02 6.663642E-01 + 3.540003E+01 3.000000E+01 4 6.414345E+01 8.994894E+01 5.716662E-02 6.414342E+01 + 3.540003E+01 3.000000E+01 5 3.450691E+02 8.995447E+01 2.742382E-01 3.450690E+02 + 3.540003E+01 3.000000E+01 6 4.163603E+01 -3.789929E-04 4.163603E+01 -2.754088E-04 + 3.540003E+01 6.000000E+01 1 1.889341E+01 8.995447E+01 1.501421E-02 1.889340E+01 + 3.540003E+01 6.000000E+01 2 3.460426E+01 8.994917E+01 3.070184E-02 3.460424E+01 + 3.540003E+01 6.000000E+01 3 1.939129E+02 1.983769E-01 1.939117E+02 6.713892E-01 + 3.540003E+01 6.000000E+01 4 1.121770E+02 8.994917E+01 9.952672E-02 1.121769E+02 + 3.540003E+01 6.000000E+01 5 2.001317E+02 8.995447E+01 1.590576E-01 2.001316E+02 + 3.540003E+01 6.000000E+01 6 4.185524E+01 -3.783190E-04 4.185524E+01 -2.763665E-04 + 3.540003E+01 9.000000E+01 1 1.955424E-06 -9.003457E+01 -1.179767E-09 -1.955423E-06 + 3.540003E+01 9.000000E+01 2 4.005956E+01 8.994917E+01 3.554284E-02 4.005954E+01 + 3.540003E+01 9.000000E+01 3 1.944197E+02 1.986047E-01 1.944185E+02 6.739168E-01 + 3.540003E+01 9.000000E+01 4 1.301551E+02 8.994928E+01 1.152196E-01 1.301550E+02 + 3.540003E+01 9.000000E+01 5 9.073657E-05 -8.999434E+01 8.957885E-09 -9.073657E-05 + 3.540003E+01 9.000000E+01 6 3.589610E-06 1.799997E+02 -3.589610E-06 1.603677E-11 + 3.550003E+01 0.000000E+00 1 3.741840E+01 8.995473E+01 2.956179E-02 3.741839E+01 + 3.550003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.550003E+01 0.000000E+00 3 1.924855E+02 1.965533E-01 1.924844E+02 6.603207E-01 + 3.550003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.550003E+01 0.000000E+00 5 3.965663E+02 8.995474E+01 3.132882E-01 3.965662E+02 + 3.550003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.550003E+01 3.000000E+01 1 3.248018E+01 8.995474E+01 2.565960E-02 3.248017E+01 + 3.550003E+01 3.000000E+01 2 1.982079E+01 8.994949E+01 1.747475E-02 1.982078E+01 + 3.550003E+01 3.000000E+01 3 1.929865E+02 1.967766E-01 1.929853E+02 6.627911E-01 + 3.550003E+01 3.000000E+01 4 6.395364E+01 8.994926E+01 5.664000E-02 6.395361E+01 + 3.550003E+01 3.000000E+01 5 3.442131E+02 8.995473E+01 2.719341E-01 3.442130E+02 + 3.550003E+01 3.000000E+01 6 4.139398E+01 -3.743564E-04 4.139398E+01 -2.704580E-04 + 3.550003E+01 6.000000E+01 1 1.883936E+01 8.995474E+01 1.488230E-02 1.883935E+01 + 3.550003E+01 6.000000E+01 2 3.450518E+01 8.994949E+01 3.042253E-02 3.450517E+01 + 3.550003E+01 6.000000E+01 3 1.939920E+02 1.972226E-01 1.939909E+02 6.677548E-01 + 3.550003E+01 6.000000E+01 4 1.118389E+02 8.994949E+01 9.860662E-02 1.118388E+02 + 3.550003E+01 6.000000E+01 5 1.996325E+02 8.995473E+01 1.577173E-01 1.996324E+02 + 3.550003E+01 6.000000E+01 6 4.161071E+01 -3.736948E-04 4.161071E+01 -2.713936E-04 + 3.550003E+01 9.000000E+01 1 1.949764E-06 -9.003439E+01 -1.170405E-09 -1.949764E-06 + 3.550003E+01 9.000000E+01 2 3.994423E+01 8.994948E+01 3.521904E-02 3.994421E+01 + 3.550003E+01 9.000000E+01 3 1.944955E+02 1.974477E-01 1.944943E+02 6.702519E-01 + 3.550003E+01 9.000000E+01 4 1.297594E+02 8.994960E+01 1.141529E-01 1.297593E+02 + 3.550003E+01 9.000000E+01 5 9.048496E-05 -8.999439E+01 8.865646E-09 -9.048496E-05 + 3.550003E+01 9.000000E+01 6 3.568554E-06 1.799997E+02 -3.568554E-06 1.574851E-11 + 3.560003E+01 0.000000E+00 1 3.731315E+01 8.995501E+01 2.930408E-02 3.731314E+01 + 3.560003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.560003E+01 0.000000E+00 3 1.925725E+02 1.954165E-01 1.925714E+02 6.567985E-01 + 3.560003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.560003E+01 0.000000E+00 5 3.955910E+02 8.995501E+01 3.106649E-01 3.955909E+02 + 3.560003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.560003E+01 3.000000E+01 1 3.238846E+01 8.995501E+01 2.543555E-02 3.238845E+01 + 3.560003E+01 3.000000E+01 2 1.976484E+01 8.994980E+01 1.731684E-02 1.976483E+01 + 3.560003E+01 3.000000E+01 3 1.930702E+02 1.956372E-01 1.930690E+02 6.592395E-01 + 3.560003E+01 3.000000E+01 4 6.376530E+01 8.994958E+01 5.611995E-02 6.376528E+01 + 3.560003E+01 3.000000E+01 5 3.433607E+02 8.995501E+01 2.696547E-01 3.433606E+02 + 3.560003E+01 3.000000E+01 6 4.115409E+01 -3.697917E-04 4.115409E+01 -2.656119E-04 + 3.560003E+01 6.000000E+01 1 1.878559E+01 8.995501E+01 1.475204E-02 1.878558E+01 + 3.560003E+01 6.000000E+01 2 3.440669E+01 8.994980E+01 3.014669E-02 3.440668E+01 + 3.560003E+01 6.000000E+01 3 1.940701E+02 1.960781E-01 1.940690E+02 6.641473E-01 + 3.560003E+01 6.000000E+01 4 1.115035E+02 8.994980E+01 9.769826E-02 1.115035E+02 + 3.560003E+01 6.000000E+01 5 1.991318E+02 8.995501E+01 1.563908E-01 1.991317E+02 + 3.560003E+01 6.000000E+01 6 4.136828E+01 -3.691419E-04 4.136828E+01 -2.665252E-04 + 3.560003E+01 9.000000E+01 1 1.944139E-06 -9.003423E+01 -1.161135E-09 -1.944139E-06 + 3.560003E+01 9.000000E+01 2 3.982970E+01 8.994980E+01 3.489913E-02 3.982968E+01 + 3.560003E+01 9.000000E+01 3 1.945722E+02 1.962985E-01 1.945710E+02 6.666135E-01 + 3.560003E+01 9.000000E+01 4 1.293665E+02 8.994991E+01 1.130998E-01 1.293664E+02 + 3.560003E+01 9.000000E+01 5 9.023506E-05 -8.999443E+01 8.774662E-09 -9.023506E-05 + 3.560003E+01 9.000000E+01 6 3.547692E-06 1.799997E+02 -3.547692E-06 1.546635E-11 + 3.570003E+01 0.000000E+00 1 3.720853E+01 8.995527E+01 2.904937E-02 3.720852E+01 + 3.570003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.570003E+01 0.000000E+00 3 1.926582E+02 1.942910E-01 1.926571E+02 6.533061E-01 + 3.570003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.570003E+01 0.000000E+00 5 3.946154E+02 8.995527E+01 3.080730E-01 3.946153E+02 + 3.570003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.570003E+01 3.000000E+01 1 3.229712E+01 8.995527E+01 2.521421E-02 3.229711E+01 + 3.570003E+01 3.000000E+01 2 1.970915E+01 8.995012E+01 1.716087E-02 1.970914E+01 + 3.570003E+01 3.000000E+01 3 1.931540E+02 1.945079E-01 1.931529E+02 6.557187E-01 + 3.570003E+01 3.000000E+01 4 6.357809E+01 8.994989E+01 5.560630E-02 6.357807E+01 + 3.570003E+01 3.000000E+01 5 3.425139E+02 8.995527E+01 2.673998E-01 3.425138E+02 + 3.570003E+01 3.000000E+01 6 4.091636E+01 -3.652969E-04 4.091636E+01 -2.608677E-04 + 3.570003E+01 6.000000E+01 1 1.873211E+01 8.995527E+01 1.462321E-02 1.873211E+01 + 3.570003E+01 6.000000E+01 2 3.430878E+01 8.995011E+01 2.987421E-02 3.430877E+01 + 3.570003E+01 6.000000E+01 3 1.941476E+02 1.949451E-01 1.941465E+02 6.605732E-01 + 3.570003E+01 6.000000E+01 4 1.111703E+02 8.995011E+01 9.680121E-02 1.111702E+02 + 3.570003E+01 6.000000E+01 5 1.986332E+02 8.995527E+01 1.550790E-01 1.986331E+02 + 3.570003E+01 6.000000E+01 6 4.112794E+01 -3.646594E-04 4.112794E+01 -2.617591E-04 + 3.570003E+01 9.000000E+01 1 1.938544E-06 -9.003404E+01 -1.151964E-09 -1.938543E-06 + 3.570003E+01 9.000000E+01 2 3.971572E+01 8.995011E+01 3.458322E-02 3.971570E+01 + 3.570003E+01 9.000000E+01 3 1.946469E+02 1.951629E-01 1.946458E+02 6.630120E-01 + 3.570003E+01 9.000000E+01 4 1.289766E+02 8.995022E+01 1.120595E-01 1.289766E+02 + 3.570003E+01 9.000000E+01 5 8.998632E-05 -8.999447E+01 8.684960E-09 -8.998632E-05 + 3.570003E+01 9.000000E+01 6 3.527016E-06 1.799998E+02 -3.527016E-06 1.519010E-11 + 3.580003E+01 0.000000E+00 1 3.710444E+01 8.995554E+01 2.879764E-02 3.710443E+01 + 3.580003E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.580003E+01 0.000000E+00 3 1.927434E+02 1.931735E-01 1.927423E+02 6.498357E-01 + 3.580003E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.580003E+01 0.000000E+00 5 3.936500E+02 8.995554E+01 3.055085E-01 3.936499E+02 + 3.580003E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.580003E+01 3.000000E+01 1 3.220644E+01 8.995554E+01 2.499547E-02 3.220643E+01 + 3.580003E+01 3.000000E+01 2 1.965380E+01 8.995042E+01 1.700681E-02 1.965379E+01 + 3.580003E+01 3.000000E+01 3 1.932356E+02 1.933892E-01 1.932345E+02 6.522228E-01 + 3.580003E+01 3.000000E+01 4 6.339210E+01 8.995020E+01 5.509906E-02 6.339207E+01 + 3.580003E+01 3.000000E+01 5 3.416677E+02 8.995554E+01 2.651704E-01 3.416676E+02 + 3.580003E+01 3.000000E+01 6 4.068060E+01 -3.608723E-04 4.068060E+01 -2.562231E-04 + 3.580003E+01 6.000000E+01 1 1.867904E+01 8.995554E+01 1.449593E-02 1.867904E+01 + 3.580003E+01 6.000000E+01 2 3.421143E+01 8.995042E+01 2.960512E-02 3.421142E+01 + 3.580003E+01 6.000000E+01 3 1.942248E+02 1.938199E-01 1.942237E+02 6.570213E-01 + 3.580003E+01 6.000000E+01 4 1.108390E+02 8.995042E+01 9.591527E-02 1.108389E+02 + 3.580003E+01 6.000000E+01 5 1.981366E+02 8.995554E+01 1.537814E-01 1.981365E+02 + 3.580003E+01 6.000000E+01 6 4.088980E+01 -3.602456E-04 4.088980E+01 -2.570935E-04 + 3.580003E+01 9.000000E+01 1 1.932983E-06 -9.003387E+01 -1.142886E-09 -1.932982E-06 + 3.580003E+01 9.000000E+01 2 3.960241E+01 8.995042E+01 3.427111E-02 3.960239E+01 + 3.580003E+01 9.000000E+01 3 1.947211E+02 1.940352E-01 1.947200E+02 6.594324E-01 + 3.580003E+01 9.000000E+01 4 1.285885E+02 8.995052E+01 1.110324E-01 1.285885E+02 + 3.580003E+01 9.000000E+01 5 8.973895E-05 -8.999451E+01 8.596469E-09 -8.973895E-05 + 3.580003E+01 9.000000E+01 6 3.506517E-06 1.799998E+02 -3.506517E-06 1.491962E-11 + 3.590002E+01 0.000000E+00 1 3.700101E+01 8.995580E+01 2.854883E-02 3.700100E+01 + 3.590002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.590002E+01 0.000000E+00 3 1.928284E+02 1.920665E-01 1.928274E+02 6.463969E-01 + 3.590002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.590002E+01 0.000000E+00 5 3.926839E+02 8.995580E+01 3.029725E-01 3.926838E+02 + 3.590002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.590002E+01 3.000000E+01 1 3.211624E+01 8.995580E+01 2.477914E-02 3.211623E+01 + 3.590002E+01 3.000000E+01 2 1.959876E+01 8.995073E+01 1.685455E-02 1.959876E+01 + 3.590002E+01 3.000000E+01 3 1.933183E+02 1.922779E-01 1.933172E+02 6.487524E-01 + 3.590002E+01 3.000000E+01 4 6.320710E+01 8.995052E+01 5.459804E-02 6.320708E+01 + 3.590002E+01 3.000000E+01 5 3.408278E+02 8.995580E+01 2.629664E-01 3.408277E+02 + 3.590002E+01 3.000000E+01 6 4.044693E+01 -3.565148E-04 4.044693E+01 -2.516752E-04 + 3.590002E+01 6.000000E+01 1 1.862624E+01 8.995580E+01 1.437013E-02 1.862623E+01 + 3.590002E+01 6.000000E+01 2 3.411459E+01 8.995072E+01 2.933923E-02 3.411458E+01 + 3.590002E+01 6.000000E+01 3 1.943020E+02 1.927044E-01 1.943009E+02 6.534997E-01 + 3.590002E+01 6.000000E+01 4 1.105094E+02 8.995072E+01 9.504028E-02 1.105094E+02 + 3.590002E+01 6.000000E+01 5 1.976456E+02 8.995580E+01 1.524990E-01 1.976455E+02 + 3.590002E+01 6.000000E+01 6 4.065371E+01 -3.558997E-04 4.065371E+01 -2.525255E-04 + 3.590002E+01 9.000000E+01 1 1.927459E-06 -9.003371E+01 -1.133897E-09 -1.927459E-06 + 3.590002E+01 9.000000E+01 2 3.948977E+01 8.995072E+01 3.396285E-02 3.948975E+01 + 3.590002E+01 9.000000E+01 3 1.947946E+02 1.929185E-01 1.947935E+02 6.558845E-01 + 3.590002E+01 9.000000E+01 4 1.282025E+02 8.995084E+01 1.100178E-01 1.282025E+02 + 3.590002E+01 9.000000E+01 5 8.949287E-05 -8.999455E+01 8.509219E-09 -8.949287E-05 + 3.590002E+01 9.000000E+01 6 3.486200E-06 1.799998E+02 -3.486200E-06 1.465479E-11 + 3.600002E+01 0.000000E+00 1 3.689823E+01 8.995605E+01 2.830295E-02 3.689822E+01 + 3.600002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.600002E+01 0.000000E+00 3 1.929125E+02 1.909696E-01 1.929114E+02 6.429854E-01 + 3.600002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.600002E+01 0.000000E+00 5 3.917276E+02 8.995605E+01 3.004604E-01 3.917275E+02 + 3.600002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.600002E+01 3.000000E+01 1 3.202650E+01 8.995605E+01 2.456541E-02 3.202649E+01 + 3.600002E+01 3.000000E+01 2 1.954401E+01 8.995103E+01 1.670416E-02 1.954401E+01 + 3.600002E+01 3.000000E+01 3 1.933998E+02 1.911795E-01 1.933987E+02 6.453182E-01 + 3.600002E+01 3.000000E+01 4 6.302334E+01 8.995081E+01 5.410337E-02 6.302332E+01 + 3.600002E+01 3.000000E+01 5 3.399887E+02 8.995605E+01 2.607855E-01 3.399886E+02 + 3.600002E+01 3.000000E+01 6 4.021523E+01 -3.522242E-04 4.021523E+01 -2.472220E-04 + 3.600002E+01 6.000000E+01 1 1.857365E+01 8.995605E+01 1.424583E-02 1.857364E+01 + 3.600002E+01 6.000000E+01 2 3.401836E+01 8.995103E+01 2.907652E-02 3.401834E+01 + 3.600002E+01 6.000000E+01 3 1.943775E+02 1.916006E-01 1.943764E+02 6.500092E-01 + 3.600002E+01 6.000000E+01 4 1.101818E+02 8.995103E+01 9.417623E-02 1.101818E+02 + 3.600002E+01 6.000000E+01 5 1.971542E+02 8.995605E+01 1.512313E-01 1.971541E+02 + 3.600002E+01 6.000000E+01 6 4.041957E+01 -3.516201E-04 4.041957E+01 -2.480520E-04 + 3.600002E+01 9.000000E+01 1 1.921960E-06 -9.003354E+01 -1.125001E-09 -1.921960E-06 + 3.600002E+01 9.000000E+01 2 3.937778E+01 8.995103E+01 3.365833E-02 3.937777E+01 + 3.600002E+01 9.000000E+01 3 1.948680E+02 1.918119E-01 1.948669E+02 6.523678E-01 + 3.600002E+01 9.000000E+01 4 1.278193E+02 8.995113E+01 1.090161E-01 1.278193E+02 + 3.600002E+01 9.000000E+01 5 8.924866E-05 -8.999459E+01 8.423156E-09 -8.924866E-05 + 3.600002E+01 9.000000E+01 6 3.466062E-06 1.799998E+02 -3.466062E-06 1.439546E-11 + 3.610002E+01 0.000000E+00 1 3.679582E+01 8.995631E+01 2.805987E-02 3.679581E+01 + 3.610002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.610002E+01 0.000000E+00 3 1.929950E+02 1.898817E-01 1.929939E+02 6.395960E-01 + 3.610002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.610002E+01 0.000000E+00 5 3.907667E+02 8.995631E+01 2.979841E-01 3.907665E+02 + 3.610002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.610002E+01 3.000000E+01 1 3.193724E+01 8.995631E+01 2.435412E-02 3.193723E+01 + 3.610002E+01 3.000000E+01 2 1.948962E+01 8.995133E+01 1.655562E-02 1.948961E+01 + 3.610002E+01 3.000000E+01 3 1.934799E+02 1.900889E-01 1.934788E+02 6.419027E-01 + 3.610002E+01 3.000000E+01 4 6.284051E+01 8.995112E+01 5.361466E-02 6.284049E+01 + 3.610002E+01 3.000000E+01 5 3.391558E+02 8.995631E+01 2.586276E-01 3.391557E+02 + 3.610002E+01 3.000000E+01 6 3.998563E+01 -3.479987E-04 3.998563E+01 -2.428617E-04 + 3.610002E+01 6.000000E+01 1 1.852148E+01 8.995631E+01 1.412293E-02 1.852147E+01 + 3.610002E+01 6.000000E+01 2 3.392264E+01 8.995133E+01 2.881715E-02 3.392263E+01 + 3.610002E+01 6.000000E+01 3 1.944521E+02 1.905053E-01 1.944511E+02 6.465414E-01 + 3.610002E+01 6.000000E+01 4 1.098569E+02 8.995133E+01 9.332321E-02 1.098569E+02 + 3.610002E+01 6.000000E+01 5 1.966663E+02 8.995631E+01 1.499770E-01 1.966662E+02 + 3.610002E+01 6.000000E+01 6 4.018764E+01 -3.474052E-04 4.018764E+01 -2.436724E-04 + 3.610002E+01 9.000000E+01 1 1.916497E-06 -9.003337E+01 -1.116193E-09 -1.916497E-06 + 3.610002E+01 9.000000E+01 2 3.926650E+01 8.995132E+01 3.335751E-02 3.926648E+01 + 3.610002E+01 9.000000E+01 3 1.949404E+02 1.907122E-01 1.949393E+02 6.488689E-01 + 3.610002E+01 9.000000E+01 4 1.274387E+02 8.995143E+01 1.080264E-01 1.274386E+02 + 3.610002E+01 9.000000E+01 5 8.900501E-05 -8.999464E+01 8.338271E-09 -8.900501E-05 + 3.610002E+01 9.000000E+01 6 3.446104E-06 1.799998E+02 -3.446104E-06 1.414156E-11 + 3.620002E+01 0.000000E+00 1 3.669408E+01 8.995657E+01 2.781959E-02 3.669407E+01 + 3.620002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.620002E+01 0.000000E+00 3 1.930782E+02 1.888036E-01 1.930771E+02 6.362386E-01 + 3.620002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.620002E+01 0.000000E+00 5 3.898209E+02 8.995657E+01 2.955300E-01 3.898207E+02 + 3.620002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.620002E+01 3.000000E+01 1 3.184851E+01 8.995657E+01 2.414526E-02 3.184850E+01 + 3.620002E+01 3.000000E+01 2 1.943553E+01 8.995162E+01 1.640883E-02 1.943553E+01 + 3.620002E+01 3.000000E+01 3 1.935594E+02 1.890092E-01 1.935584E+02 6.385192E-01 + 3.620002E+01 3.000000E+01 4 6.265878E+01 8.995142E+01 5.313190E-02 6.265875E+01 + 3.620002E+01 3.000000E+01 5 3.383251E+02 8.995657E+01 2.564960E-01 3.383250E+02 + 3.620002E+01 3.000000E+01 6 3.975798E+01 -3.438369E-04 3.975798E+01 -2.385911E-04 + 3.620002E+01 6.000000E+01 1 1.846953E+01 8.995657E+01 1.400147E-02 1.846952E+01 + 3.620002E+01 6.000000E+01 2 3.382750E+01 8.995162E+01 2.856081E-02 3.382749E+01 + 3.620002E+01 6.000000E+01 3 1.945269E+02 1.894189E-01 1.945258E+02 6.431016E-01 + 3.620002E+01 6.000000E+01 4 1.095331E+02 8.995162E+01 9.247953E-02 1.095331E+02 + 3.620002E+01 6.000000E+01 5 1.961805E+02 8.995657E+01 1.487358E-01 1.961804E+02 + 3.620002E+01 6.000000E+01 6 3.995770E+01 -3.432540E-04 3.995770E+01 -2.393830E-04 + 3.620002E+01 9.000000E+01 1 1.911062E-06 -9.003320E+01 -1.107475E-09 -1.911062E-06 + 3.620002E+01 9.000000E+01 2 3.915574E+01 8.995162E+01 3.306032E-02 3.915572E+01 + 3.620002E+01 9.000000E+01 3 1.950125E+02 1.896253E-01 1.950114E+02 6.454095E-01 + 3.620002E+01 9.000000E+01 4 1.270602E+02 8.995173E+01 1.070489E-01 1.270602E+02 + 3.620002E+01 9.000000E+01 5 8.876305E-05 -8.999467E+01 8.254527E-09 -8.876305E-05 + 3.620002E+01 9.000000E+01 6 3.426316E-06 1.799998E+02 -3.426316E-06 1.389287E-11 + 3.630002E+01 0.000000E+00 1 3.659297E+01 8.995682E+01 2.758211E-02 3.659296E+01 + 3.630002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.630002E+01 0.000000E+00 3 1.931599E+02 1.877341E-01 1.931589E+02 6.329024E-01 + 3.630002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.630002E+01 0.000000E+00 5 3.888706E+02 8.995682E+01 2.931029E-01 3.888705E+02 + 3.630002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.630002E+01 3.000000E+01 1 3.176025E+01 8.995682E+01 2.393882E-02 3.176024E+01 + 3.630002E+01 3.000000E+01 2 1.938172E+01 8.995193E+01 1.626377E-02 1.938171E+01 + 3.630002E+01 3.000000E+01 3 1.936391E+02 1.879366E-01 1.936380E+02 6.351566E-01 + 3.630002E+01 3.000000E+01 4 6.247813E+01 8.995171E+01 5.265464E-02 6.247811E+01 + 3.630002E+01 3.000000E+01 5 3.375006E+02 8.995682E+01 2.543879E-01 3.375005E+02 + 3.630002E+01 3.000000E+01 6 3.953231E+01 -3.397380E-04 3.953231E+01 -2.344087E-04 + 3.630002E+01 6.000000E+01 1 1.841787E+01 8.995682E+01 1.388142E-02 1.841787E+01 + 3.630002E+01 6.000000E+01 2 3.373294E+01 8.995192E+01 2.830754E-02 3.373293E+01 + 3.630002E+01 6.000000E+01 3 1.946010E+02 1.883430E-01 1.946000E+02 6.396926E-01 + 3.630002E+01 6.000000E+01 4 1.092118E+02 8.995192E+01 9.164707E-02 1.092118E+02 + 3.630002E+01 6.000000E+01 5 1.956963E+02 8.995682E+01 1.475096E-01 1.956962E+02 + 3.630002E+01 6.000000E+01 6 3.972966E+01 -3.391659E-04 3.972966E+01 -2.351822E-04 + 3.630002E+01 9.000000E+01 1 1.905662E-06 -9.003304E+01 -1.098845E-09 -1.905662E-06 + 3.630002E+01 9.000000E+01 2 3.904569E+01 8.995192E+01 3.276663E-02 3.904568E+01 + 3.630002E+01 9.000000E+01 3 1.950837E+02 1.885462E-01 1.950827E+02 6.419712E-01 + 3.630002E+01 9.000000E+01 4 1.266842E+02 8.995202E+01 1.060835E-01 1.266842E+02 + 3.630002E+01 9.000000E+01 5 8.852229E-05 -8.999471E+01 8.171919E-09 -8.852229E-05 + 3.630002E+01 9.000000E+01 6 3.406700E-06 1.799998E+02 -3.406700E-06 1.364934E-11 + 3.640002E+01 0.000000E+00 1 3.649230E+01 8.995706E+01 2.734727E-02 3.649229E+01 + 3.640002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.640002E+01 0.000000E+00 3 1.932409E+02 1.866754E-01 1.932399E+02 6.295972E-01 + 3.640002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.640002E+01 0.000000E+00 5 3.879283E+02 8.995706E+01 2.907011E-01 3.879281E+02 + 3.640002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.640002E+01 3.000000E+01 1 3.167256E+01 8.995706E+01 2.373479E-02 3.167255E+01 + 3.640002E+01 3.000000E+01 2 1.932821E+01 8.995221E+01 1.612047E-02 1.932820E+01 + 3.640002E+01 3.000000E+01 3 1.937179E+02 1.868748E-01 1.937168E+02 6.318254E-01 + 3.640002E+01 3.000000E+01 4 6.229844E+01 8.995201E+01 5.218397E-02 6.229842E+01 + 3.640002E+01 3.000000E+01 5 3.366772E+02 8.995706E+01 2.522999E-01 3.366771E+02 + 3.640002E+01 3.000000E+01 6 3.930856E+01 -3.357013E-04 3.930856E+01 -2.303125E-04 + 3.640002E+01 6.000000E+01 1 1.836656E+01 8.995707E+01 1.376274E-02 1.836655E+01 + 3.640002E+01 6.000000E+01 2 3.363881E+01 8.995221E+01 2.805732E-02 3.363880E+01 + 3.640002E+01 6.000000E+01 3 1.946739E+02 1.872777E-01 1.946728E+02 6.363124E-01 + 3.640002E+01 6.000000E+01 4 1.088920E+02 8.995221E+01 9.082424E-02 1.088919E+02 + 3.640002E+01 6.000000E+01 5 1.952157E+02 8.995706E+01 1.462976E-01 1.952156E+02 + 3.640002E+01 6.000000E+01 6 3.950373E+01 -3.351382E-04 3.950373E+01 -2.310678E-04 + 3.640002E+01 9.000000E+01 1 1.900292E-06 -9.003288E+01 -1.090306E-09 -1.900291E-06 + 3.640002E+01 9.000000E+01 2 3.893615E+01 8.995221E+01 3.247654E-02 3.893613E+01 + 3.640002E+01 9.000000E+01 3 1.951549E+02 1.874767E-01 1.951539E+02 6.385625E-01 + 3.640002E+01 9.000000E+01 4 1.263099E+02 8.995232E+01 1.051301E-01 1.263099E+02 + 3.640002E+01 9.000000E+01 5 8.828314E-05 -8.999475E+01 8.090429E-09 -8.828314E-05 + 3.640002E+01 9.000000E+01 6 3.387258E-06 1.799998E+02 -3.387258E-06 1.341080E-11 + 3.650002E+01 0.000000E+00 1 3.639219E+01 8.995731E+01 2.711521E-02 3.639218E+01 + 3.650002E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.650002E+01 0.000000E+00 3 1.933211E+02 1.856236E-01 1.933201E+02 6.263095E-01 + 3.650002E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.650002E+01 0.000000E+00 5 3.869905E+02 8.995731E+01 2.883295E-01 3.869904E+02 + 3.650002E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.650002E+01 3.000000E+01 1 3.158527E+01 8.995731E+01 2.353300E-02 3.158526E+01 + 3.650002E+01 3.000000E+01 2 1.927492E+01 8.995251E+01 1.597885E-02 1.927491E+01 + 3.650002E+01 3.000000E+01 3 1.937955E+02 1.858225E-01 1.937944E+02 6.285192E-01 + 3.650002E+01 3.000000E+01 4 6.212008E+01 8.995230E+01 5.171850E-02 6.212006E+01 + 3.650002E+01 3.000000E+01 5 3.358566E+02 8.995731E+01 2.502373E-01 3.358565E+02 + 3.650002E+01 3.000000E+01 6 3.908673E+01 -3.317248E-04 3.908673E+01 -2.263001E-04 + 3.650002E+01 6.000000E+01 1 1.831544E+01 8.995731E+01 1.364543E-02 1.831544E+01 + 3.650002E+01 6.000000E+01 2 3.354522E+01 8.995250E+01 2.781012E-02 3.354521E+01 + 3.650002E+01 6.000000E+01 3 1.947467E+02 1.862186E-01 1.947456E+02 6.329504E-01 + 3.650002E+01 6.000000E+01 4 1.085748E+02 8.995250E+01 9.001180E-02 1.085747E+02 + 3.650002E+01 6.000000E+01 5 1.947344E+02 8.995731E+01 1.450961E-01 1.947343E+02 + 3.650002E+01 6.000000E+01 6 3.927964E+01 -3.311723E-04 3.927964E+01 -2.270382E-04 + 3.650002E+01 9.000000E+01 1 1.894949E-06 -9.003271E+01 -1.081844E-09 -1.894949E-06 + 3.650002E+01 9.000000E+01 2 3.882741E+01 8.995250E+01 3.218987E-02 3.882740E+01 + 3.650002E+01 9.000000E+01 3 1.952245E+02 1.864177E-01 1.952235E+02 6.351821E-01 + 3.650002E+01 9.000000E+01 4 1.259385E+02 8.995260E+01 1.041880E-01 1.259385E+02 + 3.650002E+01 9.000000E+01 5 8.804460E-05 -8.999478E+01 8.010020E-09 -8.804460E-05 + 3.650002E+01 9.000000E+01 6 3.367978E-06 1.799998E+02 -3.367978E-06 1.317715E-11 + 3.660001E+01 0.000000E+00 1 3.629268E+01 8.995756E+01 2.688573E-02 3.629267E+01 + 3.660001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.660001E+01 0.000000E+00 3 1.934017E+02 1.845804E-01 1.934007E+02 6.230494E-01 + 3.660001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.660001E+01 0.000000E+00 5 3.860558E+02 8.995756E+01 2.859814E-01 3.860557E+02 + 3.660001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.660001E+01 3.000000E+01 1 3.149850E+01 8.995756E+01 2.333347E-02 3.149849E+01 + 3.660001E+01 3.000000E+01 2 1.922201E+01 8.995279E+01 1.583892E-02 1.922200E+01 + 3.660001E+01 3.000000E+01 3 1.938728E+02 1.847774E-01 1.938718E+02 6.252338E-01 + 3.660001E+01 3.000000E+01 4 6.194261E+01 8.995259E+01 5.125874E-02 6.194259E+01 + 3.660001E+01 3.000000E+01 5 3.350448E+02 8.995756E+01 2.481959E-01 3.350447E+02 + 3.660001E+01 3.000000E+01 6 3.886675E+01 -3.278083E-04 3.886675E+01 -2.223697E-04 + 3.660001E+01 6.000000E+01 1 1.826464E+01 8.995756E+01 1.352943E-02 1.826464E+01 + 3.660001E+01 6.000000E+01 2 3.345223E+01 8.995279E+01 2.756577E-02 3.345222E+01 + 3.660001E+01 6.000000E+01 3 1.948195E+02 1.851693E-01 1.948185E+02 6.296191E-01 + 3.660001E+01 6.000000E+01 4 1.082585E+02 8.995279E+01 8.920918E-02 1.082584E+02 + 3.660001E+01 6.000000E+01 5 1.942572E+02 8.995756E+01 1.439083E-01 1.942571E+02 + 3.660001E+01 6.000000E+01 6 3.905750E+01 -3.272648E-04 3.905750E+01 -2.230905E-04 + 3.660001E+01 9.000000E+01 1 1.889641E-06 -9.003255E+01 -1.073472E-09 -1.889641E-06 + 3.660001E+01 9.000000E+01 2 3.871917E+01 8.995279E+01 3.190666E-02 3.871916E+01 + 3.660001E+01 9.000000E+01 3 1.952944E+02 1.853659E-01 1.952933E+02 6.318239E-01 + 3.660001E+01 9.000000E+01 4 1.255691E+02 8.995289E+01 1.032575E-01 1.255690E+02 + 3.660001E+01 9.000000E+01 5 8.780773E-05 -8.999483E+01 7.930714E-09 -8.780773E-05 + 3.660001E+01 9.000000E+01 6 3.348868E-06 1.799998E+02 -3.348868E-06 1.294828E-11 + 3.670001E+01 0.000000E+00 1 3.619368E+01 8.995780E+01 2.665881E-02 3.619366E+01 + 3.670001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.670001E+01 0.000000E+00 3 1.934808E+02 1.835479E-01 1.934798E+02 6.198175E-01 + 3.670001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.670001E+01 0.000000E+00 5 3.851220E+02 8.995780E+01 2.836561E-01 3.851219E+02 + 3.670001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.670001E+01 3.000000E+01 1 3.141212E+01 8.995780E+01 2.313636E-02 3.141212E+01 + 3.670001E+01 3.000000E+01 2 1.916936E+01 8.995307E+01 1.570067E-02 1.916935E+01 + 3.670001E+01 3.000000E+01 3 1.939490E+02 1.837421E-01 1.939480E+02 6.219749E-01 + 3.670001E+01 3.000000E+01 4 6.176599E+01 8.995287E+01 5.080429E-02 6.176597E+01 + 3.670001E+01 3.000000E+01 5 3.342333E+02 8.995780E+01 2.461769E-01 3.342332E+02 + 3.670001E+01 3.000000E+01 6 3.864867E+01 -3.239498E-04 3.864867E+01 -2.185192E-04 + 3.670001E+01 6.000000E+01 1 1.821420E+01 8.995780E+01 1.341476E-02 1.821419E+01 + 3.670001E+01 6.000000E+01 2 3.335966E+01 8.995307E+01 2.732434E-02 3.335965E+01 + 3.670001E+01 6.000000E+01 3 1.948910E+02 1.841283E-01 1.948900E+02 6.263096E-01 + 3.670001E+01 6.000000E+01 4 1.079451E+02 8.995307E+01 8.841609E-02 1.079451E+02 + 3.670001E+01 6.000000E+01 5 1.937811E+02 8.995780E+01 1.427354E-01 1.937810E+02 + 3.670001E+01 6.000000E+01 6 3.883728E+01 -3.234157E-04 3.883728E+01 -2.192236E-04 + 3.670001E+01 9.000000E+01 1 1.884358E-06 -9.003239E+01 -1.065184E-09 -1.884358E-06 + 3.670001E+01 9.000000E+01 2 3.861162E+01 8.995307E+01 3.162677E-02 3.861161E+01 + 3.670001E+01 9.000000E+01 3 1.953642E+02 1.843226E-01 1.953632E+02 6.284927E-01 + 3.670001E+01 9.000000E+01 4 1.252020E+02 8.995317E+01 1.023381E-01 1.252020E+02 + 3.670001E+01 9.000000E+01 5 8.757207E-05 -8.999486E+01 7.852456E-09 -8.757207E-05 + 3.670001E+01 9.000000E+01 6 3.329919E-06 1.799998E+02 -3.329919E-06 1.272406E-11 + 3.680001E+01 0.000000E+00 1 3.609518E+01 8.995804E+01 2.643451E-02 3.609517E+01 + 3.680001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.680001E+01 0.000000E+00 3 1.935592E+02 1.825232E-01 1.935582E+02 6.166071E-01 + 3.680001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.680001E+01 0.000000E+00 5 3.841978E+02 8.995804E+01 2.813598E-01 3.841977E+02 + 3.680001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.680001E+01 3.000000E+01 1 3.132634E+01 8.995804E+01 2.294147E-02 3.132633E+01 + 3.680001E+01 3.000000E+01 2 1.911706E+01 8.995335E+01 1.556402E-02 1.911705E+01 + 3.680001E+01 3.000000E+01 3 1.940258E+02 1.827141E-01 1.940249E+02 6.187401E-01 + 3.680001E+01 3.000000E+01 4 6.159063E+01 8.995316E+01 5.035570E-02 6.159061E+01 + 3.680001E+01 3.000000E+01 5 3.334243E+02 8.995804E+01 2.441790E-01 3.334242E+02 + 3.680001E+01 3.000000E+01 6 3.843254E+01 -3.201480E-04 3.843254E+01 -2.147471E-04 + 3.680001E+01 6.000000E+01 1 1.816397E+01 8.995805E+01 1.330144E-02 1.816397E+01 + 3.680001E+01 6.000000E+01 2 3.326767E+01 8.995335E+01 2.708580E-02 3.326765E+01 + 3.680001E+01 6.000000E+01 3 1.949625E+02 1.830970E-01 1.949615E+02 6.230302E-01 + 3.680001E+01 6.000000E+01 4 1.076324E+02 8.995335E+01 8.763277E-02 1.076324E+02 + 3.680001E+01 6.000000E+01 5 1.933075E+02 8.995804E+01 1.415731E-01 1.933075E+02 + 3.680001E+01 6.000000E+01 6 3.861890E+01 -3.196244E-04 3.861890E+01 -2.154355E-04 + 3.680001E+01 9.000000E+01 1 1.879113E-06 -9.003223E+01 -1.056974E-09 -1.879113E-06 + 3.680001E+01 9.000000E+01 2 3.850458E+01 8.995335E+01 3.135026E-02 3.850457E+01 + 3.680001E+01 9.000000E+01 3 1.954319E+02 1.832886E-01 1.954308E+02 6.251832E-01 + 3.680001E+01 9.000000E+01 4 1.248370E+02 8.995345E+01 1.014297E-01 1.248370E+02 + 3.680001E+01 9.000000E+01 5 8.733774E-05 -8.999490E+01 7.775218E-09 -8.733774E-05 + 3.680001E+01 9.000000E+01 6 3.311137E-06 1.799998E+02 -3.311137E-06 1.250442E-11 + 3.690001E+01 0.000000E+00 1 3.599728E+01 8.995827E+01 2.621271E-02 3.599727E+01 + 3.690001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.690001E+01 0.000000E+00 3 1.936374E+02 1.815081E-01 1.936364E+02 6.134256E-01 + 3.690001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.690001E+01 0.000000E+00 5 3.832786E+02 8.995827E+01 2.790852E-01 3.832785E+02 + 3.690001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.690001E+01 3.000000E+01 1 3.124096E+01 8.995827E+01 2.274868E-02 3.124096E+01 + 3.690001E+01 3.000000E+01 2 1.906494E+01 8.995364E+01 1.542901E-02 1.906494E+01 + 3.690001E+01 3.000000E+01 3 1.941015E+02 1.816968E-01 1.941005E+02 6.155351E-01 + 3.690001E+01 3.000000E+01 4 6.141599E+01 8.995344E+01 4.991201E-02 6.141597E+01 + 3.690001E+01 3.000000E+01 5 3.326176E+02 8.995827E+01 2.422045E-01 3.326175E+02 + 3.690001E+01 3.000000E+01 6 3.821808E+01 -3.164035E-04 3.821808E+01 -2.110511E-04 + 3.690001E+01 6.000000E+01 1 1.811399E+01 8.995828E+01 1.318936E-02 1.811398E+01 + 3.690001E+01 6.000000E+01 2 3.317612E+01 8.995364E+01 2.685007E-02 3.317611E+01 + 3.690001E+01 6.000000E+01 3 1.950322E+02 1.820760E-01 1.950312E+02 6.197773E-01 + 3.690001E+01 6.000000E+01 4 1.073225E+02 8.995364E+01 8.685882E-02 1.073224E+02 + 3.690001E+01 6.000000E+01 5 1.928387E+02 8.995827E+01 1.404242E-01 1.928387E+02 + 3.690001E+01 6.000000E+01 6 3.840244E+01 -3.158883E-04 3.840244E+01 -2.117238E-04 + 3.690001E+01 9.000000E+01 1 1.873892E-06 -9.003207E+01 -1.048851E-09 -1.873891E-06 + 3.690001E+01 9.000000E+01 2 3.839815E+01 8.995363E+01 3.107703E-02 3.839814E+01 + 3.690001E+01 9.000000E+01 3 1.954996E+02 1.822653E-01 1.954986E+02 6.219084E-01 + 3.690001E+01 9.000000E+01 4 1.244742E+02 8.995373E+01 1.005322E-01 1.244741E+02 + 3.690001E+01 9.000000E+01 5 8.710453E-05 -8.999493E+01 7.699029E-09 -8.710453E-05 + 3.690001E+01 9.000000E+01 6 3.292510E-06 1.799998E+02 -3.292510E-06 1.228920E-11 + 3.700001E+01 0.000000E+00 1 3.589978E+01 8.995852E+01 2.599344E-02 3.589977E+01 + 3.700001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.700001E+01 0.000000E+00 3 1.937148E+02 1.805010E-01 1.937138E+02 6.102659E-01 + 3.700001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.700001E+01 0.000000E+00 5 3.823571E+02 8.995852E+01 2.768368E-01 3.823570E+02 + 3.700001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.700001E+01 3.000000E+01 1 3.115604E+01 8.995852E+01 2.255808E-02 3.115603E+01 + 3.700001E+01 3.000000E+01 2 1.901317E+01 8.995390E+01 1.529554E-02 1.901317E+01 + 3.700001E+01 3.000000E+01 3 1.941762E+02 1.806874E-01 1.941752E+02 6.123512E-01 + 3.700001E+01 3.000000E+01 4 6.124279E+01 8.995371E+01 4.947377E-02 6.124277E+01 + 3.700001E+01 3.000000E+01 5 3.318172E+02 8.995852E+01 2.402489E-01 3.318171E+02 + 3.700001E+01 3.000000E+01 6 3.800550E+01 -3.127140E-04 3.800550E+01 -2.074298E-04 + 3.700001E+01 6.000000E+01 1 1.806436E+01 8.995852E+01 1.307851E-02 1.806435E+01 + 3.700001E+01 6.000000E+01 2 3.308511E+01 8.995390E+01 2.661712E-02 3.308510E+01 + 3.700001E+01 6.000000E+01 3 1.951026E+02 1.810615E-01 1.951017E+02 6.165468E-01 + 3.700001E+01 6.000000E+01 4 1.070143E+02 8.995390E+01 8.609351E-02 1.070143E+02 + 3.700001E+01 6.000000E+01 5 1.923697E+02 8.995852E+01 1.392885E-01 1.923696E+02 + 3.700001E+01 6.000000E+01 6 3.818773E+01 -3.122081E-04 3.818773E+01 -2.080872E-04 + 3.700001E+01 9.000000E+01 1 1.868694E-06 -9.003191E+01 -1.040809E-09 -1.868694E-06 + 3.700001E+01 9.000000E+01 2 3.829226E+01 8.995390E+01 3.080693E-02 3.829224E+01 + 3.700001E+01 9.000000E+01 3 1.955675E+02 1.812486E-01 1.955665E+02 6.186541E-01 + 3.700001E+01 9.000000E+01 4 1.241135E+02 8.995400E+01 9.964576E-02 1.241135E+02 + 3.700001E+01 9.000000E+01 5 8.687268E-05 -8.999497E+01 7.623820E-09 -8.687268E-05 + 3.700001E+01 9.000000E+01 6 3.274045E-06 1.799998E+02 -3.274045E-06 1.207833E-11 + 3.710001E+01 0.000000E+00 1 3.580303E+01 8.995875E+01 2.577649E-02 3.580302E+01 + 3.710001E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.710001E+01 0.000000E+00 3 1.937917E+02 1.795006E-01 1.937907E+02 6.071245E-01 + 3.710001E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.710001E+01 0.000000E+00 5 3.814402E+02 8.995875E+01 2.746114E-01 3.814401E+02 + 3.710001E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.710001E+01 3.000000E+01 1 3.107160E+01 8.995875E+01 2.236967E-02 3.107159E+01 + 3.710001E+01 3.000000E+01 2 1.896167E+01 8.995418E+01 1.516363E-02 1.896166E+01 + 3.710001E+01 3.000000E+01 3 1.942503E+02 1.796866E-01 1.942493E+02 6.091916E-01 + 3.710001E+01 3.000000E+01 4 6.107037E+01 8.995399E+01 4.904100E-02 6.107035E+01 + 3.710001E+01 3.000000E+01 5 3.310197E+02 8.995875E+01 2.383163E-01 3.310196E+02 + 3.710001E+01 3.000000E+01 6 3.779467E+01 -3.090784E-04 3.779467E+01 -2.038809E-04 + 3.710001E+01 6.000000E+01 1 1.801499E+01 8.995876E+01 1.296894E-02 1.801498E+01 + 3.710001E+01 6.000000E+01 2 3.299469E+01 8.995418E+01 2.638684E-02 3.299468E+01 + 3.710001E+01 6.000000E+01 3 1.951720E+02 1.800560E-01 1.951711E+02 6.133407E-01 + 3.710001E+01 6.000000E+01 4 1.067082E+02 8.995418E+01 8.533775E-02 1.067082E+02 + 3.710001E+01 6.000000E+01 5 1.919026E+02 8.995875E+01 1.381631E-01 1.919025E+02 + 3.710001E+01 6.000000E+01 6 3.797492E+01 -3.085806E-04 3.797492E+01 -2.045233E-04 + 3.710001E+01 9.000000E+01 1 1.863535E-06 -9.003175E+01 -1.032844E-09 -1.863535E-06 + 3.710001E+01 9.000000E+01 2 3.818700E+01 8.995418E+01 3.054006E-02 3.818699E+01 + 3.710001E+01 9.000000E+01 3 1.956349E+02 1.802405E-01 1.956339E+02 6.154253E-01 + 3.710001E+01 9.000000E+01 4 1.237551E+02 8.995428E+01 9.876946E-02 1.237550E+02 + 3.710001E+01 9.000000E+01 5 8.664217E-05 -8.999501E+01 7.549617E-09 -8.664217E-05 + 3.710001E+01 9.000000E+01 6 3.255738E-06 1.799998E+02 -3.255738E-06 1.187168E-11 + 3.720000E+01 0.000000E+00 1 3.570667E+01 8.995898E+01 2.556218E-02 3.570666E+01 + 3.720000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.720000E+01 0.000000E+00 3 1.938675E+02 1.785106E-01 1.938665E+02 6.040121E-01 + 3.720000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.720000E+01 0.000000E+00 5 3.805318E+02 8.995899E+01 2.724096E-01 3.805317E+02 + 3.720000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.720000E+01 3.000000E+01 1 3.098772E+01 8.995898E+01 2.218330E-02 3.098772E+01 + 3.720000E+01 3.000000E+01 2 1.891045E+01 8.995445E+01 1.503326E-02 1.891044E+01 + 3.720000E+01 3.000000E+01 3 1.943250E+02 1.786926E-01 1.943240E+02 6.060547E-01 + 3.720000E+01 3.000000E+01 4 6.089897E+01 8.995426E+01 4.861289E-02 6.089895E+01 + 3.720000E+01 3.000000E+01 5 3.302250E+02 8.995898E+01 2.364022E-01 3.302249E+02 + 3.720000E+01 3.000000E+01 6 3.758564E+01 -3.054968E-04 3.758564E+01 -2.004038E-04 + 3.720000E+01 6.000000E+01 1 1.796583E+01 8.995899E+01 1.286062E-02 1.796583E+01 + 3.720000E+01 6.000000E+01 2 3.290464E+01 8.995445E+01 2.615929E-02 3.290462E+01 + 3.720000E+01 6.000000E+01 3 1.952406E+02 1.790596E-01 1.952397E+02 6.101611E-01 + 3.720000E+01 6.000000E+01 4 1.064036E+02 8.995445E+01 8.459132E-02 1.064035E+02 + 3.720000E+01 6.000000E+01 5 1.914371E+02 8.995898E+01 1.370518E-01 1.914371E+02 + 3.720000E+01 6.000000E+01 6 3.776382E+01 -3.050082E-04 3.776382E+01 -2.010318E-04 + 3.720000E+01 9.000000E+01 1 1.858400E-06 -9.003160E+01 -1.024959E-09 -1.858399E-06 + 3.720000E+01 9.000000E+01 2 3.808233E+01 8.995445E+01 3.027625E-02 3.808232E+01 + 3.720000E+01 9.000000E+01 3 1.957003E+02 1.792426E-01 1.956993E+02 6.122227E-01 + 3.720000E+01 9.000000E+01 4 1.233988E+02 8.995454E+01 9.790403E-02 1.233987E+02 + 3.720000E+01 9.000000E+01 5 8.641278E-05 -8.999505E+01 7.476406E-09 -8.641278E-05 + 3.720000E+01 9.000000E+01 6 3.237583E-06 1.799998E+02 -3.237583E-06 1.166921E-11 + 3.730000E+01 0.000000E+00 1 3.561084E+01 8.995921E+01 2.535003E-02 3.561084E+01 + 3.730000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.730000E+01 0.000000E+00 3 1.939441E+02 1.775283E-01 1.939431E+02 6.009256E-01 + 3.730000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.730000E+01 0.000000E+00 5 3.796246E+02 8.995921E+01 2.702333E-01 3.796245E+02 + 3.730000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.730000E+01 3.000000E+01 1 3.090408E+01 8.995921E+01 2.199898E-02 3.090407E+01 + 3.730000E+01 3.000000E+01 2 1.885950E+01 8.995472E+01 1.490441E-02 1.885950E+01 + 3.730000E+01 3.000000E+01 3 1.943984E+02 1.777083E-01 1.943975E+02 6.029441E-01 + 3.730000E+01 3.000000E+01 4 6.072842E+01 8.995454E+01 4.819021E-02 6.072840E+01 + 3.730000E+01 3.000000E+01 5 3.294380E+02 8.995921E+01 2.345089E-01 3.294380E+02 + 3.730000E+01 3.000000E+01 6 3.737830E+01 -3.019680E-04 3.737830E+01 -1.969962E-04 + 3.730000E+01 6.000000E+01 1 1.791701E+01 8.995922E+01 1.275356E-02 1.791700E+01 + 3.730000E+01 6.000000E+01 2 3.281517E+01 8.995472E+01 2.593441E-02 3.281516E+01 + 3.730000E+01 6.000000E+01 3 1.953093E+02 1.780708E-01 1.953084E+02 6.070051E-01 + 3.730000E+01 6.000000E+01 4 1.060998E+02 8.995472E+01 8.385316E-02 1.060997E+02 + 3.730000E+01 6.000000E+01 5 1.909745E+02 8.995921E+01 1.359511E-01 1.909745E+02 + 3.730000E+01 6.000000E+01 6 3.755458E+01 -3.014875E-04 3.755458E+01 -1.976103E-04 + 3.730000E+01 9.000000E+01 1 1.853295E-06 -9.003145E+01 -1.017150E-09 -1.853295E-06 + 3.730000E+01 9.000000E+01 2 3.797836E+01 8.995472E+01 3.001556E-02 3.797834E+01 + 3.730000E+01 9.000000E+01 3 1.957673E+02 1.782511E-01 1.957663E+02 6.090444E-01 + 3.730000E+01 9.000000E+01 4 1.230442E+02 8.995481E+01 9.704840E-02 1.230442E+02 + 3.730000E+01 9.000000E+01 5 8.618405E-05 -8.999508E+01 7.404151E-09 -8.618405E-05 + 3.730000E+01 9.000000E+01 6 3.219585E-06 1.799998E+02 -3.219585E-06 1.147080E-11 + 3.740000E+01 0.000000E+00 1 3.551552E+01 8.995944E+01 2.514040E-02 3.551551E+01 + 3.740000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.740000E+01 0.000000E+00 3 1.940185E+02 1.765533E-01 1.940176E+02 5.978546E-01 + 3.740000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.740000E+01 0.000000E+00 5 3.787233E+02 8.995944E+01 2.680781E-01 3.787232E+02 + 3.740000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.740000E+01 3.000000E+01 1 3.082098E+01 8.995944E+01 2.181681E-02 3.082097E+01 + 3.740000E+01 3.000000E+01 2 1.880880E+01 8.995499E+01 1.477704E-02 1.880879E+01 + 3.740000E+01 3.000000E+01 3 1.944707E+02 1.767317E-01 1.944698E+02 5.998538E-01 + 3.740000E+01 3.000000E+01 4 6.055895E+01 8.995480E+01 4.777238E-02 6.055893E+01 + 3.740000E+01 3.000000E+01 5 3.286491E+02 8.995944E+01 2.326372E-01 3.286490E+02 + 3.740000E+01 3.000000E+01 6 3.717279E+01 -2.984897E-04 3.717279E+01 -1.936564E-04 + 3.740000E+01 6.000000E+01 1 1.786840E+01 8.995944E+01 1.264762E-02 1.786839E+01 + 3.740000E+01 6.000000E+01 2 3.272618E+01 8.995499E+01 2.571209E-02 3.272617E+01 + 3.740000E+01 6.000000E+01 3 1.953771E+02 1.770899E-01 1.953762E+02 6.038708E-01 + 3.740000E+01 6.000000E+01 4 1.057991E+02 8.995499E+01 8.312398E-02 1.057991E+02 + 3.740000E+01 6.000000E+01 5 1.905139E+02 8.995944E+01 1.348622E-01 1.905138E+02 + 3.740000E+01 6.000000E+01 6 3.734701E+01 -2.980173E-04 3.734701E+01 -1.942562E-04 + 3.740000E+01 9.000000E+01 1 1.848217E-06 -9.003130E+01 -1.009421E-09 -1.848216E-06 + 3.740000E+01 9.000000E+01 2 3.787478E+01 8.995499E+01 2.975787E-02 3.787477E+01 + 3.740000E+01 9.000000E+01 3 1.958323E+02 1.772688E-01 1.958314E+02 6.058893E-01 + 3.740000E+01 9.000000E+01 4 1.226922E+02 8.995508E+01 9.620330E-02 1.226922E+02 + 3.740000E+01 9.000000E+01 5 8.595712E-05 -8.999511E+01 7.332817E-09 -8.595712E-05 + 3.740000E+01 9.000000E+01 6 3.201735E-06 1.799998E+02 -3.201735E-06 1.127630E-11 + 3.750000E+01 0.000000E+00 1 3.542072E+01 8.995967E+01 2.493308E-02 3.542071E+01 + 3.750000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.750000E+01 0.000000E+00 3 1.940933E+02 1.755875E-01 1.940924E+02 5.948136E-01 + 3.750000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.750000E+01 0.000000E+00 5 3.778259E+02 8.995967E+01 2.659465E-01 3.778258E+02 + 3.750000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.750000E+01 3.000000E+01 1 3.073839E+01 8.995967E+01 2.163660E-02 3.073838E+01 + 3.750000E+01 3.000000E+01 2 1.875841E+01 8.995525E+01 1.465115E-02 1.875840E+01 + 3.750000E+01 3.000000E+01 3 1.945428E+02 1.757639E-01 1.945419E+02 5.967901E-01 + 3.750000E+01 3.000000E+01 4 6.039027E+01 8.995507E+01 4.735931E-02 6.039025E+01 + 3.750000E+01 3.000000E+01 5 3.278664E+02 8.995967E+01 2.307838E-01 3.278663E+02 + 3.750000E+01 3.000000E+01 6 3.696891E+01 -2.950625E-04 3.696891E+01 -1.903830E-04 + 3.750000E+01 6.000000E+01 1 1.782012E+01 8.995967E+01 1.254284E-02 1.782011E+01 + 3.750000E+01 6.000000E+01 2 3.263757E+01 8.995525E+01 2.549235E-02 3.263755E+01 + 3.750000E+01 6.000000E+01 3 1.954447E+02 1.761179E-01 1.954438E+02 6.007640E-01 + 3.750000E+01 6.000000E+01 4 1.054997E+02 8.995525E+01 8.240302E-02 1.054997E+02 + 3.750000E+01 6.000000E+01 5 1.900555E+02 8.995967E+01 1.337853E-01 1.900555E+02 + 3.750000E+01 6.000000E+01 6 3.714124E+01 -2.945984E-04 3.714124E+01 -1.909695E-04 + 3.750000E+01 9.000000E+01 1 1.843173E-06 -9.003114E+01 -1.001765E-09 -1.843173E-06 + 3.750000E+01 9.000000E+01 2 3.777192E+01 8.995525E+01 2.950320E-02 3.777191E+01 + 3.750000E+01 9.000000E+01 3 1.958978E+02 1.762942E-01 1.958969E+02 6.027599E-01 + 3.750000E+01 9.000000E+01 4 1.223418E+02 8.995534E+01 9.536795E-02 1.223418E+02 + 3.750000E+01 9.000000E+01 5 8.573143E-05 -8.999515E+01 7.262398E-09 -8.573143E-05 + 3.750000E+01 9.000000E+01 6 3.184033E-06 1.799998E+02 -3.184033E-06 1.108569E-11 + 3.760000E+01 0.000000E+00 1 3.532641E+01 8.995990E+01 2.472806E-02 3.532640E+01 + 3.760000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.760000E+01 0.000000E+00 3 1.941674E+02 1.746290E-01 1.941665E+02 5.917922E-01 + 3.760000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.760000E+01 0.000000E+00 5 3.769309E+02 8.995990E+01 2.638378E-01 3.769308E+02 + 3.760000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.760000E+01 3.000000E+01 1 3.065624E+01 8.995990E+01 2.145841E-02 3.065624E+01 + 3.760000E+01 3.000000E+01 2 1.870827E+01 8.995551E+01 1.452670E-02 1.870827E+01 + 3.760000E+01 3.000000E+01 3 1.946130E+02 1.748050E-01 1.946121E+02 5.937486E-01 + 3.760000E+01 3.000000E+01 4 6.022271E+01 8.995534E+01 4.695121E-02 6.022269E+01 + 3.760000E+01 3.000000E+01 5 3.270844E+02 8.995990E+01 2.289510E-01 3.270843E+02 + 3.760000E+01 3.000000E+01 6 3.676674E+01 -2.916853E-04 3.676674E+01 -1.871746E-04 + 3.760000E+01 6.000000E+01 1 1.777201E+01 8.995990E+01 1.243931E-02 1.777201E+01 + 3.760000E+01 6.000000E+01 2 3.254964E+01 8.995551E+01 2.527520E-02 3.254963E+01 + 3.760000E+01 6.000000E+01 3 1.955117E+02 1.751526E-01 1.955108E+02 5.976764E-01 + 3.760000E+01 6.000000E+01 4 1.052019E+02 8.995551E+01 8.169108E-02 1.052018E+02 + 3.760000E+01 6.000000E+01 5 1.895983E+02 8.995990E+01 1.327199E-01 1.895982E+02 + 3.760000E+01 6.000000E+01 6 3.693717E+01 -2.912291E-04 3.693717E+01 -1.877482E-04 + 3.760000E+01 9.000000E+01 1 1.838151E-06 -9.003099E+01 -9.941880E-10 -1.838151E-06 + 3.760000E+01 9.000000E+01 2 3.766951E+01 8.995551E+01 2.925150E-02 3.766950E+01 + 3.760000E+01 9.000000E+01 3 1.959611E+02 1.753282E-01 1.959602E+02 5.996506E-01 + 3.760000E+01 9.000000E+01 4 1.219939E+02 8.995560E+01 9.454259E-02 1.219939E+02 + 3.760000E+01 9.000000E+01 5 8.550697E-05 -8.999518E+01 7.192929E-09 -8.550697E-05 + 3.760000E+01 9.000000E+01 6 3.166490E-06 1.799998E+02 -3.166490E-06 1.089889E-11 + 3.770000E+01 0.000000E+00 1 3.523265E+01 8.996011E+01 2.452518E-02 3.523264E+01 + 3.770000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.770000E+01 0.000000E+00 3 1.942398E+02 1.736797E-01 1.942389E+02 5.887948E-01 + 3.770000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.770000E+01 0.000000E+00 5 3.760396E+02 8.996012E+01 2.617493E-01 3.760395E+02 + 3.770000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.770000E+01 3.000000E+01 1 3.057445E+01 8.996011E+01 2.128232E-02 3.057444E+01 + 3.770000E+01 3.000000E+01 2 1.865842E+01 8.995577E+01 1.440366E-02 1.865842E+01 + 3.770000E+01 3.000000E+01 3 1.946850E+02 1.738515E-01 1.946841E+02 5.907283E-01 + 3.770000E+01 3.000000E+01 4 6.005615E+01 8.995560E+01 4.654782E-02 6.005613E+01 + 3.770000E+01 3.000000E+01 5 3.263070E+02 8.996011E+01 2.271385E-01 3.263069E+02 + 3.770000E+01 3.000000E+01 6 3.656622E+01 -2.883568E-04 3.656622E+01 -1.840296E-04 + 3.770000E+01 6.000000E+01 1 1.772424E+01 8.996012E+01 1.233690E-02 1.772424E+01 + 3.770000E+01 6.000000E+01 2 3.246197E+01 8.995577E+01 2.506052E-02 3.246196E+01 + 3.770000E+01 6.000000E+01 3 1.955773E+02 1.741974E-01 1.955764E+02 5.946164E-01 + 3.770000E+01 6.000000E+01 4 1.049062E+02 8.995577E+01 8.098717E-02 1.049062E+02 + 3.770000E+01 6.000000E+01 5 1.891437E+02 8.996011E+01 1.316649E-01 1.891437E+02 + 3.770000E+01 6.000000E+01 6 3.673475E+01 -2.879080E-04 3.673475E+01 -1.845900E-04 + 3.770000E+01 9.000000E+01 1 1.833153E-06 -9.003085E+01 -9.866805E-10 -1.833153E-06 + 3.770000E+01 9.000000E+01 2 3.756766E+01 8.995577E+01 2.900263E-02 3.756765E+01 + 3.770000E+01 9.000000E+01 3 1.960254E+02 1.743704E-01 1.960245E+02 5.965705E-01 + 3.770000E+01 9.000000E+01 4 1.216478E+02 8.995586E+01 9.372678E-02 1.216478E+02 + 3.770000E+01 9.000000E+01 5 8.528346E-05 -8.999522E+01 7.124344E-09 -8.528346E-05 + 3.770000E+01 9.000000E+01 6 3.149081E-06 1.799998E+02 -3.149081E-06 1.071572E-11 + 3.780000E+01 0.000000E+00 1 3.513924E+01 8.996034E+01 2.432460E-02 3.513923E+01 + 3.780000E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.780000E+01 0.000000E+00 3 1.943123E+02 1.727374E-01 1.943114E+02 5.858189E-01 + 3.780000E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.780000E+01 0.000000E+00 5 3.751520E+02 8.996034E+01 2.596821E-01 3.751519E+02 + 3.780000E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.780000E+01 3.000000E+01 1 3.049315E+01 8.996034E+01 2.110793E-02 3.049315E+01 + 3.780000E+01 3.000000E+01 2 1.860884E+01 8.995602E+01 1.428207E-02 1.860883E+01 + 3.780000E+01 3.000000E+01 3 1.947545E+02 1.729080E-01 1.947536E+02 5.877321E-01 + 3.780000E+01 3.000000E+01 4 5.989046E+01 8.995586E+01 4.614917E-02 5.989045E+01 + 3.780000E+01 3.000000E+01 5 3.255338E+02 8.996034E+01 2.253425E-01 3.255337E+02 + 3.780000E+01 3.000000E+01 6 3.636741E+01 -2.850756E-04 3.636741E+01 -1.809463E-04 + 3.780000E+01 6.000000E+01 1 1.767672E+01 8.996034E+01 1.223558E-02 1.767672E+01 + 3.780000E+01 6.000000E+01 2 3.237489E+01 8.995602E+01 2.484830E-02 3.237488E+01 + 3.780000E+01 6.000000E+01 3 1.956429E+02 1.732492E-01 1.956420E+02 5.915777E-01 + 3.780000E+01 6.000000E+01 4 1.046122E+02 8.995602E+01 8.029181E-02 1.046122E+02 + 3.780000E+01 6.000000E+01 5 1.886924E+02 8.996034E+01 1.306212E-01 1.886924E+02 + 3.780000E+01 6.000000E+01 6 3.653410E+01 -2.846348E-04 3.653410E+01 -1.814946E-04 + 3.780000E+01 9.000000E+01 1 1.828188E-06 -9.003069E+01 -9.792515E-10 -1.828188E-06 + 3.780000E+01 9.000000E+01 2 3.746643E+01 8.995602E+01 2.875663E-02 3.746642E+01 + 3.780000E+01 9.000000E+01 3 1.960886E+02 1.734206E-01 1.960877E+02 5.935124E-01 + 3.780000E+01 9.000000E+01 4 1.213039E+02 8.995612E+01 9.292052E-02 1.213038E+02 + 3.780000E+01 9.000000E+01 5 8.506112E-05 -8.999525E+01 7.056638E-09 -8.506112E-05 + 3.780000E+01 9.000000E+01 6 3.131823E-06 1.799998E+02 -3.131823E-06 1.053619E-11 + 3.789999E+01 0.000000E+00 1 3.504645E+01 8.996056E+01 2.412626E-02 3.504644E+01 + 3.789999E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.789999E+01 0.000000E+00 3 1.943845E+02 1.718028E-01 1.943837E+02 5.828659E-01 + 3.789999E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.789999E+01 0.000000E+00 5 3.742676E+02 8.996056E+01 2.576386E-01 3.742675E+02 + 3.789999E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.789999E+01 3.000000E+01 1 3.041226E+01 8.996056E+01 2.093559E-02 3.041225E+01 + 3.789999E+01 3.000000E+01 2 1.855947E+01 8.995628E+01 1.416183E-02 1.855946E+01 + 3.789999E+01 3.000000E+01 3 1.948246E+02 1.719720E-01 1.948237E+02 5.847607E-01 + 3.789999E+01 3.000000E+01 4 5.972560E+01 8.995611E+01 4.575526E-02 5.972558E+01 + 3.789999E+01 3.000000E+01 5 3.247654E+02 8.996056E+01 2.235660E-01 3.247654E+02 + 3.789999E+01 3.000000E+01 6 3.617013E+01 -2.818428E-04 3.617013E+01 -1.779240E-04 + 3.789999E+01 6.000000E+01 1 1.762939E+01 8.996056E+01 1.213540E-02 1.762938E+01 + 3.789999E+01 6.000000E+01 2 3.228830E+01 8.995628E+01 2.463846E-02 3.228829E+01 + 3.789999E+01 6.000000E+01 3 1.957083E+02 1.723089E-01 1.957074E+02 5.885640E-01 + 3.789999E+01 6.000000E+01 4 1.043195E+02 8.995628E+01 7.960381E-02 1.043195E+02 + 3.789999E+01 6.000000E+01 5 1.882422E+02 8.996056E+01 1.295894E-01 1.882421E+02 + 3.789999E+01 6.000000E+01 6 3.633500E+01 -2.814091E-04 3.633500E+01 -1.784599E-04 + 3.789999E+01 9.000000E+01 1 1.823248E-06 -9.003054E+01 -9.718899E-10 -1.823248E-06 + 3.789999E+01 9.000000E+01 2 3.736568E+01 8.995628E+01 2.851348E-02 3.736567E+01 + 3.789999E+01 9.000000E+01 3 1.961514E+02 1.724782E-01 1.961505E+02 5.904762E-01 + 3.789999E+01 9.000000E+01 4 1.209620E+02 8.995637E+01 9.212315E-02 1.209620E+02 + 3.789999E+01 9.000000E+01 5 8.483945E-05 -8.999529E+01 6.989779E-09 -8.483945E-05 + 3.789999E+01 9.000000E+01 6 3.114706E-06 1.799998E+02 -3.114706E-06 1.036019E-11 + 3.799999E+01 0.000000E+00 1 3.495421E+01 8.996078E+01 2.393005E-02 3.495420E+01 + 3.799999E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.799999E+01 0.000000E+00 3 1.944568E+02 1.708748E-01 1.944559E+02 5.799330E-01 + 3.799999E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.799999E+01 0.000000E+00 5 3.733889E+02 8.996078E+01 2.556180E-01 3.733888E+02 + 3.799999E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.799999E+01 3.000000E+01 1 3.033183E+01 8.996078E+01 2.076511E-02 3.033182E+01 + 3.799999E+01 3.000000E+01 2 1.851044E+01 8.995654E+01 1.404292E-02 1.851043E+01 + 3.799999E+01 3.000000E+01 3 1.948943E+02 1.710430E-01 1.948935E+02 5.818102E-01 + 3.799999E+01 3.000000E+01 4 5.956176E+01 8.995636E+01 4.536559E-02 5.956174E+01 + 3.799999E+01 3.000000E+01 5 3.239963E+02 8.996078E+01 2.218107E-01 3.239962E+02 + 3.799999E+01 3.000000E+01 6 3.597455E+01 -2.786547E-04 3.597455E+01 -1.749601E-04 + 3.799999E+01 6.000000E+01 1 1.758238E+01 8.996078E+01 1.203630E-02 1.758238E+01 + 3.799999E+01 6.000000E+01 2 3.220208E+01 8.995653E+01 2.443106E-02 3.220208E+01 + 3.799999E+01 6.000000E+01 3 1.957732E+02 1.713764E-01 1.957723E+02 5.855727E-01 + 3.799999E+01 6.000000E+01 4 1.040285E+02 8.995653E+01 7.892429E-02 1.040284E+02 + 3.799999E+01 6.000000E+01 5 1.877928E+02 8.996078E+01 1.285691E-01 1.877927E+02 + 3.799999E+01 6.000000E+01 6 3.613800E+01 -2.782307E-04 3.613800E+01 -1.754876E-04 + 3.799999E+01 9.000000E+01 1 1.818341E-06 -9.003040E+01 -9.646056E-10 -1.818340E-06 + 3.799999E+01 9.000000E+01 2 3.726551E+01 8.995653E+01 2.827307E-02 3.726550E+01 + 3.799999E+01 9.000000E+01 3 1.962141E+02 1.715433E-01 1.962132E+02 5.874630E-01 + 3.799999E+01 9.000000E+01 4 1.206220E+02 8.995662E+01 9.133600E-02 1.206219E+02 + 3.799999E+01 9.000000E+01 5 8.461963E-05 -8.999531E+01 6.923800E-09 -8.461963E-05 + 3.799999E+01 9.000000E+01 6 3.097734E-06 1.799998E+02 -3.097734E-06 1.018763E-11 + 3.809999E+01 0.000000E+00 1 3.486228E+01 8.996099E+01 2.373597E-02 3.486227E+01 + 3.809999E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.809999E+01 0.000000E+00 3 1.945269E+02 1.699565E-01 1.945260E+02 5.770244E-01 + 3.809999E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.809999E+01 0.000000E+00 5 3.725117E+02 8.996099E+01 2.536160E-01 3.725117E+02 + 3.809999E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.809999E+01 3.000000E+01 1 3.025176E+01 8.996099E+01 2.059648E-02 3.025176E+01 + 3.809999E+01 3.000000E+01 2 1.846157E+01 8.995678E+01 1.392544E-02 1.846156E+01 + 3.809999E+01 3.000000E+01 3 1.949627E+02 1.701212E-01 1.949619E+02 5.788776E-01 + 3.809999E+01 3.000000E+01 4 5.939889E+01 8.995661E+01 4.498062E-02 5.939887E+01 + 3.809999E+01 3.000000E+01 5 3.232348E+02 8.996099E+01 2.200700E-01 3.232347E+02 + 3.809999E+01 3.000000E+01 6 3.578088E+01 -2.755157E-04 3.578088E+01 -1.720579E-04 + 3.809999E+01 6.000000E+01 1 1.753559E+01 8.996100E+01 1.193830E-02 1.753559E+01 + 3.809999E+01 6.000000E+01 2 3.211641E+01 8.995678E+01 2.422601E-02 3.211641E+01 + 3.809999E+01 6.000000E+01 3 1.958373E+02 1.704507E-01 1.958364E+02 5.826007E-01 + 3.809999E+01 6.000000E+01 4 1.037392E+02 8.995678E+01 7.825250E-02 1.037392E+02 + 3.809999E+01 6.000000E+01 5 1.873469E+02 8.996099E+01 1.275576E-01 1.873468E+02 + 3.809999E+01 6.000000E+01 6 3.594220E+01 -2.750968E-04 3.594220E+01 -1.725709E-04 + 3.809999E+01 9.000000E+01 1 1.813455E-06 -9.003025E+01 -9.573888E-10 -1.813455E-06 + 3.809999E+01 9.000000E+01 2 3.716589E+01 8.995678E+01 2.803547E-02 3.716588E+01 + 3.809999E+01 9.000000E+01 3 1.962754E+02 1.706165E-01 1.962745E+02 5.844717E-01 + 3.809999E+01 9.000000E+01 4 1.202840E+02 8.995686E+01 9.055747E-02 1.202840E+02 + 3.809999E+01 9.000000E+01 5 8.440075E-05 -8.999535E+01 6.858656E-09 -8.440075E-05 + 3.809999E+01 9.000000E+01 6 3.080899E-06 1.799998E+02 -3.080899E-06 1.001845E-11 + 3.819999E+01 0.000000E+00 1 3.477097E+01 8.996120E+01 2.354402E-02 3.477096E+01 + 3.819999E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.819999E+01 0.000000E+00 3 1.945977E+02 1.690437E-01 1.945969E+02 5.741343E-01 + 3.819999E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.819999E+01 0.000000E+00 5 3.716402E+02 8.996120E+01 2.516356E-01 3.716401E+02 + 3.819999E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.819999E+01 3.000000E+01 1 3.017216E+01 8.996120E+01 2.042966E-02 3.017216E+01 + 3.819999E+01 3.000000E+01 2 1.841299E+01 8.995703E+01 1.380922E-02 1.841298E+01 + 3.819999E+01 3.000000E+01 3 1.950316E+02 1.692058E-01 1.950308E+02 5.759662E-01 + 3.819999E+01 3.000000E+01 4 5.923672E+01 8.995686E+01 4.459998E-02 5.923670E+01 + 3.819999E+01 3.000000E+01 5 3.224754E+02 8.996120E+01 2.183504E-01 3.224753E+02 + 3.819999E+01 3.000000E+01 6 3.558846E+01 -2.724184E-04 3.558846E+01 -1.692088E-04 + 3.819999E+01 6.000000E+01 1 1.748909E+01 8.996120E+01 1.184138E-02 1.748909E+01 + 3.819999E+01 6.000000E+01 2 3.203118E+01 8.995703E+01 2.402324E-02 3.203117E+01 + 3.819999E+01 6.000000E+01 3 1.959011E+02 1.695328E-01 1.959003E+02 5.796521E-01 + 3.819999E+01 6.000000E+01 4 1.034517E+02 8.995703E+01 7.758854E-02 1.034517E+02 + 3.819999E+01 6.000000E+01 5 1.869014E+02 8.996120E+01 1.265575E-01 1.869014E+02 + 3.819999E+01 6.000000E+01 6 3.574800E+01 -2.720069E-04 3.574800E+01 -1.697106E-04 + 3.819999E+01 9.000000E+01 1 1.808592E-06 -9.003011E+01 -9.502413E-10 -1.808592E-06 + 3.819999E+01 9.000000E+01 2 3.706679E+01 8.995703E+01 2.780049E-02 3.706678E+01 + 3.819999E+01 9.000000E+01 3 1.963370E+02 1.696968E-01 1.963362E+02 5.815037E-01 + 3.819999E+01 9.000000E+01 4 1.199473E+02 8.995711E+01 8.978783E-02 1.199473E+02 + 3.819999E+01 9.000000E+01 5 8.418305E-05 -8.999538E+01 6.794342E-09 -8.418305E-05 + 3.819999E+01 9.000000E+01 6 3.064201E-06 1.799998E+02 -3.064201E-06 9.852551E-12 + 3.829999E+01 0.000000E+00 1 3.468003E+01 8.996142E+01 2.335418E-02 3.468002E+01 + 3.829999E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.829999E+01 0.000000E+00 3 1.946672E+02 1.681380E-01 1.946664E+02 5.712622E-01 + 3.829999E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.829999E+01 0.000000E+00 5 3.707715E+02 8.996142E+01 2.496768E-01 3.707714E+02 + 3.829999E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.829999E+01 3.000000E+01 1 3.009303E+01 8.996142E+01 2.026470E-02 3.009303E+01 + 3.829999E+01 3.000000E+01 2 1.836469E+01 8.995728E+01 1.369432E-02 1.836468E+01 + 3.829999E+01 3.000000E+01 3 1.950982E+02 1.683000E-01 1.950974E+02 5.730785E-01 + 3.829999E+01 3.000000E+01 4 5.907571E+01 8.995711E+01 4.422360E-02 5.907570E+01 + 3.829999E+01 3.000000E+01 5 3.217174E+02 8.996142E+01 2.166486E-01 3.217173E+02 + 3.829999E+01 3.000000E+01 6 3.539756E+01 -2.693656E-04 3.539756E+01 -1.664151E-04 + 3.829999E+01 6.000000E+01 1 1.744281E+01 8.996142E+01 1.174549E-02 1.744281E+01 + 3.829999E+01 6.000000E+01 2 3.194634E+01 8.995728E+01 2.382282E-02 3.194633E+01 + 3.829999E+01 6.000000E+01 3 1.959636E+02 1.686223E-01 1.959627E+02 5.767229E-01 + 3.829999E+01 6.000000E+01 4 1.031661E+02 8.995728E+01 7.693203E-02 1.031660E+02 + 3.829999E+01 6.000000E+01 5 1.864578E+02 8.996141E+01 1.255679E-01 1.864578E+02 + 3.829999E+01 6.000000E+01 6 3.555539E+01 -2.689601E-04 3.555539E+01 -1.669055E-04 + 3.829999E+01 9.000000E+01 1 1.803759E-06 -9.002996E+01 -9.431657E-10 -1.803759E-06 + 3.829999E+01 9.000000E+01 2 3.696821E+01 8.995728E+01 2.756819E-02 3.696820E+01 + 3.829999E+01 9.000000E+01 3 1.963979E+02 1.687841E-01 1.963970E+02 5.785557E-01 + 3.829999E+01 9.000000E+01 4 1.196137E+02 8.995736E+01 8.902670E-02 1.196137E+02 + 3.829999E+01 9.000000E+01 5 8.396599E-05 -8.999541E+01 6.730840E-09 -8.396599E-05 + 3.829999E+01 9.000000E+01 6 3.047637E-06 1.799998E+02 -3.047637E-06 9.689864E-12 + 3.839999E+01 0.000000E+00 1 3.458966E+01 8.996162E+01 2.316631E-02 3.458965E+01 + 3.839999E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.839999E+01 0.000000E+00 3 1.947369E+02 1.672419E-01 1.947361E+02 5.684209E-01 + 3.839999E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.839999E+01 0.000000E+00 5 3.699066E+02 8.996163E+01 2.477349E-01 3.699065E+02 + 3.839999E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.839999E+01 3.000000E+01 1 3.001420E+01 8.996163E+01 2.010148E-02 3.001419E+01 + 3.839999E+01 3.000000E+01 2 1.831668E+01 8.995752E+01 1.358072E-02 1.831667E+01 + 3.839999E+01 3.000000E+01 3 1.951666E+02 1.674010E-01 1.951657E+02 5.702170E-01 + 3.839999E+01 3.000000E+01 4 5.891519E+01 8.995736E+01 4.385172E-02 5.891518E+01 + 3.839999E+01 3.000000E+01 5 3.209645E+02 8.996163E+01 2.149600E-01 3.209644E+02 + 3.839999E+01 3.000000E+01 6 3.520827E+01 -2.663557E-04 3.520827E+01 -1.636756E-04 + 3.839999E+01 6.000000E+01 1 1.739679E+01 8.996163E+01 1.165067E-02 1.739678E+01 + 3.839999E+01 6.000000E+01 2 3.186199E+01 8.995752E+01 2.362458E-02 3.186198E+01 + 3.839999E+01 6.000000E+01 3 1.960269E+02 1.677210E-01 1.960261E+02 5.738257E-01 + 3.839999E+01 6.000000E+01 4 1.028811E+02 8.995752E+01 7.628284E-02 1.028811E+02 + 3.839999E+01 6.000000E+01 5 1.860197E+02 8.996162E+01 1.245880E-01 1.860196E+02 + 3.839999E+01 6.000000E+01 6 3.536435E+01 -2.659573E-04 3.536435E+01 -1.641553E-04 + 3.839999E+01 9.000000E+01 1 1.798952E-06 -9.002982E+01 -9.361557E-10 -1.798952E-06 + 3.839999E+01 9.000000E+01 2 3.687025E+01 8.995752E+01 2.733845E-02 3.687024E+01 + 3.839999E+01 9.000000E+01 3 1.964591E+02 1.678807E-01 1.964582E+02 5.756382E-01 + 3.839999E+01 9.000000E+01 4 1.192811E+02 8.995760E+01 8.827484E-02 1.192811E+02 + 3.839999E+01 9.000000E+01 5 8.374990E-05 -8.999544E+01 6.668135E-09 -8.374990E-05 + 3.839999E+01 9.000000E+01 6 3.031218E-06 1.799998E+02 -3.031218E-06 9.530353E-12 + 3.849998E+01 0.000000E+00 1 3.449977E+01 8.996184E+01 2.298047E-02 3.449976E+01 + 3.849998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.849998E+01 0.000000E+00 3 1.948059E+02 1.663502E-01 1.948051E+02 5.655909E-01 + 3.849998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.849998E+01 0.000000E+00 5 3.690460E+02 8.996184E+01 2.458162E-01 3.690459E+02 + 3.849998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.849998E+01 3.000000E+01 1 2.993586E+01 8.996184E+01 1.994009E-02 2.993586E+01 + 3.849998E+01 3.000000E+01 2 1.826886E+01 8.995776E+01 1.346837E-02 1.826886E+01 + 3.849998E+01 3.000000E+01 3 1.952324E+02 1.665085E-01 1.952316E+02 5.673683E-01 + 3.849998E+01 3.000000E+01 4 5.875619E+01 8.995760E+01 4.348381E-02 5.875618E+01 + 3.849998E+01 3.000000E+01 5 3.202123E+02 8.996184E+01 2.132935E-01 3.202122E+02 + 3.849998E+01 3.000000E+01 6 3.502040E+01 -2.633889E-04 3.502040E+01 -1.609889E-04 + 3.849998E+01 6.000000E+01 1 1.735099E+01 8.996184E+01 1.155688E-02 1.735098E+01 + 3.849998E+01 6.000000E+01 2 3.177813E+01 8.995776E+01 2.342860E-02 3.177812E+01 + 3.849998E+01 6.000000E+01 3 1.960889E+02 1.668241E-01 1.960880E+02 5.709372E-01 + 3.849998E+01 6.000000E+01 4 1.025988E+02 8.995776E+01 7.564160E-02 1.025988E+02 + 3.849998E+01 6.000000E+01 5 1.855794E+02 8.996184E+01 1.236184E-01 1.855794E+02 + 3.849998E+01 6.000000E+01 6 3.517489E+01 -2.629961E-04 3.517489E+01 -1.614580E-04 + 3.849998E+01 9.000000E+01 1 1.794170E-06 -9.002967E+01 -9.292148E-10 -1.794169E-06 + 3.849998E+01 9.000000E+01 2 3.677270E+01 8.995776E+01 2.711136E-02 3.677269E+01 + 3.849998E+01 9.000000E+01 3 1.965185E+02 1.669825E-01 1.965177E+02 5.727317E-01 + 3.849998E+01 9.000000E+01 4 1.189512E+02 8.995784E+01 8.753150E-02 1.189511E+02 + 3.849998E+01 9.000000E+01 5 8.353601E-05 -8.999547E+01 6.606227E-09 -8.353601E-05 + 3.849998E+01 9.000000E+01 6 3.014928E-06 1.799998E+02 -3.014928E-06 9.373904E-12 + 3.859998E+01 0.000000E+00 1 3.441029E+01 8.996204E+01 2.279671E-02 3.441029E+01 + 3.859998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.859998E+01 0.000000E+00 3 1.948741E+02 1.654676E-01 1.948733E+02 5.627869E-01 + 3.859998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.859998E+01 0.000000E+00 5 3.681898E+02 8.996204E+01 2.439158E-01 3.681897E+02 + 3.859998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.859998E+01 3.000000E+01 1 2.985792E+01 8.996204E+01 1.978032E-02 2.985792E+01 + 3.859998E+01 3.000000E+01 2 1.822135E+01 8.995800E+01 1.335728E-02 1.822134E+01 + 3.859998E+01 3.000000E+01 3 1.952984E+02 1.656235E-01 1.952976E+02 5.645435E-01 + 3.859998E+01 3.000000E+01 4 5.859755E+01 8.995784E+01 4.312038E-02 5.859753E+01 + 3.859998E+01 3.000000E+01 5 3.194663E+02 8.996204E+01 2.116415E-01 3.194662E+02 + 3.859998E+01 3.000000E+01 6 3.483408E+01 -2.604633E-04 3.483408E+01 -1.583537E-04 + 3.859998E+01 6.000000E+01 1 1.730544E+01 8.996205E+01 1.146407E-02 1.730544E+01 + 3.859998E+01 6.000000E+01 2 3.169465E+01 8.995800E+01 2.323485E-02 3.169464E+01 + 3.859998E+01 6.000000E+01 3 1.961509E+02 1.659355E-01 1.961501E+02 5.680760E-01 + 3.859998E+01 6.000000E+01 4 1.023174E+02 8.995800E+01 7.500722E-02 1.023173E+02 + 3.859998E+01 6.000000E+01 5 1.851430E+02 8.996204E+01 1.226605E-01 1.851430E+02 + 3.859998E+01 6.000000E+01 6 3.498689E+01 -2.600776E-04 3.498689E+01 -1.588128E-04 + 3.859998E+01 9.000000E+01 1 1.789424E-06 -9.002953E+01 -9.223416E-10 -1.789424E-06 + 3.859998E+01 9.000000E+01 2 3.667565E+01 8.995800E+01 2.688683E-02 3.667564E+01 + 3.859998E+01 9.000000E+01 3 1.965779E+02 1.660928E-01 1.965770E+02 5.698522E-01 + 3.859998E+01 9.000000E+01 4 1.186225E+02 8.995808E+01 8.679637E-02 1.186225E+02 + 3.859998E+01 9.000000E+01 5 8.332237E-05 -8.999550E+01 6.545080E-09 -8.332237E-05 + 3.859998E+01 9.000000E+01 6 2.998770E-06 1.799998E+02 -2.998770E-06 9.220468E-12 + 3.869998E+01 0.000000E+00 1 3.432128E+01 8.996225E+01 2.261486E-02 3.432127E+01 + 3.869998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.869998E+01 0.000000E+00 3 1.949422E+02 1.645907E-01 1.949414E+02 5.600000E-01 + 3.869998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.869998E+01 0.000000E+00 5 3.673383E+02 8.996225E+01 2.420353E-01 3.673383E+02 + 3.869998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.869998E+01 3.000000E+01 1 2.978041E+01 8.996225E+01 1.962240E-02 2.978041E+01 + 3.869998E+01 3.000000E+01 2 1.817397E+01 8.995824E+01 1.324745E-02 1.817397E+01 + 3.869998E+01 3.000000E+01 3 1.953644E+02 1.647459E-01 1.953636E+02 5.617420E-01 + 3.869998E+01 3.000000E+01 4 5.843998E+01 8.995808E+01 4.276097E-02 5.843997E+01 + 3.869998E+01 3.000000E+01 5 3.187232E+02 8.996225E+01 2.100082E-01 3.187231E+02 + 3.869998E+01 3.000000E+01 6 3.464930E+01 -2.575781E-04 3.464930E+01 -1.557689E-04 + 3.869998E+01 6.000000E+01 1 1.726012E+01 8.996225E+01 1.137227E-02 1.726012E+01 + 3.869998E+01 6.000000E+01 2 3.161165E+01 8.995824E+01 2.304325E-02 3.161164E+01 + 3.869998E+01 6.000000E+01 3 1.962120E+02 1.650551E-01 1.962112E+02 5.652379E-01 + 3.869998E+01 6.000000E+01 4 1.020378E+02 8.995824E+01 7.438006E-02 1.020377E+02 + 3.869998E+01 6.000000E+01 5 1.847064E+02 8.996225E+01 1.217106E-01 1.847063E+02 + 3.869998E+01 6.000000E+01 6 3.480049E+01 -2.571990E-04 3.480049E+01 -1.562183E-04 + 3.869998E+01 9.000000E+01 1 1.784687E-06 -9.002940E+01 -9.155313E-10 -1.784687E-06 + 3.869998E+01 9.000000E+01 2 3.657920E+01 8.995824E+01 2.666473E-02 3.657919E+01 + 3.869998E+01 9.000000E+01 3 1.966374E+02 1.652094E-01 1.966366E+02 5.669930E-01 + 3.869998E+01 9.000000E+01 4 1.182951E+02 8.995831E+01 8.606980E-02 1.182951E+02 + 3.869998E+01 9.000000E+01 5 8.310971E-05 -8.999553E+01 6.484684E-09 -8.310971E-05 + 3.869998E+01 9.000000E+01 6 2.982742E-06 1.799998E+02 -2.982742E-06 9.069962E-12 + 3.879998E+01 0.000000E+00 1 3.423267E+01 8.996245E+01 2.243490E-02 3.423266E+01 + 3.879998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.879998E+01 0.000000E+00 3 1.950095E+02 1.637224E-01 1.950087E+02 5.572378E-01 + 3.879998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.879998E+01 0.000000E+00 5 3.664887E+02 8.996245E+01 2.401737E-01 3.664886E+02 + 3.879998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.879998E+01 3.000000E+01 1 2.970324E+01 8.996245E+01 1.946608E-02 2.970324E+01 + 3.879998E+01 3.000000E+01 2 1.812698E+01 8.995847E+01 1.313880E-02 1.812697E+01 + 3.879998E+01 3.000000E+01 3 1.954297E+02 1.638752E-01 1.954289E+02 5.589599E-01 + 3.879998E+01 3.000000E+01 4 5.828310E+01 8.995831E+01 4.240539E-02 5.828309E+01 + 3.879998E+01 3.000000E+01 5 3.179832E+02 8.996245E+01 2.083906E-01 3.179831E+02 + 3.879998E+01 3.000000E+01 6 3.446599E+01 -2.547337E-04 3.446599E+01 -1.532338E-04 + 3.879998E+01 6.000000E+01 1 1.721502E+01 8.996245E+01 1.128144E-02 1.721502E+01 + 3.879998E+01 6.000000E+01 2 3.152910E+01 8.995847E+01 2.285371E-02 3.152909E+01 + 3.879998E+01 6.000000E+01 3 1.962736E+02 1.641803E-01 1.962728E+02 5.624187E-01 + 3.879998E+01 6.000000E+01 4 1.017596E+02 8.995847E+01 7.376023E-02 1.017596E+02 + 3.879998E+01 6.000000E+01 5 1.842768E+02 8.996245E+01 1.207709E-01 1.842768E+02 + 3.879998E+01 6.000000E+01 6 3.461555E+01 -2.543607E-04 3.461555E+01 -1.536734E-04 + 3.879998E+01 9.000000E+01 1 1.779986E-06 -9.002926E+01 -9.087877E-10 -1.779985E-06 + 3.879998E+01 9.000000E+01 2 3.648320E+01 8.995847E+01 2.644516E-02 3.648318E+01 + 3.879998E+01 9.000000E+01 3 1.966966E+02 1.643332E-01 1.966958E+02 5.641557E-01 + 3.879998E+01 9.000000E+01 4 1.179707E+02 8.995854E+01 8.535144E-02 1.179706E+02 + 3.879998E+01 9.000000E+01 5 8.289875E-05 -8.999556E+01 6.425076E-09 -8.289875E-05 + 3.879998E+01 9.000000E+01 6 2.966845E-06 1.799998E+02 -2.966845E-06 8.922348E-12 + 3.889998E+01 0.000000E+00 1 3.414457E+01 8.996265E+01 2.225692E-02 3.414457E+01 + 3.889998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.889998E+01 0.000000E+00 3 1.950762E+02 1.628608E-01 1.950754E+02 5.544951E-01 + 3.889998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.889998E+01 0.000000E+00 5 3.656395E+02 8.996265E+01 2.383312E-01 3.656394E+02 + 3.889998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.889998E+01 3.000000E+01 1 2.962646E+01 8.996265E+01 1.931144E-02 2.962645E+01 + 3.889998E+01 3.000000E+01 2 1.808017E+01 8.995871E+01 1.303136E-02 1.808017E+01 + 3.889998E+01 3.000000E+01 3 1.954939E+02 1.630118E-01 1.954931E+02 5.561976E-01 + 3.889998E+01 3.000000E+01 4 5.812726E+01 8.995855E+01 4.205388E-02 5.812724E+01 + 3.889998E+01 3.000000E+01 5 3.172439E+02 8.996265E+01 2.067901E-01 3.172438E+02 + 3.889998E+01 3.000000E+01 6 3.428415E+01 -2.519286E-04 3.428415E+01 -1.507468E-04 + 3.889998E+01 6.000000E+01 1 1.717017E+01 8.996265E+01 1.119160E-02 1.717017E+01 + 3.889998E+01 6.000000E+01 2 3.144697E+01 8.995870E+01 2.266631E-02 3.144696E+01 + 3.889998E+01 6.000000E+01 3 1.963335E+02 1.633135E-01 1.963327E+02 5.596203E-01 + 3.889998E+01 6.000000E+01 4 1.014834E+02 8.995870E+01 7.314708E-02 1.014833E+02 + 3.889998E+01 6.000000E+01 5 1.838428E+02 8.996265E+01 1.198407E-01 1.838428E+02 + 3.889998E+01 6.000000E+01 6 3.443210E+01 -2.515617E-04 3.443210E+01 -1.511769E-04 + 3.889998E+01 9.000000E+01 1 1.775305E-06 -9.002911E+01 -9.021112E-10 -1.775304E-06 + 3.889998E+01 9.000000E+01 2 3.638785E+01 8.995870E+01 2.622797E-02 3.638784E+01 + 3.889998E+01 9.000000E+01 3 1.967545E+02 1.634650E-01 1.967537E+02 5.613403E-01 + 3.889998E+01 9.000000E+01 4 1.176478E+02 8.995878E+01 8.464115E-02 1.176478E+02 + 3.889998E+01 9.000000E+01 5 8.268830E-05 -8.999559E+01 6.366200E-09 -8.268830E-05 + 3.889998E+01 9.000000E+01 6 2.951078E-06 1.799998E+02 -2.951078E-06 8.777554E-12 + 3.899998E+01 0.000000E+00 1 3.405686E+01 8.996285E+01 2.208090E-02 3.405685E+01 + 3.899998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.899998E+01 0.000000E+00 3 1.951421E+02 1.620051E-01 1.951413E+02 5.517677E-01 + 3.899998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.899998E+01 0.000000E+00 5 3.647970E+02 8.996285E+01 2.365089E-01 3.647969E+02 + 3.899998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.899998E+01 3.000000E+01 1 2.955007E+01 8.996285E+01 1.915849E-02 2.955006E+01 + 3.899998E+01 3.000000E+01 2 1.803357E+01 8.995893E+01 1.292512E-02 1.803357E+01 + 3.899998E+01 3.000000E+01 3 1.955587E+02 1.621533E-01 1.955579E+02 5.534516E-01 + 3.899998E+01 3.000000E+01 4 5.797203E+01 8.995879E+01 4.170631E-02 5.797201E+01 + 3.899998E+01 3.000000E+01 5 3.165098E+02 8.996285E+01 2.052068E-01 3.165097E+02 + 3.899998E+01 3.000000E+01 6 3.410376E+01 -2.491638E-04 3.410376E+01 -1.483080E-04 + 3.899998E+01 6.000000E+01 1 1.712564E+01 8.996285E+01 1.110271E-02 1.712564E+01 + 3.899998E+01 6.000000E+01 2 3.136529E+01 8.995893E+01 2.248104E-02 3.136529E+01 + 3.899998E+01 6.000000E+01 3 1.963934E+02 1.624531E-01 1.963926E+02 5.568416E-01 + 3.899998E+01 6.000000E+01 4 1.012081E+02 8.995893E+01 7.254077E-02 1.012081E+02 + 3.899998E+01 6.000000E+01 5 1.834148E+02 8.996285E+01 1.189201E-01 1.834147E+02 + 3.899998E+01 6.000000E+01 6 3.425019E+01 -2.488024E-04 3.425019E+01 -1.487288E-04 + 3.899998E+01 9.000000E+01 1 1.770651E-06 -9.002898E+01 -8.954974E-10 -1.770651E-06 + 3.899998E+01 9.000000E+01 2 3.629293E+01 8.995893E+01 2.601330E-02 3.629293E+01 + 3.899998E+01 9.000000E+01 3 1.968125E+02 1.626020E-01 1.968117E+02 5.585414E-01 + 3.899998E+01 9.000000E+01 4 1.173267E+02 8.995901E+01 8.393834E-02 1.173267E+02 + 3.899998E+01 9.000000E+01 5 8.247911E-05 -8.999562E+01 6.308041E-09 -8.247911E-05 + 3.899998E+01 9.000000E+01 6 2.935438E-06 1.799998E+02 -2.935438E-06 8.635521E-12 + 3.909998E+01 0.000000E+00 1 3.396978E+01 8.996305E+01 2.190661E-02 3.396977E+01 + 3.909998E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.909998E+01 0.000000E+00 3 1.952079E+02 1.611567E-01 1.952072E+02 5.490637E-01 + 3.909998E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.909998E+01 0.000000E+00 5 3.639585E+02 8.996305E+01 2.347051E-01 3.639584E+02 + 3.909998E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.909998E+01 3.000000E+01 1 2.947422E+01 8.996305E+01 1.900715E-02 2.947422E+01 + 3.909998E+01 3.000000E+01 2 1.798721E+01 8.995917E+01 1.282006E-02 1.798721E+01 + 3.909998E+01 3.000000E+01 3 1.956223E+02 1.613045E-01 1.956215E+02 5.507337E-01 + 3.909998E+01 3.000000E+01 4 5.781799E+01 8.995901E+01 4.136275E-02 5.781797E+01 + 3.909998E+01 3.000000E+01 5 3.157769E+02 8.996305E+01 2.036388E-01 3.157769E+02 + 3.909998E+01 3.000000E+01 6 3.392479E+01 -2.464363E-04 3.392479E+01 -1.459147E-04 + 3.909998E+01 6.000000E+01 1 1.708125E+01 8.996305E+01 1.101480E-02 1.708125E+01 + 3.909998E+01 6.000000E+01 2 3.128394E+01 8.995917E+01 2.229775E-02 3.128393E+01 + 3.909998E+01 6.000000E+01 3 1.964524E+02 1.616001E-01 1.964516E+02 5.540842E-01 + 3.909998E+01 6.000000E+01 4 1.009349E+02 8.995917E+01 7.194161E-02 1.009349E+02 + 3.909998E+01 6.000000E+01 5 1.829868E+02 8.996305E+01 1.180084E-01 1.829867E+02 + 3.909998E+01 6.000000E+01 6 3.406966E+01 -2.460813E-04 3.406966E+01 -1.463267E-04 + 3.909998E+01 9.000000E+01 1 1.766017E-06 -9.002884E+01 -8.889448E-10 -1.766017E-06 + 3.909998E+01 9.000000E+01 2 3.619840E+01 8.995917E+01 2.580091E-02 3.619839E+01 + 3.909998E+01 9.000000E+01 3 1.968699E+02 1.617472E-01 1.968691E+02 5.557670E-01 + 3.909998E+01 9.000000E+01 4 1.170073E+02 8.995924E+01 8.324438E-02 1.170073E+02 + 3.909998E+01 9.000000E+01 5 8.227113E-05 -8.999564E+01 6.250598E-09 -8.227113E-05 + 3.909998E+01 9.000000E+01 6 2.919919E-06 1.799998E+02 -2.919919E-06 8.496176E-12 + 3.919997E+01 0.000000E+00 1 3.388295E+01 8.996325E+01 2.173422E-02 3.388294E+01 + 3.919997E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.919997E+01 0.000000E+00 3 1.952734E+02 1.603131E-01 1.952726E+02 5.463727E-01 + 3.919997E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.919997E+01 0.000000E+00 5 3.631222E+02 8.996325E+01 2.329175E-01 3.631221E+02 + 3.919997E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.919997E+01 3.000000E+01 1 2.939861E+01 8.996325E+01 1.885731E-02 2.939861E+01 + 3.919997E+01 3.000000E+01 2 1.794117E+01 8.995939E+01 1.271612E-02 1.794117E+01 + 3.919997E+01 3.000000E+01 3 1.956850E+02 1.604601E-01 1.956842E+02 5.480261E-01 + 3.919997E+01 3.000000E+01 4 5.766457E+01 8.995924E+01 4.102307E-02 5.766455E+01 + 3.919997E+01 3.000000E+01 5 3.150517E+02 8.996325E+01 2.020848E-01 3.150516E+02 + 3.919997E+01 3.000000E+01 6 3.374725E+01 -2.437465E-04 3.374725E+01 -1.435669E-04 + 3.919997E+01 6.000000E+01 1 1.703708E+01 8.996325E+01 1.092779E-02 1.703708E+01 + 3.919997E+01 6.000000E+01 2 3.120308E+01 8.995939E+01 2.211652E-02 3.120308E+01 + 3.919997E+01 6.000000E+01 3 1.965120E+02 1.607524E-01 1.965112E+02 5.513449E-01 + 3.919997E+01 6.000000E+01 4 1.006631E+02 8.995939E+01 7.134892E-02 1.006630E+02 + 3.919997E+01 6.000000E+01 5 1.825623E+02 8.996325E+01 1.171067E-01 1.825623E+02 + 3.919997E+01 6.000000E+01 6 3.389055E+01 -2.433969E-04 3.389055E+01 -1.439697E-04 + 3.919997E+01 9.000000E+01 1 1.761410E-06 -9.002870E+01 -8.824554E-10 -1.761410E-06 + 3.919997E+01 9.000000E+01 2 3.610443E+01 8.995939E+01 2.559089E-02 3.610442E+01 + 3.919997E+01 9.000000E+01 3 1.969265E+02 1.608983E-01 1.969257E+02 5.530092E-01 + 3.919997E+01 9.000000E+01 4 1.166896E+02 8.995947E+01 8.255763E-02 1.166896E+02 + 3.919997E+01 9.000000E+01 5 8.206412E-05 -8.999567E+01 6.193852E-09 -8.206412E-05 + 3.919997E+01 9.000000E+01 6 2.904526E-06 1.799998E+02 -2.904526E-06 8.359447E-12 + 3.929997E+01 0.000000E+00 1 3.379663E+01 8.996344E+01 2.156364E-02 3.379663E+01 + 3.929997E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.929997E+01 0.000000E+00 3 1.953394E+02 1.594785E-01 1.953386E+02 5.437119E-01 + 3.929997E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.929997E+01 0.000000E+00 5 3.622920E+02 8.996345E+01 2.311483E-01 3.622919E+02 + 3.929997E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.929997E+01 3.000000E+01 1 2.932339E+01 8.996344E+01 1.870916E-02 2.932339E+01 + 3.929997E+01 3.000000E+01 2 1.789528E+01 8.995962E+01 1.261331E-02 1.789528E+01 + 3.929997E+01 3.000000E+01 3 1.957492E+02 1.596229E-01 1.957484E+02 5.453456E-01 + 3.929997E+01 3.000000E+01 4 5.751168E+01 8.995947E+01 4.068685E-02 5.751167E+01 + 3.929997E+01 3.000000E+01 5 3.143284E+02 8.996344E+01 2.005516E-01 3.143284E+02 + 3.929997E+01 3.000000E+01 6 3.357107E+01 -2.410939E-04 3.357107E+01 -1.412631E-04 + 3.929997E+01 6.000000E+01 1 1.699323E+01 8.996345E+01 1.084175E-02 1.699322E+01 + 3.929997E+01 6.000000E+01 2 3.112264E+01 8.995962E+01 2.193721E-02 3.112263E+01 + 3.929997E+01 6.000000E+01 3 1.965709E+02 1.599131E-01 1.965702E+02 5.486308E-01 + 3.929997E+01 6.000000E+01 4 1.003924E+02 8.995962E+01 7.076288E-02 1.003924E+02 + 3.929997E+01 6.000000E+01 5 1.821382E+02 8.996344E+01 1.162149E-01 1.821382E+02 + 3.929997E+01 6.000000E+01 6 3.371286E+01 -2.407503E-04 3.371286E+01 -1.416576E-04 + 3.929997E+01 9.000000E+01 1 1.756834E-06 -9.002857E+01 -8.760297E-10 -1.756833E-06 + 3.929997E+01 9.000000E+01 2 3.601104E+01 8.995962E+01 2.538322E-02 3.601103E+01 + 3.929997E+01 9.000000E+01 3 1.969830E+02 1.600578E-01 1.969823E+02 5.502785E-01 + 3.929997E+01 9.000000E+01 4 1.163734E+02 8.995969E+01 8.187878E-02 1.163734E+02 + 3.929997E+01 9.000000E+01 5 8.185828E-05 -8.999570E+01 6.137809E-09 -8.185828E-05 + 3.929997E+01 9.000000E+01 6 2.889259E-06 1.799998E+02 -2.889259E-06 8.225309E-12 + 3.939997E+01 0.000000E+00 1 3.371078E+01 8.996364E+01 2.139489E-02 3.371077E+01 + 3.939997E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.939997E+01 0.000000E+00 3 1.954022E+02 1.586507E-01 1.954014E+02 5.410634E-01 + 3.939997E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.939997E+01 0.000000E+00 5 3.614624E+02 8.996364E+01 2.293965E-01 3.614623E+02 + 3.939997E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.939997E+01 3.000000E+01 1 2.924857E+01 8.996364E+01 1.856255E-02 2.924856E+01 + 3.939997E+01 3.000000E+01 2 1.784966E+01 8.995984E+01 1.251166E-02 1.784965E+01 + 3.939997E+01 3.000000E+01 3 1.958103E+02 1.587934E-01 1.958095E+02 5.426812E-01 + 3.939997E+01 3.000000E+01 4 5.736006E+01 8.995969E+01 4.035443E-02 5.736004E+01 + 3.939997E+01 3.000000E+01 5 3.136049E+02 8.996364E+01 1.990298E-01 3.136048E+02 + 3.939997E+01 3.000000E+01 6 3.339635E+01 -2.384769E-04 3.339635E+01 -1.390025E-04 + 3.939997E+01 6.000000E+01 1 1.694951E+01 8.996364E+01 1.075653E-02 1.694951E+01 + 3.939997E+01 6.000000E+01 2 3.104264E+01 8.995984E+01 2.175990E-02 3.104263E+01 + 3.939997E+01 6.000000E+01 3 1.966287E+02 1.590798E-01 1.966279E+02 5.459322E-01 + 3.939997E+01 6.000000E+01 4 1.001236E+02 8.995984E+01 7.018323E-02 1.001236E+02 + 3.939997E+01 6.000000E+01 5 1.817164E+02 8.996364E+01 1.153312E-01 1.817164E+02 + 3.939997E+01 6.000000E+01 6 3.353666E+01 -2.381391E-04 3.353666E+01 -1.393888E-04 + 3.939997E+01 9.000000E+01 1 1.752274E-06 -9.002843E+01 -8.696640E-10 -1.752274E-06 + 3.939997E+01 9.000000E+01 2 3.591804E+01 8.995984E+01 2.517774E-02 3.591803E+01 + 3.939997E+01 9.000000E+01 3 1.970393E+02 1.592227E-01 1.970385E+02 5.475637E-01 + 3.939997E+01 9.000000E+01 4 1.160600E+02 8.995991E+01 8.120712E-02 1.160599E+02 + 3.939997E+01 9.000000E+01 5 8.165303E-05 -8.999574E+01 6.082472E-09 -8.165303E-05 + 3.939997E+01 9.000000E+01 6 2.874111E-06 1.799998E+02 -2.874111E-06 8.093693E-12 + 3.949997E+01 0.000000E+00 1 3.362540E+01 8.996383E+01 2.122781E-02 3.362540E+01 + 3.949997E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.949997E+01 0.000000E+00 3 1.954662E+02 1.578299E-01 1.954655E+02 5.384407E-01 + 3.949997E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.949997E+01 0.000000E+00 5 3.606382E+02 8.996383E+01 2.276646E-01 3.606382E+02 + 3.949997E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.949997E+01 3.000000E+01 1 2.917422E+01 8.996383E+01 1.841743E-02 2.917421E+01 + 3.949997E+01 3.000000E+01 2 1.780424E+01 8.996006E+01 1.241106E-02 1.780424E+01 + 3.949997E+01 3.000000E+01 3 1.958724E+02 1.579709E-01 1.958716E+02 5.400416E-01 + 3.949997E+01 3.000000E+01 4 5.720912E+01 8.995992E+01 4.002571E-02 5.720910E+01 + 3.949997E+01 3.000000E+01 5 3.128855E+02 8.996383E+01 1.975245E-01 3.128854E+02 + 3.949997E+01 3.000000E+01 6 3.322294E+01 -2.358966E-04 3.322294E+01 -1.367846E-04 + 3.949997E+01 6.000000E+01 1 1.690606E+01 8.996383E+01 1.067225E-02 1.690606E+01 + 3.949997E+01 6.000000E+01 2 3.096300E+01 8.996006E+01 2.158453E-02 3.096299E+01 + 3.949997E+01 6.000000E+01 3 1.966864E+02 1.582534E-01 1.966857E+02 5.432558E-01 + 3.949997E+01 6.000000E+01 4 9.985601E+01 8.996006E+01 6.961045E-02 9.985599E+01 + 3.949997E+01 6.000000E+01 5 1.812978E+02 8.996383E+01 1.144561E-01 1.812977E+02 + 3.949997E+01 6.000000E+01 6 3.336178E+01 -2.355634E-04 3.336178E+01 -1.371622E-04 + 3.949997E+01 9.000000E+01 1 1.747740E-06 -9.002830E+01 -8.633546E-10 -1.747740E-06 + 3.949997E+01 9.000000E+01 2 3.582547E+01 8.996006E+01 2.497452E-02 3.582546E+01 + 3.949997E+01 9.000000E+01 3 1.970947E+02 1.583952E-01 1.970939E+02 5.448712E-01 + 3.949997E+01 9.000000E+01 4 1.157473E+02 8.996013E+01 8.054294E-02 1.157473E+02 + 3.949997E+01 9.000000E+01 5 8.144906E-05 -8.999577E+01 6.027777E-09 -8.144906E-05 + 3.949997E+01 9.000000E+01 6 2.859083E-06 1.799998E+02 -2.859083E-06 7.964525E-12 + 3.959997E+01 0.000000E+00 1 3.354033E+01 8.996402E+01 2.106253E-02 3.354033E+01 + 3.959997E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.959997E+01 0.000000E+00 3 1.955294E+02 1.570129E-01 1.955287E+02 5.358268E-01 + 3.959997E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.959997E+01 0.000000E+00 5 3.598151E+02 8.996402E+01 2.259508E-01 3.598151E+02 + 3.959997E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.959997E+01 3.000000E+01 1 2.910024E+01 8.996402E+01 1.827392E-02 2.910023E+01 + 3.959997E+01 3.000000E+01 2 1.775911E+01 8.996028E+01 1.231158E-02 1.775911E+01 + 3.959997E+01 3.000000E+01 3 1.959340E+02 1.571523E-01 1.959333E+02 5.374121E-01 + 3.959997E+01 3.000000E+01 4 5.705909E+01 8.996014E+01 3.970068E-02 5.705908E+01 + 3.959997E+01 3.000000E+01 5 3.121678E+02 8.996402E+01 1.960340E-01 3.121678E+02 + 3.959997E+01 3.000000E+01 6 3.305095E+01 -2.333516E-04 3.305095E+01 -1.346084E-04 + 3.959997E+01 6.000000E+01 1 1.686282E+01 8.996402E+01 1.058887E-02 1.686282E+01 + 3.959997E+01 6.000000E+01 2 3.088385E+01 8.996028E+01 2.141110E-02 3.088384E+01 + 3.959997E+01 6.000000E+01 3 1.967436E+02 1.574331E-01 1.967428E+02 5.405967E-01 + 3.959997E+01 6.000000E+01 4 9.959005E+01 8.996028E+01 6.904355E-02 9.959003E+01 + 3.959997E+01 6.000000E+01 5 1.808781E+02 8.996402E+01 1.135908E-01 1.808781E+02 + 3.959997E+01 6.000000E+01 6 3.318834E+01 -2.330239E-04 3.318834E+01 -1.349781E-04 + 3.959997E+01 9.000000E+01 1 1.743232E-06 -9.002817E+01 -8.571087E-10 -1.743231E-06 + 3.959997E+01 9.000000E+01 2 3.573349E+01 8.996028E+01 2.477355E-02 3.573348E+01 + 3.959997E+01 9.000000E+01 3 1.971499E+02 1.575725E-01 1.971491E+02 5.421928E-01 + 3.959997E+01 9.000000E+01 4 1.154367E+02 8.996035E+01 7.988608E-02 1.154367E+02 + 3.959997E+01 9.000000E+01 5 8.124601E-05 -8.999579E+01 5.973753E-09 -8.124601E-05 + 3.959997E+01 9.000000E+01 6 2.844173E-06 1.799998E+02 -2.844173E-06 7.837810E-12 + 3.969997E+01 0.000000E+00 1 3.345576E+01 8.996420E+01 2.089904E-02 3.345575E+01 + 3.969997E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.969997E+01 0.000000E+00 3 1.955931E+02 1.562038E-01 1.955923E+02 5.332388E-01 + 3.969997E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.969997E+01 0.000000E+00 5 3.590002E+02 8.996421E+01 2.242514E-01 3.590001E+02 + 3.969997E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.969997E+01 3.000000E+01 1 2.902649E+01 8.996421E+01 1.813183E-02 2.902649E+01 + 3.969997E+01 3.000000E+01 2 1.771418E+01 8.996049E+01 1.221318E-02 1.771418E+01 + 3.969997E+01 3.000000E+01 3 1.959948E+02 1.563422E-01 1.959940E+02 5.348075E-01 + 3.969997E+01 3.000000E+01 4 5.690964E+01 8.996036E+01 3.937916E-02 5.690963E+01 + 3.969997E+01 3.000000E+01 5 3.114583E+02 8.996421E+01 1.945570E-01 3.114583E+02 + 3.969997E+01 3.000000E+01 6 3.288022E+01 -2.308407E-04 3.288022E+01 -1.324721E-04 + 3.969997E+01 6.000000E+01 1 1.681982E+01 8.996421E+01 1.050632E-02 1.681982E+01 + 3.969997E+01 6.000000E+01 2 3.080498E+01 8.996049E+01 2.123948E-02 3.080497E+01 + 3.969997E+01 6.000000E+01 3 1.968004E+02 1.566199E-01 1.967996E+02 5.379595E-01 + 3.969997E+01 6.000000E+01 4 9.932550E+01 8.996049E+01 6.848279E-02 9.932548E+01 + 3.969997E+01 6.000000E+01 5 1.804632E+02 8.996420E+01 1.127336E-01 1.804632E+02 + 3.969997E+01 6.000000E+01 6 3.301622E+01 -2.305184E-04 3.301622E+01 -1.328343E-04 + 3.969997E+01 9.000000E+01 1 1.738743E-06 -9.002804E+01 -8.509217E-10 -1.738743E-06 + 3.969997E+01 9.000000E+01 2 3.564193E+01 8.996049E+01 2.457472E-02 3.564192E+01 + 3.969997E+01 9.000000E+01 3 1.972052E+02 1.567585E-01 1.972045E+02 5.395434E-01 + 3.969997E+01 9.000000E+01 4 1.151276E+02 8.996056E+01 7.923673E-02 1.151276E+02 + 3.969997E+01 9.000000E+01 5 8.104412E-05 -8.999582E+01 5.920403E-09 -8.104412E-05 + 3.969997E+01 9.000000E+01 6 2.829380E-06 1.799998E+02 -2.829380E-06 7.713447E-12 + 3.979996E+01 0.000000E+00 1 3.337165E+01 8.996440E+01 2.073719E-02 3.337165E+01 + 3.979996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.979996E+01 0.000000E+00 3 1.956555E+02 1.554000E-01 1.956548E+02 5.306646E-01 + 3.979996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.979996E+01 0.000000E+00 5 3.581830E+02 8.996440E+01 2.225686E-01 3.581829E+02 + 3.979996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.979996E+01 3.000000E+01 1 2.895323E+01 8.996440E+01 1.799129E-02 2.895322E+01 + 3.979996E+01 3.000000E+01 2 1.766949E+01 8.996072E+01 1.211583E-02 1.766948E+01 + 3.979996E+01 3.000000E+01 3 1.960547E+02 1.555372E-01 1.960539E+02 5.322164E-01 + 3.979996E+01 3.000000E+01 4 5.676097E+01 8.996057E+01 3.906113E-02 5.676096E+01 + 3.979996E+01 3.000000E+01 5 3.107473E+02 8.996440E+01 1.930959E-01 3.107473E+02 + 3.979996E+01 3.000000E+01 6 3.271090E+01 -2.283640E-04 3.271090E+01 -1.303760E-04 + 3.979996E+01 6.000000E+01 1 1.677704E+01 8.996440E+01 1.042467E-02 1.677704E+01 + 3.979996E+01 6.000000E+01 2 3.072663E+01 8.996071E+01 2.106973E-02 3.072662E+01 + 3.979996E+01 6.000000E+01 3 1.968573E+02 1.558108E-01 1.968566E+02 5.353352E-01 + 3.979996E+01 6.000000E+01 4 9.906238E+01 8.996071E+01 6.792869E-02 9.906236E+01 + 3.979996E+01 6.000000E+01 5 1.800471E+02 8.996440E+01 1.118849E-01 1.800470E+02 + 3.979996E+01 6.000000E+01 6 3.284549E+01 -2.280467E-04 3.284549E+01 -1.307305E-04 + 3.979996E+01 9.000000E+01 1 1.734281E-06 -9.002791E+01 -8.447912E-10 -1.734280E-06 + 3.979996E+01 9.000000E+01 2 3.555087E+01 8.996071E+01 2.437809E-02 3.555086E+01 + 3.979996E+01 9.000000E+01 3 1.972593E+02 1.559485E-01 1.972585E+02 5.369024E-01 + 3.979996E+01 9.000000E+01 4 1.148204E+02 8.996078E+01 7.859468E-02 1.148204E+02 + 3.979996E+01 9.000000E+01 5 8.084311E-05 -8.999584E+01 5.867694E-09 -8.084311E-05 + 3.979996E+01 9.000000E+01 6 2.814705E-06 1.799998E+02 -2.814705E-06 7.591388E-12 + 3.989996E+01 0.000000E+00 1 3.328785E+01 8.996458E+01 2.057702E-02 3.328784E+01 + 3.989996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.989996E+01 0.000000E+00 3 1.957177E+02 1.546028E-01 1.957170E+02 5.281100E-01 + 3.989996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.989996E+01 0.000000E+00 5 3.573719E+02 8.996458E+01 2.209041E-01 3.573719E+02 + 3.989996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.989996E+01 3.000000E+01 1 2.888029E+01 8.996458E+01 1.785210E-02 2.888028E+01 + 3.989996E+01 3.000000E+01 2 1.762500E+01 8.996093E+01 1.201955E-02 1.762499E+01 + 3.989996E+01 3.000000E+01 3 1.961149E+02 1.547392E-01 1.961142E+02 5.296485E-01 + 3.989996E+01 3.000000E+01 4 5.661314E+01 8.996078E+01 3.874672E-02 5.661313E+01 + 3.989996E+01 3.000000E+01 5 3.100419E+02 8.996458E+01 1.916507E-01 3.100419E+02 + 3.989996E+01 3.000000E+01 6 3.254287E+01 -2.259212E-04 3.254287E+01 -1.283188E-04 + 3.989996E+01 6.000000E+01 1 1.673446E+01 8.996458E+01 1.034388E-02 1.673446E+01 + 3.989996E+01 6.000000E+01 2 3.064868E+01 8.996093E+01 2.090178E-02 3.064867E+01 + 3.989996E+01 6.000000E+01 3 1.969134E+02 1.550093E-01 1.969127E+02 5.327333E-01 + 3.989996E+01 6.000000E+01 4 9.880065E+01 8.996093E+01 6.738003E-02 9.880063E+01 + 3.989996E+01 6.000000E+01 5 1.796355E+02 8.996458E+01 1.110448E-01 1.796355E+02 + 3.989996E+01 6.000000E+01 6 3.267602E+01 -2.256090E-04 3.267602E+01 -1.286658E-04 + 3.989996E+01 9.000000E+01 1 1.729837E-06 -9.002778E+01 -8.387184E-10 -1.729837E-06 + 3.989996E+01 9.000000E+01 2 3.546024E+01 8.996093E+01 2.418354E-02 3.546024E+01 + 3.989996E+01 9.000000E+01 3 1.973143E+02 1.551450E-01 1.973135E+02 5.342851E-01 + 3.989996E+01 9.000000E+01 4 1.145147E+02 8.996100E+01 7.795913E-02 1.145147E+02 + 3.989996E+01 9.000000E+01 5 8.064335E-05 -8.999587E+01 5.815583E-09 -8.064335E-05 + 3.989996E+01 9.000000E+01 6 2.800145E-06 1.799998E+02 -2.800145E-06 7.471601E-12 + 3.999996E+01 0.000000E+00 1 3.320465E+01 8.996477E+01 2.041850E-02 3.320465E+01 + 3.999996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.999996E+01 0.000000E+00 3 1.957785E+02 1.538118E-01 1.957778E+02 5.255712E-01 + 3.999996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.999996E+01 0.000000E+00 5 3.565649E+02 8.996477E+01 2.192550E-01 3.565648E+02 + 3.999996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 3.999996E+01 3.000000E+01 1 2.880771E+01 8.996477E+01 1.771444E-02 2.880770E+01 + 3.999996E+01 3.000000E+01 2 1.758072E+01 8.996114E+01 1.192426E-02 1.758072E+01 + 3.999996E+01 3.000000E+01 3 1.961747E+02 1.539455E-01 1.961740E+02 5.270925E-01 + 3.999996E+01 3.000000E+01 4 5.646617E+01 8.996101E+01 3.843560E-02 5.646616E+01 + 3.999996E+01 3.000000E+01 5 3.093363E+02 8.996477E+01 1.902190E-01 3.093362E+02 + 3.999996E+01 3.000000E+01 6 3.237609E+01 -2.235112E-04 3.237609E+01 -1.262993E-04 + 3.999996E+01 6.000000E+01 1 1.669209E+01 8.996478E+01 1.026392E-02 1.669209E+01 + 3.999996E+01 6.000000E+01 2 3.057104E+01 8.996114E+01 2.073569E-02 3.057104E+01 + 3.999996E+01 6.000000E+01 3 1.969688E+02 1.542149E-01 1.969681E+02 5.301523E-01 + 3.999996E+01 6.000000E+01 4 9.854043E+01 8.996114E+01 6.683791E-02 9.854041E+01 + 3.999996E+01 6.000000E+01 5 1.792234E+02 8.996477E+01 1.102135E-01 1.792234E+02 + 3.999996E+01 6.000000E+01 6 3.250790E+01 -2.232043E-04 3.250790E+01 -1.266394E-04 + 3.999996E+01 9.000000E+01 1 1.725425E-06 -9.002765E+01 -8.327025E-10 -1.725425E-06 + 3.999996E+01 9.000000E+01 2 3.537007E+01 8.996114E+01 2.399109E-02 3.537006E+01 + 3.999996E+01 9.000000E+01 3 1.973673E+02 1.543482E-01 1.973666E+02 5.316841E-01 + 3.999996E+01 9.000000E+01 4 1.142105E+02 8.996120E+01 7.733064E-02 1.142104E+02 + 3.999996E+01 9.000000E+01 5 8.044456E-05 -8.999590E+01 5.764136E-09 -8.044456E-05 + 3.999996E+01 9.000000E+01 6 2.785697E-06 1.799999E+02 -2.785697E-06 7.354008E-12 + 4.009996E+01 0.000000E+00 1 3.312164E+01 8.996495E+01 2.026160E-02 3.312163E+01 + 4.009996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.009996E+01 0.000000E+00 3 1.958400E+02 1.530287E-01 1.958392E+02 5.230594E-01 + 4.009996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.009996E+01 0.000000E+00 5 3.557611E+02 8.996495E+01 2.176235E-01 3.557611E+02 + 4.009996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.009996E+01 3.000000E+01 1 2.873561E+01 8.996495E+01 1.757813E-02 2.873560E+01 + 4.009996E+01 3.000000E+01 2 1.753668E+01 8.996135E+01 1.183001E-02 1.753667E+01 + 4.009996E+01 3.000000E+01 3 1.962338E+02 1.531619E-01 1.962331E+02 5.245677E-01 + 4.009996E+01 3.000000E+01 4 5.631999E+01 8.996121E+01 3.812789E-02 5.631998E+01 + 4.009996E+01 3.000000E+01 5 3.086360E+02 8.996495E+01 1.887998E-01 3.086359E+02 + 4.009996E+01 3.000000E+01 6 3.221068E+01 -2.211336E-04 3.221068E+01 -1.243174E-04 + 4.009996E+01 6.000000E+01 1 1.665001E+01 8.996495E+01 1.018477E-02 1.665000E+01 + 4.009996E+01 6.000000E+01 2 3.049393E+01 8.996135E+01 2.057135E-02 3.049392E+01 + 4.009996E+01 6.000000E+01 3 1.970240E+02 1.534273E-01 1.970233E+02 5.275925E-01 + 4.009996E+01 6.000000E+01 4 9.828146E+01 8.996135E+01 6.630120E-02 9.828143E+01 + 4.009996E+01 6.000000E+01 5 1.788146E+02 8.996495E+01 1.093894E-01 1.788146E+02 + 4.009996E+01 6.000000E+01 6 3.234111E+01 -2.208314E-04 3.234111E+01 -1.246502E-04 + 4.009996E+01 9.000000E+01 1 1.721028E-06 -9.002752E+01 -8.267444E-10 -1.721028E-06 + 4.009996E+01 9.000000E+01 2 3.528042E+01 8.996135E+01 2.380072E-02 3.528041E+01 + 4.009996E+01 9.000000E+01 3 1.974205E+02 1.535598E-01 1.974198E+02 5.291107E-01 + 4.009996E+01 9.000000E+01 4 1.139085E+02 8.996142E+01 7.670912E-02 1.139085E+02 + 4.009996E+01 9.000000E+01 5 8.024606E-05 -8.999592E+01 5.713281E-09 -8.024606E-05 + 4.009996E+01 9.000000E+01 6 2.771365E-06 1.799999E+02 -2.771365E-06 7.238607E-12 + 4.019996E+01 0.000000E+00 1 3.303928E+01 8.996513E+01 2.010638E-02 3.303927E+01 + 4.019996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.019996E+01 0.000000E+00 3 1.959009E+02 1.522496E-01 1.959002E+02 5.205586E-01 + 4.019996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.019996E+01 0.000000E+00 5 3.549574E+02 8.996513E+01 2.160077E-01 3.549573E+02 + 4.019996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.019996E+01 3.000000E+01 1 2.866374E+01 8.996513E+01 1.744330E-02 2.866374E+01 + 4.019996E+01 3.000000E+01 2 1.749287E+01 8.996156E+01 1.173675E-02 1.749286E+01 + 4.019996E+01 3.000000E+01 3 1.962927E+02 1.523809E-01 1.962921E+02 5.220496E-01 + 4.019996E+01 3.000000E+01 4 5.617453E+01 8.996142E+01 3.782352E-02 5.617452E+01 + 4.019996E+01 3.000000E+01 5 3.079387E+02 8.996513E+01 1.873970E-01 3.079387E+02 + 4.019996E+01 3.000000E+01 6 3.204650E+01 -2.187878E-04 3.204650E+01 -1.223717E-04 + 4.019996E+01 6.000000E+01 1 1.660806E+01 8.996513E+01 1.010648E-02 1.660806E+01 + 4.019996E+01 6.000000E+01 2 3.041706E+01 8.996156E+01 2.040876E-02 3.041706E+01 + 4.019996E+01 6.000000E+01 3 1.970783E+02 1.526451E-01 1.970776E+02 5.250474E-01 + 4.019996E+01 6.000000E+01 4 9.802399E+01 8.996156E+01 6.577053E-02 9.802396E+01 + 4.019996E+01 6.000000E+01 5 1.784067E+02 8.996513E+01 1.085742E-01 1.784067E+02 + 4.019996E+01 6.000000E+01 6 3.217555E+01 -2.184905E-04 3.217555E+01 -1.226976E-04 + 4.019996E+01 9.000000E+01 1 1.716656E-06 -9.002740E+01 -8.208414E-10 -1.716656E-06 + 4.019996E+01 9.000000E+01 2 3.519121E+01 8.996156E+01 2.361234E-02 3.519120E+01 + 4.019996E+01 9.000000E+01 3 1.974738E+02 1.527754E-01 1.974731E+02 5.265502E-01 + 4.019996E+01 9.000000E+01 4 1.136077E+02 8.996162E+01 7.609409E-02 1.136077E+02 + 4.019996E+01 9.000000E+01 5 8.004906E-05 -8.999595E+01 5.663037E-09 -8.004906E-05 + 4.019996E+01 9.000000E+01 6 2.757139E-06 1.799999E+02 -2.757139E-06 7.125311E-12 + 4.029996E+01 0.000000E+00 1 3.295703E+01 8.996532E+01 1.995263E-02 3.295702E+01 + 4.029996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.029996E+01 0.000000E+00 3 1.959606E+02 1.514774E-01 1.959600E+02 5.180761E-01 + 4.029996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.029996E+01 0.000000E+00 5 3.541636E+02 8.996532E+01 2.144059E-01 3.541636E+02 + 4.029996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.029996E+01 3.000000E+01 1 2.859224E+01 8.996532E+01 1.730978E-02 2.859224E+01 + 4.029996E+01 3.000000E+01 2 1.744927E+01 8.996177E+01 1.164448E-02 1.744927E+01 + 4.029996E+01 3.000000E+01 3 1.963510E+02 1.516075E-01 1.963503E+02 5.195538E-01 + 4.029996E+01 3.000000E+01 4 5.602977E+01 8.996163E+01 3.752217E-02 5.602976E+01 + 4.029996E+01 3.000000E+01 5 3.072437E+02 8.996532E+01 1.860085E-01 3.072437E+02 + 4.029996E+01 3.000000E+01 6 3.188359E+01 -2.164738E-04 3.188359E+01 -1.204619E-04 + 4.029996E+01 6.000000E+01 1 1.656636E+01 8.996532E+01 1.002894E-02 1.656636E+01 + 4.029996E+01 6.000000E+01 2 3.034069E+01 8.996176E+01 2.024794E-02 3.034068E+01 + 4.029996E+01 6.000000E+01 3 1.971331E+02 1.518685E-01 1.971324E+02 5.225213E-01 + 4.029996E+01 6.000000E+01 4 9.776756E+01 8.996176E+01 6.524529E-02 9.776753E+01 + 4.029996E+01 6.000000E+01 5 1.780007E+02 8.996532E+01 1.077677E-01 1.780007E+02 + 4.029996E+01 6.000000E+01 6 3.201136E+01 -2.161809E-04 3.201136E+01 -1.207811E-04 + 4.029996E+01 9.000000E+01 1 1.712306E-06 -9.002727E+01 -8.149911E-10 -1.712306E-06 + 4.029996E+01 9.000000E+01 2 3.510244E+01 8.996176E+01 2.342605E-02 3.510243E+01 + 4.029996E+01 9.000000E+01 3 1.975260E+02 1.519973E-01 1.975253E+02 5.240071E-01 + 4.029996E+01 9.000000E+01 4 1.133087E+02 8.996183E+01 7.548621E-02 1.133086E+02 + 4.029996E+01 9.000000E+01 5 7.985276E-05 -8.999597E+01 5.613394E-09 -7.985276E-05 + 4.029996E+01 9.000000E+01 6 2.743030E-06 1.799999E+02 -2.743030E-06 7.014102E-12 + 4.039996E+01 0.000000E+00 1 3.287546E+01 8.996549E+01 1.980058E-02 3.287545E+01 + 4.039996E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.039996E+01 0.000000E+00 3 1.960204E+02 1.507102E-01 1.960197E+02 5.156092E-01 + 4.039996E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.039996E+01 0.000000E+00 5 3.533676E+02 8.996549E+01 2.128220E-01 3.533676E+02 + 4.039996E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.039996E+01 3.000000E+01 1 2.852114E+01 8.996549E+01 1.717774E-02 2.852114E+01 + 4.039996E+01 3.000000E+01 2 1.740592E+01 8.996198E+01 1.155320E-02 1.740591E+01 + 4.039996E+01 3.000000E+01 3 1.964086E+02 1.508387E-01 1.964080E+02 5.170711E-01 + 4.039996E+01 3.000000E+01 4 5.588592E+01 8.996184E+01 3.722446E-02 5.588591E+01 + 4.039996E+01 3.000000E+01 5 3.065521E+02 8.996549E+01 1.846313E-01 3.065520E+02 + 4.039996E+01 3.000000E+01 6 3.172192E+01 -2.141900E-04 3.172192E+01 -1.185867E-04 + 4.039996E+01 6.000000E+01 1 1.652482E+01 8.996550E+01 9.952208E-03 1.652481E+01 + 4.039996E+01 6.000000E+01 2 3.026465E+01 8.996198E+01 2.008883E-02 3.026465E+01 + 4.039996E+01 6.000000E+01 3 1.971876E+02 1.510966E-01 1.971869E+02 5.200093E-01 + 4.039996E+01 6.000000E+01 4 9.751318E+01 8.996198E+01 6.472613E-02 9.751316E+01 + 4.039996E+01 6.000000E+01 5 1.775966E+02 8.996549E+01 1.069684E-01 1.775965E+02 + 4.039996E+01 6.000000E+01 6 3.184841E+01 -2.139018E-04 3.184841E+01 -1.188994E-04 + 4.039996E+01 9.000000E+01 1 1.707981E-06 -9.002715E+01 -8.092000E-10 -1.707981E-06 + 4.039996E+01 9.000000E+01 2 3.501406E+01 8.996197E+01 2.324169E-02 3.501406E+01 + 4.039996E+01 9.000000E+01 3 1.975780E+02 1.512246E-01 1.975773E+02 5.214803E-01 + 4.039996E+01 9.000000E+01 4 1.130111E+02 8.996204E+01 7.488450E-02 1.130111E+02 + 4.039996E+01 9.000000E+01 5 7.965770E-05 -8.999600E+01 5.564346E-09 -7.965770E-05 + 4.039996E+01 9.000000E+01 6 2.729023E-06 1.799999E+02 -2.729023E-06 6.904941E-12 + 4.049995E+01 0.000000E+00 1 3.279421E+01 8.996567E+01 1.964999E-02 3.279420E+01 + 4.049995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.049995E+01 0.000000E+00 3 1.960799E+02 1.499503E-01 1.960792E+02 5.131652E-01 + 4.049995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.049995E+01 0.000000E+00 5 3.525754E+02 8.996567E+01 2.112527E-01 3.525753E+02 + 4.049995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.049995E+01 3.000000E+01 1 2.845046E+01 8.996567E+01 1.704697E-02 2.845045E+01 + 4.049995E+01 3.000000E+01 2 1.736274E+01 8.996217E+01 1.146286E-02 1.736274E+01 + 4.049995E+01 3.000000E+01 3 1.964659E+02 1.500772E-01 1.964653E+02 5.146107E-01 + 4.049995E+01 3.000000E+01 4 5.574275E+01 8.996204E+01 3.692957E-02 5.574274E+01 + 4.049995E+01 3.000000E+01 5 3.058630E+02 8.996567E+01 1.832678E-01 3.058629E+02 + 4.049995E+01 3.000000E+01 6 3.156149E+01 -2.119369E-04 3.156149E+01 -1.167458E-04 + 4.049995E+01 6.000000E+01 1 1.648354E+01 8.996568E+01 9.876294E-03 1.648354E+01 + 4.049995E+01 6.000000E+01 2 3.018898E+01 8.996217E+01 1.993131E-02 3.018898E+01 + 4.049995E+01 6.000000E+01 3 1.972407E+02 1.503313E-01 1.972400E+02 5.175146E-01 + 4.049995E+01 6.000000E+01 4 9.725953E+01 8.996217E+01 6.421261E-02 9.725951E+01 + 4.049995E+01 6.000000E+01 5 1.771948E+02 8.996567E+01 1.061767E-01 1.771948E+02 + 4.049995E+01 6.000000E+01 6 3.168669E+01 -2.116531E-04 3.168669E+01 -1.170520E-04 + 4.049995E+01 9.000000E+01 1 1.703676E-06 -9.002702E+01 -8.034552E-10 -1.703675E-06 + 4.049995E+01 9.000000E+01 2 3.492622E+01 8.996217E+01 2.305922E-02 3.492622E+01 + 4.049995E+01 9.000000E+01 3 1.976297E+02 1.504593E-01 1.976290E+02 5.189769E-01 + 4.049995E+01 9.000000E+01 4 1.127156E+02 8.996224E+01 7.428924E-02 1.127155E+02 + 4.049995E+01 9.000000E+01 5 7.946385E-05 -8.999603E+01 5.515868E-09 -7.946385E-05 + 4.049995E+01 9.000000E+01 6 2.715130E-06 1.799999E+02 -2.715130E-06 6.797745E-12 + 4.059995E+01 0.000000E+00 1 3.271325E+01 8.996584E+01 1.950096E-02 3.271324E+01 + 4.059995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.059995E+01 0.000000E+00 3 1.961385E+02 1.491946E-01 1.961378E+02 5.107317E-01 + 4.059995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.059995E+01 0.000000E+00 5 3.517873E+02 8.996584E+01 2.096995E-01 3.517872E+02 + 4.059995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.059995E+01 3.000000E+01 1 2.837998E+01 8.996584E+01 1.691754E-02 2.837998E+01 + 4.059995E+01 3.000000E+01 2 1.731980E+01 8.996238E+01 1.137349E-02 1.731979E+01 + 4.059995E+01 3.000000E+01 3 1.965233E+02 1.493207E-01 1.965226E+02 5.121662E-01 + 4.059995E+01 3.000000E+01 4 5.560034E+01 8.996225E+01 3.663821E-02 5.560033E+01 + 4.059995E+01 3.000000E+01 5 3.051753E+02 8.996584E+01 1.819187E-01 3.051753E+02 + 4.059995E+01 3.000000E+01 6 3.140228E+01 -2.097140E-04 3.140228E+01 -1.149386E-04 + 4.059995E+01 6.000000E+01 1 1.644245E+01 8.996584E+01 9.801122E-03 1.644245E+01 + 4.059995E+01 6.000000E+01 2 3.011368E+01 8.996238E+01 1.977553E-02 3.011367E+01 + 4.059995E+01 6.000000E+01 3 1.972942E+02 1.495721E-01 1.972936E+02 5.150411E-01 + 4.059995E+01 6.000000E+01 4 9.700747E+01 8.996238E+01 6.370434E-02 9.700745E+01 + 4.059995E+01 6.000000E+01 5 1.767935E+02 8.996584E+01 1.053927E-01 1.767935E+02 + 4.059995E+01 6.000000E+01 6 3.152621E+01 -2.094345E-04 3.152621E+01 -1.152385E-04 + 4.059995E+01 9.000000E+01 1 1.699390E-06 -9.002690E+01 -7.977697E-10 -1.699390E-06 + 4.059995E+01 9.000000E+01 2 3.483888E+01 8.996238E+01 2.287880E-02 3.483887E+01 + 4.059995E+01 9.000000E+01 3 1.976806E+02 1.496988E-01 1.976799E+02 5.164867E-01 + 4.059995E+01 9.000000E+01 4 1.124213E+02 8.996244E+01 7.370064E-02 1.124213E+02 + 4.059995E+01 9.000000E+01 5 7.927052E-05 -8.999605E+01 5.467943E-09 -7.927052E-05 + 4.059995E+01 9.000000E+01 6 2.701340E-06 1.799999E+02 -2.701340E-06 6.692506E-12 + 4.069995E+01 0.000000E+00 1 3.263289E+01 8.996603E+01 1.935353E-02 3.263288E+01 + 4.069995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.069995E+01 0.000000E+00 3 1.961976E+02 1.484455E-01 1.961970E+02 5.083206E-01 + 4.069995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.069995E+01 0.000000E+00 5 3.510041E+02 8.996603E+01 2.081631E-01 3.510041E+02 + 4.069995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.069995E+01 3.000000E+01 1 2.830993E+01 8.996603E+01 1.678942E-02 2.830993E+01 + 4.069995E+01 3.000000E+01 2 1.727706E+01 8.996258E+01 1.128505E-02 1.727706E+01 + 4.069995E+01 3.000000E+01 3 1.965800E+02 1.485692E-01 1.965794E+02 5.097358E-01 + 4.069995E+01 3.000000E+01 4 5.545845E+01 8.996245E+01 3.634970E-02 5.545844E+01 + 4.069995E+01 3.000000E+01 5 3.044943E+02 8.996603E+01 1.805845E-01 3.044942E+02 + 4.069995E+01 3.000000E+01 6 3.124430E+01 -2.075199E-04 3.124430E+01 -1.131639E-04 + 4.069995E+01 6.000000E+01 1 1.640158E+01 8.996603E+01 9.726741E-03 1.640157E+01 + 4.069995E+01 6.000000E+01 2 3.003879E+01 8.996258E+01 1.962136E-02 3.003879E+01 + 4.069995E+01 6.000000E+01 3 1.973477E+02 1.488191E-01 1.973470E+02 5.125871E-01 + 4.069995E+01 6.000000E+01 4 9.675658E+01 8.996258E+01 6.320155E-02 9.675656E+01 + 4.069995E+01 6.000000E+01 5 1.763951E+02 8.996603E+01 1.046166E-01 1.763950E+02 + 4.069995E+01 6.000000E+01 6 3.136693E+01 -2.072453E-04 3.136693E+01 -1.134577E-04 + 4.069995E+01 9.000000E+01 1 1.695126E-06 -9.002678E+01 -7.921360E-10 -1.695126E-06 + 4.069995E+01 9.000000E+01 2 3.475193E+01 8.996258E+01 2.270026E-02 3.475192E+01 + 4.069995E+01 9.000000E+01 3 1.977326E+02 1.489436E-01 1.977319E+02 5.140165E-01 + 4.069995E+01 9.000000E+01 4 1.121284E+02 8.996264E+01 7.311802E-02 1.121284E+02 + 4.069995E+01 9.000000E+01 5 7.907810E-05 -8.999608E+01 5.420604E-09 -7.907810E-05 + 4.069995E+01 9.000000E+01 6 2.687661E-06 1.799999E+02 -2.687661E-06 6.589171E-12 + 4.079995E+01 0.000000E+00 1 3.255276E+01 8.996619E+01 1.920751E-02 3.255275E+01 + 4.079995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.079995E+01 0.000000E+00 3 1.962558E+02 1.477009E-01 1.962551E+02 5.059208E-01 + 4.079995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.079995E+01 0.000000E+00 5 3.502239E+02 8.996619E+01 2.066392E-01 3.502238E+02 + 4.079995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.079995E+01 3.000000E+01 1 2.824017E+01 8.996619E+01 1.666256E-02 2.824016E+01 + 4.079995E+01 3.000000E+01 2 1.723453E+01 8.996277E+01 1.119755E-02 1.723453E+01 + 4.079995E+01 3.000000E+01 3 1.966361E+02 1.478246E-01 1.966355E+02 5.073256E-01 + 4.079995E+01 3.000000E+01 4 5.531755E+01 8.996265E+01 3.606433E-02 5.531754E+01 + 4.079995E+01 3.000000E+01 5 3.038132E+02 8.996619E+01 1.792597E-01 3.038131E+02 + 4.079995E+01 3.000000E+01 6 3.108752E+01 -2.053552E-04 3.108752E+01 -1.114216E-04 + 4.079995E+01 6.000000E+01 1 1.636086E+01 8.996619E+01 9.653110E-03 1.636086E+01 + 4.079995E+01 6.000000E+01 2 2.996427E+01 8.996277E+01 1.946885E-02 2.996426E+01 + 4.079995E+01 6.000000E+01 3 1.973997E+02 1.480717E-01 1.973990E+02 5.101469E-01 + 4.079995E+01 6.000000E+01 4 9.650729E+01 8.996277E+01 6.270389E-02 9.650727E+01 + 4.079995E+01 6.000000E+01 5 1.759977E+02 8.996619E+01 1.038493E-01 1.759977E+02 + 4.079995E+01 6.000000E+01 6 3.120890E+01 -2.050848E-04 3.120890E+01 -1.117093E-04 + 4.079995E+01 9.000000E+01 1 1.690887E-06 -9.002666E+01 -7.865527E-10 -1.690886E-06 + 4.079995E+01 9.000000E+01 2 3.466522E+01 8.996277E+01 2.252354E-02 3.466521E+01 + 4.079995E+01 9.000000E+01 3 1.977833E+02 1.481944E-01 1.977827E+02 5.115621E-01 + 4.079995E+01 9.000000E+01 4 1.118374E+02 8.996284E+01 7.254177E-02 1.118374E+02 + 4.079995E+01 9.000000E+01 5 7.888634E-05 -8.999609E+01 5.373834E-09 -7.888634E-05 + 4.079995E+01 9.000000E+01 6 2.674085E-06 1.799999E+02 -2.674085E-06 6.487719E-12 + 4.089995E+01 0.000000E+00 1 3.247310E+01 8.996636E+01 1.906293E-02 3.247309E+01 + 4.089995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.089995E+01 0.000000E+00 3 1.963145E+02 1.469615E-01 1.963138E+02 5.035388E-01 + 4.089995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.089995E+01 0.000000E+00 5 3.494464E+02 8.996636E+01 2.051320E-01 3.494464E+02 + 4.089995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.089995E+01 3.000000E+01 1 2.817088E+01 8.996636E+01 1.653707E-02 2.817087E+01 + 4.089995E+01 3.000000E+01 2 1.719222E+01 8.996297E+01 1.111097E-02 1.719222E+01 + 4.089995E+01 3.000000E+01 3 1.966925E+02 1.470845E-01 1.966918E+02 5.049306E-01 + 4.089995E+01 3.000000E+01 4 5.517721E+01 8.996284E+01 3.578190E-02 5.517720E+01 + 4.089995E+01 3.000000E+01 5 3.031367E+02 8.996636E+01 1.779512E-01 3.031367E+02 + 4.089995E+01 3.000000E+01 6 3.093188E+01 -2.032194E-04 3.093188E+01 -1.097107E-04 + 4.089995E+01 6.000000E+01 1 1.632039E+01 8.996636E+01 9.580210E-03 1.632039E+01 + 4.089995E+01 6.000000E+01 2 2.989011E+01 8.996297E+01 1.931791E-02 2.989010E+01 + 4.089995E+01 6.000000E+01 3 1.974520E+02 1.473293E-01 1.974513E+02 5.077238E-01 + 4.089995E+01 6.000000E+01 4 9.625885E+01 8.996297E+01 6.221196E-02 9.625883E+01 + 4.089995E+01 6.000000E+01 5 1.756040E+02 8.996636E+01 1.030882E-01 1.756040E+02 + 4.089995E+01 6.000000E+01 6 3.105209E+01 -2.029524E-04 3.105209E+01 -1.099923E-04 + 4.089995E+01 9.000000E+01 1 1.686668E-06 -9.002654E+01 -7.810206E-10 -1.686668E-06 + 4.089995E+01 9.000000E+01 2 3.457918E+01 8.996297E+01 2.234869E-02 3.457917E+01 + 4.089995E+01 9.000000E+01 3 1.978335E+02 1.474513E-01 1.978328E+02 5.091259E-01 + 4.089995E+01 9.000000E+01 4 1.115479E+02 8.996303E+01 7.197204E-02 1.115479E+02 + 4.089995E+01 9.000000E+01 5 7.869596E-05 -8.999612E+01 5.327563E-09 -7.869596E-05 + 4.089995E+01 9.000000E+01 6 2.660611E-06 1.799999E+02 -2.660611E-06 6.388090E-12 + 4.099995E+01 0.000000E+00 1 3.239382E+01 8.996654E+01 1.891988E-02 3.239382E+01 + 4.099995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.099995E+01 0.000000E+00 3 1.963704E+02 1.462304E-01 1.963698E+02 5.011762E-01 + 4.099995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.099995E+01 0.000000E+00 5 3.486714E+02 8.996654E+01 2.036370E-01 3.486713E+02 + 4.099995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.099995E+01 3.000000E+01 1 2.810176E+01 8.996654E+01 1.641283E-02 2.810175E+01 + 4.099995E+01 3.000000E+01 2 1.715014E+01 8.996317E+01 1.102528E-02 1.715014E+01 + 4.099995E+01 3.000000E+01 3 1.967476E+02 1.463505E-01 1.967469E+02 5.025514E-01 + 4.099995E+01 3.000000E+01 4 5.503794E+01 8.996304E+01 3.550260E-02 5.503793E+01 + 4.099995E+01 3.000000E+01 5 3.024617E+02 8.996654E+01 1.766532E-01 3.024617E+02 + 4.099995E+01 3.000000E+01 6 3.077749E+01 -2.011104E-04 3.077749E+01 -1.080302E-04 + 4.099995E+01 6.000000E+01 1 1.628016E+01 8.996654E+01 9.508057E-03 1.628015E+01 + 4.099995E+01 6.000000E+01 2 2.981628E+01 8.996317E+01 1.916851E-02 2.981628E+01 + 4.099995E+01 6.000000E+01 3 1.975037E+02 1.465924E-01 1.975031E+02 5.053167E-01 + 4.099995E+01 6.000000E+01 4 9.601196E+01 8.996317E+01 6.172496E-02 9.601194E+01 + 4.099995E+01 6.000000E+01 5 1.752095E+02 8.996654E+01 1.023354E-01 1.752095E+02 + 4.099995E+01 6.000000E+01 6 3.089643E+01 -2.008485E-04 3.089643E+01 -1.083064E-04 + 4.099995E+01 9.000000E+01 1 1.682470E-06 -9.002641E+01 -7.755393E-10 -1.682470E-06 + 4.099995E+01 9.000000E+01 2 3.449349E+01 8.996317E+01 2.217570E-02 3.449348E+01 + 4.099995E+01 9.000000E+01 3 1.978830E+02 1.467138E-01 1.978823E+02 5.067064E-01 + 4.099995E+01 9.000000E+01 4 1.112597E+02 8.996323E+01 7.140781E-02 1.112596E+02 + 4.099995E+01 9.000000E+01 5 7.850649E-05 -8.999615E+01 5.281842E-09 -7.850649E-05 + 4.099995E+01 9.000000E+01 6 2.647239E-06 1.799999E+02 -2.647239E-06 6.290251E-12 + 4.109995E+01 0.000000E+00 1 3.231490E+01 8.996671E+01 1.877822E-02 3.231489E+01 + 4.109995E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.109995E+01 0.000000E+00 3 1.964281E+02 1.455039E-01 1.964275E+02 4.988329E-01 + 4.109995E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.109995E+01 0.000000E+00 5 3.479012E+02 8.996671E+01 2.021575E-01 3.479011E+02 + 4.109995E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.109995E+01 3.000000E+01 1 2.803311E+01 8.996671E+01 1.628979E-02 2.803311E+01 + 4.109995E+01 3.000000E+01 2 1.710815E+01 8.996336E+01 1.094047E-02 1.710815E+01 + 4.109995E+01 3.000000E+01 3 1.968031E+02 1.456230E-01 1.968025E+02 5.001945E-01 + 4.109995E+01 3.000000E+01 4 5.489897E+01 8.996323E+01 3.522610E-02 5.489896E+01 + 4.109995E+01 3.000000E+01 5 3.017893E+02 8.996671E+01 1.753680E-01 3.017892E+02 + 4.109995E+01 3.000000E+01 6 3.062420E+01 -1.990296E-04 3.062420E+01 -1.063799E-04 + 4.109995E+01 6.000000E+01 1 1.624005E+01 8.996671E+01 9.436644E-03 1.624005E+01 + 4.109995E+01 6.000000E+01 2 2.974290E+01 8.996336E+01 1.902069E-02 2.974290E+01 + 4.109995E+01 6.000000E+01 3 1.975564E+02 1.458618E-01 1.975558E+02 5.029322E-01 + 4.109995E+01 6.000000E+01 4 9.576618E+01 8.996336E+01 6.124310E-02 9.576616E+01 + 4.109995E+01 6.000000E+01 5 1.748182E+02 8.996671E+01 1.015888E-01 1.748182E+02 + 4.109995E+01 6.000000E+01 6 3.074196E+01 -1.987714E-04 3.074196E+01 -1.066505E-04 + 4.109995E+01 9.000000E+01 1 1.678294E-06 -9.002629E+01 -7.701091E-10 -1.678294E-06 + 4.109995E+01 9.000000E+01 2 3.440830E+01 8.996336E+01 2.200449E-02 3.440829E+01 + 4.109995E+01 9.000000E+01 3 1.979326E+02 1.459821E-01 1.979320E+02 5.043058E-01 + 4.109995E+01 9.000000E+01 4 1.109734E+02 8.996342E+01 7.084974E-02 1.109734E+02 + 4.109995E+01 9.000000E+01 5 7.831767E-05 -8.999617E+01 5.236675E-09 -7.831767E-05 + 4.109995E+01 9.000000E+01 6 2.633970E-06 1.799999E+02 -2.633970E-06 6.194161E-12 + 4.119994E+01 0.000000E+00 1 3.223639E+01 8.996688E+01 1.863800E-02 3.223639E+01 + 4.119994E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.119994E+01 0.000000E+00 3 1.964843E+02 1.447822E-01 1.964837E+02 4.965008E-01 + 4.119994E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.119994E+01 0.000000E+00 5 3.471302E+02 8.996688E+01 2.006911E-01 3.471302E+02 + 4.119994E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.119994E+01 3.000000E+01 1 2.796481E+01 8.996688E+01 1.616803E-02 2.796480E+01 + 4.119994E+01 3.000000E+01 2 1.706651E+01 8.996355E+01 1.085656E-02 1.706650E+01 + 4.119994E+01 3.000000E+01 3 1.968574E+02 1.449003E-01 1.968568E+02 4.978493E-01 + 4.119994E+01 3.000000E+01 4 5.476097E+01 8.996342E+01 3.495253E-02 5.476096E+01 + 4.119994E+01 3.000000E+01 5 3.011182E+02 8.996688E+01 1.740967E-01 3.011181E+02 + 4.119994E+01 3.000000E+01 6 3.047206E+01 -1.969765E-04 3.047206E+01 -1.047596E-04 + 4.119994E+01 6.000000E+01 1 1.620018E+01 8.996688E+01 9.365939E-03 1.620017E+01 + 4.119994E+01 6.000000E+01 2 2.966987E+01 8.996355E+01 1.887443E-02 2.966987E+01 + 4.119994E+01 6.000000E+01 3 1.976069E+02 1.451368E-01 1.976063E+02 5.005605E-01 + 4.119994E+01 6.000000E+01 4 9.552213E+01 8.996355E+01 6.076624E-02 9.552210E+01 + 4.119994E+01 6.000000E+01 5 1.744270E+02 8.996687E+01 1.008510E-01 1.744269E+02 + 4.119994E+01 6.000000E+01 6 3.058869E+01 -1.967219E-04 3.058869E+01 -1.050246E-04 + 4.119994E+01 9.000000E+01 1 1.674138E-06 -9.002617E+01 -7.647286E-10 -1.674137E-06 + 4.119994E+01 9.000000E+01 2 3.432342E+01 8.996355E+01 2.183509E-02 3.432341E+01 + 4.119994E+01 9.000000E+01 3 1.979819E+02 1.452558E-01 1.979812E+02 5.019214E-01 + 4.119994E+01 9.000000E+01 4 1.106882E+02 8.996362E+01 7.029747E-02 1.106882E+02 + 4.119994E+01 9.000000E+01 5 7.813003E-05 -8.999619E+01 5.192008E-09 -7.813003E-05 + 4.119994E+01 9.000000E+01 6 2.620804E-06 1.799999E+02 -2.620804E-06 6.099818E-12 + 4.129994E+01 0.000000E+00 1 3.215831E+01 8.996704E+01 1.849917E-02 3.215830E+01 + 4.129994E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.129994E+01 0.000000E+00 3 1.965396E+02 1.440657E-01 1.965389E+02 4.941826E-01 + 4.129994E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.129994E+01 0.000000E+00 5 3.463657E+02 8.996704E+01 1.992409E-01 3.463656E+02 + 4.129994E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.129994E+01 3.000000E+01 1 2.789677E+01 8.996704E+01 1.604749E-02 2.789677E+01 + 4.129994E+01 3.000000E+01 2 1.702501E+01 8.996375E+01 1.077350E-02 1.702500E+01 + 4.129994E+01 3.000000E+01 3 1.969117E+02 1.441831E-01 1.969111E+02 4.955220E-01 + 4.129994E+01 3.000000E+01 4 5.462371E+01 8.996362E+01 3.468196E-02 5.462370E+01 + 4.129994E+01 3.000000E+01 5 3.004536E+02 8.996704E+01 1.728359E-01 3.004535E+02 + 4.129994E+01 3.000000E+01 6 3.032113E+01 -1.949495E-04 3.032113E+01 -1.031679E-04 + 4.129994E+01 6.000000E+01 1 1.616049E+01 8.996704E+01 9.295954E-03 1.616048E+01 + 4.129994E+01 6.000000E+01 2 2.959719E+01 8.996375E+01 1.872970E-02 2.959719E+01 + 4.129994E+01 6.000000E+01 3 1.976570E+02 1.444177E-01 1.976563E+02 4.982067E-01 + 4.129994E+01 6.000000E+01 4 9.527947E+01 8.996375E+01 6.029442E-02 9.527945E+01 + 4.129994E+01 6.000000E+01 5 1.740376E+02 8.996704E+01 1.001183E-01 1.740376E+02 + 4.129994E+01 6.000000E+01 6 3.043653E+01 -1.946994E-04 3.043653E+01 -1.034277E-04 + 4.129994E+01 9.000000E+01 1 1.670004E-06 -9.002605E+01 -7.593959E-10 -1.670004E-06 + 4.129994E+01 9.000000E+01 2 3.423899E+01 8.996375E+01 2.166739E-02 3.423898E+01 + 4.129994E+01 9.000000E+01 3 1.980305E+02 1.445356E-01 1.980299E+02 4.995557E-01 + 4.129994E+01 9.000000E+01 4 1.104047E+02 8.996381E+01 6.975102E-02 1.104047E+02 + 4.129994E+01 9.000000E+01 5 7.794305E-05 -8.999622E+01 5.147867E-09 -7.794305E-05 + 4.129994E+01 9.000000E+01 6 2.607728E-06 1.799999E+02 -2.607728E-06 6.007129E-12 + 4.139994E+01 0.000000E+00 1 3.208051E+01 8.996720E+01 1.836172E-02 3.208050E+01 + 4.139994E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.139994E+01 0.000000E+00 3 1.965956E+02 1.433545E-01 1.965950E+02 4.918833E-01 + 4.139994E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.139994E+01 0.000000E+00 5 3.456003E+02 8.996720E+01 1.978056E-01 3.456002E+02 + 4.139994E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.139994E+01 3.000000E+01 1 2.782909E+01 8.996720E+01 1.592808E-02 2.782909E+01 + 4.139994E+01 3.000000E+01 2 1.698372E+01 8.996394E+01 1.069130E-02 1.698371E+01 + 4.139994E+01 3.000000E+01 3 1.969649E+02 1.434706E-01 1.969643E+02 4.932063E-01 + 4.139994E+01 3.000000E+01 4 5.448686E+01 8.996381E+01 3.441423E-02 5.448685E+01 + 4.139994E+01 3.000000E+01 5 2.997913E+02 8.996720E+01 1.715882E-01 2.997912E+02 + 4.139994E+01 3.000000E+01 6 3.017126E+01 -1.929491E-04 3.017126E+01 -1.016046E-04 + 4.139994E+01 6.000000E+01 1 1.612102E+01 8.996721E+01 9.226641E-03 1.612101E+01 + 4.139994E+01 6.000000E+01 2 2.952482E+01 8.996394E+01 1.858645E-02 2.952482E+01 + 4.139994E+01 6.000000E+01 3 1.977071E+02 1.437027E-01 1.977065E+02 4.958657E-01 + 4.139994E+01 6.000000E+01 4 9.503753E+01 8.996394E+01 5.982786E-02 9.503751E+01 + 4.139994E+01 6.000000E+01 5 1.736500E+02 8.996720E+01 9.939387E-02 1.736499E+02 + 4.139994E+01 6.000000E+01 6 3.028553E+01 -1.927027E-04 3.028553E+01 -1.018592E-04 + 4.139994E+01 9.000000E+01 1 1.665889E-06 -9.002594E+01 -7.541124E-10 -1.665889E-06 + 4.139994E+01 9.000000E+01 2 3.415503E+01 8.996394E+01 2.150146E-02 3.415503E+01 + 4.139994E+01 9.000000E+01 3 1.980793E+02 1.438184E-01 1.980787E+02 4.971993E-01 + 4.139994E+01 9.000000E+01 4 1.101234E+02 8.996400E+01 6.921072E-02 1.101233E+02 + 4.139994E+01 9.000000E+01 5 7.775707E-05 -8.999624E+01 5.104229E-09 -7.775707E-05 + 4.139994E+01 9.000000E+01 6 2.594763E-06 1.799999E+02 -2.594763E-06 5.916115E-12 + 4.149994E+01 0.000000E+00 1 3.200307E+01 8.996737E+01 1.822561E-02 3.200307E+01 + 4.149994E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.149994E+01 0.000000E+00 3 1.966507E+02 1.426483E-01 1.966501E+02 4.895974E-01 + 4.149994E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.149994E+01 0.000000E+00 5 3.448411E+02 8.996737E+01 1.963807E-01 3.448410E+02 + 4.149994E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.149994E+01 3.000000E+01 1 2.776168E+01 8.996737E+01 1.580994E-02 2.776168E+01 + 4.149994E+01 3.000000E+01 2 1.694263E+01 8.996412E+01 1.060992E-02 1.694263E+01 + 4.149994E+01 3.000000E+01 3 1.970181E+02 1.427636E-01 1.970174E+02 4.909084E-01 + 4.149994E+01 3.000000E+01 4 5.435096E+01 8.996400E+01 3.414890E-02 5.435095E+01 + 4.149994E+01 3.000000E+01 5 2.991281E+02 8.996737E+01 1.703518E-01 2.991280E+02 + 4.149994E+01 3.000000E+01 6 3.002252E+01 -1.909746E-04 3.002252E+01 -1.000691E-04 + 4.149994E+01 6.000000E+01 1 1.608171E+01 8.996738E+01 9.158031E-03 1.608171E+01 + 4.149994E+01 6.000000E+01 2 2.945286E+01 8.996412E+01 1.844464E-02 2.945286E+01 + 4.149994E+01 6.000000E+01 3 1.977572E+02 1.429930E-01 1.977566E+02 4.935420E-01 + 4.149994E+01 6.000000E+01 4 9.479705E+01 8.996412E+01 5.936589E-02 9.479704E+01 + 4.149994E+01 6.000000E+01 5 1.732650E+02 8.996737E+01 9.867683E-02 1.732650E+02 + 4.149994E+01 6.000000E+01 6 3.013568E+01 -1.907316E-04 3.013568E+01 -1.003185E-04 + 4.149994E+01 9.000000E+01 1 1.661794E-06 -9.002582E+01 -7.488778E-10 -1.661794E-06 + 4.149994E+01 9.000000E+01 2 3.407139E+01 8.996412E+01 2.133723E-02 3.407138E+01 + 4.149994E+01 9.000000E+01 3 1.981269E+02 1.431084E-01 1.981263E+02 4.948636E-01 + 4.149994E+01 9.000000E+01 4 1.098428E+02 8.996418E+01 6.867573E-02 1.098428E+02 + 4.149994E+01 9.000000E+01 5 7.757172E-05 -8.999626E+01 5.061101E-09 -7.757172E-05 + 4.149994E+01 9.000000E+01 6 2.581888E-06 1.799999E+02 -2.581888E-06 5.826696E-12 + 4.159994E+01 0.000000E+00 1 3.192614E+01 8.996753E+01 1.809090E-02 3.192613E+01 + 4.159994E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.159994E+01 0.000000E+00 3 1.967056E+02 1.419500E-01 1.967050E+02 4.873366E-01 + 4.159994E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.159994E+01 0.000000E+00 5 3.440872E+02 8.996753E+01 1.949723E-01 3.440872E+02 + 4.159994E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.159994E+01 3.000000E+01 1 2.769471E+01 8.996753E+01 1.569294E-02 2.769471E+01 + 4.159994E+01 3.000000E+01 2 1.690174E+01 8.996431E+01 1.052938E-02 1.690174E+01 + 4.159994E+01 3.000000E+01 3 1.970720E+02 1.420630E-01 1.970714E+02 4.886332E-01 + 4.159994E+01 3.000000E+01 4 5.421552E+01 8.996419E+01 3.388662E-02 5.421551E+01 + 4.159994E+01 3.000000E+01 5 2.984710E+02 8.996753E+01 1.691272E-01 2.984709E+02 + 4.159994E+01 3.000000E+01 6 2.987486E+01 -1.890252E-04 2.987486E+01 -9.856051E-05 + 4.159994E+01 6.000000E+01 1 1.604262E+01 8.996753E+01 9.090105E-03 1.604262E+01 + 4.159994E+01 6.000000E+01 2 2.938123E+01 8.996431E+01 1.830431E-02 2.938122E+01 + 4.159994E+01 6.000000E+01 3 1.978063E+02 1.422910E-01 1.978056E+02 4.912407E-01 + 4.159994E+01 6.000000E+01 4 9.455788E+01 8.996431E+01 5.890870E-02 9.455786E+01 + 4.159994E+01 6.000000E+01 5 1.728810E+02 8.996753E+01 9.796600E-02 1.728810E+02 + 4.159994E+01 6.000000E+01 6 2.998695E+01 -1.887858E-04 2.998695E+01 -9.880501E-05 + 4.159994E+01 9.000000E+01 1 1.657723E-06 -9.002570E+01 -7.436894E-10 -1.657723E-06 + 4.159994E+01 9.000000E+01 2 3.398825E+01 8.996431E+01 2.117467E-02 3.398825E+01 + 4.159994E+01 9.000000E+01 3 1.981756E+02 1.424040E-01 1.981750E+02 4.925489E-01 + 4.159994E+01 9.000000E+01 4 1.095636E+02 8.996436E+01 6.814620E-02 1.095636E+02 + 4.159994E+01 9.000000E+01 5 7.738743E-05 -8.999628E+01 5.018445E-09 -7.738743E-05 + 4.159994E+01 9.000000E+01 6 2.569109E-06 1.799999E+02 -2.569109E-06 5.738859E-12 + 4.169994E+01 0.000000E+00 1 3.184952E+01 8.996770E+01 1.795752E-02 3.184951E+01 + 4.169994E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.169994E+01 0.000000E+00 3 1.967602E+02 1.412541E-01 1.967596E+02 4.850822E-01 + 4.169994E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.169994E+01 0.000000E+00 5 3.433343E+02 8.996770E+01 1.935746E-01 3.433342E+02 + 4.169994E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.169994E+01 3.000000E+01 1 2.762793E+01 8.996770E+01 1.557708E-02 2.762793E+01 + 4.169994E+01 3.000000E+01 2 1.686105E+01 8.996449E+01 1.044969E-02 1.686105E+01 + 4.169994E+01 3.000000E+01 3 1.971250E+02 1.413667E-01 1.971244E+02 4.863688E-01 + 4.169994E+01 3.000000E+01 4 5.408092E+01 8.996438E+01 3.362707E-02 5.408091E+01 + 4.169994E+01 3.000000E+01 5 2.978172E+02 8.996770E+01 1.679160E-01 2.978172E+02 + 4.169994E+01 3.000000E+01 6 2.972837E+01 -1.871010E-04 2.972837E+01 -9.707885E-05 + 4.169994E+01 6.000000E+01 1 1.600369E+01 8.996770E+01 9.022900E-03 1.600369E+01 + 4.169994E+01 6.000000E+01 2 2.930994E+01 8.996449E+01 1.816543E-02 2.930993E+01 + 4.169994E+01 6.000000E+01 3 1.978561E+02 1.415912E-01 1.978555E+02 4.889480E-01 + 4.169994E+01 6.000000E+01 4 9.431992E+01 8.996449E+01 5.845638E-02 9.431990E+01 + 4.169994E+01 6.000000E+01 5 1.724973E+02 8.996770E+01 9.726115E-02 1.724973E+02 + 4.169994E+01 6.000000E+01 6 2.983928E+01 -1.868654E-04 2.983928E+01 -9.731831E-05 + 4.169994E+01 9.000000E+01 1 1.653668E-06 -9.002559E+01 -7.385495E-10 -1.653668E-06 + 4.169994E+01 9.000000E+01 2 3.390548E+01 8.996449E+01 2.101381E-02 3.390548E+01 + 4.169994E+01 9.000000E+01 3 1.982223E+02 1.417046E-01 1.982217E+02 4.902453E-01 + 4.169994E+01 9.000000E+01 4 1.092858E+02 8.996455E+01 6.762217E-02 1.092858E+02 + 4.169994E+01 9.000000E+01 5 7.720428E-05 -8.999631E+01 4.976278E-09 -7.720428E-05 + 4.169994E+01 9.000000E+01 6 2.556429E-06 1.799999E+02 -2.556429E-06 5.652582E-12 + 4.179993E+01 0.000000E+00 1 3.177319E+01 8.996786E+01 1.782549E-02 3.177319E+01 + 4.179993E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.179993E+01 0.000000E+00 3 1.968141E+02 1.405636E-01 1.968135E+02 4.828432E-01 + 4.179993E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.179993E+01 0.000000E+00 5 3.425842E+02 8.996786E+01 1.921921E-01 3.425841E+02 + 4.179993E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.179993E+01 3.000000E+01 1 2.756153E+01 8.996786E+01 1.546244E-02 2.756153E+01 + 4.179993E+01 3.000000E+01 2 1.682053E+01 8.996468E+01 1.037080E-02 1.682053E+01 + 4.179993E+01 3.000000E+01 3 1.971770E+02 1.406749E-01 1.971764E+02 4.841162E-01 + 4.179993E+01 3.000000E+01 4 5.394693E+01 8.996456E+01 3.337028E-02 5.394692E+01 + 4.179993E+01 3.000000E+01 5 2.971655E+02 8.996786E+01 1.667133E-01 2.971654E+02 + 4.179993E+01 3.000000E+01 6 2.958294E+01 -1.852015E-04 2.958294E+01 -9.562315E-05 + 4.179993E+01 6.000000E+01 1 1.596499E+01 8.996786E+01 8.956323E-03 1.596499E+01 + 4.179993E+01 6.000000E+01 2 2.923900E+01 8.996467E+01 1.802796E-02 2.923900E+01 + 4.179993E+01 6.000000E+01 3 1.979050E+02 1.408982E-01 1.979044E+02 4.866752E-01 + 4.179993E+01 6.000000E+01 4 9.408327E+01 8.996467E+01 5.800894E-02 9.408326E+01 + 4.179993E+01 6.000000E+01 5 1.721169E+02 8.996786E+01 9.656462E-02 1.721168E+02 + 4.179993E+01 6.000000E+01 6 2.969277E+01 -1.849691E-04 2.969277E+01 -9.585775E-05 + 4.179993E+01 9.000000E+01 1 1.649634E-06 -9.002547E+01 -7.334572E-10 -1.649634E-06 + 4.179993E+01 9.000000E+01 2 3.382306E+01 8.996467E+01 2.085456E-02 3.382305E+01 + 4.179993E+01 9.000000E+01 3 1.982701E+02 1.410097E-01 1.982695E+02 4.879587E-01 + 4.179993E+01 9.000000E+01 4 1.090095E+02 8.996473E+01 6.710392E-02 1.090095E+02 + 4.179993E+01 9.000000E+01 5 7.702148E-05 -8.999633E+01 4.934618E-09 -7.702148E-05 + 4.179993E+01 9.000000E+01 6 2.543847E-06 1.799999E+02 -2.543847E-06 5.567821E-12 + 4.189993E+01 0.000000E+00 1 3.169726E+01 8.996802E+01 1.769472E-02 3.169726E+01 + 4.189993E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.189993E+01 0.000000E+00 3 1.968671E+02 1.398788E-01 1.968665E+02 4.806201E-01 + 4.189993E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.189993E+01 0.000000E+00 5 3.418394E+02 8.996802E+01 1.908225E-01 3.418393E+02 + 4.189993E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.189993E+01 3.000000E+01 1 2.749547E+01 8.996802E+01 1.534886E-02 2.749546E+01 + 4.189993E+01 3.000000E+01 2 1.678023E+01 8.996486E+01 1.029271E-02 1.678022E+01 + 4.189993E+01 3.000000E+01 3 1.972283E+02 1.399894E-01 1.972278E+02 4.818829E-01 + 4.189993E+01 3.000000E+01 4 5.381390E+01 8.996474E+01 3.311593E-02 5.381388E+01 + 4.189993E+01 3.000000E+01 5 2.965127E+02 8.996802E+01 1.655249E-01 2.965127E+02 + 4.189993E+01 3.000000E+01 6 2.943853E+01 -1.833262E-04 2.943853E+01 -9.419290E-05 + 4.189993E+01 6.000000E+01 1 1.592647E+01 8.996802E+01 8.890377E-03 1.592647E+01 + 4.189993E+01 6.000000E+01 2 2.916839E+01 8.996486E+01 1.789187E-02 2.916839E+01 + 4.189993E+01 6.000000E+01 3 1.979532E+02 1.402093E-01 1.979526E+02 4.844135E-01 + 4.189993E+01 6.000000E+01 4 9.384766E+01 8.996486E+01 5.756581E-02 9.384765E+01 + 4.189993E+01 6.000000E+01 5 1.717385E+02 8.996802E+01 9.587416E-02 1.717384E+02 + 4.189993E+01 6.000000E+01 6 2.954734E+01 -1.830975E-04 2.954734E+01 -9.442304E-05 + 4.189993E+01 9.000000E+01 1 1.645620E-06 -9.002537E+01 -7.284074E-10 -1.645620E-06 + 4.189993E+01 9.000000E+01 2 3.374107E+01 8.996486E+01 2.069700E-02 3.374106E+01 + 4.189993E+01 9.000000E+01 3 1.983167E+02 1.403194E-01 1.983161E+02 4.856843E-01 + 4.189993E+01 9.000000E+01 4 1.087346E+02 8.996491E+01 6.659083E-02 1.087346E+02 + 4.189993E+01 9.000000E+01 5 7.684010E-05 -8.999635E+01 4.893390E-09 -7.684010E-05 + 4.189993E+01 9.000000E+01 6 2.531352E-06 1.799999E+02 -2.531352E-06 5.484548E-12 + 4.199993E+01 0.000000E+00 1 3.162169E+01 8.996818E+01 1.756517E-02 3.162169E+01 + 4.199993E+01 0.000000E+00 2 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.199993E+01 0.000000E+00 3 1.969216E+02 1.391986E-01 1.969211E+02 4.784157E-01 + 4.199993E+01 0.000000E+00 4 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.199993E+01 0.000000E+00 5 3.410953E+02 8.996818E+01 1.894655E-01 3.410952E+02 + 4.199993E+01 0.000000E+00 6 0.000000E+00 9.000000E+01 0.000000E+00 0.000000E+00 + 4.199993E+01 3.000000E+01 1 2.742975E+01 8.996818E+01 1.523634E-02 2.742974E+01 + 4.199993E+01 3.000000E+01 2 1.674008E+01 8.996504E+01 1.021539E-02 1.674008E+01 + 4.199993E+01 3.000000E+01 3 1.972803E+02 1.393080E-01 1.972797E+02 4.796635E-01 + 4.199993E+01 3.000000E+01 4 5.368106E+01 8.996492E+01 3.286424E-02 5.368105E+01 + 4.199993E+01 3.000000E+01 5 2.958658E+02 8.996818E+01 1.643461E-01 2.958658E+02 + 4.199993E+01 3.000000E+01 6 2.929523E+01 -1.814753E-04 2.929523E+01 -9.278800E-05 + 4.199993E+01 6.000000E+01 1 1.588813E+01 8.996818E+01 8.825126E-03 1.588813E+01 + 4.199993E+01 6.000000E+01 2 2.909819E+01 8.996503E+01 1.775723E-02 2.909819E+01 + 4.199993E+01 6.000000E+01 3 1.980013E+02 1.395273E-01 1.980007E+02 4.821744E-01 + 4.199993E+01 6.000000E+01 4 9.361299E+01 8.996503E+01 5.712739E-02 9.361298E+01 + 4.199993E+01 6.000000E+01 5 1.713600E+02 8.996818E+01 9.519084E-02 1.713600E+02 + 4.199993E+01 6.000000E+01 6 2.940291E+01 -1.812501E-04 2.940291E+01 -9.301350E-05 + 4.199993E+01 9.000000E+01 1 1.641623E-06 -9.002525E+01 -7.234043E-10 -1.641623E-06 + 4.199993E+01 9.000000E+01 2 3.365955E+01 8.996503E+01 2.054098E-02 3.365954E+01 + 4.199993E+01 9.000000E+01 3 1.983625E+02 1.396369E-01 1.983619E+02 4.834336E-01 + 4.199993E+01 9.000000E+01 4 1.084613E+02 8.996510E+01 6.608290E-02 1.084613E+02 + 4.199993E+01 9.000000E+01 5 7.665897E-05 -8.999638E+01 4.852652E-09 -7.665897E-05 + 4.199993E+01 9.000000E+01 6 2.518950E-06 1.799999E+02 -2.518950E-06 5.402741E-12 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.fst b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.fst new file mode 100644 index 00000000..a19bf661 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.fst @@ -0,0 +1,71 @@ +------- OpenFAST EXAMPLE INPUT FILE -------------------------------------------- +Floating MHK turbine, based on the RM1 tidal current rotor +---------------------- SIMULATION CONTROL -------------------------------------- +False Echo - Echo input data to .ech (flag) +"FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} + 100 TMax - Total run time (s) + 0.01 DT - Recommended module time step (s) + 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} + 2 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 1 DT_UJac - Time between calls to get Jacobians (s) + 1E+06 UJacSclFact - Scaling factor used in Jacobians (-) +---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades} + 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from OpenFOAM} + 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDyn v14; 2=AeroDyn v15} + 1 CompServo - Compute control and electrical-drive dynamics (switch) {0=None; 1=ServoDyn} + 1 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} + 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} + 3 CompMooring - Compute mooring system (switch) {0=None; 1=MAP++; 2=FEAMooring; 3=MoorDyn; 4=OrcaFlex} + 0 CompIce - Compute ice loads (switch) {0=None; 1=IceFloe; 2=IceDyn} + 2 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} +---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- + 9.80665 Gravity - Gravitational acceleration (m/s^2) + 1.225 AirDens - Air density (kg/m^3) + 1025.0 WtrDens - Water density (kg/m^3) + 1.06E-06 KinVisc - Kinematic viscosity of working fluid (m^2/s) + 1500 SpdSound - Speed of sound in working fluid (m/s) + 101325 Patm - Atmospheric pressure (Pa) [used only for an MHK turbine cavitation check] + 2500 Pvap - Vapour pressure of working fluid (Pa) [used only for an MHK turbine cavitation check] + 50 WtrDpth - Water depth (m) + 0 MSL2SWL - Offset between still-water level and mean sea level (m) [positive upward] +---------------------- INPUT FILES --------------------------------------------- +"MHK_RM1_Floating_ElastoDyn.dat" EDFile - Name of file containing ElastoDyn input parameters (quoted string) +"unused" BDBldFile(1) - Name of file containing BeamDyn input parameters for blade 1 (quoted string) +"unused" BDBldFile(2) - Name of file containing BeamDyn input parameters for blade 2 (quoted string) +"unused" BDBldFile(3) - Name of file containing BeamDyn input parameters for blade 3 (quoted string) +"MHK_RM1_Floating_InflowWind.dat" InflowFile - Name of file containing inflow wind input parameters (quoted string) +"MHK_RM1_Floating_AeroDyn15.dat" AeroFile - Name of file containing aerodynamic input parameters (quoted string) +"MHK_RM1_ServoDyn.dat" ServoFile - Name of file containing control and electrical-drive input parameters (quoted string) +"MHK_RM1_Floating_HydroDyn.dat" HydroFile - Name of file containing hydrodynamic input parameters (quoted string) +"unused" SubFile - Name of file containing sub-structural input parameters (quoted string) +"MHK_RM1_Floating_MoorDyn.dat" MooringFile - Name of file containing mooring system input parameters (quoted string) +"unused" IceFile - Name of file containing ice input parameters (quoted string) +---------------------- OUTPUT -------------------------------------------------- +True SumPrint - Print summary data to ".sum" (flag) + 5 SttsTime - Amount of time between screen status messages (s) + 99999 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) + default DT_Out - Time step for tabular output (s) (or "default") + 0 TStart - Time to begin tabular output (s) + 3 OutFileFmt - Format for tabular (time-marching) output file (switch) {0: uncompressed binary [.outb], 1: text file [.out], 2: binary file [.outb], 3: both 1 and 2} +True TabDelim - Use tab delimiters in text tabular output file? (flag) {uses spaces if false} +"ES10.3E2" OutFmt - Format used for text tabular output, excluding the time channel. Resulting field should be 10 characters. (quoted string) +---------------------- LINEARIZATION ------------------------------------------- +False Linearize - Linearization analysis (flag) +False CalcSteady - Calculate a steady-state periodic operating point before linearization? [unused if Linearize=False] (flag) + 1 TrimCase - Controller parameter to be trimmed {1:yaw; 2:torque; 3:pitch} [used only if CalcSteady=True] (-) + 0.01 TrimTol - Tolerance for the rotational speed convergence [used only if CalcSteady=True] (-) + 0.01 TrimGain - Proportional gain for the rotational speed error (>0) [used only if CalcSteady=True] (rad/(rad/s) for yaw or pitch; Nm/(rad/s) for torque) + 0 Twr_Kdmp - Damping factor for the tower [used only if CalcSteady=True] (N/(m/s)) + 0 Bld_Kdmp - Damping factor for the blades [used only if CalcSteady=True] (N/(m/s)) + 0 NLinTimes - Number of times to linearize (-) [>=1] [unused if Linearize=False] + 0 LinTimes - List of times at which to linearize (s) [1 to NLinTimes] [used only when Linearize=True and CalcSteady=False] + 0 LinInputs - Inputs included in linearization (switch) {0=none; 1=standard; 2=all module inputs (debug)} [unused if Linearize=False] + 0 LinOutputs - Outputs included in linearization (switch) {0=none; 1=from OutList(s); 2=all module outputs (debug)} [unused if Linearize=False] +False LinOutJac - Include full Jacobians in linearization output (for debug) (flag) [unused if Linearize=False; used only if LinInputs=LinOutputs=2] +False LinOutMod - Write module-level linearization output files in addition to output for full system? (flag) [unused if Linearize=False] +---------------------- VISUALIZATION ------------------------------------------- + 0 WrVTK - VTK visualization data output: (switch) {0=none; 1=initialization data only; 2=animation; 3=mode shapes} + 1 VTK_type - Type of VTK visualization data: (switch) {1=surfaces; 2=basic meshes (lines/points); 3=all meshes (debug)} [unused if WrVTK=0] +False VTK_fields - Write mesh fields to VTK data files? (flag) {true/false} [unused if WrVTK=0] + 0 VTK_fps - Frame rate for VTK output (frames per second){will use closest integer multiple of DT} [used only if WrVTK=2 or WrVTK=3] diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.hst b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.hst new file mode 100644 index 00000000..7f6dc63e --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.hst @@ -0,0 +1,36 @@ + 1 1 0.000000E+00 + 1 2 0.000000E+00 + 1 3 0.000000E+00 + 1 4 0.000000E+00 + 1 5 0.000000E+00 + 1 6 0.000000E+00 + 2 1 0.000000E+00 + 2 2 0.000000E+00 + 2 3 0.000000E+00 + 2 4 0.000000E+00 + 2 5 0.000000E+00 + 2 6 0.000000E+00 + 3 1 0.000000E+00 + 3 2 0.000000E+00 + 3 3 2.083175E+02 + 3 4 0.000000E+00 + 3 5 0.000000E+00 + 3 6 0.000000E+00 + 4 1 0.000000E+00 + 4 2 0.000000E+00 + 4 3 0.000000E+00 + 4 4 -1.035433E+03 + 4 5 0.000000E+00 + 4 6 0.000000E+00 + 5 1 0.000000E+00 + 5 2 0.000000E+00 + 5 3 0.000000E+00 + 5 4 0.000000E+00 + 5 5 6.307686E+04 + 5 6 0.000000E+00 + 6 1 0.000000E+00 + 6 2 0.000000E+00 + 6 3 0.000000E+00 + 6 4 0.000000E+00 + 6 5 0.000000E+00 + 6 6 0.000000E+00 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat new file mode 100644 index 00000000..707ba8d9 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat @@ -0,0 +1,123 @@ +------- AERODYN v15 for OpenFAST INPUT FILE --------------------------------------------------------- +Floating MHK turbine hydrodynamic input properties, based on the RM1 tidal current rotor +====== General Options ============================================================================ +False Echo - Echo the input to ".AD.ech"? (flag) +"default" DTAero - Time interval for aerodynamic calculations {or "default"} (s) + 2 WakeMod - Type of wake/induction model (switch) {0=none, 1=BEMT, 2=DBEMT, 3=OLAF} [WakeMod cannot be 2 or 3 when linearizing] + 1 AFAeroMod - Type of blade airfoil aerodynamics model (switch) {1=steady model, 2=Beddoes-Leishman unsteady model} [AFAeroMod must be 1 when linearizing] + 1 TwrPotent - Type tower influence on wind based on potential flow around the tower (switch) {0=none, 1=baseline potential flow, 2=potential flow with Bak correction} + 0 TwrShadow - Calculate tower influence on wind based on downstream tower shadow (switch) {0=none, 1=Powles model, 2=Eames model} +True TwrAero - Calculate tower aerodynamic loads? (flag) +False FrozenWake - Assume frozen wake during linearization? (flag) [used only when WakeMod=1 and when linearizing] +True CavitCheck - Perform cavitation check? (flag) [AFAeroMod must be 1 when CavitCheck=true] +True Buoyancy - Include buoyancy effects? (flag) +False CompAA - Flag to compute AeroAcoustics calculation [used only when WakeMod = 1 or 2] +"unused" AA_InputFile - AeroAcoustics input file [used only when CompAA=true] +====== Environmental Conditions =================================================================== +"default" AirDens - Air density (kg/m^3) +"default" KinVisc - Kinematic viscosity of working fluid (m^2/s) +"default" SpdSound - Speed of sound in working fluid (m/s) +"default" Patm - Atmospheric pressure (Pa) [used only when CavitCheck=True] +"default" Pvap - Vapour pressure of working fluid (Pa) [used only when CavitCheck=True] +====== Blade-Element/Momentum Theory Options ====================================================== [unused when WakeMod=0 or 3] + 2 SkewMod - Type of skewed-wake correction model (switch) {1=uncoupled, 2=Pitt/Peters, 3=coupled} [unused when WakeMod=0 or 3] +"default" SkewModFactor - Constant used in Pitt/Peters skewed wake model {or "default" is 15/32*pi} (-) [used only when SkewMod=2; unused when WakeMod=0 or 3] +True TipLoss - Use the Prandtl tip-loss model? (flag) [unused when WakeMod=0 or 3] +True HubLoss - Use the Prandtl hub-loss model? (flag) [unused when WakeMod=0 or 3] +True TanInd - Include tangential induction in BEMT calculations? (flag) [unused when WakeMod=0 or 3] +True AIDrag - Include the drag term in the axial-induction calculation? (flag) [unused when WakeMod=0 or 3] +True TIDrag - Include the drag term in the tangential-induction calculation? (flag) [unused when WakeMod=0,3 or TanInd=FALSE] +"default" IndToler - Convergence tolerance for BEMT nonlinear solve residual equation {or "default"} (-) [unused when WakeMod=0 or 3] + 1000 MaxIter - Maximum number of iteration steps (-) [unused when WakeMod=0] +====== Dynamic Blade-Element/Momentum Theory Options ============================================== [used only when WakeMod=2] + 2 DBEMT_Mod - Type of dynamic BEMT (DBEMT) model {1=constant tau1, 2=time-dependent tau1} (-) [used only when WakeMod=2] + 4 tau1_const - Time constant for DBEMT (s) [used only when WakeMod=2 and DBEMT_Mod=1] +====== OLAF -- cOnvecting LAgrangian Filaments (Free Vortex Wake) Theory Options ================== [used only when WakeMod=3] +"unused" OLAFInputFileName - Input file for OLAF [used only when WakeMod=3] +====== Beddoes-Leishman Unsteady Airfoil Aerodynamics Options ===================================== [used only when AFAeroMod=2] + 3 UAMod - Unsteady Aero Model Switch (switch) {1=Baseline model (Original), 2=Gonzalez's variant (changes in Cn,Cc,Cm), 3=Minnema/Pierce variant (changes in Cc and Cm)} [used only when AFAeroMod=2] +True FLookup - Flag to indicate whether a lookup for f' will be calculated (TRUE) or whether best-fit exponential equations will be used (FALSE); if FALSE S1-S4 must be provided in airfoil input files (flag) [used only when AFAeroMod=2] +====== Airfoil Information ========================================================================= + 2 AFTabMod - Interpolation method for multiple airfoil tables {1=1D interpolation on AoA (first table only); 2=2D interpolation on AoA and Re; 3=2D interpolation on AoA and UserProp} (-) + 1 InCol_Alfa - The column in the airfoil tables that contains the angle of attack (-) + 2 InCol_Cl - The column in the airfoil tables that contains the lift coefficient (-) + 3 InCol_Cd - The column in the airfoil tables that contains the drag coefficient (-) + 0 InCol_Cm - The column in the airfoil tables that contains the pitching-moment coefficient; use zero if there is no Cm column (-) + 4 InCol_Cpmin - The column in the airfoil tables that contains the Cpmin coefficient; use zero if there is no Cpmin column (-) + 9 NumAFfiles - Number of airfoil files used (-) +"Airfoils/NACA6_1000.dat" AFNames - Airfoil file names (NumAFfiles lines) (quoted strings) +"Airfoils/NACA6_0864.dat" +"Airfoils/NACA6_0629.dat" +"Airfoils/NACA6_0444.dat" +"Airfoils/NACA6_0329.dat" +"Airfoils/NACA6_0276.dat" +"Airfoils/NACA6_0259.dat" +"Airfoils/NACA6_0247.dat" +"Airfoils/NACA6_0240.dat" +====== Rotor/Blade Properties ===================================================================== +False UseBlCm - Include aerodynamic pitching moment in calculations? (flag) +"MHK_RM1_AeroDyn15_Blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) +"MHK_RM1_AeroDyn15_Blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] +"unused" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] +====== Hub Properties ============================================================================== [used only when Buoyancy=True] +7.2 VolHub - Hub volume (m^3) +0.2222 HubCenBx - Hub center of buoyancy x direction offset (m) +====== Nacelle Properties ========================================================================== [used only when Buoyancy=True] +38.6 VolNac - Nacelle volume (m^3) +0.43,0,0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) +====== Tail fin Aerodynamics ======================================================================== +False TFinAero - Calculate tail fin aerodynamics model (flag) +"unused" TFinFile - Input file for tail fin aerodynamics [used only when TFinAero=True] +====== Tower Influence and Aerodynamics ============================================================ [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or Buoyancy=True] + 4 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or Buoyancy=True] +TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True +(m) (m) (-) (-) (-) +-9 0.3253 0.2 0.0 1.0 +-14 0.3253 0.2 0.0 1.0 +-19 0.3253 0.2 0.0 1.0 +-24 0.3253 0.2 0.0 1.0 +====== Outputs ==================================================================================== +True SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) + 9 NBlOuts - Number of blade node outputs [0 - 9] (-) +1,5,9,13,17,21,25,27,30 BlOutNd - Blade nodes whose values will be output (-) + 4 NTwOuts - Number of tower node outputs [0 - 9] (-) + 1,2,3,4 TwOutNd - Tower nodes whose values will be output (-) + OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels. +"TwN1Fbx" - x-component of buoyant force per unit length at Tw node 1 +"TwN3Fby" - y-component of buoyant force per unit length at Tw node 3 +"TwN4Fbz" - z-component of buoyant force per unit length at Tw node 4 +"TwN1Mbx" - x-component of buoyant moment per unit length at Tw node 6 +"TwN2Mby" - y-component of buoyant moment per unit length at Tw node 5 +"TwN3Mbz" - z-component of buoyant moment per unit length at Tw node 2 +"B2N4Fbn" - Buoyant force normal to chord per unit length at blade 2 node 4 +"B1N7Fbt" - Buoyant force tangential to chord per unit length at blade 1 node 7 +"B2N8Fbs" - Buoyant spanwise force per unit length at blade 2 node 8 +"B1N2Mbn" - Buoyant moment normal to chord per unit length at blade 1 node 2 +"B2N3Mbt" - Buoyant moment tangential to chord per unit length at blade 2 node 3 +"B1N6Mbs" - Buoyant spanwise moment per unit length at blade 1 node 6 +"B1FldFz" - Total blade aerodynamic/hydrodynamic load for blade 1 (force in z-direction) +"B2FldMx" - Total blade aerodynamic/hydrodynamic load for blade 2 (moment in x-direction) +"HbFbx" - x-component of buoyant force at hub node +"HbFby" - y-component of buoyant force at hub node +"HbFbz" - z-component of buoyant force at hub node +"HbMbx" - x-component of buoyant moment at hub node +"HbMby" - y-component of buoyant moment at hub node +"HbMbz" - z-component of buoyant moment at hub node +"NcFbx" - x-component of buoyant force at nacelle node +"NcFby" - y-component of buoyant force at nacelle node +"NcFbz" - z-component of buoyant force at nacelle node +"NcMbx" - x-component of buoyant moment at nacelle node +"NcMby" - y-component of buoyant moment at nacelle node +"NcMbz" - z-component of buoyant moment at nacelle node +"RtFldFxh" - Total rotor aerodynamic/hydrodynamic and buoyant load (force in x direction) +"RtFldFyh" - Total rotor aerodynamic/hydrodynamic and buoyant load (force in y direction) +"RtFldFzg" - Total rotor aerodynamic/hydrodynamic and buoyant load (force in global z direction) +"RtFldMxh" - Total rotor aerodynamic/hydrodynamic and buoyant load (moment in x direction) +"RtFldMyg" - Total rotor aerodynamic/hydrodynamic and buoyant load (moment in global y direction) +"RtFldMzh" - Total rotor aerodynamic/hydrodynamic and buoyant load (moment in z direction) +"B1N3SigCr" - Critical cavitation number blade 1 node 3 +"B2N5SigCr" - Critical cavitation number blade 2 node 5 +"B1N2SgCav" - Cavitation number blade 1 node 2 +"B2N6SgCav" - Cavitation number blade 2 node 6 +END of input file (the word "END" must appear in the first 3 columns of this last OutList line) +----------------------------------------------------------------------------------------------------- diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat new file mode 100644 index 00000000..5a79e239 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat @@ -0,0 +1,134 @@ +------- ELASTODYN for OpenFAST INPUT FILE -------------------------------------- +Floating MHK turbine structural input properties, based on the RM1 tidal current rotor +---------------------- SIMULATION CONTROL -------------------------------------- +False Echo - Echo input data to ".ech" (flag) + 3 Method - Integration method: {1: RK4, 2: AB4, or 3: ABM4} (-) +"default" DT - Integration time step (s) +---------------------- DEGREES OF FREEDOM -------------------------------------- +False FlapDOF1 - First flapwise blade mode DOF (flag) +False FlapDOF2 - Second flapwise blade mode DOF (flag) +False EdgeDOF - First edgewise blade mode DOF (flag) +False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] +False DrTrDOF - Drivetrain rotational-flexibility DOF (flag) +True GenDOF - Generator DOF (flag) +False YawDOF - Yaw DOF (flag) +False TwFADOF1 - First fore-aft tower bending-mode DOF (flag) +False TwFADOF2 - Second fore-aft tower bending-mode DOF (flag) +False TwSSDOF1 - First side-to-side tower bending-mode DOF (flag) +False TwSSDOF2 - Second side-to-side tower bending-mode DOF (flag) +True PtfmSgDOF - Platform horizontal surge translation DOF (flag) +True PtfmSwDOF - Platform horizontal sway translation DOF (flag) +True PtfmHvDOF - Platform vertical heave translation DOF (flag) +True PtfmRDOF - Platform roll tilt rotation DOF (flag) +True PtfmPDOF - Platform pitch tilt rotation DOF (flag) +True PtfmYDOF - Platform yaw rotation DOF (flag) +---------------------- INITIAL CONDITIONS -------------------------------------- + 0 OoPDefl - Initial out-of-plane blade-tip displacement (meters) + 0 IPDefl - Initial in-plane blade-tip deflection (meters) + 10 BlPitch(1) - Blade 1 initial pitch (degrees) + 10 BlPitch(2) - Blade 2 initial pitch (degrees) + 10 BlPitch(3) - Blade 3 initial pitch (degrees) [unused for 2 blades] + 0 TeetDefl - Initial or fixed teeter angle (degrees) [unused for 3 blades] + 0 Azimuth - Initial azimuth angle for blade 1 (degrees) + 11.50 RotSpeed - Initial or fixed rotor speed (rpm) + 0 NacYaw - Initial or fixed nacelle-yaw angle (degrees) + 0 TTDspFA - Initial fore-aft tower-top displacement (meters) + 0 TTDspSS - Initial side-to-side tower-top displacement (meters) + 20 PtfmSurge - Initial or fixed horizontal surge translational displacement of platform (meters) + 0 PtfmSway - Initial or fixed horizontal sway translational displacement of platform (meters) + 0 PtfmHeave - Initial or fixed vertical heave translational displacement of platform (meters) + 0 PtfmRoll - Initial or fixed roll tilt rotational displacement of platform (degrees) + 0 PtfmPitch - Initial or fixed pitch tilt rotational displacement of platform (degrees) + 0 PtfmYaw - Initial or fixed yaw rotational displacement of platform (degrees) +---------------------- TURBINE CONFIGURATION ----------------------------------- + 2 NumBl - Number of blades (-) + 10.0 TipRad - The distance from the rotor apex to the blade tip (meters) + 1.0 HubRad - The distance from the rotor apex to the blade root (meters) + 0.0 PreCone(1) - Blade 1 cone angle (degrees) + 0.0 PreCone(2) - Blade 2 cone angle (degrees) + 0.0 PreCone(3) - Blade 3 cone angle (degrees) [unused for 2 blades] + 0.2222 HubCM - Distance from rotor apex to hub mass [positive downwind] (meters) + 0 UndSling - Undersling length [distance from teeter pin to the rotor apex] (meters) [unused for 3 blades] + 0 Delta3 - Delta-3 angle for teetering rotors (degrees) [unused for 3 blades] + 0 AzimB1Up - Azimuth value to use for I/O when blade 1 points up (degrees) + -4.91 OverHang - Distance from yaw axis to rotor apex [3 blades] or teeter pin [2 blades] (meters) + 0 ShftGagL - Distance from rotor apex [3 blades] or teeter pin [2 blades] to shaft strain gages [positive for upwind rotors] (meters) + 0 ShftTilt - Rotor shaft tilt angle (degrees) + 0.43 NacCMxn - Downwind distance from the tower-top to the nacelle CM (meters) + 0 NacCMyn - Lateral distance from the tower-top to the nacelle CM (meters) + -1.2 NacCMzn - Vertical distance from the tower-top to the nacelle CM (meters) + 0 NcIMUxn - Downwind distance from the tower-top to the nacelle IMU (meters) + 0 NcIMUyn - Lateral distance from the tower-top to the nacelle IMU (meters) + -1.2 NcIMUzn - Vertical distance from the tower-top to the nacelle IMU (meters) + -1.2 Twr2Shft - Vertical distance from the tower-top to the rotor shaft (meters) + -24.0 TowerHt - Height of tower relative to ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] (meters) + -9.0 TowerBsHt - Height of tower base relative to ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] (meters) + 0 PtfmCMxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) + 0 PtfmCMyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) + -6.09 PtfmCMzt - Vertical distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) + 0 PtfmRefzt - Vertical distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) +---------------------- MASS AND INERTIA ---------------------------------------- + 0 TipMass(1) - Tip-brake mass, blade 1 (kg) + 0 TipMass(2) - Tip-brake mass, blade 2 (kg) + 0 TipMass(3) - Tip-brake mass, blade 3 (kg) [unused for 2 blades] + 140 HubMass - Hub mass (kg) + 79.6 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) + 139.50 GenIner - Generator inertia about HSS (kg m^2) + 40100 NacMass - Nacelle mass (kg) + 244643 NacYIner - Nacelle inertia about yaw axis (kg m^2) + 0 YawBrMass - Yaw bearing mass (kg) + 2525214 PtfmMass - Platform mass (kg) + 195242474 PtfmRIner - Platform inertia for roll tilt rotation about the platform CM (kg m^2) + 919435755 PtfmPIner - Platform inertia for pitch tilt rotation about the platform CM (kg m^2) + 1053535885 PtfmYIner - Platform inertia for yaw rotation about the platform CM (kg m^2) +---------------------- BLADE --------------------------------------------------- + 8 BldNodes - Number of blade nodes (per blade) used for analysis (-) +"MHK_RM1_ElastoDyn_Blade.dat" BldFile(1) - Name of file containing properties for blade 1 (quoted string) +"MHK_RM1_ElastoDyn_Blade.dat" BldFile(2) - Name of file containing properties for blade 2 (quoted string) +"unused" BldFile(3) - Name of file containing properties for blade 3 (quoted string) [unused for 2 blades] +---------------------- ROTOR-TEETER -------------------------------------------- + 0 TeetMod - Rotor-teeter spring/damper model {0: none, 1: standard, 2: user-defined from routine UserTeet} (switch) [unused for 3 blades] + 0 TeetDmpP - Rotor-teeter damper position (degrees) [used only for 2 blades and when TeetMod=1] + 0 TeetDmp - Rotor-teeter damping constant (N-m/(rad/s)) [used only for 2 blades and when TeetMod=1] + 0 TeetCDmp - Rotor-teeter rate-independent Coulomb-damping moment (N-m) [used only for 2 blades and when TeetMod=1] + 0 TeetSStP - Rotor-teeter soft-stop position (degrees) [used only for 2 blades and when TeetMod=1] + 0 TeetHStP - Rotor-teeter hard-stop position (degrees) [used only for 2 blades and when TeetMod=1] + 0 TeetSSSp - Rotor-teeter soft-stop linear-spring constant (N-m/rad) [used only for 2 blades and when TeetMod=1] + 0 TeetHSSp - Rotor-teeter hard-stop linear-spring constant (N-m/rad) [used only for 2 blades and when TeetMod=1] +---------------------- DRIVETRAIN ---------------------------------------------- + 92 GBoxEff - Gearbox efficiency (%) + 53 GBRatio - Gearbox ratio (-) + 600000 DTTorSpr - Drivetrain torsional spring (N-m/rad) + 100000 DTTorDmp - Drivetrain torsional damper (N-m/(rad/s)) +---------------------- FURLING ------------------------------------------------- +False Furling - Read in additional model properties for furling turbine (flag) [must currently be FALSE) +"unused" FurlFile - Name of file containing furling properties (quoted string) [unused when Furling=False] +---------------------- TOWER --------------------------------------------------- + 2 TwrNodes - Number of tower nodes used for analysis (-) +"MHK_RM1_ElastoDyn_Tower.dat" TwrFile - Name of file containing tower properties (quoted string) +---------------------- OUTPUT -------------------------------------------------- +True SumPrint - Print summary data to ".sum" (flag) + 1 OutFile - Switch to determine where output will be placed: {1: in module output file only; 2: in glue code output file only; 3: both} (currently unused) +True TabDelim - Use tab delimiters in text tabular output file? (flag) (currently unused) +"ES10.3E2" OutFmt - Format used for text tabular output (except time). Resulting field should be 10 characters. (quoted string) (currently unused) + 0 TStart - Time to begin tabular output (s) (currently unused) + 1 DecFact - Decimation factor for tabular output {1: output every time step} (-) (currently unused) + 0 NTwGages - Number of tower nodes that have strain gages for output [0 to 9] (-) + 0 TwrGagNd - List of tower nodes that have strain gages [1 to TwrNodes] (-) [unused if NTwGages=0] + 0 NBlGages - Number of blade nodes that have strain gages for output [0 to 9] (-) + 0 BldGagNd - List of blade nodes that have strain gages [1 to BldNodes] (-) [unused if NBlGages=0] + OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) +"PtfmSurge" +"PtfmSway" +"PtfmHeave" +"PtfmRoll" +"PtfmPitch" +"PtfmYaw" +"TwrTpTDxi" +"TwrTpTDyi" +"TwrTpTDzi" +"OoPDefl1" +"RotSpeed" +"GenSpeed" +END of input file (the word "END" must appear in the first 3 columns of this last OutList line) +-------------------------------------------------------------------------------- diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat new file mode 100644 index 00000000..336853a1 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat @@ -0,0 +1,207 @@ +------- HydroDyn Input File ---------------------------------------------------- +Floating MHK turbine hydrodynamic support structure input properties, based on the RM1 tidal current rotor with a quad-style floating platform +False Echo - Echo the input file data (flag) +---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- +"DEFAULT" WtrDens - Water density (kg/m^3) +"DEFAULT" WtrDpth - Water depth (meters) +"DEFAULT" MSL2SWL - Offset between still-water level and mean sea level (meters) [positive upward; unused when WaveMod = 6; must be zero if PotMod=1 or 2] +---------------------- WAVES --------------------------------------------------- + 0 WaveMod - Incident wave kinematics model {0: none=still water, 1: regular (periodic), 1P#: regular with user-specified phase, 2: JONSWAP/Pierson-Moskowitz spectrum (irregular), 3: White noise spectrum (irregular), 4: user-defined spectrum from routine UserWaveSpctrm (irregular), 5: Externally generated wave-elevation time series, 6: Externally generated full wave-kinematics time series [option 6 is invalid for PotMod/=0]} (switch) + 0 WaveStMod - Model for stretching incident wave kinematics to instantaneous free surface {0: none=no stretching, 1: vertical stretching, 2: extrapolation stretching, 3: Wheeler stretching} (switch) [unused when WaveMod=0 or when PotMod/=0] + 3600 WaveTMax - Analysis time for incident wave calculations (sec) [unused when WaveMod=0; determines WaveDOmega=2Pi/WaveTMax in the IFFT] + 0.1 WaveDT - Time step for incident wave calculations (sec) [unused when WaveMod=0; 0.1<=WaveDT<=1.0 recommended; determines WaveOmegaMax=Pi/WaveDT in the IFFT] + 1.0 WaveHs - Significant wave height of incident waves (meters) [used only when WaveMod=1, 2, or 3] + 10 WaveTp - Peak-spectral period of incident waves (sec) [used only when WaveMod=1 or 2] +"DEFAULT" WavePkShp - Peak-shape parameter of incident wave spectrum (-) or DEFAULT (string) [used only when WaveMod=2; use 1.0 for Pierson-Moskowitz] + 0.314159 WvLowCOff - Low cut-off frequency or lower frequency limit of the wave spectrum beyond which the wave spectrum is zeroed (rad/s) [unused when WaveMod=0, 1, or 6] + 1.570796 WvHiCOff - High cut-off frequency or upper frequency limit of the wave spectrum beyond which the wave spectrum is zeroed (rad/s) [unused when WaveMod=0, 1, or 6] + 0 WaveDir - Incident wave propagation heading direction (degrees) [unused when WaveMod=0 or 6] + 0 WaveDirMod - Directional spreading function {0: none, 1: COS2S} (-) [only used when WaveMod=2,3, or 4] + 1 WaveDirSpread - Wave direction spreading coefficient ( > 0 ) (-) [only used when WaveMod=2,3, or 4 and WaveDirMod=1] + 1 WaveNDir - Number of wave directions (-) [only used when WaveMod=2,3, or 4 and WaveDirMod=1; odd number only] + 0 WaveDirRange - Range of wave directions (full range: WaveDir +/- 1/2*WaveDirRange) (degrees) [only used when WaveMod=2,3,or 4 and WaveDirMod=1] + 123456789 WaveSeed(1) - First random seed of incident waves [-2147483648 to 2147483647] (-) [unused when WaveMod=0, 5, or 6] + RANLUX WaveSeed(2) - Second random seed of incident waves [-2147483648 to 2147483647] for intrinsic pRNG, or an alternative pRNG: "RanLux" (-) [unused when WaveMod=0, 5, or 6] +FALSE WaveNDAmp - Flag for normally distributed amplitudes (flag) [only used when WaveMod=2, 3, or 4] +"" WvKinFile - Root name of externally generated wave data file(s) (quoted string) [used only when WaveMod=5 or 6] + 1 NWaveElev - Number of points where the incident wave elevations can be computed (-) [maximum of 9 output locations] + 0 WaveElevxi - List of xi-coordinates for points where the incident wave elevations can be output (meters) [NWaveElev points, separated by commas or white space; usused if NWaveElev = 0] + 0 WaveElevyi - List of yi-coordinates for points where the incident wave elevations can be output (meters) [NWaveElev points, separated by commas or white space; usused if NWaveElev = 0] +---------------------- 2ND-ORDER WAVES ----------------------------------------- [unused with WaveMod=0 or 6] +FALSE WvDiffQTF - Full difference-frequency 2nd-order wave kinematics (flag) +FALSE WvSumQTF - Full summation-frequency 2nd-order wave kinematics (flag) + 0 WvLowCOffD - Low frequency cutoff used in the difference-frequencies (rad/s) [Only used with a difference-frequency method] + 1.256637 WvHiCOffD - High frequency cutoff used in the difference-frequencies (rad/s) [Only used with a difference-frequency method] + 0.618319 WvLowCOffS - Low frequency cutoff used in the summation-frequencies (rad/s) [Only used with a summation-frequency method] + 3.141593 WvHiCOffS - High frequency cutoff used in the summation-frequencies (rad/s) [Only used with a summation-frequency method] +---------------------- CURRENT ------------------------------------------------- [unused with WaveMod=6] + 1 CurrMod - Current profile model {0: none=no current, 1: standard, 2: user-defined from routine UserCurrent} (switch) + 0 CurrSSV0 - Sub-surface current velocity at still water level (m/s) [used only when CurrMod=1] + 0 CurrSSDir - Sub-surface current heading direction (degrees) or DEFAULT (string) [used only when CurrMod=1] + 12.2 CurrNSRef - Near-surface current reference depth (meters) [used only when CurrMod=1] + 0 CurrNSV0 - Near-surface current velocity at still water level (m/s) [used only when CurrMod=1] + 0 CurrNSDir - Near-surface current heading direction (degrees) [used only when CurrMod=1] + 1.9 CurrDIV - Depth-independent current velocity (m/s) [used only when CurrMod=1] + 0 CurrDIDir - Depth-independent current heading direction (degrees) [used only when CurrMod=1] +---------------------- FLOATING PLATFORM --------------------------------------- [unused with WaveMod=6] + 1 PotMod - Potential-flow model {0: none=no potential flow, 1: frequency-to-time-domain transforms based on WAMIT output, 2: fluid-impulse theory (FIT)} (switch) + 1 ExctnMod - Wave-excitation model {0: no wave-excitation calculation, 1: DFT, 2: state-space} (switch) [only used when PotMod=1; STATE-SPACE REQUIRES *.ssexctn INPUT FILE] + 1 RdtnMod - Radiation memory-effect model {0: no memory-effect calculation, 1: convolution, 2: state-space} (switch) [only used when PotMod=1; STATE-SPACE REQUIRES *.ss INPUT FILE] + 60 RdtnTMax - Analysis time for wave radiation kernel calculations (sec) [only used when PotMod=1 and RdtnMod=1; determines RdtnDOmega=Pi/RdtnTMax in the cosine transform; MAKE SURE THIS IS LONG ENOUGH FOR THE RADIATION IMPULSE RESPONSE FUNCTIONS TO DECAY TO NEAR-ZERO FOR THE GIVEN PLATFORM!] + "DEFAULT" RdtnDT - Time step for wave radiation kernel calculations (sec) [only used when PotMod=1 and ExctnMod>1 or RdtnMod>0; DT<=RdtnDT<=0.1 recommended; determines RdtnOmegaMax=Pi/RdtnDT in the cosine transform] + 1 NBody - Number of WAMIT bodies to be used (-) [>=1; only used when PotMod=1. If NBodyMod=1, the WAMIT data contains a vector of size 6*NBody x 1 and matrices of size 6*NBody x 6*NBody; if NBodyMod>1, there are NBody sets of WAMIT data each with a vector of size 6 x 1 and matrices of size 6 x 6] + 2 NBodyMod - Body coupling model {1: include coupling terms between each body and NBody in HydroDyn equals NBODY in WAMIT, 2: neglect coupling terms between each body and NBODY=1 with XBODY=0 in WAMIT, 3: Neglect coupling terms between each body and NBODY=1 with XBODY=/0 in WAMIT} (switch) [only used when PotMod=1] +"MHK_RM1_Floating" PotFile - Root name of potential-flow model data; WAMIT output files containing the linear, nondimensionalized, hydrostatic restoring matrix (.hst), frequency-dependent hydrodynamic added mass matrix and damping matrix (.1), and frequency- and direction-dependent wave excitation force vector per unit wave amplitude (.3) (quoted string) [1 to NBody if NBodyMod>1] [only used when PotMod=1 and ExctnMod>0 or RdtnMod>0] [MAKE SURE THE FREQUENCIES INHERENT IN THESE WAMIT FILES SPAN THE PHYSICALLY-SIGNIFICANT RANGE OF FREQUENCIES FOR THE GIVEN PLATFORM; THEY MUST CONTAIN THE ZERO- AND INFINITE-FREQUENCY LIMITS!] + 1 WAMITULEN - Characteristic body length scale used to redimensionalize WAMIT output (meters) [1 to NBody if NBodyMod>1] [only used when PotMod=1 and ExctnMod=1 or RdtnMod=1] + 0 PtfmRefxt - The xt offset of the body reference point(s) from (0,0,0) (meters) [1 to NBody] [only used when PotMod=1] + 0 PtfmRefyt - The yt offset of the body reference point(s) from (0,0,0) (meters) [1 to NBody] [only used when PotMod=1] + 0 PtfmRefzt - The zt offset of the body reference point(s) from (0,0,0) (meters) [1 to NBody] [only used when PotMod=1. If NBodyMod=2,PtfmRefzt=0.0] + 0 PtfmRefztRot - The rotation about zt of the body reference frame(s) from xt/yt (degrees) [1 to NBody] [only used when PotMod=1] + 2671.85 PtfmVol0 - **Note - 2672.6 from WAMIT with -0.748 correction for missing tower base hydrostatic pressure ** Displaced volume of water when the body is in its undisplaced position (m^3) [1 to NBody] [only used when PotMod=1; USE THE SAME VALUE COMPUTED BY WAMIT AS OUTPUT IN THE .OUT FILE!] + 0 PtfmCOBxt - The xt offset of the center of buoyancy (COB) from (0,0) (meters) [1 to NBody] [only used when PotMod=1] + 0 PtfmCOByt - The yt offset of the center of buoyancy (COB) from (0,0) (meters) [1 to NBody] [only used when PotMod=1] +---------------------- 2ND-ORDER FLOATING PLATFORM FORCES ---------------------- [unused with WaveMod=0 or 6, or PotMod=0 or 2] + 0 MnDrift - Mean-drift 2nd-order forces computed {0: None; [7, 8, 9, 10, 11, or 12]: WAMIT file to use} [Only one of MnDrift, NewmanApp, or DiffQTF can be non-zero. If NBody>1, MnDrift /=8] + 0 NewmanApp - Mean- and slow-drift 2nd-order forces computed with Newman's approximation {0: None; [7, 8, 9, 10, 11, or 12]: WAMIT file to use} [Only one of MnDrift, NewmanApp, or DiffQTF can be non-zero. If NBody>1, NewmanApp/=8. Used only when WaveDirMod=0] + 0 DiffQTF - Full difference-frequency 2nd-order forces computed with full QTF {0: None; [10, 11, or 12]: WAMIT file to use} [Only one of MnDrift, NewmanApp, or DiffQTF can be non-zero] + 0 SumQTF - Full summation -frequency 2nd-order forces computed with full QTF {0: None; [10, 11, or 12]: WAMIT file to use} +---------------------- PLATFORM ADDITIONAL STIFFNESS AND DAMPING -------------- [unused with PotMod=0 or 2] + 0 AddF0 - Additional preload (N, N-m) [If NBodyMod=1, one size 6*NBody x 1 vector; if NBodyMod>1, NBody size 6 x 1 vectors] + 0 + 0 + 0 + 0 + 0 + 0 0 0 0 0 0 AddCLin - Additional linear stiffness (N/m, N/rad, N-m/m, N-m/rad) [If NBodyMod=1, one size 6*NBody x 6*NBody matrix; if NBodyMod>1, NBody size 6 x 6 matrices] + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 AddBLin - Additional linear damping(N/(m/s), N/(rad/s), N-m/(m/s), N-m/(rad/s)) [If NBodyMod=1, one size 6*NBody x 6*NBody matrix; if NBodyMod>1, NBody size 6 x 6 matrices] + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 AddBQuad - Additional quadratic drag(N/(m/s)^2, N/(rad/s)^2, N-m(m/s)^2, N-m/(rad/s)^2) [If NBodyMod=1, one size 6*NBody x 6*NBody matrix; if NBodyMod>1, NBody size 6 x 6 matrices] + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 + 0 0 0 0 0 0 +---------------------- AXIAL COEFFICIENTS -------------------------------------- + 2 NAxCoef - Number of axial coefficients (-) +AxCoefID AxCd AxCa AxCp +(-) (-) (-) (-) +1 0.00 0.00 0.00 ! Columns / Braces (no exposed member ends) +2 1.00 1.00 1.00 ! Heave Plates +---------------------- MEMBER JOINTS ------------------------------------------- + 33 NJoints - Number of joints (-) [must be exactly 0 or at least 2] +JointID Jointxi Jointyi Jointzi JointAxID JointOvrlp [JointOvrlp= 0: do nothing at joint, 1: eliminate overlaps by calculating super member] +(-) (m) (m) (m) (-) (switch) +0 28.0 0 -10 1 0 ! Downstream Column +1 28.0 0 6 1 0 +2 -28.0 0 -10 1 0 ! Upstream Column +3 -28.0 0 6 1 0 +4 0 -12.0 -10 1 0 ! Starboard Column +5 0 -12.0 6 1 0 +6 0 12.0 -10 1 0 ! Port Column +7 0 12.0 6 1 0 +8 3.67658 10.4243 4.5 1 0 ! Upper Braces +9 24.3234 1.57568 4.5 1 0 +10 3.67658 -10.4243 4.5 1 0 +11 24.3234 -1.57568 4.5 1 0 +12 -3.67658 10.4243 4.5 1 0 +13 -24.3234 1.57568 4.5 1 0 +14 -3.67658 -10.4243 4.5 1 0 +15 -24.3234 -1.57568 4.5 1 0 +16 3.67658 10.4243 -8.5 1 0 ! Lower Braces +17 24.3234 1.57568 -8.5 1 0 +18 3.67658 -10.4243 -8.5 1 0 +19 24.3234 -1.57568 -8.5 1 0 +20 -3.67658 10.4243 -8.5 1 0 +21 -24.3234 1.57568 -8.5 1 0 +22 -3.67658 -10.4243 -8.5 1 0 +23 -24.3234 -1.57568 -8.5 1 0 +24 0 -8 4.5 1 0 ! Tower Braces +25 0 8 4.5 1 0 +26 0 -8 -8.5 1 0 +27 0 8 -8.5 1 0 +28 0 0 -8.5 1 0 +29 28.0 0 -10.5 2 0 ! Heave Plates +30 -28.0 0 -10.5 2 0 +31 0 -12.0 -10.5 2 0 +32 0 12.0 -10.5 2 0 +---------------------- MEMBER CROSS-SECTION PROPERTIES ------------------------- + 4 NPropSets - Number of member property sets (-) +PropSetID PropD PropThck +(-) (m) (m) +0 8.0 0.02 ! Columns +1 2.0 0.02 ! Braces +2 2.0 0.081 ! Flooded Braces (not flooded in hydrodyn) +3 12.0 0.3925 ! Flooded Heave Plates (not flooded in hydrodyn) +---------------------- SIMPLE HYDRODYNAMIC COEFFICIENTS (model 1) -------------- +SimplCd SimplCdMG SimplCa SimplCaMG SimplCp SimplCpMG SimplAxCd SimplAxCdMG SimplAxCa SimplAxCaMG SimplAxCp SimplAxCpMG +(-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) +1.2 0.00 1.00 0.00 1.00 1.00 0.00 0.00 0.00 0.00 1.00 1.00 +---------------------- DEPTH-BASED HYDRODYNAMIC COEFFICIENTS (model 2) --------- + 0 NCoefDpth - Number of depth-dependent coefficients (-) +Dpth DpthCd DpthCdMG DpthCa DpthCaMG DpthCp DpthCpMG DpthAxCd DpthAxCdMG DpthAxCa DpthAxCaMG DpthAxCp DpthAxCpMG +(m) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) +---------------------- MEMBER-BASED HYDRODYNAMIC COEFFICIENTS (model 3) -------- + 0 NCoefMembers - Number of member-based coefficients (-) +MemberID MemberCd1 MemberCd2 MemberCdMG1 MemberCdMG2 MemberCa1 MemberCa2 MemberCaMG1 MemberCaMG2 MemberCp1 MemberCp2 MemberCpMG1 MemberCpMG2 MemberAxCd1 MemberAxCd2 MemberAxCdMG1 MemberAxCdMG2 MemberAxCa1 MemberAxCa2 MemberAxCaMG1 MemberAxCaMG2 MemberAxCp1 MemberAxCp2 MemberAxCpMG1 MemberAxCpMG2 +(-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) +-------------------- MEMBERS --------------------------------------------------- + 20 NMembers - Number of members (-) +MemberID MJointID1 MJointID2 MPropSetID1 MPropSetID2 MDivSize MCoefMod PropPot [MCoefMod=1: use simple coeff table, 2: use depth-based coeff table, 3: use member-based coeff table] [ PropPot/=0 if member is modeled with potential-flow theory] +(-) (-) (-) (-) (-) (m) (switch) (flag) +0 0 1 0 0 0.1 1 TRUE ! Columns +1 2 3 0 0 0.1 1 TRUE +2 4 5 0 0 0.1 1 TRUE +3 6 7 0 0 0.1 1 TRUE +4 8 9 1 1 0.1 1 TRUE ! Upper Braces +5 10 11 1 1 0.1 1 TRUE +6 12 13 1 1 0.1 1 TRUE +7 14 15 1 1 0.1 1 TRUE +8 16 17 2 2 0.1 1 TRUE ! Lower Braces +9 18 19 2 2 0.1 1 TRUE +10 20 21 2 2 0.1 1 TRUE +11 22 23 2 2 0.1 1 TRUE +12 24 25 1 1 0.1 1 TRUE ! Tower Braces +13 26 27 1 1 0.1 1 TRUE +14 24 28 1 1 0.1 1 TRUE +15 25 28 1 1 0.1 1 TRUE +16 0 29 3 3 0.1 1 TRUE ! Heave Plates +17 2 30 3 3 0.1 1 TRUE +18 4 31 3 3 0.1 1 TRUE +19 6 32 3 3 0.1 1 TRUE +---------------------- FILLED MEMBERS ------------------------------------------ + 0 NFillGroups - Number of filled member groups (-) [If FillDens = DEFAULT, then FillDens = WtrDens; FillFSLoc is related to MSL2SWL] +FillNumM FillMList FillFSLoc FillDens +(-) (-) (m) (kg/m^3) +---------------------- MARINE GROWTH ------------------------------------------- + 0 NMGDepths - Number of -growth depths specified (-) +MGDpth MGThck MGDens +(m) (m) (kg/m^3) +---------------------- MEMBER OUTPUT LIST -------------------------------------- + 0 NMOutputs - Number of member outputs (-) [must be < 10] +MemberID NOutLoc NodeLocs [NOutLoc < 10; node locations are normalized distance from the start of the member, and must be >=0 and <= 1] [unused if NMOutputs=0] +(-) (-) (-) +---------------------- JOINT OUTPUT LIST --------------------------------------- + 0 NJOutputs - Number of joint outputs [Must be < 10] + 0 JOutLst - List of JointIDs which are to be output (-)[unused if NJOutputs=0] +---------------------- OUTPUT -------------------------------------------------- +True HDSum - Output a summary file [flag] +False OutAll - Output all user-specified member and joint loads (only at each member end, not interior locations) [flag] + 2 OutSwtch - Output requested channels to: [1=Hydrodyn.out, 2=GlueCode.out, 3=both files] +"E15.7e2" OutFmt - Output format for numerical results (quoted string) [not checked for validity!] +"A11" OutSFmt - Output format for header strings (quoted string) [not checked for validity!] +---------------------- OUTPUT CHANNELS ----------------------------------------- +"Wave1Elev" - Wave elevation at the platform reference point (0, 0) +"HydroFxi" - Buoyancy force [N] in the X direction. +"HydroFyi" - Buoyancy force [N] in the Y direction. +"HydroFzi" - Buoyancy force [N] in the vertical direction (Z). +END of output channels and end of file. (the word "END" must appear in the first 3 columns of this line) + diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_InflowWind.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_InflowWind.dat new file mode 100644 index 00000000..73c0b2f7 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_InflowWind.dat @@ -0,0 +1,69 @@ +------- InflowWind INPUT FILE --------------------------------------------------------------------------------- +Steady 1.9 m/s inflow for floating MHK turbine, based on the RM1 tidal current rotor +--------------------------------------------------------------------------------------------------------------- +False Echo - Echo input data to .ech (flag) + 1 WindType - Switch for wind file type (1=steady; 2=uniform; 3=binary TurbSim FF; 4=binary Bladed-style FF; 5=HAWC format; 6=User defined; 7=native Bladed FF) + 0 PropagationDir - Direction of wind propagation (meteorological rotation from aligned with X (positive rotates towards -Y) -- degrees) (not used for native Bladed format WindType=7) + 0 VFlowAng - Upflow angle (degrees) (not used for native Bladed format WindType=7) +False VelInterpCubic - Use cubic interpolation for velocity in time (false=linear, true=cubic) [Used with WindType=2,3,4,5,7] + 1 NWindVel - Number of points to output the wind velocity (0 to 9) + 0 WindVxiList - List of coordinates in the inertial X direction (m) + 0 WindVyiList - List of coordinates in the inertial Y direction (m) + 12.2 WindVziList - List of coordinates in the inertial Z direction (m) +================== Parameters for Steady Wind Conditions [used only for WindType = 1] ======================= + 1.9 HWindSpeed - Horizontal wind speed (m/s) + 12.2 RefHt - Reference height for horizontal wind speed (m) + 0 PLExp - Power law exponent (-) +================== Parameters for Uniform wind file [used only for WindType = 2] ============================ +"unused" Filename_Uni - Filename of time series data for uniform wind field. (-) + 30 RefHt_Uni - Reference height for horizontal wind speed (m) + 125.88 RefLength - Reference length for linear horizontal and vertical sheer (-) +================== Parameters for Binary TurbSim Full-Field files [used only for WindType = 3] ============== +"unused" FileName_BTS - Name of the Full field wind file to use (.bts) +================== Parameters for Binary Bladed-style Full-Field files [used only for WindType = 4 or WindType = 7] ======= +"unused" FileNameRoot - WindType=4: Rootname of the full-field wind file to use (.wnd, .sum); WindType=7: name of the intermediate file with wind scaling values +False TowerFile - Have tower file (.twr) (flag) ignored when WindType = 7 +================== Parameters for HAWC-format binary files [Only used with WindType = 5] ==================== +"unused" FileName_u - name of the file containing the u-component fluctuating wind (.bin) +"unused" FileName_v - name of the file containing the v-component fluctuating wind (.bin) +"unused" FileName_w - name of the file containing the w-component fluctuating wind (.bin) + 64 nx - number of grids in the x direction (in the 3 files above) (-) + 32 ny - number of grids in the y direction (in the 3 files above) (-) + 32 nz - number of grids in the z direction (in the 3 files above) (-) + 16 dx - distance (in meters) between points in the x direction (m) + 3 dy - distance (in meters) between points in the y direction (m) + 3 dz - distance (in meters) between points in the z direction (m) + 90 RefHt_Hawc - reference height; the height (in meters) of the vertical center of the grid (m) + ------------- Scaling parameters for turbulence --------------------------------------------------------- + 1 ScaleMethod - Turbulence scaling method [0 = none, 1 = direct scaling, 2 = calculate scaling factor based on a desired standard deviation] + 1 SFx - Turbulence scaling factor for the x direction (-) [ScaleMethod=1] + 1 SFy - Turbulence scaling factor for the y direction (-) [ScaleMethod=1] + 1 SFz - Turbulence scaling factor for the z direction (-) [ScaleMethod=1] + 1 SigmaFx - Turbulence standard deviation to calculate scaling from in x direction (m/s) [ScaleMethod=2] + 1 SigmaFy - Turbulence standard deviation to calculate scaling from in y direction (m/s) [ScaleMethod=2] + 1 SigmaFz - Turbulence standard deviation to calculate scaling from in z direction (m/s) [ScaleMethod=2] + ------------- Mean wind profile parameters (added to HAWC-format files) --------------------------------- + 5 URef - Mean u-component wind speed at the reference height (m/s) + 2 WindProfile - Wind profile type (0=constant;1=logarithmic,2=power law) + 0 PLExp_Hawc - Power law exponent (-) (used for PL wind profile type only) + 0.03 Z0 - Surface roughness length (m) (used for LG wind profile type only) + 0 XOffset - Initial offset in +x direction (shift of wind box) +================== LIDAR Parameters =========================================================================== +0 SensorType - Switch for lidar configuration (0 = None, 1 = Single Point Beam(s), 2 = Continuous, 3 = Pulsed) +0 NumPulseGate - Number of lidar measurement gates (used when SensorType = 3) +30 PulseSpacing - Distance between range gates (m) (used when SensorType = 3) +0 NumBeam - Number of lidar measurement beams (0-5)(used when SensorType = 1) +-200 FocalDistanceX - Focal distance co-ordinates of the lidar beam in the x direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceY - Focal distance co-ordinates of the lidar beam in the y direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceZ - Focal distance co-ordinates of the lidar beam in the z direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0.0 0.0 0.0 RotorApexOffsetPos - Offset of the lidar from hub height (m) +17 URefLid - Reference average wind speed for the lidar[m/s] +0.25 MeasurementInterval - Time between each measurement [s] +False LidRadialVel - TRUE => return radial component, FALSE => return 'x' direction estimate +1 ConsiderHubMotion - Flag whether to consider the hub motion's impact on Lidar measurements +================== OUTPUT ===================================================================================== +True SumPrint - Print summary data to .IfW.sum (flag) + OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) +Wind1VelX +END of input file (the word "END" must appear in the first 3 columns of this last OutList line) +--------------------------------------------------------------------------------------------------------------- diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat new file mode 100644 index 00000000..89e416dc --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat @@ -0,0 +1,58 @@ +--------------------- MoorDyn Input File ------------------------------------ +Floating MHK turbine mooring input properties, based on the RM1 tidal current rotor with a quad-style floating platform +FALSE Echo - echo the input file data (flag) +----------------------- LINE TYPES Chain studless 0.018m -------------------- +Name Diam MassDen EA BA/-zeta EI Cd Ca CdAx CaAx +(-) (m) (kg/m) (N) (N-s/-) (-) (-) (-) (-) (-) +main 0.324 644.8 85.4e8 -0.8 0.8 2.4 1.0 1.15 0.5 +---------------------- POINTS ----------------------------------------------- +Node Type X Y Z M V CdA CA +(-) (-) (m) (m) (m) (kg) (m^3) (m^2) (-) +1 Fixed -152.0 -50.0 -50.0 0 0 0 0 +2 Fixed -152.0 0.0 -50.0 0 0 0 0 +3 Fixed -152.0 50.0 -50.0 0 0 0 0 +4 Fixed 152.0 -50.0 -50.0 0 0 0 0 +5 Fixed 152.0 0.0 -50.0 0 0 0 0 +6 Fixed 152.0 50.0 -50.0 0 0 0 0 +7 Vessel -34.0 0.0 -10.0 0 0 0 0 +8 Vessel -34.0 0.0 -10.0 0 0 0 0 +9 Vessel -34.0 0.0 -10.0 0 0 0 0 +10 Vessel 34.0 0.0 -10.0 0 0 0 0 +11 Vessel 34.0 0.0 -10.0 0 0 0 0 +12 Vessel 34.0 0.0 -10.0 0 0 0 0 +---------------------- LINES ------------------------------------------------ +Line LineType AttachA AttachB UnstrLen NumSegs Outputs +(-) (-) (-) (-) (m) (-) (-) +1 main 1 7 160.0 30 - +2 main 2 8 152.0 30 - +3 main 3 9 160.0 30 - +4 main 4 10 160.0 30 - +5 main 5 11 152.0 30 - +6 main 6 12 160.0 30 - +---------------------- SOLVER OPTIONS --------------------------------------- +0.5e-4 dtM - time step to use in mooring integration (s) +3.0e6 kbot - bottom stiffness (Pa/m) +3.0e5 cbot - bottom damping (Pa-s/m) +1.0 dtIC - time interval for analyzing convergence during IC gen (s) +10.0 TmaxIC - max time for ic gen (s) +4.0 CdScaleIC - factor by which to scale drag coefficients during dynamic relaxation (-) +0.1 threshIC - threshold for IC convergence (-) +------------------------ OUTPUTS -------------------------------------------- +FairTen1 FairTen2 FairTen3 FairTen4 FairTen5 FairTen6 +AnchTen1 AnchTen2 AnchTen3 AnchTen4 AnchTen5 AnchTen6 +Con1fX Con1fY Con1fZ +Con2fX Con2fY Con2fZ +Con3fX Con3fY Con3fZ +Con4fX Con4fY Con4fZ +Con5fX Con5fY Con5fZ +Con6fX Con6fY Con6fZ +Con7fX Con7fY Con7fZ Con7pX Con7pY Con7pZ +Con8fX Con8fY Con8fZ Con8pX Con8pY Con8pZ +Con9fX Con9fY Con9fZ Con9pX Con9pY Con9pZ +Con10fX Con10fY Con10fZ Con10pX Con10pY Con10pZ +Con11fX Con11fY Con11fZ Con11pX Con11pY Con11pZ +Con12fX Con12fY Con12fZ Con12pX Con12pY Con12pZ +L1N1pZ L1N2pZ L1N3pZ L1N4pZ L1N5pZ L1N6pZ L1N7pZ L1N8pZ L1N9pZ L1N10pZ L1N11pZ L1N12pZ L1N13pZ L1N14pZ L1N15pZ L1N16pZ L1N17pZ L1N18pZ L1N19pZ L1N20pZ L1N21pZ L1N22pZ L1N23pZ L1N24pZ L1N25pZ L1N26pZ L1N27pZ L1N28pZ L1N29pZ L1N30pZ +L2N1pZ L2N2pZ L2N3pZ L2N4pZ L2N5pZ L2N6pZ L2N7pZ L2N8pZ L2N9pZ L2N10pZ L2N11pZ L2N12pZ L2N13pZ L2N14pZ L2N15pZ L2N16pZ L2N17pZ L2N18pZ L2N19pZ L2N20pZ L2N21pZ L2N22pZ L2N23pZ L2N24pZ L2N25pZ L2N26pZ L2N27pZ L2N28pZ L2N29pZ L2N30pZ +END +------------------------- need this line ------------------------------------ diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat new file mode 100644 index 00000000..c41f6a55 --- /dev/null +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat @@ -0,0 +1,111 @@ +------- SERVODYN v1.05.* INPUT FILE -------------------------------------------- +NREL 5.0 MW Baseline Wind Turbine for Use in Offshore Analysis. Properties from Dutch Offshore Wind Energy Converter (DOWEC) 6MW Pre-Design (10046_009.pdf) and REpower 5M 5MW (5m_uk.pdf) +---------------------- SIMULATION CONTROL -------------------------------------- +False Echo - Echo input data to .ech (flag) +"default" DT - Communication interval for controllers (s) (or "default") +---------------------- PITCH CONTROL ------------------------------------------- + 5 PCMode - Pitch control mode {0: none, 3: user-defined from routine PitchCntrl, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) + 0 TPCOn - Time to enable active pitch control (s) [unused when PCMode=0] + 9999.9 TPitManS(1) - Time to start override pitch maneuver for blade 1 and end standard pitch control (s) + 9999.9 TPitManS(2) - Time to start override pitch maneuver for blade 2 and end standard pitch control (s) + 9999.9 TPitManS(3) - Time to start override pitch maneuver for blade 3 and end standard pitch control (s) [unused for 2 blades] + 2 PitManRat(1) - Pitch rate at which override pitch maneuver heads toward final pitch angle for blade 1 (deg/s) + 2 PitManRat(2) - Pitch rate at which override pitch maneuver heads toward final pitch angle for blade 2 (deg/s) + 2 PitManRat(3) - Pitch rate at which override pitch maneuver heads toward final pitch angle for blade 3 (deg/s) [unused for 2 blades] + 0 BlPitchF(1) - Blade 1 final pitch for pitch maneuvers (degrees) + 0 BlPitchF(2) - Blade 2 final pitch for pitch maneuvers (degrees) + 0 BlPitchF(3) - Blade 3 final pitch for pitch maneuvers (degrees) [unused for 2 blades] +---------------------- GENERATOR AND TORQUE CONTROL ---------------------------- + 5 VSContrl - Variable-speed control mode {0: none, 1: simple VS, 3: user-defined from routine UserVSCont, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) + 2 GenModel - Generator model {1: simple, 2: Thevenin, 3: user-defined from routine UserGen} (switch) [used only when VSContrl=0] + 94.4 GenEff - Generator efficiency [ignored by the Thevenin and user-defined generator models] (%) +True GenTiStr - Method to start the generator {T: timed using TimGenOn, F: generator speed using SpdGenOn} (flag) +True GenTiStp - Method to stop the generator {T: timed using TimGenOf, F: when generator power = 0} (flag) + 9999.9 SpdGenOn - Generator speed to turn on the generator for a startup (HSS speed) (rpm) [used only when GenTiStr=False] + 0 TimGenOn - Time to turn on the generator for a startup (s) [used only when GenTiStr=True] + 9999.9 TimGenOf - Time to turn off the generator (s) [used only when GenTiStp=True] +---------------------- SIMPLE VARIABLE-SPEED TORQUE CONTROL -------------------- + 9999.9 VS_RtGnSp - Rated generator speed for simple variable-speed generator control (HSS side) (rpm) [used only when VSContrl=1] + 9999.9 VS_RtTq - Rated generator torque/constant generator torque in Region 3 for simple variable-speed generator control (HSS side) (N-m) [used only when VSContrl=1] + 9999.9 VS_Rgn2K - Generator torque constant in Region 2 for simple variable-speed generator control (HSS side) (N-m/rpm^2) [used only when VSContrl=1] + 9999.9 VS_SlPc - Rated generator slip percentage in Region 2 1/2 for simple variable-speed generator control (%) [used only when VSContrl=1] +---------------------- SIMPLE INDUCTION GENERATOR ------------------------------ + 9999.9 SIG_SlPc - Rated generator slip percentage (%) [used only when VSContrl=0 and GenModel=1] + 9999.9 SIG_SySp - Synchronous (zero-torque) generator speed (rpm) [used only when VSContrl=0 and GenModel=1] + 9999.9 SIG_RtTq - Rated torque (N-m) [used only when VSContrl=0 and GenModel=1] + 9999.9 SIG_PORt - Pull-out ratio (Tpullout/Trated) (-) [used only when VSContrl=0 and GenModel=1] +---------------------- THEVENIN-EQUIVALENT INDUCTION GENERATOR ----------------- + 9999.9 TEC_Freq - Line frequency [50 or 60] (Hz) [used only when VSContrl=0 and GenModel=2] + 9998 TEC_NPol - Number of poles [even integer > 0] (-) [used only when VSContrl=0 and GenModel=2] + 9999.9 TEC_SRes - Stator resistance (ohms) [used only when VSContrl=0 and GenModel=2] + 9999.9 TEC_RRes - Rotor resistance (ohms) [used only when VSContrl=0 and GenModel=2] + 9999.9 TEC_VLL - Line-to-line RMS voltage (volts) [used only when VSContrl=0 and GenModel=2] + 9999.9 TEC_SLR - Stator leakage reactance (ohms) [used only when VSContrl=0 and GenModel=2] + 9999.9 TEC_RLR - Rotor leakage reactance (ohms) [used only when VSContrl=0 and GenModel=2] + 9999.9 TEC_MR - Magnetizing reactance (ohms) [used only when VSContrl=0 and GenModel=2] +---------------------- HIGH-SPEED SHAFT BRAKE ---------------------------------- + 0 HSSBrMode - HSS brake model {0: none, 1: simple, 3: user-defined from routine UserHSSBr, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) + 9999.9 THSSBrDp - Time to initiate deployment of the HSS brake (s) + 0.6 HSSBrDT - Time for HSS-brake to reach full deployment once initiated (sec) [used only when HSSBrMode=1] + 28116.2 HSSBrTqF - Fully deployed HSS-brake torque (N-m) +---------------------- NACELLE-YAW CONTROL ------------------------------------- + 0 YCMode - Yaw control mode {0: none, 3: user-defined from routine UserYawCont, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) + 9999.9 TYCOn - Time to enable active yaw control (s) [unused when YCMode=0] + 0 YawNeut - Neutral yaw position--yaw spring force is zero at this yaw (degrees) +9.02832E+09 YawSpr - Nacelle-yaw spring constant (N-m/rad) + 1.916E+07 YawDamp - Nacelle-yaw damping constant (N-m/(rad/s)) + 9999.9 TYawManS - Time to start override yaw maneuver and end standard yaw control (s) + 2 YawManRat - Yaw maneuver rate (in absolute value) (deg/s) + 0 NacYawF - Final yaw angle for override yaw maneuvers (degrees) +---------------------- AERODYNAMIC FLOW CONTROL -------------------------------- + 0 AfCmode - Airfoil control mode {0: none, 1: cosine wave cycle, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) + 0 AfC_Mean - Mean level for cosine cycling or steady value (-) [used only with AfCmode==1] + 0 AfC_Amp - Amplitude for for cosine cycling of flap signal (-) [used only with AfCmode==1] + 0 AfC_Phase - Phase relative to the blade azimuth (0 is vertical) for for cosine cycling of flap signal (deg) [used only with AfCmode==1] +---------------------- STRUCTURAL CONTROL -------------------------------------- +0 NumBStC - Number of blade structural controllers (integer) +"unused" BStCfiles - Name of the files for blade structural controllers (quoted strings) [unused when NumBStC==0] +0 NumNStC - Number of nacelle structural controllers (integer) +"unused" NStCfiles - Name of the files for nacelle structural controllers (quoted strings) [unused when NumNStC==0] +0 NumTStC - Number of tower structural controllers (integer) +"unused" TStCfiles - Name of the files for tower structural controllers (quoted strings) [unused when NumTStC==0] +0 NumSStC - Number of substructure structural controllers (integer) +"unused" SStCfiles - Name of the files for substructure structural controllers (quoted strings) [unused when NumSStC==0] +---------------------- CABLE CONTROL ------------------------------------------- + 0 CCmode - Cable control mode {0: none, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) +---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] +"../../../lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"MHK_RM1_DISCON.IN" DLL_InFile - Name of input file sent to the DLL (-) [used only with Bladed Interface] +"DISCON" DLL_ProcName - Name of procedure in DLL to be called (-) [case sensitive; used only with DLL Interface] +"default" DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] +false DLL_Ramp - Whether a linear ramp should be used between DLL_DT time steps [introduces time shift when true] (flag) [used only with Bladed Interface] + 9999.9 BPCutoff - Cutoff frequency for low-pass filter on blade pitch from DLL (Hz) [used only with Bladed Interface] + 0 NacYaw_North - Reference yaw angle of the nacelle when the upwind end points due North (deg) [used only with Bladed Interface] + 1 Ptch_Cntrl - Record 28: Use individual pitch control {0: collective pitch; 1: individual pitch control} (switch) [used only with Bladed Interface] + 0 Ptch_SetPnt - Record 5: Below-rated pitch angle set-point (deg) [used only with Bladed Interface] + 0 Ptch_Min - Record 6: Minimum pitch angle (deg) [used only with Bladed Interface] + 0 Ptch_Max - Record 7: Maximum pitch angle (deg) [used only with Bladed Interface] + 0 PtchRate_Min - Record 8: Minimum pitch rate (most negative value allowed) (deg/s) [used only with Bladed Interface] + 0 PtchRate_Max - Record 9: Maximum pitch rate (deg/s) [used only with Bladed Interface] + 0 Gain_OM - Record 16: Optimal mode gain (Nm/(rad/s)^2) [used only with Bladed Interface] + 0 GenSpd_MinOM - Record 17: Minimum generator speed (rpm) [used only with Bladed Interface] + 0 GenSpd_MaxOM - Record 18: Optimal mode maximum speed (rpm) [used only with Bladed Interface] + 0 GenSpd_Dem - Record 19: Demanded generator speed above rated (rpm) [used only with Bladed Interface] + 0 GenTrq_Dem - Record 22: Demanded generator torque above rated (Nm) [used only with Bladed Interface] + 0 GenPwr_Dem - Record 13: Demanded power (W) [used only with Bladed Interface] +---------------------- BLADED INTERFACE TORQUE-SPEED LOOK-UP TABLE ------------- + 0 DLL_NumTrq - Record 26: No. of points in torque-speed look-up table {0 = none and use the optimal mode parameters; nonzero = ignore the optimal mode PARAMETERs by setting Record 16 to 0.0} (-) [used only with Bladed Interface] + GenSpd_TLU GenTrq_TLU + (rpm) (Nm) +---------------------- OUTPUT -------------------------------------------------- +True SumPrint - Print summary data to .sum (flag) (currently unused) + 1 OutFile - Switch to determine where output will be placed: {1: in module output file only; 2: in glue code output file only; 3: both} (currently unused) +True TabDelim - Use tab delimiters in text tabular output file? (flag) (currently unused) +"ES10.3E2" OutFmt - Format used for text tabular output (except time). Resulting field should be 10 characters. (quoted string) (currently unused) + 0 TStart - Time to begin tabular output (s) (currently unused) + OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) +"GenPwr" - Electrical generator power and torque +"GenTq" - Electrical generator power and torque +"GenSpeed" +END of input file (the word "END" must appear in the first 3 columns of this last OutList line) +--------------------------------------------------------------------------------------- diff --git a/Test_Cases/NREL-5MW/AeroData/Cylinder1.dat b/Examples/Test_Cases/NREL-5MW/AeroData/Cylinder1.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/Cylinder1.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/Cylinder1.dat diff --git a/Test_Cases/NREL-5MW/AeroData/Cylinder2.dat b/Examples/Test_Cases/NREL-5MW/AeroData/Cylinder2.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/Cylinder2.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/Cylinder2.dat diff --git a/Test_Cases/NREL-5MW/AeroData/DU21_A17.dat b/Examples/Test_Cases/NREL-5MW/AeroData/DU21_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/DU21_A17.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/DU21_A17.dat diff --git a/Test_Cases/NREL-5MW/AeroData/DU25_A17.dat b/Examples/Test_Cases/NREL-5MW/AeroData/DU25_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/DU25_A17.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/DU25_A17.dat diff --git a/Test_Cases/NREL-5MW/AeroData/DU30_A17.dat b/Examples/Test_Cases/NREL-5MW/AeroData/DU30_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/DU30_A17.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/DU30_A17.dat diff --git a/Test_Cases/NREL-5MW/AeroData/DU35_A17.dat b/Examples/Test_Cases/NREL-5MW/AeroData/DU35_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/DU35_A17.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/DU35_A17.dat diff --git a/Test_Cases/NREL-5MW/AeroData/DU40_A17.dat b/Examples/Test_Cases/NREL-5MW/AeroData/DU40_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/DU40_A17.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/DU40_A17.dat diff --git a/Test_Cases/NREL-5MW/AeroData/NACA64_A17.dat b/Examples/Test_Cases/NREL-5MW/AeroData/NACA64_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/AeroData/NACA64_A17.dat rename to Examples/Test_Cases/NREL-5MW/AeroData/NACA64_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/Cylinder1.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder1.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/Cylinder1.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder1.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/Cylinder1_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder1_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/Cylinder1_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder1_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/Cylinder2.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder2.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/Cylinder2.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder2.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/Cylinder2_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder2_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/Cylinder2_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/Cylinder2_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/DU21_A17.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/DU21_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU21_A17.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU21_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/DU21_A17_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/DU21_A17_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU21_A17_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU21_A17_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/DU25_A17.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/DU25_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU25_A17.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU25_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/DU25_A17_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/DU25_A17_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU25_A17_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU25_A17_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/DU30_A17.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/DU30_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU30_A17.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU30_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/DU30_A17_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/DU30_A17_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU30_A17_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU30_A17_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/DU35_A17.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/DU35_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU35_A17.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU35_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/DU35_A17_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/DU35_A17_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU35_A17_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU35_A17_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/DU40_A17.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/DU40_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU40_A17.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU40_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/DU40_A17_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/DU40_A17_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/DU40_A17_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/DU40_A17_coords.txt diff --git a/Test_Cases/NREL-5MW/Airfoils/NACA64_A17.dat b/Examples/Test_Cases/NREL-5MW/Airfoils/NACA64_A17.dat similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/NACA64_A17.dat rename to Examples/Test_Cases/NREL-5MW/Airfoils/NACA64_A17.dat diff --git a/Test_Cases/NREL-5MW/Airfoils/NACA64_A17_coords.txt b/Examples/Test_Cases/NREL-5MW/Airfoils/NACA64_A17_coords.txt similarity index 100% rename from Test_Cases/NREL-5MW/Airfoils/NACA64_A17_coords.txt rename to Examples/Test_Cases/NREL-5MW/Airfoils/NACA64_A17_coords.txt diff --git a/Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt b/Examples/Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt similarity index 100% rename from Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt rename to Examples/Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt diff --git a/Test_Cases/NREL-5MW/DISCON.IN b/Examples/Test_Cases/NREL-5MW/DISCON.IN similarity index 54% rename from Test_Cases/NREL-5MW/DISCON.IN rename to Examples/Test_Cases/NREL-5MW/DISCON.IN index 0ddb6aa4..0d8024d1 100644 --- a/Test_Cases/NREL-5MW/DISCON.IN +++ b/Examples/Test_Cases/NREL-5MW/DISCON.IN @@ -1,49 +1,59 @@ ! Controller parameter input file for the NREL-5MW wind turbine -! - File written using ROSCO version 2.8.0 controller tuning logic on 04/10/23 +! - File written using ROSCO version 2.8.0 controller tuning logic on 01/05/24 -!------- DEBUG ------------------------------------------------------------ -1 ! LoggingLevel - (0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)) +!------- SIMULATION CONTROL ------------------------------------------------------------ +1 ! LoggingLevel - {0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)} +0 ! DT_Out - {Time step to output .dbg* files, or 0 to match sampling period of OpenFAST} +1 ! Ext_Interface - (0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0.) 0 ! Echo - (0 - no Echo, 1 - Echo input data to .echo) !------- CONTROLLER FLAGS ------------------------------------------------- -1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals -0 ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} +1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals 0 ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} -3 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} -1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} -0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} -1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} -2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} -1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} -0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} -0 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} -0 ! TD_Mode - Tower damper mode {0: no tower damper, 1: feed back translational nacelle accelleration to pitch angle} -0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} -0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time} -0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} -0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} -0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} -0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} -0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} -0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] -0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] +3 ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)} +0 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} +1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} +0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} +1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} +0 ! PRC_Mode - Power reference tracking mode{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints} +2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} +1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} +0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} +0 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} +0 ! TD_Mode - Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle +0 ! TRA_Mode - Tower resonance avoidance mode (0- no tower resonsnace avoidance, 1- use torque control setpoints to avoid a specific frequency +0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} +0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: rotor position control} +0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} +0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} +0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} +0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} +0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} +0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] +0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] !------- FILTERS ---------------------------------------------------------- -1.57080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] -0.00000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] -0.00000 ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s] -0.000000 0.250000 ! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] +1.57080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] +0.00000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] +0 ! F_NumNotchFilts - Number of notch filters placed on sensors +0.0000 ! F_NotchFreqs - Natural frequency of the notch filters. Array with length F_NumNotchFilts +0.0000 ! F_NotchBetaNum - Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] +0.0000 ! F_NotchBetaDen - Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] +0 ! F_GenSpdNotch_N - Number of notch filters on generator speed +0 ! F_GenSpdNotch_Ind - Indices of notch filters on generator speed +0 ! F_TwrTopNotch_N - Number of notch filters on tower top acceleration signal +0 ! F_TwrTopNotch_Ind - Indices of notch filters on tower top acceleration signal 0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. 0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. 0.000000 1.000000 ! F_FlCornerFreq - Natural frequency and damping in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s, -]. -0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. -0.000000 1.000000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control [rad/s, -]. +0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. +0.0000 1.0000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control !------- BLADE PITCH CONTROL ---------------------------------------------- 30 ! PC_GS_n - Amount of gain-scheduling table entries 0.056789 0.084492 0.106018 0.124332 0.140807 0.155903 0.169931 0.183270 0.196062 0.208354 0.220050 0.231503 0.242646 0.253377 0.263967 0.274233 0.284343 0.294292 0.303997 0.313626 0.322957 0.332260 0.341319 0.350368 0.359221 0.368059 0.376700 0.385301 0.393691 0.402050 ! PC_GS_angles - Gain-schedule table: pitch angles [rad]. --0.020655 -0.018159 -0.016134 -0.014459 -0.013049 -0.011846 -0.010809 -0.009904 -0.009108 -0.008403 -0.007774 -0.007209 -0.006698 -0.006235 -0.005813 -0.005427 -0.005072 -0.004745 -0.004442 -0.004162 -0.003901 -0.003657 -0.003430 -0.003217 -0.003017 -0.002829 -0.002652 -0.002484 -0.002326 -0.002176 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. +-0.018995 -0.016672 -0.014787 -0.013228 -0.011916 -0.010797 -0.009831 -0.008989 -0.008248 -0.007592 -0.007006 -0.006480 -0.006005 -0.005574 -0.005182 -0.004822 -0.004492 -0.004187 -0.003906 -0.003644 -0.003402 -0.003175 -0.002963 -0.002765 -0.002579 -0.002404 -0.002239 -0.002083 -0.001936 -0.001797 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. -0.008388 -0.007514 -0.006805 -0.006218 -0.005725 -0.005304 -0.004940 -0.004624 -0.004345 -0.004098 -0.003878 -0.003680 -0.003501 -0.003339 -0.003192 -0.003056 -0.002932 -0.002817 -0.002712 -0.002613 -0.002522 -0.002437 -0.002357 -0.002283 -0.002212 -0.002147 -0.002085 -0.002026 -0.001971 -0.001918 ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-]. 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 ! PC_GS_KD - Gain-schedule table: pitch controller kd gains 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 ! PC_GS_TF - Gain-schedule table: pitch controller tf gains (derivative filter) @@ -71,32 +81,39 @@ 47402.87063000 ! VS_MaxTq - Maximum generator torque in Region 3 (HSS side), [Nm]. 0.000000000000 ! VS_MinTq - Minimum generator torque (HSS side), [Nm]. 35.29006000000 ! VS_MinOMSpd - Minimum generator speed [rad/s] -2.185750000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side), [Nm/(rad/s)^2] +2.063350000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side). Only used in VS_ControlMode = 1,3 5000000.000000 ! VS_RtPwr - Wind turbine rated power [W] 43093.51876000 ! VS_RtTq - Rated torque, [Nm]. 122.9096700000 ! VS_RefSpd - Rated generator speed [rad/s] 1 ! VS_n - Number of generator PI torque controller gains -657.442080000 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -104.507080000 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -7.64 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio [rad]. +7.64 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. +0.314000000000 ! VS_PwrFiltF - Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. !------- SETPOINT SMOOTHER --------------------------------------------- 1.00000 ! SS_VSGain - Variable speed torque controller setpoint smoother gain, [-]. 0.00100 ! SS_PCGain - Collective pitch controller setpoint smoother gain, [-]. +!------- POWER REFERENCE TRACKING -------------------------------------- +2 ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array +0.07854 ! PRC_LPF_Freq - Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] +3.0000 25.0000 ! PRC_WindSpeeds - Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] +0.7917 0.7917 ! PRC_GenSpeeds - Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + !------- WIND SPEED ESTIMATOR --------------------------------------------- 63.000 ! WE_BladeRadius - Blade length (distance from hub center to blade tip), [m] 1 ! WE_CP_n - Amount of parameters in the Cp array 0.0 ! WE_CP - Parameters that define the parameterized CP(lambda) function -0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] +0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] 97.0 ! WE_GearboxRatio - Gearbox ratio [>=1], [-] -43702538.05700 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] +43702538.05700 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] 1.225 ! WE_RhoAir - Air density, [kg m^-3] "Cp_Ct_Cq.NREL5MW.txt" ! PerfFileName - File containing rotor performance tables (Cp,Ct,Cq) (absolute path or relative to this file) 36 26 ! PerfTableSize - Size of rotor performance tables, first number refers to number of blade pitch angles, second number referse to number of tip-speed ratios 60 ! WE_FOPoles_N - Number of first-order system poles used in EKF 3.0000 3.2897 3.5793 3.8690 4.1586 4.4483 4.7379 5.0276 5.3172 5.6069 5.8966 6.1862 6.4759 6.7655 7.0552 7.3448 7.6345 7.9241 8.2138 8.5034 8.7931 9.0828 9.3724 9.6621 9.9517 10.2414 10.5310 10.8207 11.1103 11.4000 11.8533 12.3067 12.7600 13.2133 13.6667 14.1200 14.5733 15.0267 15.4800 15.9333 16.3867 16.8400 17.2933 17.7467 18.2000 18.6533 19.1067 19.5600 20.0133 20.4667 20.9200 21.3733 21.8267 22.2800 22.7333 23.1867 23.6400 24.0933 24.5467 25.0000 ! WE_FOPoles_v - Wind speeds corresponding to first-order system poles [m/s] --0.01638154 -0.01796321 -0.01954487 -0.02112654 -0.02270820 -0.02428987 -0.02587154 -0.02745320 -0.02903487 -0.03061653 -0.03219820 -0.03377987 -0.03536153 -0.03694320 -0.03852486 -0.04010653 -0.04168820 -0.04326986 -0.04485153 -0.04643319 -0.04801486 -0.04959652 -0.05117819 -0.05275986 -0.05434152 -0.05592319 -0.05758373 -0.05882656 -0.06845507 -0.05992890 0.02094683 0.01327182 0.00285485 -0.00935731 -0.02210773 -0.03573037 -0.04990222 -0.06404904 -0.07899629 -0.09463190 -0.10954192 -0.12525205 -0.14168652 -0.15843395 -0.17415061 -0.19052486 -0.20780146 -0.22581018 -0.24373777 -0.26010871 -0.27706767 -0.29551708 -0.31430599 -0.33428552 -0.35420853 -0.37183729 -0.38936451 -0.40828911 -0.42758878 -0.44818175 ! WE_FOPoles - First order system poles [1/s] +-0.01638154 -0.01796321 -0.01954487 -0.02112654 -0.02270820 -0.02428987 -0.02587154 -0.02745320 -0.02903487 -0.03061653 -0.03219820 -0.03377987 -0.03536153 -0.03694320 -0.03852486 -0.04010653 -0.04168820 -0.04326986 -0.04485153 -0.04643319 -0.04801486 -0.04959652 -0.05117819 -0.05275986 -0.05434152 -0.05592319 -0.05758373 -0.05882656 -0.06845507 -0.05992890 -0.05031134 -0.05798636 -0.06840333 -0.08061549 -0.09336590 -0.10698855 -0.12116040 -0.13530722 -0.15025447 -0.16589008 -0.18080009 -0.19651023 -0.21294470 -0.22969213 -0.24540879 -0.26178304 -0.27905964 -0.29706835 -0.31499595 -0.33136688 -0.34832584 -0.36677525 -0.38556416 -0.40554370 -0.42546670 -0.44309547 -0.46062268 -0.47954729 -0.49884696 -0.51943992 ! WE_FOPoles - First order system poles [1/s] !------- YAW CONTROL ------------------------------------------------------ 0.00000 ! Y_uSwitch - Wind speed to switch between Y_ErrThresh. If zero, only the second value of Y_ErrThresh is used [m/s] @@ -107,22 +124,27 @@ 0.00000 ! Y_IPC_KP - Yaw-by-IPC proportional controller gain Kp 0.00000 ! Y_IPC_KI - Yaw-by-IPC integral controller gain Ki -!------- TOWER FORE-AFT DAMPING ------------------------------------------- --1.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller [rad s/m] -0.0 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] -0.0 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] +!------- TOWER CONTROL ------------------------------------------------------ +0.00000 ! TRA_ExclSpeed - Rotor speed for exclusion [LSS, rad/s] +0.00000 ! TRA_ExclBand - Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 +0.00000e+00 ! TRA_RateLimit - Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/400. +0.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller, [rad*s/m] +0.00000 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] +0.00000 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] !------- MINIMUM PITCH SATURATION ------------------------------------------- 60 ! PS_BldPitchMin_N - Number of values in minimum blade pitch lookup table (should equal number of values in PS_WindSpeeds and PS_BldPitchMin) -3.0000 3.2897 3.5793 3.8690 4.1586 4.4483 4.7379 5.0276 5.3172 5.6069 5.8966 6.1862 6.4759 6.7655 7.0552 7.3448 7.6345 7.9241 8.2138 8.5034 8.7931 9.0828 9.3724 9.6621 9.9517 10.2414 10.5310 10.8207 11.1103 11.4000 11.8533 12.3067 12.7600 13.2133 13.6667 14.1200 14.5733 15.0267 15.4800 15.9333 16.3867 16.8400 17.2933 17.7467 18.2000 18.6533 19.1067 19.5600 20.0133 20.4667 20.9200 21.3733 21.8267 22.2800 22.7333 23.1867 23.6400 24.0933 24.5467 25.0000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] -0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.00088027 0.01116187 0.02310060 0.03164156 0.03968639 0.04741131 0.05899071 0.07019329 0.08090119 0.09141661 0.10169361 0.11174124 0.12170066 0.13137494 0.14103377 0.15048120 0.15989580 0.16913227 0.17831010 0.18739638 0.19643591 0.20537011 0.21419674 0.22293719 0.23161365 0.24025975 0.24885012 0.25735704 0.26578040 0.27407178 0.28233051 0.29047594 0.29867838 0.30674517 0.31490089 0.32284411 ! PS_BldPitchMin - Minimum blade pitch angles [rad] +3.000 3.290 3.579 3.869 4.159 4.448 4.738 5.028 5.317 5.607 5.897 6.186 6.476 6.766 7.055 7.345 7.634 7.924 8.214 8.503 8.793 9.083 9.372 9.662 9.952 10.241 10.531 10.821 11.110 11.400 11.853 12.307 12.760 13.213 13.667 14.120 14.573 15.027 15.480 15.933 16.387 16.840 17.293 17.747 18.200 18.653 19.107 19.560 20.013 20.467 20.920 21.373 21.827 22.280 22.733 23.187 23.640 24.093 24.547 25.000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] +0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.001 0.011 0.023 0.032 0.040 0.047 0.059 0.070 0.081 0.091 0.102 0.112 0.122 0.131 0.141 0.150 0.160 0.169 0.178 0.187 0.196 0.205 0.214 0.223 0.232 0.240 0.249 0.257 0.266 0.274 0.282 0.290 0.299 0.307 0.315 0.323 ! PS_BldPitchMin - Minimum blade pitch angles [rad] !------- SHUTDOWN ----------------------------------------------------------- 0.436300000000 ! SD_MaxPit - Maximum blade pitch angle to initiate shutdown, [rad] 0.418880000000 ! SD_CornerFreq - Cutoff Frequency for first order low-pass filter for blade pitch angle, [rad/s] !------- Floating ----------------------------------------------------------- -0.000000000000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +1 ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1 +0.0000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +0.0000 ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] !------- FLAP ACTUATION ----------------------------------------------------- 0.000000000000 ! Flp_Angle - Initial or steady state flap angle [rad] @@ -133,26 +155,28 @@ !------- Open Loop Control ----------------------------------------------------- "unused" ! OL_Filename - Input file with open loop timeseries (absolute path or relative to this file) 0 ! Ind_Breakpoint - The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) -0 ! Ind_BldPitch - The column in OL_Filename that contains the blade pitch input in rad + 0 0 0 ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array] 0 ! Ind_GenTq - The column in OL_Filename that contains the generator torque in Nm -0 ! Ind_YawRate - The column in OL_Filename that contains the nacelle yaw rate rad/s +0 ! Ind_YawRate - The column in OL_Filename that contains the yaw rate in rad/s +0 ! Ind_Azimuth - The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) +0.0000 0.0000 0.0000 0.0000 ! RP_Gains - PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) 0 ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N] 0 ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N] !------- Pitch Actuator Model ----------------------------------------------------- -3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] -0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] +3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] +0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] !------- Pitch Actuator Faults ----------------------------------------------------- 0.00000000 0.00000000 0.00000000 ! PF_Offsets - Constant blade pitch offsets for blades 1-3 [rad] !------- Active Wake Control ----------------------------------------------------- -1 ! AWC_NumModes - Number of user-defined AWC forcing modes -1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) -1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) -0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] -1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] -0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] +1 ! AWC_NumModes - Number of user-defined AWC forcing modes +1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) +1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) +0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] +1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] +0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] !------- External Controller Interface ----------------------------------------------------- "unused" ! DLL_FileName - Name/location of the dynamic library in the Bladed-DLL format @@ -161,13 +185,14 @@ !------- ZeroMQ Interface --------------------------------------------------------- "tcp://localhost:5555" ! ZMQ_CommAddress - Communication address for ZMQ server, (e.g. "tcp://localhost:5555") -2 ! ZMQ_UpdatePeriod - Call ZeroMQ every [x] seconds, [s] +1.000000 ! ZMQ_UpdatePeriod - Update period at zmq interface to send measurements and wait for setpoint [sec.] +0 ! ZMQ_ID - Integer identifier of turbine !------- Cable Control --------------------------------------------------------- 1 ! CC_Group_N - Number of cable control groups - 0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL +0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL 20.000000 ! CC_ActTau - Time constant for line actuator [s] !------- Structural Controllers --------------------------------------------------------- 1 ! StC_Group_N - Number of cable control groups - 0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output +0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output diff --git a/Test_Cases/NREL-5MW/IceDyn_Input.dat b/Examples/Test_Cases/NREL-5MW/IceDyn_Input.dat similarity index 100% rename from Test_Cases/NREL-5MW/IceDyn_Input.dat rename to Examples/Test_Cases/NREL-5MW/IceDyn_Input.dat diff --git a/Test_Cases/NREL-5MW/IceFloe_IEC_Crushing.dat b/Examples/Test_Cases/NREL-5MW/IceFloe_IEC_Crushing.dat similarity index 100% rename from Test_Cases/NREL-5MW/IceFloe_IEC_Crushing.dat rename to Examples/Test_Cases/NREL-5MW/IceFloe_IEC_Crushing.dat diff --git a/Test_Cases/NREL-5MW/NREL-5MW.fst b/Examples/Test_Cases/NREL-5MW/NREL-5MW.fst similarity index 100% rename from Test_Cases/NREL-5MW/NREL-5MW.fst rename to Examples/Test_Cases/NREL-5MW/NREL-5MW.fst diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat similarity index 75% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat index 3fd8bc13..13a784f1 100644 --- a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat @@ -5,6 +5,7 @@ False Echo - Echo input data to .ech (flag) 1 WindType - switch for wind file type (1=steady; 2=uniform; 3=binary TurbSim FF; 4=binary Bladed-style FF; 5=HAWC format; 6=User defined) 0 PropagationDir - Direction of wind propagation (meteoroligical rotation from aligned with X (positive rotates towards -Y) -- degrees) 0 VFlowAng - Upflow angle (degrees) (not used for native Bladed format WindType=7) +False VelInterpCubic - Use cubic interpolation for velocity in time (false=linear, true=cubic) [Used with WindType=2,3,4,5,7] 1 NWindVel - Number of points to output the wind velocity (0 to 9) 0 WindVxiList - List of coordinates in the inertial X direction (m) 0 WindVyiList - List of coordinates in the inertial Y direction (m) @@ -47,6 +48,19 @@ False TowerFile - Have tower file (.twr) (flag) ignored when WindTy 0.2 PLExp_Hawc - Power law exponent (-) (used for PL wind profile type only) 0.03 Z0 - Surface roughness length (m) (used for LG wind profile type only) 0 XOffset - Initial offset in +x direction (shift of wind box) +================== LIDAR Parameters =========================================================================== +0 SensorType - Switch for lidar configuration (0 = None, 1 = Single Point Beam(s), 2 = Continuous, 3 = Pulsed) +0 NumPulseGate - Number of lidar measurement gates (used when SensorType = 3) +30 PulseSpacing - Distance between range gates (m) (used when SensorType = 3) +0 NumBeam - Number of lidar measurement beams (0-5)(used when SensorType = 1) +-200 FocalDistanceX - Focal distance co-ordinates of the lidar beam in the x direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceY - Focal distance co-ordinates of the lidar beam in the y direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceZ - Focal distance co-ordinates of the lidar beam in the z direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0.0 0.0 0.0 RotorApexOffsetPos - Offset of the lidar from hub height (m) +17 URefLid - Reference average wind speed for the lidar[m/s] +0.25 MeasurementInterval - Time between each measurement [s] +False LidRadialVel - TRUE => return radial component, FALSE => return 'x' direction estimate +1 ConsiderHubMotion - Flag whether to consider the hub motion's impact on Lidar measurements ====================== OUTPUT ================================================== False SumPrint - Print summary data to .IfW.sum (flag) OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Monopile_IEC_Crushing.inp b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Monopile_IEC_Crushing.inp similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Monopile_IEC_Crushing.inp rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Monopile_IEC_Crushing.inp diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn_Tower.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn_Tower.dat similarity index 100% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn_Tower.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn_Tower.dat diff --git a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat similarity index 97% rename from Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat rename to Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat index 86351f2d..41627843 100644 --- a/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat @@ -74,7 +74,7 @@ True GenTiStp - Method to stop the generator {T: timed using TimGen ---------------------- CABLE CONTROL ------------------------------------------- 0 CCmode - Cable control mode {0: none, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"../../ROSCO/install/lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"../../../lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] "DISCON.IN" DLL_InFile - Name of input file sent to the DLL (-) [used only with Bladed Interface] "DISCON" DLL_ProcName - Name of procedure in DLL to be called (-) [case sensitive; used only with DLL Interface] "default" DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] diff --git a/Test_Cases/NREL-5MW/README.md b/Examples/Test_Cases/NREL-5MW/README.md similarity index 100% rename from Test_Cases/NREL-5MW/README.md rename to Examples/Test_Cases/NREL-5MW/README.md diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF00_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF00_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF00_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF00_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF01_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF01_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF01_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF01_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF02_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF02_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF02_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF02_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF03_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF03_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF03_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF03_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF04_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF04_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF04_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF04_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF05_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF05_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF05_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF05_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF06_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF06_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF06_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF06_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF07_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF07_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF07_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF07_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF08_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF08_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF08_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF08_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF09_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF09_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF09_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF09_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF10_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF10_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF10_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF10_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF11_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF11_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF11_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF11_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF12_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF12_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF12_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF12_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF13_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF13_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF13_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF13_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF14_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF14_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF14_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF14_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF15_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF15_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF15_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF15_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF16_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF16_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF16_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF16_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF17_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF17_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF17_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF17_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF18_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF18_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF18_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF18_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF19_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF19_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF19_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF19_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF20_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF20_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF20_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF20_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF21_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF21_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF21_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF21_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF22_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF22_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF22_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF22_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF23_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF23_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF23_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF23_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF24_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF24_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF24_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF24_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF25_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF25_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF25_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF25_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF26_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF26_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF26_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF26_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF27_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF27_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF27_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF27_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF28_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF28_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF28_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF28_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF29_Coords.txt b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF29_Coords.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF29_Coords.txt rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AF29_Coords.txt diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_00.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_00.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_00.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_00.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_01.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_01.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_01.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_01.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_02.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_02.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_02.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_02.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_03.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_03.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_03.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_03.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_04.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_04.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_04.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_04.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_05.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_05.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_05.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_05.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_06.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_06.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_06.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_06.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_07.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_07.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_07.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_07.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_08.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_08.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_08.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_08.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_09.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_09.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_09.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_09.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_10.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_10.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_10.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_10.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_11.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_11.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_11.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_11.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_12.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_12.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_12.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_12.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_13.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_13.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_13.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_13.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_14.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_14.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_14.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_14.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_15.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_15.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_15.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_15.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_16.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_16.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_16.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_16.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_17.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_17.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_17.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_17.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_18.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_18.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_18.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_18.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_19.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_19.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_19.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_19.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_20.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_20.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_20.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_20.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_21.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_21.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_21.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_21.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_22.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_22.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_22.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_22.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_23.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_23.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_23.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_23.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_24.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_24.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_24.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_24.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_25.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_25.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_25.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_25.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_26.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_26.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_26.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_26.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_27.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_27.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_27.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_27.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_28.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_28.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_28.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_28.dat diff --git a/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_29.dat b/Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_29.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_29.dat rename to Examples/Test_Cases/NREL_2p8_127/Airfoils/NREL-2p8-127_AeroDyn15_Polar_29.dat diff --git a/Test_Cases/NREL_2p8_127/NREL-2.8-127.xlsx b/Examples/Test_Cases/NREL_2p8_127/NREL-2.8-127.xlsx similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2.8-127.xlsx rename to Examples/Test_Cases/NREL_2p8_127/NREL-2.8-127.xlsx diff --git a/Test_Cases/NREL_2p8_127/NREL-2.8-127_pitch-speed.csv b/Examples/Test_Cases/NREL_2p8_127/NREL-2.8-127_pitch-speed.csv similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2.8-127_pitch-speed.csv rename to Examples/Test_Cases/NREL_2p8_127/NREL-2.8-127_pitch-speed.csv diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127.fst b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127.fst similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127.fst rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127.fst diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_Cp_Ct_Cq.txt b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_Cp_Ct_Cq.txt similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_Cp_Ct_Cq.txt rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_Cp_Ct_Cq.txt diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN similarity index 54% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN index ec720eb5..31d0ed79 100644 --- a/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN @@ -1,49 +1,59 @@ ! Controller parameter input file for the NREL-2p8-127 wind turbine -! - File written using ROSCO version 2.8.0 controller tuning logic on 04/10/23 +! - File written using ROSCO version 2.8.0 controller tuning logic on 01/05/24 -!------- DEBUG ------------------------------------------------------------ -2 ! LoggingLevel - (0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)) +!------- SIMULATION CONTROL ------------------------------------------------------------ +2 ! LoggingLevel - {0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)} +0 ! DT_Out - {Time step to output .dbg* files, or 0 to match sampling period of OpenFAST} +1 ! Ext_Interface - (0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0.) 0 ! Echo - (0 - no Echo, 1 - Echo input data to .echo) !------- CONTROLLER FLAGS ------------------------------------------------- -1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals -0 ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} +1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals 1 ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} -3 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} -1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} -0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} -1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} -2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} -1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} -0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} -0 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} -0 ! TD_Mode - Tower damper mode {0: no tower damper, 1: feed back translational nacelle accelleration to pitch angle} -0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} -0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time} -0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} -0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} -0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} -0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} -0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} -0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] -0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] +3 ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)} +0 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} +1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} +0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} +1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} +0 ! PRC_Mode - Power reference tracking mode{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints} +2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} +1 ! PS_Mode - Pitch saturation mode {0: no pitch saturation, 1: implement pitch saturation} +0 ! SD_Mode - Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} +0 ! Fl_Mode - Floating specific feedback mode {0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty} +0 ! TD_Mode - Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle +0 ! TRA_Mode - Tower resonance avoidance mode (0- no tower resonsnace avoidance, 1- use torque control setpoints to avoid a specific frequency +0 ! Flp_Mode - Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control} +0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: rotor position control} +0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} +0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} +0 ! AWC_Mode - Active wake control {0 - not used, 1 - complex number method, 2 - Coleman transform method} +0 ! Ext_Mode - External control mode {0 - not used, 1 - call external dynamic library} +0 ! ZMQ_Mode - Fuse ZeroMQ interface {0: unused, 1: Yaw Control} +0 ! CC_Mode - Cable control mode [0- unused, 1- User defined, 2- Open loop control] +0 ! StC_Mode - Structural control mode [0- unused, 1- User defined, 2- Open loop control] !------- FILTERS ---------------------------------------------------------- -2.07080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] -0.00000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] -0.00000 ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s] -0.000000 0.250000 ! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] +2.07080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] +0.00000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] +0 ! F_NumNotchFilts - Number of notch filters placed on sensors +0.0000 ! F_NotchFreqs - Natural frequency of the notch filters. Array with length F_NumNotchFilts +0.0000 ! F_NotchBetaNum - Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] +0.0000 ! F_NotchBetaDen - Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] +0 ! F_GenSpdNotch_N - Number of notch filters on generator speed +0 ! F_GenSpdNotch_Ind - Indices of notch filters on generator speed +0 ! F_TwrTopNotch_N - Number of notch filters on tower top acceleration signal +0 ! F_TwrTopNotch_Ind - Indices of notch filters on tower top acceleration signal 0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. 0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. 0.000000 1.000000 ! F_FlCornerFreq - Natural frequency and damping in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s, -]. -0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. -0.000000 1.000000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control [rad/s, -]. +0.01042 ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s]. +0.0000 1.0000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control !------- BLADE PITCH CONTROL ---------------------------------------------- 30 ! PC_GS_n - Amount of gain-scheduling table entries 0.075990 0.104503 0.127446 0.147544 0.164940 0.181678 0.197073 0.211624 0.225753 0.238993 0.252021 0.264458 0.276515 0.288229 0.299596 0.310932 0.321646 0.332112 0.342584 0.353105 0.363012 0.373072 0.382733 0.392195 0.401619 0.411107 0.420504 0.429096 0.437752 0.446357 ! PC_GS_angles - Gain-schedule table: pitch angles [rad]. --0.024441 -0.021943 -0.019855 -0.018085 -0.016566 -0.015246 -0.014091 -0.013070 -0.012161 -0.011347 -0.010614 -0.009951 -0.009347 -0.008795 -0.008289 -0.007824 -0.007394 -0.006995 -0.006625 -0.006280 -0.005958 -0.005657 -0.005375 -0.005109 -0.004860 -0.004624 -0.004401 -0.004191 -0.003991 -0.003802 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. +-0.023307 -0.020910 -0.018908 -0.017210 -0.015752 -0.014487 -0.013378 -0.012398 -0.011527 -0.010746 -0.010043 -0.009406 -0.008827 -0.008298 -0.007813 -0.007366 -0.006953 -0.006571 -0.006216 -0.005885 -0.005577 -0.005288 -0.005017 -0.004762 -0.004522 -0.004296 -0.004083 -0.003881 -0.003689 -0.003508 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. -0.000804 -0.000732 -0.000672 -0.000621 -0.000577 -0.000539 -0.000505 -0.000476 -0.000450 -0.000426 -0.000405 -0.000386 -0.000369 -0.000353 -0.000338 -0.000325 -0.000312 -0.000301 -0.000290 -0.000280 -0.000271 -0.000262 -0.000254 -0.000246 -0.000239 -0.000232 -0.000226 -0.000220 -0.000214 -0.000209 ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-]. 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 ! PC_GS_KD - Gain-schedule table: pitch controller kd gains 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 0.000000 ! PC_GS_TF - Gain-schedule table: pitch controller tf gains (derivative filter) @@ -71,32 +81,39 @@ 26673.40024000 ! VS_MaxTq - Maximum generator torque in Region 3 (HSS side), [Nm]. 0.000000000000 ! VS_MinTq - Minimum generator torque (HSS side), [Nm]. 37.81562000000 ! VS_MinOMSpd - Minimum generator speed [rad/s] -1.931170000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side), [Nm/(rad/s)^2] +1.654680000000 ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side). Only used in VS_ControlMode = 1,3 2800000.000000 ! VS_RtPwr - Wind turbine rated power [W] 24248.54567000 ! VS_RtTq - Rated torque, [Nm]. 122.9096700000 ! VS_RefSpd - Rated generator speed [rad/s] 1 ! VS_n - Number of generator PI torque controller gains -600.450450000 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -85.3230300000 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) -8.25 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio [rad]. +8.25 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. +0.314000000000 ! VS_PwrFiltF - Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. !------- SETPOINT SMOOTHER --------------------------------------------- 1.00000 ! SS_VSGain - Variable speed torque controller setpoint smoother gain, [-]. 0.00100 ! SS_PCGain - Collective pitch controller setpoint smoother gain, [-]. +!------- POWER REFERENCE TRACKING -------------------------------------- +2 ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array +0.07854 ! PRC_LPF_Freq - Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] +3.0000 25.0000 ! PRC_WindSpeeds - Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] +0.7917 0.7917 ! PRC_GenSpeeds - Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + !------- WIND SPEED ESTIMATOR --------------------------------------------- 63.457 ! WE_BladeRadius - Blade length (distance from hub center to blade tip), [m] 1 ! WE_CP_n - Amount of parameters in the Cp array 0.0 ! WE_CP - Parameters that define the parameterized CP(lambda) function -0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] +0.0 ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad] 97.0 ! WE_GearboxRatio - Gearbox ratio [>=1], [-] -66347470.49793 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] +66347470.49793 ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2] 1.225 ! WE_RhoAir - Air density, [kg m^-3] "NREL-2p8-127_Cp_Ct_Cq.txt" ! PerfFileName - File containing rotor performance tables (Cp,Ct,Cq) (absolute path or relative to this file) 30 30 ! PerfTableSize - Size of rotor performance tables, first number refers to number of blade pitch angles, second number referse to number of tip-speed ratios 60 ! WE_FOPoles_N - Number of first-order system poles used in EKF 3.0000 3.2897 3.5793 3.8690 4.1586 4.4483 4.7379 5.0276 5.3172 5.6069 5.8966 6.1862 6.4759 6.7655 7.0552 7.3448 7.6345 7.9241 8.2138 8.5034 8.7931 9.0828 9.3724 9.6621 9.9517 10.2414 10.5310 10.8207 11.1103 11.4000 11.8533 12.3067 12.7600 13.2133 13.6667 14.1200 14.5733 15.0267 15.4800 15.9333 16.3867 16.8400 17.2933 17.7467 18.2000 18.6533 19.1067 19.5600 20.0133 20.4667 20.9200 21.3733 21.8267 22.2800 22.7333 23.1867 23.6400 24.0933 24.5467 25.0000 ! WE_FOPoles_v - Wind speeds corresponding to first-order system poles [m/s] --0.01246409 -0.01366752 -0.01487095 -0.01607438 -0.01727781 -0.01848123 -0.01968466 -0.02088809 -0.02209152 -0.02329495 -0.02449838 -0.02570181 -0.02690524 -0.02810867 -0.02931210 -0.03051553 -0.03171896 -0.03292239 -0.03412582 -0.03532924 -0.03653267 -0.03773610 -0.03893953 -0.04014296 -0.03876534 -0.03527029 -0.03014051 -0.02417865 -0.01714772 -0.00815401 0.00419449 -0.00048731 -0.00466276 -0.01071643 -0.01560323 -0.02192148 -0.02762358 -0.03415246 -0.03995877 -0.04666898 -0.05357684 -0.06017881 -0.06783693 -0.07545934 -0.08285355 -0.09099765 -0.09868985 -0.10643139 -0.11560625 -0.12454786 -0.13353192 -0.14319807 -0.15242426 -0.16161402 -0.17122186 -0.18158081 -0.19160223 -0.20032125 -0.20983653 -0.21909214 ! WE_FOPoles - First order system poles [1/s] +-0.01246409 -0.01366752 -0.01487095 -0.01607438 -0.01727781 -0.01848123 -0.01968466 -0.02088809 -0.02209152 -0.02329495 -0.02449838 -0.02570181 -0.02690524 -0.02810867 -0.02931210 -0.03051553 -0.03171896 -0.03292239 -0.03412582 -0.03532924 -0.03653267 -0.03773610 -0.03893953 -0.04014296 -0.03876534 -0.03527029 -0.03014051 -0.02417865 -0.01714772 -0.00815401 -0.02209033 -0.02677213 -0.03094759 -0.03700125 -0.04188805 -0.04820630 -0.05390840 -0.06043728 -0.06624359 -0.07295380 -0.07986166 -0.08646363 -0.09412176 -0.10174417 -0.10913837 -0.11728247 -0.12497467 -0.13271621 -0.14189107 -0.15083268 -0.15981675 -0.16948290 -0.17870908 -0.18789884 -0.19750668 -0.20786563 -0.21788705 -0.22660607 -0.23612135 -0.24537696 ! WE_FOPoles - First order system poles [1/s] !------- YAW CONTROL ------------------------------------------------------ 0.00000 ! Y_uSwitch - Wind speed to switch between Y_ErrThresh. If zero, only the second value of Y_ErrThresh is used [m/s] @@ -107,22 +124,27 @@ 0.00000 ! Y_IPC_KP - Yaw-by-IPC proportional controller gain Kp 0.00000 ! Y_IPC_KI - Yaw-by-IPC integral controller gain Ki -!------- TOWER FORE-AFT DAMPING ------------------------------------------- --1.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller [rad s/m] -0.0 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] -0.0 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] +!------- TOWER CONTROL ------------------------------------------------------ +0.00000 ! TRA_ExclSpeed - Rotor speed for exclusion [LSS, rad/s] +0.00000 ! TRA_ExclBand - Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 +0.00000e+00 ! TRA_RateLimit - Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/400. +0.00000 ! FA_KI - Integral gain for the fore-aft tower damper controller, [rad*s/m] +0.00000 ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] +0.00000 ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad] !------- MINIMUM PITCH SATURATION ------------------------------------------- 60 ! PS_BldPitchMin_N - Number of values in minimum blade pitch lookup table (should equal number of values in PS_WindSpeeds and PS_BldPitchMin) -3.0000 3.2897 3.5793 3.8690 4.1586 4.4483 4.7379 5.0276 5.3172 5.6069 5.8966 6.1862 6.4759 6.7655 7.0552 7.3448 7.6345 7.9241 8.2138 8.5034 8.7931 9.0828 9.3724 9.6621 9.9517 10.2414 10.5310 10.8207 11.1103 11.4000 11.8533 12.3067 12.7600 13.2133 13.6667 14.1200 14.5733 15.0267 15.4800 15.9333 16.3867 16.8400 17.2933 17.7467 18.2000 18.6533 19.1067 19.5600 20.0133 20.4667 20.9200 21.3733 21.8267 22.2800 22.7333 23.1867 23.6400 24.0933 24.5467 25.0000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] -0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.00000000 0.01902632 0.03121162 0.04101621 0.04957537 0.05812141 0.06604528 0.07366393 0.08564088 0.09644430 0.10731742 0.11740081 0.12723365 0.13691718 0.14655371 0.15552079 0.16457871 0.17358206 0.18261499 0.19163393 0.20072294 0.20968649 0.21849678 0.22748802 0.23597095 0.24444734 0.25312967 0.26178025 0.27046099 0.27863869 0.28691931 0.29527580 0.30349928 0.31191439 0.32017189 0.32834804 0.33653924 0.34452172 ! PS_BldPitchMin - Minimum blade pitch angles [rad] +3.000 3.290 3.579 3.869 4.159 4.448 4.738 5.028 5.317 5.607 5.897 6.186 6.476 6.766 7.055 7.345 7.634 7.924 8.214 8.503 8.793 9.083 9.372 9.662 9.952 10.241 10.531 10.821 11.110 11.400 11.853 12.307 12.760 13.213 13.667 14.120 14.573 15.027 15.480 15.933 16.387 16.840 17.293 17.747 18.200 18.653 19.107 19.560 20.013 20.467 20.920 21.373 21.827 22.280 22.733 23.187 23.640 24.093 24.547 25.000 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] +0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.000 0.019 0.031 0.041 0.050 0.058 0.066 0.074 0.086 0.096 0.107 0.117 0.127 0.137 0.147 0.156 0.165 0.174 0.183 0.192 0.201 0.210 0.218 0.227 0.236 0.244 0.253 0.262 0.270 0.279 0.287 0.295 0.303 0.312 0.320 0.328 0.337 0.345 ! PS_BldPitchMin - Minimum blade pitch angles [rad] !------- SHUTDOWN ----------------------------------------------------------- 0.436300000000 ! SD_MaxPit - Maximum blade pitch angle to initiate shutdown, [rad] 0.418880000000 ! SD_CornerFreq - Cutoff Frequency for first order low-pass filter for blade pitch angle, [rad/s] !------- Floating ----------------------------------------------------------- -0.000000000000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +1 ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1 +0.0000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +0.0000 ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] !------- FLAP ACTUATION ----------------------------------------------------- 0.000000000000 ! Flp_Angle - Initial or steady state flap angle [rad] @@ -133,26 +155,28 @@ !------- Open Loop Control ----------------------------------------------------- "unused" ! OL_Filename - Input file with open loop timeseries (absolute path or relative to this file) 0 ! Ind_Breakpoint - The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) -0 ! Ind_BldPitch - The column in OL_Filename that contains the blade pitch input in rad + 0 0 0 ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array] 0 ! Ind_GenTq - The column in OL_Filename that contains the generator torque in Nm -0 ! Ind_YawRate - The column in OL_Filename that contains the nacelle yaw rate rad/s +0 ! Ind_YawRate - The column in OL_Filename that contains the yaw rate in rad/s +0 ! Ind_Azimuth - The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) +0.0000 0.0000 0.0000 0.0000 ! RP_Gains - PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) 0 ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N] 0 ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N] !------- Pitch Actuator Model ----------------------------------------------------- -3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] -0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] +3.140000000000 ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s] +0.707000000000 ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1] !------- Pitch Actuator Faults ----------------------------------------------------- 0.00000000 0.00000000 0.00000000 ! PF_Offsets - Constant blade pitch offsets for blades 1-3 [rad] !------- Active Wake Control ----------------------------------------------------- -1 ! AWC_NumModes - Number of user-defined AWC forcing modes -1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) -1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) -0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] -1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] -0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] +1 ! AWC_NumModes - Number of user-defined AWC forcing modes +1 ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure) +1 ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2) +0.0500 ! AWC_freq - Frequency(s) of forcing mode(s) [Hz] +1.0000 ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg] +0.0000 ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg] !------- External Controller Interface ----------------------------------------------------- "unused" ! DLL_FileName - Name/location of the dynamic library in the Bladed-DLL format @@ -161,13 +185,14 @@ !------- ZeroMQ Interface --------------------------------------------------------- "tcp://localhost:5555" ! ZMQ_CommAddress - Communication address for ZMQ server, (e.g. "tcp://localhost:5555") -2 ! ZMQ_UpdatePeriod - Call ZeroMQ every [x] seconds, [s] +1.000000 ! ZMQ_UpdatePeriod - Update period at zmq interface to send measurements and wait for setpoint [sec.] +0 ! ZMQ_ID - Integer identifier of turbine !------- Cable Control --------------------------------------------------------- 1 ! CC_Group_N - Number of cable control groups - 0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL +0 ! CC_GroupIndex - First index for cable control group, should correspond to deltaL 20.000000 ! CC_ActTau - Time constant for line actuator [s] !------- Structural Controllers --------------------------------------------------------- 1 ! StC_Group_N - Number of cable control groups - 0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output +0 ! StC_GroupIndex - First index for structural control group, options specified in ServoDyn summary output diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_tower.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_tower.dat similarity index 100% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_tower.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_tower.dat diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_InflowFile.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_InflowFile.dat similarity index 76% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_InflowFile.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_InflowFile.dat index 401fd0a0..f1e0f032 100644 --- a/Test_Cases/NREL_2p8_127/NREL-2p8-127_InflowFile.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_InflowFile.dat @@ -5,6 +5,7 @@ False Echo - Echo input data to .ech (flag) 1 WindType - switch for wind file type (1=steady; 2=uniform; 3=binary TurbSim FF; 4=binary Bladed-style FF; 5=HAWC format; 6=User defined; 7=native Bladed FF) 0.0 PropagationDir - Direction of wind propagation (meteoroligical rotation from aligned with X (positive rotates towards -Y) -- degrees) 0.0 VFlowAng - Upflow angle (degrees) (not used for native Bladed format WindType=7) +False VelInterpCubic - Use cubic interpolation for velocity in time (false=linear, true=cubic) [Used with WindType=2,3,4,5,7] 1 NWindVel - Number of points to output the wind velocity (0 to 9) 0.0 WindVxiList - List of coordinates in the inertial X direction (m) 0.0 WindVyiList - List of coordinates in the inertial Y direction (m) @@ -47,6 +48,19 @@ False TowerFile - Have tower file (.twr) (flag) 0.0 PLExp_Hawc - Power law exponent (-) (used for PL wind profile type only) 0.0 Z0 - Surface roughness length (m) (used for LG wind profile type only) 0 XOffset - Initial offset in +x direction (shift of wind box) (-) +================== LIDAR Parameters =========================================================================== +0 SensorType - Switch for lidar configuration (0 = None, 1 = Single Point Beam(s), 2 = Continuous, 3 = Pulsed) +0 NumPulseGate - Number of lidar measurement gates (used when SensorType = 3) +30 PulseSpacing - Distance between range gates (m) (used when SensorType = 3) +0 NumBeam - Number of lidar measurement beams (0-5)(used when SensorType = 1) +-200 FocalDistanceX - Focal distance co-ordinates of the lidar beam in the x direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceY - Focal distance co-ordinates of the lidar beam in the y direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0 FocalDistanceZ - Focal distance co-ordinates of the lidar beam in the z direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m) +0.0 0.0 0.0 RotorApexOffsetPos - Offset of the lidar from hub height (m) +17 URefLid - Reference average wind speed for the lidar[m/s] +0.25 MeasurementInterval - Time between each measurement [s] +False LidRadialVel - TRUE => return radial component, FALSE => return 'x' direction estimate +1 ConsiderHubMotion - Flag whether to consider the hub motion's impact on Lidar measurements ====================== OUTPUT ================================================== False SumPrint - Print summary data to .IfW.sum (flag) OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) diff --git a/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat similarity index 98% rename from Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat rename to Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat index bdc2d74d..078bd87f 100644 --- a/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat @@ -74,7 +74,7 @@ True GenTiStp - Method to stop the generator {T: timed usin ---------------------- CABLE CONTROL ------------------------------------------- 0 CCmode - Cable control mode {0: none, 4: user-defined from Simulink/Labview, 5: user-defined from Bladed-style DLL} (switch) ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"/pscratch/ndeveld/awc/ROSCO_B/ROSCO/build/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"/pscratch/ndeveld/awc/ROSCO_B/lib/libdiscon.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] "NREL-2p8-127_DISCON.IN" DLL_InFile - Name of input file sent to the DLL (-) [used only with Bladed Interface] "DISCON" DLL_ProcName - Name of procedure in DLL to be called (-) [case sensitive; used only with DLL Interface] default DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] diff --git a/Test_Cases/Wind/90m_12mps_twr.inp b/Examples/Test_Cases/Wind/90m_12mps_twr.inp similarity index 100% rename from Test_Cases/Wind/90m_12mps_twr.inp rename to Examples/Test_Cases/Wind/90m_12mps_twr.inp diff --git a/Test_Cases/Wind/NoShr_3-15_50s.wnd b/Examples/Test_Cases/Wind/NoShr_3-15_50s.wnd similarity index 100% rename from Test_Cases/Wind/NoShr_3-15_50s.wnd rename to Examples/Test_Cases/Wind/NoShr_3-15_50s.wnd diff --git a/Examples/Test_Cases/update_libdiscon_extension.py b/Examples/Test_Cases/update_libdiscon_extension.py new file mode 100644 index 00000000..f11d18a0 --- /dev/null +++ b/Examples/Test_Cases/update_libdiscon_extension.py @@ -0,0 +1,21 @@ +import glob +import os +from rosco import discon_lib_path + +if __name__ == "__main__": + this_dir = os.path.dirname(os.path.abspath(__file__)) + servo_list = glob.glob(os.path.join(this_dir, '*/*Servo*.dat')) + + for ifile in servo_list: + # Read in current ServoDyn file + with open(ifile, "r") as f: + lines = f.readlines() + + # Write correction + with open(ifile, "w") as f: + for line in lines: + if line.find("DLL_FileName") >= 0: + f.write(f"\"{discon_lib_path}\" DLL_FileName - Name/location of the dynamic library (.dll [Windows] or .so [Linux]) in the Bladed-DLL format (-) [used only with Bladed Interface]\n") + else: + f.write(line) + diff --git a/Test_Cases/update_rosco_discons.py b/Examples/Test_Cases/update_rosco_discons.py similarity index 87% rename from Test_Cases/update_rosco_discons.py rename to Examples/Test_Cases/update_rosco_discons.py index 9a299991..07cdc5e5 100644 --- a/Test_Cases/update_rosco_discons.py +++ b/Examples/Test_Cases/update_rosco_discons.py @@ -3,7 +3,7 @@ ''' import os -from ROSCO_toolbox.ofTools.fast_io.update_discons import update_discons +from rosco.toolbox.ofTools.fast_io.update_discons import update_discons if __name__=="__main__": @@ -14,6 +14,7 @@ 'IEA15MW.yaml': 'IEA-15-240-RWT-UMaineSemi/DISCON-UMaineSemi.IN', 'BAR.yaml': 'BAR_10/BAR_10_DISCON.IN', 'NREL2p8.yaml': 'NREL_2p8_127/NREL-2p8-127_DISCON.IN', + 'RM1_MHK.yaml': 'MHK_RM1/MHK_RM1_DISCON.IN', } # Directories diff --git a/Tune_Cases/BAR.yaml b/Examples/Tune_Cases/BAR.yaml similarity index 95% rename from Tune_Cases/BAR.yaml rename to Examples/Tune_Cases/BAR.yaml index e1d7c463..bb21281d 100644 --- a/Tune_Cases/BAR.yaml +++ b/Examples/Tune_Cases/BAR.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'BAR_10.fst' # Name of *.fst file FAST_directory: '../Test_Cases/BAR_10' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.BAR_10.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/BAR_10/Cp_Ct_Cq.BAR_10.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: diff --git a/Tune_Cases/IEA15MW.yaml b/Examples/Tune_Cases/IEA15MW.yaml similarity index 96% rename from Tune_Cases/IEA15MW.yaml rename to Examples/Tune_Cases/IEA15MW.yaml index fa2aeb57..0bf65e99 100644 --- a/Tune_Cases/IEA15MW.yaml +++ b/Examples/Tune_Cases/IEA15MW.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: @@ -53,4 +53,5 @@ controller_params: ps_percent: 0.8 # Percent peak shaving [%, <= 1 ], {default = 80%} PA_CornerFreq: 1.5708 # Pitch actuator natural frequency [rad/s] PA_Damping: 0.707 # Pitch actuator natural frequency [rad/s] + rgn2k_factor: 0.85926 diff --git a/Tune_Cases/IEA15MW_ExtInterface.yaml b/Examples/Tune_Cases/IEA15MW_ExtInterface.yaml similarity index 94% rename from Tune_Cases/IEA15MW_ExtInterface.yaml rename to Examples/Tune_Cases/IEA15MW_ExtInterface.yaml index 7abe10da..32780386 100644 --- a/Tune_Cases/IEA15MW_ExtInterface.yaml +++ b/Examples/Tune_Cases/IEA15MW_ExtInterface.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: @@ -54,6 +54,6 @@ controller_params: ps_percent: 0.8 # Percent peak shaving [%, <= 1 ], {default = 80%} DISCON: - DLL_FileName: /Users/dzalkind/Tools/ROSCO/ROSCO/build/libdiscon_copy.dylib + DLL_FileName: /Users/dzalkind/Tools/ROSCO/lib/libdiscon_copy.dylib DLL_InFile: /Users/dzalkind/Tools/ROSCO/Test_Cases/NREL-5MW/DISCON.IN - DLL_ProcName: DISCON \ No newline at end of file + DLL_ProcName: DISCON diff --git a/Tune_Cases/IEA15MW_FOCAL.yaml b/Examples/Tune_Cases/IEA15MW_FOCAL.yaml similarity index 96% rename from Tune_Cases/IEA15MW_FOCAL.yaml rename to Examples/Tune_Cases/IEA15MW_FOCAL.yaml index 06a36cf8..4f28825a 100644 --- a/Tune_Cases/IEA15MW_FOCAL.yaml +++ b/Examples/Tune_Cases/IEA15MW_FOCAL.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: diff --git a/Tune_Cases/IEA15MW_MultiOmega.yaml b/Examples/Tune_Cases/IEA15MW_MultiOmega.yaml similarity index 96% rename from Tune_Cases/IEA15MW_MultiOmega.yaml rename to Examples/Tune_Cases/IEA15MW_MultiOmega.yaml index 20278253..bee656b5 100644 --- a/Tune_Cases/IEA15MW_MultiOmega.yaml +++ b/Examples/Tune_Cases/IEA15MW_MultiOmega.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: diff --git a/Tune_Cases/IEA15MW_OL.yaml b/Examples/Tune_Cases/IEA15MW_OL.yaml similarity index 96% rename from Tune_Cases/IEA15MW_OL.yaml rename to Examples/Tune_Cases/IEA15MW_OL.yaml index faaa6943..b14e3895 100644 --- a/Tune_Cases/IEA15MW_OL.yaml +++ b/Examples/Tune_Cases/IEA15MW_OL.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: @@ -39,6 +39,7 @@ controller_params: SD_Mode: 0 # Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} Fl_Mode: 1 # Floating specific feedback mode {0: no nacelle velocity feedback, 1: nacelle velocity feedback} Flp_Mode: 0 # Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control} + OL_Mode: 1 # Controller parameters zeta_pc: 1.0 # Pitch controller desired damping ratio [-] omega_pc: 0.3 # Pitch controller desired natural frequency [rad/s] @@ -51,7 +52,7 @@ controller_params: open_loop: flag: True OL_Ind_Breakpoint: 1 - OL_Ind_BldPitch: 2 + OL_Ind_BldPitch: [2,2,2] filename: /Users/dzalkind/Downloads/pitch_LC2p2_4ROSCO.dat # dt: 0.05 # t_max: 200 diff --git a/Examples/Tune_Cases/IEA15MW_PRC.yaml b/Examples/Tune_Cases/IEA15MW_PRC.yaml new file mode 100644 index 00000000..5df0361e --- /dev/null +++ b/Examples/Tune_Cases/IEA15MW_PRC.yaml @@ -0,0 +1,67 @@ +# --------------------- ROSCO controller tuning input file ------------------- + # Written for use with ROSCO_Toolbox tuning procedures + # Turbine: IEA 15MW Reference Wind Turbine +# ------------------------------ OpenFAST PATH DEFINITIONS ------------------------------ +path_params: + FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file + FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives + # Optional (but suggested...) + rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + +# -------------------------------- TURBINE PARAMETERS ----------------------------------- +turbine_params: + rotor_inertia: 310619488. # Rotor inertia [kg m^2], {Available in Elastodyn .sum file} + rated_rotor_speed: 0.7916813478 # Rated rotor speed [rad/s] + v_min: 3. # Cut-in wind speed [m/s] + v_rated: 10.74 # Rated wind speed [m/s] + v_max: 25.0 # Cut-out wind speed [m/s], -- Does not need to be exact (JUST ASSUME FOR NOW) + max_pitch_rate: 0.0349 # Maximum blade pitch rate [rad/s] + max_torque_rate: 4500000. # Maximum torque rate [Nm/s], {~1/4 VS_RtTq/s} + rated_power: 15000000. # Rated Power [W] + bld_edgewise_freq: 4.0324 # Blade edgewise first natural frequency [rad/s] + bld_flapwise_freq: 3.4872 # Blade flapwise first natural frequency [rad/s] + TSR_operational: 9.0 + +#------------------------------- CONTROLLER PARAMETERS ---------------------------------- +controller_params: + # Controller flags + LoggingLevel: 2 # {0: write no debug files, 1: write standard output .dbg-file, 2: write standard output .dbg-file and complete avrSWAP-array .dbg2-file + F_LPFType: 2 # {1: first-order low-pass filter, 2: second-order low-pass filter}, [rad/s] (currently filters generator speed and pitch control signals) + F_NotchType: 0 # Notch on the measured generator speed {0: disable, 1: enable} + IPC_ControlMode: 0 # Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} + VS_ControlMode: 2 # Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control} + PC_ControlMode: 1 # Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} + Y_ControlMode: 0 # Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} + SS_Mode: 1 # Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} + WE_Mode: 2 # Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator (Ortega et al.)} + PS_Mode: 3 # Pitch saturation mode {0: no pitch saturation, 1: peak shaving, 2: Cp-maximizing pitch saturation, 3: peak shaving and Cp-maximizing pitch saturation} + SD_Mode: 0 # Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} + Fl_Mode: 2 # Floating specific feedback mode {0: no nacelle velocity feedback, 1: nacelle velocity feedback} + Flp_Mode: 0 # Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control} + PA_Mode: 2 # Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} + # Controller parameters + # U_pc: [14] + zeta_pc: 1.0 # Pitch controller desired damping ratio [-] + omega_pc: 0.2 # Pitch controller desired natural frequency [rad/s] + zeta_vs: 0.85 # Torque controller desired damping ratio [-] + omega_vs: 0.12 # Torque controller desired natural frequency [rad/s] + twr_freq: 3.355 # for semi only! + ptfm_freq: 0.213 # for semi only! + # Optional - these can be defined, but do not need to be + min_pitch: 0.0 # Minimum pitch angle [rad], {default = 0 degrees} + vs_minspd: 0.523598775 # Minimum rotor speed [rad/s], {default = 0 rad/s} + ps_percent: 0.8 # Percent peak shaving [%, <= 1 ], {default = 80%} + PA_CornerFreq: 1.5708 # Pitch actuator natural frequency [rad/s] + PA_Damping: 0.707 # Pitch actuator natural frequency [rad/s] + + DISCON: + PS_BldPitchMin_N: 56 + PS_WindSpeeds: [ 3. , 3.4, 3.8, 4.2, 4.6, 5. , 5.4, 5.8, 6.2, 6.6, 7. , 7.4, 7.8, 8.2, 8.6, 9. , 9.4, 9.8, 10.2, 10.6, 11. , 11.4, 11.8, 12.2, 12.6, 13. , 13.4, 13.8, 14.2, 14.6, 15. , 15.4, 15.8, 16.2, 16.6, 17. , 17.4, 17.8, 18.2, 18.6, 19. , 19.4, 19.8, 20.2, 20.6, 21. , 21.4, 21.8, 22.2, 22.6, 23. , 23.4, 23.8, 24.2, 24.6, 25. ] + PS_BldPitchMin: [ 0.052, 0.032, 0.012, -0.012, -0.017, -0.017, -0.017, -0.017, -0.017, -0.017, -0.001, 0.01 , 0.02 , 0.029, 0.048, 0.068, 0.085, 0.1 , 0.113, 0.129, 0.145, 0.159, 0.172, 0.185, 0.197, 0.208, 0.219, 0.229, 0.238, 0.244, 0.251, 0.26 , 0.269, 0.277, 0.286, 0.296, 0.304, 0.313, 0.322, 0.332, 0.341, 0.35 , 0.359, 0.369, 0.378, 0.387, 0.396, 0.407, 0.416, 0.424, 0.434, 0.444, 0.454, 0.463, 0.473, 0.481] + PRC_GenSpeeds: [0.292, 0.292, 0.292, 0.292, 0.311, 0.338, 0.365, 0.392, 0.419, 0.446, 0.459, 0.459, 0.459, 0.459, 0.475, 0.497, 0.519, 0.542, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.564, 0.558, 0.553, 0.547, 0.542, 0.536, 0.531, 0.526, 0.52 , 0.515, 0.509, 0.504, 0.498, 0.493, 0.487, 0.482, 0.477, 0.471, 0.466, 0.46 , 0.455, 0.449, 0.444, 0.439, 0.433, 0.428] + PRC_WindSpeeds: [ 3. , 3.4, 3.8, 4.2, 4.6, 5. , 5.4, 5.8, 6.2, 6.6, 7. , 7.4, 7.8, 8.2, 8.6, 9. , 9.4, 9.8, 10.2, 10.6, 11. , 11.4, 11.8, 12.2, 12.6, 13. , 13.4, 13.8, 14.2, 14.6, 15. , 15.4, 15.8, 16.2, 16.6, 17. , 17.4, 17.8, 18.2, 18.6, 19. , 19.4, 19.8, 20.2, 20.6, 21. , 21.4, 21.8, 22.2, 22.6, 23. , 23.4, 23.8, 24.2, 24.6, 25. ] + PRC_n: 56 + PRC_Mode: 1 + VS_MinOMSpd: 0 + Fl_Mode: 0 + diff --git a/Tune_Cases/IEA15MW_ballast.yaml b/Examples/Tune_Cases/IEA15MW_ballast.yaml similarity index 94% rename from Tune_Cases/IEA15MW_ballast.yaml rename to Examples/Tune_Cases/IEA15MW_ballast.yaml index 6bf34418..2781aaca 100644 --- a/Tune_Cases/IEA15MW_ballast.yaml +++ b/Examples/Tune_Cases/IEA15MW_ballast.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: @@ -39,7 +39,8 @@ controller_params: Fl_Mode: 2 # Floating specific feedback mode {0: no nacelle velocity feedback, 1: nacelle velocity feedback} Flp_Mode: 0 # Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control} PA_Mode: 2 # Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} - StC_Mode: 1 + StC_Mode: 2 + OL_Mode: 1 # Controller parameters # U_pc: [14] zeta_pc: 1.0 # Pitch controller desired damping ratio [-] diff --git a/Tune_Cases/IEA15MW_cable.yaml b/Examples/Tune_Cases/IEA15MW_cable.yaml similarity index 96% rename from Tune_Cases/IEA15MW_cable.yaml rename to Examples/Tune_Cases/IEA15MW_cable.yaml index c17b006b..abba79fe 100644 --- a/Tune_Cases/IEA15MW_cable.yaml +++ b/Examples/Tune_Cases/IEA15MW_cable.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: @@ -39,7 +39,8 @@ controller_params: Fl_Mode: 2 # Floating specific feedback mode {0: no nacelle velocity feedback, 1: nacelle velocity feedback} Flp_Mode: 0 # Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control} PA_Mode: 2 # Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} - CC_Mode: 1 + CC_Mode: 2 + OL_Mode: 1 # Controller parameters # U_pc: [14] zeta_pc: 1.0 # Pitch controller desired damping ratio [-] diff --git a/Tune_Cases/IEA15MW_robust.yaml b/Examples/Tune_Cases/IEA15MW_robust.yaml similarity index 96% rename from Tune_Cases/IEA15MW_robust.yaml rename to Examples/Tune_Cases/IEA15MW_robust.yaml index cb7e611d..984ec52b 100644 --- a/Tune_Cases/IEA15MW_robust.yaml +++ b/Examples/Tune_Cases/IEA15MW_robust.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'IEA-15-240-RWT-UMaineSemi.fst' # Name of *.fst file FAST_directory: '../Test_Cases/IEA-15-240-RWT-UMaineSemi' # Main OpenFAST model directory, where the *.fst lives # Optional (but suggested...) - rotor_performance_filename: 'Cp_Ct_Cq.IEA15MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/IEA-15-240-RWT-UMaineSemi/Cp_Ct_Cq.IEA15MW.txt' # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: diff --git a/Tune_Cases/NREL2p8.yaml b/Examples/Tune_Cases/NREL2p8.yaml similarity index 93% rename from Tune_Cases/NREL2p8.yaml rename to Examples/Tune_Cases/NREL2p8.yaml index bbba19a2..c1562a83 100644 --- a/Tune_Cases/NREL2p8.yaml +++ b/Examples/Tune_Cases/NREL2p8.yaml @@ -1,4 +1,4 @@ -path_params: {FAST_InputFile: NREL-2p8-127.fst, FAST_directory: ../Test_Cases/NREL_2p8_127, rotor_performance_filename: NREL-2p8-127_Cp_Ct_Cq.txt} +path_params: {FAST_InputFile: NREL-2p8-127.fst, FAST_directory: ../Test_Cases/NREL_2p8_127, rotor_performance_filename: ../Test_Cases/NREL_2p8_127/NREL-2p8-127_Cp_Ct_Cq.txt} controller_params: LoggingLevel: 2 F_LPFType: 1 @@ -25,6 +25,7 @@ controller_params: TD_Mode: 0 PwC_Mode: 0 ZMQ_Mode: 0 + ZMQ_UpdatePeriod: 2 PA_Mode: 0 Ext_Mode: 0 U_pc: [12] diff --git a/Tune_Cases/NREL5MW.yaml b/Examples/Tune_Cases/NREL5MW.yaml similarity index 96% rename from Tune_Cases/NREL5MW.yaml rename to Examples/Tune_Cases/NREL5MW.yaml index 9ad252dc..21f5acab 100644 --- a/Tune_Cases/NREL5MW.yaml +++ b/Examples/Tune_Cases/NREL5MW.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'NREL-5MW.fst' # Name of *.fst file FAST_directory: '../Test_Cases/NREL-5MW' # Main OpenFAST model directory, where the *.fst lives # Optional - rotor_performance_filename: 'Cp_Ct_Cq.NREL5MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: diff --git a/Tune_Cases/NREL5MW_PassThrough.yaml b/Examples/Tune_Cases/NREL5MW_PassThrough.yaml similarity index 96% rename from Tune_Cases/NREL5MW_PassThrough.yaml rename to Examples/Tune_Cases/NREL5MW_PassThrough.yaml index 2ad3be80..7f126785 100644 --- a/Tune_Cases/NREL5MW_PassThrough.yaml +++ b/Examples/Tune_Cases/NREL5MW_PassThrough.yaml @@ -6,7 +6,7 @@ path_params: FAST_InputFile: 'NREL-5MW.fst' # Name of *.fst file FAST_directory: '../Test_Cases/NREL-5MW' # Main OpenFAST model directory, where the *.fst lives # Optional - rotor_performance_filename: 'Cp_Ct_Cq.NREL5MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + rotor_performance_filename: '../Test_Cases/NREL-5MW/Cp_Ct_Cq.NREL5MW.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) # -------------------------------- TURBINE PARAMETERS ----------------------------------- turbine_params: diff --git a/Tune_Cases/README.md b/Examples/Tune_Cases/README.md similarity index 100% rename from Tune_Cases/README.md rename to Examples/Tune_Cases/README.md diff --git a/Examples/Tune_Cases/RM1_MHK.yaml b/Examples/Tune_Cases/RM1_MHK.yaml new file mode 100644 index 00000000..12b294c2 --- /dev/null +++ b/Examples/Tune_Cases/RM1_MHK.yaml @@ -0,0 +1,68 @@ +--- # ---------------------NREL Generic controller tuning input file ------------------- + # Written for use with ROSCO_Toolbox tuning procedures + # Turbine: NREL 5MW Reference Wind Turbine +# ------------------------------ OpenFAST PATH DEFINITIONS ------------------------------ +path_params: + FAST_InputFile: 'MHK_RM1_Floating.fst' # Name of *.fst file + FAST_directory: '../Test_Cases/MHK_RM1' # Main OpenFAST model directory, where the *.fst lives + # Optional + rotor_performance_filename: '../Test_Cases/MHK_RM1/MHK_RM1_Cp_Ct_Cq.txt' # Filename for rotor performance text file (if it has been generated by ccblade already) + +# -------------------------------- TURBINE PARAMETERS ----------------------------------- +turbine_params: + rotor_inertia: 92169 # Rotor inertia [kg m^2], {Available in Elastodyn .sum file} + rated_rotor_speed: 1.204 # 11.5 rpm # Rated rotor speed [rad/s] + v_min: 0.5 # Cut-in wind speed [m/s] + v_rated: 2.0 # Rated wind speed [m/s] + v_max: 3.0 # Cut-out wind speed [m/s], -- Does not need to be exact (JUST ASSUME FOR NOW) + max_pitch_rate: 0.1745 # Maximum blade pitch rate [rad/s] + max_torque_rate: 1500000. # Maximum torque rate [Nm/s], {~1/4 VS_RtTq/s} + rated_power: 500000 # Rated Power [W] + bld_edgewise_freq: 60.2831853 # Blade edgewise first natural frequency [rad/s] + bld_flapwise_freq: 0.0 # Blade flapwise first natural frequency [rad/s] + reynolds_ref: 8e6 + # Optional + # TSR_operational: # None # Desired below-rated operational tip speed ratio (Cp-maximizing TSR is used if not defined) +#------------------------------- CONTROLLER PARAMETERS ---------------------------------- +controller_params: + # Controller flags + LoggingLevel: 2 # {0: write no debug files, 1: write standard output .dbg-file, 2: write standard output .dbg-file and complete avrSWAP-array .dbg2-file + F_LPFType: 1 # {1: first-order low-pass filter, 2: second-order low-pass filter}, [rad/s] (currently filters generator speed and pitch control signals) + F_NotchType: 1 # Notch filter on generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} + IPC_ControlMode: 0 # Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} + VS_ControlMode: 3 # Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control} + VS_ConstPower: 1 # Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control} + PC_ControlMode: 1 # Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} + Y_ControlMode: 0 # Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} + SS_Mode: 1 # Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} + WE_Mode: 0 # Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator (Ortega et al.)} + PS_Mode: 0 # Pitch saturation mode {0: no pitch saturation, 1: peak shaving, 2: Cp-maximizing pitch saturation, 3: peak shaving and Cp-maximizing pitch saturation} + SD_Mode: 0 # Shutdown mode {0: no shutdown procedure, 1: pitch to max pitch at shutdown} + Fl_Mode: 1 # Floating specific feedback mode {0: no nacelle velocity feedback, 1: nacelle velocity feedback} + Flp_Mode: 0 # Flap control mode {0: no flap control, 1: steady state flap angle, 2: Proportional flap control} + # Controller parameters + U_pc: [2.3,2.5] + interp_type: sigma + zeta_pc: [0.7,0.7] # Pitch controller desired damping ratio [-] + omega_pc: [0.9,0.9] # Pitch controller desired natural frequency [rad/s] + zeta_vs: 0.7 # Torque controller desired damping ratio [-] + omega_vs: 0.7 # Torque controller desired natural frequency [rad/s] + twr_freq: 3.3404 # Tower natural frequency [rad/s] # 0.4499 (old value) 3.3404(new value) + # twr_freq: 0.061009 # 2P + ptfm_freq: 0.6613 # Platform natural frequency [rad/s] (OC4Hywind Parameters, here) 0.2325 (old value) 0.6613879263 (new value) + # Optional + ps_percent: 0.80 # Percent peak shaving [%, <= 1 ], {default = 80%} + sd_maxpit: 0.4363 # Maximum blade pitch angle to initiate shutdown [rad], {default = bld pitch at v_max} + Kp_float: -0.3897 + max_torque_factor: 1.5 + DISCON: + F_NumNotchFilts: 2 + F_NotchFreqs: [1.0, 2.4200] # 2P + F_NotchBetaNum: [0.0, 0.0] + F_NotchBetaDen: [0.25, 0.25] + F_GenSpdNotch_N: 2 + F_GenSpdNotch_Ind: [1,2] + F_TwrTopNotch_N: 2 + F_TwrTopNotch_Ind: [1,2] + F_NotchCornerFreq_GS: [2.42] + F_FlHighPassFreq: 1.5 diff --git a/Examples/example_19.py b/Examples/example_19.py deleted file mode 100644 index fbbe67d1..00000000 --- a/Examples/example_19.py +++ /dev/null @@ -1,29 +0,0 @@ -''' ------------ XX_update_discon_version ----------------- -Test and demonstrate update_discon_version() function for converting an old ROSCO input -to the current version -''' - -import os -from ROSCO_toolbox.tune import update_discon_version - -this_dir = os.path.dirname(os.path.abspath(__file__)) -rosco_dir = os.path.dirname(this_dir) - - -def main(): - - old_discon_filename = os.path.join(this_dir,'example_inputs','DISCON_v2.2.0.IN') # An IEA-15MW input - - # Tuning yaml can be anything, does not have to correspond to old discon - tuning_yaml = os.path.join(rosco_dir,'Tune_Cases','NREL5MW.yaml') # dummy for now - update_discon_version( - old_discon_filename, - tuning_yaml, - os.path.join(this_dir,'examples_out','18_UPDATED_DISCON.IN') - ) - - - -if __name__ == "__main__": - main() \ No newline at end of file diff --git a/Examples/example_inputs/minimal_DISCON.IN b/Examples/example_inputs/minimal_DISCON.IN index 21716d03..305379fd 100644 --- a/Examples/example_inputs/minimal_DISCON.IN +++ b/Examples/example_inputs/minimal_DISCON.IN @@ -7,7 +7,8 @@ !------- CONTROLLER FLAGS ------------------------------------------------- 1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals -3 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} +2 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} +1 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} 1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} 1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} 2 ! WE_Mode - Wind speed estimator mode {0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter} @@ -17,6 +18,7 @@ Extra lines that ROSCO doesn't care about anymore !------- FILTERS ---------------------------------------------------------- 1.57080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] +0 ! F_NumNotchFilts - Number of notch filters placed on sensors 0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. 0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. diff --git a/Examples/example_inputs/minimal_DISCON_err.IN b/Examples/example_inputs/minimal_DISCON_err.IN index 327af71c..269736e0 100644 --- a/Examples/example_inputs/minimal_DISCON_err.IN +++ b/Examples/example_inputs/minimal_DISCON_err.IN @@ -7,9 +7,8 @@ !------- CONTROLLER FLAGS ------------------------------------------------- 1 ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals -0 ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} -1 ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {0: off, 1: 1P reductions, 2: 1P+2P reductions} -3 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} +2 ! VS_ControlMode - Generator torque control mode in above rated conditions {0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power} +1 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} 1 ! PC_ControlMode - Blade pitch control mode {0: No pitch, fix to fine pitch, 1: active PI blade pitch control} 0 ! Y_ControlMode - Yaw control mode {0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC} 1 ! SS_Mode - Setpoint Smoother mode {0: no setpoint smoothing, 1: introduce setpoint smoothing} @@ -32,9 +31,7 @@ Extra lines that ROSCO doesn't care about anymore !------- FILTERS ---------------------------------------------------------- 1.57080 ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s] -0.00000 ! F_LPFDamping - Damping coefficient {used only when F_FilterType = 2} [-] -0.00000 ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s] -0.000000 0.250000 ! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] +0 ! F_NumNotchFilts - Number of notch filters placed on sensors 0.62830 ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s]. 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. 0.17952 ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s]. diff --git a/Matlab_Toolbox/rosco_filters.m b/Matlab_Toolbox/rosco_filters.m new file mode 100644 index 00000000..3804d5f0 --- /dev/null +++ b/Matlab_Toolbox/rosco_filters.m @@ -0,0 +1,65 @@ +%% ROSCO Filters + +clear; + +dbg = ROSCOout2Matlab('/Users/dzalkind/Tools/ROSCO1/Examples/examples_out/26_MHK/5_low_ws_debug/RM1_MHK/power_curve/base/RM1_MHK_0.RO.dbg2'); + + +%% + + + +%% + +num2 = 0.001; +den2 = 0.1; + +num1 = 0.001; +den1 = 0.1; + +NF1 = notch(1,num1,den1,0.01); +NF2 = notch(2.42,num2,den2,0.01); + +figure(1); +bode(NF1) +bode(NF2) +bode(NF1*NF2) + +% BS = fdesign.bandstop( + + + + +y = lsim(NF1*NF2,dbg.GenSpeed,dbg.Time); +% % +% % +figure(2); +plot(dbg.Time,dbg.GenSpeed) +hold on; +plot(dbg.Time,dbg.GenSpeedF) +plot(dbg.Time,y) +% % +% % +hold off + +%% Notch Filter + +function notch_filt = notch(omega,BetaNum,BetaDen,DT) + +% DT = 0.01; +% +% omega = 1; +% BetaNum = 0.01; +% BetaDen = 0.25; + + K = 2.0/DT; + b2 = (K^2.0 + 2.0*omega*BetaNum*K + omega^2.0)/(K^2.0 + 2.0*omega*BetaDen*K + omega^2.0); + b1 = (2.0*omega^2.0 - 2.0*K^2.0) / (K^2.0 + 2.0*omega*BetaDen*K + omega^2.0); + b0 = (K^2.0 - 2.0*omega*BetaNum*K + omega^2.0) / (K^2.0 + 2.0*omega*BetaDen*K + omega^2.0); + a1 = (2.0*omega^2.0 - 2.0*K^2.0) / (K^2.0 + 2.0*omega*BetaDen*K + omega^2.0); + a0 = (K^2.0 - 2.0*omega*BetaDen*K + omega^2.0)/ (K^2.0 + 2.0*omega*BetaDen*K + omega^2.0); + + notch_filt = tf([b2,b1,b0],[1,a1,a0],DT); + +end + diff --git a/ROSCO/src/ZeroMQInterface.f90 b/ROSCO/src/ZeroMQInterface.f90 deleted file mode 100644 index 88ea2ecf..00000000 --- a/ROSCO/src/ZeroMQInterface.f90 +++ /dev/null @@ -1,77 +0,0 @@ -module ZeroMQInterface - USE, INTRINSIC :: ISO_C_BINDING, only: C_CHAR, C_DOUBLE, C_NULL_CHAR - IMPLICIT NONE - ! - -CONTAINS - SUBROUTINE UpdateZeroMQ(LocalVar, CntrPar, zmqVar, ErrVar) - USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, ZMQ_Variables, ErrorVariables - IMPLICIT NONE - TYPE(LocalVariables), INTENT(INOUT) :: LocalVar - TYPE(ControlParameters), INTENT(INOUT) :: CntrPar - TYPE(ZMQ_Variables), INTENT(INOUT) :: zmqVar - TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar - - character(256) :: zmq_address - real(C_DOUBLE) :: setpoints(5) - real(C_DOUBLE) :: turbine_measurements(16) - CHARACTER(*), PARAMETER :: RoutineName = 'UpdateZeroMQ' - - ! C interface with ZeroMQ client -#ifdef ZMQ_CLIENT - interface - subroutine zmq_client(zmq_address, measurements, setpoints) bind(C, name="zmq_client") - import :: C_CHAR, C_DOUBLE - implicit none - character(C_CHAR), intent(out) :: zmq_address(*) - real(C_DOUBLE) :: measurements(16) - real(C_DOUBLE) :: setpoints(5) - end subroutine zmq_client - end interface -#endif - - ! Communicate if threshold has been reached - IF ((MODULO(LocalVar%Time, CntrPar%ZMQ_UpdatePeriod) == 0) .OR. (LocalVar%iStatus == -1)) THEN - ! Collect measurements to be sent to ZeroMQ server - turbine_measurements(1) = LocalVar%iStatus - turbine_measurements(2) = LocalVar%Time - turbine_measurements(3) = LocalVar%VS_MechGenPwr - turbine_measurements(4) = LocalVar%VS_GenPwr - turbine_measurements(5) = LocalVar%GenSpeed - turbine_measurements(6) = LocalVar%RotSpeed - turbine_measurements(7) = LocalVar%GenTqMeas - turbine_measurements(8) = LocalVar%NacHeading - turbine_measurements(9) = LocalVar%NacVane - turbine_measurements(10) = LocalVar%HorWindV - turbine_measurements(11) = LocalVar%rootMOOP(1) - turbine_measurements(12) = LocalVar%rootMOOP(2) - turbine_measurements(13) = LocalVar%rootMOOP(3) - turbine_measurements(14) = LocalVar%FA_Acc - turbine_measurements(15) = LocalVar%NacIMU_FA_Acc - turbine_measurements(16) = LocalVar%Azimuth - - write (zmq_address, "(A,A)") TRIM(CntrPar%ZMQ_CommAddress), C_NULL_CHAR -#ifdef ZMQ_CLIENT - call zmq_client(zmq_address, turbine_measurements, setpoints) -#else - ! Add RoutineName to error message - ErrVar%aviFAIL = -1 - IF (CntrPar%ZMQ_Mode > 0) THEN - ErrVar%ErrMsg = " >> The ZeroMQ client has not been properly installed, " & - //"please install it to use ZMQ_Mode > 0." - ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg) - ENDIF -#endif - - ! write (*,*) "ZeroMQInterface: torque setpoint from ssc: ", setpoints(1) - ! write (*,*) "ZeroMQInterface: yaw setpoint from ssc: ", setpoints(2) - ! write (*,*) "ZeroMQInterface: pitch 1 setpoint from ssc: ", setpoints(3) - ! write (*,*) "ZeroMQInterface: pitch 2 setpoint from ssc: ", setpoints(4) - ! write (*,*) "ZeroMQInterface: pitch 3 setpoint from ssc: ", setpoints(5) - zmqVar%Yaw_Offset = setpoints(2) - - ENDIF - - - END SUBROUTINE UpdateZeroMQ -end module ZeroMQInterface \ No newline at end of file diff --git a/ROSCO_toolbox/control_interface.py b/ROSCO_toolbox/control_interface.py deleted file mode 100644 index 4d17dba2..00000000 --- a/ROSCO_toolbox/control_interface.py +++ /dev/null @@ -1,472 +0,0 @@ -# Copyright 2019 NREL - -# Licensed under the Apache License, Version 2.0 (the "License"); you may not use -# this file except in compliance with the License. You may obtain a copy of the -# License at http://www.apache.org/licenses/LICENSE-2.0 - -# Unless required by applicable law or agreed to in writing, software distributed -# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR -# CONDITIONS OF ANY KIND, either express or implied. See the License for the -# specific language governing permissions and limitations under the License. - -from ctypes import byref, cdll, POINTER, c_float, c_char_p, c_double, create_string_buffer, c_int32, c_void_p -import numpy as np -import platform, ctypes -import zmq - -# Some useful constants -deg2rad = np.deg2rad(1) -rad2deg = np.rad2deg(1) -rpm2RadSec = 2.0*(np.pi)/60.0 - -class ControllerInterface(): - """ - Define interface to a given controller using the avrSWAP array - - Methods: - -------- - call_discon - call_controller - show_control_values - - Parameters: - ----------- - lib_name : str - name of compiled dynamic library containing controller, (.dll,.so,.dylib) - - """ - - def __init__(self, lib_name, param_filename='DISCON.IN', **kwargs): - """ - Setup the interface - """ - self.lib_name = lib_name - self.param_name = param_filename - - # Set default parameters - # PARAMETERS - self.DT = 0.1 - self.num_blade = 3 - self.char_buffer = 500 - self.avr_size = 500 - self.sim_name = 'simDEBUG' - - # Set kwargs, like DT - for (k, w) in kwargs.items(): - try: - setattr(self, k, w) - except: - pass - - self.init_discon() - - def init_discon(self): - - # Initialize - self.pitch = 0 - self.torque = 0 - # -- discon - self.discon = cdll.LoadLibrary(self.lib_name) - self.avrSWAP = np.zeros(self.avr_size) - - # Define some avrSWAP parameters, NOTE: avrSWAP indices are offset by -1 from Fortran - self.avrSWAP[2] = self.DT - self.avrSWAP[60] = self.num_blade - self.avrSWAP[19] = 1.0 # HARD CODE initial gen speed = 1 rad/s - self.avrSWAP[20] = 1.0 # HARD CODE initial rot speed = 1 rad/s - self.avrSWAP[82] = 0 # HARD CODE initial nacIMU = 0 - self.avrSWAP[26] = 10 # HARD CODE initial wind speed = 10 m/s - - # Blade pitch initial conditions - self.avrSWAP[3] = 0 * np.deg2rad(1) - self.avrSWAP[32] = 0 * np.deg2rad(1) - self.avrSWAP[33] = 0 * np.deg2rad(1) - - self.avrSWAP[27] = 1 # IPC - - # Torque initial condition - self.avrSWAP[22] = 0 - - # Code this as first call - self.avrSWAP[0] = 0 - - # Put some values in - self.avrSWAP[58] = self.char_buffer - self.avrSWAP[49] = len(self.param_name) - self.avrSWAP[50] = self.char_buffer - self.avrSWAP[51] = self.char_buffer - - # Initialize DISCON and related - self.aviFAIL = c_int32() # 1 - self.accINFILE = self.param_name.encode('utf-8') - self.avcOUTNAME = (self.sim_name + '.RO.dbg').encode('utf-8') - self.avcMSG = create_string_buffer(1000) - self.discon.DISCON.argtypes = [POINTER(c_float), POINTER(c_int32), c_char_p, c_char_p, c_char_p] # (all defined by ctypes) - - # Run DISCON - self.call_discon() - - # Code as not first run now that DISCON has been initialized - self.avrSWAP[0] = 1 - - - def call_discon(self): - ''' - Call libdiscon.dll (or .so,.dylib,...) - ''' - # Convert AVR swap to the c pointer - c_float_p = POINTER(c_float) - data = self.avrSWAP.astype(np.float32) - p_data = data.ctypes.data_as(c_float_p) - - # Run DISCON - self.discon.DISCON(p_data, byref(self.aviFAIL), self.accINFILE, self.avcOUTNAME, self.avcMSG) - - # Push back to avr swap - self.avrSWAP = data - - - def call_controller(self, turbine_state, end=False): - ''' - Runs the controller. Passes current turbine state to the controller, and returns control inputs back - - Parameters: - ----------- - turbine_state: dict - t: float - time, (s) - dt: float - timestep, (s) - pitch: float - blade pitch, (rad) - genspeed: float - generator speed, (rad/s) - geneff: float - generator efficiency, (rad/s) - rotspeed: float - rotor speed, (rad/s) - ws: float - wind speed, (m/s) - yaw: float, optional - nacelle yaw position (from north) (deg) - yawerr: float, optional - yaw misalignment, defined as the wind direction minus the yaw - position (deg) - ''' - - # Add states to avr - self.avrSWAP[0] = turbine_state['iStatus'] - self.avrSWAP[1] = turbine_state['t'] - self.avrSWAP[2] = turbine_state['dt'] - self.avrSWAP[3] = turbine_state['bld_pitch'] - self.avrSWAP[32] = turbine_state['bld_pitch'] - self.avrSWAP[33] = turbine_state['bld_pitch'] - self.avrSWAP[14] = turbine_state['gen_speed'] * turbine_state['gen_torque'] * turbine_state['gen_eff'] - self.avrSWAP[22] = turbine_state['gen_torque'] - self.avrSWAP[19] = turbine_state['gen_speed'] - self.avrSWAP[20] = turbine_state['rot_speed'] - self.avrSWAP[23] = turbine_state['Y_MeasErr'] - self.avrSWAP[26] = turbine_state['ws'] - self.avrSWAP[36] = turbine_state['Yaw_fromNorth'] - try: - self.avrSWAP[82] = turbine_state['NacIMU_FA_Acc'] - except KeyError: - self.avrSWAP[82] = 0 - - # call controller - self.call_discon() - - # return controller states - self.pitch = self.avrSWAP[41] - self.torque = self.avrSWAP[46] - self.nac_yawrate = self.avrSWAP[47] - - return(self.torque,self.pitch,self.nac_yawrate) - - def show_control_values(self): - ''' - Show control values - should be obvious - ''' - print('Pitch',self.pitch) - print('Torque',self.torque) - - def kill_discon(self): - ''' - Unload the dylib from memory: https://github.com/bwoodsend/cslug/blob/master/cslug/_stdlib.py - ''' - - print('Shutting down {}'.format(self.lib_name)) - handle = self.discon._handle - - # Start copy here - OS = platform.system() - - def null_free_dll(*spam): # pragma: no cover - pass - - # Try to find a good runtime library which is always available and contains - # the standard library C functions such as malloc() or printf(). - # XXX: Keep chosen library names in sync with the table in `cslug/stdlib.py`. - - extra_libs = [] - - if OS == "Windows": # pragma: Windows - try: - _dlclose = ctypes.windll.kernel32.FreeLibrary - dlclose = lambda handle: 0 if _dlclose(handle) else 1 - except: - kernel32 = ctypes.WinDLL('kernel32',use_last_error=True) - kernel32.FreeLibrary.argtypes = [ctypes.wintypes.HMODULE] - dlclose = lambda handle: 0 if kernel32.FreeLibrary(handle) else 1 - # There's some controversy as to whether this DLL is guaranteed to exist. - # It always has so far but isn't documented. However, MinGW assumes that it - # is so, should this DLL be removed, then we have much bigger problems than - # just this line. There is also vcruntime140.dll which isn't a standard part - # of the OS but is always shipped with Python so we can guarantee its - # presence. But vcruntime140 contains only a tiny strict-subset of msvcrt. - stdlib = ctypes.CDLL("msvcrt") - - elif OS == "Darwin": # pragma: Darwin - try: - try: - # macOS 11 (Big Sur). Possibly also later macOS 10s. - stdlib = ctypes.CDLL("libc.dylib") - except OSError: # pragma: no cover - stdlib = ctypes.CDLL("libSystem") - except OSError: # pragma: no cover - # Older macOSs. Not only is the name inconsistent but it's - # not even in PATH. - _stdlib = "/usr/lib/system/libsystem_c.dylib" - if os.path.exists(_stdlib): - stdlib = ctypes.CDLL(_stdlib) - else: - stdlib = None - if stdlib is not None: # pragma: no branch - dlclose = stdlib.dlclose - else: # pragma: no cover - # I hope this never happens. - dlclose = null_free_dll - - elif OS == "Linux": # pragma: Linux - try: - stdlib = ctypes.CDLL("") - except OSError: # pragma: no cover - # Either Alpine Linux or Android. - # Unfortunately, there doesn't seem to be any practical way - # to tell them apart. - stdlib = ctypes.CDLL("libc.so") - - # Android, like FreeBSD puts its math functions - # in a dedicated `libm.so`. - # The only way to know that this is not Alpine is to check if the math - # functions are already available in `libc.so`. - if not hasattr(stdlib, "sin"): - extra_libs.append(ctypes.CDLL("libm.so")) - dlclose = stdlib.dlclose - - # End copy here - dlclose.argtypes = [c_void_p] - dlclose(handle) - - del self.discon - - -class farm_zmq_server(): - def __init__(self, network_addresses=["tcp://*:5555", "tcp://*:5556"], - identifiers=None, timeout=600.0, verbose=False): - """Python implementation for communicating with multiple instances - of the ROSCO ZeroMQ interface. This is useful for SOWFA and FAST.Farm - simulations in which multiple turbines are running in real time. - Args: - network_addresses (str, optional): List with the network addresses - used to communicate with the desired instances of ROSCO. - identifiers (iteratible, optional): List of strings denoting the - turbine identification string, e.g., ["WTG-01", "WTG-02"]. - If left unspecified, will simple name the turbines "0" to - nturbs - 1. - timeout (float, optional): Seconds to wait for a message from - the ZeroMQ server before timing out. Defaults to 600.0. - verbose (bool, optional): Print to console. Defaults to False. - """ - self.network_addresses = network_addresses - self.verbose = verbose - self.nturbs = len(self.network_addresses) - - if identifiers is None: - identifiers = ["%d" % i for i in range(self.nturbs)] - - # Initialize ZeroMQ servers - self.zmq_servers = [None for _ in range(self.nturbs)] - for ti, address in enumerate(self.network_addresses): - self.zmq_servers[ti] = turbine_zmq_server( - network_address=address, - identifier=identifiers[ti], - timeout=timeout, - verbose=verbose) - - def get_measurements(self): - ''' - Get measurements from zmq servers - ''' - measurements = [None for _ in range(self.nturbs)] - for ti in range(self.nturbs): - measurements[ti] = self.zmq_servers[ti].get_measurements() - return measurements - - def send_setpoints(self, genTorques=None, nacelleHeadings=None, - bladePitchAngles=None): - ''' - Send setpoints to DLL via zmq server for farm level controls - - Parameters: - ----------- - genTorques: List - List of generator torques of length self.nturbs - nacelleHeadings: List - List of nacelle headings of length self.nturbs - bladePitchAngles: List - List of blade pitch angles of length self.nturbs - ''' - # Default choices if unspecified - if genTorques is None: - genTorques = [0.0] * self.nturbs - if nacelleHeadings is None: - nacelleHeadings = [0.0] * self.nturbs - if bladePitchAngles is None: - bladePitchAngles = [[0.0, 0.0, 0.0]] * self.nturbs - - # Send setpoints - for ti in range(self.nturbs): - self.zmq_servers[ti].send_setpoints( - genTorque=genTorques[ti], - nacelleHeading=nacelleHeadings[ti], - bladePitch=bladePitchAngles[ti] - ) - - -class turbine_zmq_server(): - def __init__(self, network_address="tcp://*:5555", identifier="0", - timeout=600.0, verbose=False): - """Python implementation of the ZeroMQ server side for the ROSCO - ZeroMQ wind farm control interface. This class makes it easy for - users to receive measurements from ROSCO and then send back control - setpoints (generator torque, nacelle heading and/or blade pitch - angles). - Args: - network_address (str, optional): The network address to - communicate over with the desired instance of ROSCO. Note that, - if running a wind farm simulation in SOWFA or FAST.Farm, there - are multiple instances of ROSCO and each of these instances - needs to communicate over a unique port. Also, for each of those - instances, you will need an instance of zmq_server. This variable - Defaults to "tcp://*:5555". - identifier (str, optional): Turbine identifier. Defaults to "0". - timeout (float, optional): Seconds to wait for a message from - the ZeroMQ server before timing out. Defaults to 600.0. - verbose (bool, optional): Print to console. Defaults to False. - """ - self.network_address = network_address - self.identifier = identifier - self.timeout = timeout - self.verbose = verbose - self._connect() - - def _connect(self): - ''' - Connect to zmq server - ''' - address = self.network_address - - # Connect socket - context = zmq.Context() - self.socket = context.socket(zmq.REP) - self.socket.setsockopt(zmq.LINGER, 0) - self.socket.bind(address) - - if self.verbose: - print("[%s] Successfully established connection with %s" % (self.identifier, address)) - - def _disconnect(self): - ''' - Disconnect from zmq server - ''' - self.socket.close() - context = zmq.Context() - context.term() - - def get_measurements(self): - ''' - Receive measurements from ROSCO .dll - ''' - if self.verbose: - print("[%s] Waiting to receive measurements from ROSCO..." % (self.identifier)) - - # Initialize a poller for timeouts - poller = zmq.Poller() - poller.register(self.socket, zmq.POLLIN) - timeout_ms = int(self.timeout * 1000) - if poller.poll(timeout_ms): - # Receive measurements over network protocol - message_in = self.socket.recv_string() - else: - raise IOError("[%s] Connection to '%s' timed out." - % (self.identifier, self.network_address)) - - # Convert to individual strings and then to floats - measurements = message_in - measurements = measurements.replace('\x00', '').split(',') - measurements = [float(m) for m in measurements] - - # Convert to a measurement dict - measurements = dict({ - 'iStatus': measurements[0], - 'Time': measurements[1], - 'VS_MechGenPwr': measurements[2], - 'VS_GenPwr': measurements[3], - 'GenSpeed': measurements[4], - 'RotSpeed': measurements[5], - 'GenTqMeas': measurements[6], - 'NacelleHeading': measurements[7], - 'NacelleVane': measurements[8], - 'HorWindV': measurements[9], - 'rootMOOP1': measurements[10], - 'rootMOOP2': measurements[11], - 'rootMOOP3': measurements[12], - 'FA_Acc': measurements[13], - 'NacIMU_FA_Acc': measurements[14], - 'Azimuth': measurements[15], - }) - - if self.verbose: - print('[%s] Measurements received:' % self.identifier, measurements) - - return measurements - - def send_setpoints(self, genTorque=0.0, nacelleHeading=0.0, - bladePitch=[0.0, 0.0, 0.0]): - ''' - Send setpoints to ROSCO .dll ffor individual turbine control - - Parameters: - ----------- - genTorques: float - Generator torque setpoint - nacelleHeadings: float - Nacelle heading setpoint - bladePitchAngles: List (len=3) - Blade pitch angle setpoint - ''' - # Create a message with setpoints to send to ROSCO - message_out = b"%016.5f, %016.5f, %016.5f, %016.5f, %016.5f" % ( - genTorque, nacelleHeading, bladePitch[0], bladePitch[1], - bladePitch[2]) - - # Send reply back to client - if self.verbose: - print("[%s] Sending setpoint string to ROSCO: %s." % (self.identifier, message_out)) - - # Send control setpoints over network protocol - self.socket.send(message_out) - - if self.verbose: - print("[%s] Setpoints sent successfully." % self.identifier) diff --git a/docs/conf.py b/docs/conf.py index fb94dae9..952f6936 100644 --- a/docs/conf.py +++ b/docs/conf.py @@ -23,8 +23,8 @@ author = 'Nikhar J. Abbas, Daniel S. Zalkind' # The full version, including alpha/beta/rc tags -import ROSCO_toolbox -release = str(ROSCO_toolbox.__version__) +import rosco.toolbox +release = str(rosco.toolbox.__version__) from unittest import mock class MockModule(mock.Mock): @@ -52,6 +52,7 @@ def __getattr__(cls, name): "sphinx.ext.intersphinx", "sphinx.ext.graphviz", "sphinx.ext.autosectionlabel", + "sphinx_rtd_theme", # "sphinxcontrib.bibtex", ] @@ -84,7 +85,7 @@ def __getattr__(cls, name): # The theme to use for HTML and HTML Help pages. See the documentation for # a list of builtin themes. # -html_theme = "furo" +html_theme = "sphinx_rtd_theme" # Add any paths that contain custom static files (such as style sheets) here, # relative to this directory. They are copied after the builtin static files, diff --git a/docs/index.rst b/docs/index.rst index 1e60107e..e763859e 100644 --- a/docs/index.rst +++ b/docs/index.rst @@ -3,54 +3,39 @@ ROSCO Documentation :Version: |release| :Date: |today| -NREL's Reference OpenSource Controller (ROSCO) tool-set for wind turbine applications designed to ease controller implementation for the wind turbine researcher. The purpose of these documents is to provide information for the use of the tool-set. +NREL's "Reference Open Source Controller" (ROSCO) is a reference controller framework that facilitates design and implementation of wind turbine and wind farm controllers for fixed and floating offshore wind turbines. -:numref:`fig-RT` shows the general workflow for the ROSCO tool-chain. with OpenFAST +ROSCO frameworks includes a large set of available controllers and advanced functionalities that can be combined in a modular fashion based on the intended application and can be easily adapted to a wide variety wind turbines. +For example, ROSCO can be used to design turbine yaw controller along with an individual blade pitch controller with floating platform feedback for an offshore turbine while simulating a pitch actuator fault and running a user-defined torque controller. -.. _fig-RT: -.. figure:: /source/figures/ROSCO_toolbox.svg - :align: center - :width: 80% +ROSCO provides a single framework for designing controllers for onshore and offshore turbines of varying sizes. +It can be used to run representative dynamic simulations using OpenFAST. +This helps researchers perform 'apples-to-apples' comparison of controller capabilities across turbines. +Control engineers can also design their own controllers and compare them with reference controller design using ROSCO for existing and new turbines. +ROSCO has been used to provide reference controllers for many recent reference turbines including the `IEA 3.4-MW `_ , `IEA 10-MW `_ , `IEA 15-MW `_ and the upcoming `IEA 22-MW `_ turbines. - ROSCO toolchain general workflow +The ROSCO framework also includes a python based toolbox that primarily enables tuning the controllers. +The tuning process is extemely simple where only a tuning parameters need to be provided. +It is not necessary to run aeroelastic simulations or provide linearized state-space models to tune the controller to tune the controllers. +The toolbox has other capabilities like simple 1-DOF turbine simulations for quick controller capability verifications, linear model analysis, and parsing of input and output files. +Source code for ROSCO toolset can be found in this `github repository `_ and it can be installed following the instructions provided in :ref:`install`. -**ROSCO Toolbox** -The python-based toolbox primarily used for tuning the controller and writing the DISCON.IN. +**Documentation Directory** -* Generic tuning of NREL's ROSCO controller -* Simple 1-DOF turbine simulations for quick controller capability verifications -* Parsing of OpenFAST input and output files -* Linear model analysis capability - -**ROSCO Controller** -The controller implementation itself. This is compiled to :code:`libdiscon.*` file, reads the DISCON.IN file, and interfaces with OpenFAST using the Bladed-style interface. - -* Fortran based -* Follows Bladed-style control interface -* Modular - -Standard Use ------------- - -For the standard use case in OpenFAST (or similar), ROSCO will need to be compiled. This is made possible via the instructions found in :ref:`install`. Once the controller is compiled, the turbine model needs to point to the compiled binary. In OpenFAST, this is ensured by changing the :code:`DLL_FileName` parameter in the ServoDyn input file. - -Additionally, an additional input file is needed for the ROSCO controller. Though the controller only needs to be compiled once, each individual turbine/controller tuning requires an input file. This input file is generically dubbed "DISCON.IN''. In OpenFAST, the :code:`DLL_InFile` parameter should be set to point to the desired input file. The ROSCO toolbox is used to automatically generate the input file. These instructions are provided in the instructions for :ref:`standard_use`. - -Technical Documentation ------------------------ -A publication highlighting much of the theory behind the controller tuning and implementation methods can be found at: -https://wes.copernicus.org/preprints/wes-2021-19/ - -Survey ------- -Please help us better understand the ROSCO user-base and how we can improve ROSCO through this brief survey: - -.. raw:: html - - +.. toctree:: + :maxdepth: 3 + :numbered: - + source/standard_use.rst + source/install.rst + source/examples.rst + source/rosco.rst + source/rosco_toolbox.rst + source/api_change.rst + source/toolbox_input.rst + source/how_to_contribute_code.rst + source/ROSCO_instructions_for_Bladed.rst License ------- @@ -67,15 +52,3 @@ distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License. - -.. toctree:: - :maxdepth: 3 - :numbered: - - source/install.rst - source/standard_use.rst - source/rosco_toolbox.rst - source/rosco.rst - source/api_change.rst - source/toolbox_input.rst - source/ROSCO_instructions_for_Bladed.rst diff --git a/docs/requirements.txt b/docs/requirements.txt index 6ff6c653..5b42fa1e 100644 --- a/docs/requirements.txt +++ b/docs/requirements.txt @@ -1,4 +1,4 @@ # File: docs/requirements.txt sphinx>4.0.0 -furo \ No newline at end of file +sphinx_rtd_theme diff --git a/docs/source/api_change.rst b/docs/source/api_change.rst index 4fecc5a6..0127cd07 100644 --- a/docs/source/api_change.rst +++ b/docs/source/api_change.rst @@ -9,17 +9,112 @@ The changes are tabulated according to the line number, and flag name. The line number corresponds to the resulting line number after all changes are implemented. Thus, be sure to implement each in order so that subsequent line numbers are correct. +2.8.0 to 2.9.0 +------------------------------- +**Flag to use exteneded Bladed Interface** + +* Set `Ext_Interface` to 1 to use the extened bladed interface with OpenFAST v3.5.0 and greater + +**Gain scheduling of floating feedback** + +* The floating feedback gain can be scheduled on the low pass filtered wind speed signal. Note that Fl_Kp can now be an array. + +**Rotor position tracking** + +* Control the azimuth position of the rotor with `OL_Mode` of 2 using a PID torque controller with gains defined by `RP_Gains`. +* Control all three blade pitch inputs in open loop + +**New torque control mode settings** + +* VS_ControlMode determines how the generator speed set point is determined: using the WSE (mode 2) or (P/K)^(1/3) (mode 3). The power signal in mode 3 is filtered using `VS_PwrFiltF`. +* VS_ConstPower determines whether constant power is used (0 is constant torque, 1 is constant power) + +**Multiple notch filters** + +* Users can list any number of notch filters and apply them to either the generator speed and/or tower top accelleration signal based on their index + +**Power reference control via generator speed set points** + +* With this feature, enabled with `PRC_Mode`, a user can prescribe a set of generator speed set points (`PRC_GenSpeeds`) vs. the estimated wind speed (`PRC_WindSpeeds`), which can be used to avoid certain natural frequencies or implement a soft cut-out scheme. +* A low pass filter with frequency `PRC_LPF_Freq` is used to filter the wind speed estimate. A lower value increases the stability of the generator speed reference signal. + +**ZeroMQ Interface** + +* Each turbine is assigned a `ZMQ_ID` by the controller, which is tracked by a farm-level controller + +**Tower resonance avoidance** + +* When `TRA_Mode` is 1, change the torque control generator speed setpoint to avoid TRA_ExclSpeed +/- TRA_ExclBand. +* The set point is changed at a slow rate `TRA_RateLimit` to avoid generator power spikes. `VS_RefSpd`/100 is recommended. + +====== ======================= =============================================================================================================================================================================================================================================================== +Removed in ROSCO develop +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- +Line Input Name Example Value +====== ======================= =============================================================================================================================================================================================================================================================== +11 F_NotchType 2 ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion} +35 F_NotchCornerFreq 3.35500 ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s] +36 F_NotchBetaNumDen 0.000000 0.250000 ! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] +====== ======================= =============================================================================================================================================================================================================================================================== + + +====== ======================= =============================================================================================================================================================================================================================================================== +New in ROSCO develop +------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- +Line Input Name Example Value +====== ======================= =============================================================================================================================================================================================================================================================== +7 Ext_Interface 1 ! Ext_Interface - (0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0.) +14 VS_ConstPower 0 ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque} +18 PRC_Mode 0 ! PRC_Mode - Power reference tracking mode{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints} +38 F_NumNotchFilts 1 ! F_NumNotchFilts - Number of notch filters placed on sensors +39 F_NotchFreqs 3.3550 ! F_NotchFreqs - Natural frequency of the notch filters. Array with length F_NumNotchFilts +40 F_NotchBetaNum 0.0000 ! F_NotchBetaNum - Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] +41 F_NotchBetaDen 0.2500 ! F_NotchBetaDen - Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] +42 F_GenSpdNotch_N 0 ! F_GenSpdNotch_N - Number of notch filters on generator speed +43 F_GenSpdNotch_Ind 0 ! F_GenSpdNotch_Ind - Indices of notch filters on generator speed +44 F_TwrTopNotch_N 1 ! F_TwrTopNotch_N - Number of notch filters on tower top acceleration signal +45 F_TwrTopNotch_Ind 1 ! F_TwrTopNotch_Ind - Indices of notch filters on tower top acceleration signal +92 VS_PwrFiltF 0.3140 ! VS_PwrFiltF - Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. +98 PRC_Section !------- POWER REFERENCE TRACKING -------------------------------------- +99 PRC_n 2 ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array +100 PRC_LPF_Freq 0.07854 ! PRC_LPF_Freq - Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] +101 PRC_WindSpeeds 3.0000 25.0000 ! PRC_WindSpeeds - Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] +102 PRC_GenSpeeds 0.7917 0.7917 ! PRC_GenSpeeds - Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] +103 Empty Line +128 TRA_ExclSpeed 0.00000 ! TRA_ExclSpeed - Rotor speed for exclusion [LSS, rad/s] +129 TRA_ExclBand 0.00000 ! TRA_ExclBand - Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 +130 TRA_RateLimit 0.00000e+00 ! TRA_RateLimit - Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/100. +145 Fl_n 1 ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1 +147 Fl_U 0.0000 ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] +161 Ind_Azimuth 0 ! Ind_Azimuth - The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) +162 RP_Gains 0.0000 0.0000 0.0000 0.0000 ! RP_Gains - PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) +186 ZMQ_ID 0 ! ZMQ_ID - Integer identifier of turbine +====== ======================= =============================================================================================================================================================================================================================================================== + +====== ================= ====================================================================================================================================================================================================== +Changed in ROSCO develop +---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- +Line Input Name Example Value +====== ================= ====================================================================================================================================================================================================== +12 VS_ControlMode 2 ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)}126 OL_mode 0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: rotor position control} +125 Twr_Section !------- TOWER CONTROL ------------------------------------------------------ + +141 Fl_Kp 0.0000 ! Fl_Kp - Nacelle velocity proportional feedback gain [s] +153 Ind_BldPitch 0 0 0 ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array] +====== ================= ====================================================================================================================================================================================================== + + 2.7.0 to 2.8.0 ------------------------------- Optional Inputs -- ROSCO now reads in the whole input file and searches for keywords to set the inputs. Blank spaces and specific ordering are no longer required. -- Input requirements depend on control modes. E.g., open loop inputs are not required if `OL_Mode = 0`` +- ROSCO now reads in the whole input file and searches for keywords to set the inputs. Blank spaces and specific ordering are no longer required. +- Input requirements depend on control modes. E.g., open loop inputs are not required if `OL_Mode = 0`` Cable Control -- Can control OpenFAST cables (MoorDyn or SubDyn) using ROSCO +- Can control OpenFAST cables (MoorDyn or SubDyn) using ROSCO Structural Control -- Can control OpenFAST structural control elements (ServoDyn) using ROSCO +- Can control OpenFAST structural control elements (ServoDyn) using ROSCO Active wake control -- Added Active Wake Control (AWC) implementation +- Added Active Wake Control (AWC) implementation ====== ================= ====================================================================================================================================================================================================== New in ROSCO 2.8.0 @@ -55,15 +150,16 @@ Line Input Name Example Value 2.6.0 to 2.7.0 ------------------------------- Pitch Faults -- Constant pitch actuator offsets (PF_Mode = 1) +- Constant pitch actuator offsets (PF_Mode = 1) IPC Saturation Modes -- Added options for saturating the IPC command with the peak shaving limit +- Added options for saturating the IPC command with the peak shaving limit ====== ================= ====================================================================================================================================================================================================== New in ROSCO 2.7.0 ---------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------- Line Input Name Example Value ====== ================= ====================================================================================================================================================================================================== +22 PA_Mode 0 ! PA_Mode - Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} 23 PF_Mode 0 ! PF_Mode - Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} 56 IPC_SatMode 2 ! IPC_SatMode - IPC Saturation method (0 - no saturation (except by PC_MinPit), 1 - saturate by PS_BldPitchMin, 2 - saturate sotfly (full IPC cycle) by PC_MinPit, 3 - saturate softly by PS_BldPitchMin) 139 PF_Section !------- Pitch Actuator Faults --------------------------------------------------------- @@ -72,22 +168,22 @@ Line Input Name Example Value ====== ================= ====================================================================================================================================================================================================== -2.5.0 to 2.6.0 +2.5.0 to develop ------------------------------- IPC -- A wind speed based soft cut-in using a sigma interpolation is added for the IPC controller +- A wind speed based soft cut-in using a sigma interpolation is added for the IPC controller Pitch Actuator -- A first or second order filter can be used to model a pitch actuator +- A first or second order filter can be used to model a pitch actuator External Control Interface -- Call another control library from ROSCO +- Call another control library from ROSCO ZeroMQ Interface -- Communicate with an external routine via ZeroMQ. Only yaw control currently supported +- Communicate with an external routine via ZeroMQ. Only yaw control currently supported Updated yaw control -- Filter wind direction with deadband, and yaw until direction error changes signs (https://iopscience.iop.org/article/10.1088/1742-6596/1037/3/032011) +- Filter wind direction with deadband, and yaw until direction error changes signs (https://iopscience.iop.org/article/10.1088/1742-6596/1037/3/032011) ====== ================= ====================================================================================================================================================================================================== New in ROSCO 2.6.0 @@ -141,18 +237,18 @@ Line Input Name Example Value ROSCO v2.4.1 to ROSCO v2.5.0 ------------------------------- Two filter parameters were added to -- change the high pass filter in the floating feedback module -- change the low pass filter of the wind speed estimator signal that is used in torque control +- change the high pass filter in the floating feedback module +- change the low pass filter of the wind speed estimator signal that is used in torque control Open loop control inputs, users must specify: -- The open loop input filename, an example can be found in Examples/Example_OL_Input.dat -- Indices (columns) of values specified in OL_Filename +- The open loop input filename, an example can be found in Examples/Example_OL_Input.dat +- Indices (columns) of values specified in OL_Filename IPC -- Proportional Control capabilities were added, 1P and 2P gains should be specified +- Proportional Control capabilities were added, 1P and 2P gains should be specified ====== ================= ====================================================================================================================================================================================================== -Line Flag Name Example Value +Line Input Name Example Value ====== ================= ====================================================================================================================================================================================================== 20 OL_Mode 0 ! OL_Mode - Open loop control mode {0: no open loop control, 1: open loop control vs. time, 2: open loop control vs. wind speed} 27 F_WECornerFreq 0.20944 ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s]. diff --git a/docs/source/examples.rst b/docs/source/examples.rst new file mode 100644 index 00000000..5302c1c0 --- /dev/null +++ b/docs/source/examples.rst @@ -0,0 +1,100 @@ + +.. toctree:: + +.. _examplepage: + +ROSCO Examples +============== +Methods for reading turbine models, generating the control parameters of a :code:`DISCON.IN`: file, and running aeroelastic simulations to test controllers +Reading Turbine Models +---------------------- +Control parameters depend on the turbine model. +The rosco.toolbox uses OpenFAST inputs and an additional :code:`.yaml` formatted file to set up a :code:`turbine` object in python. +Several OpenFAST inputs are located in `Test_Cases/ `_. +The controller tuning :code:`.yaml` are located in `Tune_Cases/ `_. +A detailed description of the ROSCO control inputs and tuning :code:`.yaml` are provided in :ref:`discon_in` and :ref:`rt_tuning_yaml`, respectively. + +* :code:`01_turbine_model.py` loads an OpenFAST turbine model and displays a summary of its information + +ROSCO requires the power and thrust coefficients for tuning control inputs and running the extended Kalman filter wind speed estimator. + +* :code:`02_ccblade.py` runs cc-blade, a blade element momentum solver from WISDEM, to generate a :math:`C_p` surface. + +The :code:`Cp_Cq_Ct.txt` (or similar) file contains the rotor performance tables that are necessary to run the ROSCO controller. +This file can be located wherever you desire, just be sure to point to it properly with the :code:`PerfFileName` parameter in :code:`DISCON.IN`. + + +Tuning Controllers and Generating DISCON.IN +------------------------------------------- +The ROSCO :code:`turbine` object, which contains turbine information required for controller tuning, along with control parameters in the tuning yaml and the :math:`C_p` surface are used to generate control parameters and :code:`DISCON.IN` files. +To tune the PI gains of the torque control, set :code:`omega_vs` and :code:`zeta_vs` in the yaml. +Similarly, set :code:`omega_pc` and :code:`zeta_pc` to tune the PI pitch controller; gain scheduling is automatically handled using turbine information. +Generally :code:`omega_*` increases the responsiveness of the controller, reducing generator speed variations, but an also increases loading on the turbine. +:code:`zeta_*` changes the damping of the controller and is generally less important of a tuning parameter, but could also help with loading. +The default parameters in `Tune_Cases/ `_ are known to work well with the turbines in this repository. + +* :code:`03_tune_controller.py` loads a turbine and tunes the PI control gains +* :code:`04_simple_sim.py` tunes a controller and runs a simple simualtion (not using OpenFAST) +* :code:`05_openfast_sim.py` loads a turbine, tunes a controller, and runs an OpenFAST simulation + +Each of these examples generates a :code:`DISCON.IN` file, which is an input to libdiscon.*. +When running the controller in OpenFAST, :code:`DISCON.IN` must be appropriately named using the :code:`DLL_FileName` parameter in ServoDyn. + +OpenFAST can be installed from `source `_ or in a conda environment using: + +.. code-block:: bash + + conda install -c conda-forge openfast + +ROSCO can implement peak shaving (or thrust clipping) by changing the minimum pitch angle based on the estimated wind speed: + +* :code:`06_peak_shaving.py` loads a turbine and tunes a controller with peak shaving. + +By setting the :code:`ps_percent` value in the tuning yaml, the minimum pitch versus wind speed table changes and is updated in the :code:`DISCON.IN` file. + +ROSCO also contains a method for distributed aerodynamic control (e.g., via trailing edge flaps): + +* :code:`09_distributed_aero.py` tunes a controller for distributed aerodynamic control + +The ROSCO toolbox also contains methods for working with OpenFAST linear models +* :code:`10_linear_params.py` exports a file of the parameters used for the simplified linear models used to tune ROSCO +* :code:`11_robust_tuning.py` shows how linear models generated using OpenFAST can be used to tune controllers with robust stability properties. +* :code:`12_tune_ipc.py` shows the tuning procedure for IPC + +Running OpenFAST Simulations +---------------------------- + +To run an aeroelastic simulation with ROSCO, the ROSCO input (:code:`DISCON.IN`) must point to a properly formatted :code:`Cp_Cq_Ct.txt` file using the :code:`PerfFileName` parameter. +If called from OpenFAST, the main OpenFAST input points to the ServoDyn input, which points to the :code:`DISCON.IN` file and the :code:`libdiscon.*` dynamic library. + +For example in `Test_Cases/NREL-5MW`: + +* :code:`NREL-5MW.fst` has :code:`"NRELOffshrBsline5MW_Onshore_ServoDyn.dat"` as the :code:`ServoFile` input +* :code:`NRELOffshrBsline5MW_Onshore_ServoDyn.dat` has :code:`"../../ROSCO/build/libdiscon.dylib"` as the :code:`DLL_FileName` input and :code:`"DISCON.IN"` as the :code:`DLL_InFile` input. + Note that these file paths are relative to the path of the main fast input (:code:`NREL-5MW.fst`) +* :code:`DISCON.IN` has :code:`"Cp_Ct_Cq.NREL5MW.txt"` as the :code:`PerfFileName` input + +The rosco.toolbox has methods for running OpenFAST (and other) binary executables using system calls, as well as post-processing tools in `ofTools/ `_. + +Several example scripts are set up to quickly simulate ROSCO with OpenFAST: + +* :code:`05_openfast_sim.py` loads a turbine, tunes a controller, and runs an OpenFAST simulation +* :code:`07_openfast_outputs.py` loads the OpenFAST output files and plots the results +* :code:`08_run_turbsim.py` runs TurbSim, for generating turbulent wind inputs +* :code:`14_open_loop_control.py` runs an OpenFAST simulation with ROSCO providing open loop control inputs + + +Testing ROSCO +------------- + +The rosco.toolbox also contains tools for testing ROSCO in IEC design load cases (DLCs), located in `ROSCO_testing/ `_. +The script :code:`run_Testing.py` allows the user to set up their own set of tests. +By setting :code:`testtype`, the user can run a variety of tests: + +* :code:`lite`, which runs DLC 1.1 simulations at 5 wind speed from cut-in to cut-out, in 330 second simulations +* :code:`heavy`, which runs DLC 1.3 from cut-in to cut-out in 2 m/s steps and 2 seeds for each, in 630 seconds, as well as DLC 1.4 simulations +* :code:`binary-comp`, where the user can compare :code:`libdiscon.*` dynamic libraries (compiled ROSCO source code), with either a lite or heavy set of simulations +* :code:`discon-comp`, where the user can compare :code:`DISCON.IN` controller tunings (and the complied ROSCO source is constant) + +Setting the :code:`turbine2test` allows the user to test either the IEA-15MW with the UMaine floating semisubmersible or the NREL-5MW reference onshore turbine. + diff --git a/docs/source/figures/ROSCOFramework.svg b/docs/source/figures/ROSCOFramework.svg new file mode 100644 index 00000000..9ef35b0c --- /dev/null +++ b/docs/source/figures/ROSCOFramework.svg @@ -0,0 +1,4 @@ + + + +
Tuning.yaml
Tuning.yaml
ROSCO
Toolbox
ROSCO...
OpenFAST
Model
OpenFAST...
DISCON.IN
DISCON.IN
ROSCO
Controller
ROSCO...
OpenFAST
OpenFASTText is not SVG - cannot display \ No newline at end of file diff --git a/docs/source/figures/ROSCO_toolbox.svg b/docs/source/figures/ROSCO_toolbox.svg index 8bbc5587..2ba1daf5 100644 --- a/docs/source/figures/ROSCO_toolbox.svg +++ b/docs/source/figures/ROSCO_toolbox.svg @@ -1,13 +1,5 @@ image/svg+xmlROSCOControllerROSCO`_. +If any example fails, this information is passed on to GitHub and a red X will be shown next to the commit. +Otherwise, if all tests pass, a green check mark appears to signify the code changes are valid. + +The examples that are covered are shown in :code:`ROSCO/rosco/test/test_examples.py`. +If you add an example to ROSCO, make sure to add a call to it in the :code:`run_examples.py` script as well. + + +Pull requests +------------- +Once you have added or modified code, submit a pull request via the GitHub interface. +This will automatically go through all of the tests in the repo to make sure everything is functioning properly. +The main developers of ROSCO will then merge in the request or provide feedback on how to improve the contribution. + diff --git a/docs/source/install.rst b/docs/source/install.rst index ecd12be2..40734441 100644 --- a/docs/source/install.rst +++ b/docs/source/install.rst @@ -2,11 +2,44 @@ .. _install: -Installing the ROSCO tools -=========================== -As a reminder, the ROSCO toolbox is a python-based tool used to write the DISCON.IN file, which is read by the ROSCO controller (a compiled binary file). If you only wish to run the controller, you *do not* need to install the ROSCO toolbox. +Installing ROSCO toolset +======================== +ROSCO toolsets can be utilized either to run an existing controller or to design and tune a controller from scratch. +We recommend using the instructions provided in the :ref:`full_rosco` to install the full ROSCO toolset. +This allows for full use of the provided functionalities including the controller and toolbox to facilitate controller tuning. +However, if only the ROSCO binary is needed (to run an existing controller, for example), then users should follow the instructions provided in :ref:`rosco_controller` -Depending on what is needed, a user can choose to use just the ROSCO controller or to use both the ROSCO controller and the toolbox. Both the controller and the toolbox should be installed if one wishes to leverage the full ROSCO tool-chain. :numref:`rosco_table` provides an overview of the primary methods available for :ref:`rosco_controller`. Additionally, :numref:`roscotoolbox_table` provides an overview of the primary methods available to acquire the ROSCO toolbox. Finally, if you wish to install and use both the controller and toolbox, the section about :ref:`full_rosco` provides the best methods of doing so. +.. _full_rosco: + +Complete ROSCO Installation +--------------------------- +Steps for the installation of the complete rosco toolset are: + +1. Create a conda environment for ROSCO + +.. code-block:: bash + + conda config --add channels conda-forge # (Enable Conda-forge Channel For Conda Package Manager) + conda create -y --name rosco-env python=3.10 # (Create a new environment named "rosco-env" that contains Python 3.8) + conda activate rosco-env # (Activate your "rosco-env" environment) + +2. Clone and Install the ROSCO toolbox with ROSCO controller + +.. code-block:: bash + + git clone https://github.com/NREL/ROSCO.git + cd ROSCO + pip install -e . + +This step creates the rosco controller binary (:code:`libdiscon.so` (Linux), :code:`libdiscon.dylib` (Mac), or :code:`libdisscon.dll` (Windows)`) in the directory :code:`ROSCO/rosco/lib` and installs the python toolbox in the conda environment in the develop mode. + + + +.. _rosco_controller: + +Installing only the ROSCO controller +------------------------------------ +:numref:`rosco_table` provides an overview of the primary methods available for installing only the ROSCO controller binary. .. _rosco_table: .. list-table:: Methods for Installing the ROSCO Controller @@ -16,34 +49,18 @@ Depending on what is needed, a user can choose to use just the ROSCO controller * - Method - Use Case * - :ref:`rosco_direct_download` - - Best for users who simply want to use a released version of the controller without working through the compilation procedures. + - Best for users who simply want to use a released version of the controller binary without working through the compilation procedures. * - :ref:`rosco_anaconda_download` - - Best for users who just want to use the controller but prefer to download using the Anaconda package man age Full ROSCO Installation. - * - :ref:`full_rosco` - - Best for users who wish to both use the controller and leverage the tools in the ROSCO toolbox + - Best for users who just want to use the controller binary but prefer to download using the Anaconda package manager. * - :ref:`cmake_compile` - - Best for users who need to re-compile the source code often, plan to use non-released versions of ROSCO (including modified source code), or who simply want to compile the controller themselves so they have the full code available locally. This is necessary for users who wish to use the :ref:`zmq_build`. - -.. _roscotoolbox_table: -.. list-table:: Methods for Installing the ROSCO Toolbox - :widths: 30 70 - :header-rows: 1 - - * - Method - - Use Case - * - :ref:`roscotoolbox_anaconda_download` - - Best for users who simply want to use the primary ROSCO toolbox functions - * - :ref:`full_rosco` - - (Recommended) Best for users who wish to both use the primary ROSCO toolbox functions, as well run and use the many example and testing scripts available. This process can be done with or without compiling ROSCO. - -For many of the methods used to install both ROSCO and the ROSCO toolbox, both Anaconda_ and CMake_ are necessary. Anaconda is a popular package manager used to distribute software packages of various types. Anaconda is used to download requisite packages and distribute pre-compiled versions of the ROSCO tools. CMake is a build configuration system that creates files as input to a build tool like GNU Make, Visual Studio, or Ninja. CMake does not compile code or run compilers directly, but rather creates the environment needed for another tool to run compilers and create binaries. CMake is used to ease the processes of compiling the ROSCO controller locally. For more information on CMake, please see `understanding CMake `_ in the OpenFAST documentation. + - Best for users who need to re-compile the source code often, plan to use non-released versions of ROSCO (including modified source code), or who simply want to compile the controller themselves so they have the full code available locally. - -.. _rosco_controller: - -Installing the ROSCO controller --------------------------------- -The standard ROSCO controller is based in Fortran and must be compiled; the source code can be found at: https://github.com/NREL/ROSCO/ROSCO. +Anaconda is a popular package manager used to distribute software packages of various types. +Anaconda is used to download requisite packages and distribute pre-compiled versions of the ROSCO tools. +CMake is a build configuration system that creates files as input to a build tool like GNU Make, Visual Studio, or Ninja. +CMake does not compile code or run compilers directly, but rather creates the environment needed for another tool to run compilers and create binaries. +CMake is used to ease the processes of compiling the ROSCO controller locally. +For more information on CMake, please see `understanding CMake `_ in the OpenFAST documentation. .. _rosco_direct_download: @@ -53,15 +70,15 @@ The most recent tagged version releases of the controller are `available for dow .. _rosco_anaconda_download: -Anaconda Download - ROSCO -.......................... +Anaconda Download +................. Using the popular package manager, Anaconda_, the tagged 64-bit versions of ROSCO are available through the conda-forge channel. In order to download the most recently compiled version release, from an anaconda powershell (Windows) or terminal (Mac/Linux) window, create a new anaconda virtual environment: .. code-block:: bash conda config --add channels conda-forge - conda create -y --name rosco-env python=3.8 + conda create -y --name rosco-env python=3.10 conda activate rosco-env navigate to your desired folder to save the compiled binary using: @@ -114,108 +131,16 @@ Once the CMake and the required compilers are downloaded, the following code can git clone https://github.com/NREL/ROSCO.git # Compile ROSCO - cd ROSCO/ROSCO + cd ROSCO/rosco/controller mkdir build cd build cmake .. # Mac/linux only cmake .. -G "MinGW Makefiles" # Windows only make install -This will generate a file called :code:`libdiscon.so` (Linux), :code:`libdiscon.dylib` (Mac), or :code:`libdisscon.dll` (Windows) in the :code:`/ROSCO/install/lib` directory. - -.. _zmq_build: - -ZeroMQ Interface -..................... -There is an option to interface ROSCO with external inputs using `ZeroMQ `_. Currently, only externally commanded yaw offset inputs are supported, though this could easily be expanded if the need arises. - -To use the ZeroMQ interface, the software must be downloaded following the `ZeroMQ download instructions `_. Using CMake, ROSCO can then be compiled to enable this interface by using the :code:`ZMQ_CLIENT:ON` flag with the :code:`cmake` command in :ref:`cmake_compile`: - -.. code-block:: bash - - cmake -DZMQ_CLIENT:ON .. - -.. _rosco_toolbox_install: - -Installing the ROSCO toolbox ----------------------------- -The ROSCO toolbox is based in python and contains all relevant ROSCO tools; the source code can be found at: https://github.com/NREL/ROSCO/. In addition to tuning procedures, the ROSCO toolbox also contains example scripts, a Simulink Model of ROSCO, OpenFAST pre-and post-processing functions, linearized systems analysis tools, and a testing suite. - -.. _roscotoolbox_anaconda_download: - -Anaconda Download - ROSCO Toolbox -.................................. -If one wishes to simply use the modules provided in the ROSCO toolbox through scripts of their own, the ROSCO toolbox can be installed via the conda-forge channel of Anaconda. They can then be accessed using the standard methods of loading modules in python, e.g: - -.. code-block:: python - - from ROSCO_toolbox import controller as ROSCO_controller - from ROSCO_toolbox import turbine as ROSCO_turbine - -Note that the install procedures for the ROSCO toolbox are the same as in :ref:`rosco_anaconda_download`, but do not involve moving the controller binary file. -In order to download the most recently compiled version release, from an anaconda powershell (Windows) or terminal (Mac/Linux) window, create a new anaconda virtual environment: - -.. code-block:: bash - - conda config --add channels conda-forge - conda create -y --name rosco-env python=3.8 - conda activate rosco-env - -navigate to your desired folder to save the compiled binary using: - -.. code-block:: bash - - cd - -and download the controller: - -.. code-block:: bash - - conda install -y ROSCO - - - -.. _full_rosco: - -Full ROSCO Installation ------------------------ - -We recommend using the full ROSCO tool-chain. This allows for full use of the provided functions along with the developed python packages and controller code, - -Please follow the following steps to install the ROSCO tool-chain. You should do step 2 *or* 3. If you simply want to install the ROSCO toolbox without the controller, do step 3. If you would like to install the ROSCO toolbox and compile the controller simultaneously, do step 2. - -1. Create a conda environment for ROSCO - -.. code-block:: bash - - conda config --add channels conda-forge # (Enable Conda-forge Channel For Conda Package Manager) - conda create -y --name rosco-env python=3.8 # (Create a new environment named "rosco-env" that contains Python 3.8) - conda activate rosco-env # (Activate your "rosco-env" environment) - -2. Clone and Install the ROSCO toolbox with ROSCO controller - -.. code-block:: bash - - git clone https://github.com/NREL/ROSCO.git - cd ROSCO - conda install compilers # (Mac/Linux only) - conda install m2w64-toolchain libpython # (Windows only) - conda env config vars set FC=gfortran # Sometimes needed for Windows - conda install -y wisdem=3.5.0 - python setup.py install --compile-rosco - -3. Clone and Install the ROSCO toolbox without ROSCO controller - -.. code-block:: bash - - git clone https://github.com/NREL/ROSCO.git - cd ROSCO - python setup.py install +This will generate a file called :code:`libdiscon.so` (Linux), :code:`libdiscon.dylib` (Mac), or :code:`libdisscon.dll` (Windows). -Getting Started ----------------- -Please see :ref:`standard_use` for several example scripts using ROSCO and the ROSCO_toolbox. .. _Anaconda: https://www.anaconda.com/ diff --git a/docs/source/rosco.rst b/docs/source/rosco.rst index cb6e75a9..167e7fff 100644 --- a/docs/source/rosco.rst +++ b/docs/source/rosco.rst @@ -2,8 +2,8 @@ .. _rosco: -ROSCO Controller Structure -========================== +ROSCO Structure: Controller +=========================== Here, we give an overview of the structure of the ROSCO controller and how the code is implemented. ----- @@ -14,12 +14,15 @@ The primary functions of the ROSCO toolbox are separated into several files. The * :code:`DISCON.f90` is the primary driver function. * :code:`ReadSetParameters.f90` primarily handles file I/O and the Bladed Interface. -* :code:`ROSCO_Types.f90` allocates variables in memory. +* :code:`ROSCO_Types.f90` allocates variables in memory; it is procedurally generated from :code:`rosco_registry` * :code:`Constants.f90` establishes some global constants. * :code:`Controllers.f90` contains the primary controller algorithms (e.g. blade pitch control) * :code:`ControllerBlocks.f90` contains additional control features that are not necessarily primary controllers (e.g. wind speed estimator) * :code:`Filters.f90` contains the various filter implementations. * :code:`Functions.f90` contains various functions used in the controller. +* :code:`ExtControl.f90` contains subroutines for calling external dynamic libraries +* :code:`ROSCO_Helpers.f90` contains subroutines for file I/O and other helpful routines, borrowed heavily from NWTC.IO in OpenFAST +* :code:`ROSCO_IO.f90` is procedurally generated using the :code:`rosco_registry` for writing debug and checkpoint files .. _discon_in: diff --git a/docs/source/rosco_toolbox.rst b/docs/source/rosco_toolbox.rst index a61b3131..637c0f8f 100644 --- a/docs/source/rosco_toolbox.rst +++ b/docs/source/rosco_toolbox.rst @@ -2,7 +2,7 @@ .. _rosco_toolbox_main: -ROSCO Toolbox Structure +ROSCO Structure: Toolbox ======================== Here, we give an overview of the structure of the ROSCO toolbox and how the code is implemented. @@ -25,28 +25,30 @@ The source code for the ROSCO toolbox generic tuning implementations lives here. Examples ......... -A number of examples are included to showcase the numerous capabilities of the ROSCO toolbox; they are described in the :ref:`standard_use`. - -Matlab_Toolbox -............... -A simulink implementation of the ROSCO controller is included in the Matlab Toolbox. Some requisite MATLAB utility scripts are also included. +A number of examples are included to showcase the numerous capabilities of the ROSCO toolbox; they are described in the :ref:`examplepage`. ROSCO_testing ............. Testing scripts for the ROSCO toolbox are held here and showcased with :code:`run_testing.py`. These can be used to compare different controller tunings or different controllers all together. -Test_Cases -.......... +Examples/Test_Cases +................... Example OpenFAST models consistent with the latest release of OpenFAST are provided here for simple testing and simulation cases. -Tune_Cases -.......... +Examples/Tune_Cases +................... Some example tuning scripts and tuning input files are provided here. The code found in :code:`tune_ROSCO.py` can be modified by the user to easily enable tuning of their own wind turbine model. The ROSCO Toolbox Tuning File ------------------------------ A yaml_ formatted input file is used for the standard ROSCO toolbox tuning process. This file contains the necessary inputs for the ROSCO toolbox to load an OpenFAST input file deck and tune the ROSCO controller. It can be found here: :ref:`rt_tuning_yaml`. - + +Matlab_Toolbox +............... +A simulink implementation of the ROSCO controller is included in the Matlab Toolbox. Some requisite MATLAB utility scripts are also included. +These scripts are not maintained by NREL as of ROSCO v2.5.0. +The Simulink controller there should not be used and referenenced as "ROSCO" because it has never been validated against the official ROSCO dynamic library and has drifted away from the official implementation. +We will leave the implementation in place to be used only as a learning tool. .. _OpenFAST: https://github.com/openfast/openfast .. _yaml: https://yaml.org/ diff --git a/docs/source/standard_use.rst b/docs/source/standard_use.rst index a23310dc..08cc8caa 100644 --- a/docs/source/standard_use.rst +++ b/docs/source/standard_use.rst @@ -4,99 +4,30 @@ Standard ROSCO Workflow ======================= -This page outlines methods for reading turbine models, generating the control parameters of a :code:`DISCON.IN`: file, and running aeroelastic simulations to test controllers. -A set of `example scripts `_ demonstrate the functionality of the ROSCO toolbox and controller. -Reading Turbine Models ----------------------- -Control parameters depend on the turbine model. -The ROSCO_toolbox uses OpenFAST inputs and an additional :code:`.yaml` formatted file to set up a :code:`turbine` object in python. -Several OpenFAST inputs are located in `Test_Cases/ `_. -The controller tuning :code:`.yaml` are located in `Tune_Cases/ `_. -A detailed description of the ROSCO control inputs and tuning :code:`.yaml` are provided in :ref:`discon_in` and :ref:`rt_tuning_yaml`, respectively. +.. _fig-RT: +.. figure:: /source/figures/ROSCOFramework.svg + :align: center + :width: 90% -* :code:`01_turbine_model.py` loads an OpenFAST turbine model and displays a summary of its information + ROSCO toolchain general workflow -ROSCO requires the power and thrust coefficients for tuning control inputs and running the extended Kalman filter wind speed estimator. +:numref:`fig-RT` shows the general workflow for the ROSCO tool-chain with OpenFAST. +For the standard use case in OpenFAST (or similar), ROSCO controller needs to be compiled. +The controller is a fortran based module that follows the bladed-style control interface. +Compiling the controller ouputs a dynamic-link library (or equivalent) called :code:`libdiscon.dll` for windows, :code:`libdiscon.so` for linux and, :code:`libdiscon.dylib` for mac-os. +Instructions for the compilation are provided in :ref:`install`. +Once the controller is compiled the turbine simulation tool must point to the compiled library. +In OpenFAST, this is ensured by changing the :code:`DLL_FileName` parameter in the ServoDyn input file. +This step enables communication between the ROSCO controller and OpenFAST. -* :code:`02_ccblade.py` runs cc-blade, a blade element momentum solver from WISDEM, to generate a :math:`C_p` surface. - -The :code:`Cp_Cq_Ct.txt` (or similar) file contains the rotor performance tables that are necessary to run the ROSCO controller. -This file can be located wherever you desire, just be sure to point to it properly with the :code:`PerfFileName` parameter in :code:`DISCON.IN`. - - -Tuning Controllers and Generating DISCON.IN -------------------------------------------- -The ROSCO :code:`turbine` object, which contains turbine information required for controller tuning, along with control parameters in the tuning yaml and the :math:`C_p` surface are used to generate control parameters and :code:`DISCON.IN` files. -To tune the PI gains of the torque control, set :code:`omega_vs` and :code:`zeta_vs` in the yaml. -Similarly, set :code:`omega_pc` and :code:`zeta_pc` to tune the PI pitch controller; gain scheduling is automatically handled using turbine information. -Generally :code:`omega_*` increases the responsiveness of the controller, reducing generator speed variations, but an also increases loading on the turbine. -:code:`zeta_*` changes the damping of the controller and is generally less important of a tuning parameter, but could also help with loading. -The default parameters in `Tune_Cases/ `_ are known to work well with the turbines in this repository. - -* :code:`03_tune_controller.py` loads a turbine and tunes the PI control gains -* :code:`04_simple_sim.py` tunes a controller and runs a simple simualtion (not using OpenFAST) -* :code:`05_openfast_sim.py` loads a turbine, tunes a controller, and runs an OpenFAST simulation - -Each of these examples generates a :code:`DISCON.IN` file, which is an input to libdiscon.*. -When running the controller in OpenFAST, :code:`DISCON.IN` must be appropriately named using the :code:`DLL_FileName` parameter in ServoDyn. - -OpenFAST can be installed from `source `_ or in a conda environment using: - -.. code-block:: bash - - conda install -c conda-forge openfast - -ROSCO can implement peak shaving (or thrust clipping) by changing the minimum pitch angle based on the estimated wind speed: - -* :code:`06_peak_shaving.py` loads a turbine and tunes a controller with peak shaving. - -By setting the :code:`ps_percent` value in the tuning yaml, the minimum pitch versus wind speed table changes and is updated in the :code:`DISCON.IN` file. - -ROSCO also contains a method for distributed aerodynamic control (e.g., via trailing edge flaps): - -* :code:`09_distributed_aero.py` tunes a controller for distributed aerodynamic control - -The ROSCO toolbox also contains methods for working with OpenFAST linear models -* :code:`10_linear_params.py` exports a file of the parameters used for the simplified linear models used to tune ROSCO -* :code:`11_robust_tuning.py` shows how linear models generated using OpenFAST can be used to tune controllers with robust stability properties. -* :code:`12_tune_ipc.py` shows the tuning procedure for IPC - -Running OpenFAST Simulations ----------------------------- - -To run an aeroelastic simulation with ROSCO, the ROSCO input (:code:`DISCON.IN`) must point to a properly formatted :code:`Cp_Cq_Ct.txt` file using the :code:`PerfFileName` parameter. -If called from OpenFAST, the main OpenFAST input points to the ServoDyn input, which points to the :code:`DISCON.IN` file and the :code:`libdiscon.*` dynamic library. - -For example in `Test_Cases/NREL-5MW`: - -* :code:`NREL-5MW.fst` has :code:`"NRELOffshrBsline5MW_Onshore_ServoDyn.dat"` as the :code:`ServoFile` input -* :code:`NRELOffshrBsline5MW_Onshore_ServoDyn.dat` has :code:`"../../ROSCO/build/libdiscon.dylib"` as the :code:`DLL_FileName` input and :code:`"DISCON.IN"` as the :code:`DLL_InFile` input. - Note that these file paths are relative to the path of the main fast input (:code:`NREL-5MW.fst`) -* :code:`DISCON.IN` has :code:`"Cp_Ct_Cq.NREL5MW.txt"` as the :code:`PerfFileName` input - -The ROSCO_toolbox has methods for running OpenFAST (and other) binary executables using system calls, as well as post-processing tools in `ofTools/ `_. - -Several example scripts are set up to quickly simulate ROSCO with OpenFAST: - -* :code:`05_openfast_sim.py` loads a turbine, tunes a controller, and runs an OpenFAST simulation -* :code:`07_openfast_outputs.py` loads the OpenFAST output files and plots the results -* :code:`08_run_turbsim.py` runs TurbSim, for generating turbulent wind inputs -* :code:`14_open_loop_control.py` runs an OpenFAST simulation with ROSCO providing open loop control inputs - - -Testing ROSCO -------------- - -The ROSCO_toolbox also contains tools for testing ROSCO in IEC design load cases (DLCs), located in `ROSCO_testing/ `_. -The script :code:`run_Testing.py` allows the user to set up their own set of tests. -By setting :code:`testtype`, the user can run a variety of tests: - -* :code:`lite`, which runs DLC 1.1 simulations at 5 wind speed from cut-in to cut-out, in 330 second simulations -* :code:`heavy`, which runs DLC 1.3 from cut-in to cut-out in 2 m/s steps and 2 seeds for each, in 630 seconds, as well as DLC 1.4 simulations -* :code:`binary-comp`, where the user can compare :code:`libdiscon.*` dynamic libraries (compiled ROSCO source code), with either a lite or heavy set of simulations -* :code:`discon-comp`, where the user can compare :code:`DISCON.IN` controller tunings (and the complied ROSCO source is constant) - -Setting the :code:`turbine2test` allows the user to test either the IEA-15MW with the UMaine floating semisubmersible or the NREL-5MW reference onshore turbine. +The compiled ROSCO controller library requires an input file (generally called :code:`DISCON.IN`). +It stores several flags and parameters needed by the controller and is read by the compiled dynamic-link library. +Several different :code:`DISCON.IN` files, for varous turbines and controller tunings, can use the same dynamic-link library. +In OpenFAST, the :code:`DLL_InFile` parameter in the ServoDyn input file determines the desired input file. +The ROSCO toolbox is used to tune the ROSCO controller and generate a :code:`DISCON.IN` input file. +To tune the controller, ROSCO toolbox needs the OpenFAST model of the turbine and some user inputs in the form of a :code:`tuning.yaml` file. +The functionality of ROSCO toolset can be best understood by following the set of included example scripts in :ref:`examplepage`. +ROSCO toolset can be installed using the instructions provided in :ref:`install`. diff --git a/docs/source/toolbox_input.rst b/docs/source/toolbox_input.rst index 5b205c70..7aa7f007 100644 --- a/docs/source/toolbox_input.rst +++ b/docs/source/toolbox_input.rst @@ -22,11 +22,11 @@ path_params :code:`FAST_directory` : String Main OpenFAST model directory, where the `*.fst` lives, relative - to ROSCO dir (if applicable) + to directory of this yaml (if applicable) :code:`rotor_performance_filename` : String Filename for rotor performance text file (if it has been generated - by ccblade already) + by ccblade already), relative to directory of this yaml @@ -89,6 +89,14 @@ turbine_params *Minimum* = 0 +:code:`reynolds_ref` : Float + Reynolds number near rated speeds, used to interpolate airfoils, + if provided + + *Default* = 0 + + *Minimum* = 0 + controller_params @@ -136,15 +144,24 @@ controller_params :code:`VS_ControlMode` : Float - Generator torque control mode in above rated conditions (0- - constant torque, 1- constant power, 2- TSR tracking PI control - with constant torque, 3- TSR tracking with constant power) + Generator torque control mode in above rated conditions (0- no + torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR + Tracking, 3- Power-based TSR Tracking) *Default* = 2 *Minimum* = 0 *Maximum* = 3 +:code:`VS_ConstPower` : Float + Do constant power torque control, where above rated torque varies, + 0 for constant torque + + *Default* = 0 + + *Minimum* = 0 *Maximum* = 1 + + :code:`PC_ControlMode` : Float Blade pitch control mode (0- No pitch, fix to fine pitch, 1- active PI blade pitch control) @@ -210,6 +227,15 @@ controller_params *Minimum* = 0 *Maximum* = 1 +:code:`TRA_Mode` : Float + Tower resonance avoidance mode (0- no tower resonsnace avoidance, + 1- use torque control setpoints to avoid a specific frequency + + *Default* = 0 + + *Minimum* = 0 *Maximum* = 1 + + :code:`Fl_Mode` : Float Floating specific feedback mode (0- no nacelle velocity feedback, 1 - nacelle velocity feedback, 2 - nacelle pitching acceleration @@ -247,6 +273,13 @@ controller_params *Minimum* = 0 *Maximum* = 1 +:code:`ZMQ_UpdatePeriod` : Float + Call ZeroMQ every [x] seconds, [s] + + *Default* = 2 + + *Minimum* = 0 + :code:`PA_Mode` : Float Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} @@ -265,6 +298,24 @@ controller_params *Minimum* = 0 *Maximum* = 1 +:code:`OL_Mode` : Float + Open loop control mode {0- no open loop control, 1- open loop + control} + + *Default* = 0 + + *Minimum* = 0 *Maximum* = 2 + + +:code:`AWC_Mode` : Float + Active wake control mode {0 - not used, 1 - SNL method, 2 - NREL + method} + + *Default* = 0 + + *Minimum* = 0 *Maximum* = 2 + + :code:`Ext_Mode` : Float External control mode [0 - not used, 1 - call external dynamic library] @@ -275,20 +326,21 @@ controller_params :code:`CC_Mode` : Float - Cable control mode [0- unused, 1- User defined, 2- Position - control (not yet implemented)] + Cable control mode [0- unused, 1- User defined, 2- Open loop + control] *Default* = 0 - *Minimum* = 0 *Maximum* = 1 + *Minimum* = 0 *Maximum* = 2 :code:`StC_Mode` : Float - Structural control mode [0- unused, 1- User defined] + Structural control mode [0- unused, 1- User defined, 2- Open loop + control] *Default* = 0 - *Minimum* = 0 *Maximum* = 1 + *Minimum* = 0 *Maximum* = 2 :code:`U_pc` : Array of Floats @@ -396,14 +448,20 @@ controller_params *Minimum* = 0 -:code:`Kp_float` : Float, s - Gain of floating feedback control +:code:`Kp_float` : Float, s or Array of Floats + Gain(s) of floating feedback control :code:`tune_Fl` : Boolean Whether to automatically tune Kp_float *Default* = True +:code:`U_Fl` : Array of Floats or String or Float + List of wind speeds for tuning floating feedback, or "all" for all + above-rated wind speeds + + *Default* = [] + :code:`zeta_flp` : Float Flap controller desired damping ratio [-] @@ -466,6 +524,15 @@ controller_params *Minimum* = 0.0 +:code:`rgn2k_factor` : Float + Factor on VS_Rgn2K to increase/decrease optimal torque control + gain, default is 1. Sometimes environmental conditions or + differences in BEM solvers necessitate this change. + + *Default* = 1 + + *Minimum* = 0 + filter_params @@ -537,26 +604,49 @@ open_loop *Default* = unused -:code:`OL_Ind_Breakpoint` : Float +:code:`Ind_Breakpoint` : Float Index (column, 1-indexed) of breakpoint (time) in open loop index *Default* = 1 -:code:`OL_Ind_BldPitch` : Float - Index (column, 1-indexed) of breakpoint (time) in open loop index + *Minimum* = 0 + +:code:`Ind_BldPitch` : Array of Floats + Indices (columns, 1-indexed) of pitch (1,2,3) inputs in open loop + input + + *Default* = [0, 0, 0] + + *Minimum* = 0 + +:code:`Ind_GenTq` : Float + Index (column, 1-indexed) of generator torque in open loop input *Default* = 0 -:code:`OL_Ind_GenTq` : Float - Index (column, 1-indexed) of breakpoint (time) in open loop index + *Minimum* = 0 + +:code:`Ind_YawRate` : Float + Index (column, 1-indexed) of nacelle yaw in open loop input *Default* = 0 -:code:`OL_Ind_YawRate` : Float - Index (column, 1-indexed) of breakpoint (time) in open loop index + *Minimum* = 0 + +:code:`Ind_Azimuth` : Float + The column in OL_Filename that contains the desired azimuth + position in rad (used if OL_Mode = 2) *Default* = 0 +:code:`Ind_CableControl` : Array of Floats + The column in OL_Filename that contains the cable control inputs + in m + +:code:`Ind_StructControl` : Array of Floats + The column in OL_Filename that contains the structural control + inputs in various units + :code:`PA_CornerFreq` : Float, rad/s Pitch actuator natural frequency [rad/s] @@ -577,7 +667,7 @@ DISCON ######################################## -These are pass-through parameters for the DISCON.IN file. Use with caution. +These are pass-through parameters for the DISCON.IN file. Use with caution. Do not set defaults in schema. :code:`LoggingLevel` : Float (0- write no debug files, 1- write standard output .dbg-file, 2- @@ -589,10 +679,30 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. *Default* = 0 +:code:`DT_Out` : Float + Time step to output .dbg* files, or 0 to match sampling period of + OpenFAST + + *Default* = 0 + :code:`F_LPFType` : Float 1- first-order low-pass filter, 2- second-order low-pass filter (currently filters generator speed and pitch control signals +:code:`VS_ControlMode` : Float + Generator torque control mode in above rated conditions (0- no + torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR + Tracking, 3- Power-based TSR Tracking) + + *Minimum* = 0 *Maximum* = 3 + + +:code:`VS_ConstPower` : Float + Do constant power torque control, where above rated torque varies + + *Minimum* = 0 *Maximum* = 1 + + :code:`F_NotchType` : Float Notch on the measured generator speed and/or tower fore-aft motion (for floating) (0- disable, 1- generator speed, 2- tower-top fore- @@ -603,12 +713,6 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. (pitch contribution) (0- off, 1- 1P reductions, 2- 1P+2P reductions) -:code:`VS_ControlMode` : Float - Generator torque control mode in above rated conditions (0- - constant torque, 1- constant power, 2- TSR tracking PI control - with constant torque, 3- TSR tracking PI control with constant - power) - :code:`PC_ControlMode` : Float Blade pitch control mode (0- No pitch, fix to fine pitch, 1- active PI blade pitch control) @@ -643,18 +747,42 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. Flap control mode (0- no flap control, 1- steady state flap angle, 2- Proportional flap control) +:code:`OL_Mode` : Float + Open loop control mode (0 - no open-loop control, 1 - direct open + loop control, 2 - rotor position control) + :code:`F_LPFCornerFreq` : Float, rad/s Corner frequency (-3dB point) in the low-pass filters, :code:`F_LPFDamping` : Float Damping coefficient (used only when F_FilterType = 2 [-] -:code:`F_NotchCornerFreq` : Float, rad/s - Natural frequency of the notch filter, +:code:`F_NumNotchFilts` : Float + Number of notch filters placed on sensors + +:code:`F_NotchFreqs` : Array of Floats or Float, rad/s + Natural frequency of the notch filters. Array with length + F_NumNotchFilts + +:code:`F_NotchBetaNum` : Array of Floats or Float + Damping value of numerator (determines the width of notch). Array + with length F_NumNotchFilts, [-] + +:code:`F_NotchBetaDen` : Array of Floats or Float + Damping value of denominator (determines the depth of notch). + Array with length F_NumNotchFilts, [-] -:code:`F_NotchBetaNumDen` : Array of Floats - Two notch damping values (numerator and denominator, resp) - - determines the width and depth of the notch, [-] +:code:`F_GenSpdNotch_N` : Float + Number of notch filters on generator speed + +:code:`F_TwrTopNotch_N` : Float + Number of notch filters on tower top acceleration signal + +:code:`F_GenSpdNotch_Ind` : Array of Floats or Float + Indices of notch filters on generator speed + +:code:`F_TwrTopNotch_Ind` : Array of Floats or Float + Indices of notch filters on tower top acceleration signal :code:`F_SSCornerFreq` : Float, rad/s. Corner frequency (-3dB point) in the first order low pass filter @@ -759,7 +887,8 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. Minimum generator speed :code:`VS_Rgn2K` : Float, Nm/(rad/s)^2 - Generator torque constant in Region 2 (HSS side) + Generator torque constant in Region 2 (HSS side). Only used in + VS_ControlMode = 1,3 :code:`VS_RtPwr` : Float, W Wind turbine rated power @@ -782,7 +911,14 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. the transitional 2.5 region if VS_ControlMode =/ 2) :code:`VS_TSRopt` : Float, rad - Power-maximizing region 2 tip-speed-ratio + Power-maximizing region 2 tip-speed-ratio. Only used in + VS_ControlMode = 2. + +:code:`VS_PwrFiltF` : Float, rad + Low pass filter on power used to determine generator speed set + point. Only used in VS_ControlMode = 3. + + *Default* = 0.314 :code:`SS_VSGain` : Float Variable speed torque controller setpoint smoother gain @@ -790,6 +926,49 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. :code:`SS_PCGain` : Float Collective pitch controller setpoint smoother gain +:code:`PRC_Mode` : Float + Power reference tracking mode, 0- use standard rotor speed set + points, 1- use PRC rotor speed setpoints + +:code:`PRC_WindSpeeds` : Array of Floats + Array of wind speeds used in rotor speed vs. wind speed lookup + table [m/s] + +:code:`PRC_GenSpeeds` : Array of Floats + Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + +:code:`PRC_LPF_Freq` : Float + Frequency of the low pass filter on the wind speed estimate used + to set PRC_GenSpeeds [rad/s] + + *Default* = 0.078539 + +:code:`PRC_n` : Float + Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array + +:code:`TRA_ExclSpeed` : Float + Rotor speed for exclusion [LSS, rad/s] + + *Default* = 0.0 + + *Minimum* = 0 + +:code:`TRA_ExclBand` : Float + Size of the rotor frequency exclusion band [LSS, rad/s]. Torque + controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 + + *Default* = 0.0 + + *Minimum* = 0 + +:code:`TRA_RateLimit` : Float + Rate limit of change in rotor speed reference [LSS, rad/s]. + Suggested to be VS_RefSpd/400. + + *Default* = 0.0 + + *Minimum* = 0 + :code:`WE_BladeRadius` : Float, m Blade length (distance from hub center to blade tip) @@ -895,9 +1074,17 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. Cutoff Frequency for first order low-pass filter for blade pitch angle -:code:`Fl_Kp` : Float, s +:code:`Fl_n` : Float, s + Number of Fl_Kp gains in gain scheduling, optional with default of + 1 + +:code:`Fl_Kp` : Array of Floats Nacelle velocity proportional feedback gain +:code:`Fl_U` : Array of Floats + Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single + value [m/s] + :code:`Flp_Angle` : Float, rad Initial or steady state flap angle @@ -916,7 +1103,7 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. :code:`Ind_Breakpoint` : Float The column in OL_Filename that contains the breakpoint (time if - OL_Mode = 1) + OL_Mode > 0) :code:`Ind_BldPitch` : Float The column in OL_Filename that contains the blade pitch input in @@ -928,6 +1115,24 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. :code:`Ind_YawRate` : Float The column in OL_Filename that contains the generator torque in Nm +:code:`Ind_Azimuth` : Float + The column in OL_Filename that contains the desired azimuth + position in rad (used if OL_Mode = 2) + +:code:`RP_Gains` : Array of Floats + PID gains and Tf of derivative for rotor position control (used if + OL_Mode = 2) + + *Default* = [0, 0, 0, 0] + +:code:`Ind_CableControl` : Array of Floats + The column in OL_Filename that contains the cable control inputs + in m + +:code:`Ind_StructControl` : Array of Floats + The column in OL_Filename that contains the structural control + inputs in various units + :code:`DLL_FileName` : String Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format @@ -947,6 +1152,8 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. :code:`PF_Offsets` : Array of Floats Pitch angle offsets for each blade (array with length of 3) + *Default* = [0, 0, 0] + :code:`CC_Group_N` : Float Number of cable control groups @@ -973,6 +1180,63 @@ These are pass-through parameters for the DISCON.IN file. Use with caution. *Default* = [0] +:code:`AWC_Mode` : Float + Active wake control mode {0 - not used, 1 - complex number method, + 2 - Coleman transformation method} + + *Default* = 0 + + *Minimum* = 0 *Maximum* = 2 + + +:code:`AWC_NumModes` : Float, rad + Number of AWC modes + + *Default* = 1 + +:code:`AWC_n` : Array of Floats + AWC azimuthal number (only used in complex number method) + + *Default* = [1] + +:code:`AWC_harmonic` : Array of Integers + AWC Coleman transform harmonic (only used in Coleman transform + method) + + *Default* = [1] + +:code:`AWC_freq` : Array of Floats + AWC frequency [Hz] + + *Default* = [0.05] + +:code:`AWC_amp` : Array of Floats + AWC amplitude [deg] + + *Default* = [1.0] + +:code:`AWC_clockangle` : Array of Floats + AWC clock angle [deg] + + *Default* = [0] + +:code:`ZMQ_CommAddress` : String + Communication address for ZMQ server, (e.g. + "tcp://localhost:5555") + + *Default* = tcp://localhost:5555 + +:code:`ZMQ_UpdatePeriod` : Float + Update period at zmq interface to send measurements and wait for + setpoint [sec.] + + *Default* = 1.0 + +:code:`ZMQ_ID` : Float + Integer identifier of turbine + + *Default* = 0 + linmodel_tuning diff --git a/environment.yml b/environment.yml index d90d5165..fdec1ba3 100644 --- a/environment.yml +++ b/environment.yml @@ -3,16 +3,20 @@ channels: - defaults dependencies: + - cmake + - cmake-build-extension + - control + - make + - ninja - matplotlib - numpy - - pytest - - scipy - - pyYAML - pandas - - wisdem - - cmake - - pyparsing==2.4.7 - - control + - pyYAML + - pyparsing + - pytest - pyzmq - - mpi4py + - scipy - treon + - wisdem + - compilers + - sphinx_rtd_theme diff --git a/pyproject.toml b/pyproject.toml new file mode 100644 index 00000000..ce80267c --- /dev/null +++ b/pyproject.toml @@ -0,0 +1,139 @@ +[build-system] +requires = ["setuptools", "cmake", "numpy", "wheel", "pyzmq", "cmake-build-extension"] +build-backend = "setuptools.build_meta" + +[project] +name = "rosco" +version = "2.9.0" +description = "A reference open source controller toolset for wind turbine applications." +readme = "README.md" +requires-python = ">=3.9" +license = {text = "Apache-2.0"} +keywords = ["wind", "turbine", "control", "", ""] +authors = [ + {name = "National Wind Technology Center, NREL", email = "daniel.zalkind@nrel.gov" } +] +maintainers = [ + {name = "Daniel Zalkind", email = "daniel.zalkind@nrel.gov" } +] +classifiers = [ # Optional + # How mature is this project? Common values are + # 3 - Alpha + # 4 - Beta + # 5 - Production/Stable + "Development Status :: 4 - Beta", + + # Indicate who your project is intended for + "Intended Audience :: Science/Research", + "Topic :: Scientific/Engineering", + + "License :: OSI Approved :: Apache Software License", + + # Specify the Python versions you support here. In particular, ensure + # that you indicate you support Python 3. These classifiers are *not* + # checked by "pip install". See instead "python_requires" below. + "Programming Language :: Python :: 3", + "Programming Language :: Python :: 3.9", + "Programming Language :: Python :: 3.10", + "Programming Language :: Python :: 3.11", + "Programming Language :: Python :: 3 :: Only", + "Programming Language :: Fortran", +] + +dependencies = [ + "control", + "numpy", + "matplotlib", + "scipy", + "pandas", + "pyparsing", + "pyYAML", + "pyzmq", + "treon", + "wisdem", + "ruamel.yaml", +] + +# List additional groups of dependencies here (e.g. development +# dependencies). Users will be able to install these using the "extras" +# syntax, for example: +# +# $ pip install sampleproject[dev] +# +# Similar to `dependencies` above, these must be valid existing +# projects. +[project.optional-dependencies] # Optional +dev = ["cmake"] +test = ["pytest"] + +# List URLs that are relevant to your project +# +# This field corresponds to the "Project-URL" and "Home-Page" metadata fields: +# https://packaging.python.org/specifications/core-metadata/#project-url-multiple-use +# https://packaging.python.org/specifications/core-metadata/#home-page-optional +# +# Examples listed include a pattern for specifying where the package tracks +# issues, where the source is hosted, where to say thanks to the package +# maintainers, and where to support the project financially. The key is +# what's used to render the link text on PyPI. +[project.urls] # Optional +"Homepage" = "https://github.com/NREL/ROSCO" +"Documentation" = "https://rosco.readthedocs.io" + +# This is configuration specific to the `setuptools` build backend. +# If you are using a different build backend, you will need to change this. +[tool.setuptools] +zip-safe = false +include-package-data = true + +#[tool.setuptools.packages] +#find = {} + +[tool.setuptools.packages.find] +#where = ["rosco"] +exclude = ["Matlab_Toolbox"] +namespaces = true + +[tool.setuptools.package-data] +# If there are data files included in your packages that need to be +# installed, specify them here. +"*" = ["*.yaml", "*.xlsx", "*.txt", "*.so", "*.lib", "*.pyd", "*.pdb", "*.dylib", "*.dll", "*.exe"] + +[tool.black] +line-length = 120 +target-version = ['py311'] +include = '\.pyi?$' +exclude = ''' +/( + \.git + | \.hg + | \.mypy_cache + | \.tox + | \.venv + | _build + | buck-out + | build + | dist +)/ +''' + +[tool.isort] +# https://github.com/PyCQA/isort +multi_line_output = "3" +include_trailing_comma = true +force_grid_wrap = false +use_parentheses = true +line_length = "120" +sections = ["FUTURE", "STDLIB", "THIRDPARTY", "FIRSTPARTY", "LOCALFOLDER"] +known_first_party = ["wisdem"] +length_sort = "1" +profile = "black" +skip_glob = ['__init__.py'] +atomic = true +#lines_after_imports = 2 +#lines_between_types = 1 +#src_paths=isort,test + +[tool.cibuildwheel] +skip = ["cp36-*", "cp37-*", "cp38-*", "*-win32"] +build-frontend = "build" diff --git a/rosco/__init__.py b/rosco/__init__.py new file mode 100644 index 00000000..040a848d --- /dev/null +++ b/rosco/__init__.py @@ -0,0 +1,30 @@ +import platform +import os +import sysconfig + +if platform.system() == "Windows": + lib_ext = ".dll" +elif platform.system() == "Darwin": + lib_ext = ".dylib" +else: + lib_ext = ".so" + +rosco_dir = os.path.dirname( os.path.abspath(__file__) ) +libname = "libdiscon" + +lib_path = [os.path.join(rosco_dir, "lib", libname+lib_ext), # pip installs (regular and editable) + os.path.join(rosco_dir, "..", "..", "local", "lib", libname+lib_ext), # WEIS library + os.path.join(os.path.dirname( sysconfig.get_path('stdlib') ), libname+lib_ext), # conda installs + os.path.join( sysconfig.get_path('platlib'), "rosco", "lib", libname+lib_ext), # system-wide pip installs + os.path.join( sysconfig.get_config_var("userbase"), "lib", "python", "site-packages", "rosco", "lib", libname+lib_ext), # system wide local + ] + +discon_lib_path = None +for p in lib_path: + if os.path.exists(p): + discon_lib_path = str(p) + break + +if discon_lib_path is None: + raise Exception(f"Cannot find {libname+lib_ext} in {lib_path}") + diff --git a/ROSCO/CMakeLists.txt b/rosco/controller/CMakeLists.txt similarity index 87% rename from ROSCO/CMakeLists.txt rename to rosco/controller/CMakeLists.txt index b450a30f..0d290851 100644 --- a/ROSCO/CMakeLists.txt +++ b/rosco/controller/CMakeLists.txt @@ -1,5 +1,5 @@ cmake_minimum_required(VERSION 3.6) -project(ROSCO VERSION 2.8.0 LANGUAGES Fortran C) +project(ROSCO VERSION 2.9.0 LANGUAGES Fortran C) set(CMAKE_Fortran_MODULE_DIRECTORY "${CMAKE_BINARY_DIR}/ftnmods") @@ -26,13 +26,6 @@ set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -libs:static -free -static -fpp endif() endif() -# Enable ZMQ_Client if compiler flag is set -option(ZMQ_CLIENT "Enable use of ZeroMQ client" off) -if(ZMQ_Client) - set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -lzmq") -endif() - - set(SOURCES src/Constants.f90 src/ControllerBlocks.f90 @@ -69,11 +62,11 @@ else (NWTC_SYS_FILE) message(FATAL_ERROR "Cannot determine system file used with NWTC_Library") endif (NWTC_SYS_FILE) -# Library -if(ZMQ_CLIENT) +# ZMQ Library +find_package(PkgConfig) +pkg_check_modules(PC_ZeroMQ libzmq) +if(PC_ZeroMQ_FOUND) # Find ZeroMQ installation - find_package(PkgConfig) - pkg_check_modules(PC_ZeroMQ libzmq) find_path(ZeroMQ_INCLUDE_DIR NAMES zmq.h PATHS ${PC_ZeroMQ_INCLUDE_DIRS} @@ -84,20 +77,21 @@ if(ZMQ_CLIENT) ) include_directories(${ZeroMQ_INCLUDE_DIR}) + set(CMAKE_Fortran_FLAGS "${CMAKE_Fortran_FLAGS} -L${PC_ZeroMQ_LIBRARY_DIRS} -lzmq") # Compile C-based ZeroMQ client as object library add_compile_options(-I${ZeroMQ_INCLUDE_DIR} -l${ZeroMQ_LIBRARY} -fPIC) - add_library(zmq_client OBJECT ../src/zmq_client.c) + add_library(zmq_client OBJECT src/zmq_client.c) # Add definition add_definitions(-DZMQ_CLIENT="TRUE") - set(SOURCES ${SOURCES} + set(SOURCES ${SOURCES} $) endif() add_library(discon SHARED ${SOURCES}) -if(ZMQ_CLIENT) +if(PC_ZeroMQ_FOUND) target_include_directories(discon PUBLIC ${ZeroMQ_INCLUDE_DIR}) target_link_libraries(discon PUBLIC ${ZeroMQ_LIBRARY}) endif() @@ -114,5 +108,5 @@ set(linuxDefault ${CMAKE_INSTALL_PREFIX} STREQUAL "/usr/local") set(windowsDefault ${CMAKE_INSTALL_PREFIX} STREQUAL "C:\\Program Files (x86)") if(${linuxDefault} OR ${windowsDefault}) message("TRUE") - set(CMAKE_INSTALL_PREFIX "${CMAKE_SOURCE_DIR}/install") -endif() \ No newline at end of file + set(CMAKE_INSTALL_PREFIX "${CMAKE_SOURCE_DIR}/../../") +endif() diff --git a/ROSCO/rosco_registry/__init__.py b/rosco/controller/__init__.py similarity index 100% rename from ROSCO/rosco_registry/__init__.py rename to rosco/controller/__init__.py diff --git a/ROSCO_toolbox/inputs/__init__.py b/rosco/controller/rosco_registry/__init__.py similarity index 100% rename from ROSCO_toolbox/inputs/__init__.py rename to rosco/controller/rosco_registry/__init__.py diff --git a/ROSCO/rosco_registry/rosco_types.yaml b/rosco/controller/rosco_registry/rosco_types.yaml similarity index 85% rename from ROSCO/rosco_registry/rosco_types.yaml rename to rosco/controller/rosco_registry/rosco_types.yaml index 759c9d0a..6f888f81 100644 --- a/ROSCO/rosco_registry/rosco_types.yaml +++ b/rosco/controller/rosco_registry/rosco_types.yaml @@ -1,7 +1,8 @@ default_types: integer: &integer type: integer - description: + description: + dimension: allocatable: False equals: size: 0 @@ -73,31 +74,69 @@ default_types: ControlParameters: + ZMQ_ID: + <<: *integer + description: 0000 - 9999, Identifier of the rosco, used for zeromq interface only LoggingLevel: <<: *integer description: 0 - write no debug files, 1 - write standard output .dbg-file, 2 - write standard output .dbg-file and complete avrSWAP-array .dbg2-file Echo: <<: *integer description: 0 - no Echo, 1 - Echo input data to .echo + Ext_Interface: + <<: *integer + description: 0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0. + + DT_Out: + <<: *real + description: Output time step + + n_DT_Out: + <<: *integer + description: output every this many steps + + n_DT_ZMQ: + <<: *integer + description: Send measurements to ZMQ after this many time steps + # Filters F_LPFType: <<: *integer description: 'Low pass filter on the rotor and generator speed {1 - first-order low-pass filter, 2 - second-order low-pass filter}, [rad/s]' - F_NotchType: - <<: *integer - description: Notch on the measured generator speed {0 - disable, 1 - enable} F_LPFCornerFreq: <<: *real description: Corner frequency (-3dB point) in the first-order low-pass filter, [rad/s] F_LPFDamping: <<: *real description: Damping coefficient [used only when F_FilterType = 2] - F_NotchCornerFreq: + F_NumNotchFilts: + <<: *integer + description: Number of notch filters + F_GenSpdNotch_N: + <<: *integer + description: Number of gen speed notch filters + F_GenSpdNotch_Ind: + <<: *integer + description: Indices of gen speed notch filters + allocatable: True + F_TwrTopNotch_N: + <<: *integer + description: Number of tower top notch filters + F_TwrTopNotch_Ind: + <<: *integer + description: Indices of tower top notch filters + allocatable: True + F_NotchFreqs: <<: *real - description: Natural frequency of the notch filter, [rad/s] - F_NotchBetaNumDen: + description: Natural frequencies of notch filters, [rad/s] + allocatable: True + F_NotchBetaNum: + <<: *real + description: Notch Filter Numerator damping (determines width) + allocatable: True + F_NotchBetaDen: <<: *real - description: These two notch damping values (numerator and denominator) determines the width and depth of the notch + description: Notch Filter Numerator damping (determines depth?) allocatable: True F_SSCornerFreq: <<: *real @@ -121,9 +160,21 @@ ControlParameters: allocatable: True # Tower fore-aft damping + TRA_Mode: + <<: *integer + description: Tower Fore-Aft control mode {0 - no fore-aft control, 1 - Tower fore-aft damping, 2 -Frequency exclusion zone, 3- Options 1 and 2} + TRA_ExclSpeed: + <<: *real + description: Rotor speed for exclusion [LSS] [rad/s] + TRA_ExclBand: + <<: *real + description: One-half of the total frequency exclusion band. Torque controller reference will be TRA_ExclFreq +/- TRA_ExlBand [rad/s] + TRA_RateLimit: + <<: *real + description: Time constant for gain change when in exclusion zone [s] TD_Mode: <<: *integer - description: Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle + description: Tower Fore-Aft control mode {0 - no fore-aft control, 1 - Tower fore-aft damping, 2 -Frequency exclusion zone, 3- Options 1 and 2} FA_HPFCornerFreq: <<: *real description: Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] @@ -216,7 +267,10 @@ ControlParameters: # Generator Torque Controller VS_ControlMode: <<: *integer - description: Generator torque control mode in above rated conditions {0 - constant torque, 1 - constant power, 2 - TSR Tracking, 3 - TSR Tracking w/ const power} + description: Generator torque control mode in above rated conditions {0 - no torque control, 1 - komega^2 with PI trans, 2 - WSE TSR Tracking, 3 - Power TSR Tracking} + VS_ConstPower: + <<: *integer + description: Constant power torque control VS_GenEff: <<: *real description: Generator efficiency mechanical power -> electrical power [-] @@ -261,6 +315,9 @@ ControlParameters: VS_TSRopt: <<: *real description: Power-maximizing region 2 tip-speed ratio [rad] + VS_PwrFiltF: + <<: *real + description: Cut-off frequency of filter on generator power for power-based tsr tracking control # Setpoint Smoother SS_Mode: @@ -272,6 +329,25 @@ ControlParameters: SS_PCGain: <<: *real description: Collective pitch controller setpoint smoother gain, [-]. + + # Power reference tracking + PRC_Mode: + <<: *integer + description: Power reference tracking mode, 0- use standard rotor speed set points, 1- use PRC rotor speed setpoints + PRC_WindSpeeds: + <<: *real + description: Array of wind speeds used in rotor speed vs. wind speed lookup table + allocatable: True + PRC_GenSpeeds: + <<: *real + description: Array of rotor speeds corresponding to PRC_WindSpeeds + allocatable: True + PRC_n: + <<: *integer + description: Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array + PRC_LPF_Freq: + <<: *real + description: Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] # Wind Speed Estimator WE_Mode: @@ -376,9 +452,17 @@ ControlParameters: Fl_Mode: <<: *integer description: Floating specific feedback mode {0 - no nacelle velocity feedback, 1 - nacelle velocity feedback} + Fl_n: + <<: *integer + description: Number of Fl_Kp for gain scheduling Fl_Kp: <<: *real description: Nacelle velocity proportional feedback gain [s] + allocatable: True + Fl_U: + <<: *real + description: Wind speeds for scheduling Fl_Kp [m/s] + allocatable: True # Trailing edge flaps Flp_Mode: @@ -410,13 +494,21 @@ ControlParameters: description: The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) Ind_BldPitch: <<: *integer - description: The column in OL_Filename that contains the blade pitch input in rad + description: The columns in OL_Filename that contains the blade pitch inputs (1,2,3) in rad + allocatable: True Ind_GenTq: <<: *integer description: The column in OL_Filename that contains the generator torque in Nm Ind_YawRate: <<: *integer description: The column in OL_Filename that contains the generator torque in Nm + Ind_Azimuth: + <<: *integer + description: The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) + RP_Gains: + <<: *real + description: PID gains and Tf on derivative term for rotor position control (used if OL_Mode = 2) + allocatable: True Ind_CableControl: <<: *integer allocatable: True @@ -429,10 +521,18 @@ ControlParameters: <<: *real allocatable: True description: Open loop breakpoints in timeseries - OL_BldPitch: + OL_BldPitch1: <<: *real allocatable: True - description: Open blade pitch timeseries + description: Open loop blade pitch 1 timeseries + OL_BldPitch2: + <<: *real + allocatable: True + description: Open loop blade pitch 2 timeseries + OL_BldPitch3: + <<: *real + allocatable: True + description: Open loop blade pitch 3 timeseries OL_CableControl: <<: *real allocatable: True @@ -444,11 +544,15 @@ ControlParameters: OL_GenTq: <<: *real allocatable: True - description: Open generator torque timeseries + description: Open loop generator torque timeseries OL_YawRate: <<: *real allocatable: True - description: Open yaw rate timeseries + description: Open loop yaw rate timeseries + OL_Azimuth: + <<: *real + allocatable: True + description: Open loop azimuth timeseries OL_Channels: <<: *real allocatable: True @@ -493,31 +597,7 @@ ControlParameters: <<: *real allocatable: True description: AWC clocking angle [deg] - - # Active wake control - AWC_Mode: - <<: *integer - description: Active wake control mode [0 - unused, 1 - SNL method, 2 - NREL method] - AWC_NumModes: - <<: *integer - description: AWC- Number of modes to include [-] - AWC_n: - <<: *integer - allocatable: True - description: AWC azimuthal mode [-] - AWC_freq: - <<: *real - allocatable: True - description: AWC frequency [Hz] - AWC_amp: - <<: *real - allocatable: True - description: AWC amplitude [deg] - AWC_clockangle: - <<: *real - allocatable: True - description: AWC clocking angle [deg] - + # Pitch actuator error PF_Mode: <<: *integer @@ -527,6 +607,7 @@ ControlParameters: description: Pitch actuator fault offsets for blade 1-3 [rad/s] allocatable: True + # External Control Ext_Mode: <<: *integer @@ -834,6 +915,10 @@ piParams: <<: *real dimension: (99) description: Previous integrator term - second integrator + ELast: + <<: *real + dimension: (99) + description: Previous error term for derivative LocalVariables: iStatus: @@ -845,9 +930,21 @@ LocalVariables: DT: <<: *real description: Time step [s] + WriteThisStep: + <<: *logical + description: Write an output line this time step + n_DT: + <<: *integer + description: number of timesteps since start + Time_Last: + <<: *real + description: Last time [s] VS_GenPwr: <<: *real description: Generator power [W] + VS_GenPwrF: + <<: *real + description: Generator power [W] GenSpeed: <<: *real description: Generator speed (HSS) [rad/s] @@ -881,6 +978,22 @@ LocalVariables: Azimuth: <<: *real description: Rotor aziumuth angle [rad] + OL_Azimuth: + <<: *real + description: Rotor aziumuth angle [rad] + AzUnwrapped: + <<: *real + description: Rotor aziumuth angle [rad] + AzError: + <<: *real + description: Azimuth error angle [rad] + GenTqAz: + <<: *real + description: Gen torque command due to azimuth error + AzBuffer: + <<: *real + size: 2 + description: Current and last rotor aziumuth angles [rad] NumBl: <<: *integer description: Number of blades [-] @@ -900,6 +1013,27 @@ LocalVariables: <<: *real description: Tower fore-aft vibration damping pitch contribution [rad] size: 3 + VS_RefSpd: + <<: *real + description: Torque control generator speed set point [rad/s] + VS_RefSpd_TSR: + <<: *real + description: Torque control generator speed set point based on optimal TSR [rad/s] + VS_RefSpd_TRA: + <<: *real + description: Torque control generator speed set point after freq avoidance [rad/s] + VS_RefSpd_RL: + <<: *real + description: Torque control generator speed set point after rate limit [rad/s] + PC_RefSpd: + <<: *real + description: Generator speed set point of pitch controller [rad/s] + PC_RefSpd_SS: + <<: *real + description: Generator speed set point of pitch controller after setpoint smoothing [rad/s] + PC_RefSpd_PRC: + <<: *real + description: Generator speed set point of pitch controller after power ref control [rad/s] RotSpeedF: <<: *real description: Filtered LSS (generator) speed [rad/s]. @@ -943,6 +1077,9 @@ LocalVariables: PC_PitComT: <<: *real description: Total command pitch based on the sum of the proportional and integral terms [rad]. + PC_PitComT: + <<: *real + description: Collective pitch commmand from PI control [rad]. PC_PitComT_Last: <<: *real description: Last total command pitch based on the sum of the proportional and integral terms [rad]. @@ -1017,6 +1154,9 @@ LocalVariables: TestType: <<: *real description: Test variable, no use + Kp_Float: + <<: *real + description: Local, instantaneous Kp_Float, scheduled on wind speed, if desired VS_MaxTq: <<: *real description: Maximum allowable generator torque [Nm]. @@ -1059,6 +1199,9 @@ LocalVariables: VS_LastGenTrqF: <<: *real description: Differentiated integrated wind speed quantity for estimation [m/s] + PRC_WSE_F: + <<: *real + description: Filtered wind speed estimate for power reference control SD: <<: *logical description: Shutdown, .FALSE. if inactive, .TRUE. if active @@ -1069,6 +1212,15 @@ LocalVariables: <<: *real FA_AccF: <<: *real + FA_Hist: + <<: *integer + description: Hysteresis state for tower resonance avoidance. + TRA_LastRefSpd: + <<: *real + description: Last reference generator speed + VS_RefSpeed: + <<: *real + description: Torque controller reference speed PtfmTDX: <<: *real description: Platform motion -- Displacement TDX (m)') @@ -1158,6 +1310,19 @@ LocalVariables: <<: *complex description: Complex angle for each blade, sum of modes? size: 3 + ZMQ_ID: + <<: *integer + description: 0000 - 9999, Identifier of the rosco, used for zeromq interface only + ZMQ_YawOffset: + <<: *real + description: Yaw offset command, [rad] + ZMQ_TorqueOffset: + <<: *real + description: Torque offset command, [Nm] + ZMQ_PitOffset: + <<: *real + size: 3 + description: Pitch command offset provided by ZeroMQ WE: <<: *derived_type id: WE @@ -1284,7 +1449,6 @@ DebugVariables: axisYaw_2P: <<: *real description: Yaw component of coleman transformation, 2P - YawRateCom: <<: *real description: Commanded yaw rate [rad/s]. @@ -1300,6 +1464,12 @@ DebugVariables: YawState: <<: *real description: State of yaw controller + VS_RefSpd: + <<: *real + description: Torque control generator speed set point [rad/s] + PC_RefSpd: + <<: *real + description: Generator speed set point of pitch controller [rad/s] ErrorVariables: size_avcMSG: @@ -1338,14 +1508,7 @@ ExtDLL_Type: size: 3 length: 1024 description: The name of the procedure in the DLL that will be called. - -ZMQ_Variables: - ZMQ_Flag: - <<: *logical - description: Flag if we're using zeroMQ at all (0-False, 1-True) - Yaw_Offset: - <<: *real - description: Yaw offsety command, [rad] + ExtControlType: avrSWAP: diff --git a/rosco/controller/rosco_registry/wfc_interface.yaml b/rosco/controller/rosco_registry/wfc_interface.yaml new file mode 100644 index 00000000..63b6e895 --- /dev/null +++ b/rosco/controller/rosco_registry/wfc_interface.yaml @@ -0,0 +1,27 @@ +measurements: [ + ZMQ_ID, + iStatus, + Time, + VS_MechGenPwr, + VS_GenPwr, + GenSpeed, + RotSpeed, + GenTqMeas, + NacHeading, + NacVane, + HorWindV, + rootMOOP(1), + rootMOOP(2), + rootMOOP(3), + FA_Acc, + NacIMU_FA_Acc, + Azimuth, + ] + +setpoints: [ + ZMQ_TorqueOffset, + ZMQ_YawOffset, + ZMQ_PitOffset(1), + ZMQ_PitOffset(2), + ZMQ_PitOffset(3), + ] \ No newline at end of file diff --git a/ROSCO/rosco_registry/write_registry.py b/rosco/controller/rosco_registry/write_registry.py similarity index 87% rename from ROSCO/rosco_registry/write_registry.py rename to rosco/controller/rosco_registry/write_registry.py index 2f31b400..1c07fc98 100644 --- a/ROSCO/rosco_registry/write_registry.py +++ b/rosco/controller/rosco_registry/write_registry.py @@ -1,7 +1,7 @@ import yaml -import ROSCO_toolbox +import rosco.toolbox import os -from ROSCO_toolbox.ofTools.util.FileTools import load_yaml +from rosco.toolbox.ofTools.util.FileTools import load_yaml def generate(yfile): ''' @@ -26,7 +26,7 @@ def write_types(yfile): file = open(registry_fname, 'w') # Header file.write('! ROSCO Registry\n') - file.write('! This file is automatically generated by write_registry.py using ROSCO v{}\n'.format(ROSCO_toolbox.__version__)) + file.write('! This file is automatically generated by write_registry.py using ROSCO v{}\n'.format(rosco.toolbox.__version__)) file.write('! For any modification to the registry, please edit the rosco_types.yaml accordingly\n \n') file.write('MODULE ROSCO_Types\n') file.write('USE, INTRINSIC :: ISO_C_Binding\n') @@ -62,7 +62,7 @@ def write_roscoio(yfile): registry_fname = os.path.join(os.path.dirname(os.path.dirname(os.path.abspath(__file__))),'src','ROSCO_IO.f90') file = open(registry_fname, 'w') file.write('! ROSCO IO\n') - file.write('! This file is automatically generated by write_registry.py using ROSCO v{}\n'.format(ROSCO_toolbox.__version__)) + file.write('! This file is automatically generated by write_registry.py using ROSCO v{}\n'.format(rosco.toolbox.__version__)) file.write('! For any modification to the registry, please edit the rosco_types.yaml accordingly\n \n') file.write('MODULE ROSCO_IO\n') file.write(' USE, INTRINSIC :: ISO_C_Binding\n') @@ -80,7 +80,7 @@ def write_roscoio(yfile): file.write(" TYPE(ObjectInstances), INTENT(INOUT) :: objInst\n") file.write(" TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar\n") file.write(" INTEGER(IntKi), INTENT(IN) :: size_avcOUTNAME\n") - file.write(" CHARACTER(size_avcOUTNAME-1), INTENT(IN) :: RootName \n") + file.write(" CHARACTER(size_avcOUTNAME), INTENT(IN) :: RootName \n") file.write(" \n") file.write(" INTEGER(IntKi) :: Un ! I/O unit for pack/unpack (checkpoint & restart)\n") file.write(" INTEGER(IntKi) :: I ! Generic index.\n") @@ -95,7 +95,8 @@ def write_roscoio(yfile): file.write(" OPEN(unit=Un, FILE=TRIM(InFile), STATUS='UNKNOWN', FORM='UNFORMATTED' , ACCESS='STREAM', IOSTAT=ErrStat, ACTION='WRITE' )\n") file.write("\n") file.write(" IF ( ErrStat /= 0 ) THEN\n") - file.write(" ErrMsg = 'Cannot open file "'//TRIM( InFile )//'". Another program may have locked it for writing.'\n") + file.write(" ErrVar%aviFAIL = 1\n") + file.write(" ErrVar%ErrMsg = 'ROSCO_IO: Cannot open checkpoint file '//TRIM(InFile)//' for writing'\n") file.write("\n") file.write(" ELSE\n") @@ -112,22 +113,25 @@ def write_roscoio(yfile): for var in reg['ObjectInstances']: file.write(' WRITE( Un, IOSTAT=ErrStat) objInst%{}\n'.format(var)) file.write(' Close ( Un )\n') + file.write(" IF ( ErrStat /= 0 ) THEN\n") + file.write(" ErrVar%aviFAIL = 1\n") + file.write(" ErrVar%ErrMsg = 'ROSCO_IO: Error writing checkpoint file.'\n") + file.write(" ENDIF\n") file.write(' ENDIF\n') file.write('END SUBROUTINE WriteRestartFile\n') file.write('\n \n') # ------------------------------------------------ # ------------ ReadRestartFile ------------------ # ------------------------------------------------ - file.write('SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootName, size_avcOUTNAME, zmqVar, ErrVar)\n') + file.write('SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootName, size_avcOUTNAME, ErrVar)\n') file.write(" TYPE(LocalVariables), INTENT(INOUT) :: LocalVar\n") file.write(" TYPE(ControlParameters), INTENT(INOUT) :: CntrPar\n") file.write(" TYPE(ObjectInstances), INTENT(INOUT) :: objInst\n") file.write(" TYPE(PerformanceData), INTENT(INOUT) :: PerfData\n") file.write(" TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar\n") - file.write(" TYPE(ZMQ_Variables), INTENT(INOUT) :: zmqVar\n") file.write(" REAL(ReKi), INTENT(IN) :: avrSWAP(*)\n") file.write(" INTEGER(IntKi), INTENT(IN) :: size_avcOUTNAME\n") - file.write(" CHARACTER(size_avcOUTNAME-1), INTENT(IN) :: RootName \n") + file.write(" CHARACTER(size_avcOUTNAME), INTENT(IN) :: RootName \n") file.write(" \n") file.write(" INTEGER(IntKi) :: Un ! I/O unit for pack/unpack (checkpoint & restart)\n") file.write(" INTEGER(IntKi) :: I ! Generic index.\n") @@ -142,7 +146,8 @@ def write_roscoio(yfile): file.write(" OPEN(unit=Un, FILE=TRIM(InFile), STATUS='UNKNOWN', FORM='UNFORMATTED' , ACCESS='STREAM', IOSTAT=ErrStat, ACTION='READ' )\n") file.write("\n") file.write(" IF ( ErrStat /= 0 ) THEN\n") - file.write(" ErrMsg = 'Cannot open file "'//TRIM( InFile )//'". Another program may have locked it for writing.'\n") + file.write(" ErrVar%aviFAIL = 1\n") + file.write(" ErrVar%ErrMsg = 'ROSCO_IO: Cannot open checkpoint file '//TRIM(InFile)//' for reading'\n") file.write("\n") file.write(" ELSE\n") @@ -161,9 +166,13 @@ def write_roscoio(yfile): for var in reg['ObjectInstances']: file.write(' READ( Un, IOSTAT=ErrStat) objInst%{}\n'.format(var)) file.write(' Close ( Un )\n') + file.write(" IF ( ErrStat /= 0 ) THEN\n") + file.write(" ErrVar%aviFAIL = 1\n") + file.write(" ErrVar%ErrMsg = 'ROSCO_IO: Error reading checkpoint file.'\n") + file.write(" ENDIF\n") file.write(' ENDIF\n') file.write(' ! Read Parameter files\n') - file.write(' CALL ReadControlParameterFileSub(CntrPar, zmqVar, LocalVar%ACC_INFILE, LocalVar%ACC_INFILE_SIZE, RootName, ErrVar)\n') + file.write(' CALL ReadControlParameterFileSub(CntrPar, LocalVar, LocalVar%ACC_INFILE, LocalVar%ACC_INFILE_SIZE, RootName, ErrVar)\n') file.write(' IF (CntrPar%WE_Mode > 0) THEN\n') file.write(' CALL READCpFile(CntrPar, PerfData, ErrVar)\n') file.write(' ENDIF\n') @@ -188,7 +197,7 @@ def write_roscoio(yfile): file.write(' INTEGER(IntKi), SAVE :: UnDb2 ! I/O unit for the debugging information, avrSWAP\n') file.write(' INTEGER(IntKi), SAVE :: UnDb3 ! I/O unit for the debugging information, avrSWAP\n') file.write(' REAL(ReKi), INTENT(INOUT) :: avrSWAP(*) ! The swap array, used to pass data to, and receive data from, the DLL controller.\n') - file.write(' CHARACTER(size_avcOUTNAME-1), INTENT(IN) :: RootName ! a Fortran version of the input C string (not considered an array here) [subtract 1 for the C null-character]\n') + file.write(' CHARACTER(size_avcOUTNAME), INTENT(IN) :: RootName ! a Fortran version of the input C string (not considered an array here) [subtract 1 for the C null-character]\n') file.write(' CHARACTER(200) :: Version ! git version of ROSCO\n') file.write(' CHARACTER(15), ALLOCATABLE :: DebugOutStrings(:), DebugOutUnits(:)\n') file.write('\n') @@ -337,31 +346,46 @@ def write_roscoio(yfile): file.write(" ! Process DebugOutData, LocalVarOutData\n") file.write(" ! Remove very small numbers that cause ******** outputs\n") file.write(" DO I = 1,SIZE(DebugOutData)\n") - file.write(" IF (ABS(DebugOutData(I)) < 1E-10) THEN\n") + file.write(" IF (ABS(DebugOutData(I)) < 1E-99) THEN\n") file.write(" DebugOutData(I) = 0\n") file.write(" END IF\n") + file.write(" IF (ABS(DebugOutData(I)) > 1E+99) THEN\n") + file.write(" DebugOutData(I) = 1E+99\n") + file.write(" END IF\n") file.write(" END DO\n") file.write(" \n") file.write(" DO I = 1,SIZE(LocalVarOutData)\n") - file.write(" IF (ABS(LocalVarOutData(I)) < 1E-10) THEN\n") + file.write(" IF (ABS(LocalVarOutData(I)) < 1E-99) THEN\n") file.write(" LocalVarOutData(I) = 0\n") file.write(" END IF\n") + file.write(" IF (ABS(LocalVarOutData(I)) > 1E+99) THEN\n") + file.write(" LocalVarOutData(I) = 1E+99\n") + file.write(" END IF\n") file.write(" END DO\n") file.write(" \n") file.write(" ! Write debug files\n") file.write(f' FmtDat = "(F20.5,TR5,{n_lv_outputs}(ES20.5E2,TR5:))" ! The format of the debugging data\n') - file.write(" IF(CntrPar%LoggingLevel > 0) THEN\n") - file.write(" WRITE (UnDb, TRIM(FmtDat)) LocalVar%Time, DebugOutData\n") - file.write(" END IF\n") + file.write(" IF ( MOD(LocalVar%n_DT, CntrPar%n_DT_Out) == 0) THEN\n") + file.write(" IF(CntrPar%LoggingLevel > 0) THEN\n") + file.write(" WRITE (UnDb, TRIM(FmtDat)) LocalVar%Time, DebugOutData\n") + file.write(" END IF\n") file.write("\n") - file.write(" IF(CntrPar%LoggingLevel > 1) THEN\n") - file.write(" WRITE (UnDb2, TRIM(FmtDat)) LocalVar%Time, LocalVarOutData\n") - file.write(" END IF\n") + file.write(" IF(CntrPar%LoggingLevel > 1) THEN\n") + file.write(" WRITE (UnDb2, TRIM(FmtDat)) LocalVar%Time, LocalVarOutData\n") + file.write(" END IF\n") file.write("\n") - file.write(" IF(CntrPar%LoggingLevel > 2) THEN\n") - file.write(" WRITE (UnDb3, TRIM(FmtDat)) LocalVar%Time, avrSWAP(avrIndices)\n") + file.write(" IF(CntrPar%LoggingLevel > 2) THEN\n") + file.write(" WRITE (UnDb3, TRIM(FmtDat)) LocalVar%Time, avrSWAP(avrIndices)\n") + file.write(" END IF\n") file.write(" END IF\n") file.write("\n") + file.write(" ! Close all files when simulation finished\n") + file.write(" IF (LocalVar%iStatus < 0) THEN\n") + file.write(" CLOSE(UnDb)\n") + file.write(" CLOSE(UnDb2)\n") + file.write(" CLOSE(UnDb3)\n") + file.write(" ENDIF\n") + file.write("END SUBROUTINE Debug\n") file.write("\n") file.write("END MODULE ROSCO_IO") @@ -383,6 +407,8 @@ def read_type(param): f90type = 'INTEGER(IntKi)' if param['allocatable']: f90type += ', DIMENSION(:), ALLOCATABLE' + elif param['dimension']: + f90type += ', DIMENSION{}'.format(param['dimension']) elif param['type'] == 'real': f90type = 'REAL(DbKi)' if param['allocatable']: diff --git a/rosco/controller/rosco_registry/write_wfc_interface.py b/rosco/controller/rosco_registry/write_wfc_interface.py new file mode 100644 index 00000000..06895db8 --- /dev/null +++ b/rosco/controller/rosco_registry/write_wfc_interface.py @@ -0,0 +1,229 @@ +import rosco.toolbox +import os +from rosco.toolbox.ofTools.util.FileTools import load_yaml +import re + +this_dir = os.path.dirname(__file__) +src_dir = os.path.realpath(os.path.join(this_dir,'../src')) + + +def has_number_in_parentheses(input_string): + pattern = r'\(\d+\)' + match = re.search(pattern, input_string) + if match: + return match.group() + else: + return None + + +def main(): + + # Read wfc_interface yaml and rosco_types for checking + wfc_int = load_yaml(os.path.join(this_dir,'wfc_interface.yaml')) + rosco_types = load_yaml(os.path.join(this_dir,'rosco_types.yaml')) + + local_vars = rosco_types['LocalVariables'] + + # Check that measurements/setpoints are a LocalVar + for ms in wfc_int['setpoints'] + wfc_int['measurements']: + ind = has_number_in_parentheses(ms) + if ind: + ms = ms.strip(ind) + ind_int = int(ind[1:-1]) + else: + ind_int = 0 + + if ms not in local_vars: + raise Exception(f'WFC variable {ms} not in LocalVars') + + if ind_int: + if local_vars[ms]['size'] < ind_int: + raise Exception(f'Requested index ({ind_int}) of WFC variable {ms} is greater than LocalVars version.') + + + write_zmq_f90(wfc_int) + write_client_c(wfc_int) + +def write_zmq_f90(wfc_int_yaml): + + + n_measurements = len(wfc_int_yaml['measurements']) + n_setpoints = len(wfc_int_yaml['setpoints']) + + + with open(os.path.join(src_dir,'ZeroMQInterface.f90'),'w') as f: + + f.write("module ZeroMQInterface\n") + f.write(" USE, INTRINSIC :: ISO_C_BINDING, only: C_CHAR, C_DOUBLE, C_NULL_CHAR\n") + f.write(" IMPLICIT NONE\n") + f.write(" ! \n") + f.write("\n") + f.write("CONTAINS\n") + f.write(" SUBROUTINE UpdateZeroMQ(LocalVar, CntrPar, ErrVar)\n") + f.write(" USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, ErrorVariables\n") + f.write(" IMPLICIT NONE\n") + f.write(" TYPE(LocalVariables), INTENT(INOUT) :: LocalVar\n") + f.write(" TYPE(ControlParameters), INTENT(INOUT) :: CntrPar\n") + f.write(" TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar\n") + f.write("\n") + f.write(" character(256) :: zmq_address\n") + f.write(f" real(C_DOUBLE) :: setpoints({n_setpoints})\n") + f.write(f" real(C_DOUBLE) :: turbine_measurements({n_measurements})\n") + f.write(" CHARACTER(*), PARAMETER :: RoutineName = 'UpdateZeroMQ'\n") + f.write("\n") + f.write(" ! C interface with ZeroMQ client\n") + f.write("#ifdef ZMQ_CLIENT\n") + f.write(" interface\n") + f.write(" subroutine zmq_client(zmq_address, measurements, setpoints) bind(C, name='zmq_client')\n") + f.write(" import :: C_CHAR, C_DOUBLE\n") + f.write(" implicit none\n") + f.write(" character(C_CHAR), intent(out) :: zmq_address(*)\n") + f.write(f" real(C_DOUBLE) :: measurements({n_measurements})\n") + f.write(f" real(C_DOUBLE) :: setpoints({n_setpoints})\n") + f.write(" end subroutine zmq_client\n") + f.write(" end interface\n") + f.write("#endif\n") + f.write("\n") + f.write(" ! Communicate if threshold has been reached\n") + f.write(" IF ( MOD(LocalVar%n_DT, CntrPar%n_DT_ZMQ) == 0 .OR. LocalVar%iStatus == -1 ) THEN\n") + f.write(" ! Collect measurements to be sent to ZeroMQ server\n") + + ## Write measurements + for i_meas, meas in enumerate(wfc_int_yaml['measurements']): + f.write(f" turbine_measurements({i_meas+1}) = LocalVar%{meas}\n") + f.write("\n") + + f.write(" write (zmq_address, '(A,A)') TRIM(CntrPar%ZMQ_CommAddress), C_NULL_CHAR\n") + f.write("#ifdef ZMQ_CLIENT\n") + f.write(" call zmq_client(zmq_address, turbine_measurements, setpoints)\n") + f.write("#else\n") + f.write(" ! Add RoutineName to error message\n") + f.write(" ErrVar%aviFAIL = -1\n") + f.write(" IF (CntrPar%ZMQ_Mode > 0) THEN\n") + f.write(" ErrVar%ErrMsg = ' >> The ZeroMQ client has not been properly installed, ' &\n") + f.write(" //'please install it to use ZMQ_Mode > 0.'\n") + f.write(" ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg)\n") + f.write(" ENDIF\n") + f.write("#endif\n") + f.write("\n") + f.write(" ! write (*,*) 'ZeroMQInterface: torque setpoint from ssc: ', setpoints(1)\n") + f.write(" ! write (*,*) 'ZeroMQInterface: yaw setpoint from ssc: ', setpoints(2)\n") + f.write(" ! write (*,*) 'ZeroMQInterface: pitch 1 setpoint from ssc: ', setpoints(3)\n") + f.write(" ! write (*,*) 'ZeroMQInterface: pitch 2 setpoint from ssc: ', setpoints(4)\n") + f.write(" ! write (*,*) 'ZeroMQInterface: pitch 3 setpoint from ssc: ', setpoints(5)\n") + + ## Write setpoints + for i_set, set in enumerate(wfc_int_yaml['setpoints']): + f.write(f" LocalVar%{set} = setpoints({i_set+1})\n") + + f.write(" \n") + f.write(" ENDIF\n") + f.write("\n") + f.write("\n") + f.write(" END SUBROUTINE UpdateZeroMQ\n") + f.write("end module ZeroMQInterface\n") + +def write_client_c(wfc_int_yaml): + + n_measurements = len(wfc_int_yaml['measurements']) + n_setpoints = len(wfc_int_yaml['setpoints']) + + with open(os.path.join(src_dir,'zmq_client.c'),'w') as f: + f.write('#include \n') + f.write('#include \n') + f.write('#include \n') + f.write('#include \n') + f.write('#include \n') + f.write('\n') + f.write('\n') + f.write('void delete_blank_spaces_in_string(char *s)\n') + f.write('{\n') + f.write(' int i,k=0;\n') + f.write(' for(i=0;s[i];i++)\n') + f.write(' {\n') + f.write(' s[i]=s[i+k];\n') + f.write(r' if(s[i]==" "|| s[i]=="\t")' + '\n') + f.write(' {\n') + f.write(' k++;\n') + f.write(' i--;\n') + f.write(' }\n') + f.write(' }\n') + f.write('}\n') + f.write('\n') + f.write('\n') + f.write('int zmq_client (\n') + f.write(' char *zmq_address,\n') + f.write(f' double measurements[{n_measurements}],\n') + f.write(f' double setpoints[{n_setpoints}]\n') + f.write(')\n') + f.write('{\n') + f.write(f' int num_measurements = {n_measurements}; // Number of setpoints and measurements, respectively, and float precision (character length)\n') + f.write(' int char_buffer_size_single = 20; // Char buffer for a single measurement\n') + f.write(' int char_buffer_size_array = (num_measurements * (char_buffer_size_single + 1)); // Char buffer for full messages to and from ROSCO\n') + f.write(' char string_to_ssc[char_buffer_size_array];\n') + f.write(' char string_from_ssc[char_buffer_size_array];\n') + f.write('\n') + f.write(' int verbose = 0; // Variable to define verbose\n') + f.write(' \n') + f.write(' if (verbose == 1) {\n') + f.write(r' printf ("Connecting to ZeroMQ server at %s...\n", zmq_address);' + '\n') + f.write(' }\n') + f.write(' // Open connection with ZeroMQ server\n') + f.write(' void *context = zmq_ctx_new ();\n') + f.write(' void *requester = zmq_socket (context, ZMQ_REQ);\n') + f.write(' zmq_connect (requester, zmq_address); // string_to_zmq is something like "tcp://localhost:5555"\n') + f.write('\n') + f.write(' // Create a string with measurements to be sent to ZeroMQ server (e.g., Python)\n') + f.write(' char a[char_buffer_size_array], b[char_buffer_size_single];\n') + f.write(' sprintf(b, "%.6e", measurements[0]);\n') + f.write(' strncpy(a, b, char_buffer_size_single);\n') + f.write(r' //printf ("zmq_client.c: a[char_buffer_size_single]: measurements[0]: %s\n", a);'+ '\n') + f.write(' int i = 1;\n') + f.write(' while (i < num_measurements) {\n') + f.write(' strcat(a, ","); // Add a comma\n') + f.write(' sprintf(b, "%.6e", measurements[i]); // Add value\n') + f.write(' strcat(a, b); // Concatenate b to a\n') + f.write(r' //printf ("zmq_client.c: b[char_buffer_size_single]: measurements[i]: %s\n", b);'+ '\n') + f.write(r' //printf (" --> zmq_client.c: a[char_buffer_size_single]: measurements[i]: %s\n", a);'+ '\n') + f.write(' i = i + 1;\n') + f.write(' }\n') + f.write(' strncpy(string_to_ssc, a, char_buffer_size_array);\n') + f.write('\n') + f.write(' // Print the string\n') + f.write(' if (verbose == 1) {\n') + f.write(r' printf ("zmq_client.c: string_to_ssc: %s…\n", string_to_ssc);'+ '\n') + f.write(' }\n') + f.write('\n') + f.write(' // Core ZeroMQ communication: receive data and send back signals\n') + f.write(' zmq_send (requester, string_to_ssc, char_buffer_size_array, 0);\n') + f.write(' zmq_recv (requester, string_from_ssc, char_buffer_size_array, 0);\n') + f.write('\n') + f.write(' if (verbose == 1) {\n') + f.write(r' printf ("zmq_client.c: Received a response: %s\n", string_from_ssc);'+ '\n') + f.write(' }\n') + f.write('\n') + f.write(' // Convert string_from_ssc string to separate floats\n') + f.write(' delete_blank_spaces_in_string(string_from_ssc);\n') + f.write(' char *pt;\n') + f.write(' pt = strtok (string_from_ssc,",");\n') + f.write(' i = 0;\n') + f.write(' while (pt != NULL) {\n') + f.write(' double dtmp = atof(pt);\n') + f.write(' if (verbose == 1) {\n') + f.write(r' printf("pt subloop: %s (var), %f (double) \n", pt, dtmp);'+ '\n') + f.write(r' printf("zmq_client.c: setpoint[%d]: %f \n", i, dtmp);'+ '\n') + f.write(' }\n') + f.write(' pt = strtok (NULL, ",");\n') + f.write(' setpoints[i] = dtmp; // Save values to setpoints\n') + f.write(' i = i + 1;\n') + f.write(' }\n') + f.write('\n') + f.write(' // Close connection\n') + f.write(' zmq_close (requester);\n') + f.write(' zmq_ctx_destroy (context);\n') + f.write(' return 0;\n') + f.write('}\n') + + +if __name__=="__main__": + main() \ No newline at end of file diff --git a/ROSCO/src/Constants.f90 b/rosco/controller/src/Constants.f90 similarity index 97% rename from ROSCO/src/Constants.f90 rename to rosco/controller/src/Constants.f90 index b85eefaa..56298879 100644 --- a/ROSCO/src/Constants.f90 +++ b/rosco/controller/src/Constants.f90 @@ -14,7 +14,7 @@ MODULE Constants USE, INTRINSIC :: ISO_C_Binding - Character(*), PARAMETER :: rosco_version = 'v2.8.0' ! ROSCO version + Character(*), PARAMETER :: rosco_version = 'v2.9.0' ! ROSCO version INTEGER, PARAMETER :: DbKi = C_DOUBLE !< Default kind for double floating-point numbers INTEGER, PARAMETER :: ReKi = C_FLOAT !< Default kind for single floating-point numbers INTEGER, PARAMETER :: IntKi = C_INT !< Default kind for integer numbers diff --git a/ROSCO/src/ControllerBlocks.f90 b/rosco/controller/src/ControllerBlocks.f90 similarity index 76% rename from ROSCO/src/ControllerBlocks.f90 rename to rosco/controller/src/ControllerBlocks.f90 index 390be8d0..be9e6400 100644 --- a/ROSCO/src/ControllerBlocks.f90 +++ b/rosco/controller/src/ControllerBlocks.f90 @@ -24,63 +24,95 @@ MODULE ControllerBlocks CONTAINS ! ----------------------------------------------------------------------------------- ! Calculate setpoints for primary control actions - SUBROUTINE ComputeVariablesSetpoints(CntrPar, LocalVar, objInst) - USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances + SUBROUTINE ComputeVariablesSetpoints(CntrPar, LocalVar, objInst, DebugVar, ErrVar) + USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances, DebugVariables, ErrorVariables USE Constants ! Allocate variables TYPE(ControlParameters), INTENT(INOUT) :: CntrPar TYPE(LocalVariables), INTENT(INOUT) :: LocalVar TYPE(ObjectInstances), INTENT(INOUT) :: objInst + TYPE(DebugVariables), INTENT(INOUT) :: DebugVar + TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar - REAL(DbKi) :: VS_RefSpd ! Referece speed for variable speed torque controller, [rad/s] - REAL(DbKi) :: PC_RefSpd ! Referece speed for pitch controller, [rad/s] - REAL(DbKi) :: Omega_op ! Optimal TSR-tracking generator speed, [rad/s] ! ----- Pitch controller speed and power error ----- + + ! Power reference tracking generator speed + IF (CntrPar%PRC_Mode == 1) THEN + LocalVar%PRC_WSE_F = LPFilter(LocalVar%WE_Vw, LocalVar%DT,CntrPar%PRC_LPF_Freq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instLPF) + LocalVar%PC_RefSpd_PRC = interp1d(CntrPar%PRC_WindSpeeds,CntrPar%PRC_GenSpeeds,LocalVar%PRC_WSE_F,ErrVar) + ELSE + LocalVar%PC_RefSpd_PRC = CntrPar%PC_RefSpd + ENDIF + ! Implement setpoint smoothing IF (LocalVar%SS_DelOmegaF < 0) THEN - PC_RefSpd = CntrPar%PC_RefSpd - LocalVar%SS_DelOmegaF + LocalVar%PC_RefSpd_SS = LocalVar%PC_RefSpd_PRC - LocalVar%SS_DelOmegaF ELSE - PC_RefSpd = CntrPar%PC_RefSpd + LocalVar%PC_RefSpd_SS = LocalVar%PC_RefSpd_PRC ENDIF - LocalVar%PC_SpdErr = PC_RefSpd - LocalVar%GenSpeedF ! Speed error - LocalVar%PC_PwrErr = CntrPar%VS_RtPwr - LocalVar%VS_GenPwr ! Power error - + ! Compute error for pitch controller + LocalVar%PC_RefSpd = LocalVar%PC_RefSpd_SS + LocalVar%PC_SpdErr = LocalVar%PC_RefSpd - LocalVar%GenSpeedF ! Speed error + LocalVar%PC_PwrErr = CntrPar%VS_RtPwr - LocalVar%VS_GenPwr ! Power error, unused + ! ----- Torque controller reference errors ----- ! Define VS reference generator speed [rad/s] - IF ((CntrPar%VS_ControlMode == 2) .OR. (CntrPar%VS_ControlMode == 3)) THEN - VS_RefSpd = (CntrPar%VS_TSRopt * LocalVar%We_Vw_F / CntrPar%WE_BladeRadius) * CntrPar%WE_GearboxRatio - VS_RefSpd = saturate(VS_RefSpd,CntrPar%VS_MinOMSpd, CntrPar%VS_RefSpd) + IF (CntrPar%VS_ControlMode == 2) THEN + LocalVar%VS_RefSpd_TSR = (CntrPar%VS_TSRopt * LocalVar%We_Vw_F / CntrPar%WE_BladeRadius) * CntrPar%WE_GearboxRatio + ELSEIF (CntrPar%VS_ControlMode == 3) THEN + LocalVar%VS_GenPwrF = LPFilter(LocalVar%VS_GenPwr, LocalVar%DT,CntrPar%VS_PwrFiltF, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instLPF) + LocalVar%VS_RefSpd_TSR = (LocalVar%VS_GenPwrF/CntrPar%VS_Rgn2K)**(1./3.) ! Genspeed reference that doesnt depend on wind speed estimate (https://doi.org/10.2172/1259805) ELSE - VS_RefSpd = CntrPar%VS_RefSpd + LocalVar%VS_RefSpd_TSR = CntrPar%VS_RefSpd ENDIF + + LocalVar%VS_RefSpd = LocalVar%VS_RefSpd_TSR + + ! Exclude reference speeds specified by user + IF (CntrPar%TRA_Mode > 0) THEN + CALL RefSpeedExclusion(LocalVar, CntrPar, objInst, DebugVar) + END IF + + ! Saturate torque reference speed between min speed and rated speed + LocalVar%VS_RefSpd = saturate(LocalVar%VS_RefSpd,CntrPar%VS_MinOMSpd, CntrPar%VS_RefSpd) + + ! Implement power reference rotor speed (overwrites above), convert to generator speed + IF (CntrPar%PRC_Mode == 1) THEN + LocalVar%VS_RefSpd = interp1d(CntrPar%PRC_WindSpeeds,CntrPar%PRC_GenSpeeds,LocalVar%WE_Vw_F,ErrVar) + ENDIF ! Implement setpoint smoothing IF (LocalVar%SS_DelOmegaF > 0) THEN - VS_RefSpd = VS_RefSpd - LocalVar%SS_DelOmegaF + LocalVar%VS_RefSpd = LocalVar%VS_RefSpd - LocalVar%SS_DelOmegaF ENDIF ! Force zero torque in shutdown mode IF (LocalVar%SD) THEN - VS_RefSpd = CntrPar%VS_MinOMSpd + LocalVar%VS_RefSpd = CntrPar%VS_MinOMSpd ENDIF ! Force minimum rotor speed - VS_RefSpd = max(VS_RefSpd, CntrPar%VS_MinOmSpd) + LocalVar%VS_RefSpd = max(LocalVar%VS_RefSpd, CntrPar%VS_MinOmSpd) - ! TSR-tracking reference error + ! Reference error IF ((CntrPar%VS_ControlMode == 2) .OR. (CntrPar%VS_ControlMode == 3)) THEN - LocalVar%VS_SpdErr = VS_RefSpd - LocalVar%GenSpeedF + LocalVar%VS_SpdErr = LocalVar%VS_RefSpd - LocalVar%GenSpeedF ENDIF ! Define transition region setpoint errors - LocalVar%VS_SpdErrAr = VS_RefSpd - LocalVar%GenSpeedF ! Current speed error - Region 2.5 PI-control (Above Rated) + LocalVar%VS_SpdErrAr = LocalVar%VS_RefSpd - LocalVar%GenSpeedF ! Current speed error - Region 2.5 PI-control (Above Rated) LocalVar%VS_SpdErrBr = CntrPar%VS_MinOMSpd - LocalVar%GenSpeedF ! Current speed error - Region 1.5 PI-control (Below Rated) ! Region 3 minimum pitch angle for state machine LocalVar%VS_Rgn3Pitch = LocalVar%PC_MinPit + CntrPar%PC_Switch + ! Debug Vars + DebugVar%VS_RefSpd = LocalVar%VS_RefSpd + DebugVar%PC_RefSpd = LocalVar%PC_RefSpd + + END SUBROUTINE ComputeVariablesSetpoints !------------------------------------------------------------------------------------------------------------------------------- SUBROUTINE StateMachine(CntrPar, LocalVar) @@ -107,7 +139,7 @@ SUBROUTINE StateMachine(CntrPar, LocalVar) IF (LocalVar%iStatus == 0) THEN ! .TRUE. if we're on the first call to the DLL IF (LocalVar%PitCom(1) >= LocalVar%VS_Rgn3Pitch) THEN ! We are in region 3 - IF (CntrPar%VS_ControlMode == 1) THEN ! Constant power tracking + IF (CntrPar%VS_ConstPower == 1) THEN ! Constant power tracking LocalVar%VS_State = 5 LocalVar%PC_State = 1 ELSE ! Constant torque tracking @@ -131,7 +163,7 @@ SUBROUTINE StateMachine(CntrPar, LocalVar) ! --- Torque control state machine --- IF (LocalVar%PC_PitComT >= LocalVar%VS_Rgn3Pitch) THEN - IF (CntrPar%VS_ControlMode == 1) THEN ! Region 3 + IF (CntrPar%VS_ConstPower == 1) THEN ! Region 3 LocalVar%VS_State = 5 ! Constant power tracking ELSE LocalVar%VS_State = 4 ! Constant torque tracking @@ -248,8 +280,8 @@ SUBROUTINE WindSpeedEstimator(LocalVar, CntrPar, objInst, PerfData, DebugVar, Er ! Initialize recurring values LocalVar%WE%om_r = WE_Inp_Speed LocalVar%WE%v_t = 0.0 - LocalVar%WE%v_m = LocalVar%HorWindV - LocalVar%WE%v_h = LocalVar%HorWindV + LocalVar%WE%v_m = max(LocalVar%HorWindV, 3.0_DbKi) ! avoid divide by 0 below if HorWindV is 0, which some AMRWind setups create + LocalVar%WE%v_h = max(LocalVar%HorWindV, 3.0_DbKi) ! avoid divide by 0 below if HorWindV is 0, which some AMRWind setups create lambda = WE_Inp_Speed * CntrPar%WE_BladeRadius/LocalVar%WE%v_h LocalVar%WE%xh = RESHAPE((/LocalVar%WE%om_r, LocalVar%WE%v_t, LocalVar%WE%v_m/),(/3,1/)) LocalVar%WE%P = RESHAPE((/0.01, 0.0, 0.0, 0.0, 0.01, 0.0, 0.0, 0.0, 1.0/),(/3,3/)) @@ -381,9 +413,7 @@ REAL(DbKi) FUNCTION PitchSaturation(LocalVar, CntrPar, objInst, DebugVar, ErrVar END FUNCTION PitchSaturation !------------------------------------------------------------------------------------------------------------------------------- REAL(DbKi) FUNCTION Shutdown(LocalVar, CntrPar, objInst) - ! PeakShaving defines a minimum blade pitch angle based on a lookup table provided by DISON.IN - ! SS_Mode = 0, No setpoint smoothing - ! SS_Mode = 1, Implement setpoint smoothing + ! Shutdown controller USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, ObjectInstances IMPLICIT NONE ! Inputs @@ -424,4 +454,62 @@ REAL(DbKi) FUNCTION Shutdown(LocalVar, CntrPar, objInst) END FUNCTION Shutdown !------------------------------------------------------------------------------------------------------------------------------- +!------------------------------------------------------------------------------------------------------------------------------- + SUBROUTINE RefSpeedExclusion(LocalVar, CntrPar, objInst, DebugVar) + ! Reference speed exclusion: + ! Changes torque controllerr reference speed to avoid specified frequencies by a prescribed bandwidth + USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, DebugVariables, ObjectInstances + IMPLICIT NONE + ! Inputs + TYPE(ControlParameters), INTENT(IN ) :: CntrPar + TYPE(LocalVariables), INTENT(INOUT) :: LocalVar + TYPE(DebugVariables), INTENT(INOUT) :: DebugVar + TYPE(ObjectInstances), INTENT(INOUT) :: objInst + + + REAL(DbKi) :: VS_RefSpeed_LSS + + ! Get LSS Ref speed + VS_RefSpeed_LSS = LocalVar%VS_RefSpd/CntrPar%WE_GearboxRatio + + IF ((VS_RefSpeed_LSS > CntrPar%TRA_ExclSpeed - CntrPar%TRA_ExclBand / 2) .AND. & + (VS_RefSpeed_LSS < CntrPar%TRA_ExclSpeed + CntrPar%TRA_ExclBand / 2)) THEN + ! In hysteresis zone, hold reference speed + LocalVar%FA_Hist = 1 ! Set negative hysteris if ref < exclusion band + ELSE + LocalVar%FA_Hist = 0 + END IF + + ! Initialize last reference speed state + IF (LocalVar%restart) THEN + ! If starting in hist band + IF (LocalVar%FA_Hist > 0) THEN + IF (VS_RefSpeed_LSS > CntrPar%TRA_ExclSpeed) THEN + LocalVar%TRA_LastRefSpd = CntrPar%TRA_ExclSpeed + CntrPar%TRA_ExclBand / 2 + ELSE + LocalVar%TRA_LastRefSpd = CntrPar%TRA_ExclSpeed - CntrPar%TRA_ExclBand / 2 + ENDIF + ELSE + LocalVar%TRA_LastRefSpd = LocalVar%VS_RefSpd + END IF + END IF + + + IF (LocalVar%FA_Hist > 0) THEN + LocalVar%VS_RefSpd_TRA = LocalVar%TRA_LastRefSpd + ELSE + LocalVar%VS_RefSpd_TRA = LocalVar%VS_RefSpd + END IF + + ! Save last reference speed + LocalVar%TRA_LastRefSpd = LocalVar%VS_RefSpd_TRA + + ! Rate limit reference speed + LocalVar%VS_RefSpd_RL = ratelimit(LocalVar%VS_RefSpd_TRA, -CntrPar%TRA_RateLimit, CntrPar%TRA_RateLimit, LocalVar%DT, LocalVar%restart, LocalVar%rlP,objInst%instRL) + LocalVar%VS_RefSpd = LocalVar%VS_RefSpd_RL * CntrPar%WE_GearboxRatio + + + + END SUBROUTINE RefSpeedExclusion +!------------------------------------------------------------------------------------------------------------------------------- END MODULE ControllerBlocks diff --git a/ROSCO/src/Controllers.f90 b/rosco/controller/src/Controllers.f90 similarity index 87% rename from ROSCO/src/Controllers.f90 rename to rosco/controller/src/Controllers.f90 index 221dd16b..a32c391c 100644 --- a/ROSCO/src/Controllers.f90 +++ b/rosco/controller/src/Controllers.f90 @@ -67,7 +67,7 @@ SUBROUTINE PitchControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) END IF ! Include tower fore-aft tower vibration damping control - IF ((CntrPar%TD_Mode > 0) .OR. (CntrPar%Y_ControlMode == 2)) THEN + IF (CntrPar%TD_Mode > 0) THEN CALL ForeAftDamping(CntrPar, LocalVar, objInst) ELSE LocalVar%FA_PitCom = 0.0 ! THIS IS AN ARRAY!! @@ -84,7 +84,7 @@ SUBROUTINE PitchControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) ! FloatingFeedback IF (CntrPar%Fl_Mode > 0) THEN - LocalVar%Fl_PitCom = FloatingFeedback(LocalVar, CntrPar, objInst) + LocalVar%Fl_PitCom = FloatingFeedback(LocalVar, CntrPar, objInst, ErrVar) DebugVar%FL_PitCom = LocalVar%Fl_PitCom LocalVar%PC_PitComT = LocalVar%PC_PitComT + LocalVar%Fl_PitCom ENDIF @@ -109,6 +109,9 @@ SUBROUTINE PitchControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) IF (CntrPar%IPC_SatMode == 1) THEN LocalVar%PitCom(K) = saturate(LocalVar%PitCom(K), LocalVar%PC_MinPit, CntrPar%PC_MaxPit) END IF + + ! Add ZeroMQ pitch commands + LocalVar%PitCom(K) = LocalVar%PitCom(K) + LocalVar%ZMQ_PitOffset(K) ! Rate limit LocalVar%PitCom(K) = ratelimit(LocalVar%PitCom(K), CntrPar%PC_MinRat, CntrPar%PC_MaxRat, LocalVar%DT, LocalVar%restart, LocalVar%rlP,objInst%instRL,LocalVar%BlPitch(K)) ! Saturate the overall command of blade K using the pitch rate limit @@ -116,11 +119,19 @@ SUBROUTINE PitchControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) ! Open Loop control, use if ! Open loop mode active Using OL blade pitch control - IF ((CntrPar%OL_Mode == 1) .AND. (CntrPar%Ind_BldPitch > 0)) THEN + IF (CntrPar%OL_Mode > 0) THEN IF (LocalVar%Time >= CntrPar%OL_Breakpoints(1)) THEN ! Time > first open loop breakpoint - DO K = 1,LocalVar%NumBl ! Loop through all blades - LocalVar%PitCom(K) = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_BldPitch,LocalVar%Time, ErrVar) - END DO + IF (CntrPar%Ind_BldPitch(1) > 0) THEN + LocalVar%PitCom(1) = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_BldPitch1,LocalVar%Time, ErrVar) + ENDIF + + IF (CntrPar%Ind_BldPitch(2) > 0) THEN + LocalVar%PitCom(2) = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_BldPitch2,LocalVar%Time, ErrVar) + ENDIF + + IF (CntrPar%Ind_BldPitch(3) > 0) THEN + LocalVar%PitCom(3) = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_BldPitch3,LocalVar%Time, ErrVar) + ENDIF ENDIF ENDIF @@ -201,20 +212,25 @@ SUBROUTINE VariableSpeedControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) ! VS_MaxTq = CntrPar%VS_MaxTq ! NJA: May want to boost max torque LocalVar%VS_MaxTq = CntrPar%VS_RtTq ENDIF - + ! Optimal Tip-Speed-Ratio tracking controller IF ((CntrPar%VS_ControlMode == 2) .OR. (CntrPar%VS_ControlMode == 3)) THEN ! Constant Power, update VS_MaxTq - IF (CntrPar%VS_ControlMode == 3) THEN + IF (CntrPar%VS_ConstPower == 1) THEN LocalVar%VS_MaxTq = min((CntrPar%VS_RtPwr/(CntrPar%VS_GenEff/100.0))/LocalVar%GenSpeedF, CntrPar%VS_MaxTq) END IF ! PI controller - LocalVar%GenTq = PIController(LocalVar%VS_SpdErr, CntrPar%VS_KP(1), CntrPar%VS_KI(1), CntrPar%VS_MinTq, LocalVar%VS_MaxTq, LocalVar%DT, LocalVar%VS_LastGenTrq, LocalVar%piP, LocalVar%restart, objInst%instPI) + LocalVar%GenTq = PIController( & + LocalVar%VS_SpdErr, & + CntrPar%VS_KP(1), & + CntrPar%VS_KI(1), & + CntrPar%VS_MinTq, LocalVar%VS_MaxTq, & + LocalVar%DT, LocalVar%VS_LastGenTrq, LocalVar%piP, LocalVar%restart, objInst%instPI) LocalVar%GenTq = saturate(LocalVar%GenTq, CntrPar%VS_MinTq, LocalVar%VS_MaxTq) ! K*Omega^2 control law with PI torque control in transition regions - ELSE + ELSEIF (CntrPar%VS_ControlMode == 1) THEN ! Update PI loops for region 1.5 and 2.5 PI control LocalVar%GenArTq = PIController(LocalVar%VS_SpdErrAr, CntrPar%VS_KP(1), CntrPar%VS_KI(1), CntrPar%VS_MaxOMTq, CntrPar%VS_ArSatTq, LocalVar%DT, CntrPar%VS_MaxOMTq, LocalVar%piP, LocalVar%restart, objInst%instPI) LocalVar%GenBrTq = PIController(LocalVar%VS_SpdErrBr, CntrPar%VS_KP(1), CntrPar%VS_KI(1), CntrPar%VS_MinTq, CntrPar%VS_MinOMTq, LocalVar%DT, CntrPar%VS_MinOMTq, LocalVar%piP, LocalVar%restart, objInst%instPI) @@ -234,6 +250,8 @@ SUBROUTINE VariableSpeedControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) ! Saturate LocalVar%GenTq = saturate(LocalVar%GenTq, CntrPar%VS_MinTq, CntrPar%VS_MaxTq) + ELSE ! VS_ControlMode of 0 + LocalVar%GenTq = 0 ENDIF @@ -244,10 +262,35 @@ SUBROUTINE VariableSpeedControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) LocalVar%GenTq = ratelimit(LocalVar%GenTq, -CntrPar%VS_MaxRat, CntrPar%VS_MaxRat, LocalVar%DT, LocalVar%restart, LocalVar%rlP,objInst%instRL) ! Saturate the command using the torque rate limit ! Open loop torque control - IF ((CntrPar%OL_Mode == 1) .AND. (CntrPar%Ind_GenTq > 0)) THEN + IF ((CntrPar%OL_Mode > 0) .AND. (CntrPar%Ind_GenTq > 0)) THEN + ! Get current OL GenTq, applies for OL_Mode 1 and 2 IF (LocalVar%Time >= CntrPar%OL_Breakpoints(1)) THEN LocalVar%GenTq = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_GenTq,LocalVar%Time,ErrVar) ENDIF + + ! Azimuth tracking control + IF (CntrPar%OL_Mode == 2) THEN + + ! Push, pop and unwrap azimuth buffer + ! Initialize + IF (LocalVar%iStatus == 0) THEN + LocalVar%AzBuffer(1) = LocalVar%Azimuth + LocalVar%AzBuffer(2) = LocalVar%Azimuth + ENDIF + LocalVar%AzBuffer(1) = LocalVar%AzBuffer(2) + LocalVar%AzBuffer(2) = LocalVar%Azimuth + LocalVar%AzBuffer = UNWRAP(LocalVar%AzBuffer, ErrVar) + LocalVar%AzUnwrapped = LocalVar%AzBuffer(2) + + ! Current desired Azimuth, error + LocalVar%OL_Azimuth = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_Azimuth,LocalVar%Time,ErrVar) + LocalVar%AzError = LocalVar%OL_Azimuth - LocalVar%AzUnwrapped + + LocalVar%GenTqAz = PIDController(LocalVar%AzError, CntrPar%RP_Gains(1), CntrPar%RP_Gains(2), CntrPar%RP_Gains(3), CntrPar%RP_Gains(4), -LocalVar%VS_MaxTq * 2, LocalVar%VS_MaxTq * 2, LocalVar%DT, 0.0_DbKi, LocalVar%piP, LocalVar%restart, objInst, LocalVar) + LocalVar%GenTq = LocalVar%GenTq + LocalVar%GenTqAz + + ENDIF + ENDIF ! Reset the value of LocalVar%VS_LastGenTrq to the current values: @@ -264,14 +307,14 @@ SUBROUTINE VariableSpeedControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) END SUBROUTINE VariableSpeedControl !------------------------------------------------------------------------------------------------------------------------------- - SUBROUTINE YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, zmqVar, DebugVar, ErrVar) + SUBROUTINE YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) ! Yaw rate controller ! Y_ControlMode = 0, No yaw control ! Y_ControlMode = 1, Yaw rate control using yaw drive ! TODO: Lots of R2D->D2R, this should be cleaned up. ! TODO: The constant offset implementation is sort of circular here as a setpoint is already being defined in SetVariablesSetpoints. This could also use cleanup - USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances, DebugVariables, ErrorVariables, ZMQ_Variables + USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances, DebugVariables, ErrorVariables REAL(ReKi), INTENT(INOUT) :: avrSWAP(*) ! The swap array, used to pass data to, and receive data from, the DLL controller. @@ -280,7 +323,6 @@ SUBROUTINE YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, zmqVar, DebugVar, TYPE(ObjectInstances), INTENT(INOUT) :: objInst TYPE(DebugVariables), INTENT(INOUT) :: DebugVar TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar - TYPE(ZMQ_Variables), INTENT(INOUT) :: zmqVar ! Allocate Variables REAL(DbKi), SAVE :: NacVaneOffset ! For offset control @@ -309,7 +351,7 @@ SUBROUTINE YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, zmqVar, DebugVar, ! Compute/apply offset IF (CntrPar%ZMQ_Mode == 1) THEN - NacVaneOffset = zmqVar%Yaw_Offset + NacVaneOffset = LocalVar%ZMQ_YawOffset ELSE NacVaneOffset = CntrPar%Y_MErrSet ! (deg) # Offset from setpoint ENDIF @@ -371,6 +413,14 @@ SUBROUTINE YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, zmqVar, DebugVar, ! Output yaw rate command in rad/s avrSWAP(48) = YawRateCom * D2R + ! If using open loop yaw rate control, overwrite controlled output + ! Open loop yaw rate control - control input in rad/s + IF ((CntrPar%OL_Mode > 0) .AND. (CntrPar%Ind_YawRate > 0)) THEN + IF (LocalVar%Time >= CntrPar%OL_Breakpoints(1)) THEN + avrSWAP(48) = interp1d(CntrPar%OL_Breakpoints,CntrPar%OL_YawRate,LocalVar%Time, ErrVar) + ENDIF + ENDIF + ! Save for debug DebugVar%YawRateCom = YawRateCom DebugVar%NacHeadingTarget = NacHeadingTarget @@ -501,28 +551,33 @@ SUBROUTINE ForeAftDamping(CntrPar, LocalVar, objInst) END SUBROUTINE ForeAftDamping !------------------------------------------------------------------------------------------------------------------------------- - REAL(DbKi) FUNCTION FloatingFeedback(LocalVar, CntrPar, objInst) + REAL(DbKi) FUNCTION FloatingFeedback(LocalVar, CntrPar, objInst, ErrVar) ! FloatingFeedback defines a minimum blade pitch angle based on a lookup table provided by DISON.IN ! Fl_Mode = 0, No feedback ! Fl_Mode = 1, Proportional feedback of nacelle velocity (translational) ! Fl_Mode = 2, Proportional feedback of nacelle velocity (rotational) - USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, ObjectInstances + USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, ObjectInstances, ErrorVariables IMPLICIT NONE ! Inputs TYPE(ControlParameters), INTENT(IN) :: CntrPar TYPE(LocalVariables), INTENT(INOUT) :: LocalVar TYPE(ObjectInstances), INTENT(INOUT) :: objInst + TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar ! Allocate Variables REAL(DbKi) :: FA_vel ! Tower fore-aft velocity [m/s] REAL(DbKi) :: NacIMU_FA_vel ! Tower fore-aft pitching velocity [rad/s] + + ! Gain scheduling + LocalVar%Kp_Float = interp1d(CntrPar%Fl_U,CntrPar%Fl_Kp,LocalVar%WE_Vw_F,ErrVar) ! Schedule based on WSE ! Calculate floating contribution to pitch command FA_vel = PIController(LocalVar%FA_AccF, 0.0_DbKi, 1.0_DbKi, -100.0_DbKi , 100.0_DbKi ,LocalVar%DT, 0.0_DbKi, LocalVar%piP, LocalVar%restart, objInst%instPI) ! NJA: should never reach saturation limits.... - NacIMU_FA_vel = PIController(LocalVar%NacIMU_FA_AccF, 0.0_DbKi, 1.0_DbKi, -100.0_DbKi , 100.0_DbKi ,LocalVar%DT, 0.0_DbKi, LocalVar%piP, LocalVar%restart, objInst%instPI) ! NJA: should never reach saturation limits.... + NacIMU_FA_vel = PIController(LocalVar%NacIMU_FA_AccF, 0.0_DbKi, 1.0_DbKi, -100.0_DbKi , 100.0_DbKi ,LocalVar%DT, 0.0_DbKi, LocalVar%piP, LocalVar%restart, objInst%instPI) ! NJA: should never reach saturation limits.... +! Mod made by A. Wright: use the gain scheduled value of KPfloat in the floating fb equ's below (instead of the old value of CntrPar%Fl_Kp), for either value of CntrPar%Fl_Mode... if (CntrPar%Fl_Mode == 1) THEN - FloatingFeedback = (0.0_DbKi - FA_vel) * CntrPar%Fl_Kp !* LocalVar%PC_KP/maxval(CntrPar%PC_GS_KP) + FloatingFeedback = (0.0_DbKi - FA_vel) * LocalVar%Kp_Float ! Mod made by A. Wright: use the gain scheduled value of KPfloat in the floating fb equ's below (instead of the old value of CntrPar%Fl_Kp), for either value of CntrPar%Fl_Mode... ELSEIF (CntrPar%Fl_Mode == 2) THEN - FloatingFeedback = (0.0_DbKi - NacIMU_FA_vel) * CntrPar%Fl_Kp !* LocalVar%PC_KP/maxval(CntrPar%PC_GS_KP) + FloatingFeedback = (0.0_DbKi - NacIMU_FA_vel) *LocalVar%Kp_Float ! Mod made by A. Wright: use the gain scheduled value of KPfloat in the floating fb equ's below (instead of the old value of CntrPar%Fl_Kp), for either value of CntrPar%Fl_Mode... END IF END FUNCTION FloatingFeedback @@ -557,7 +612,7 @@ SUBROUTINE FlapControl(avrSWAP, CntrPar, LocalVar, objInst) LocalVar%Flp_Angle(3) = CntrPar%Flp_Angle ! Initialize controller IF (CntrPar%Flp_Mode == 2) THEN - LocalVar%Flp_Angle(K) = PIIController(RootMyb_VelErr(K), 0 - LocalVar%Flp_Angle(K), CntrPar%Flp_Kp, CntrPar%Flp_Ki, 0.05, -CntrPar%Flp_MaxPit , CntrPar%Flp_MaxPit , LocalVar%DT, 0.0, LocalVar%piP, LocalVar%restart, objInst%instPI) + LocalVar%Flp_Angle(K) = PIIController(RootMyb_VelErr(K), 0 - LocalVar%Flp_Angle(K), CntrPar%Flp_Kp, CntrPar%Flp_Ki, 0.05_DbKi, -CntrPar%Flp_MaxPit , CntrPar%Flp_MaxPit , LocalVar%DT, 0.0_DbKi, LocalVar%piP, LocalVar%restart, objInst%instPI) ENDIF ! Steady flap angle @@ -570,7 +625,7 @@ SUBROUTINE FlapControl(avrSWAP, CntrPar, LocalVar, objInst) ELSEIF (CntrPar%Flp_Mode == 2) THEN DO K = 1,LocalVar%NumBl ! Find flap angle command - includes an integral term to encourage zero flap angle - LocalVar%Flp_Angle(K) = PIIController(-LocalVar%rootMOOPF(K), 0 - LocalVar%Flp_Angle(K), CntrPar%Flp_Kp, CntrPar%Flp_Ki, REAL(0.05,DbKi), -CntrPar%Flp_MaxPit , CntrPar%Flp_MaxPit , LocalVar%DT, 0.0, LocalVar%piP, LocalVar%restart, objInst%instPI) + LocalVar%Flp_Angle(K) = PIIController(-LocalVar%rootMOOPF(K), 0 - LocalVar%Flp_Angle(K), CntrPar%Flp_Kp, CntrPar%Flp_Ki, 0.05_DbKi, -CntrPar%Flp_MaxPit , CntrPar%Flp_MaxPit , LocalVar%DT, 0.0_DbKi, LocalVar%piP, LocalVar%restart, objInst%instPI) ! Saturation Limits LocalVar%Flp_Angle(K) = saturate(LocalVar%Flp_Angle(K), -CntrPar%Flp_MaxPit, CntrPar%Flp_MaxPit) * R2D END DO @@ -656,7 +711,7 @@ SUBROUTINE ActiveWakeControl(CntrPar, LocalVar, DebugVar) IF (CntrPar%AWC_NumModes == 1) THEN AWC_TiltYaw(2) = PI/180*CntrPar%AWC_amp(1)*cos(LocalVar%Time*2*PI*CntrPar%AWC_freq(1) + 2*CntrPar%AWC_clockangle(1)*PI/180) ENDIF - CALL ColemanTransformInverse(AWC_TiltYaw(1), AWC_TiltYaw(2), LocalVar%Azimuth, CntrPar%AWC_harmonic(Imode), 0.0, AWC_angle) + CALL ColemanTransformInverse(AWC_TiltYaw(1), AWC_TiltYaw(2), LocalVar%Azimuth, CntrPar%AWC_harmonic(Imode), REAL(0.0,DbKi), AWC_angle) DO K = 1,LocalVar%NumBl ! Loop through all blades, apply AWC_angle LocalVar%PitCom(K) = LocalVar%PitCom(K) + AWC_angle(K) @@ -689,6 +744,8 @@ SUBROUTINE CableControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) ! Internal Variables Integer(IntKi) :: I_GROUP + CHARACTER(*), PARAMETER :: RoutineName = 'StructuralControl' + IF (CntrPar%CC_Mode == 1) THEN @@ -725,7 +782,7 @@ SUBROUTINE CableControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) DO I_GROUP = 1, CntrPar%CC_Group_N ! Get Actuated deltaL - LocalVar%CC_ActuatedDL(I_GROUP) = SecLPFilter_Vel(LocalVar%CC_DesiredL(I_GROUP),LocalVar%DT,2*PI/CntrPar%CC_ActTau,1.0, & + LocalVar%CC_ActuatedDL(I_GROUP) = SecLPFilter_Vel(LocalVar%CC_DesiredL(I_GROUP),LocalVar%DT,2*PI/CntrPar%CC_ActTau,REAL(1.0,DbKi), & LocalVar%FP,LocalVar%iStatus,LocalVar%restart,objInst%instSecLPFV) ! Integrate @@ -743,10 +800,15 @@ SUBROUTINE CableControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) END DO + ! Add RoutineName to error message + IF (ErrVar%aviFAIL < 0) THEN + ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg) + ENDIF + END SUBROUTINE CableControl !------------------------------------------------------------------------------------------------------------------------------- -SUBROUTINE StructuralControl(avrSWAP, CntrPar, LocalVar, objInst) +SUBROUTINE StructuralControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) ! Cable controller ! StC_Mode = 0, No cable control, this code not executed ! StC_Mode = 1, User-defined cable control @@ -754,20 +816,24 @@ SUBROUTINE StructuralControl(avrSWAP, CntrPar, LocalVar, objInst) ! ! Note that LocalVar%StC_Input() has a fixed max size of 12, which can be increased in rosco_types.yaml ! - USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances + USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances, ErrorVariables REAL(ReKi), INTENT(INOUT) :: avrSWAP(*) ! The swap array, used to pass data to, and receive data from, the DLL controller. TYPE(ControlParameters), INTENT(INOUT) :: CntrPar TYPE(LocalVariables), INTENT(INOUT) :: LocalVar TYPE(ObjectInstances), INTENT(INOUT) :: objInst + TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar + ! Internal Variables Integer(IntKi) :: I_GROUP + CHARACTER(*), PARAMETER :: RoutineName = 'StructuralControl' + IF (CntrPar%StC_Mode == 1) THEN - ! User defined control + ! User defined control, step example IF (LocalVar%Time > 500) THEN ! Step change in input of -4500 N @@ -778,6 +844,18 @@ SUBROUTINE StructuralControl(avrSWAP, CntrPar, LocalVar, objInst) END IF + ELSEIF (CntrPar%StC_Mode == 2) THEN + + + DO I_GROUP = 1,CntrPar%StC_Group_N + IF (CntrPar%Ind_StructControl(I_GROUP) > 0) THEN + LocalVar%StC_Input(I_GROUP) = interp1d(CntrPar%OL_Breakpoints, & + CntrPar%OL_StructControl(I_GROUP,:), & + LocalVar%Time,ErrVar) + ENDIF + ENDDO + + END IF @@ -787,6 +865,11 @@ SUBROUTINE StructuralControl(avrSWAP, CntrPar, LocalVar, objInst) avrSWAP(CntrPar%StC_GroupIndex(I_GROUP)) = LocalVar%StC_Input(I_GROUP) END DO + ! Add RoutineName to error message + IF (ErrVar%aviFAIL < 0) THEN + ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg) + ENDIF + END SUBROUTINE StructuralControl !------------------------------------------------------------------------------------------------------------------------------- END MODULE Controllers diff --git a/ROSCO/src/DISCON.F90 b/rosco/controller/src/DISCON.F90 similarity index 89% rename from ROSCO/src/DISCON.F90 rename to rosco/controller/src/DISCON.F90 index 3b0f7291..4787e19f 100644 --- a/ROSCO/src/DISCON.F90 +++ b/rosco/controller/src/DISCON.F90 @@ -49,7 +49,7 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME CHARACTER(KIND=C_CHAR), INTENT(IN ) :: accINFILE(NINT(avrSWAP(50))) ! The name of the parameter input file CHARACTER(KIND=C_CHAR), INTENT(IN ) :: avcOUTNAME(NINT(avrSWAP(51))) ! OUTNAME (Simulation RootName) CHARACTER(KIND=C_CHAR), INTENT(INOUT) :: avcMSG(NINT(avrSWAP(49))) ! MESSAGE (Message from DLL to simulation code [ErrMsg]) The message which will be displayed by the calling program if aviFAIL <> 0. -CHARACTER(SIZE(avcOUTNAME)-1) :: RootName ! a Fortran version of the input C string (not considered an array here) [subtract 1 for the C null-character] +CHARACTER(SIZE(avcOUTNAME)) :: RootName ! a Fortran version of the input C string (not considered an array here) [subtract 1 for the C null-character] CHARACTER(SIZE(avcMSG)-1) :: ErrMsg ! a Fortran version of the C string argument (not considered an array here) [subtract 1 for the C null-character] TYPE(ControlParameters), SAVE :: CntrPar @@ -58,7 +58,6 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME TYPE(PerformanceData), SAVE :: PerfData TYPE(DebugVariables), SAVE :: DebugVar TYPE(ErrorVariables), SAVE :: ErrVar -TYPE(ZMQ_Variables), SAVE :: zmqVar TYPE(ExtControlType), SAVE :: ExtDLL @@ -72,7 +71,7 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME ! Check for restart IF ( (NINT(avrSWAP(1)) == -9) .AND. (aviFAIL >= 0)) THEN ! Read restart files - CALL ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootName, SIZE(avcOUTNAME), zmqVar, ErrVar) + CALL ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootName, SIZE(avcOUTNAME), ErrVar) IF ( CntrPar%LoggingLevel > 0 ) THEN CALL Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, SIZE(avcOUTNAME)) END IF @@ -82,7 +81,7 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME CALL ReadAvrSWAP(avrSWAP, LocalVar, CntrPar) ! Set Control Parameters -CALL SetParameters(avrSWAP, accINFILE, SIZE(avcMSG), CntrPar, LocalVar, objInst, PerfData, zmqVar, RootName, ErrVar) +CALL SetParameters(avrSWAP, accINFILE, SIZE(avcMSG), CntrPar, LocalVar, objInst, PerfData, RootName, ErrVar) ! Call external controller, if desired IF (CntrPar%Ext_Mode > 0 .AND. ErrVar%aviFAIL >= 0) THEN @@ -90,7 +89,6 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME ! Data from external dll is in ExtDLL%avrSWAP, it's unused in the following code END IF - ! Filter signals CALL PreFilterMeasuredSignals(CntrPar, LocalVar, DebugVar, objInst, ErrVar) @@ -98,19 +96,19 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME IF ((LocalVar%iStatus == -8) .AND. (ErrVar%aviFAIL >= 0)) THEN ! Write restart files CALL WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, SIZE(avcOUTNAME)) ENDIF - IF (zmqVar%ZMQ_Flag) THEN - CALL UpdateZeroMQ(LocalVar, CntrPar, zmqVar, ErrVar) + IF (CntrPar%ZMQ_Mode > 0) THEN + CALL UpdateZeroMQ(LocalVar, CntrPar, ErrVar) ENDIF CALL WindSpeedEstimator(LocalVar, CntrPar, objInst, PerfData, DebugVar, ErrVar) - CALL ComputeVariablesSetpoints(CntrPar, LocalVar, objInst) + CALL ComputeVariablesSetpoints(CntrPar, LocalVar, objInst, DebugVar, ErrVar) CALL StateMachine(CntrPar, LocalVar) CALL SetpointSmoother(LocalVar, CntrPar, objInst) CALL VariableSpeedControl(avrSWAP, CntrPar, LocalVar, objInst, ErrVar) CALL PitchControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) IF (CntrPar%Y_ControlMode > 0) THEN - CALL YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, zmqVar, DebugVar, ErrVar) + CALL YawRateControl(avrSWAP, CntrPar, LocalVar, objInst, DebugVar, ErrVar) END IF IF (CntrPar%Flp_Mode > 0) THEN @@ -124,14 +122,14 @@ SUBROUTINE DISCON(avrSWAP, aviFAIL, accINFILE, avcOUTNAME, avcMSG) BIND (C, NAME ! Structural control IF (CntrPar%StC_Mode > 0) THEN - CALL StructuralControl(avrSWAP,CntrPar,LocalVar, objInst) + CALL StructuralControl(avrSWAP,CntrPar,LocalVar, objInst, ErrVar) END IF IF ( CntrPar%LoggingLevel > 0 ) THEN CALL Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, SIZE(avcOUTNAME)) END IF -ELSEIF ((LocalVar%iStatus == -1) .AND. (zmqVar%ZMQ_Flag)) THEN - CALL UpdateZeroMQ(LocalVar, CntrPar, zmqVar, ErrVar) +ELSEIF ((LocalVar%iStatus == -1) .AND. (CntrPar%ZMQ_Mode > 0)) THEN + CALL UpdateZeroMQ(LocalVar, CntrPar, ErrVar) END IF diff --git a/ROSCO/src/ExtControl.f90 b/rosco/controller/src/ExtControl.f90 similarity index 100% rename from ROSCO/src/ExtControl.f90 rename to rosco/controller/src/ExtControl.f90 diff --git a/ROSCO/src/Filters.f90 b/rosco/controller/src/Filters.f90 similarity index 86% rename from ROSCO/src/Filters.f90 rename to rosco/controller/src/Filters.f90 index 2a5ee24b..0358e7da 100644 --- a/ROSCO/src/Filters.f90 +++ b/rosco/controller/src/Filters.f90 @@ -322,7 +322,7 @@ REAL(DbKi) FUNCTION NotchFilter(InputSignal, DT, omega, betaNum, betaDen, FP, iS END FUNCTION NotchFilter !------------------------------------------------------------------------------------------------------------------------------- SUBROUTINE PreFilterMeasuredSignals(CntrPar, LocalVar, DebugVar, objInst, ErrVar) - ! Prefilter measured wind turbine signals to separate the filtering from the actual control actions + ! Prefilter shared measured wind turbine signals USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, DebugVariables, ObjectInstances, ErrorVariables @@ -332,6 +332,7 @@ SUBROUTINE PreFilterMeasuredSignals(CntrPar, LocalVar, DebugVar, objInst, ErrVar TYPE(ObjectInstances), INTENT(INOUT) :: objInst TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar INTEGER(IntKi) :: K ! Integer used to loop through turbine blades + INTEGER(IntKi) :: n ! Integer used to loop through notch filters ! If there's an error, don't even try to run IF (ErrVar%aviFAIL < 0) THEN @@ -346,36 +347,53 @@ SUBROUTINE PreFilterMeasuredSignals(CntrPar, LocalVar, DebugVar, objInst, ErrVar LocalVar%GenSpeedF = SecLPFilter(LocalVar%GenSpeed, LocalVar%DT, CntrPar%F_LPFCornerFreq, CntrPar%F_LPFDamping, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instSecLPF) ! Second-order low-pass filter on generator speed LocalVar%RotSpeedF = SecLPFilter(LocalVar%RotSpeed, LocalVar%DT, CntrPar%F_LPFCornerFreq, CntrPar%F_LPFDamping, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instSecLPF) ! Second-order low-pass filter on generator speed ENDIF - ! Apply Notch Fitler - IF (CntrPar%F_NotchType == 1 .OR. CntrPar%F_NotchType == 3) THEN - LocalVar%GenSpeedF = NotchFilter(LocalVar%GenSpeedF, LocalVar%DT, CntrPar%F_NotchCornerFreq, CntrPar%F_NotchBetaNumDen(1), CntrPar%F_NotchBetaNumDen(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) - ENDIF + + ! Apply Notch Fitler to Gen Speed + DO n = 1,CntrPar%F_GenSpdNotch_N + LocalVar%GenSpeedF = NotchFilter(LocalVar%GenSpeedF, LocalVar%DT, & + CntrPar%F_NotchFreqs(CntrPar%F_GenSpdNotch_Ind(n)), & + CntrPar%F_NotchBetaNum(CntrPar%F_GenSpdNotch_Ind(n)), & + CntrPar%F_NotchBetaDen(CntrPar%F_GenSpdNotch_Ind(n)), & + LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) + END DO ! Filtering the tower fore-aft acceleration signal - IF (CntrPar%Fl_Mode > 0) THEN - ! Force to start at 0 - IF (LocalVar%iStatus == 0 .AND. LocalVar%Time == 0) THEN - LocalVar%NacIMU_FA_Acc = 0 - LocalVar%FA_Acc = 0 - ENDIF - LocalVar%NacIMU_FA_AccF = SecLPFilter(LocalVar%NacIMU_FA_Acc, LocalVar%DT, CntrPar%F_FlCornerFreq(1), CntrPar%F_FlCornerFreq(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instSecLPF) ! Fixed Damping - LocalVar%FA_AccF = SecLPFilter(LocalVar%FA_Acc, LocalVar%DT, CntrPar%F_FlCornerFreq(1), CntrPar%F_FlCornerFreq(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instSecLPF) ! Fixed Damping - LocalVar%NacIMU_FA_AccF = HPFilter(LocalVar%NacIMU_FA_AccF, LocalVar%DT, CntrPar%F_FlHighPassFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instHPF) - LocalVar%FA_AccF = HPFilter(LocalVar%FA_AccF, LocalVar%DT, CntrPar%F_FlHighPassFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instHPF) + ! Force to start at 0 + IF (LocalVar%iStatus == 0 .AND. LocalVar%Time == 0) THEN + LocalVar%NacIMU_FA_Acc = 0 + LocalVar%FA_Acc = 0 + ENDIF + + ! Low pass + LocalVar%NacIMU_FA_AccF = SecLPFilter(LocalVar%NacIMU_FA_Acc, LocalVar%DT, CntrPar%F_FlCornerFreq(1), CntrPar%F_FlCornerFreq(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instSecLPF) ! Fixed Damping + LocalVar%FA_AccF = SecLPFilter(LocalVar%FA_Acc, LocalVar%DT, CntrPar%F_FlCornerFreq(1), CntrPar%F_FlCornerFreq(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instSecLPF) ! Fixed Damping + + ! High pass + LocalVar%NacIMU_FA_AccF = HPFilter(LocalVar%NacIMU_FA_AccF, LocalVar%DT, CntrPar%F_FlHighPassFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instHPF) + LocalVar%FA_AccF = HPFilter(LocalVar%FA_AccF, LocalVar%DT, CntrPar%F_FlHighPassFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instHPF) + + ! Notch filters + DO n = 1,CntrPar%F_TwrTopNotch_N + LocalVar%NACIMU_FA_AccF = NotchFilter(LocalVar%NacIMU_FA_AccF, LocalVar%DT, & + CntrPar%F_NotchFreqs(CntrPar%F_TwrTopNotch_Ind(n)), & + CntrPar%F_NotchBetaNum(CntrPar%F_TwrTopNotch_Ind(n)), & + CntrPar%F_NotchBetaDen(CntrPar%F_TwrTopNotch_Ind(n)), & + LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) - IF (CntrPar%F_NotchType >= 2) THEN - LocalVar%NACIMU_FA_AccF = NotchFilter(LocalVar%NacIMU_FA_AccF, LocalVar%DT, CntrPar%F_NotchCornerFreq, CntrPar%F_NotchBetaNumDen(1), CntrPar%F_NotchBetaNumDen(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) ! Fixed Damping - LocalVar%FA_AccF = NotchFilter(LocalVar%FA_AccF, LocalVar%DT, CntrPar%F_NotchCornerFreq, CntrPar%F_NotchBetaNumDen(1), CntrPar%F_NotchBetaNumDen(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) ! Fixed Damping - ENDIF - ENDIF + LocalVar%FA_AccF = NotchFilter(LocalVar%FA_AccF, LocalVar%DT, & + CntrPar%F_NotchFreqs(CntrPar%F_TwrTopNotch_Ind(n)), & + CntrPar%F_NotchBetaNum(CntrPar%F_TwrTopNotch_Ind(n)), & + CntrPar%F_NotchBetaDen(CntrPar%F_TwrTopNotch_Ind(n)), & + LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) + END DO ! FA acc for ForeAft damping, condition matches whether it's used in Controllers.f90 - IF ((CntrPar%TD_Mode > 0) .OR. (CntrPar%Y_ControlMode == 2)) THEN + IF (CntrPar%TD_Mode > 0) THEN LocalVar%FA_AccHPF = HPFilter(LocalVar%FA_Acc, LocalVar%DT, CntrPar%FA_HPFCornerFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instHPF) ENDIF ! Filter Wind Speed Estimator Signal - LocalVar%We_Vw_F = LPFilter(LocalVar%WE_Vw, LocalVar%DT,CntrPar%F_WECornerFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instLPF) ! 30 second time constant + LocalVar%We_Vw_F = LPFilter(LocalVar%WE_Vw, LocalVar%DT,CntrPar%F_WECornerFreq, LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instLPF) ! Blade root bending moment for IPC DO K = 1,LocalVar%NumBl @@ -385,8 +403,14 @@ SUBROUTINE PreFilterMeasuredSignals(CntrPar, LocalVar, DebugVar, objInst, ErrVar ELSEIF ( CntrPar%Flp_Mode == 2 ) THEN ! Filter Blade root bending moments LocalVar%RootMOOPF(K) = SecLPFilter(LocalVar%rootMOOP(K),LocalVar%DT, CntrPar%F_FlpCornerFreq(1), CntrPar%F_FlpCornerFreq(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart,objInst%instSecLPF) - LocalVar%RootMOOPF(K) = NotchFilter(LocalVar%RootMOOPF(K), LocalVar%DT, CntrPar%F_NotchCornerFreq, CntrPar%F_NotchBetaNumDen(1), CntrPar%F_NotchBetaNumDen(2), LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) LocalVar%RootMOOPF(K) = HPFilter(LocalVar%rootMOOPF(K),LocalVar%DT, 0.1_DbKi, LocalVar%FP, LocalVar%iStatus, LocalVar%restart,objInst%instHPF) + + ! Use same as generator speed signal because that's how it was before + LocalVar%RootMOOPF(K) = NotchFilter(LocalVar%RootMOOPF(K), LocalVar%DT, & + CntrPar%F_NotchFreqs(CntrPar%F_GenSpdNotch_Ind(n)), & + CntrPar%F_NotchBetaNum(CntrPar%F_GenSpdNotch_Ind(n)), & + CntrPar%F_NotchBetaDen(CntrPar%F_GenSpdNotch_Ind(n)), & + LocalVar%FP, LocalVar%iStatus, LocalVar%restart, objInst%instNotch) ELSE LocalVar%RootMOOPF(K) = LocalVar%rootMOOP(K) ENDIF diff --git a/ROSCO/src/Functions.f90 b/rosco/controller/src/Functions.f90 similarity index 86% rename from ROSCO/src/Functions.f90 rename to rosco/controller/src/Functions.f90 index 4f4a936e..7fac0bc9 100644 --- a/ROSCO/src/Functions.f90 +++ b/rosco/controller/src/Functions.f90 @@ -22,13 +22,14 @@ ! interp1d: 1-d interpolation ! interp2d: 2-d interpolation ! matinv3: 3x3 matrix inverse -! PIController: implement a PI controller +! PIDController: implement a PID controller ! ratelimit: Rate limit signal ! saturate: Saturate signal MODULE Functions USE Constants +USE Filters IMPLICIT NONE @@ -90,7 +91,7 @@ REAL(DbKi) FUNCTION ratelimit(inputSignal, minRate, maxRate, DT, reset, rlP, ins END FUNCTION ratelimit -!------------------------------------------------------------------------------------------------------------------------------- + !------------------------------------------------------------------------------------------------------------------------------- REAL(DbKi) FUNCTION PIController(error, kp, ki, minValue, maxValue, DT, I0, piP, reset, inst) USE ROSCO_Types, ONLY : piParams @@ -130,6 +131,66 @@ REAL(DbKi) FUNCTION PIController(error, kp, ki, minValue, maxValue, DT, I0, piP, END FUNCTION PIController + +!------------------------------------------------------------------------------------------------------------------------------- + REAL(DbKi) FUNCTION PIDController(error, kp, ki, kd, tf, minValue, maxValue, DT, I0, piP, reset, objInst, LocalVar) + USE ROSCO_Types, ONLY : piParams, LocalVariables, ObjectInstances + + ! PI controller, with output saturation + + IMPLICIT NONE + ! Allocate Inputs + REAL(DbKi), INTENT(IN) :: error + REAL(DbKi), INTENT(IN) :: kp + REAL(DbKi), INTENT(IN) :: ki + REAL(DbKi), INTENT(IN) :: kd + REAL(DbKi), INTENT(IN) :: tf + REAL(DbKi), INTENT(IN) :: minValue + REAL(DbKi), INTENT(IN) :: maxValue + REAL(DbKi), INTENT(IN) :: DT + TYPE(ObjectInstances), INTENT(INOUT) :: objInst ! all object instances (PI, filters used here) + TYPE(LocalVariables), INTENT(INOUT) :: LocalVar + + REAL(DbKi), INTENT(IN) :: I0 + TYPE(piParams), INTENT(INOUT) :: piP + LOGICAL, INTENT(IN) :: reset + + ! Allocate local variables + INTEGER(IntKi) :: i ! Counter for making arrays + REAL(DbKi) :: PTerm, DTerm ! Proportional, deriv. terms + REAL(DbKi) :: EFilt ! Filtered error for derivative + + ! Always filter error + EFilt = LPFilter(error, DT, tf, LocalVar%FP, LocalVar%iStatus, reset, objInst%instLPF) + + ! Initialize persistent variables/arrays, and set inital condition for integrator term + IF (reset) THEN + piP%ITerm(objInst%instPI) = I0 + piP%ITermLast(objInst%instPI) = I0 + piP%ELast(objInst%instPI) = 0.0_DbKi + PIDController = I0 + ELSE + ! Proportional + PTerm = kp*error + + ! Integrate and saturate + piP%ITerm(objInst%instPI) = piP%ITerm(objInst%instPI) + DT*ki*error + piP%ITerm(objInst%instPI) = saturate(piP%ITerm(objInst%instPI), minValue, maxValue) + + ! Derivative (filtered) + DTerm = kd * (EFilt - piP%ELast(objInst%instPI)) / DT + + ! Saturate all + PIDController = saturate(PTerm + piP%ITerm(objInst%instPI) + DTerm, minValue, maxValue) + + ! Save lasts + piP%ITermLast(objInst%instPI) = piP%ITerm(objInst%instPI) + piP%ELast(objInst%instPI) = EFilt + END IF + objInst%instPI = objInst%instPI + 1 + + END FUNCTION PIDController + !------------------------------------------------------------------------------------------------------------------------------- REAL(DbKi) FUNCTION PIIController(error, error2, kp, ki, ki2, minValue, maxValue, DT, I0, piP, reset, inst) ! PI controller, with output saturation. @@ -599,5 +660,48 @@ REAL(DbKi) FUNCTION sigma(x, x0, x1, y0, y1, ErrVar) END FUNCTION sigma +!------------------------------------------------------------------------------------------------------------------------------- + FUNCTION unwrap(x, ErrVar) result(y) + ! Unwrap function + ! If difference between signal elements is < -pi, add 2 pi to reset of signal, and the opposite + ! Someday, generalize period and check difference is less than period/2 + USE ROSCO_Types, ONLY : ErrorVariables + IMPLICIT NONE + + ! Inputs + TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar + REAL(DbKi), DIMENSION(:), Intent(IN) :: x + + ! Output + REAL(DbKi), DIMENSION(SIZE(x)) :: y + + ! Local + INTEGER(IntKi) :: i + + CHARACTER(*), PARAMETER :: RoutineName = 'unwrap' + y = x ! set initial + DO i = 2, SIZE(x) + DO while (y(i) - y(i-1) .LE. -PI) + y(i:SIZE(x)) = y(i:SIZE(x)) + 2 * PI + END DO + + DO while (y(i) - y(i-1) .GE. PI) + y(i:SIZE(x)) = y(i:SIZE(x)) - 2 * PI + END DO + END DO + + ! Add RoutineName to error message + IF (ErrVar%aviFAIL < 0) THEN + ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg) + ENDIF + + ! Debug + ! write(400,*) x + ! write(401,*) y + + END FUNCTION unwrap + + +!------------------------------------------------------------------------------------------------------------------------------- END MODULE Functions diff --git a/ROSCO/src/ROSCO_Helpers.f90 b/rosco/controller/src/ROSCO_Helpers.f90 similarity index 99% rename from ROSCO/src/ROSCO_Helpers.f90 rename to rosco/controller/src/ROSCO_Helpers.f90 index 13f9d2d6..68209ce9 100644 --- a/ROSCO/src/ROSCO_Helpers.f90 +++ b/rosco/controller/src/ROSCO_Helpers.f90 @@ -34,7 +34,7 @@ MODULE ROSCO_Helpers ! MODULE PROCEDURE ParseInput_Log ! Parses an LOGICAL from a string. END INTERFACE - INTERFACE ParseAry ! Parse an array of numbers from a string. + INTERFACE ParseAry ! Parse an array of numbers from a string. MODULE PROCEDURE ParseDbAry ! Parse an array of double-precision REAL values. MODULE PROCEDURE ParseInAry ! Parse an array of whole numbers. MODULE PROCEDURE ParseInAry_Opt ! Parse an array of whole numbers. Optional inputs. @@ -258,7 +258,7 @@ subroutine ParseInput_Dbl_Opt(FileLines, VarName, Variable, FileName, ErrVar, Al ErrVar%aviFAIL = -1 ErrVar%ErrMsg = NewLine//' >> A fatal error occurred when parsing data from "' & //TRIM( FileName )//'".'//NewLine// & - ' >> The variable "'//TRIM( Words(2) )//'" was not assigned valid INTEGER value on line #' & + ' >> The variable "'//TRIM( Words(2) )//'" was not assigned valid REAL value on line #' & //TRIM( Int2LStr( CurLine ) )//'.'//NewLine//& ' >> The text being parsed was :'//NewLine//' "'//TRIM( Line )//'"' ENDIF @@ -697,7 +697,7 @@ SUBROUTINE ParseInAry ( Un, LineNum, ParamName, Ary, AryLen, FileName, ErrVar, C ErrVar%aviFAIL = -1 ErrVar%ErrMsg = RoutineName//':A fatal error occurred when parsing data from "' & //TRIM( FileName )//'".'//NewLine// & - ' >> The "'//TRIM( ParamName )//'" array was not assigned valid REAL values on line #' & + ' >> The "'//TRIM( ParamName )//'" array was not assigned valid INTEGER values on line #' & //TRIM( Int2LStr( LineNum ) )//'.'//NewLine//' >> The text being parsed was :'//NewLine & //' "'//TRIM( Line )//'"' RETURN @@ -943,7 +943,7 @@ SUBROUTINE ParseDbAry_Opt ( FileLines, ParamName, Ary, AryLen, FileName, ErrVar, ENDIF Ary = 0 ! Default of allocatable arrays is 0 for now - PRINT *, "ROSCO Warning: Did not find correct size"//TRIM( ParamName )//" in input file. Using default value of [", Ary, "]" + PRINT *, "ROSCO Warning: Did not find correct size "//TRIM( ParamName )//" in input file. Using default value of [", Ary, "]" ENDIF IF (FoundLine) THEN @@ -1014,6 +1014,8 @@ END SUBROUTINE Cleanup END SUBROUTINE ParseDbAry_Opt + + !======================================================================= !> This subroutine checks the data to be parsed to make sure it finds @@ -1491,8 +1493,11 @@ SUBROUTINE GetNewUnit ( UnIn, ErrVar ) INTEGER :: Un ! Unit number LOGICAL :: Opened ! Flag indicating whether or not a file is opened. INTEGER(IntKi), PARAMETER :: StartUnit = 10 ! Starting unit number to check (numbers less than 10 reserved) - INTEGER(IntKi), PARAMETER :: MaxUnit = 99 ! The maximum unit number available (or 10 less than the number of files you want to have open at a time) - + ! NOTE: maximum unit numbers in fortran 90 and later is 2**31-1. However, there are limits within the OS. + ! macos -- 256 (change with ulimit -n) + ! linux -- 1024 (change with ulimit -n) + ! windows -- 512 (not sure how to change -- ADP) + INTEGER(IntKi), PARAMETER :: MaxUnit = 1024 ! The maximum unit number available (or 10 less than the number of files you want to have open at a time) ! Initialize subroutine outputs @@ -1716,4 +1721,4 @@ FUNCTION CurDate( ) END FUNCTION CurDate -END MODULE ROSCO_Helpers \ No newline at end of file +END MODULE ROSCO_Helpers diff --git a/ROSCO/src/ROSCO_IO.f90 b/rosco/controller/src/ROSCO_IO.f90 similarity index 75% rename from ROSCO/src/ROSCO_IO.f90 rename to rosco/controller/src/ROSCO_IO.f90 index fc05e7b1..a4f44283 100644 --- a/ROSCO/src/ROSCO_IO.f90 +++ b/rosco/controller/src/ROSCO_IO.f90 @@ -1,5 +1,5 @@ ! ROSCO IO -! This file is automatically generated by write_registry.py using ROSCO v2.8.0 +! This file is automatically generated by write_registry.py using ROSCO v2.9.0 ! For any modification to the registry, please edit the rosco_types.yaml accordingly MODULE ROSCO_IO @@ -17,7 +17,7 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a TYPE(ObjectInstances), INTENT(INOUT) :: objInst TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar INTEGER(IntKi), INTENT(IN) :: size_avcOUTNAME - CHARACTER(size_avcOUTNAME-1), INTENT(IN) :: RootName + CHARACTER(size_avcOUTNAME), INTENT(IN) :: RootName INTEGER(IntKi) :: Un ! I/O unit for pack/unpack (checkpoint & restart) INTEGER(IntKi) :: I ! Generic index. @@ -32,13 +32,18 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a OPEN(unit=Un, FILE=TRIM(InFile), STATUS='UNKNOWN', FORM='UNFORMATTED' , ACCESS='STREAM', IOSTAT=ErrStat, ACTION='WRITE' ) IF ( ErrStat /= 0 ) THEN - ErrMsg = 'Cannot open file //TRIM( InFile )//. Another program may have locked it for writing.' + ErrVar%aviFAIL = 1 + ErrVar%ErrMsg = 'ROSCO_IO: Cannot open checkpoint file '//TRIM(InFile)//' for writing' ELSE WRITE( Un, IOSTAT=ErrStat) LocalVar%iStatus WRITE( Un, IOSTAT=ErrStat) LocalVar%Time WRITE( Un, IOSTAT=ErrStat) LocalVar%DT + WRITE( Un, IOSTAT=ErrStat) LocalVar%WriteThisStep + WRITE( Un, IOSTAT=ErrStat) LocalVar%n_DT + WRITE( Un, IOSTAT=ErrStat) LocalVar%Time_Last WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_GenPwr + WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_GenPwrF WRITE( Un, IOSTAT=ErrStat) LocalVar%GenSpeed WRITE( Un, IOSTAT=ErrStat) LocalVar%RotSpeed WRITE( Un, IOSTAT=ErrStat) LocalVar%NacHeading @@ -55,6 +60,12 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) LocalVar%BlPitch(3) WRITE( Un, IOSTAT=ErrStat) LocalVar%BlPitchCMeas WRITE( Un, IOSTAT=ErrStat) LocalVar%Azimuth + WRITE( Un, IOSTAT=ErrStat) LocalVar%OL_Azimuth + WRITE( Un, IOSTAT=ErrStat) LocalVar%AzUnwrapped + WRITE( Un, IOSTAT=ErrStat) LocalVar%AzError + WRITE( Un, IOSTAT=ErrStat) LocalVar%GenTqAz + WRITE( Un, IOSTAT=ErrStat) LocalVar%AzBuffer(1) + WRITE( Un, IOSTAT=ErrStat) LocalVar%AzBuffer(2) WRITE( Un, IOSTAT=ErrStat) LocalVar%NumBl WRITE( Un, IOSTAT=ErrStat) LocalVar%FA_Acc WRITE( Un, IOSTAT=ErrStat) LocalVar%NacIMU_FA_Acc @@ -63,6 +74,13 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) LocalVar%FA_PitCom(1) WRITE( Un, IOSTAT=ErrStat) LocalVar%FA_PitCom(2) WRITE( Un, IOSTAT=ErrStat) LocalVar%FA_PitCom(3) + WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd + WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd_TSR + WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd_TRA + WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd_RL + WRITE( Un, IOSTAT=ErrStat) LocalVar%PC_RefSpd + WRITE( Un, IOSTAT=ErrStat) LocalVar%PC_RefSpd_SS + WRITE( Un, IOSTAT=ErrStat) LocalVar%PC_RefSpd_PRC WRITE( Un, IOSTAT=ErrStat) LocalVar%RotSpeedF WRITE( Un, IOSTAT=ErrStat) LocalVar%GenSpeedF WRITE( Un, IOSTAT=ErrStat) LocalVar%GenTq @@ -110,6 +128,7 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) LocalVar%PitComAct(3) WRITE( Un, IOSTAT=ErrStat) LocalVar%SS_DelOmegaF WRITE( Un, IOSTAT=ErrStat) LocalVar%TestType + WRITE( Un, IOSTAT=ErrStat) LocalVar%Kp_Float WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_MaxTq WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_LastGenTrq WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_LastGenPwr @@ -124,10 +143,14 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) LocalVar%WE_VwI WRITE( Un, IOSTAT=ErrStat) LocalVar%WE_VwIdot WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_LastGenTrqF + WRITE( Un, IOSTAT=ErrStat) LocalVar%PRC_WSE_F WRITE( Un, IOSTAT=ErrStat) LocalVar%SD WRITE( Un, IOSTAT=ErrStat) LocalVar%Fl_PitCom WRITE( Un, IOSTAT=ErrStat) LocalVar%NACIMU_FA_AccF WRITE( Un, IOSTAT=ErrStat) LocalVar%FA_AccF + WRITE( Un, IOSTAT=ErrStat) LocalVar%FA_Hist + WRITE( Un, IOSTAT=ErrStat) LocalVar%TRA_LastRefSpd + WRITE( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpeed WRITE( Un, IOSTAT=ErrStat) LocalVar%PtfmTDX WRITE( Un, IOSTAT=ErrStat) LocalVar%PtfmTDY WRITE( Un, IOSTAT=ErrStat) LocalVar%PtfmTDZ @@ -206,6 +229,12 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) LocalVar%AWC_complexangle(1) WRITE( Un, IOSTAT=ErrStat) LocalVar%AWC_complexangle(2) WRITE( Un, IOSTAT=ErrStat) LocalVar%AWC_complexangle(3) + WRITE( Un, IOSTAT=ErrStat) LocalVar%ZMQ_ID + WRITE( Un, IOSTAT=ErrStat) LocalVar%ZMQ_YawOffset + WRITE( Un, IOSTAT=ErrStat) LocalVar%ZMQ_TorqueOffset + WRITE( Un, IOSTAT=ErrStat) LocalVar%ZMQ_PitOffset(1) + WRITE( Un, IOSTAT=ErrStat) LocalVar%ZMQ_PitOffset(2) + WRITE( Un, IOSTAT=ErrStat) LocalVar%ZMQ_PitOffset(3) WRITE( Un, IOSTAT=ErrStat) LocalVar%WE%om_r WRITE( Un, IOSTAT=ErrStat) LocalVar%WE%v_t WRITE( Un, IOSTAT=ErrStat) LocalVar%WE%v_m @@ -263,6 +292,7 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) LocalVar%piP%ITermLast WRITE( Un, IOSTAT=ErrStat) LocalVar%piP%ITerm2 WRITE( Un, IOSTAT=ErrStat) LocalVar%piP%ITermLast2 + WRITE( Un, IOSTAT=ErrStat) LocalVar%piP%ELast WRITE( Un, IOSTAT=ErrStat) LocalVar%rlP%LastSignal WRITE( Un, IOSTAT=ErrStat) objInst%instLPF WRITE( Un, IOSTAT=ErrStat) objInst%instSecLPF @@ -273,20 +303,23 @@ SUBROUTINE WriteRestartFile(LocalVar, CntrPar, ErrVar, objInst, RootName, size_a WRITE( Un, IOSTAT=ErrStat) objInst%instPI WRITE( Un, IOSTAT=ErrStat) objInst%instRL Close ( Un ) + IF ( ErrStat /= 0 ) THEN + ErrVar%aviFAIL = 1 + ErrVar%ErrMsg = 'ROSCO_IO: Error writing checkpoint file.' + ENDIF ENDIF END SUBROUTINE WriteRestartFile -SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootName, size_avcOUTNAME, zmqVar, ErrVar) +SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootName, size_avcOUTNAME, ErrVar) TYPE(LocalVariables), INTENT(INOUT) :: LocalVar TYPE(ControlParameters), INTENT(INOUT) :: CntrPar TYPE(ObjectInstances), INTENT(INOUT) :: objInst TYPE(PerformanceData), INTENT(INOUT) :: PerfData TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar - TYPE(ZMQ_Variables), INTENT(INOUT) :: zmqVar REAL(ReKi), INTENT(IN) :: avrSWAP(*) INTEGER(IntKi), INTENT(IN) :: size_avcOUTNAME - CHARACTER(size_avcOUTNAME-1), INTENT(IN) :: RootName + CHARACTER(size_avcOUTNAME), INTENT(IN) :: RootName INTEGER(IntKi) :: Un ! I/O unit for pack/unpack (checkpoint & restart) INTEGER(IntKi) :: I ! Generic index. @@ -301,13 +334,18 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa OPEN(unit=Un, FILE=TRIM(InFile), STATUS='UNKNOWN', FORM='UNFORMATTED' , ACCESS='STREAM', IOSTAT=ErrStat, ACTION='READ' ) IF ( ErrStat /= 0 ) THEN - ErrMsg = 'Cannot open file //TRIM( InFile )//. Another program may have locked it for writing.' + ErrVar%aviFAIL = 1 + ErrVar%ErrMsg = 'ROSCO_IO: Cannot open checkpoint file '//TRIM(InFile)//' for reading' ELSE READ( Un, IOSTAT=ErrStat) LocalVar%iStatus READ( Un, IOSTAT=ErrStat) LocalVar%Time READ( Un, IOSTAT=ErrStat) LocalVar%DT + READ( Un, IOSTAT=ErrStat) LocalVar%WriteThisStep + READ( Un, IOSTAT=ErrStat) LocalVar%n_DT + READ( Un, IOSTAT=ErrStat) LocalVar%Time_Last READ( Un, IOSTAT=ErrStat) LocalVar%VS_GenPwr + READ( Un, IOSTAT=ErrStat) LocalVar%VS_GenPwrF READ( Un, IOSTAT=ErrStat) LocalVar%GenSpeed READ( Un, IOSTAT=ErrStat) LocalVar%RotSpeed READ( Un, IOSTAT=ErrStat) LocalVar%NacHeading @@ -324,6 +362,12 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) LocalVar%BlPitch(3) READ( Un, IOSTAT=ErrStat) LocalVar%BlPitchCMeas READ( Un, IOSTAT=ErrStat) LocalVar%Azimuth + READ( Un, IOSTAT=ErrStat) LocalVar%OL_Azimuth + READ( Un, IOSTAT=ErrStat) LocalVar%AzUnwrapped + READ( Un, IOSTAT=ErrStat) LocalVar%AzError + READ( Un, IOSTAT=ErrStat) LocalVar%GenTqAz + READ( Un, IOSTAT=ErrStat) LocalVar%AzBuffer(1) + READ( Un, IOSTAT=ErrStat) LocalVar%AzBuffer(2) READ( Un, IOSTAT=ErrStat) LocalVar%NumBl READ( Un, IOSTAT=ErrStat) LocalVar%FA_Acc READ( Un, IOSTAT=ErrStat) LocalVar%NacIMU_FA_Acc @@ -332,6 +376,13 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) LocalVar%FA_PitCom(1) READ( Un, IOSTAT=ErrStat) LocalVar%FA_PitCom(2) READ( Un, IOSTAT=ErrStat) LocalVar%FA_PitCom(3) + READ( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd + READ( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd_TSR + READ( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd_TRA + READ( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpd_RL + READ( Un, IOSTAT=ErrStat) LocalVar%PC_RefSpd + READ( Un, IOSTAT=ErrStat) LocalVar%PC_RefSpd_SS + READ( Un, IOSTAT=ErrStat) LocalVar%PC_RefSpd_PRC READ( Un, IOSTAT=ErrStat) LocalVar%RotSpeedF READ( Un, IOSTAT=ErrStat) LocalVar%GenSpeedF READ( Un, IOSTAT=ErrStat) LocalVar%GenTq @@ -379,6 +430,7 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) LocalVar%PitComAct(3) READ( Un, IOSTAT=ErrStat) LocalVar%SS_DelOmegaF READ( Un, IOSTAT=ErrStat) LocalVar%TestType + READ( Un, IOSTAT=ErrStat) LocalVar%Kp_Float READ( Un, IOSTAT=ErrStat) LocalVar%VS_MaxTq READ( Un, IOSTAT=ErrStat) LocalVar%VS_LastGenTrq READ( Un, IOSTAT=ErrStat) LocalVar%VS_LastGenPwr @@ -393,10 +445,14 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) LocalVar%WE_VwI READ( Un, IOSTAT=ErrStat) LocalVar%WE_VwIdot READ( Un, IOSTAT=ErrStat) LocalVar%VS_LastGenTrqF + READ( Un, IOSTAT=ErrStat) LocalVar%PRC_WSE_F READ( Un, IOSTAT=ErrStat) LocalVar%SD READ( Un, IOSTAT=ErrStat) LocalVar%Fl_PitCom READ( Un, IOSTAT=ErrStat) LocalVar%NACIMU_FA_AccF READ( Un, IOSTAT=ErrStat) LocalVar%FA_AccF + READ( Un, IOSTAT=ErrStat) LocalVar%FA_Hist + READ( Un, IOSTAT=ErrStat) LocalVar%TRA_LastRefSpd + READ( Un, IOSTAT=ErrStat) LocalVar%VS_RefSpeed READ( Un, IOSTAT=ErrStat) LocalVar%PtfmTDX READ( Un, IOSTAT=ErrStat) LocalVar%PtfmTDY READ( Un, IOSTAT=ErrStat) LocalVar%PtfmTDZ @@ -476,6 +532,12 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) LocalVar%AWC_complexangle(1) READ( Un, IOSTAT=ErrStat) LocalVar%AWC_complexangle(2) READ( Un, IOSTAT=ErrStat) LocalVar%AWC_complexangle(3) + READ( Un, IOSTAT=ErrStat) LocalVar%ZMQ_ID + READ( Un, IOSTAT=ErrStat) LocalVar%ZMQ_YawOffset + READ( Un, IOSTAT=ErrStat) LocalVar%ZMQ_TorqueOffset + READ( Un, IOSTAT=ErrStat) LocalVar%ZMQ_PitOffset(1) + READ( Un, IOSTAT=ErrStat) LocalVar%ZMQ_PitOffset(2) + READ( Un, IOSTAT=ErrStat) LocalVar%ZMQ_PitOffset(3) READ( Un, IOSTAT=ErrStat) LocalVar%WE%om_r READ( Un, IOSTAT=ErrStat) LocalVar%WE%v_t READ( Un, IOSTAT=ErrStat) LocalVar%WE%v_m @@ -533,6 +595,7 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) LocalVar%piP%ITermLast READ( Un, IOSTAT=ErrStat) LocalVar%piP%ITerm2 READ( Un, IOSTAT=ErrStat) LocalVar%piP%ITermLast2 + READ( Un, IOSTAT=ErrStat) LocalVar%piP%ELast READ( Un, IOSTAT=ErrStat) LocalVar%rlP%LastSignal READ( Un, IOSTAT=ErrStat) objInst%instLPF READ( Un, IOSTAT=ErrStat) objInst%instSecLPF @@ -543,9 +606,13 @@ SUBROUTINE ReadRestartFile(avrSWAP, LocalVar, CntrPar, objInst, PerfData, RootNa READ( Un, IOSTAT=ErrStat) objInst%instPI READ( Un, IOSTAT=ErrStat) objInst%instRL Close ( Un ) + IF ( ErrStat /= 0 ) THEN + ErrVar%aviFAIL = 1 + ErrVar%ErrMsg = 'ROSCO_IO: Error reading checkpoint file.' + ENDIF ENDIF ! Read Parameter files - CALL ReadControlParameterFileSub(CntrPar, zmqVar, LocalVar%ACC_INFILE, LocalVar%ACC_INFILE_SIZE, RootName, ErrVar) + CALL ReadControlParameterFileSub(CntrPar, LocalVar, LocalVar%ACC_INFILE, LocalVar%ACC_INFILE_SIZE, RootName, ErrVar) IF (CntrPar%WE_Mode > 0) THEN CALL READCpFile(CntrPar, PerfData, ErrVar) ENDIF @@ -568,7 +635,7 @@ SUBROUTINE Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, size_av INTEGER(IntKi), SAVE :: UnDb2 ! I/O unit for the debugging information, avrSWAP INTEGER(IntKi), SAVE :: UnDb3 ! I/O unit for the debugging information, avrSWAP REAL(ReKi), INTENT(INOUT) :: avrSWAP(*) ! The swap array, used to pass data to, and receive data from, the DLL controller. - CHARACTER(size_avcOUTNAME-1), INTENT(IN) :: RootName ! a Fortran version of the input C string (not considered an array here) [subtract 1 for the C null-character] + CHARACTER(size_avcOUTNAME), INTENT(IN) :: RootName ! a Fortran version of the input C string (not considered an array here) [subtract 1 for the C null-character] CHARACTER(200) :: Version ! git version of ROSCO CHARACTER(15), ALLOCATABLE :: DebugOutStrings(:), DebugOutUnits(:) @@ -583,7 +650,7 @@ SUBROUTINE Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, size_av CHARACTER(15), ALLOCATABLE :: LocalVarOutStrings(:) REAL(DbKi), ALLOCATABLE :: LocalVarOutData(:) - nDebugOuts = 24 + nDebugOuts = 26 Allocate(DebugOutData(nDebugOuts)) Allocate(DebugOutStrings(nDebugOuts)) Allocate(DebugOutUnits(nDebugOuts)) @@ -611,123 +678,154 @@ SUBROUTINE Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, size_av DebugOutData(22) = DebugVar%NacVaneOffset DebugOutData(23) = DebugVar%Yaw_Err DebugOutData(24) = DebugVar%YawState + DebugOutData(25) = DebugVar%VS_RefSpd + DebugOutData(26) = DebugVar%PC_RefSpd DebugOutStrings = [CHARACTER(15) :: 'WE_Cp', 'WE_b', 'WE_w', 'WE_t', 'WE_Vm', & 'WE_Vt', 'WE_Vw', 'WE_lambda', 'PC_PICommand', 'GenSpeedF', & 'RotSpeedF', 'NacIMU_FA_AccF', 'FA_AccF', 'Fl_PitCom', 'PC_MinPit', & 'axisTilt_1P', 'axisYaw_1P', 'axisTilt_2P', 'axisYaw_2P', 'YawRateCom', & - 'NacHeadingTarget', 'NacVaneOffset', 'Yaw_Err', 'YawState'] + 'NacHeadingTarget', 'NacVaneOffset', 'Yaw_Err', 'YawState', 'VS_RefSpd', & + 'PC_RefSpd'] DebugOutUnits = [CHARACTER(15) :: '[-]', '[-]', '[-]', '[-]', '[m/s]', & '[m/s]', '[m/s]', '[rad]', '[rad]', '[rad/s]', & '[rad/s]', '[rad/s]', '[m/s]', '[rad]', '[rad]', & '[N/A]', '[N/A]', '[N/A]', '[N/A]', '[rad/s]', & - '[deg]', '[deg]', '[deg]', '[N/A]'] - nLocalVars = 100 + '[deg]', '[deg]', '[deg]', '[N/A]', '[rad/s]', & + '[rad/s]'] + nLocalVars = 124 Allocate(LocalVarOutData(nLocalVars)) Allocate(LocalVarOutStrings(nLocalVars)) LocalVarOutData(1) = LocalVar%iStatus LocalVarOutData(2) = LocalVar%Time LocalVarOutData(3) = LocalVar%DT - LocalVarOutData(4) = LocalVar%VS_GenPwr - LocalVarOutData(5) = LocalVar%GenSpeed - LocalVarOutData(6) = LocalVar%RotSpeed - LocalVarOutData(7) = LocalVar%NacHeading - LocalVarOutData(8) = LocalVar%NacVane - LocalVarOutData(9) = LocalVar%HorWindV - LocalVarOutData(10) = LocalVar%rootMOOP(1) - LocalVarOutData(11) = LocalVar%rootMOOPF(1) - LocalVarOutData(12) = LocalVar%BlPitch(1) - LocalVarOutData(13) = LocalVar%BlPitchCMeas - LocalVarOutData(14) = LocalVar%Azimuth - LocalVarOutData(15) = LocalVar%NumBl - LocalVarOutData(16) = LocalVar%FA_Acc - LocalVarOutData(17) = LocalVar%NacIMU_FA_Acc - LocalVarOutData(18) = LocalVar%FA_AccHPF - LocalVarOutData(19) = LocalVar%FA_AccHPFI - LocalVarOutData(20) = LocalVar%FA_PitCom(1) - LocalVarOutData(21) = LocalVar%RotSpeedF - LocalVarOutData(22) = LocalVar%GenSpeedF - LocalVarOutData(23) = LocalVar%GenTq - LocalVarOutData(24) = LocalVar%GenTqMeas - LocalVarOutData(25) = LocalVar%GenArTq - LocalVarOutData(26) = LocalVar%GenBrTq - LocalVarOutData(27) = LocalVar%IPC_PitComF(1) - LocalVarOutData(28) = LocalVar%PC_KP - LocalVarOutData(29) = LocalVar%PC_KI - LocalVarOutData(30) = LocalVar%PC_KD - LocalVarOutData(31) = LocalVar%PC_TF - LocalVarOutData(32) = LocalVar%PC_MaxPit - LocalVarOutData(33) = LocalVar%PC_MinPit - LocalVarOutData(34) = LocalVar%PC_PitComT - LocalVarOutData(35) = LocalVar%PC_PitComT_Last - LocalVarOutData(36) = LocalVar%PC_PitComTF - LocalVarOutData(37) = LocalVar%PC_PitComT_IPC(1) - LocalVarOutData(38) = LocalVar%PC_PwrErr - LocalVarOutData(39) = LocalVar%PC_SpdErr - LocalVarOutData(40) = LocalVar%IPC_AxisTilt_1P - LocalVarOutData(41) = LocalVar%IPC_AxisYaw_1P - LocalVarOutData(42) = LocalVar%IPC_AxisTilt_2P - LocalVarOutData(43) = LocalVar%IPC_AxisYaw_2P - LocalVarOutData(44) = LocalVar%axisTilt_1P - LocalVarOutData(45) = LocalVar%axisYaw_1P - LocalVarOutData(46) = LocalVar%axisYawF_1P - LocalVarOutData(47) = LocalVar%axisTilt_2P - LocalVarOutData(48) = LocalVar%axisYaw_2P - LocalVarOutData(49) = LocalVar%axisYawF_2P - LocalVarOutData(50) = LocalVar%IPC_KI(1) - LocalVarOutData(51) = LocalVar%IPC_KP(1) - LocalVarOutData(52) = LocalVar%IPC_IntSat - LocalVarOutData(53) = LocalVar%PC_State - LocalVarOutData(54) = LocalVar%PitCom(1) - LocalVarOutData(55) = LocalVar%PitComAct(1) - LocalVarOutData(56) = LocalVar%SS_DelOmegaF - LocalVarOutData(57) = LocalVar%TestType - LocalVarOutData(58) = LocalVar%VS_MaxTq - LocalVarOutData(59) = LocalVar%VS_LastGenTrq - LocalVarOutData(60) = LocalVar%VS_LastGenPwr - LocalVarOutData(61) = LocalVar%VS_MechGenPwr - LocalVarOutData(62) = LocalVar%VS_SpdErrAr - LocalVarOutData(63) = LocalVar%VS_SpdErrBr - LocalVarOutData(64) = LocalVar%VS_SpdErr - LocalVarOutData(65) = LocalVar%VS_State - LocalVarOutData(66) = LocalVar%VS_Rgn3Pitch - LocalVarOutData(67) = LocalVar%WE_Vw - LocalVarOutData(68) = LocalVar%WE_Vw_F - LocalVarOutData(69) = LocalVar%WE_VwI - LocalVarOutData(70) = LocalVar%WE_VwIdot - LocalVarOutData(71) = LocalVar%VS_LastGenTrqF - LocalVarOutData(72) = LocalVar%Fl_PitCom - LocalVarOutData(73) = LocalVar%NACIMU_FA_AccF - LocalVarOutData(74) = LocalVar%FA_AccF - LocalVarOutData(75) = LocalVar%PtfmTDX - LocalVarOutData(76) = LocalVar%PtfmTDY - LocalVarOutData(77) = LocalVar%PtfmTDZ - LocalVarOutData(78) = LocalVar%PtfmRDX - LocalVarOutData(79) = LocalVar%PtfmRDY - LocalVarOutData(80) = LocalVar%PtfmRDZ - LocalVarOutData(81) = LocalVar%PtfmTVX - LocalVarOutData(82) = LocalVar%PtfmTVY - LocalVarOutData(83) = LocalVar%PtfmTVZ - LocalVarOutData(84) = LocalVar%PtfmRVX - LocalVarOutData(85) = LocalVar%PtfmRVY - LocalVarOutData(86) = LocalVar%PtfmRVZ - LocalVarOutData(87) = LocalVar%PtfmTAX - LocalVarOutData(88) = LocalVar%PtfmTAY - LocalVarOutData(89) = LocalVar%PtfmTAZ - LocalVarOutData(90) = LocalVar%PtfmRAX - LocalVarOutData(91) = LocalVar%PtfmRAY - LocalVarOutData(92) = LocalVar%PtfmRAZ - LocalVarOutData(93) = LocalVar%CC_DesiredL(1) - LocalVarOutData(94) = LocalVar%CC_ActuatedL(1) - LocalVarOutData(95) = LocalVar%CC_ActuatedDL(1) - LocalVarOutData(96) = LocalVar%StC_Input(1) - LocalVarOutData(97) = LocalVar%Flp_Angle(1) - LocalVarOutData(98) = LocalVar%RootMyb_Last(1) - LocalVarOutData(99) = LocalVar%ACC_INFILE_SIZE - LocalVarOutData(100) = LocalVar%AWC_complexangle(1) - LocalVarOutStrings = [CHARACTER(15) :: 'iStatus', 'Time', 'DT', 'VS_GenPwr', 'GenSpeed', & - 'RotSpeed', 'NacHeading', 'NacVane', 'HorWindV', 'rootMOOP', & - 'rootMOOPF', 'BlPitch', 'BlPitchCMeas', 'Azimuth', 'NumBl', & - 'FA_Acc', 'NacIMU_FA_Acc', 'FA_AccHPF', 'FA_AccHPFI', 'FA_PitCom', & + LocalVarOutData(4) = LocalVar%n_DT + LocalVarOutData(5) = LocalVar%Time_Last + LocalVarOutData(6) = LocalVar%VS_GenPwr + LocalVarOutData(7) = LocalVar%VS_GenPwrF + LocalVarOutData(8) = LocalVar%GenSpeed + LocalVarOutData(9) = LocalVar%RotSpeed + LocalVarOutData(10) = LocalVar%NacHeading + LocalVarOutData(11) = LocalVar%NacVane + LocalVarOutData(12) = LocalVar%HorWindV + LocalVarOutData(13) = LocalVar%rootMOOP(1) + LocalVarOutData(14) = LocalVar%rootMOOPF(1) + LocalVarOutData(15) = LocalVar%BlPitch(1) + LocalVarOutData(16) = LocalVar%BlPitchCMeas + LocalVarOutData(17) = LocalVar%Azimuth + LocalVarOutData(18) = LocalVar%OL_Azimuth + LocalVarOutData(19) = LocalVar%AzUnwrapped + LocalVarOutData(20) = LocalVar%AzError + LocalVarOutData(21) = LocalVar%GenTqAz + LocalVarOutData(22) = LocalVar%AzBuffer(1) + LocalVarOutData(23) = LocalVar%NumBl + LocalVarOutData(24) = LocalVar%FA_Acc + LocalVarOutData(25) = LocalVar%NacIMU_FA_Acc + LocalVarOutData(26) = LocalVar%FA_AccHPF + LocalVarOutData(27) = LocalVar%FA_AccHPFI + LocalVarOutData(28) = LocalVar%FA_PitCom(1) + LocalVarOutData(29) = LocalVar%VS_RefSpd + LocalVarOutData(30) = LocalVar%VS_RefSpd_TSR + LocalVarOutData(31) = LocalVar%VS_RefSpd_TRA + LocalVarOutData(32) = LocalVar%VS_RefSpd_RL + LocalVarOutData(33) = LocalVar%PC_RefSpd + LocalVarOutData(34) = LocalVar%PC_RefSpd_SS + LocalVarOutData(35) = LocalVar%PC_RefSpd_PRC + LocalVarOutData(36) = LocalVar%RotSpeedF + LocalVarOutData(37) = LocalVar%GenSpeedF + LocalVarOutData(38) = LocalVar%GenTq + LocalVarOutData(39) = LocalVar%GenTqMeas + LocalVarOutData(40) = LocalVar%GenArTq + LocalVarOutData(41) = LocalVar%GenBrTq + LocalVarOutData(42) = LocalVar%IPC_PitComF(1) + LocalVarOutData(43) = LocalVar%PC_KP + LocalVarOutData(44) = LocalVar%PC_KI + LocalVarOutData(45) = LocalVar%PC_KD + LocalVarOutData(46) = LocalVar%PC_TF + LocalVarOutData(47) = LocalVar%PC_MaxPit + LocalVarOutData(48) = LocalVar%PC_MinPit + LocalVarOutData(49) = LocalVar%PC_PitComT + LocalVarOutData(50) = LocalVar%PC_PitComT_Last + LocalVarOutData(51) = LocalVar%PC_PitComTF + LocalVarOutData(52) = LocalVar%PC_PitComT_IPC(1) + LocalVarOutData(53) = LocalVar%PC_PwrErr + LocalVarOutData(54) = LocalVar%PC_SpdErr + LocalVarOutData(55) = LocalVar%IPC_AxisTilt_1P + LocalVarOutData(56) = LocalVar%IPC_AxisYaw_1P + LocalVarOutData(57) = LocalVar%IPC_AxisTilt_2P + LocalVarOutData(58) = LocalVar%IPC_AxisYaw_2P + LocalVarOutData(59) = LocalVar%axisTilt_1P + LocalVarOutData(60) = LocalVar%axisYaw_1P + LocalVarOutData(61) = LocalVar%axisYawF_1P + LocalVarOutData(62) = LocalVar%axisTilt_2P + LocalVarOutData(63) = LocalVar%axisYaw_2P + LocalVarOutData(64) = LocalVar%axisYawF_2P + LocalVarOutData(65) = LocalVar%IPC_KI(1) + LocalVarOutData(66) = LocalVar%IPC_KP(1) + LocalVarOutData(67) = LocalVar%IPC_IntSat + LocalVarOutData(68) = LocalVar%PC_State + LocalVarOutData(69) = LocalVar%PitCom(1) + LocalVarOutData(70) = LocalVar%PitComAct(1) + LocalVarOutData(71) = LocalVar%SS_DelOmegaF + LocalVarOutData(72) = LocalVar%TestType + LocalVarOutData(73) = LocalVar%Kp_Float + LocalVarOutData(74) = LocalVar%VS_MaxTq + LocalVarOutData(75) = LocalVar%VS_LastGenTrq + LocalVarOutData(76) = LocalVar%VS_LastGenPwr + LocalVarOutData(77) = LocalVar%VS_MechGenPwr + LocalVarOutData(78) = LocalVar%VS_SpdErrAr + LocalVarOutData(79) = LocalVar%VS_SpdErrBr + LocalVarOutData(80) = LocalVar%VS_SpdErr + LocalVarOutData(81) = LocalVar%VS_State + LocalVarOutData(82) = LocalVar%VS_Rgn3Pitch + LocalVarOutData(83) = LocalVar%WE_Vw + LocalVarOutData(84) = LocalVar%WE_Vw_F + LocalVarOutData(85) = LocalVar%WE_VwI + LocalVarOutData(86) = LocalVar%WE_VwIdot + LocalVarOutData(87) = LocalVar%VS_LastGenTrqF + LocalVarOutData(88) = LocalVar%PRC_WSE_F + LocalVarOutData(89) = LocalVar%Fl_PitCom + LocalVarOutData(90) = LocalVar%NACIMU_FA_AccF + LocalVarOutData(91) = LocalVar%FA_AccF + LocalVarOutData(92) = LocalVar%FA_Hist + LocalVarOutData(93) = LocalVar%TRA_LastRefSpd + LocalVarOutData(94) = LocalVar%VS_RefSpeed + LocalVarOutData(95) = LocalVar%PtfmTDX + LocalVarOutData(96) = LocalVar%PtfmTDY + LocalVarOutData(97) = LocalVar%PtfmTDZ + LocalVarOutData(98) = LocalVar%PtfmRDX + LocalVarOutData(99) = LocalVar%PtfmRDY + LocalVarOutData(100) = LocalVar%PtfmRDZ + LocalVarOutData(101) = LocalVar%PtfmTVX + LocalVarOutData(102) = LocalVar%PtfmTVY + LocalVarOutData(103) = LocalVar%PtfmTVZ + LocalVarOutData(104) = LocalVar%PtfmRVX + LocalVarOutData(105) = LocalVar%PtfmRVY + LocalVarOutData(106) = LocalVar%PtfmRVZ + LocalVarOutData(107) = LocalVar%PtfmTAX + LocalVarOutData(108) = LocalVar%PtfmTAY + LocalVarOutData(109) = LocalVar%PtfmTAZ + LocalVarOutData(110) = LocalVar%PtfmRAX + LocalVarOutData(111) = LocalVar%PtfmRAY + LocalVarOutData(112) = LocalVar%PtfmRAZ + LocalVarOutData(113) = LocalVar%CC_DesiredL(1) + LocalVarOutData(114) = LocalVar%CC_ActuatedL(1) + LocalVarOutData(115) = LocalVar%CC_ActuatedDL(1) + LocalVarOutData(116) = LocalVar%StC_Input(1) + LocalVarOutData(117) = LocalVar%Flp_Angle(1) + LocalVarOutData(118) = LocalVar%RootMyb_Last(1) + LocalVarOutData(119) = LocalVar%ACC_INFILE_SIZE + LocalVarOutData(120) = LocalVar%AWC_complexangle(1) + LocalVarOutData(121) = LocalVar%ZMQ_ID + LocalVarOutData(122) = LocalVar%ZMQ_YawOffset + LocalVarOutData(123) = LocalVar%ZMQ_TorqueOffset + LocalVarOutData(124) = LocalVar%ZMQ_PitOffset(1) + LocalVarOutStrings = [CHARACTER(15) :: 'iStatus', 'Time', 'DT', 'n_DT', 'Time_Last', & + 'VS_GenPwr', 'VS_GenPwrF', 'GenSpeed', 'RotSpeed', 'NacHeading', & + 'NacVane', 'HorWindV', 'rootMOOP', 'rootMOOPF', 'BlPitch', & + 'BlPitchCMeas', 'Azimuth', 'OL_Azimuth', 'AzUnwrapped', 'AzError', & + 'GenTqAz', 'AzBuffer', 'NumBl', 'FA_Acc', 'NacIMU_FA_Acc', & + 'FA_AccHPF', 'FA_AccHPFI', 'FA_PitCom', 'VS_RefSpd', 'VS_RefSpd_TSR', & + 'VS_RefSpd_TRA', 'VS_RefSpd_RL', 'PC_RefSpd', 'PC_RefSpd_SS', 'PC_RefSpd_PRC', & 'RotSpeedF', 'GenSpeedF', 'GenTq', 'GenTqMeas', 'GenArTq', & 'GenBrTq', 'IPC_PitComF', 'PC_KP', 'PC_KI', 'PC_KD', & 'PC_TF', 'PC_MaxPit', 'PC_MinPit', 'PC_PitComT', 'PC_PitComT_Last', & @@ -735,16 +833,17 @@ SUBROUTINE Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, size_av 'IPC_AxisYaw_1P', 'IPC_AxisTilt_2P', 'IPC_AxisYaw_2P', 'axisTilt_1P', 'axisYaw_1P', & 'axisYawF_1P', 'axisTilt_2P', 'axisYaw_2P', 'axisYawF_2P', 'IPC_KI', & 'IPC_KP', 'IPC_IntSat', 'PC_State', 'PitCom', 'PitComAct', & - 'SS_DelOmegaF', 'TestType', 'VS_MaxTq', 'VS_LastGenTrq', 'VS_LastGenPwr', & - 'VS_MechGenPwr', 'VS_SpdErrAr', 'VS_SpdErrBr', 'VS_SpdErr', 'VS_State', & - 'VS_Rgn3Pitch', 'WE_Vw', 'WE_Vw_F', 'WE_VwI', 'WE_VwIdot', & - 'VS_LastGenTrqF', 'Fl_PitCom', 'NACIMU_FA_AccF', 'FA_AccF', 'PtfmTDX', & + 'SS_DelOmegaF', 'TestType', 'Kp_Float', 'VS_MaxTq', 'VS_LastGenTrq', & + 'VS_LastGenPwr', 'VS_MechGenPwr', 'VS_SpdErrAr', 'VS_SpdErrBr', 'VS_SpdErr', & + 'VS_State', 'VS_Rgn3Pitch', 'WE_Vw', 'WE_Vw_F', 'WE_VwI', & + 'WE_VwIdot', 'VS_LastGenTrqF', 'PRC_WSE_F', 'Fl_PitCom', 'NACIMU_FA_AccF', & + 'FA_AccF', 'FA_Hist', 'TRA_LastRefSpd', 'VS_RefSpeed', 'PtfmTDX', & 'PtfmTDY', 'PtfmTDZ', 'PtfmRDX', 'PtfmRDY', 'PtfmRDZ', & 'PtfmTVX', 'PtfmTVY', 'PtfmTVZ', 'PtfmRVX', 'PtfmRVY', & 'PtfmRVZ', 'PtfmTAX', 'PtfmTAY', 'PtfmTAZ', 'PtfmRAX', & 'PtfmRAY', 'PtfmRAZ', 'CC_DesiredL', 'CC_ActuatedL', 'CC_ActuatedDL', & - 'StC_Input', 'Flp_Angle', 'RootMyb_Last', 'ACC_INFILE_SIZE', 'AWC_complexangle' & - ] + 'StC_Input', 'Flp_Angle', 'RootMyb_Last', 'ACC_INFILE_SIZE', 'AWC_complexangle', & + 'ZMQ_ID', 'ZMQ_YawOffset', 'ZMQ_TorqueOffset', 'ZMQ_PitOffset'] ! Initialize debug file IF ((LocalVar%iStatus == 0) .OR. (LocalVar%iStatus == -9)) THEN ! .TRUE. if we're on the first call to the DLL IF (CntrPar%LoggingLevel > 0) THEN @@ -759,8 +858,8 @@ SUBROUTINE Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, size_av CALL GetNewUnit(UnDb2, ErrVar) OPEN(unit=UnDb2, FILE=TRIM(RootName)//'.RO.dbg2') WRITE(UnDb2, *) 'Generated on '//CurDate()//' at '//CurTime()//' using ROSCO-'//TRIM(rosco_version) - WRITE(UnDb2, '(101(a20,TR5:))') 'Time', LocalVarOutStrings - WRITE(UnDb2, '(101(a20,TR5:))') + WRITE(UnDb2, '(125(a20,TR5:))') 'Time', LocalVarOutStrings + WRITE(UnDb2, '(125(a20,TR5:))') END IF IF (CntrPar%LoggingLevel > 2) THEN @@ -805,31 +904,45 @@ SUBROUTINE Debug(LocalVar, CntrPar, DebugVar, ErrVar, avrSWAP, RootName, size_av ! Process DebugOutData, LocalVarOutData ! Remove very small numbers that cause ******** outputs DO I = 1,SIZE(DebugOutData) - IF (ABS(DebugOutData(I)) < 1E-10) THEN + IF (ABS(DebugOutData(I)) < 1E-99) THEN DebugOutData(I) = 0 END IF + IF (ABS(DebugOutData(I)) > 1E+99) THEN + DebugOutData(I) = 1E+99 + END IF END DO DO I = 1,SIZE(LocalVarOutData) - IF (ABS(LocalVarOutData(I)) < 1E-10) THEN + IF (ABS(LocalVarOutData(I)) < 1E-99) THEN LocalVarOutData(I) = 0 END IF + IF (ABS(LocalVarOutData(I)) > 1E+99) THEN + LocalVarOutData(I) = 1E+99 + END IF END DO ! Write debug files - FmtDat = "(F20.5,TR5,100(ES20.5E2,TR5:))" ! The format of the debugging data - IF(CntrPar%LoggingLevel > 0) THEN - WRITE (UnDb, TRIM(FmtDat)) LocalVar%Time, DebugOutData - END IF + FmtDat = "(F20.5,TR5,124(ES20.5E2,TR5:))" ! The format of the debugging data + IF ( MOD(LocalVar%n_DT, CntrPar%n_DT_Out) == 0) THEN + IF(CntrPar%LoggingLevel > 0) THEN + WRITE (UnDb, TRIM(FmtDat)) LocalVar%Time, DebugOutData + END IF - IF(CntrPar%LoggingLevel > 1) THEN - WRITE (UnDb2, TRIM(FmtDat)) LocalVar%Time, LocalVarOutData - END IF + IF(CntrPar%LoggingLevel > 1) THEN + WRITE (UnDb2, TRIM(FmtDat)) LocalVar%Time, LocalVarOutData + END IF - IF(CntrPar%LoggingLevel > 2) THEN - WRITE (UnDb3, TRIM(FmtDat)) LocalVar%Time, avrSWAP(avrIndices) + IF(CntrPar%LoggingLevel > 2) THEN + WRITE (UnDb3, TRIM(FmtDat)) LocalVar%Time, avrSWAP(avrIndices) + END IF END IF + ! Close all files when simulation finished + IF (LocalVar%iStatus < 0) THEN + CLOSE(UnDb) + CLOSE(UnDb2) + CLOSE(UnDb3) + ENDIF END SUBROUTINE Debug END MODULE ROSCO_IO \ No newline at end of file diff --git a/ROSCO/src/ROSCO_Types.f90 b/rosco/controller/src/ROSCO_Types.f90 similarity index 83% rename from ROSCO/src/ROSCO_Types.f90 rename to rosco/controller/src/ROSCO_Types.f90 index ec19d6b8..64385192 100644 --- a/ROSCO/src/ROSCO_Types.f90 +++ b/rosco/controller/src/ROSCO_Types.f90 @@ -1,5 +1,5 @@ ! ROSCO Registry -! This file is automatically generated by write_registry.py using ROSCO v2.8.0 +! This file is automatically generated by write_registry.py using ROSCO v2.9.0 ! For any modification to the registry, please edit the rosco_types.yaml accordingly MODULE ROSCO_Types @@ -8,21 +8,35 @@ MODULE ROSCO_Types IMPLICIT NONE TYPE, PUBLIC :: ControlParameters + INTEGER(IntKi) :: ZMQ_ID ! 0000 - 9999, Identifier of the rosco, used for zeromq interface only INTEGER(IntKi) :: LoggingLevel ! 0 - write no debug files, 1 - write standard output .dbg-file, 2 - write standard output .dbg-file and complete avrSWAP-array .dbg2-file INTEGER(IntKi) :: Echo ! 0 - no Echo, 1 - Echo input data to .echo + INTEGER(IntKi) :: Ext_Interface ! 0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0. + REAL(DbKi) :: DT_Out ! Output time step + INTEGER(IntKi) :: n_DT_Out ! output every this many steps + INTEGER(IntKi) :: n_DT_ZMQ ! Send measurements to ZMQ after this many time steps INTEGER(IntKi) :: F_LPFType ! Low pass filter on the rotor and generator speed {1 - first-order low-pass filter, 2 - second-order low-pass filter}, [rad/s] - INTEGER(IntKi) :: F_NotchType ! Notch on the measured generator speed {0 - disable, 1 - enable} REAL(DbKi) :: F_LPFCornerFreq ! Corner frequency (-3dB point) in the first-order low-pass filter, [rad/s] REAL(DbKi) :: F_LPFDamping ! Damping coefficient [used only when F_FilterType = 2] - REAL(DbKi) :: F_NotchCornerFreq ! Natural frequency of the notch filter, [rad/s] - REAL(DbKi), DIMENSION(:), ALLOCATABLE :: F_NotchBetaNumDen ! These two notch damping values (numerator and denominator) determines the width and depth of the notch + INTEGER(IntKi) :: F_NumNotchFilts ! Number of notch filters + INTEGER(IntKi) :: F_GenSpdNotch_N ! Number of gen speed notch filters + INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: F_GenSpdNotch_Ind ! Indices of gen speed notch filters + INTEGER(IntKi) :: F_TwrTopNotch_N ! Number of tower top notch filters + INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: F_TwrTopNotch_Ind ! Indices of tower top notch filters + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: F_NotchFreqs ! Natural frequencies of notch filters, [rad/s] + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: F_NotchBetaNum ! Notch Filter Numerator damping (determines width) + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: F_NotchBetaDen ! Notch Filter Numerator damping (determines depth?) REAL(DbKi) :: F_SSCornerFreq ! Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother [rad/s] REAL(DbKi) :: F_WECornerFreq ! Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s] REAL(DbKi), DIMENSION(:), ALLOCATABLE :: F_FlCornerFreq ! Corner frequency (-3dB point) in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s]. REAL(DbKi) :: F_FlHighPassFreq ! Natural frequency of first-roder high-pass filter for nacelle fore-aft motion [rad/s]. REAL(DbKi) :: F_YawErr ! Corner low pass filter corner frequency for yaw controller [rad/s]. REAL(DbKi), DIMENSION(:), ALLOCATABLE :: F_FlpCornerFreq ! Corner frequency (-3dB point) in the second order low pass filter of the blade root bending moment for flap control [rad/s]. - INTEGER(IntKi) :: TD_Mode ! Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle + INTEGER(IntKi) :: TRA_Mode ! Tower Fore-Aft control mode {0 - no fore-aft control, 1 - Tower fore-aft damping, 2 -Frequency exclusion zone, 3- Options 1 and 2} + REAL(DbKi) :: TRA_ExclSpeed ! Rotor speed for exclusion [LSS] [rad/s] + REAL(DbKi) :: TRA_ExclBand ! One-half of the total frequency exclusion band. Torque controller reference will be TRA_ExclFreq +/- TRA_ExlBand [rad/s] + REAL(DbKi) :: TRA_RateLimit ! Time constant for gain change when in exclusion zone [s] + INTEGER(IntKi) :: TD_Mode ! Tower Fore-Aft control mode {0 - no fore-aft control, 1 - Tower fore-aft damping, 2 -Frequency exclusion zone, 3- Options 1 and 2} REAL(DbKi) :: FA_HPFCornerFreq ! Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s] REAL(DbKi) :: FA_IntSat ! Integrator saturation (maximum signal amplitude contrbution to pitch from FA damper), [rad] REAL(DbKi) :: FA_KI ! Integral gain for the fore-aft tower damper controller, -1 = off / >0 = on [rad s/m] @@ -48,7 +62,8 @@ MODULE ROSCO_Types REAL(DbKi) :: PC_RefSpd ! Desired (reference) HSS speed for pitch controller, [rad/s]. REAL(DbKi) :: PC_FinePit ! Record 5 - Below-rated pitch angle set-point (deg) [used only with Bladed Interface] REAL(DbKi) :: PC_Switch ! Angle above lowest minimum pitch angle for switch [rad] - INTEGER(IntKi) :: VS_ControlMode ! Generator torque control mode in above rated conditions {0 - constant torque, 1 - constant power, 2 - TSR Tracking, 3 - TSR Tracking w/ const power} + INTEGER(IntKi) :: VS_ControlMode ! Generator torque control mode in above rated conditions {0 - no torque control, 1 - komega^2 with PI trans, 2 - WSE TSR Tracking, 3 - Power TSR Tracking} + INTEGER(IntKi) :: VS_ConstPower ! Constant power torque control REAL(DbKi) :: VS_GenEff ! Generator efficiency mechanical power -> electrical power [-] REAL(DbKi) :: VS_ArSatTq ! Above rated generator torque PI control saturation, [Nm] -- 212900 REAL(DbKi) :: VS_MaxRat ! Maximum torque rate (in absolute value) in torque controller, [Nm/s]. @@ -63,9 +78,15 @@ MODULE ROSCO_Types REAL(DbKi), DIMENSION(:), ALLOCATABLE :: VS_KP ! Proportional gain for generator PI torque controller, used in the transitional 2.5 region REAL(DbKi), DIMENSION(:), ALLOCATABLE :: VS_KI ! Integral gain for generator PI torque controller, used in the transitional 2.5 region REAL(DbKi) :: VS_TSRopt ! Power-maximizing region 2 tip-speed ratio [rad] + REAL(DbKi) :: VS_PwrFiltF ! Cut-off frequency of filter on generator power for power-based tsr tracking control INTEGER(IntKi) :: SS_Mode ! Setpoint Smoother mode {0 - no setpoint smoothing, 1 - introduce setpoint smoothing} REAL(DbKi) :: SS_VSGain ! Variable speed torque controller setpoint smoother gain, [-]. REAL(DbKi) :: SS_PCGain ! Collective pitch controller setpoint smoother gain, [-]. + INTEGER(IntKi) :: PRC_Mode ! Power reference tracking mode, 0- use standard rotor speed set points, 1- use PRC rotor speed setpoints + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: PRC_WindSpeeds ! Array of wind speeds used in rotor speed vs. wind speed lookup table + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: PRC_GenSpeeds ! Array of rotor speeds corresponding to PRC_WindSpeeds + INTEGER(IntKi) :: PRC_n ! Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array + REAL(DbKi) :: PRC_LPF_Freq ! Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] INTEGER(IntKi) :: WE_Mode ! Wind speed estimator mode {0 - One-second low pass filtered hub height wind speed, 1 - Imersion and Invariance Estimator (Ortega et al.) REAL(DbKi) :: WE_BladeRadius ! Blade length [m] INTEGER(IntKi) :: WE_CP_n ! Amount of parameters in the Cp array @@ -95,7 +116,9 @@ MODULE ROSCO_Types REAL(DbKi) :: SD_MaxPit ! Maximum blade pitch angle to initiate shutdown, [rad] REAL(DbKi) :: SD_CornerFreq ! Cutoff Frequency for first order low-pass filter for blade pitch angle, [rad/s] INTEGER(IntKi) :: Fl_Mode ! Floating specific feedback mode {0 - no nacelle velocity feedback, 1 - nacelle velocity feedback} - REAL(DbKi) :: Fl_Kp ! Nacelle velocity proportional feedback gain [s] + INTEGER(IntKi) :: Fl_n ! Number of Fl_Kp for gain scheduling + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: Fl_Kp ! Nacelle velocity proportional feedback gain [s] + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: Fl_U ! Wind speeds for scheduling Fl_Kp [m/s] INTEGER(IntKi) :: Flp_Mode ! Flap actuator mode {0 - off, 1 - fixed flap position, 2 - PI flap control} REAL(DbKi) :: Flp_Angle ! Fixed flap angle (degrees) REAL(DbKi) :: Flp_Kp ! PI flap control proportional gain @@ -104,22 +127,27 @@ MODULE ROSCO_Types CHARACTER(1024) :: OL_Filename ! Input file with open loop timeseries INTEGER(IntKi) :: OL_Mode ! Open loop control mode {0 - no open loop control, 1 - open loop control vs. time, 2 - open loop control vs. wind speed} INTEGER(IntKi) :: Ind_Breakpoint ! The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) - INTEGER(IntKi) :: Ind_BldPitch ! The column in OL_Filename that contains the blade pitch input in rad + INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: Ind_BldPitch ! The columns in OL_Filename that contains the blade pitch inputs (1,2,3) in rad INTEGER(IntKi) :: Ind_GenTq ! The column in OL_Filename that contains the generator torque in Nm INTEGER(IntKi) :: Ind_YawRate ! The column in OL_Filename that contains the generator torque in Nm + INTEGER(IntKi) :: Ind_Azimuth ! The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: RP_Gains ! PID gains and Tf on derivative term for rotor position control (used if OL_Mode = 2) INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: Ind_CableControl ! The column in OL_Filename that contains the cable control inputs in m INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: Ind_StructControl ! The column in OL_Filename that contains the structural control inputs in various units REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_Breakpoints ! Open loop breakpoints in timeseries - REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_BldPitch ! Open blade pitch timeseries + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_BldPitch1 ! Open loop blade pitch 1 timeseries + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_BldPitch2 ! Open loop blade pitch 2 timeseries + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_BldPitch3 ! Open loop blade pitch 3 timeseries REAL(DbKi), DIMENSION(:,:), ALLOCATABLE :: OL_CableControl ! None REAL(DbKi), DIMENSION(:,:), ALLOCATABLE :: OL_StructControl ! None - REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_GenTq ! Open generator torque timeseries - REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_YawRate ! Open yaw rate timeseries + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_GenTq ! Open loop generator torque timeseries + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_YawRate ! Open loop yaw rate timeseries + REAL(DbKi), DIMENSION(:), ALLOCATABLE :: OL_Azimuth ! Open loop azimuth timeseries REAL(DbKi), DIMENSION(:,:), ALLOCATABLE :: OL_Channels ! Open loop channels in timeseries INTEGER(IntKi) :: PA_Mode ! Pitch actuator mode {0 - not used, 1 - first order filter, 2 - second order filter} REAL(DbKi) :: PA_CornerFreq ! Pitch actuator bandwidth/cut-off frequency [rad/s] REAL(DbKi) :: PA_Damping ! Pitch actuator damping ratio [-, unused if PA_Mode = 1] - INTEGER(IntKi) :: AWC_Mode ! Active wake control mode [0 - unused, 1 - SNL method, 2 - NREL method] + INTEGER(IntKi) :: AWC_Mode ! Active wake control mode [0 - unused, 1 - complex number method, 2 - Coleman transform method] INTEGER(IntKi) :: AWC_NumModes ! AWC- Number of modes to include [-] INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: AWC_n ! AWC azimuthal mode [-] INTEGER(IntKi), DIMENSION(:), ALLOCATABLE :: AWC_harmonic ! AWC AWC Coleman transform harmonic [-] @@ -215,13 +243,18 @@ MODULE ROSCO_Types REAL(DbKi), DIMENSION(99) :: ITermLast ! Previous integrator term REAL(DbKi), DIMENSION(99) :: ITerm2 ! Integrator term - second integrator REAL(DbKi), DIMENSION(99) :: ITermLast2 ! Previous integrator term - second integrator + REAL(DbKi), DIMENSION(99) :: ELast ! Previous error term for derivative END TYPE piParams TYPE, PUBLIC :: LocalVariables INTEGER(IntKi) :: iStatus ! Initialization status REAL(DbKi) :: Time ! Time [s] REAL(DbKi) :: DT ! Time step [s] + LOGICAL :: WriteThisStep ! Write an output line this time step + INTEGER(IntKi) :: n_DT ! number of timesteps since start + REAL(DbKi) :: Time_Last ! Last time [s] REAL(DbKi) :: VS_GenPwr ! Generator power [W] + REAL(DbKi) :: VS_GenPwrF ! Generator power [W] REAL(DbKi) :: GenSpeed ! Generator speed (HSS) [rad/s] REAL(DbKi) :: RotSpeed ! Rotor speed (LSS) [rad/s] REAL(DbKi) :: NacHeading ! Nacelle heading of the turbine w.r.t. north [deg] @@ -232,12 +265,24 @@ MODULE ROSCO_Types REAL(DbKi) :: BlPitch(3) ! Blade pitch [rad] REAL(DbKi) :: BlPitchCMeas ! Mean (collective) blade pitch [rad] REAL(DbKi) :: Azimuth ! Rotor aziumuth angle [rad] + REAL(DbKi) :: OL_Azimuth ! Rotor aziumuth angle [rad] + REAL(DbKi) :: AzUnwrapped ! Rotor aziumuth angle [rad] + REAL(DbKi) :: AzError ! Azimuth error angle [rad] + REAL(DbKi) :: GenTqAz ! Gen torque command due to azimuth error + REAL(DbKi) :: AzBuffer(2) ! Current and last rotor aziumuth angles [rad] INTEGER(IntKi) :: NumBl ! Number of blades [-] REAL(DbKi) :: FA_Acc ! Tower fore-aft acceleration [m/s^2] REAL(DbKi) :: NacIMU_FA_Acc ! Tower fore-aft acceleration [rad/s^2] REAL(DbKi) :: FA_AccHPF ! High-pass filtered fore-aft acceleration [m/s^2] REAL(DbKi) :: FA_AccHPFI ! Tower velocity, high-pass filtered and integrated fore-aft acceleration [m/s] REAL(DbKi) :: FA_PitCom(3) ! Tower fore-aft vibration damping pitch contribution [rad] + REAL(DbKi) :: VS_RefSpd ! Torque control generator speed set point [rad/s] + REAL(DbKi) :: VS_RefSpd_TSR ! Torque control generator speed set point based on optimal TSR [rad/s] + REAL(DbKi) :: VS_RefSpd_TRA ! Torque control generator speed set point after freq avoidance [rad/s] + REAL(DbKi) :: VS_RefSpd_RL ! Torque control generator speed set point after rate limit [rad/s] + REAL(DbKi) :: PC_RefSpd ! Generator speed set point of pitch controller [rad/s] + REAL(DbKi) :: PC_RefSpd_SS ! Generator speed set point of pitch controller after setpoint smoothing [rad/s] + REAL(DbKi) :: PC_RefSpd_PRC ! Generator speed set point of pitch controller after power ref control [rad/s] REAL(DbKi) :: RotSpeedF ! Filtered LSS (generator) speed [rad/s]. REAL(DbKi) :: GenSpeedF ! Filtered HSS (generator) speed [rad/s]. REAL(DbKi) :: GenTq ! Electrical generator torque, [Nm]. @@ -251,7 +296,7 @@ MODULE ROSCO_Types REAL(DbKi) :: PC_TF ! First-order filter parameter for derivative action REAL(DbKi) :: PC_MaxPit ! Maximum pitch setting in pitch controller (variable) [rad]. REAL(DbKi) :: PC_MinPit ! Minimum pitch setting in pitch controller (variable) [rad]. - REAL(DbKi) :: PC_PitComT ! Total command pitch based on the sum of the proportional and integral terms [rad]. + REAL(DbKi) :: PC_PitComT ! Collective pitch commmand from PI control [rad]. REAL(DbKi) :: PC_PitComT_Last ! Last total command pitch based on the sum of the proportional and integral terms [rad]. REAL(DbKi) :: PC_PitComTF ! Filtered Total command pitch based on the sum of the proportional and integral terms [rad]. REAL(DbKi) :: PC_PitComT_IPC(3) ! Total command pitch based on the sum of the proportional and integral terms, including IPC term [rad]. @@ -275,6 +320,7 @@ MODULE ROSCO_Types REAL(DbKi) :: PitComAct(3) ! Actuated pitch command of each blade [rad]. REAL(DbKi) :: SS_DelOmegaF ! Filtered setpoint shifting term defined in setpoint smoother [rad/s]. REAL(DbKi) :: TestType ! Test variable, no use + REAL(DbKi) :: Kp_Float ! Local, instantaneous Kp_Float, scheduled on wind speed, if desired REAL(DbKi) :: VS_MaxTq ! Maximum allowable generator torque [Nm]. REAL(DbKi) :: VS_LastGenTrq ! Commanded electrical generator torque the last time the controller was called [Nm]. REAL(DbKi) :: VS_LastGenPwr ! Commanded electrical generator torque the last time the controller was called [Nm]. @@ -289,10 +335,14 @@ MODULE ROSCO_Types REAL(DbKi) :: WE_VwI ! Integrated wind speed quantity for estimation [m/s] REAL(DbKi) :: WE_VwIdot ! Differentiated integrated wind speed quantity for estimation [m/s] REAL(DbKi) :: VS_LastGenTrqF ! Differentiated integrated wind speed quantity for estimation [m/s] + REAL(DbKi) :: PRC_WSE_F ! Filtered wind speed estimate for power reference control LOGICAL :: SD ! Shutdown, .FALSE. if inactive, .TRUE. if active REAL(DbKi) :: Fl_PitCom ! Shutdown, .FALSE. if inactive, .TRUE. if active REAL(DbKi) :: NACIMU_FA_AccF ! None REAL(DbKi) :: FA_AccF ! None + INTEGER(IntKi) :: FA_Hist ! Hysteresis state for tower resonance avoidance. + REAL(DbKi) :: TRA_LastRefSpd ! Last reference generator speed + REAL(DbKi) :: VS_RefSpeed ! Torque controller reference speed REAL(DbKi) :: PtfmTDX ! Platform motion -- Displacement TDX (m)') REAL(DbKi) :: PtfmTDY ! Platform motion -- Displacement TDY (m)') REAL(DbKi) :: PtfmTDZ ! Platform motion -- Displacement TDZ (m)') @@ -321,6 +371,10 @@ MODULE ROSCO_Types CHARACTER, DIMENSION(:), ALLOCATABLE :: ACC_INFILE ! Parameter input filename LOGICAL :: restart ! Restart flag COMPLEX(DbKi) :: AWC_complexangle(3) ! Complex angle for each blade, sum of modes? + INTEGER(IntKi) :: ZMQ_ID ! 0000 - 9999, Identifier of the rosco, used for zeromq interface only + REAL(DbKi) :: ZMQ_YawOffset ! Yaw offset command, [rad] + REAL(DbKi) :: ZMQ_TorqueOffset ! Torque offset command, [Nm] + REAL(DbKi) :: ZMQ_PitOffset(3) ! Pitch command offset provided by ZeroMQ TYPE(WE) :: WE ! Wind speed estimator parameters derived type TYPE(FilterParameters) :: FP ! Filter parameters derived type TYPE(piParams) :: piP ! PI parameters derived type @@ -371,6 +425,8 @@ MODULE ROSCO_Types REAL(DbKi) :: NacVaneOffset ! Nacelle vane angle with offset [deg]. REAL(DbKi) :: Yaw_Err ! Yaw error [deg]. REAL(DbKi) :: YawState ! State of yaw controller + REAL(DbKi) :: VS_RefSpd ! Torque control generator speed set point [rad/s] + REAL(DbKi) :: PC_RefSpd ! Generator speed set point of pitch controller [rad/s] END TYPE DebugVariables TYPE, PUBLIC :: ErrorVariables @@ -388,11 +444,6 @@ MODULE ROSCO_Types CHARACTER(1024) :: ProcName(3) = "" ! The name of the procedure in the DLL that will be called. END TYPE ExtDLL_Type -TYPE, PUBLIC :: ZMQ_Variables - LOGICAL :: ZMQ_Flag ! Flag if we're using zeroMQ at all (0-False, 1-True) - REAL(DbKi) :: Yaw_Offset ! Yaw offsety command, [rad] -END TYPE ZMQ_Variables - TYPE, PUBLIC :: ExtControlType REAL(ReKi), DIMENSION(:), ALLOCATABLE :: avrSWAP ! The swap array- used to pass data to and from the DLL controller [see Bladed DLL documentation] END TYPE ExtControlType diff --git a/ROSCO/src/ReadSetParameters.f90 b/rosco/controller/src/ReadSetParameters.f90 similarity index 75% rename from ROSCO/src/ReadSetParameters.f90 rename to rosco/controller/src/ReadSetParameters.f90 index 23a5bde7..36db8c4b 100644 --- a/ROSCO/src/ReadSetParameters.f90 +++ b/rosco/controller/src/ReadSetParameters.f90 @@ -26,7 +26,7 @@ MODULE ReadSetParameters ! ----------------------------------------------------------------------------------- ! Read avrSWAP array passed from ServoDyn SUBROUTINE ReadAvrSWAP(avrSWAP, LocalVar, CntrPar) - USE ROSCO_Types, ONLY : LocalVariables, ZMQ_Variables + USE ROSCO_Types, ONLY : LocalVariables REAL(ReKi), INTENT(INOUT) :: avrSWAP(*) ! The swap array, used to pass data to, and receive data from, the DLL controller. TYPE(LocalVariables), INTENT(INOUT) :: LocalVar @@ -55,25 +55,29 @@ SUBROUTINE ReadAvrSWAP(avrSWAP, LocalVar, CntrPar) LocalVar%Azimuth = avrSWAP(60) LocalVar%NumBl = NINT(avrSWAP(61)) - ! Platform signals - LocalVar%PtfmTDX = avrSWAP(1001) - LocalVar%PtfmTDY = avrSWAP(1002) - LocalVar%PtfmTDZ = avrSWAP(1003) - LocalVar%PtfmRDX = avrSWAP(1004) - LocalVar%PtfmRDY = avrSWAP(1005) - LocalVar%PtfmRDZ = avrSWAP(1006) - LocalVar%PtfmTVX = avrSWAP(1007) - LocalVar%PtfmTVY = avrSWAP(1008) - LocalVar%PtfmTVZ = avrSWAP(1009) - LocalVar%PtfmRVX = avrSWAP(1010) - LocalVar%PtfmRVY = avrSWAP(1011) - LocalVar%PtfmRVZ = avrSWAP(1012) - LocalVar%PtfmTAX = avrSWAP(1013) - LocalVar%PtfmTAY = avrSWAP(1014) - LocalVar%PtfmTAZ = avrSWAP(1015) - LocalVar%PtfmRAX = avrSWAP(1016) - LocalVar%PtfmRAY = avrSWAP(1017) - LocalVar%PtfmRAZ = avrSWAP(1018) + if (CntrPar%Ext_Interface > 0) THEN ! Use extended bladed interface + + ! Platform signals + LocalVar%PtfmTDX = avrSWAP(1001) + LocalVar%PtfmTDY = avrSWAP(1002) + LocalVar%PtfmTDZ = avrSWAP(1003) + LocalVar%PtfmRDX = avrSWAP(1004) + LocalVar%PtfmRDY = avrSWAP(1005) + LocalVar%PtfmRDZ = avrSWAP(1006) + LocalVar%PtfmTVX = avrSWAP(1007) + LocalVar%PtfmTVY = avrSWAP(1008) + LocalVar%PtfmTVZ = avrSWAP(1009) + LocalVar%PtfmRVX = avrSWAP(1010) + LocalVar%PtfmRVY = avrSWAP(1011) + LocalVar%PtfmRVZ = avrSWAP(1012) + LocalVar%PtfmTAX = avrSWAP(1013) + LocalVar%PtfmTAY = avrSWAP(1014) + LocalVar%PtfmTAZ = avrSWAP(1015) + LocalVar%PtfmRAX = avrSWAP(1016) + LocalVar%PtfmRAY = avrSWAP(1017) + LocalVar%PtfmRAZ = avrSWAP(1018) + + ENDIF ! GenTemp = avrSWAP(1026) @@ -110,12 +114,19 @@ SUBROUTINE ReadAvrSWAP(avrSWAP, LocalVar, CntrPar) LocalVar%restart = .False. ENDIF + ! Increment timestep counter + IF (LocalVar%iStatus == 0 .AND. LocalVar%Time == 0) THEN + LocalVar%n_DT = 0 + ELSE + LocalVar%n_DT = LocalVar%n_DT + 1 + ENDIF + END SUBROUTINE ReadAvrSWAP ! ----------------------------------------------------------------------------------- ! Define parameters for control actions - SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, objInst, PerfData, zmqVar, RootName, ErrVar) + SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, objInst, PerfData, RootName, ErrVar) - USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances, PerformanceData, ErrorVariables, ZMQ_Variables + USE ROSCO_Types, ONLY : ControlParameters, LocalVariables, ObjectInstances, PerformanceData, ErrorVariables REAL(ReKi), INTENT(INOUT) :: avrSWAP(*) ! The swap array, used to pass data to, and receive data from, the DLL controller. CHARACTER(C_CHAR), INTENT(IN ) :: accINFILE(NINT(avrSWAP(50))) ! The name of the parameter input file @@ -125,7 +136,6 @@ SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, obj TYPE(LocalVariables), INTENT(INOUT) :: LocalVar TYPE(ObjectInstances), INTENT(INOUT) :: objInst TYPE(PerformanceData), INTENT(INOUT) :: PerfData - TYPE(ZMQ_Variables), INTENT(INOUT) :: zmqVar TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar CHARACTER(NINT(avrSWAP(50))-1), INTENT(IN) :: RootName @@ -133,7 +143,7 @@ SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, obj INTEGER(IntKi) :: K, I, I_OL ! Index used for looping through blades. CHARACTER(1024) :: OL_String ! Open description loop string INTEGER(IntKi) :: OL_Count ! Number of open loop channels - + INTEGER(IntKi) :: UnOpenLoop ! Open Loop file unit INTEGER(IntKi) :: N_OL_Cables INTEGER(IntKi) :: N_OL_StCs @@ -189,7 +199,7 @@ SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, obj LocalVar%ACC_INFILE = accINFILE ! Read Control Parameter File - CALL ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, NINT(avrSWAP(50)), RootName, ErrVar) + CALL ReadControlParameterFileSub(CntrPar, LocalVar, accINFILE, NINT(avrSWAP(50)), RootName, ErrVar) ! If there's been an file reading error, don't continue ! Add RoutineName to error message IF (ErrVar%aviFAIL < 0) THEN @@ -201,7 +211,7 @@ SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, obj CALL READCpFile(CntrPar,PerfData,ErrVar) ENDIF - ! Initialize the SAVED variables: + ! Initialize the Local variables: LocalVar%PitCom = LocalVar%BlPitch ! This will ensure that the variable speed controller picks the correct control region and the pitch controller picks the correct gain on the first call ! Wind speed estimator initialization @@ -219,125 +229,42 @@ SUBROUTINE SetParameters(avrSWAP, accINFILE, size_avcMSG, CntrPar, LocalVar, obj ENDIF LocalVar%VS_LastGenTrq = LocalVar%GenTq LocalVar%VS_MaxTq = CntrPar%VS_MaxTq + LocalVar%VS_GenPwr = LocalVar%GenTq * LocalVar%GenSpeed - ! Check validity of input parameters: - CALL CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) - ! Initialize variables LocalVar%CC_DesiredL = 0 LocalVar%CC_ActuatedL = 0 LocalVar%CC_ActuatedDL = 0 LocalVar%StC_Input = 0 + + LocalVar%ZMQ_YawOffset = 0 + LocalVar%ZMQ_PitOffset = 0 + LocalVar%ZMQ_ID = CntrPar%ZMQ_ID - ! Initialize open loop control - ! Read open loop input, if desired - IF (CntrPar%OL_Mode == 1) THEN - OL_String = '' ! Display string - OL_Count = 1 - IF (CntrPar%Ind_BldPitch > 0) THEN - OL_String = TRIM(OL_String)//' BldPitch ' - OL_Count = OL_Count + 1 - ENDIF - - IF (CntrPar%Ind_GenTq > 0) THEN - OL_String = TRIM(OL_String)//' GenTq ' - OL_Count = OL_Count + 1 - ENDIF - - IF (CntrPar%Ind_YawRate > 0) THEN - OL_String = TRIM(OL_String)//' YawRate ' - OL_Count = OL_Count + 1 - ENDIF - - N_OL_Cables = 0 - IF (ANY(CntrPar%Ind_CableControl > 0)) THEN - DO I = 1,SIZE(CntrPar%Ind_CableControl) - IF (CntrPar%Ind_CableControl(I) > 0) THEN - OL_String = TRIM(OL_String)//' Cable'//TRIM(Int2LStr(I))//' ' - OL_Count = OL_Count + 1 - N_OL_Cables = N_OL_Cables + 1 - ENDIF - ENDDO - ENDIF - - N_OL_StCs = 0 - IF (ANY(CntrPar%Ind_StructControl > 0)) THEN - DO I = 1,SIZE(CntrPar%Ind_StructControl) - IF (CntrPar%Ind_StructControl(I) > 0) THEN - OL_String = TRIM(OL_String)//' StC'//TRIM(Int2LStr(I))//' ' - OL_Count = OL_Count + 1 - N_OL_StCs = N_OL_StCs + 1 - ENDIF - ENDDO - ENDIF - - - PRINT *, 'ROSCO: Implementing open loop control for'//TRIM(OL_String) - CALL Read_OL_Input(CntrPar%OL_Filename,110_IntKi,OL_Count,CntrPar%OL_Channels, ErrVar) - - CntrPar%OL_Breakpoints = CntrPar%OL_Channels(:,CntrPar%Ind_Breakpoint) - - IF (CntrPar%Ind_BldPitch > 0) THEN - CntrPar%OL_BldPitch = CntrPar%OL_Channels(:,CntrPar%Ind_BldPitch) - ENDIF - - IF (CntrPar%Ind_GenTq > 0) THEN - CntrPar%OL_GenTq = CntrPar%OL_Channels(:,CntrPar%Ind_GenTq) - ENDIF - - IF (CntrPar%Ind_YawRate > 0) THEN - CntrPar%OL_YawRate = CntrPar%OL_Channels(:,CntrPar%Ind_YawRate) - ENDIF - - IF (ANY(CntrPar%Ind_CableControl > 0)) THEN - ALLOCATE(CntrPar%OL_CableControl(N_OL_Cables,SIZE(CntrPar%OL_Channels,DIM=1))) - I_OL = 1 - DO I = 1,SIZE(CntrPar%Ind_CableControl) - IF (CntrPar%Ind_CableControl(I) > 0) THEN - CntrPar%OL_CableControl(I_OL,:) = CntrPar%OL_Channels(:,CntrPar%Ind_CableControl(I)) - I_OL = I_OL + 1 - ENDIF - ENDDO - ENDIF - - IF (ANY(CntrPar%Ind_StructControl > 0)) THEN - ALLOCATE(CntrPar%OL_StructControl(N_OL_StCs,SIZE(CntrPar%OL_Channels,DIM=1))) - I_OL = 1 - DO I = 1,SIZE(CntrPar%Ind_StructControl) - IF (CntrPar%Ind_StructControl(I) > 0) THEN - CntrPar%OL_StructControl(I_OL,:) = CntrPar%OL_Channels(:,CntrPar%Ind_StructControl(I)) - I_OL = I_OL + 1 - ENDIF - ENDDO - ENDIF - - END IF - + ! Check validity of input parameters: + CALL CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ! Add RoutineName to error message IF (ErrVar%aviFAIL < 0) THEN ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg) ENDIF - - ! Check if we're using zeromq - IF (CntrPar%ZMQ_Mode == 1) THEN ! add .OR. statements as more functionality is built in - zmqVar%ZMQ_Flag = .TRUE. - ENDIF ENDIF END SUBROUTINE SetParameters + ! ----------------------------------------------------------------------------------- ! Read all constant control parameters from DISCON.IN parameter file - SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_size, RootName, ErrVar)!, accINFILE_size) + ! Also, all computed CntrPar%* parameters should be computed in this subroutine + SUBROUTINE ReadControlParameterFileSub(CntrPar, LocalVar, accINFILE, accINFILE_size, RootName, ErrVar)!, accINFILE_size) USE, INTRINSIC :: ISO_C_Binding - USE ROSCO_Types, ONLY : ControlParameters, ErrorVariables, ZMQ_Variables + USE ROSCO_Types, ONLY : ControlParameters, ErrorVariables, LocalVariables INTEGER(IntKi) :: accINFILE_size ! size of DISCON input filename CHARACTER(accINFILE_size), INTENT(IN ) :: accINFILE(accINFILE_size) ! DISCON input filename TYPE(ControlParameters), INTENT(INOUT) :: CntrPar ! Control parameter type + TYPE(LocalVariables), INTENT(INOUT) :: LocalVar ! Control parameter type TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar ! Control parameter type - TYPE(ZMQ_Variables), INTENT(INOUT) :: zmqVar ! Control parameter type CHARACTER(accINFILE_size), INTENT(IN) :: RootName @@ -350,6 +277,13 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz INTEGER(IntKi) :: UnEc CHARACTER(128) :: EchoFilename ! Input checkpoint file CHARACTER(MaxLineLength), DIMENSION(:), ALLOCATABLE :: FileLines + + INTEGER(IntKi) :: I, I_OL ! Index used for looping through blades. + CHARACTER(1024) :: OL_String ! Open description loop string + INTEGER(IntKi) :: OL_Count ! Number of open loop channels + INTEGER(IntKi) :: UnOpenLoop ! Open Loop file unit + INTEGER(IntKi) :: N_OL_Cables + INTEGER(IntKi) :: N_OL_StCs CHARACTER(*), PARAMETER :: RoutineName = 'ReadControlParameterFileSub' @@ -373,8 +307,10 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz READ(UnControllerParameters,'(A)',IOSTAT=IOS) FileLines(I_LINE) END DO - !----------------------- DEBUG -------------------------- - CALL ParseInput(FileLines,'LoggingLevel', CntrPar%LoggingLevel, accINFILE(1), ErrVar) + ! Close Input File + CLOSE(UnControllerParameters) + + ! Read Echo first, so file can be set up, if desired CALL ParseInput(FileLines,'Echo', CntrPar%Echo, accINFILE(1), ErrVar) IF (ErrVar%aviFAIL < 0) RETURN @@ -396,19 +332,27 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz ENDIF ENDIF + !----------------------- Simulation Control -------------------------- + CALL ParseInput(FileLines,'LoggingLevel', CntrPar%LoggingLevel, accINFILE(1), ErrVar, .TRUE., UnEc=UnEc) + CALL ParseInput(FileLines,'DT_Out', CntrPar%DT_Out, accINFILE(1), ErrVar, .TRUE., UnEc=UnEc) + CALL ParseInput(FileLines,'Ext_Interface', CntrPar%Ext_Interface, accINFILE(1), ErrVar, .TRUE., UnEc=UnEc) + IF (ErrVar%aviFAIL < 0) RETURN + !----------------- CONTROLLER FLAGS --------------------- CALL ParseInput(FileLines,'F_LPFType', CntrPar%F_LPFType, accINFILE(1), ErrVar, UnEc=UnEc) - CALL ParseInput(FileLines,'F_NotchType', CntrPar%F_NotchType, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'IPC_ControlMode', CntrPar%IPC_ControlMode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'VS_ControlMode', CntrPar%VS_ControlMode, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines,'VS_ConstPower', CntrPar%VS_ConstPower, accINFILE(1), ErrVar, .TRUE., UnEc=UnEc) ! Default is 0 CALL ParseInput(FileLines,'PC_ControlMode', CntrPar%PC_ControlMode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'Y_ControlMode', CntrPar%Y_ControlMode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'SS_Mode', CntrPar%SS_Mode, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines,'PRC_Mode', CntrPar%PRC_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'WE_Mode', CntrPar%WE_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'PS_Mode', CntrPar%PS_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'SD_Mode', CntrPar%SD_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'FL_Mode', CntrPar%FL_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'TD_Mode', CntrPar%TD_Mode, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines,'TRA_Mode', CntrPar%TRA_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'Flp_Mode', CntrPar%Flp_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'OL_Mode', CntrPar%OL_Mode, accINFILE(1), ErrVar, UnEc=UnEc) CALL ParseInput(FileLines,'PA_Mode', CntrPar%PA_Mode, accINFILE(1), ErrVar, UnEc=UnEc) @@ -421,16 +365,29 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz IF (ErrVar%aviFAIL < 0) RETURN !----------------- FILTER CONSTANTS --------------------- - CALL ParseInput(FileLines, 'F_LPFCornerFreq', CntrPar%F_LPFCornerFreq, accINFILE(1), ErrVar, .FALSE., UnEc) - CALL ParseInput(FileLines, 'F_LPFDamping', CntrPar%F_LPFDamping, accINFILE(1), ErrVar, CntrPar%F_LPFType == 1, UnEc) - CALL ParseInput(FileLines, 'F_NotchCornerFreq', CntrPar%F_NotchCornerFreq, accINFILE(1), ErrVar, CntrPar%F_NotchType == 0, UnEc) - CALL ParseAry( FileLines, 'F_NotchBetaNumDen', CntrPar%F_NotchBetaNumDen, 2, accINFILE(1), ErrVar, CntrPar%F_NotchType == 0, UnEc) - CALL ParseInput(FileLines, 'F_SSCornerFreq', CntrPar%F_SSCornerFreq, accINFILE(1), ErrVar, CntrPar%SS_Mode == 0, UnEc) - CALL ParseInput(FileLines, 'F_WECornerFreq', CntrPar%F_WECornerFreq, accINFILE(1), ErrVar, .FALSE., UnEc) - CALL ParseInput(FileLines, 'F_YawErr', CntrPar%F_YawErr, accINFILE(1), ErrVar, CntrPar%Y_ControlMode == 0, UnEc) - CALL ParseAry( FileLines, 'F_FlCornerFreq', CntrPar%F_FlCornerFreq, 2, accINFILE(1), ErrVar, CntrPar%FL_Mode == 0, UnEc) - CALL ParseInput(FileLines, 'F_FlHighPassFreq', CntrPar%F_FlHighPassFreq, accINFILE(1), ErrVar, CntrPar%FL_Mode == 0, UnEc) - CALL ParseAry( FileLines, 'F_FlpCornerFreq', CntrPar%F_FlpCornerFreq, 2, accINFILE(1), ErrVar, CntrPar%Flp_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'F_LPFCornerFreq', CntrPar%F_LPFCornerFreq, accINFILE(1), ErrVar, .FALSE., UnEc) + CALL ParseInput(FileLines, 'F_LPFDamping', CntrPar%F_LPFDamping, accINFILE(1), ErrVar, CntrPar%F_LPFType == 1, UnEc) + CALL ParseInput(FileLines, 'F_NumNotchFilts', CntrPar%F_NumNotchFilts, accINFILE(1), ErrVar, .TRUE., UnEc) + CALL ParseAry( FileLines, 'F_NotchFreqs', CntrPar%F_NotchFreqs, CntrPar%F_NumNotchFilts, accINFILE(1), ErrVar, CntrPar%F_NumNotchFilts == 0, UnEc) + CALL ParseAry( FileLines, 'F_NotchBetaNum', CntrPar%F_NotchBetaNum, CntrPar%F_NumNotchFilts, accINFILE(1), ErrVar, CntrPar%F_NumNotchFilts == 0, UnEc) + CALL ParseAry( FileLines, 'F_NotchBetaDen', CntrPar%F_NotchBetaDen, CntrPar%F_NumNotchFilts, accINFILE(1), ErrVar, CntrPar%F_NumNotchFilts == 0, UnEc) + CALL ParseInput(FileLines, 'F_GenSpdNotch_N', CntrPar%F_GenSpdNotch_N, accINFILE(1), ErrVar, CntrPar%F_NumNotchFilts == 0, UnEc) + CALL ParseInput(FileLines, 'F_TwrTopNotch_N', CntrPar%F_TwrTopNotch_N, accINFILE(1), ErrVar, CntrPar%F_NumNotchFilts == 0, UnEc) + CALL ParseInput(FileLines, 'F_SSCornerFreq', CntrPar%F_SSCornerFreq, accINFILE(1), ErrVar, CntrPar%SS_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'F_WECornerFreq', CntrPar%F_WECornerFreq, accINFILE(1), ErrVar, .FALSE., UnEc) + CALL ParseInput(FileLines, 'F_YawErr', CntrPar%F_YawErr, accINFILE(1), ErrVar, CntrPar%Y_ControlMode == 0, UnEc) + CALL ParseAry( FileLines, 'F_FlCornerFreq', CntrPar%F_FlCornerFreq, 2, accINFILE(1), ErrVar, CntrPar%FL_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'F_FlHighPassFreq', CntrPar%F_FlHighPassFreq, accINFILE(1), ErrVar, CntrPar%FL_Mode == 0, UnEc) + CALL ParseAry( FileLines, 'F_FlpCornerFreq', CntrPar%F_FlpCornerFreq, 2, accINFILE(1), ErrVar, CntrPar%Flp_Mode == 0, UnEc) + + ! Optional filter inds + IF (CntrPar%F_GenSpdNotch_N > 0) THEN + CALL ParseAry(FileLines, 'F_GenSpdNotch_Ind', CntrPar%F_GenSpdNotch_Ind, CntrPar%F_GenSpdNotch_N, accINFILE(1), ErrVar, CntrPar%F_GenSpdNotch_N == 0, UnEc) + ENDIF + IF (CntrPar%F_TwrTopNotch_N > 0) THEN + CALL ParseAry(FileLines, 'F_TwrTopNotch_Ind', CntrPar%F_TwrTopNotch_Ind, CntrPar%F_TwrTopNotch_N, accINFILE(1), ErrVar, CntrPar%F_TwrTopNotch_N == 0, UnEc) + ENDIF + IF (ErrVar%aviFAIL < 0) RETURN !----------- BLADE PITCH CONTROLLER CONSTANTS ----------- @@ -461,12 +418,12 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz !------------ VS TORQUE CONTROL CONSTANTS ---------------- CALL ParseInput(FileLines, 'VS_GenEff', CntrPar%VS_GenEff, accINFILE(1), ErrVar, .FALSE., UnEc) - CALL ParseInput(FileLines, 'VS_ArSatTq', CntrPar%VS_ArSatTq, accINFILE(1), ErrVar, CntrPar%VS_ControlMode > 1, UnEc) - CALL ParseInput(FileLines, 'VS_MaxRat', CntrPar%VS_MaxRat, accINFILE(1), ErrVar, CntrPar%VS_ControlMode > 1, UnEc) + CALL ParseInput(FileLines, 'VS_ArSatTq', CntrPar%VS_ArSatTq, accINFILE(1), ErrVar, CntrPar%VS_ControlMode .NE. 1, UnEc) + CALL ParseInput(FileLines, 'VS_MaxRat', CntrPar%VS_MaxRat, accINFILE(1), ErrVar, CntrPar%VS_ControlMode .NE. 1, UnEc) CALL ParseInput(FileLines, 'VS_MaxTq', CntrPar%VS_MaxTq, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseInput(FileLines, 'VS_MinTq', CntrPar%VS_MinTq, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseInput(FileLines, 'VS_MinOMSpd', CntrPar%VS_MinOMSpd, accINFILE(1), ErrVar) ! Default 0 is fin, UnEce - CALL ParseInput(FileLines, 'VS_Rgn2K', CntrPar%VS_Rgn2K, accINFILE(1), ErrVar, CntrPar%VS_ControlMode > 1, UnEc) + CALL ParseInput(FileLines, 'VS_Rgn2K', CntrPar%VS_Rgn2K, accINFILE(1), ErrVar, CntrPar%VS_ControlMode == 2, UnEc) CALL ParseInput(FileLines, 'VS_RtPwr', CntrPar%VS_RtPwr, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseInput(FileLines, 'VS_RtTq', CntrPar%VS_RtTq, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseInput(FileLines, 'VS_RefSpd', CntrPar%VS_RefSpd, accINFILE(1), ErrVar, .FALSE., UnEc) @@ -474,6 +431,7 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz CALL ParseAry( FileLines, 'VS_KP', CntrPar%VS_KP, CntrPar%VS_n, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseAry( FileLines, 'VS_KI', CntrPar%VS_KI, CntrPar%VS_n, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseInput(FileLines, 'VS_TSRopt', CntrPar%VS_TSRopt, accINFILE(1), ErrVar, CntrPar%VS_ControlMode < 2, UnEc) + CALL ParseInput(FileLines, 'VS_PwrFiltF', CntrPar%VS_PwrFiltF, accINFILE(1), ErrVar, CntrPar%VS_ControlMode .NE. 3, UnEc) IF (ErrVar%aviFAIL < 0) RETURN !------- Setpoint Smoother -------------------------------- @@ -481,6 +439,12 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz CALL ParseInput(FileLines, 'SS_PCGain', CntrPar%SS_PCGain, accINFILE(1), ErrVar, CntrPar%SS_Mode == 0, UnEc) IF (ErrVar%aviFAIL < 0) RETURN + !------------ POWER REFERENCE TRACKING SETPOINTS -------------- + CALL ParseInput(FileLines, 'PRC_n', CntrPar%PRC_n, accINFILE(1), ErrVar, CntrPar%PRC_Mode == 0) + CALL ParseInput(FileLines, 'PRC_LPF_Freq', CntrPar%PRC_LPF_Freq, accINFILE(1), ErrVar, CntrPar%PRC_Mode == 0) + CALL ParseAry( FileLines, 'PRC_WindSpeeds', CntrPar%PRC_WindSpeeds, CntrPar%PRC_n, accINFILE(1), ErrVar, CntrPar%PRC_Mode == 0) + CALL ParseAry( FileLines, 'PRC_GenSpeeds', CntrPar%PRC_GenSpeeds, CntrPar%PRC_n, accINFILE(1), ErrVar, CntrPar%PRC_Mode == 0) + !------------ WIND SPEED ESTIMATOR CONTANTS -------------- CALL ParseInput(FileLines, 'WE_BladeRadius', CntrPar%WE_BladeRadius, accINFILE(1), ErrVar, .FALSE., UnEc) CALL ParseInput(FileLines, 'WE_Gamma', CntrPar%WE_Gamma, accINFILE(1), ErrVar, CntrPar%WE_Mode .NE. 1, UnEc) @@ -509,9 +473,12 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz IF (ErrVar%aviFAIL < 0) RETURN !------------ FORE-AFT TOWER DAMPER CONSTANTS ------------ - CALL ParseInput(FileLines, 'FA_KI', CntrPar%FA_KI, accINFILE(1), ErrVar, .NOT. ((CntrPar%TD_Mode > 0) .OR. (CntrPar%Y_ControlMode == 2)), UnEc) - CALL ParseInput(FileLines, 'FA_HPFCornerFreq', CntrPar%FA_HPFCornerFreq, accINFILE(1), ErrVar, .NOT. ((CntrPar%TD_Mode > 0) .OR. (CntrPar%Y_ControlMode == 2)), UnEc) - CALL ParseInput(FileLines, 'FA_IntSat', CntrPar%FA_IntSat, accINFILE(1), ErrVar, .NOT. ((CntrPar%TD_Mode > 0) .OR. (CntrPar%Y_ControlMode == 2)), UnEc) + CALL ParseInput(FileLines, 'TRA_ExclSpeed', CntrPar%TRA_ExclSpeed, accINFILE(1), ErrVar, CntrPar%TRA_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'TRA_ExclBand', CntrPar%TRA_ExclBand, accINFILE(1), ErrVar, CntrPar%TRA_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'TRA_RateLimit', CntrPar%TRA_RateLimit, accINFILE(1), ErrVar, CntrPar%TRA_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'FA_KI', CntrPar%FA_KI, accINFILE(1), ErrVar, CntrPar%TD_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'FA_HPFCornerFreq', CntrPar%FA_HPFCornerFreq, accINFILE(1), ErrVar, CntrPar%TD_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'FA_IntSat', CntrPar%FA_IntSat, accINFILE(1), ErrVar, CntrPar%TD_Mode == 0, UnEc) IF (ErrVar%aviFAIL < 0) RETURN !------------ PEAK SHAVING ------------ @@ -526,7 +493,10 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz IF (ErrVar%aviFAIL < 0) RETURN !------------ FLOATING ------------ - CALL ParseInput(FileLines, 'Fl_Kp', CntrPar%Fl_Kp, accINFILE(1), ErrVar, CntrPar%FL_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'Fl_n', CntrPar%Fl_n, accINFILE(1), ErrVar, .TRUE., UnEc) + IF (CntrPar%Fl_n == 0) CntrPar%Fl_n = 1 ! Default is 1 + CALL ParseAry(FileLines, 'Fl_Kp', CntrPar%Fl_Kp, CntrPar%Fl_n, accINFILE(1), ErrVar, CntrPar%FL_Mode == 0, UnEc) + CALL ParseAry(FileLines, 'Fl_U', CntrPar%Fl_U, CntrPar%Fl_n, accINFILE(1), ErrVar, CntrPar%Fl_n == 1, UnEc) ! Allow default if only one Fl_Kp IF (ErrVar%aviFAIL < 0) RETURN !------------ Flaps ------------ @@ -538,13 +508,14 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz !------------ Open loop input ------------ ! Indices can be left 0 by default, checked later - CALL ParseInput(FileLines, 'OL_Filename', CntrPar%OL_Filename, accINFILE(1), ErrVar, CntrPar%OL_Mode == 0, UnEc) - CALL ParseInput(FileLines, 'Ind_Breakpoint', CntrPar%Ind_Breakpoint, accINFILE(1), ErrVar, UnEc=UnEc) - CALL ParseInput(FileLines, 'Ind_BldPitch', CntrPar%Ind_BldPitch, accINFILE(1), ErrVar, UnEc=UnEc) - CALL ParseInput(FileLines, 'Ind_GenTq', CntrPar%Ind_GenTq, accINFILE(1), ErrVar, UnEc=UnEc) - CALL ParseInput(FileLines, 'Ind_YawRate', CntrPar%Ind_YawRate, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines, 'OL_Filename', CntrPar%OL_Filename, accINFILE(1), ErrVar, CntrPar%OL_Mode == 0, UnEc) + CALL ParseInput(FileLines, 'Ind_Breakpoint', CntrPar%Ind_Breakpoint, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseAry( FileLines, 'Ind_BldPitch', CntrPar%Ind_BldPitch, 3, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines, 'Ind_GenTq', CntrPar%Ind_GenTq, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines, 'Ind_YawRate', CntrPar%Ind_YawRate, accINFILE(1), ErrVar, UnEc=UnEc) + CALL ParseInput(FileLines, 'Ind_Azimuth', CntrPar%Ind_Azimuth, accINFILE(1), ErrVar, CntrPar%OL_Mode .NE. 2, UnEc=UnEc) + CALL ParseAry( FileLines, 'RP_Gains', CntrPar%RP_Gains, 4, accINFILE(1), ErrVar, CntrPar%OL_Mode .NE. 2, UnEc=UnEc) IF (ErrVar%aviFAIL < 0) RETURN - !------------ Pitch Actuator Inputs ------------ CALL ParseInput(FileLines, 'PA_CornerFreq', CntrPar%PA_CornerFreq, accINFILE(1), ErrVar, CntrPar%PA_Mode == 0, UnEc) @@ -571,6 +542,7 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz IF (ErrVar%aviFAIL < 0) RETURN !------------ ZeroMQ ------------ + CALL ParseInput(FileLines, 'ZMQ_ID', CntrPar%ZMQ_ID, accINFILE(1), ErrVar, .TRUE., UnEc=UnEc) CALL ParseInput(FileLines, 'ZMQ_CommAddress', CntrPar%ZMQ_CommAddress, accINFILE(1), ErrVar, CntrPar%ZMQ_Mode == 0, UnEc) CALL ParseInput(FileLines, 'ZMQ_UpdatePeriod', CntrPar%ZMQ_UpdatePeriod, accINFILE(1), ErrVar, CntrPar%ZMQ_Mode == 0, UnEc) IF (ErrVar%aviFAIL < 0) RETURN @@ -593,7 +565,19 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz IF (UnEc > 0) CLOSE(UnEc) ! Close echo file - !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! + !------------------- + !------------------- CALCULATED CONSTANTS ----------------------- + !---------------------------------------------------------------- + + ! Fix defaults manually for now + IF (CntrPar%DT_Out == 0) THEN + CntrPar%DT_Out = LocalVar%DT + ENDIF + + ! DT_Out + CntrPar%n_DT_Out = NINT(CntrPar%DT_Out / LocalVar%DT) + CntrPar%n_DT_ZMQ = NINT(CntrPar%ZMQ_UpdatePeriod / LocalVar%DT) + ! Fix Paths (add relative paths if called from another dir, UnEc) IF (PathIsRelative(CntrPar%PerfFileName)) CntrPar%PerfFileName = TRIM(PriPath)//TRIM(CntrPar%PerfFileName) @@ -601,17 +585,141 @@ SUBROUTINE ReadControlParameterFileSub(CntrPar, zmqVar, accINFILE, accINFILE_siz ! Convert yaw rate to deg/s CntrPar%Y_Rate = CntrPar%Y_Rate * R2D - - ! END OF INPUT FILE - - ! Close Input File - CLOSE(UnControllerParameters) - - !------------------- CALCULATED CONSTANTS ----------------------- + CntrPar%PC_RtTq99 = CntrPar%VS_RtTq*0.99 CntrPar%VS_MinOMTq = CntrPar%VS_Rgn2K*CntrPar%VS_MinOMSpd**2 CntrPar%VS_MaxOMTq = CntrPar%VS_Rgn2K*CntrPar%VS_RefSpd**2 + + ! Read open loop input, if desired + IF (CntrPar%OL_Mode > 0) THEN + OL_String = '' ! Display string + OL_Count = 1 + IF (CntrPar%Ind_BldPitch(1) > 0) THEN + OL_String = TRIM(OL_String)//' BldPitch1 ' + OL_Count = OL_Count + 1 + ENDIF + + IF (CntrPar%Ind_BldPitch(2) > 0) THEN + OL_String = TRIM(OL_String)//' BldPitch2 ' + ! If there are duplicate indices, don't increment OL_Count + IF (.NOT. ((CntrPar%Ind_BldPitch(2) == CntrPar%Ind_BldPitch(1)) .OR. & + (CntrPar%Ind_BldPitch(2) == CntrPar%Ind_BldPitch(3)))) THEN + OL_Count = OL_Count + 1 + ENDIF + ENDIF + + IF (CntrPar%Ind_BldPitch(3) > 0) THEN + OL_String = TRIM(OL_String)//' BldPitch3 ' + ! If there are duplicate indices, don't increment OL_Count + IF (.NOT. ((CntrPar%Ind_BldPitch(3) == CntrPar%Ind_BldPitch(1)) .OR. & + (CntrPar%Ind_BldPitch(3) == CntrPar%Ind_BldPitch(2)))) THEN + OL_Count = OL_Count + 1 + ENDIF + ENDIF + + IF (CntrPar%Ind_GenTq > 0) THEN + OL_String = TRIM(OL_String)//' GenTq ' + OL_Count = OL_Count + 1 ! Read channel still, so we don't have issues + ENDIF + + IF (CntrPar%Ind_YawRate > 0) THEN + OL_String = TRIM(OL_String)//' YawRate ' + OL_Count = OL_Count + 1 + ENDIF + + IF (CntrPar%Ind_Azimuth > 0) THEN + IF (CntrPar%OL_Mode == 2) THEN + OL_String = TRIM(OL_String)//' Azimuth ' + OL_Count = OL_Count + 1 + END IF + ENDIF + + N_OL_Cables = 0 + IF (ANY(CntrPar%Ind_CableControl > 0)) THEN + DO I = 1,SIZE(CntrPar%Ind_CableControl) + IF (CntrPar%Ind_CableControl(I) > 0) THEN + OL_String = TRIM(OL_String)//' Cable'//TRIM(Int2LStr(I))//' ' + OL_Count = OL_Count + 1 + N_OL_Cables = N_OL_Cables + 1 + ENDIF + ENDDO + ENDIF + + N_OL_StCs = 0 + IF (ANY(CntrPar%Ind_StructControl > 0)) THEN + DO I = 1,SIZE(CntrPar%Ind_StructControl) + IF (CntrPar%Ind_StructControl(I) > 0) THEN + OL_String = TRIM(OL_String)//' StC'//TRIM(Int2LStr(I))//' ' + OL_Count = OL_Count + 1 + N_OL_StCs = N_OL_StCs + 1 + ENDIF + ENDDO + ENDIF + + + PRINT *, 'ROSCO: Implementing open loop control for'//TRIM(OL_String) + IF (CntrPar%OL_Mode == 2) THEN + PRINT *, 'ROSCO: OL_Mode = 2 will change generator torque control for Azimuth tracking' + ENDIF + + CALL GetNewUnit(UnOpenLoop, ErrVar) + CALL Read_OL_Input(CntrPar%OL_Filename,UnOpenLoop,OL_Count,CntrPar%OL_Channels, ErrVar) + IF (ErrVar%aviFAIL < 0) THEN + RETURN + ENDIF + + CntrPar%OL_Breakpoints = CntrPar%OL_Channels(:,CntrPar%Ind_Breakpoint) + + ! Set OL Inputs based on indices + IF (CntrPar%Ind_BldPitch(1) > 0) THEN + CntrPar%OL_BldPitch1 = CntrPar%OL_Channels(:,CntrPar%Ind_BldPitch(1)) + ENDIF + + IF (CntrPar%Ind_BldPitch(2) > 0) THEN + CntrPar%OL_BldPitch2 = CntrPar%OL_Channels(:,CntrPar%Ind_BldPitch(2)) + ENDIF + + IF (CntrPar%Ind_BldPitch(3) > 0) THEN + CntrPar%OL_BldPitch3 = CntrPar%OL_Channels(:,CntrPar%Ind_BldPitch(3)) + ENDIF + + IF (CntrPar%Ind_GenTq > 0) THEN + CntrPar%OL_GenTq = CntrPar%OL_Channels(:,CntrPar%Ind_GenTq) + ENDIF + + IF (CntrPar%Ind_YawRate > 0) THEN + CntrPar%OL_YawRate = CntrPar%OL_Channels(:,CntrPar%Ind_YawRate) + ENDIF + + IF (CntrPar%Ind_Azimuth > 0) THEN + CntrPar%OL_Azimuth = Unwrap(CntrPar%OL_Channels(:,CntrPar%Ind_Azimuth),ErrVar) + ENDIF + + IF (ANY(CntrPar%Ind_CableControl > 0)) THEN + ALLOCATE(CntrPar%OL_CableControl(N_OL_Cables,SIZE(CntrPar%OL_Channels,DIM=1))) + I_OL = 1 + DO I = 1,SIZE(CntrPar%Ind_CableControl) + IF (CntrPar%Ind_CableControl(I) > 0) THEN + CntrPar%OL_CableControl(I_OL,:) = CntrPar%OL_Channels(:,CntrPar%Ind_CableControl(I)) + I_OL = I_OL + 1 + ENDIF + ENDDO + ENDIF + + IF (ANY(CntrPar%Ind_StructControl > 0)) THEN + ALLOCATE(CntrPar%OL_StructControl(N_OL_StCs,SIZE(CntrPar%OL_Channels,DIM=1))) + I_OL = 1 + DO I = 1,SIZE(CntrPar%Ind_StructControl) + IF (CntrPar%Ind_StructControl(I) > 0) THEN + CntrPar%OL_StructControl(I_OL,:) = CntrPar%OL_Channels(:,CntrPar%Ind_StructControl(I)) + I_OL = I_OL + 1 + ENDIF + ENDDO + ENDIF + + END IF + !------------------- HOUSEKEEPING ----------------------- CntrPar%PerfFileName = TRIM(CntrPar%PerfFileName) @@ -699,8 +807,8 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) IMPLICIT NONE ! Inputs - TYPE(ControlParameters), INTENT(IN ) :: CntrPar - TYPE(LocalVariables), INTENT(IN ) :: LocalVar + TYPE(ControlParameters), INTENT(INOUT) :: CntrPar + TYPE(LocalVariables), INTENT(INOUT) :: LocalVar TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar INTEGER(IntKi), INTENT(IN ) :: size_avcMSG INTEGER(IntKi) :: Imode ! Index used for looping through AWC modes @@ -724,24 +832,33 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ErrVar%ErrMsg = 'LoggingLevel must be 0 - 3.' ENDIF - !------- CONTROLLER FLAGS ------------------------------------------------- + IF (CntrPar%DT_Out .le. 0) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'DT_Out must be greater than 0' + ENDIF - ! F_LPFType - IF ((CntrPar%F_LPFType < 1) .OR. (CntrPar%F_LPFType > 2)) THEN + IF (CntrPar%DT_Out < LocalVar%DT) THEN ErrVar%aviFAIL = -1 - ErrVar%ErrMsg = 'F_LPFType must be 1 or 2.' + ErrVar%ErrMsg = 'DT_Out must be greater than or equal to DT in OpenFAST' ENDIF - ! F_NotchType - IF ((CntrPar%F_NotchType < 0) .OR. (CntrPar%F_NotchType > 3)) THEN + IF (ABS(CntrPar%DT_out - Localvar%DT * CntrPar%n_DT_Out) > 0.001_DbKi) THEN ErrVar%aviFAIL = -1 - ErrVar%ErrMsg = 'F_NotchType must be 0, 1, 2, or 3.' + ErrVar%ErrMsg = 'DT_Out must be a factor of DT in OpenFAST' ENDIF - ! F_NotchType - IF ((CntrPar%F_NotchType < 0) .OR. (CntrPar%F_NotchType > 2)) THEN + IF (CntrPar%ZMQ_Mode > 0) THEN + IF (ABS(CntrPar%ZMQ_UpdatePeriod - Localvar%DT * CntrPar%n_DT_ZMQ) > 0.001_DbKi) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'ZMQ_UpdatePeriod must be a factor of DT in OpenFAST' + ENDIF + ENDIF + !------- CONTROLLER FLAGS ------------------------------------------------- + + ! F_LPFType + IF ((CntrPar%F_LPFType < 1) .OR. (CntrPar%F_LPFType > 2)) THEN ErrVar%aviFAIL = -1 - ErrVar%ErrMsg = 'F_NotchType must be 0, 1, or 2.' + ErrVar%ErrMsg = 'F_LPFType must be 1 or 2.' ENDIF ! IPC_ControlMode @@ -756,6 +873,12 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ErrVar%ErrMsg = 'VS_ControlMode must be 0, 1, 2, or 3.' ENDIF + ! VS_ConstPower + IF ((CntrPar%VS_ConstPower < 0) .OR. (CntrPar%VS_ConstPower > 1)) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'VS_ConstPower must be 0 or 1.' + ENDIF + ! PC_ControlMode IF ((CntrPar%PC_ControlMode < 0) .OR. (CntrPar%PC_ControlMode > 1)) THEN ErrVar%aviFAIL = -1 @@ -830,18 +953,18 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ENDIF ! Notch Filter Params - IF (CntrPar%F_NotchType > 0) THEN + IF (CntrPar%F_NumNotchFilts > 0) THEN ! F_NotchCornerFreq - IF (CntrPar%F_NotchCornerFreq <= 0.0) THEN + IF (ANY(CntrPar%F_NotchFreqs <= 0.0)) THEN ErrVar%aviFAIL = -1 - ErrVar%ErrMsg = 'F_NotchCornerFreq must be greater than zero.' + ErrVar%ErrMsg = 'F_NotchFreqs must be greater than zero.' ENDIF - ! F_NotchBetaNumDen(2) - IF (CntrPar%F_NotchBetaNumDen(2) <= 0.0) THEN + ! F_NotchBetaDen + IF (ANY(CntrPar%F_NotchBetaDen <= 0.0)) THEN ErrVar%aviFAIL = -1 - ErrVar%ErrMsg = 'F_NotchBetaNumDen(2) must be greater than zero.' + ErrVar%ErrMsg = 'F_NotchBetaDen must be greater than zero.' ENDIF ENDIF @@ -1029,6 +1152,10 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ErrVar%aviFAIL = -1 ErrVar%ErrMsg = 'SS_PCGain must be greater than zero.' ENDIF + + IF (CntrPar%PRC_Mode > 0) THEN + PRINT *, "Note: PRC Mode = ", CntrPar%PRC_Mode, ", which will ignore VS_RefSpeed, VS_TSRopt, and PC_RefSpeed" + ENDIF !------- WIND SPEED ESTIMATOR --------------------------------------------- @@ -1095,6 +1222,44 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ENDIF ENDIF + ! ---- Tower Control ---- + IF (CntrPar%TD_Mode < 0 .OR. CntrPar%TD_Mode > 1) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'TD_Mode must be 0 or 1.' + END IF + + IF (CntrPar%TRA_Mode < 0 .OR. CntrPar%TRA_Mode > 1) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'TRA_Mode must be 0 or 1.' + END IF + + IF (CntrPar%TRA_Mode > 1) THEN ! Frequency avoidance is active + IF (CntrPar%TRA_ExclSpeed < 0) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'TRA_ExclSpeed must be greater than 0.' + END IF + + IF (CntrPar%TRA_ExclBand < 0) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'TRA_ExclBand must be greater than 0.' + END IF + + IF (CntrPar%TRA_RateLimit < 0) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'TRA_RateLimit must be greater than 0.' + END IF + + IF ( .NOT. ((CntrPar%VS_ControlMode == 2) .OR. (CntrPar%VS_ControlMode == 3) )) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'VS_ControlMode must be 2 or 3 to use frequency avoidance control.' + END IF + + IF (CntrPar%PRC_Mode == 1) THEN + PRINT *, "ROSCO Warning: Note that frequency avoidance control (TRA_Mode > 1) will affect PRC set points" + END IF + + END IF + !------- MINIMUM PITCH SATURATION ------------------------------------------- IF (CntrPar%PS_Mode > 0) THEN @@ -1113,18 +1278,11 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ENDIF - ! --- Floating Control --- - IF (CntrPar%Fl_Mode > 0) THEN - IF (CntrPar%F_NotchType < 1 .OR. CntrPar%F_NotchCornerFreq == 0.0) THEN - ErrVar%aviFAIL = -1 - ErrVar%ErrMsg = 'F_NotchType and F_NotchCornerFreq must be specified for Fl_Mode greater than zero.' - ENDIF - ENDIF ! --- Open loop control --- IF (CntrPar%OL_Mode > 0) THEN ! Get all open loop indices - ALLOCATE(All_OL_Indices(3)) ! Will need to increase to 5 when IPC + ALLOCATE(All_OL_Indices(5)) ! Will need to increase to 5 when IPC All_OL_Indices = (/CntrPar%Ind_BldPitch, & CntrPar%Ind_GenTq, & CntrPar%Ind_YawRate/) @@ -1152,6 +1310,17 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ErrVar%ErrMsg = 'At least one open loop input channel must be non-zero' ENDIF + IF (CntrPar%OL_Mode == 2) THEN + IF ((CntrPar%Ind_BldPitch(1) == 0) .OR. & + (CntrPar%Ind_BldPitch(2) == 0) .OR. & + (CntrPar%Ind_BldPitch(3) == 0) .OR. & + (CntrPar%Ind_GenTq == 0) .OR. & + (CntrPar%Ind_Azimuth == 0)) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'If OL_Mode = 2, Ind_BldPitch, Ind_GenTq, and Ind_Azimuth must be greater than zero' + ENDIF + ENDIF + IF (ANY(CntrPar%Ind_CableControl > 0) .AND. CntrPar%CC_Mode .NE. 2) THEN ErrVar%aviFAIL = -1 ErrVar%ErrMsg = 'CC_Mode must be 2 if using open loop cable control via Ind_CableControl' @@ -1170,6 +1339,8 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) PRINT *, "ROSCO WARNING: Individual pitch control and active wake control are both enabled. Performance may be compromised." ENDIF + + ! --- Pitch Actuator --- IF (CntrPar%PA_Mode > 0) THEN IF ((CntrPar%PA_Mode < 0) .OR. (CntrPar%PA_Mode > 2)) THEN @@ -1235,6 +1406,13 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) END IF IF (CntrPar%CC_Mode > 0) THEN + + ! Extended avrSWAP must be used + IF (CntrPar%Ext_Interface == 0) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'The OpenFAST extended bladed interface must be used with Ext_Interface > 0 in the DISCON' + ENDIF + IF (CntrPar%CC_ActTau .LE. 0) THEN ErrVar%aviFAIL = -1 ErrVar%ErrMsg = 'CC_ActTau must be greater than 0.' @@ -1249,6 +1427,14 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) END IF IF (CntrPar%StC_Mode > 0) THEN + + ! Extended avrSWAP must be used + IF (CntrPar%Ext_Interface == 0) THEN + ErrVar%aviFAIL = -1 + ErrVar%ErrMsg = 'The OpenFAST extended bladed interface must be used with Ext_Interface > 0 in the DISCON' + ENDIF + + ! Check indices DO I = 1,CntrPar%StC_Group_N IF (CntrPar%StC_GroupIndex(I) < 2801) THEN ErrVar%aviFAIL = -1 @@ -1277,7 +1463,12 @@ SUBROUTINE CheckInputs(LocalVar, CntrPar, avrSWAP, ErrVar, size_avcMSG) ErrVar%ErrMsg = 'Pitch angle actuator not requested.' ENDIF - IF (NINT(avrSWAP(28)) == 0 .AND. ((CntrPar%IPC_ControlMode > 0) .OR. (CntrPar%Y_ControlMode > 1))) THEN + IF ((NINT(avrSWAP(28)) == 0) .AND. & + ((CntrPar%IPC_ControlMode > 0) .OR. & + (CntrPar%Y_ControlMode > 1) .OR. & + (CntrPar%Ind_BldPitch(2) > 0) .OR. & + (CntrPar%Ind_BldPitch(3) > 0) & + )) THEN ErrVar%aviFAIL = -1 ErrVar%ErrMsg = 'IPC enabled, but Ptch_Cntrl in ServoDyn has a value of 0. Set it to 1 for individual pitch control.' ENDIF diff --git a/ROSCO/src/SysFiles/SysGnuLinux.f90 b/rosco/controller/src/SysFiles/SysGnuLinux.f90 similarity index 100% rename from ROSCO/src/SysFiles/SysGnuLinux.f90 rename to rosco/controller/src/SysFiles/SysGnuLinux.f90 diff --git a/ROSCO/src/SysFiles/SysGnuWin.f90 b/rosco/controller/src/SysFiles/SysGnuWin.f90 similarity index 100% rename from ROSCO/src/SysFiles/SysGnuWin.f90 rename to rosco/controller/src/SysFiles/SysGnuWin.f90 diff --git a/ROSCO/src/SysFiles/SysIFL.f90 b/rosco/controller/src/SysFiles/SysIFL.f90 similarity index 100% rename from ROSCO/src/SysFiles/SysIFL.f90 rename to rosco/controller/src/SysFiles/SysIFL.f90 diff --git a/ROSCO/src/SysFiles/SysIVF.f90 b/rosco/controller/src/SysFiles/SysIVF.f90 similarity index 100% rename from ROSCO/src/SysFiles/SysIVF.f90 rename to rosco/controller/src/SysFiles/SysIVF.f90 diff --git a/rosco/controller/src/ZeroMQInterface.f90 b/rosco/controller/src/ZeroMQInterface.f90 new file mode 100644 index 00000000..9a3c1d19 --- /dev/null +++ b/rosco/controller/src/ZeroMQInterface.f90 @@ -0,0 +1,81 @@ +module ZeroMQInterface + USE, INTRINSIC :: ISO_C_BINDING, only: C_CHAR, C_DOUBLE, C_NULL_CHAR + IMPLICIT NONE + ! + +CONTAINS + SUBROUTINE UpdateZeroMQ(LocalVar, CntrPar, ErrVar) + USE ROSCO_Types, ONLY : LocalVariables, ControlParameters, ErrorVariables + IMPLICIT NONE + TYPE(LocalVariables), INTENT(INOUT) :: LocalVar + TYPE(ControlParameters), INTENT(INOUT) :: CntrPar + TYPE(ErrorVariables), INTENT(INOUT) :: ErrVar + + character(256) :: zmq_address + real(C_DOUBLE) :: setpoints(5) + real(C_DOUBLE) :: turbine_measurements(17) + CHARACTER(*), PARAMETER :: RoutineName = 'UpdateZeroMQ' + + ! C interface with ZeroMQ client +#ifdef ZMQ_CLIENT + interface + subroutine zmq_client(zmq_address, measurements, setpoints) bind(C, name='zmq_client') + import :: C_CHAR, C_DOUBLE + implicit none + character(C_CHAR), intent(out) :: zmq_address(*) + real(C_DOUBLE) :: measurements(17) + real(C_DOUBLE) :: setpoints(5) + end subroutine zmq_client + end interface +#endif + + ! Communicate if threshold has been reached + IF ( MOD(LocalVar%n_DT, CntrPar%n_DT_ZMQ) == 0 .OR. LocalVar%iStatus == -1 ) THEN + ! Collect measurements to be sent to ZeroMQ server + turbine_measurements(1) = LocalVar%ZMQ_ID + turbine_measurements(2) = LocalVar%iStatus + turbine_measurements(3) = LocalVar%Time + turbine_measurements(4) = LocalVar%VS_MechGenPwr + turbine_measurements(5) = LocalVar%VS_GenPwr + turbine_measurements(6) = LocalVar%GenSpeed + turbine_measurements(7) = LocalVar%RotSpeed + turbine_measurements(8) = LocalVar%GenTqMeas + turbine_measurements(9) = LocalVar%NacHeading + turbine_measurements(10) = LocalVar%NacVane + turbine_measurements(11) = LocalVar%HorWindV + turbine_measurements(12) = LocalVar%rootMOOP(1) + turbine_measurements(13) = LocalVar%rootMOOP(2) + turbine_measurements(14) = LocalVar%rootMOOP(3) + turbine_measurements(15) = LocalVar%FA_Acc + turbine_measurements(16) = LocalVar%NacIMU_FA_Acc + turbine_measurements(17) = LocalVar%Azimuth + + write (zmq_address, '(A,A)') TRIM(CntrPar%ZMQ_CommAddress), C_NULL_CHAR +#ifdef ZMQ_CLIENT + call zmq_client(zmq_address, turbine_measurements, setpoints) +#else + ! Add RoutineName to error message + ErrVar%aviFAIL = -1 + IF (CntrPar%ZMQ_Mode > 0) THEN + ErrVar%ErrMsg = ' >> The ZeroMQ client has not been properly installed, ' & + //'please install it to use ZMQ_Mode > 0.' + ErrVar%ErrMsg = RoutineName//':'//TRIM(ErrVar%ErrMsg) + ENDIF +#endif + + ! write (*,*) 'ZeroMQInterface: torque setpoint from ssc: ', setpoints(1) + ! write (*,*) 'ZeroMQInterface: yaw setpoint from ssc: ', setpoints(2) + ! write (*,*) 'ZeroMQInterface: pitch 1 setpoint from ssc: ', setpoints(3) + ! write (*,*) 'ZeroMQInterface: pitch 2 setpoint from ssc: ', setpoints(4) + ! write (*,*) 'ZeroMQInterface: pitch 3 setpoint from ssc: ', setpoints(5) + LocalVar%ZMQ_TorqueOffset = setpoints(1) + LocalVar%ZMQ_YawOffset = setpoints(2) + LocalVar%ZMQ_PitOffset(1) = setpoints(3) + LocalVar%ZMQ_PitOffset(2) = setpoints(4) + LocalVar%ZMQ_PitOffset(3) = setpoints(5) + + ENDIF + + + END SUBROUTINE UpdateZeroMQ +end module ZeroMQInterface diff --git a/ROSCO/src/zmq_client.c b/rosco/controller/src/zmq_client.c similarity index 79% rename from ROSCO/src/zmq_client.c rename to rosco/controller/src/zmq_client.c index 0e3974a2..5df4b656 100644 --- a/ROSCO/src/zmq_client.c +++ b/rosco/controller/src/zmq_client.c @@ -7,37 +7,36 @@ void delete_blank_spaces_in_string(char *s) { - int i,k=0; - for(i=0;s[i];i++) + int i,k=0; + for(i=0;s[i];i++) { - s[i]=s[i+k]; - if(s[i]==' '|| s[i]=='\t') - { - k++; - i--; - } + s[i]=s[i+k]; + if(s[i]==" "|| s[i]=="\t") + { + k++; + i--; + } } } int zmq_client ( char *zmq_address, - double measurements[16], + double measurements[17], double setpoints[5] ) { - int num_measurements = 16; // Number of setpoints and measurements, respectively, and float precision (character length) - int char_buffer_size_single = 20; // Char buffer for a single measurement + int num_measurements = 17; // Number of setpoints and measurements, respectively, and float precision (character length) + int char_buffer_size_single = 20; // Char buffer for a single measurement int char_buffer_size_array = (num_measurements * (char_buffer_size_single + 1)); // Char buffer for full messages to and from ROSCO - char string_to_ssc[char_buffer_size_array]; + char string_to_ssc[char_buffer_size_array]; char string_from_ssc[char_buffer_size_array]; - int verbose = 0; // Variable to define verbose - + int verbose = 0; // Variable to define verbose + if (verbose == 1) { printf ("Connecting to ZeroMQ server at %s...\n", zmq_address); } - // Open connection with ZeroMQ server void *context = zmq_ctx_new (); void *requester = zmq_socket (context, ZMQ_REQ); @@ -46,12 +45,12 @@ int zmq_client ( // Create a string with measurements to be sent to ZeroMQ server (e.g., Python) char a[char_buffer_size_array], b[char_buffer_size_single]; sprintf(b, "%.6e", measurements[0]); - strncpy(a, b, char_buffer_size_single); + strncpy(a, b, char_buffer_size_single); //printf ("zmq_client.c: a[char_buffer_size_single]: measurements[0]: %s\n", a); int i = 1; while (i < num_measurements) { - strcat(a, ","); // Add a comma - sprintf(b, "%.6e", measurements[i]); // Add value + strcat(a, ","); // Add a comma + sprintf(b, "%.6e", measurements[i]); // Add value strcat(a, b); // Concatenate b to a //printf ("zmq_client.c: b[char_buffer_size_single]: measurements[i]: %s\n", b); //printf (" --> zmq_client.c: a[char_buffer_size_single]: measurements[i]: %s\n", a); @@ -92,4 +91,4 @@ int zmq_client ( zmq_close (requester); zmq_ctx_destroy (context); return 0; -} \ No newline at end of file +} diff --git a/ROSCO_toolbox/linear/__init__.py b/rosco/lib/__init__.py similarity index 100% rename from ROSCO_toolbox/linear/__init__.py rename to rosco/lib/__init__.py diff --git a/ROSCO_testing/ROSCO_testing.py b/rosco/test/ROSCO_testing.py similarity index 95% rename from ROSCO_testing/ROSCO_testing.py rename to rosco/test/ROSCO_testing.py index 7ddfea70..8b4f61d3 100644 --- a/ROSCO_testing/ROSCO_testing.py +++ b/rosco/test/ROSCO_testing.py @@ -13,17 +13,20 @@ ''' import numpy as np -import os, platform -import glob +import os +import platform import multiprocessing as mp -from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST -from ROSCO_toolbox.ofTools.case_gen.CaseGen_IEC import CaseGen_IEC -from ROSCO_toolbox.ofTools.case_gen.runFAST_pywrapper import runFAST_pywrapper_batch -from matplotlib.backends.backend_pdf import FigureCanvasPdf, PdfPages -from ROSCO_toolbox.ofTools.fast_io import output_processing +from rosco import discon_lib_path +from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +from rosco.toolbox.ofTools.case_gen.CaseGen_IEC import CaseGen_IEC +from rosco.toolbox.ofTools.case_gen.runFAST_pywrapper import runFAST_pywrapper_batch +from matplotlib.backends.backend_pdf import PdfPages #, FigureCanvasPdf +from rosco.toolbox.ofTools.fast_io import output_processing import matplotlib.pyplot as plt +this_dir = os.path.dirname(os.path.realpath(__file__)) +rosco_root = os.path.dirname( os.path.dirname( this_dir ) ) class ROSCO_testing(): @@ -35,17 +38,14 @@ def __init__(self, **kwargs): # Setup simulation parameters - self.runDir = os.path.join(os.path.dirname( os.path.realpath(__file__) ), 'testing' ) # directory to run simulations in + self.runDir = os.path.join(this_dir, 'testing' ) # directory to run simulations in self.wind_dir = None self.namebase = 'ROtest' # root name for output simulations self.FAST_exe = 'openfast_single' # name of openfast executable (may need full path) self.Turbsim_exe = 'turbsim_single' # name of turbsim executable self.FAST_ver = 'OpenFAST' # Fast version # Path to ROSCO controller - default to ROSCO Toolbox submodule - try: - self.rosco_path = glob.glob(os.path.join(os.path.dirname(os.path.realpath(__file__)),'../ROSCO/build/libdiscon.*'))[0] - except: - print('No compiled ROSCO version found, please provide ROSCO_testing.rosco_path.') + self.rosco_path = discon_lib_path self.debug_level = 2 # debug level. 0 - no outputs, 1 - minimal outputs, 2 - all outputs self.overwrite = False # overwrite existing files? self.cores = 4 # number of cores to use @@ -58,7 +58,7 @@ def __init__(self, **kwargs): # - Default to NREL 5MW self.Turbine_Class = 'I' self.Turbulence_Class = 'A' - self.FAST_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../Test_Cases/NREL-5MW') + self.FAST_directory = os.path.join(rosco_root, 'Examples', 'Test_Cases','NREL-5MW') self.FAST_InputFile = 'NREL-5MW.fst' # Desired output channesl @@ -544,9 +544,6 @@ def print_results(self,outfiles): if __name__=='__main__': rt = ROSCO_testing() - this_dir = os.path.dirname(__file__) - - ## =================== INITIALIZATION =================== # Setup simulation parameters rt.namebase = 'IEA-15MW' # Base name for FAST files @@ -554,11 +551,13 @@ def print_results(self,outfiles): rt.Turbsim_exe = 'turbsim' # Turbsim executable path # path to compiled ROSCO controller if platform.system() == 'Windows': - rt.rosco_path = os.path.join(this_dir, '../ROSCO/build/libdiscon.dll') + sfx = 'dll' elif platform.system() == 'Darwin': - rt.rosco_path = os.path.join(this_dir, '../ROSCO/build/libdiscon.dylib') + sfx = 'dylib' else: - rt.rosco_path = os.path.join(this_dir, '../ROSCO/build/libdiscon.so') + sfx = 'so' + rt.rosco_path = discon_lib_path + rt.debug_level = 2 # debug level. 0 - no outputs, 1 - minimal outputs, 2 - all outputs rt.overwrite = True # overwite fast sims? rt.cores = 1 # number of cores if multiprocessings @@ -569,7 +568,7 @@ def print_results(self,outfiles): # Setup turbine rt.Turbine_Class = 'I' rt.Turbulence_Class = 'B' - rt.FAST_directory = os.path.join(this_dir, '../Test_Cases/IEA-15-240-RWT-UMaineSemi') + rt.FAST_directory = os.path.join(rosco_root, 'Examples','Test_Cases','IEA-15-240-RWT-UMaineSemi') rt.FAST_InputFile = 'IEA-15-240-RWT-UMaineSemi.fst' # Additional inputs diff --git a/ROSCO_testing/__init__.py b/rosco/test/__init__.py similarity index 100% rename from ROSCO_testing/__init__.py rename to rosco/test/__init__.py diff --git a/ROSCO_testing/run_Testing.py b/rosco/test/run_Testing.py similarity index 92% rename from ROSCO_testing/run_Testing.py rename to rosco/test/run_Testing.py index f10c0d01..1a375bb1 100644 --- a/ROSCO_testing/run_Testing.py +++ b/rosco/test/run_Testing.py @@ -5,7 +5,7 @@ import os import glob import ROSCO_testing -import importlib +from rosco import discon_lib_path os.system("taskset -p 0xffffffffffff %d" % os.getpid()) @@ -52,12 +52,12 @@ def run_testing(turbine2test, testtype, rosco_binaries=[], discon_files=[], **kw if turbine2test == 'NREL-5MW': rt.Turbine_Class = 'I' rt.Turbulence_Class = 'A' - rt.FAST_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../Test_Cases/NREL-5MW') + rt.FAST_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../Examples/Test_Cases/NREL-5MW') rt.FAST_InputFile = 'NREL-5MW.fst' elif turbine2test == 'IEA-15MW': rt.Turbine_Class = 'I' rt.Turbulence_Class = 'B' - rt.FAST_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../Test_Cases/IEA-15-240-RWT-UMaineSemi') + rt.FAST_directory = os.path.join(os.path.dirname(os.path.realpath(__file__)), '../../Examples/Test_Cases/IEA-15-240-RWT-UMaineSemi') rt.FAST_InputFile = 'IEA-15-240-RWT-UMaineSemi.fst' else: raise ValueError('{} is not an available turbine to test!'.format(turbine2test)) @@ -106,8 +106,8 @@ def run_testing(turbine2test, testtype, rosco_binaries=[], discon_files=[], **kw testtype = 'heavy' # lite, heavy, binary-comp, discon-comp # Only fill one of these if comparing controllers - rosco_binaries = [glob.glob(os.path.join(this_dir,'../ROSCO/build/libdiscon.*'))[0]] # Differently named libdiscons to compare discon_files = [] # Differently named DISCON.IN files to compare # Run testing - run_testing(turbine2test, testtype, rosco_binaries=rosco_binaries, discon_files=discon_files, **rt_kwargs) + run_testing(turbine2test, testtype, rosco_binaries=discon_lib_path, + discon_files=discon_files, **rt_kwargs) diff --git a/ROSCO_testing/submit.sh b/rosco/test/submit.sh similarity index 100% rename from ROSCO_testing/submit.sh rename to rosco/test/submit.sh diff --git a/ROSCO_testing/test_checkpoint.py b/rosco/test/test_checkpoint.py similarity index 77% rename from ROSCO_testing/test_checkpoint.py rename to rosco/test/test_checkpoint.py index e1d15f03..78c65db8 100644 --- a/ROSCO_testing/test_checkpoint.py +++ b/rosco/test/test_checkpoint.py @@ -11,44 +11,36 @@ import numpy as np # Python Modules -import os -import platform from shutil import copyfile # ROSCO toolbox modules -from ROSCO_toolbox.inputs.validation import load_rosco_yaml -from ROSCO_toolbox.ofTools.fast_io import output_processing -from ROSCO_toolbox.ofTools.case_gen.CaseLibrary import set_channels -from ROSCO_toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General -from ROSCO_toolbox.ofTools.fast_io.FAST_writer import InputReader_OpenFAST, InputWriter_OpenFAST -from ROSCO_toolbox.utilities import run_openfast +from rosco import discon_lib_path +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.ofTools.fast_io import output_processing +from rosco.toolbox.ofTools.case_gen.CaseLibrary import set_channels +from rosco.toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General +from rosco.toolbox.ofTools.fast_io.FAST_writer import InputReader_OpenFAST, InputWriter_OpenFAST +from rosco.toolbox.utilities import run_openfast class RegressionTesting(unittest.TestCase): def test_restart(self): this_dir = os.path.dirname(os.path.abspath(__file__)) - rosco_dir = os.path.dirname(this_dir) + rosco_dir = os.path.dirname( os.path.dirname(this_dir) ) test_out_dir = os.path.join(this_dir, 'test_out') # Load yaml file (Open Loop Case) - parameter_filename = os.path.join(rosco_dir, 'Tune_Cases/IEA15MW.yaml') + tune_directory = os.path.join(rosco_dir,'Examples','Tune_Cases') + parameter_filename = os.path.join(tune_directory, 'IEA15MW.yaml') inps = load_rosco_yaml(parameter_filename) path_params = inps['path_params'] turbine_params = inps['turbine_params'] controller_params = inps['controller_params'] - # Set rosco_dll - if platform.system() == 'Windows': - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.dll') - elif platform.system() == 'Darwin': - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.dylib') - else: - rosco_dll = os.path.join(rosco_dir, 'ROSCO/build/libdiscon.so') - case_inputs = {} case_inputs[('Fst', 'TMax')] = {'vals': [3.], 'group': 0} - case_inputs[('ServoDyn', 'DLL_FileName')] = {'vals': [rosco_dll], 'group': 0} + case_inputs[('ServoDyn', 'DLL_FileName')] = {'vals': [discon_lib_path], 'group': 0} case_inputs[('Fst', 'ChkptTime')] = {'vals': [1.], 'group': 1} case_inputs[('Fst', 'OutFileFmt')] = {'vals': [2], 'group': 1} case_inputs[('Fst', 'DT')] = {'vals': [0.025], 'group': 0} @@ -67,7 +59,8 @@ def test_restart(self): reader = InputReader_OpenFAST() writer = InputWriter_OpenFAST() reader.FAST_InputFile = path_params['FAST_InputFile'] - reader.FAST_directory = os.path.realpath(os.path.join( rosco_dir, 'Tune_Cases', path_params['FAST_directory'])) + reader.FAST_directory = os.path.realpath(os.path.join( tune_directory, path_params['FAST_directory'])) + reader.execute() writer.fst_vt = reader.fst_vt writer.FAST_runDirectory = test_out_dir @@ -115,6 +108,7 @@ def test_restart(self): fig, ax = op.plot_fast_out(cases=cases, showplot=False) plt.show() + print(fastout[1]['GenPwr'], fastout[0]['GenPwr']) self.check_relative_error(fastout[1]['GenPwr'], fastout[0]['GenPwr'], 1e-3) def check_relative_error(self, meas, real, tol): diff --git a/Examples/test_examples.py b/rosco/test/test_examples.py similarity index 72% rename from Examples/test_examples.py rename to rosco/test/test_examples.py index 0bd6840e..2aa44cc0 100644 --- a/Examples/test_examples.py +++ b/rosco/test/test_examples.py @@ -19,18 +19,27 @@ '14_open_loop_control', '15_pass_through', '16_external_dll', - '17_zeromq_interface', # NJA: only runs on unix in CI + '17a_zeromq_simple', # only runs on unix in CI + '17b_zeromq_multi_openfast', # only runs on unix in CI '18_pitch_offsets', '19_update_discon_version', '20_active_wake_control', '21_optional_inputs', '22_cable_control', + '23_structural_control', + '24_floating_feedback', + '25_rotor_position_control', + '26_marine_hydro', + '27_power_ref_control', + '28_tower_resonance', 'update_rosco_discons', ] def execute_script(fscript): - examples_dir = os.path.dirname(os.path.realpath(__file__)) - test_case_dir = os.path.realpath(os.path.join(os.path.dirname(os.path.realpath(__file__)),'../Test_Cases')) + this_dir = os.path.dirname(os.path.abspath(__file__)) + rosco_dir = os.path.dirname( os.path.dirname(this_dir) ) + examples_dir = os.path.join(rosco_dir,'Examples') + test_case_dir = os.path.join(examples_dir,'Test_Cases') # Go to location due to relative path use for airfoil files print("\n\n") @@ -49,7 +58,7 @@ def execute_script(fscript): # Use runpy to execute examples s = time() runpy.run_path(os.path.realpath(fullpath), run_name='__main__') - print(time() - s, "seconds to run") + print(f"{fscript} took {time() - s} seconds to run") class TestExamples(unittest.TestCase): diff --git a/ROSCO_toolbox/__init__.py b/rosco/toolbox/__init__.py similarity index 63% rename from ROSCO_toolbox/__init__.py rename to rosco/toolbox/__init__.py index e200b2d2..3aa708bc 100644 --- a/ROSCO_toolbox/__init__.py +++ b/rosco/toolbox/__init__.py @@ -1,6 +1,6 @@ # -*- coding: utf-8 -*- -"""Top-level package for ROSCO_toolbox Repo.""" +"""Top-level package for ROSCO Repo.""" __author__ = """Nikhar J. Abbas and Daniel S. Zalkind""" __email__ = 'daniel.zalkind@nrel.gov' -__version__ = '2.8.0' +__version__ = '2.9.0' diff --git a/rosco/toolbox/control_interface.py b/rosco/toolbox/control_interface.py new file mode 100644 index 00000000..1a92decf --- /dev/null +++ b/rosco/toolbox/control_interface.py @@ -0,0 +1,582 @@ +# Copyright 2019 NREL + +# Licensed under the Apache License, Version 2.0 (the "License"); you may not use +# this file except in compliance with the License. You may obtain a copy of the +# License at http://www.apache.org/licenses/LICENSE-2.0 + +# Unless required by applicable law or agreed to in writing, software distributed +# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR +# CONDITIONS OF ANY KIND, either express or implied. See the License for the +# specific language governing permissions and limitations under the License. + +import ctypes +from ctypes import ( + byref, + cdll, + POINTER, + c_float, + c_char_p, + #c_double, + create_string_buffer, + c_int32, + c_void_p, +) +import numpy as np +import platform +import os +import zmq +import logging +from rosco.toolbox.ofTools.util.FileTools import load_yaml + + + +logger = logging.getLogger(__name__) +# Choose logging level below +logger.setLevel(logging.INFO) # For a basic level of logs +# logger.setLevel(logging.DEBUG) # For more detailed logs helpful for debugging + + + +# Some useful constants +deg2rad = np.deg2rad(1) +rad2deg = np.rad2deg(1) +rpm2RadSec = 2.0 * (np.pi) / 60.0 + + +class ControllerInterface: + """ + Define interface to a given controller using the avrSWAP array + + Methods: + -------- + call_discon + call_controller + show_control_values + + Parameters: + ----------- + lib_name : str + name of compiled dynamic library containing controller, (.dll,.so,.dylib) + + """ + + def __init__(self, lib_name, param_filename="DISCON.IN", **kwargs): + """ + Setup the interface + """ + self.lib_name = lib_name + self.param_name = param_filename + + # Set default parameters + # PARAMETERS + self.DT = 0.1 + self.num_blade = 3 + self.char_buffer = 500 + self.avr_size = 500 + self.sim_name = "simDEBUG" + + # Set kwargs, like DT + for k, w in kwargs.items(): + try: + setattr(self, k, w) + except: + pass + + try: + self.init_discon() + except ValueError: + pass + + def init_discon(self): + # Initialize + self.pitch = 0 + self.torque = 0 + # -- discon + self.discon = cdll.LoadLibrary(self.lib_name) + self.avrSWAP = np.zeros(self.avr_size) + + # Define some avrSWAP parameters, NOTE: avrSWAP indices are offset by -1 from Fortran + self.avrSWAP[2] = self.DT + self.avrSWAP[60] = self.num_blade + self.avrSWAP[19] = 1.0 # HARD CODE initial gen speed = 1 rad/s + self.avrSWAP[20] = 1.0 # HARD CODE initial rot speed = 1 rad/s + self.avrSWAP[82] = 0 # HARD CODE initial nacIMU = 0 + self.avrSWAP[26] = 10 # HARD CODE initial wind speed = 10 m/s + + # Blade pitch initial conditions + self.avrSWAP[3] = 0 * np.deg2rad(1) + self.avrSWAP[32] = 0 * np.deg2rad(1) + self.avrSWAP[33] = 0 * np.deg2rad(1) + + self.avrSWAP[27] = 1 # IPC + + # Torque initial condition + self.avrSWAP[22] = 0 + + # Code this as first call + self.avrSWAP[0] = 0 + + # Initialize DISCON and related + self.aviFAIL = c_int32() # 1 + self.accINFILE = self.param_name.encode("utf-8") + self.avcOUTNAME = (self.sim_name).encode("utf-8") + self.avcMSG = create_string_buffer(1000) + self.discon.DISCON.argtypes = [ + POINTER(c_float), + POINTER(c_int32), + c_char_p, + c_char_p, + c_char_p, + ] # (all defined by ctypes) + + # Put some values in + self.avrSWAP[48] = self.char_buffer + self.avrSWAP[49] = len(self.param_name) + self.avrSWAP[50] = len(self.avcOUTNAME) + self.avrSWAP[51] = self.char_buffer + + # Run DISCON + self.call_discon() + + # Code as not first run now that DISCON has been initialized + self.avrSWAP[0] = 1 + + if self.aviFAIL.value < 0: + raise ValueError("ROSCO dynamic library has returned an error") + + def call_discon(self): + """ + Call libdiscon.dll (or .so,.dylib,...) + """ + # Convert AVR swap to the c pointer + c_float_p = POINTER(c_float) + data = self.avrSWAP.astype(np.float32) + p_data = data.ctypes.data_as(c_float_p) + + # Run DISCON + self.discon.DISCON( + p_data, byref(self.aviFAIL), self.accINFILE, self.avcOUTNAME, self.avcMSG + ) + + # Push back to avr swap + self.avrSWAP = data + + def call_controller(self, turbine_state, end=False): + """ + Runs the controller. Passes current turbine state to the controller, and returns control inputs back + + Parameters: + ----------- + turbine_state: dict + t: float + time, (s) + dt: float + timestep, (s) + pitch: float + blade pitch, (rad) + genspeed: float + generator speed, (rad/s) + geneff: float + generator efficiency, (rad/s) + rotspeed: float + rotor speed, (rad/s) + ws: float + wind speed, (m/s) + yaw: float, optional + nacelle yaw position (from north) (deg) + yawerr: float, optional + yaw misalignment, defined as the wind direction minus the yaw + position (deg) + """ + + # Add states to avr + self.avrSWAP[0] = turbine_state["iStatus"] + self.avrSWAP[1] = turbine_state["t"] + self.avrSWAP[2] = turbine_state["dt"] + self.avrSWAP[3] = turbine_state["bld_pitch"] + self.avrSWAP[32] = turbine_state["bld_pitch"] + self.avrSWAP[33] = turbine_state["bld_pitch"] + self.avrSWAP[14] = ( + turbine_state["gen_speed"] + * turbine_state["gen_torque"] + * turbine_state["gen_eff"] + ) + self.avrSWAP[22] = turbine_state["gen_torque"] + self.avrSWAP[19] = turbine_state["gen_speed"] + self.avrSWAP[20] = turbine_state["rot_speed"] + self.avrSWAP[23] = turbine_state["Y_MeasErr"] + self.avrSWAP[26] = turbine_state["ws"] + self.avrSWAP[36] = turbine_state["Yaw_fromNorth"] + try: + self.avrSWAP[82] = turbine_state["NacIMU_FA_Acc"] + except KeyError: + self.avrSWAP[82] = 0 + + # call controller + self.call_discon() + + # return controller states + self.pitch = self.avrSWAP[41] + self.torque = self.avrSWAP[46] + self.nac_yawrate = self.avrSWAP[47] + + return (self.torque, self.pitch, self.nac_yawrate) + + def show_control_values(self): + """ + Show control values - should be obvious + """ + print("Pitch", self.pitch) + print("Torque", self.torque) + + def kill_discon(self): + """ + Unload the dylib from memory: https://github.com/bwoodsend/cslug/blob/master/cslug/_stdlib.py + """ + + print("Shutting down {}".format(self.lib_name)) + handle = self.discon._handle + + # Start copy here + OS = platform.system() + + def null_free_dll(*spam): # pragma: no cover + pass + + # Try to find a good runtime library which is always available and contains + # the standard library C functions such as malloc() or printf(). + # XXX: Keep chosen library names in sync with the table in `cslug/stdlib.py`. + + extra_libs = [] + + if OS == "Windows": # pragma: Windows + try: + _dlclose = ctypes.windll.kernel32.FreeLibrary + dlclose = lambda handle: 0 if _dlclose(handle) else 1 + except: + kernel32 = ctypes.WinDLL("kernel32", use_last_error=True) + kernel32.FreeLibrary.argtypes = [ctypes.wintypes.HMODULE] + dlclose = lambda handle: 0 if kernel32.FreeLibrary(handle) else 1 + # There's some controversy as to whether this DLL is guaranteed to exist. + # It always has so far but isn't documented. However, MinGW assumes that it + # is so, should this DLL be removed, then we have much bigger problems than + # just this line. There is also vcruntime140.dll which isn't a standard part + # of the OS but is always shipped with Python so we can guarantee its + # presence. But vcruntime140 contains only a tiny strict-subset of msvcrt. + stdlib = ctypes.CDLL("msvcrt") + + elif OS == "Darwin": # pragma: Darwin + try: + try: + # macOS 11 (Big Sur). Possibly also later macOS 10s. + stdlib = ctypes.CDLL("libc.dylib") + except OSError: # pragma: no cover + stdlib = ctypes.CDLL("libSystem") + except OSError: # pragma: no cover + # Older macOSs. Not only is the name inconsistent but it's + # not even in PATH. + _stdlib = "/usr/lib/system/libsystem_c.dylib" + if os.path.exists(_stdlib): + stdlib = ctypes.CDLL(_stdlib) + else: + stdlib = None + if stdlib is not None: # pragma: no branch + dlclose = stdlib.dlclose + else: # pragma: no cover + # I hope this never happens. + dlclose = null_free_dll + + elif OS == "Linux": # pragma: Linux + try: + stdlib = ctypes.CDLL("") + except OSError: # pragma: no cover + # Either Alpine Linux or Android. + # Unfortunately, there doesn't seem to be any practical way + # to tell them apart. + stdlib = ctypes.CDLL("libc.so") + + # Android, like FreeBSD puts its math functions + # in a dedicated `libm.so`. + # The only way to know that this is not Alpine is to check if the math + # functions are already available in `libc.so`. + if not hasattr(stdlib, "sin"): + extra_libs.append(ctypes.CDLL("libm.so")) + dlclose = stdlib.dlclose + + # End copy here + dlclose.argtypes = [c_void_p] + dlclose(handle) + + del self.discon + + +class wfc_zmq_server: + """Server side implementation of wind farm control interface for the ROSCO using ZeroMQ + + This class enables users to receive measurements from ROSCO and then send back control + setpoints (generator torque, nacelle heading and/or blade pitch angles) using ZeroMQ + messaging library. + + Attirbutes + ---------- + network_address : str + Address of the server usually in the format "tcp://*:5555" + timeout : float + Time till server time out + verbose : bool + Prints details of messages being passed using the server + logfile : string + Path of the logfile; if logfile is not provided, logging is disabled + + methods + ------- + runserver() + Run the server to recieve and send data to ROSCO controllers + wfc_controller(id, current_time) + User defined method that contains the controller algorithm. + """ + + # Read the interface file to obtain the structure of measurements and setpoints + interface_file = os.path.realpath( + os.path.join( + os.path.dirname(__file__), "../controller/rosco_registry/wfc_interface.yaml" + ) + ) + wfc_interface = load_yaml(interface_file) + + def __init__(self, network_address="tcp://*:5555", timeout=600.0, verbose=False,logfile=None): + """Instanciate the server""" + self.network_address = network_address + self.timeout = timeout + self.verbose = verbose + self.context = zmq.Context() + self.socket = self.context.socket(zmq.REP) + self.connections = wfc_zmq_connections(self.wfc_interface) + self.socket.setsockopt(zmq.LINGER, 0) + self.socket.bind(self.network_address) + if self.verbose: + print( + f"Successfully established connection a ZeroMQ server at {network_address}" + ) + + if logfile is not None: + print(logfile) + logger_filehandler = logging.FileHandler(logfile, "w+") + logger_filehandler.setFormatter(logging.Formatter("%(asctime)s: %(message)s")) + logger.addHandler(logger_filehandler) + else: + logging.disable() + if self.verbose: + print('Logging disabled') + + logger.info( + f"Successfully established connection a ZeroMQ server at {network_address}" + ) + + + def runserver(self): + """Run the server to get measurements and send setpoints to ROSCO""" + connect_zmq = True + while connect_zmq: + # Wait for and obtain measurements from ROSCO + measurements = self._get_measurements() + + # Obtain the identifier from the measurments + id = int(measurements["ZMQ_ID"]) + + # Add turbie id to the list of connected turbines + self.connections._add_unique(id) + + # Update the measurements of the turbine + self.connections._update_measurements(id, measurements) + try: + # Try to get the setpoints of the turbine + logger.debug(f"Trying to get setpoints for id = {id}") + self._get_setpoints(id, measurements) + except NotImplementedError as e: + # Disconnect from the server and raise an error + # if the user has not defined a wind farm controller + self._disconnect() + logger.critical(f'Disconnected due to wfc_controller not being defined by the user') + raise e + else: + # If setpoints are successfully read then + # send the setpoint to the ROSCO client + self._send_setpoints(id) + + # Check if there are no clients connected to the server + # and if so, disconnect the server + logger.debug('Checking for disconnect') + connect_zmq = self._check_for_disconnect() + + def _get_setpoints(self, id, measurements): + """Get current setpoint from the wind farm controller + + Gets the setpoint for the current turbine at the current time step + """ + current_time = self.connections.measurements[id]["Time"] + logger.debug( + f"Asking wfc_controller for setpoints at time = {current_time} for id = {id}" + ) + setpoints = self.wfc_controller(id, current_time, measurements) + logger.info(f"Received setpoints {setpoints} from wfc_controller for time = {current_time} and id = {id}") + + for s in self.wfc_interface["setpoints"]: + self.connections.setpoints[id][s] = setpoints.get(s, 0) + logger.debug(f'Set setpoint {s} in the connections list to {setpoints.get(s,0)} for id = {id}') + + def wfc_controller(self, id, current_time, measurements): + """User defined wind farm controller + + Users needs to overwrite this method by their wind farm controller. + The user defined method should take as argument the turbine id, the + current time and current measurements and return the setpoints + for the particular turbine for the current time. It should ouput the + setpoints as a dictionary whose keys should be as defined in + wfc_zmq_server.wfc_interface. If user does not overwrite this method, + an exception is raised and the simulation stops. + + Examples + -------- + >>> # Define the wind farm controller + >>> def wfc_controller(id, current_time): + >>> if current_time <= 10.0: + >>> YawOffset = 0.0 + >>> else: + >>> if id == 1: + >>> YawOffset = -10.0 + >>> else: + >>> YawOffset = 10 + >>> setpoints = {} + >>> setpoints["ZMQ_YawOffset"] = YawOffset + >>> return setpoints + >>> + >>> # Overwrite the wfc_controller method of the server + >>> server.wfc_controller = wfc_controller + """ + logger.critical("User defined wind farm controller not found") + raise NotImplementedError("Wind farm controller needs to be defined.") + + def _get_measurements(self): + """Receive measurements from ROSCO .dll""" + if self.verbose: + print("[%s] Waiting to receive measurements from ROSCO...") + + # message_in = self.socket.recv_string() + # Initialize a poller for timeouts + poller = zmq.Poller() + poller.register(self.socket, zmq.POLLIN) + timeout_ms = int(self.timeout * 1000) + # poller.poll(timeout_ms) + events = poller.poll(timeout_ms) + if self.socket in dict(events): + # if poller.poll(timeout_ms): + # Receive measurements over network protocol + logger.debug( + f"Checked for timeout and waiting for measurements from a ROSCO client" + ) + message_in = self.socket.recv_string() + logger.debug(f"Received raw message: {message_in} ") + else: + # raise IOError("[%s] Connection to '%s' timed out." + # % (self.identifier, self.network_address)) + logger.info(f"Connection timed out") + raise IOError("Connection timed out") + + # Convert to individual strings and then to floats + meas_float = message_in + meas_float = meas_float.replace("\x00", "").split(",") + meas_float = [float(m) for m in meas_float] + + # Convert to a measurement dict + meas_dict = {} + for i_meas, meas in enumerate(self.wfc_interface["measurements"]): + meas_dict[meas] = meas_float[i_meas] + logger.info(f"Received message (formatted): {meas_dict}") + if self.verbose: + print("[%s] Measurements received:", meas_dict) + + return meas_dict + + def _send_setpoints(self, id): + """Send setpoints to ROSCO .dll ffor individual turbine control""" + + # Create a string message with setpoints to send to ROSCO + message_out = ", ".join( + [f"{s:016.5f}" for s in self.connections.setpoints[id].values()] + ).encode("utf-8") + + # Send reply back to client + + logger.debug(f"Raw setpoints to be sent to id = {id} is {message_out}") + if self.verbose: + print("[%s] Sending setpoint string to ROSCO: %s." % (id, message_out)) + + # Send control setpoints over network protocol + self.socket.send(message_out) + logger.info(f"Sent setpoints {self.connections.setpoints[id]} to id = {id}") + + if self.verbose: + print("[%s] Setpoints sent successfully." % id) + + def _check_for_disconnect(self): + """Disconnect if no clients are connected to the server""" + num_connected = sum(self.connections.connected.values()) + logger.debug(f'Still connected to {num_connected} clients') + if num_connected > 0: + connect_zmq = True + if self.verbose: + print("Still connected to ", num_connected, " ROSCO clients") + else: + connect_zmq = False + logger.info('Shutting down server as all the clients have dropped off') + self._disconnect() + return connect_zmq + + def _disconnect(self): + """Disconnect from zmq server""" + logger.info('Socket terminated') + self.socket.close() + context = zmq.Context() + context.term() + + +class wfc_zmq_connections: + """ + This class is used to track the current ROSCO client connections, + their current measurements and setpoints. + """ + + # Dictionary of ROSCO clients connected to the server + connected = {} + + def __init__(self, wfc_interface): + self.wfc_interface = wfc_interface + self.setpoints = {} + self.measurements = {} + + def _add_unique(self, id): + """Add to the dictionary of connected client + + Add the current turbine to the dictionary of connected clients, + if it has not been added before. Next, initilize the measurements + and setpoints for the turbine to 0. + """ + if id not in wfc_zmq_connections.connected.keys(): + wfc_zmq_connections.connected.update({id: True}) + logger.info(f"Connected to a new ROSCO with id = {id}") + + self.setpoints.update( + {id: {s: 0.0 for s in self.wfc_interface["setpoints"]}} + ) # init setpoints with zeros + self.measurements.update( + {id: {s: 0.0 for s in self.wfc_interface["measurements"]}} + ) # init measurements with zeros + + def _update_measurements(self, id, measurements): + """Update the measurements and remove turbine from connected clients""" + self.measurements.update({id: measurements}) + logger.debug(f"Updated measurements for ROSCO with id = {id} ") + if measurements["iStatus"] == -1: + wfc_zmq_connections.connected[id] = False + logger.info(f"Received disconnect signal from ROSCO with id = {id}") diff --git a/ROSCO_toolbox/controller.py b/rosco/toolbox/controller.py similarity index 85% rename from ROSCO_toolbox/controller.py rename to rosco/toolbox/controller.py index c5896517..9b78cce5 100644 --- a/ROSCO_toolbox/controller.py +++ b/rosco/toolbox/controller.py @@ -13,7 +13,7 @@ import os import datetime from scipy import interpolate, integrate -from ROSCO_toolbox.utilities import list_check +from rosco.toolbox.utilities import list_check from scipy import optimize # Some useful constants @@ -54,6 +54,7 @@ def __init__(self, controller_params): self.F_NotchType = controller_params['F_NotchType'] self.IPC_ControlMode = controller_params['IPC_ControlMode'] self.VS_ControlMode = controller_params['VS_ControlMode'] + self.VS_ConstPower = controller_params['VS_ConstPower'] self.PC_ControlMode = controller_params['PC_ControlMode'] self.Y_ControlMode = controller_params['Y_ControlMode'] self.SS_Mode = controller_params['SS_Mode'] @@ -62,6 +63,7 @@ def __init__(self, controller_params): self.SD_Mode = controller_params['SD_Mode'] self.Fl_Mode = controller_params['Fl_Mode'] self.TD_Mode = controller_params['TD_Mode'] + self.TRA_Mode = controller_params['TRA_Mode'] self.Flp_Mode = controller_params['Flp_Mode'] self.PA_Mode = controller_params['PA_Mode'] self.PF_Mode = controller_params['PF_Mode'] @@ -94,7 +96,8 @@ def __init__(self, controller_params): self.Ki_ipc1p = controller_params['IPC_Ki1p'] self.Kp_ipc2p = controller_params['IPC_Kp2p'] self.Ki_ipc2p = controller_params['IPC_Kp2p'] - self.IPC_Vramp = controller_params['IPC_Vramp'] + self.IPC_Vramp = controller_params['IPC_Vramp'] + self.ZMQ_UpdatePeriod = controller_params['ZMQ_UpdatePeriod'] # Optional parameters without defaults if self.Flp_Mode > 0: @@ -103,20 +106,20 @@ def __init__(self, controller_params): self.flp_tau = controller_params['flp_tau'] except: raise Exception( - 'ROSCO_toolbox:controller: flp_kp_norm and flp_tau must be set if Flp_Mode > 0') + 'rosco.toolbox:controller: flp_kp_norm and flp_tau must be set if Flp_Mode > 0') if self.Fl_Mode > 0: try: self.twr_freq = controller_params['twr_freq'] self.ptfm_freq = controller_params['ptfm_freq'] except: - raise Exception('ROSCO_toolbox:controller: twr_freq and ptfm_freq must be set if Fl_Mode > 0') + raise Exception('rosco.toolbox:controller: twr_freq and ptfm_freq must be set if Fl_Mode > 0') # Kp_float direct setting if 'Kp_float' in controller_params: self.Kp_float = controller_params['Kp_float'] else: - self.Kp_float = 0 + self.Kp_float = np.array([0]) self.tune_Fl = controller_params['tune_Fl'] @@ -138,10 +141,12 @@ def __init__(self, controller_params): self.f_yawerr = controller_params['filter_params']['f_yawerr'] self.f_sd_cornerfreq = controller_params['filter_params']['f_sd_cornerfreq'] + # Open loop parameters: set up and error catching - self.OL_Mode = int(controller_params['open_loop']['flag']) + self.OL_Mode = controller_params['OL_Mode'] self.OL_Filename = controller_params['open_loop']['filename'] - self.OL_Ind_Breakpoint = self.OL_Ind_BldPitch = self.OL_Ind_GenTq = self.OL_Ind_YawRate = 0 + self.OL_Ind_Breakpoint = self.OL_Ind_GenTq = self.OL_Ind_YawRate = self.OL_Ind_Azimuth = 0 + self.OL_Ind_BldPitch = [0,0,0] self.OL_Ind_CableControl = [0] self.OL_Ind_StructControl = [0] @@ -151,11 +156,12 @@ def __init__(self, controller_params): self.OL_Ind_BldPitch = ol_params['OL_Ind_BldPitch'] self.OL_Ind_GenTq = ol_params['OL_Ind_GenTq'] self.OL_Ind_YawRate = ol_params['OL_Ind_YawRate'] + self.OL_Ind_Azimuth = ol_params['OL_Ind_Azimuth'] self.OL_Ind_CableControl = ol_params['OL_Ind_CableControl'] self.OL_Ind_StructControl = ol_params['OL_Ind_StructControl'] # Check that file exists because we won't write it - if not os.path.exists(self.OL_Filename): + if not os.path.exists(controller_params['open_loop']['filename']): raise Exception(f'Open-loop control set up, but the open loop file {self.OL_Filename} does not exist') @@ -280,7 +286,7 @@ def tune_controller(self, turbine): Pi_wind = 1/2 * rho * Ar * v**2 * dCt_dTSR * dlambda_dv + rho * Ar * v * Ct_op # Second order system coefficients - if self.VS_ControlMode in [0,2]: # Constant torque above rated + if not self.VS_ConstPower: # Constant torque above rated A = dtau_domega/J else: # Constant power above rated A = dtau_domega/J @@ -319,7 +325,8 @@ def tune_controller(self, turbine): self.vs_gain_schedule.second_order_PI(self.zeta_vs, self.omega_vs,A_vs,B_tau[0:len(v_below_rated)],linearize=False,v=v_below_rated) # -- Find K for Komega_g^2 -- - self.vs_rgn2K = (pi*rho*R**5.0 * turbine.Cp.max) / (2.0 * turbine.Cp.TSR_opt**3 * Ng**3)/ (turbine.GBoxEff/100) + self.vs_rgn2K = (pi*rho*R**5.0 * turbine.Cp.max * turbine.GBoxEff/100 * turbine.GenEff/100) / \ + (2.0 * turbine.Cp.TSR_opt**3 * Ng**3) * self.controller_params['rgn2k_factor'] self.vs_refspd = min(turbine.TSR_operational * turbine.v_rated/R, turbine.rated_rotor_speed) * Ng # -- Define some setpoints -- @@ -344,6 +351,9 @@ def tune_controller(self, turbine): self.v = v # Wind speed (m/s) self.v_above_rated = v_above_rated self.v_below_rated = v_below_rated + # Mod by A. Wright + self.v_for_gs = v[-len(v_above_rated)+1:] + # end self.pitch_op = pitch_op self.pitch_op_pc = pitch_op[-len(v_above_rated)+1:] self.TSR_op = TSR_op @@ -372,24 +382,53 @@ def tune_controller(self, turbine): self.ps.min_pitch_saturation(self,turbine) # --- Floating feedback term --- + if self.Fl_Mode >= 1: # Floating feedback - # If we haven't set Kp_float as a control parameter + + # Wind speed gain scheduling + self.U_Fl = self.controller_params['U_Fl'] + if self.U_Fl: # default is [], only have one Fl_Kp + if type(self.U_Fl) == str: + if self.U_Fl == 'all': + # Mod by A. Wright: get the array of Kp_float values at the values of v-above rated (see self.v_for_gs calculated around line 344). + self.U_Fl = self.v_for_gs + else: + raise Exception("Invalid entry in controller_params for U_Fl, please see schema") + else: + self.U_Fl = np.array([turbine.v_rated * (1.05)]) + + + # If we haven't set Kp_float as a control parameter, we tune it automatically here if self.tune_Fl: Kp_float = (dtau_dv/dtau_dbeta) * Ng if self.Fl_Mode == 2: Kp_float *= turbine.TowerHt f_kp = interpolate.interp1d(v,Kp_float) - self.Kp_float = f_kp(turbine.v_rated * (1.05)) # get Kp at v_rated + 0.5 m/s + self.Kp_float = f_kp(self.U_Fl) # get Kp at v_rated + 0.5 m/s - # Turn on the notch filter if floating - self.F_NotchType = 2 + # Make arrays if not + if not np.shape(self.Kp_float): + self.Kp_float = np.array([self.Kp_float]) + if not np.shape(self.U_Fl): + self.U_Fl = np.array([self.U_Fl]) + # Check size of Kp_float and U_Fl + if len(self.Kp_float) != len(self.U_Fl): + raise Exception('The sizes of Kp_float and U_Fl are not equal, please check your controller_params') + + + + # Turn on the notch filter if floating and not already on + if not self.F_NotchType: + self.F_NotchType = 2 + # And check for .yaml input inconsistencies if self.twr_freq == 0.0 or self.ptfm_freq == 0.0: print('WARNING: twr_freq and ptfm_freq should be defined for floating turbine control!!') else: - self.Kp_float = 0.0 + self.Kp_float = np.array([0.0]) + self.U_Fl = np.array([0.0]) # Flap actuation if self.Flp_Mode >= 1: @@ -410,6 +449,29 @@ def tune_controller(self, turbine): # --- Set up filters --- self.f_lpf_cornerfreq = turbine.bld_edgewise_freq / 4 + # Notch filters + self.f_notch_freqs = [] + self.f_notch_beta_nums = [] + self.f_notch_beta_dens = [] + self.f_notch_gen_inds = [] + self.f_notch_twr_inds = [] + + if self.F_NotchType: + if self.Flp_Mode: + self.f_notch_freqs.append(turbine.bld_flapwise_freq) + self.f_notch_beta_nums.append(0.0) + self.f_notch_beta_dens.append(0.50) + else: + self.f_notch_freqs.append(self.twr_freq) + self.f_notch_beta_nums.append(0.0) + self.f_notch_beta_dens.append(0.25) + + if self.F_NotchType == 1 or self.F_NotchType == 3: + self.f_notch_gen_inds.append(1) + elif self.F_NotchType == 2: + self.f_notch_twr_inds.append(1) + + # --- Direct input passthrough --- if 'f_lpf_cornerfreq' in self.controller_params['filter_params']: self.f_lpf_cornerfreq = self.controller_params['filter_params']['f_lpf_cornerfreq'] @@ -759,39 +821,60 @@ def write_input(self,ol_filename): # Init indices OL_Ind_Breakpoint = 1 - OL_Ind_BldPitch = OL_Ind_GenTq = OL_Ind_YawRate = 0 + OL_Ind_Azimuth = OL_Ind_GenTq = OL_Ind_YawRate = 0 + OL_Ind_BldPitch = 3*[0] OL_Ind_CableControl = [] OL_Ind_StructControl = [] - self.OL_Ind_Breakpoint = 1 - ol_index_counter = 2 # start input index at 2 - + ol_index_counter = 0 # start input index at 2 + + # Write time first, initialize OL matrix if 'time' in ol_timeseries: ol_control_array = ol_timeseries['time'] - + Ind_Breakpoint = 1 else: raise Exception('WARNING: no time index for open loop control. This is only index currently supported') - if 'blade_pitch' in ol_timeseries: - OL_Ind_BldPitch = ol_index_counter - ol_index_counter += 1 - - ol_control_array = np.c_[ol_control_array,ol_timeseries['blade_pitch']] + for channel in ol_timeseries: - if 'generator_torque' in ol_timeseries: - OL_Ind_GenTq = ol_index_counter + # increment index counter first for 1-indexing in input file ol_index_counter += 1 - - ol_control_array = np.c_[ol_control_array,ol_timeseries['generator_torque']] - - if 'nacelle_yaw_rate' in ol_timeseries: - OL_Ind_YawRate = ol_index_counter - ol_index_counter += 1 - - ol_control_array = np.c_[ol_control_array,ol_timeseries['nacelle_yaw_rate']] - if 'nacelle_yaw' in ol_timeseries and 'nacelle_yaw_rate' not in ol_timeseries: - raise Exception('nacelle_yaw is in ol_timeseries and nacelle_yaw_rate is not. ROSCO can only command yaw rate. Use compute_yaw_rate() to convert.') + # skip writing for certain channels + skip_write = False + + # Set open loop index based on name + if channel == 'time': + OL_Ind_Breakpoint = ol_index_counter + skip_write = True + elif channel == 'blade_pitch': # collective blade pitch + OL_Ind_BldPitch = 3 * [ol_index_counter] + elif channel == 'generator_torque': + OL_Ind_GenTq = ol_index_counter + elif channel == 'nacelle_yaw_rate': + OL_Ind_YawRate = ol_index_counter + elif channel == 'nacelle_yaw': + ol_index_counter -= 1 # don't increment counter + skip_write = True + elif channel == 'blade_pitch1': + OL_Ind_BldPitch[0] = ol_index_counter + elif channel == 'blade_pitch2': + OL_Ind_BldPitch[1] = ol_index_counter + elif channel == 'blade_pitch3': + OL_Ind_BldPitch[2] = ol_index_counter + elif channel == 'azimuth': + OL_Ind_Azimuth = ol_index_counter + elif 'cable_control' in channel or 'struct_control' in channel: + skip_write = True + ol_index_counter -= 1 # don't increment counter + + + + # append open loop input array for non-ptfm channels + if not skip_write: + ol_control_array = np.c_[ol_control_array,ol_timeseries[channel]] + + ol_index_counter += 1 # Increment counter so it's 1 more than time, just like above in each iteration # Cable control is_cable_chan = np.array(['cable_control' in ol_chan for ol_chan in ol_timeseries.keys()]) @@ -825,19 +908,37 @@ def write_input(self,ol_filename): with open(ol_filename,'w') as f: # Write header + headers = [''] * ol_index_counter + units = [''] * ol_index_counter header_line = '!\tTime' unit_line = '!\t(sec.)' - if OL_Ind_BldPitch: - header_line += '\t\tBldPitch' - unit_line += '\t\t(rad.)' + + headers[0] = 'Time' + units[0] = 'sec.' if OL_Ind_GenTq: - header_line += '\t\tGenTq' - unit_line += '\t\t(Nm)' + headers[OL_Ind_GenTq-1] = 'GenTq' + units[OL_Ind_GenTq-1] = '(Nm)' if OL_Ind_YawRate: - header_line += '\t\tYawRate' - unit_line += '\t\t(rad/s)' + headers[OL_Ind_YawRate-1] = 'YawRate' + units[OL_Ind_YawRate-1] = '(rad/s)' + + if OL_Ind_Azimuth: + headers[OL_Ind_Azimuth-1] = 'Azimuth' + units[OL_Ind_Azimuth-1] = '(rad)' + + if any(OL_Ind_BldPitch): + if all_same(OL_Ind_BldPitch): + headers[OL_Ind_BldPitch[0]-1] = 'BldPitch123' + units[OL_Ind_BldPitch[0]-1] = '(rad)' + else: + headers[OL_Ind_BldPitch[0]-1] = 'BldPitch1' + units[OL_Ind_BldPitch[0]-1] = '(rad)' + headers[OL_Ind_BldPitch[1]-1] = 'BldPitch2' + units[OL_Ind_BldPitch[1]-1] = '(rad)' + headers[OL_Ind_BldPitch[2]-1] = 'BldPitch3' + units[OL_Ind_BldPitch[2]-1] = '(rad)' if OL_Ind_CableControl: for i_chan in range(1,n_cable_chan+1): @@ -853,8 +954,9 @@ def write_input(self,ol_filename): else: OL_Ind_StructControl = [0] - header_line += '\n' - unit_line += '\n' + # Join headers and units + header_line = '!' + '\t\t'.join(headers) + '\n' + unit_line = '!' + '\t\t'.join(units) + '\n' f.write(header_line) f.write(unit_line) @@ -866,15 +968,16 @@ def write_input(self,ol_filename): # Output open_loop dict for control params open_loop = {} - open_loop['flag'] = True open_loop['filename'] = ol_filename open_loop['OL_Ind_Breakpoint'] = OL_Ind_Breakpoint open_loop['OL_Ind_BldPitch'] = OL_Ind_BldPitch open_loop['OL_Ind_GenTq'] = OL_Ind_GenTq open_loop['OL_Ind_YawRate'] = OL_Ind_YawRate + open_loop['OL_Ind_Azimuth'] = OL_Ind_Azimuth open_loop['OL_Ind_CableControl'] = OL_Ind_CableControl open_loop['OL_Ind_StructControl'] = OL_Ind_StructControl + return open_loop @@ -956,3 +1059,6 @@ def multi_sigma(xx,x_bp,y_bp): plt.show() return yy + +def all_same(items): + return all(x == items[0] for x in items) diff --git a/ROSCO_toolbox/inputs/.gitignore b/rosco/toolbox/inputs/.gitignore similarity index 100% rename from ROSCO_toolbox/inputs/.gitignore rename to rosco/toolbox/inputs/.gitignore diff --git a/ROSCO_toolbox/ofTools/__init__.py b/rosco/toolbox/inputs/__init__.py similarity index 100% rename from ROSCO_toolbox/ofTools/__init__.py rename to rosco/toolbox/inputs/__init__.py diff --git a/ROSCO_toolbox/inputs/schema2rst.py b/rosco/toolbox/inputs/schema2rst.py similarity index 100% rename from ROSCO_toolbox/inputs/schema2rst.py rename to rosco/toolbox/inputs/schema2rst.py diff --git a/ROSCO_toolbox/inputs/toolbox_schema.yaml b/rosco/toolbox/inputs/toolbox_schema.yaml similarity index 81% rename from ROSCO_toolbox/inputs/toolbox_schema.yaml rename to rosco/toolbox/inputs/toolbox_schema.yaml index 80a5486d..44573ae1 100644 --- a/ROSCO_toolbox/inputs/toolbox_schema.yaml +++ b/rosco/toolbox/inputs/toolbox_schema.yaml @@ -18,11 +18,11 @@ properties: # default: IEA-15-240-RWT-UMaineSemi.fst FAST_directory: type: string - description: Main OpenFAST model directory, where the `*.fst` lives, relative to ROSCO dir (if applicable) + description: Main OpenFAST model directory, where the `*.fst` lives, relative to directory of this yaml (if applicable) # default: Test_Cases/IEA-15-240-RWT-UMaineSemi rotor_performance_filename: type: string - description: Filename for rotor performance text file (if it has been generated by ccblade already) + description: Filename for rotor performance text file (if it has been generated by ccblade already), relative to directory of this yaml # default: Cp_Ct_Cq.IEA15MW.txt turbine_params: @@ -90,6 +90,12 @@ properties: unit: none default: 0 minimum: 0 + reynolds_ref: + type: number + description: Reynolds number near rated speeds, used to interpolate airfoils, if provided + unit: none + default: 0 + minimum: 0 controller_params: @@ -124,7 +130,13 @@ properties: minimum: 0 maximum: 3 default: 2 - description: Generator torque control mode in above rated conditions (0- constant torque, 1- constant power, 2- TSR tracking PI control with constant torque, 3- TSR tracking with constant power) + description: Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking) + VS_ConstPower: + type: number + minimum: 0 + maximum: 1 + default: 0 + description: Do constant power torque control, where above rated torque varies, 0 for constant torque PC_ControlMode: type: number minimum: 0 @@ -167,6 +179,12 @@ properties: maximum: 1 default: 0 description: Tower damper mode (0- no tower damper, 1- feed back translational nacelle accelleration to pitch angle + TRA_Mode: + type: number + minimum: 0 + maximum: 1 + default: 0 + description: Tower resonance avoidance mode (0- no tower resonsnace avoidance, 1- use torque control setpoints to avoid a specific frequency Fl_Mode: type: number minimum: 0 @@ -191,6 +209,11 @@ properties: maximum: 1 default: 0 description: ZMQ Mode (0 - ZMQ Inteface, 1 - ZMQ for yaw control) + ZMQ_UpdatePeriod: + type: number + minimum: 0 + default: 2 + description: Call ZeroMQ every [x] seconds, [s] PA_Mode: type: number minimum: 0 @@ -203,6 +226,12 @@ properties: maximum: 1 default: 0 description: Pitch fault mode {0 - not used, 1 - constant offset on one or more blades} + OL_Mode: + type: number + minimum: 0 + maximum: 2 + default: 0 + description: Open loop control mode {0- no open loop control, 1- open loop control} AWC_Mode: type: number minimum: 0 @@ -331,13 +360,21 @@ properties: minimum: 0 default: 30 Kp_float: - type: number - description: Gain of floating feedback control + type: [number, array] + description: Gain(s) of floating feedback control unit: s + items: + type: number tune_Fl: type: boolean description: Whether to automatically tune Kp_float default: True + U_Fl: + type: [array, string, number] + description: List of wind speeds for tuning floating feedback, or "all" for all above-rated wind speeds + default: [] + items: + type: number zeta_flp: type: number minimum: 0 @@ -392,6 +429,11 @@ properties: minimum: 0.0 default: [0.0, 0.0] unit: m/s + rgn2k_factor: + type: number + description: Factor on VS_Rgn2K to increase/decrease optimal torque control gain, default is 1. Sometimes environmental conditions or differences in BEM solvers necessitate this change. + default: 1 + minimum: 0 filter_params: type: object @@ -450,22 +492,44 @@ properties: description: Filename of open loop input that ROSCO reads type: string default: unused - OL_Ind_Breakpoint: + Ind_Breakpoint: description: Index (column, 1-indexed) of breakpoint (time) in open loop index type: number default: 1 - OL_Ind_BldPitch: - description: Index (column, 1-indexed) of breakpoint (time) in open loop index + minimum: 0 + Ind_BldPitch: + description: Indices (columns, 1-indexed) of pitch (1,2,3) inputs in open loop input + type: array + items: + type: number + minimum: 0 + default: [0, 0, 0] + Ind_GenTq: + description: Index (column, 1-indexed) of generator torque in open loop input type: number default: 0 - OL_Ind_GenTq: - description: Index (column, 1-indexed) of breakpoint (time) in open loop index + minimum: 0 + Ind_YawRate: + description: Index (column, 1-indexed) of nacelle yaw in open loop input type: number default: 0 - OL_Ind_YawRate: - description: Index (column, 1-indexed) of breakpoint (time) in open loop index + minimum: 0 + Ind_Azimuth: type: number default: 0 + description: The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) + Ind_CableControl: + type: array + items: + type: number + description: The column in OL_Filename that contains the cable control inputs in m + # default: [0] # No default because it's defined in controller and DISCON_Dict + Ind_StructControl: + type: array + items: + type: number + description: The column in OL_Filename that contains the structural control inputs in various units + # default: [0] # No default because it's defined in controller and DISCON_Dict PA_CornerFreq: type: number description: Pitch actuator natural frequency [rad/s] @@ -480,7 +544,7 @@ properties: DISCON: type: object - description: These are pass-through parameters for the DISCON.IN file. Use with caution. + description: These are pass-through parameters for the DISCON.IN file. Use with caution. Do not set defaults in schema. default: {} properties: LoggingLevel: @@ -490,18 +554,35 @@ properties: type: number description: 0 - no Echo, 1 - Echo input data to .echo default: 0 + DT_Out: + type: number + description: Time step to output .dbg* files, or 0 to match sampling period of OpenFAST + default: 0 + Ext_Interface: + type: number + description: 0 - use standard bladed interface, 1 - Use the extened DLL interface introduced in OpenFAST 3.5.0. + minimum: 0 + maximum: 1 + default: 1 F_LPFType: type: number description: 1- first-order low-pass filter, 2- second-order low-pass filter (currently filters generator speed and pitch control signals + VS_ControlMode: + type: number + minimum: 0 + maximum: 3 + description: Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking) + VS_ConstPower: + type: number + minimum: 0 + maximum: 1 + description: Do constant power torque control, where above rated torque varies F_NotchType: type: number description: Notch on the measured generator speed and/or tower fore-aft motion (for floating) (0- disable, 1- generator speed, 2- tower-top fore-aft motion, 3- generator speed and tower-top fore-aft motion) IPC_ControlMode: type: number description: Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) (0- off, 1- 1P reductions, 2- 1P+2P reductions) - VS_ControlMode: - type: number - description: Generator torque control mode in above rated conditions (0- constant torque, 1- constant power, 2- TSR tracking PI control with constant torque, 3- TSR tracking PI control with constant power) PC_ControlMode: type: number description: Blade pitch control mode (0- No pitch, fix to fine pitch, 1- active PI blade pitch control) @@ -526,6 +607,9 @@ properties: Flp_Mode: type: number description: Flap control mode (0- no flap control, 1- steady state flap angle, 2- Proportional flap control) + OL_Mode: + type: number + description: Open loop control mode (0 - no open-loop control, 1 - direct open loop control, 2 - rotor position control) F_LPFCornerFreq: type: number description: Corner frequency (-3dB point) in the low-pass filters, @@ -533,15 +617,41 @@ properties: F_LPFDamping: type: number description: Damping coefficient (used only when F_FilterType = 2 [-] - F_NotchCornerFreq: + F_NumNotchFilts: type: number - description: Natural frequency of the notch filter, + description: Number of notch filters placed on sensors + F_NotchFreqs: + type: [array,number] + items: + type: number + description: Natural frequency of the notch filters. Array with length F_NumNotchFilts units: rad/s - F_NotchBetaNumDen: - type: array + F_NotchBetaNum: + type: [array, number] + items: + type: number + description: Damping value of numerator (determines the width of notch). Array with length F_NumNotchFilts, [-] + F_NotchBetaDen: + type: [array, number] items: type: number - description: Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-] + description: Damping value of denominator (determines the depth of notch). Array with length F_NumNotchFilts, [-] + F_GenSpdNotch_N: + type: number + description: Number of notch filters on generator speed + F_TwrTopNotch_N: + type: number + description: Number of notch filters on tower top acceleration signal + F_GenSpdNotch_Ind: + type: [array, number] + items: + type: number + description: Indices of notch filters on generator speed + F_TwrTopNotch_Ind: + type: [array, number] + items: + type: number + description: Indices of notch filters on tower top acceleration signal F_SSCornerFreq: type: number description: Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, @@ -677,7 +787,7 @@ properties: units: rad/s VS_Rgn2K: type: number - description: Generator torque constant in Region 2 (HSS side) + description: Generator torque constant in Region 2 (HSS side). Only used in VS_ControlMode = 1,3 units: Nm/(rad/s)^2 VS_RtPwr: type: number @@ -703,14 +813,54 @@ properties: units: s VS_TSRopt: type: number - description: Power-maximizing region 2 tip-speed-ratio + description: Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. units: rad + VS_PwrFiltF: + type: number + description: Low pass filter on power used to determine generator speed set point. Only used in VS_ControlMode = 3. + units: rad + default: 0.314 SS_VSGain: type: number description: Variable speed torque controller setpoint smoother gain SS_PCGain: type: number description: Collective pitch controller setpoint smoother gain + PRC_Mode: + type: number + description: Power reference tracking mode, 0- use standard rotor speed set points, 1- use PRC rotor speed setpoints + PRC_WindSpeeds: + type: array + items: + type: number + description: Array of wind speeds used in rotor speed vs. wind speed lookup table [m/s] + PRC_GenSpeeds: + type: array + items: + type: number + description: Array of generator speeds corresponding to PRC_WindSpeeds [rad/s] + PRC_LPF_Freq: + type: number + description: Frequency of the low pass filter on the wind speed estimate used to set PRC_GenSpeeds [rad/s] + default: 0.078539 + PRC_n: + type: number + description: Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array + TRA_ExclSpeed: + type: number + minimum: 0 + description: Rotor speed for exclusion [LSS, rad/s] + default: 0.0 + TRA_ExclBand: + type: number + minimum: 0 + description: Size of the rotor frequency exclusion band [LSS, rad/s]. Torque controller reference will be TRA_ExclSpeed +/- TRA_ExlBand/2 + default: 0.0 + TRA_RateLimit: + type: number + minimum: 0 + description: Rate limit of change in rotor speed reference [LSS, rad/s]. Suggested to be VS_RefSpd/400. + default: 0.0 WE_BladeRadius: type: number description: Blade length (distance from hub center to blade tip) @@ -834,10 +984,22 @@ properties: type: number description: Cutoff Frequency for first order low-pass filter for blade pitch angle units: rad/s - Fl_Kp: + Fl_n: type: number + description: Number of Fl_Kp gains in gain scheduling, optional with default of 1 + units: s + Fl_Kp: + type: array description: Nacelle velocity proportional feedback gain units: s + items: + type: number + Fl_U: + type: array + description: Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s] + units: s + items: + type: number Flp_Angle: type: number description: Initial or steady state flap angle @@ -858,7 +1020,7 @@ properties: description: Input file with open loop timeseries (absolute path or relative to this file) Ind_Breakpoint: type: number - description: The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1) + description: The column in OL_Filename that contains the breakpoint (time if OL_Mode > 0) Ind_BldPitch: type: number description: The column in OL_Filename that contains the blade pitch input in rad @@ -868,6 +1030,15 @@ properties: Ind_YawRate: type: number description: The column in OL_Filename that contains the generator torque in Nm + Ind_Azimuth: + type: number + description: The column in OL_Filename that contains the desired azimuth position in rad (used if OL_Mode = 2) + RP_Gains: + type: array + description: PID gains and Tf of derivative for rotor position control (used if OL_Mode = 2) + default: [0,0,0,0] + items: + type: number Ind_CableControl: type: array items: @@ -967,6 +1138,18 @@ properties: description: AWC clock angle [deg] units: deg default: [0] + ZMQ_CommAddress: + type: string + description: Communication address for ZMQ server, (e.g. "tcp://localhost:5555") + default: tcp://localhost:5555 + ZMQ_UpdatePeriod: + type: number + description: Update period at zmq interface to send measurements and wait for setpoint [sec.] + default: 1.0 + ZMQ_ID: + type: number + description: Integer identifier of turbine + default: 0 linmodel_tuning: type: object diff --git a/ROSCO_toolbox/inputs/validation.py b/rosco/toolbox/inputs/validation.py similarity index 100% rename from ROSCO_toolbox/inputs/validation.py rename to rosco/toolbox/inputs/validation.py diff --git a/ROSCO_toolbox/ofTools/case_gen/__init__.py b/rosco/toolbox/linear/__init__.py similarity index 100% rename from ROSCO_toolbox/ofTools/case_gen/__init__.py rename to rosco/toolbox/linear/__init__.py diff --git a/rosco/toolbox/linear/getMats.py b/rosco/toolbox/linear/getMats.py new file mode 100644 index 00000000..7682b368 --- /dev/null +++ b/rosco/toolbox/linear/getMats.py @@ -0,0 +1,603 @@ +############################################################# +# Extract OpenFAST Matrices from linearization files # +# Authors: Srinivasa B. Ramisetti # +# Created: 01-July-2020 # +# E-mail: ramisettisrinivas@yahoo.com # +# Web: http://ramisetti.github.io # +############################################################# +#!/usr/bin/env python + +import os +from itertools import islice +import numpy as np +import re + +def _isbool(str): + flag=0 + if str=='T' or str=='True': + flag=1 + return flag + + +def findBladeTriplets(rotFrame, Desc, verbose=True): + + # Find the number of, and indices for, triplets in the rotating frame: + chkStr = [r'[Bb]lade \d', r'[Bb]lade [Rr]oot \d', r'BD_\d', r'[Bb]\d', r'[Bb]lade\d', r'PitchBearing\d', r'\d'] + + origDesc = Desc; + + # hack for ElastoDyn state names (remove unnecessary text in parenthesis) + for i in range(len(rotFrame)): + if Desc[i] is None: + raise Exception('Description not defined, likely a bug.') + ix = Desc[i].find('(internal DOF index = ') + if ix>0: + ix2 = Desc[i].find(')') + Desc[i] = Desc[i][:ix]+Desc[i][ix2+1:] + + + NTriplets = 0; # first initialize to zero + Triplets = []; + for i in range(len(rotFrame)): # loop through inputs/outputs/states + if rotFrame[i] == 'T': # this is in the rotating frame + Tmp = -1*np.ones(3) + foundTriplet = False + foundBladeNumber = False + for chk in chkStr: + BldNoCol = re.search(chk,Desc[i]) + if BldNoCol!=None: + foundBladeNumber = True + + Bldstr=BldNoCol.group() + # create another regular expression to find the + # exact match on a different blade: + strng = re.split(Bldstr,Desc[i],1) #this should return the strings before and after the match + + + FirstStr = strng[0] + Bldstr[:len(Bldstr)-1] + '.' + checkThisStr = FirstStr + strng[1] + + #we need to get rid of the special characters that + #may exist in Desc{}: + checkThisStr=checkThisStr.replace(')',r'\)').replace('(', r'\(').replace('^',r'\^') + FirstStr = FirstStr. replace(')',r'\)').replace('(', r'\(').replace('^',r'\^') + + k = int(Bldstr[len(Bldstr)-1]) + Tmp[k-1] = int(i) + break + + #print(Tmp,j) + + # find the other match values + if foundBladeNumber: + for j in range((i+1),len(rotFrame)): # loop through all remaining control inputs + #print(i, j) + if rotFrame[j]: # this is in the rotating frame + BldNoCol = re.search(checkThisStr, Desc[j]) + if BldNoCol!=None: + Num = re.search(FirstStr,Desc[j]).group(); + k = int(Num[len(Num)-1]); + Tmp[k-1] = int(j); # save the indices for the remaining blades + #TmpTmp=Tmp+1 + #print(BldNoCol.group(),i,j,k) + if ( (Tmp>-1).all() ): # true if all the elements of Tmp are nonzero; thus, we found a triplet of rotating indices + foundTriplet = True; + + Triplets.append(Tmp); # these are the indices for control input triplets in the rotating frame + + NTriplets = NTriplets + 1; # this is the number of control input triplets in the rotating frame + + # we'll set rotFrame to false so that we don't have to check the found channels again; also allows us to throw error if we have a rotating channel that doesn't have a unique match + for idx in Tmp: + id=int(idx) + rotFrame[id] = 0; + + break; + + if foundTriplet==False: + if verbose: + print('Rotating channel "', i, Desc[i], '" does not form a unique blade triplet. Blade(s) not found: ', np.array(np.where(Tmp == -1))+1 ) + else: + if verbose: + print( 'Could not find blade number in rotating channel "', Desc[i], '".') + #print(NTriplets) + #print(Triplets) + + return Triplets, NTriplets + +def reOrderByIdx_1D(arry,Indi): + tmp=[None]*len(arry) + j=0 + for i in Indi: + tmp[i]=arry[j] + j=j+1 + return tmp + +def reOrderByIdx_2D(arry,Indi,Indj): + #tmp=[[None]*arry.shape[0]]*arry.shape[1] + tmp=np.empty((arry.shape[0], arry.shape[1])) + #print(arry.shape, len(Indi), len(Indj)) + if arry.shape[0]!= len(Indi): + Indi=np.arange(0,arry.shape[0]) + if arry.shape[1]!= len(Indj): + Indj=np.arange(0,arry.shape[1]) + + p=0 + q=0 + for i in Indi: + q=0 + for j in Indj: + tmp[i][j]=arry[p][q] + q=q+1 + p=p+1 + return tmp + +def getStateOrderingIndx(matData): + + #StateOrderingIndx={} + StateOrderingIndx = np.arange(0,matData['NumStates']) + lastModName = ''; + lastModOrd = 0; + mod_nDOFs = 0; # number of DOFs in each module + sum_nDOFs2 = 0; # running total of second-order DOFs + sum_nDOFs1 = 0; # running total of first-order DOFs + indx_start = 0; # starting index of the modules + + for i in range(0,matData['NumStates']): + + tmp=(matData['DescStates'][i]); # name of the module whose states we are looking at + modName = tmp.split(' ')[0] + ModOrd = matData['StateDerivOrder'][i] + + if lastModName!=modName or lastModOrd!= ModOrd: + # this is the start of a new set of DOFs, so we'll set the + # indices for the last matrix + if lastModOrd == 2: + mod_nDOFs = int(mod_nDOFs/2); + #print('mmmm ', mod_nDOFs, indx_start, matData['ndof2'], i) + StateOrderingIndx[ indx_start :(indx_start+mod_nDOFs)] = sum_nDOFs2 + np.arange(0,mod_nDOFs); # q2 starts at 1 + StateOrderingIndx[ (indx_start+mod_nDOFs):(i)] = sum_nDOFs2 + matData['ndof2'] + np.arange(0,mod_nDOFs); # q2_dot starts at matData.ndof2 + 1 + + sum_nDOFs2 = sum_nDOFs2 + mod_nDOFs; + else: + if indx_start < mod_nDOFs: + StateOrderingIndx[indx_start:(indx_start+mod_nDOFs)] = sum_nDOFs1 + matData['NumStates2'] + np.arange(0,mod_nDOFs); # q1 starts at matData.NumStates2 + 1 + + sum_nDOFs1 = sum_nDOFs1 + mod_nDOFs; + + # reset for a new module (or new 1st-order states in the same module) + mod_nDOFs = 0; + + indx_start = i; #start of this module + lastModName = modName; + lastModOrd = matData['StateDerivOrder'][i]; + + mod_nDOFs = mod_nDOFs+1; + + + # repeat for the last module found: + if lastModOrd == 2: + mod_nDOFs = int(mod_nDOFs/2); + #print(mod_nDOFs,indx_start) + StateOrderingIndx[indx_start:(indx_start+mod_nDOFs)] = sum_nDOFs2 + np.arange(0,mod_nDOFs); # q2 starts at 1 + StateOrderingIndx[(indx_start+mod_nDOFs):matData['NumStates']] = sum_nDOFs2 + matData['ndof2'] + np.arange(0,mod_nDOFs); # q2_dot starts at matData.ndof2 + 1 + else: + StateOrderingIndx[indx_start:(indx_start+mod_nDOFs)] = sum_nDOFs1 + matData['NumStates2'] + np.arange(0,mod_nDOFs); # q1 starts at matData.NumStates2 + 1 + + #print(StateOrderingIndx) + return StateOrderingIndx + +def readOP(fid, n, defaultDerivOrder=2): + OP=[] + Var = {'RotatingFrame': [], 'DerivativeOrder': [], 'Description': []} + colNames=fid.readline().strip() + dummy= fid.readline().strip() + bHasDeriv= colNames.find('Derivative Order')>=0 + for i, line in enumerate(fid): + sp=line.strip().split() + if sp[1].find(',')>=0: + # Most likely this OP has three values (e.g. orientation angles) + # For now we discard the two other values + OP.append(float(sp[1][:-1])) + iRot=4 + else: + OP.append(float(sp[1])) + iRot=2 + Var['RotatingFrame'].append(sp[iRot]) + if bHasDeriv: + Var['DerivativeOrder'].append(int(sp[iRot+1])) + Var['Description'].append(' '.join(sp[iRot+2:]).strip()) + else: + Var['DerivativeOrder'].append(defaultDerivOrder) + Var['Description'].append(' '.join(sp[iRot+1:]).strip()) + if i>=n-1: + break + + tmp = dict() + tmp['x_op'] = OP + tmp['x_rotFrame'] = Var['RotatingFrame'] + tmp['x_DerivOrder'] = Var['DerivativeOrder'] + tmp['x_desc'] = Var['Description'] + + return tmp + + + +def readFASTMatrix(f): + name="" + m=0 + tmp=[] + for line in islice(f,1): + # copy matrix name to tmp_name + tmp_name=line.strip().split(':')[0] + # get matrix dimensions if matrix exists + if tmp_name != "": + m=int(line.strip().split(':')[1].split('x')[0]) + n=int(line.strip().split(':')[1].split('x')[1]) + + # copy matrix into tmp list + if m!=0: + name=tmp_name + for line in islice(f,m): + tmp.append([float(num) for num in line.split()]) + tmp=np.array(tmp) + return name,tmp + +def ReadFASTLinear(filename): + + def extractVal(lines, key): + for l in lines: + if l.find(key)>=0: + return l.split(key)[1].split()[0] + return None + + def readToMarker(fid, marker, nMax): + lines=[] + for i, line in enumerate(fid): + if i>nMax: + raise BrokenFormatError('`{}` not found in file'.format(marker)) + if line.find(marker)>=0: + break + lines.append(line.strip()) + return lines, line + + with open(filename) as f: + info = {} + data = {} + SetOfMatrices = 1 + info['name'] = os.path.splitext(os.path.basename(filename))[0] + + # --- + header, lastLine=readToMarker(f, 'Jacobians included', 30) + header.append(lastLine) + data['t'] = float(extractVal(header,'Simulation time:' )) + data['n_x'] = int(extractVal(header,'Number of continuous states:')) + data['n_xd'] = int(extractVal(header,'Number of discrete states:' )) + data['n_z'] = int(extractVal(header,'Number of constraint states:')) + data['n_u'] = int(extractVal(header,'Number of inputs:' )) + data['n_y'] = int(extractVal(header,'Number of outputs:' )) + bJac = extractVal(header,'Jacobians included in this file?') + if bJac: + SetOfMatrices = 2 + try: + data['Azimuth'] = float(extractVal(header,'Azimuth:')) + except: + data['Azimuth'] = None + try: + data['RotSpeed'] = float(extractVal(header,'Rotor Speed:')) # rad/s + except: + data['RotSpeed'] = np.nan + try: + data['WindSpeed'] = float(extractVal(header,'Wind Speed:')) + except: + data['WindSpeed'] = np.nan + + # --- Old method for reading + # header = [f.readline() for _ in range(17)] + # info['fast_version'] = header[1].strip() + # info['modules'] = header[2].strip() + # info['description'] = header[4].strip() + # ln=7; + # data = np.array([line.split() for line in f.readlines()]).astype(np.float) + # data['t']=np.float(header[ln].split(':')[1].strip().split(' ')[0]) + # data['RotSpeed']=np.float(header[ln+1].split(':')[1].strip().split(' ')[0]) + # data['Azimuth']=np.float(header[ln+2].split(':')[1].strip().split(' ')[0]) + # data['WindSpeed']=np.float(header[ln+3].split(':')[1].strip().split(' ')[0]) + # data['n_x']=np.float(header[ln+4].split(':')[1].strip().split(' ')[0]) + # data['n_xd']=np.float(header[ln+5].split(':')[1].strip().split(' ')[0]) + # data['n_z']=np.float(header[ln+6].split(':')[1].strip().split(' ')[0]) + # data['n_u']=np.float(header[ln+7].split(':')[1].strip().split(' ')[0]) + # data['n_y']=np.float(header[ln+8].split(':')[1].strip().split(' ')[0]) + # if header[ln+9].split('?')[1].strip()=='Yes': + # SetOfMatrices=2 + + data['Azimuth']=np.mod(data['Azimuth'],2.0*np.pi) + try: + # skip next three lines + for line in islice(f,2): + pass + if data['n_x'] > 0: + temp = readOP(f, data['n_x']) + data['x_op']=temp['x_op'] + data['x_rotFrame']=temp['x_rotFrame'] + data['x_DerivOrder']=temp['x_DerivOrder'] + data['x_desc']=temp['x_desc'] + + # skip next three lines + for line in islice(f,2): + pass + + temp = readOP(f, data['n_x'], defaultDerivOrder=2) + data['xdot_op']=temp['x_op'] + data['xdot_desc']=temp['x_desc'] + + #(number of second-order states) + data['n_x2'] = sum(1 for i in data['x_DerivOrder'] if i == 2) + else: + data['n_x2'] = 0; + + + if data['n_xd'] > 0: + # skip next three lines + for line in islice(f,2): + pass + temp = readOP(f, data['n_xd'], defaultDerivOrder=2) + data['xd_op']=temp['x_op'] + data['xd_desc']=temp['x_desc'] + if data['n_z'] > 0: + # skip next three lines + for line in islice(f,2): + pass + temp = readOP(f, data['n_z'], defaultDerivOrder=0) + data['z_op']=temp['x_op'] + data['z_desc']=temp['x_desc'] + if data['n_u'] > 0: + # skip next three lines + for line in islice(f,2): + pass + temp = readOP(f, data['n_u'], defaultDerivOrder=0) + data['u_op']=temp['x_op'] + data['u_desc']=temp['x_desc'] + data['u_rotFrame']=temp['x_rotFrame'] + if data['n_y'] > 0: + # skip next three lines + for line in islice(f,2): + pass + temp = readOP(f, data['n_y'], defaultDerivOrder=0) + data['y_op']=temp['x_op'] + data['y_desc']=temp['x_desc'] + data['y_rotFrame']=temp['x_rotFrame'] + + # skip next one line + for line in islice(f,4): + pass + + mat_names=[] + while True: + name,mat=readFASTMatrix(f) + if not name: + break; + mat_names.append(name) + data[name]=mat + + return data, info + + except (ValueError, AssertionError): + raise + + +def get_Mats(FileNames, verbose=True, removeTwrAzimuth=False): + NAzimStep = len(FileNames) + data = [None]*NAzimStep + # --- Read all files + for iFile, filename in enumerate(FileNames): + data[iFile],_= ReadFASTLinear(FileNames[iFile]); + Azimuth = np.array([d['Azimuth'] for d in data])*180/np.pi + # --- Sort by azimuth, not required, but filenames are not sorted, nor are the lin times azimuth + ISort = np.argsort(Azimuth) + Azimuth = Azimuth[ISort] + data = [data[i] for i in ISort] + FileNames = [FileNames[i] for i in ISort] + if removeTwrAzimuth: + IDiscard = [i for i,a in enumerate(Azimuth) if np.any(np.abs(np.array([60,180,300])-a)<4) ] + n=len(FileNames[0]); sfmt='{:'+str(n+2)+'s}' + for i in IDiscard: + print(' discard: '+sfmt.format(FileNames[i]) + ' (psi={:5.1f})'.format(Azimuth[i])) + data = [d for i,d in enumerate(data) if i not in IDiscard] + NAzimStep= len(data) + + + matData={} + matData['NAzimStep']= NAzimStep; + + # --- Using last azimuth to initial some of the "matData" variables + # Input data from linearization files + matData['NumStates'] = int(data[NAzimStep-1]['n_x']); + matData['NumStates2'] = int(data[NAzimStep-1]['n_x2']); + + #return data, matData + matData['ndof1'] = int(matData['NumStates'] - matData['NumStates2']); # number of first-order states = number of first-order DOFs + matData['ndof2'] = int(data[NAzimStep-1]['n_x2'] / 2); # half the number of second-order states = number of second-order DOFs + #% matData['ndof'] = matData['ndof2'] + matData['ndof1']; #half the number of second-order states plus the number of first-order states (i.e., states that aren't derivatives) + + matData['NumInputs'] = int(data[NAzimStep-1]['n_u']); + matData['NumOutputs'] = int(data[NAzimStep-1]['n_y']); + + # allocate space for these variables + matData['Azimuth'] = np.zeros(NAzimStep); + matData['Omega'] = np.zeros(NAzimStep); + matData['OmegaDot'] = np.zeros(NAzimStep); + + matData['WindSpeed'] = np.zeros(NAzimStep)*np.nan; + + if matData['NumStates'] > 0: + matData['DescStates'] = data[NAzimStep-1]['x_desc']; + matData['StateDerivOrder'] = data[NAzimStep-1]['x_DerivOrder']; + matData['xdop'] = np.zeros((matData['NumStates'], NAzimStep)) + matData['xop'] = np.zeros((matData['NumStates'], NAzimStep)) + matData['A'] = np.zeros((matData['NumStates'], matData['NumStates'], NAzimStep)) + + if matData['NumInputs'] > 0: + matData['DescCntrlInpt'] = data[NAzimStep-1]['u_desc']; + matData['u_op'] = np.zeros((matData['NumInputs'],NAzimStep)) + if matData['NumStates']>0: + matData['B'] = np.zeros((matData['NumStates'], matData['NumInputs'],NAzimStep)) + + if matData['NumOutputs'] > 0: + matData['DescOutput'] = data[NAzimStep-1]['y_desc'] + matData['y_op'] = np.zeros((matData['NumOutputs'],NAzimStep)) + + if matData['NumStates'] > 0: + matData['C'] = np.zeros((matData['NumOutputs'], matData['NumStates'], NAzimStep)) + if matData['NumInputs'] > 0: + matData['D'] = np.zeros((matData['NumOutputs'], matData['NumInputs'], NAzimStep)) + + # Reorder state matrices so that they follow the {q2, q2_dot, q1} + # format that is assumed in the MBC3 equations. + if matData['NumStates'] > 0: + # keep StateOrderingIndx for applying inverse of MBC3 later + # (to visualize mode shapes) + matData['StateOrderingIndx'] = getStateOrderingIndx(matData) + + sortedIndx=matData['StateOrderingIndx'] + #print(sortedIndx) + x_rotFrame= reOrderByIdx_1D(data[NAzimStep-1]['x_rotFrame'],sortedIndx) + matData['DescStates'] = reOrderByIdx_1D(data[NAzimStep-1]['x_desc'],sortedIndx) + matData['StateDerivOrder'] = reOrderByIdx_1D(data[NAzimStep-1]['x_DerivOrder'],sortedIndx) + + # --- Store file data into matData + for iFile in np.arange(0,NAzimStep): + matData['Omega'][iFile] = data[iFile]['RotSpeed'] ; + matData['Azimuth'][iFile] = data[iFile]['Azimuth']*180/np.pi; + + matData['WindSpeed'][iFile] = data[iFile]['WindSpeed'] + + if 'A' in data[iFile]: + matData['A'][:,:,iFile]=reOrderByIdx_2D(data[iFile]['A'],sortedIndx,sortedIndx) + #print('size of matData[A] for file ', iFile, ' is :', matData['A'].shape) + if 'B' in data[iFile]: + matData['B'][:,:,iFile]=reOrderByIdx_2D(data[iFile]['B'],sortedIndx,np.arange(0,matData['NumStates'])) + #print('size of matData[B] for file ', iFile, ' is :', matData['B'].shape) + if 'C' in data[iFile]: + matData['C'][:,:,iFile]=reOrderByIdx_2D(data[iFile]['C'],np.arange(0,matData['NumStates']),sortedIndx) + #print('size of matData[C] for file ', iFile, ' is :', matData['C'].shape) + if 'D' in data[iFile]: + matData['D'][:,:,iFile]=reOrderByIdx_2D(data[iFile]['D'],sortedIndx,sortedIndx) + #print('size of matData[D] for file ', iFile, ' is :', matData['D'].shape) + + if 'x_op' in data[iFile]: + matData['xop'][:,iFile] = reOrderByIdx_1D(data[iFile]['x_op'],sortedIndx) + #print('matData[xop] for file ', iFile,' is :',(matData['xop'][:,iFile])) + if 'xdot_op' in data[iFile]: + matData['xdop'][:,iFile] = reOrderByIdx_1D(data[iFile]['xdot_op'],sortedIndx) + #print('matData[xdop] for file ', iFile,' is :',(matData['xdop'][:,iFile])) + + if 'u_op' in data[iFile]: + matData['u_op'][:,iFile] = data[iFile]['u_op'] + + if 'y_op' in data[iFile]: + matData['y_op'][:,iFile] = data[iFile]['y_op'] + + + # Find the azimuth-averaged linearized 1st order state matrices: + if 'A' in matData: + matData['Avgxdop'] = np.mean(matData['xdop'],axis=1) + matData['Avgxop'] = np.mean(matData['xop'], axis=1) + matData['AvgA'] = np.mean(matData['A'],axis=2) + + #print(matData['AvgA']) + if 'B' in matData: + matData['AvgB'] = np.mean(matData['B'],axis=2) + + if 'C' in matData: + matData['AvgC'] = np.mean(matData['C'],axis=2) + + if 'D' in matData: + matData['AvgD'] = np.mean(matData['D'],axis=2) + + + foundED = True; + for i in range(matData['ndof2']): + # find the starting index of the string 'DOF_GeAz' + if (matData['DescStates'][i].find('DOF_GeAz') != -1): + matData['Omega'] = matData['xdop'][i,:] + matData['OmegaDot'] = matData['xdop'][i+matData['ndof2'],:] + foundED = True + break + + for i in range(matData['ndof2']): + # find the starting index of the string 'DOF_DrTr' + if (matData['DescStates'][i].find('DOF_DrTr') != -1): + matData['Omega'] = matData['Omega'] + matData['xdop'][i,:] #This always comes after DOF_GeAz so let's just add it here (it won't get written over later). + matData['OmegaDot'] = matData['OmegaDot'] + matData['xdop'][i+matData['ndof2'],:] + foundED = True + break + + if not foundED: + for i in range(matData['ndof2']): + # find the starting index of the string 'Gearbox_Rot' + if (matData['DescStates'][i].find('MBD Gearbox_Rot') != -1): + matData['Omega'] = matData['xdop'][i,:] + matData['OmegaDot'] = matData['xdop'][i+matData['ndof2'],:] + break + + #print("\n".join(matData['DescStates'])) + #exit() + # ----------- Find multi-blade coordinate (MBC) transformation indices ---- + + # Find the indices for, state triplets in the rotating frame + # (note that we avoid the "first time derivative" states) + if matData['ndof2'] > 0: + matData['RotTripletIndicesStates2'], matData['n_RotTripletStates2'] = findBladeTriplets(x_rotFrame[0:matData['ndof2']],matData['DescStates'][0:matData['ndof2']], verbose=verbose) + else: + matData['RotTripletIndicesStates2'] = []; + matData['n_RotTripletStates2'] = 0; + + if matData['ndof1'] > 0: + matData['RotTripletIndicesStates1'], matData['n_RotTripletStates1'] = findBladeTriplets( x_rotFrame[matData['NumStates2']:] ,matData['DescStates'][matData['NumStates2']:] , verbose=verbose); + else: + matData['RotTripletIndicesStates1'] = []; + matData['n_RotTripletStates1'] = 0; + + # Find the indices for control input triplets in the rotating frame: + if matData['NumInputs'] > 0: + matData['RotTripletIndicesCntrlInpt'], matData['n_RotTripletInputs'] = findBladeTriplets(data[0]['u_rotFrame'],matData['DescCntrlInpt'], verbose=verbose ); + else: + matData['RotTripletIndicesCntrlInpt'] = []; + matData['n_RotTripletInputs'] = 0; + + # Find the indices for output measurement triplets in the rotating frame: + if (matData['NumOutputs'] > 0 ): + matData['RotTripletIndicesOutput'], matData['n_RotTripletOutputs'] = findBladeTriplets(data[0]['y_rotFrame'],matData['DescOutput'], verbose=verbose ); + else: + matData['RotTripletIndicesOutput'] = []; + matData['n_RotTripletOutputs'] = 0; + + return matData, data + +#matData,FAST_linData=get_Mats(FileNames) + +#print("\n".join(matData['DescStates'])) + +# print(info) +# print(data['t']) +# print(data['RotSpeed']) +# print(data['Azimuth']) +# print(data['WindSpeed']) +# print(data['n_x']) +# print(data['n_xd']) +# print(data['n_z']) +# print(data['n_u']) +# print(data['n_y']) +# print(data['n_x2']) +# print(data['x_op']) +# print(data['x_desc']) +# print(data['x_rotFrame']) +# print(data['xdot_op']) +# print(data['xdot_desc']) +# print(data['u_op']) +# print(data['u_desc']) +# print(data['u_rotFrame']) +# print(data['y_op']) +# print(data['y_desc']) +# print(data['y_rotFrame']) diff --git a/ROSCO_toolbox/linear/lin_util.py b/rosco/toolbox/linear/lin_util.py similarity index 100% rename from ROSCO_toolbox/linear/lin_util.py rename to rosco/toolbox/linear/lin_util.py diff --git a/ROSCO_toolbox/linear/lin_vis.py b/rosco/toolbox/linear/lin_vis.py similarity index 97% rename from ROSCO_toolbox/linear/lin_vis.py rename to rosco/toolbox/linear/lin_vis.py index 35d50714..56694e09 100644 --- a/ROSCO_toolbox/linear/lin_vis.py +++ b/rosco/toolbox/linear/lin_vis.py @@ -1,7 +1,7 @@ ''' Visualization helpers for linear models ''' -from ROSCO_toolbox.linear.lin_util import add_pcomp, pc_openloop +from rosco.toolbox.linear.lin_util import add_pcomp, pc_openloop import numpy as np import matplotlib.pyplot as plt import scipy as sp diff --git a/ROSCO_toolbox/linear/linear_models.py b/rosco/toolbox/linear/linear_models.py similarity index 98% rename from ROSCO_toolbox/linear/linear_models.py rename to rosco/toolbox/linear/linear_models.py index f096ce56..f2004a7a 100644 --- a/ROSCO_toolbox/linear/linear_models.py +++ b/rosco/toolbox/linear/linear_models.py @@ -11,15 +11,9 @@ import control as co import matplotlib.pyplot as plt import multiprocessing as mp -from itertools import chain from scipy.io import loadmat -try: - import pyFAST.linearization.mbc as mbc -except ImportError: - import weis.control.mbc.mbc3 as mbc -except ImportError: - raise ImportError('Unable to load mbc3 from pyFAST or WEIS') +import rosco.toolbox.linear.mbc3 as mbc class LinearTurbineModel(object): @@ -462,7 +456,7 @@ def solve(self, disturbance, Plot=False, open_loop=True, controller={}, reduce_s OutList = [out_name.split()[1][:-1] for out_name in P_op.OutputName] OutData_arr = y.T - # Turn OutData into dict like in ROSCO_toolbox + # Turn OutData into dict like in rosco.toolbox OutData = {} for i, out_chan in enumerate(OutList): OutData[out_chan] = OutData_arr[:, i] @@ -710,7 +704,7 @@ def run_mbc3(fnames): Helper function to run mbc3 ''' print('Loading linearizations from:', ''.join(fnames[0].split('.')[:-2])) - MBC, matData = mbc.fx_mbc3(fnames, verbose=False) + MBC, matData, _ = mbc.fx_mbc3(fnames, verbose=False) return MBC, matData diff --git a/rosco/toolbox/linear/mbc3.py b/rosco/toolbox/linear/mbc3.py new file mode 100644 index 00000000..e80956e8 --- /dev/null +++ b/rosco/toolbox/linear/mbc3.py @@ -0,0 +1,1071 @@ +############################################################# +# Perform MBC3 Analysis and plot Campbell Diagram # +############################################################# + +import rosco.toolbox.linear.getMats as gm +import numpy as np +import scipy.linalg as scp +import re +import os +import sys +# import plotCampbellData as pCD + +def getScaleFactors(DescStates, TowerLen, BladeLen): + + ScalingFactor = np.ones(len(DescStates)) + + # look at the state description strings for tower and blade + # translational dofs: + for i in range(len(ScalingFactor)): + + # look for blade dofs: + if DescStates[i].find('blade')!=-1 or DescStates[i].find('Blade')!=-1: + if DescStates[i].find('rotational')==-1: # make sure this isn't a rotational dof from BeamDyn + ScalingFactor[i] = 1.0/BladeLen; + #print(DescStates[i]) + + # look for tower translational dofs: + if DescStates[i].find('tower')!=-1 or DescStates[i].find('Tower')!=-1: + ScalingFactor[i] = 1.0/TowerLen; + + # look for blade dofs: + elif DescStates[i].find('blade')!=-1 or DescStates[i].find('Blade')!=-1: + if DescStates[i].find('rotational')==-1: # make sure this isn't a rotational dof from BeamDyn + ScalingFactor[i] = 1.0/BladeLen; + + return ScalingFactor + + +def IdentifyModes(CampbellData): + """ + Attempts to perform an identification of the modes. + For now, the method is based on the energy content of the modes, and the state descriptions where the energy is maximum + + Original contribution by: Srinivasa B. Ramisett, ramisettisrinivas@yahoo.com, http://ramisetti.github.io + """ + + # --- Looking at states descriptions (of first run, first mode), to see if we are offshore. + # NOTE: DescStates is likely the same for all modes + DescStates = CampbellData[0]['Modes'][0]['DescStates'] + hasHeave = any(['heave' in s.lower() for s in DescStates]) + hasSurge = any(['surge' in s.lower() for s in DescStates]) + hasSway = any(['sway' in s.lower() for s in DescStates]) + hasYaw = any(['platform yaw' in s.lower() for s in DescStates]) + hasRoll = any(['platform roll tilt' in s.lower() for s in DescStates]) + hasPitch = any(['platform pitch tilt' in s.lower() for s in DescStates]) + hasEdge1Col = any(['1st edgewise bending-mode dof of blade collective' in s.lower() for s in DescStates]) + + # --- Setting up a list of modes with + modesDesc = [] + modesDesc.append( ['Generator DOF (not shown)' , 'ED Variable speed generator DOF, rad'] ) + # Platform DOFs + if hasSurge: + modesDesc.append( ['Platform surge', 'ED Platform horizontal surge translation DOF, m'] ) + if hasSway: + modesDesc.append( ['Platform sway', 'ED Platform horizontal sway translation DOF, m'] ) + if hasHeave: + modesDesc.append( ['Platform heave', 'ED Platform vertical heave translation DOF, m'] ) + if hasRoll: + modesDesc.append( ['Platform roll', 'ED Platform roll tilt rotation DOF, rad'] ) + if hasPitch: + modesDesc.append( ['Platform pitch', 'ED Platform pitch tilt rotation DOF, rad'] ) + if hasYaw: + modesDesc.append( ['Platform yaw', 'ED Platform yaw rotation DOF, rad'] ) + + modesDesc.append( ['1st Tower FA' , 'ED 1st tower fore-aft bending mode DOF, m'] ) + modesDesc.append( ['1st Tower SS' , 'ED 1st tower side-to-side bending mode DOF, m'] ) + modesDesc.append( ['1st Blade Flap (Regressive)' , 'ED 1st flapwise bending-mode DOF of blade (sine|cosine), m', r'Blade (sine|cosine) finite element node \d rotational displacement in Y, rad'] ) + modesDesc.append( ['1st Blade Flap (Collective)' , 'ED 1st flapwise bending-mode DOF of blade collective, m', r'Blade collective finite element node \d rotational displacement in Y, rad'] ) + modesDesc.append( ['1st Blade Flap (Progressive)' , 'ED 1st flapwise bending-mode DOF of blade (sine|cosine), m'] ) # , ... # 'Blade (sine|cosine) finite element node \d rotational displacement in Y, rad'] + modesDesc.append( ['1st Blade Edge (Regressive)' , 'ED 1st edgewise bending-mode DOF of blade (sine|cosine), m', r'Blade (sine|cosine) finite element node \d rotational displacement in X, rad'] ) + if hasEdge1Col: + modesDesc.append(['1st Blade Edge (Collective)', 'ED 1st edgewise bending-mode DOF of blade collective, m'] ) # , ... # 'Blade (sine|cosine) finite element node \d rotational displacement in Y, rad'] + modesDesc.append( ['1st Blade Edge (Progressive)' , 'ED 1st edgewise bending-mode DOF of blade (sine|cosine), m'] ) + modesDesc.append( ['1st Drivetrain Torsion' , 'ED Drivetrain rotational-flexibility DOF, rad'] ) + modesDesc.append( ['2nd Tower FA' , 'ED 2nd tower fore-aft bending mode DOF, m'] ) + modesDesc.append( ['2nd Tower SS' , 'ED 2nd tower side-to-side bending mode DOF, m'] ) + modesDesc.append( ['2nd Blade Flap (Regressive)' , 'ED 2nd flapwise bending-mode DOF of blade (sine|cosine), m'] ) + modesDesc.append( ['2nd Blade Flap (Collective)' , 'ED 2nd flapwise bending-mode DOF of blade collective, m', r'Blade collective finite element node \d rotational displacement in Y, rad'] ) + modesDesc.append( ['2nd Blade Flap (Progressive)' , 'ED 2nd flapwise bending-mode DOF of blade (sine|cosine), m'] ) + modesDesc.append( ['Nacelle Yaw (not shown)' , 'ED Nacelle yaw DOF, rad'] ) + + + nModes = int(len(modesDesc)) + nRuns = int(len(CampbellData)) + modeID_table=np.zeros((nModes,nRuns)).astype(int) + + + + def doesDescriptionMatch(description, listOfModePatterns): + """ loop through all mode desrption """ + for iModePattern, modeIDdescList in enumerate(listOfModePatterns): + modeIDName = modeIDdescList[0] + patternList = modeIDdescList[1:] # list of patterns for a given mode + found, pattern = doesDescriptionMatchPatternList(description, patternList) + if found: + return True, iModePattern, pattern + return False, -1, '' + + def doesDescriptionMatchPatternList(description, patternList): + """ loop through all patterns to find a match """ + for pattern in patternList: + # Looking for targetDesc into description + if re.search(pattern ,description, re.IGNORECASE)!=None: + return True, pattern + return False, '' + + + verbose=False + Levels=[1,2,3] + + + # --- Loop on operating points/Runs + for i in range(nRuns): + Modes = CampbellData[i]['Modes'] + nModes = len(Modes) + # Array of logical, False for Modes that are not identified + modesIdentified = [False] * nModes + modesSkipped = [False] * nModes + #verbose=verbose and i==0 # only display for first mode for now.. + #verbose=i==1 + + # --- Give an index to each mode so that we can easily identify them + for im, mode in enumerate(Modes): + mode['index']=im + + # --- Skip modes based on simple criteria + for im, mode in enumerate(Modes): + if mode['NaturalFreq_Hz'] < 1e-5 or mode['DampingRatio'] > 0.98: + modesSkipped[im]=True + + + + modesDescLocal = modesDesc.copy() + + # --- Level 1 - Find well-defined modes (modes which have only one Max) + if 1 in Levels: + for im, mode in enumerate(Modes): + if modesIdentified[im] or modesSkipped[im]: + continue # skip this mode since it has already been identified + stateMax=np.argwhere((mode['StateHasMaxAtThisMode']==1)).flatten() + if len(stateMax)==1: + description = mode['DescStates'][stateMax[0]] + if description.startswith('AD'): + # We skipp the pure "AD" modes + modesSkipped[im] = True + continue + found, modeID, patternMatched = doesDescriptionMatch(description, modesDescLocal) + if found and modeID_table[modeID,i]==0: + modesDescLocal[modeID] = [None,] # we empty this mode patternlist so that it cannot be matched again + modesIdentified[im] = True + modeID_table[modeID,i] = im+1 # Using Matlab Indexing + if verbose: + print('L1 Mode {} identified using pattern: {}'.format(im+1,patternMatched)) + print(' String was: ', description) + #else: + # print('>>> Cannot identify mode with description {}. Update MBC3 script.'.format(description)) + + # --- Level 2 - Find modes with several max - Looping on mode pattern to respect expected frequency order + if 2 in Levels: + for modeID, modeIDdescList in enumerate(modesDescLocal): + modeIDName = modeIDdescList[0] + patternList = modeIDdescList[1:] + # Skip modes already identified above + if modeID_table[modeID,i]>0: + continue + if verbose: + print('------------------------- LEVEL 2 - LOOKING FOR MODE ',modeIDName) + + found = False; + # --- Loop on all non-identified modes in increasing order + im = 0; + for im, mode in enumerate(Modes): + if modesIdentified[im] or modesSkipped[im]: + continue # move to next mode + # List of component descriptions where this mode has maximum values + stateMax=np.argwhere((mode['StateHasMaxAtThisMode']==1)).flatten() + descriptions = np.array(mode['DescStates'])[stateMax] + descriptions = descriptions[:7] # we keep only the first 7 descriptions + descriptionsED = [d for d in descriptions if d.startswith('ED')] + descriptionsBD = [d for d in descriptions if d.startswith('BD')] + descriptionsAD = [d for d in descriptions if d.startswith('AD')] + descriptionsMisc = [d for d in descriptions if d not in descriptionsED+descriptionsBD+descriptionsAD] + descriptions = descriptionsED+descriptionsBD+descriptionsMisc # NOTE: we skipp AD descriptions + j = 0; + for description in descriptions: + found, pattern = doesDescriptionMatchPatternList(description, patternList) + if found: + if verbose: + print('L2 Mode {} identified using pattern {}'.format(im+1,pattern)) + modeID_table[modeID,i] = im+1 # Using Matlab Indexing + modesDescLocal[modeID] = [None,] # we empty this mode patternlist so that it cannot be matched again + modesIdentified[im] = True; + break + if found: + break + if verbose: + print('>> modeIDTable',modeID_table[:,i]) + # We disqualify modes that had max and that didn't match anything: + for im, mode in enumerate(Modes): + if modesIdentified[im] or modesSkipped[im]: + continue # move to next mode + stateMax=np.argwhere((mode['StateHasMaxAtThisMode']==1)).flatten() + if len(stateMax)>=1: + modesSkipped[im]=True + shortdescr = CampbellData[i]['ShortModeDescr'][im] + if shortdescr.find('ED')>=0: + print('>>>> short', CampbellData[i]['ShortModeDescr'][im]) + print('>>>> Problem in IndentifyModes. ED DOF found in level 2') + # import pdb; pdb.set_trace() + + if 3 in Levels: + # --- Level 3 - Try our best for modes with no max + # Loop on modes to be identified + for modeID, modeIDdescList in enumerate(modesDescLocal): + modeIDName = modeIDdescList[0] + patternList = modeIDdescList[1:] + + # Skip modes already identified above + if modeID_table[modeID,i]>0: + continue + if verbose: + print('------------------------- LEVEL 3 - LOOKING FOR MODE ',modeIDName) + + found = False; + # --- Loop on all non-identified modes in increasing order + im = 0; + while not found and im < nModes: # Loop on modes + mode = Modes[im] + if modesIdentified[im] or modesSkipped[im]: + pass + else: + # --- Otherwise, use as mode descriptions the other ones. Seems weird + stateMax=np.argwhere((mode['StateHasMaxAtThisMode']==0)).flatten() + descriptions = np.array(mode['DescStates'])[stateMax] + ADcounts = np.sum([s.startswith('AD') for s in descriptions[:5]]) + + descriptions2= np.array(mode['DescStates'])[mode['StateHasMaxAtThisMode']] + if len(descriptions2) == 0: + noMax=True + descriptions3 = mode['DescStates'][:5] + else: + noMax=False +# import pdb; pdb.set_trace() + if ADcounts<5: + descriptions=[d for d in descriptions if not d.startswith('AD')] +# descriptionsED = [d for d in descriptions if d.startswith('ED')] +# descriptionsBD = [d for d in descriptions if d.startswith('BD')] +# descriptionsAD = [d for d in descriptions if d.startswith('AD')] +# descriptionsMisc = [d for d in descriptions if d not in descriptionsED+descriptionsBD+descriptionsAD] +# descriptions = descriptionsED+descriptionsBD+descriptionsMisc # NOTE: we skipp AD descriptions + descriptions = descriptions[:5] # we keep only the first 7 descriptions + if verbose: + print('>>> Mode',mode['index'], modesIdentified[im], modesSkipped[im]) + print('>>>> descr', [replaceModeDescription(s) for s in descriptions]) + print('>>>> short', CampbellData[i]['ShortModeDescr'][im]) + else: + descriptions=[] +# #descriptions = descriptions[:7] # we keep only the first 7 descriptions + + j = 0; + while not found and j < len(descriptions): + j = j + 1; + if not found: + for targetDesc in patternList: + # Looking for targetDesc into list of descriptions + if re.search(targetDesc ,descriptions[j-1],re.IGNORECASE)!=None: + modeID_table[modeID,i] = im+1 # Using Matlab Indexing + if verbose: + print('L3 Mode {} identified as {}'.format(im+1,targetDesc)) + print(' String was: ', descriptions[j-1]) + modesIdentified[im] = True; + found = True; + break; + im=im+1; # increment counter + if verbose: + print('>> modeIDTable',modeID_table[:,i]) + + if verbose: + print('---------- Summary') + for j in np.arange(len(modeID_table)): + print('{:32s} {:d}'.format(modesDesc[j][0],modeID_table[j,i])) + print('---------- ') + + + return modeID_table,modesDesc + +def IdentifiedModesDict(CampbellData,modeID_table,modesDesc): + """ + To be called with the results of IdentifyModes. + Create a list of dictionaries to more easily interprete the result + """ + nOP = modeID_table.shape[1] + modesInfoPerOP=[] + for iOP in np.arange(nOP): + modesInfo={} + for i in np.arange(len(modesDesc)): + desc = modesDesc[i][0] + ID = int(modeID_table[i,iOP]) + if ID==0: + freq=np.nan + damp=np.nan + cont='' + else: + freq = np.around(CampbellData[iOP]['Modes'][ID-1]['NaturalFreq_Hz'],5) + damp = np.around(CampbellData[iOP]['Modes'][ID-1]['DampingRatio'],5) + cont = CampbellData[iOP]['ShortModeDescr'][ID-1] + modesInfo[desc]={'ID':ID,'f0':freq,'zeta':damp,'cont':cont} + modesInfoPerOP.append(modesInfo) + return modesInfoPerOP + +def campbell_diagram_data(mbc_data, BladeLen, TowerLen): + """ + + Original contribution by: Srinivasa B. Ramisett, ramisettisrinivas@yahoo.com, http://ramisetti.github.io + """ + + CampbellData={} + usePercent = False; + # + # mbc_data.eigSol = eiganalysis(mbc_data.AvgA); + ndof = mbc_data['ndof2'] + mbc_data['ndof1']; #size(mbc_data.AvgA,1)/2; # number of translational states + nModes = len(mbc_data['eigSol']['Evals']) + #print(nModes) + DescStates = PrettyStateDescriptions(mbc_data['DescStates'], mbc_data['ndof2'], mbc_data['performedTransformation']); + + ## store indices of max mode for state and to order natural frequencies + #StatesMaxMode_vals = np.amax(mbc_data['eigSol']['MagnitudeModes'],axis=1); # find which mode has the maximum value for each state (max of each row before scaling) + StatesMaxMode = np.argmax(mbc_data['eigSol']['MagnitudeModes'],axis=1); # find which mode has the maximum value for each state (max of each row before scaling) + SortedFreqIndx = np.argsort((mbc_data['eigSol']['NaturalFreqs_Hz']).flatten(),kind="heapsort"); + #print(SortedFreqIndx) + + + if BladeLen!=0 or TowerLen!=0: + ## get the scaling factors for the mode rows + ScalingFactor = getScaleFactors(DescStates, TowerLen, BladeLen); + + ## scale the magnitude of the modes by ScalingFactor (for consistent units) + # and then scale the columns so that their maximum is 1 + + ModesMagnitude = np.matmul(np.diag(ScalingFactor), mbc_data['eigSol']['MagnitudeModes']); # scale the rows + #print(ModesMagnitude) + + CampbellData['ScalingFactor'] = ScalingFactor; + else: + ModesMagnitude = mbc_data['eigSol']['MagnitudeModes']; + + if usePercent: + scaleCol = np.sum( ModesMagnitude )/100; # find the sum of the column, and multiply by 100 (divide here) to get a percentage + else: + scaleCol = np.amax(ModesMagnitude,axis=0); #find the maximum value in the column, so the first element has value of 1 + + ModesMagnitude = np.matmul(ModesMagnitude,np.diag(1./scaleCol)) # scale the columns + + # --- Summary data (array for all modes) + CampbellData['NaturalFreq_Hz'] = mbc_data['eigSol']['NaturalFreqs_Hz'][SortedFreqIndx] + CampbellData['DampingRatio'] = mbc_data['eigSol']['DampRatios'][SortedFreqIndx] + CampbellData['RotSpeed_rpm'] = mbc_data['RotSpeed_rpm'] + if 'WindSpeed' in mbc_data: + CampbellData['WindSpeed'] = mbc_data['WindSpeed'] + + #print(ModesMagnitude) + + # --- Storing data per mode + CampbellData['Modes']=[] + + for i in range(nModes): + CData={} + CData['NaturalFreq_Hz'] = mbc_data['eigSol']['NaturalFreqs_Hz'][SortedFreqIndx[i]][0] + CData['DampedFreq_Hz'] = mbc_data['eigSol']['DampedFreqs_Hz'][SortedFreqIndx[i]][0]; + CData['DampingRatio'] = mbc_data['eigSol']['DampRatios'][SortedFreqIndx[i]][0]; + + + #print(np.argsort(ModesMagnitude[:,SortedFreqIndx[0]])[::-1]) + # sort indices in descending order + sort_state = np.argsort( ModesMagnitude[:,SortedFreqIndx[i]])[::-1]; + + #print(type(sort_state)) + CData['DescStates']=[DescStates[i] for i in sort_state] + CData['MagnitudePhase']=ModesMagnitude[sort_state,SortedFreqIndx[i]]; + Phase = mbc_data['eigSol']['PhaseModes_deg'][sort_state,SortedFreqIndx[i]]; + # if the phase is more than +/- 90 degrees different than the first + # one (whose value == 1 or is the largest %), we'll stick a negative value on the magnitude: + Phase = np.mod(Phase, 360); + + CData['PhaseDiff'] = np.mod( Phase - Phase[0], 360); # difference in range [0, 360) + PhaseIndx = CData['PhaseDiff'] > 180; + CData['PhaseDiff'][PhaseIndx] = CData['PhaseDiff'][PhaseIndx] - 360; # move to range (-180, 180] + + if ~usePercent: + PhaseIndx = CData['PhaseDiff'] > 90; + CData['MagnitudePhase'][PhaseIndx] = -1*CData['MagnitudePhase'][PhaseIndx]; + CData['PhaseDiff'][PhaseIndx] = CData['PhaseDiff'][PhaseIndx] - 180; + + PhaseIndx = CData['PhaseDiff'] <= -90; + CData['MagnitudePhase'][PhaseIndx] = -1*CData['MagnitudePhase'][PhaseIndx]; + CData['PhaseDiff'][PhaseIndx] = CData['PhaseDiff'][PhaseIndx] + 180; + + #print(CData['MagnitudePhase']) + #print(CData['PhaseDiff']) + + CData['StateHasMaxAtThisMode'] = np.ones(ndof, dtype=bool); + ix = (StatesMaxMode == SortedFreqIndx[i]); + tmp=ix[sort_state] + CData['StateHasMaxAtThisMode']=tmp + + #print(CData['StateHasMaxAtThisMode']) + #print(CData['NaturalFreq_Hz']) + CampbellData['Modes'].append(CData) + + #print(CampbellData[0]['MagnitudePhase']) + # Adding short description to summary + CampbellData['ShortModeDescr'] =[extractShortModeDescription(CampbellData['Modes'][i]) for i in range(nModes)] + + + CampbellData['nColsPerMode'] = 5; + CampbellData['ModesTable'] = {} + + for i in range(nModes): + colStart = i*CampbellData['nColsPerMode']; + CampbellData['ModesTable'][1, colStart+1 ] = 'Mode number:'; + CampbellData['ModesTable'][1, colStart+2 ] = i; + + CampbellData['ModesTable'][2, colStart+1 ] = 'Natural (undamped) frequency (Hz):'; + CampbellData['ModesTable'][2, colStart+2 ] = CampbellData['Modes'][i]['NaturalFreq_Hz'] + + CampbellData['ModesTable'][3, colStart+1 ] = 'Damped frequency (Hz):'; + CampbellData['ModesTable'][3, colStart+2 ] = CampbellData['Modes'][i]['DampedFreq_Hz'] + + CampbellData['ModesTable'][4, colStart+1 ] = 'Damping ratio (-):'; + CampbellData['ModesTable'][4, colStart+2 ] = CampbellData['Modes'][i]['DampingRatio'] + + CampbellData['ModesTable'][5, colStart+1 ] = 'Mode ' + str(i) + ' state description'; + CampbellData['ModesTable'][5, colStart+2 ] = 'State has max at mode ' + str(i); + if usePercent: + CampbellData['ModesTable'][5, colStart+3 ] = 'Mode ' + str(i) + ' contribution (%)'; + else: + CampbellData['ModesTable'][5, colStart+3 ] = 'Mode ' + str(i) + ' signed magnitude'; + + CampbellData['ModesTable'][5, colStart+4 ] = 'Mode ' + str(i) + ' phase (deg)'; + + # need to cross check these 4 lines + CampbellData['ModesTable'][6,colStart+1] = CampbellData['Modes'][i]['DescStates']; + CampbellData['ModesTable'][6,colStart+2] = CampbellData['Modes'][i]['StateHasMaxAtThisMode']; + CampbellData['ModesTable'][6,colStart+3] = CampbellData['Modes'][i]['MagnitudePhase']; + CampbellData['ModesTable'][6,colStart+4] = CampbellData['Modes'][i]['PhaseDiff']; + + #print(CampbellData['ModesTable']) + return CampbellData + + + +def extractShortModeDescription(mode): + """ + Look at which modes have max, append these description, perform shortening substitution + The description starts with noMax if no maximum exsits in this mode + The ElastoDyn modes are placed first + """ + descriptions = np.array(mode['DescStates'])[mode['StateHasMaxAtThisMode']] + if len(descriptions) == 0: + noMax=True + descriptions = mode['DescStates'][:5] + else: + noMax=False + sED = [s for s in descriptions if s.startswith('ED')] + sBD = [s for s in descriptions if s.startswith('BD')] + sMisc = [s for s in descriptions if s not in sED+sBD] + sAll = [replaceModeDescription(s) for s in sED+sBD+sMisc] + shortdescr = ' - '.join(sAll) + if noMax: + shortdescr = 'NoMax - ' + shortdescr + return shortdescr + + +def replaceModeDescription(s): + """ Perform substitutions to make the mode description shorter""" + s = s.replace('Blade','Bld') + s = s.replace('blade','Bld') + s = s.replace('First time derivative of','d/dt of') + s = s.replace('fore-aft bending mode DOF, m','FA') + s = s.replace('side-to-side bending mode DOF, m','SS') + s = s.replace('bending-mode DOF of Bld ','') + s = s.replace(' rotational-flexibility DOF, rad','-rot') + s = s.replace('rotational displacement in ','rot') + s = s.replace('translational displacement in ','trans') + s = s.replace('Platform horizontal surge translation DOF','Platform surge') + s = s.replace('Platform vertical heave translation DOF','Platform heave') + s = s.replace('Platform pitch tilt rotation DOF','Platform pitch') + s = s.replace(', rad','') + s = s.replace(', m','') + s = s.replace('finite element node ','N') + s = s.replace('cosine','cos') + s = s.replace('sine','sin') + s = s.replace('flapwise','FLAP') + s = s.replace('edgewise','EDGE') + s = s.replace('collective','coll.') + s = s.replace('rotZ','TORS-ROT') + s = s.replace('transX','FLAP-DISP') + s = s.replace('transY','EDGE-DISP') + s = s.replace('rotX','EDGE') + s = s.replace('rotY','FLAP') + return s + + +def PrettyStateDescriptions(DescStates, ndof2, performedTransformation): + idx=np.array(list(range(0,ndof2))+list(range(ndof2*2+1,len(DescStates)))) + tmpDS = [DescStates[i] for i in idx] + + if performedTransformation: + key_vals=[['BD_1','Blade collective'],['BD_2','Blade cosine'],['BD_3','Blade sine'],['blade 1','blade collective'], ['blade 2','blade cosine'], ['blade 3','Blade sine '], + ['PitchBearing1','Pitch bearing collective '], ['PitchBearing2','Pitch bearing cosine '], ['PitchBearing3','Pitch bearing sine '], + ['at Blade', 'at blade'], + ['of Blade', 'of blade'], + ] + # Replace Substrings from String List + sub = dict(key_vals) + for key, val in sub.items(): + for idx, ele in enumerate(tmpDS): + if key in ele: + tmpDS[idx] = ele.replace(key, val) + + StateDesc=tmpDS + else: + StateDesc = tmpDS + + for i in range(len( StateDesc )): + First = re.split(r'\(',StateDesc[i],2) + Last = re.split(r'\)',StateDesc[i],2) + + if len(First)>0 and len(Last)>0 and len(First[0]) != len(StateDesc[i]) and len( Last[-1] ) != len(StateDesc[i]): + StateDesc[i] = (First[0]).strip() + Last[-1]; + #print(StateDesc[i]) + + return StateDesc + + +def get_tt_inverse(sin_col, cos_col): + + c1 = cos_col[0]; + c2 = cos_col[1]; + c3 = cos_col[2]; + + s1 = sin_col[0]; + s2 = sin_col[1]; + s3 = sin_col[2]; + + + ttv = [ [c2*s3 - s2*c3, c3*s1 - s3*c1, c1*s2 - s1*c2], + [ s2 - s3 , s3 - s1, s1 - s2 ], + [ c3 - c2 , c1 - c3, c2 - c1 ] ] + ttv = ttv/(1.5*np.sqrt(3)); + + return ttv + +def get_new_seq(rot_triplet,ntot): +# rot_triplet is size n x 3 + #print('rot_triplet ', len(rot_triplet)) + rot_triplet=np.array(rot_triplet,dtype=int) + if (rot_triplet.size==0): + nRotTriplets=0 + nb=0 + #return np.array([]),0,0; + else: + nRotTriplets,nb = rot_triplet.shape; + + #print(nRotTriplets,nb,rot_triplet.flatten()) + + if (nb != 3 and nRotTriplets != 0 and ntot!= 0): + print('**ERROR: the number of column vectors in the rotating triplet must equal 3, the num of blades'); + new_seq = np.range(1,ntot) + else: + non_rotating = np.ones(ntot,dtype=int); + #print(non_rotating) + non_rotating[rot_triplet.flatten()] = 0; # if they are rotating, set them false; + a=np.array(np.nonzero(non_rotating)).flatten() + b=(rot_triplet.reshape(nRotTriplets*nb, 1)).flatten() + new_seq = np.concatenate((a,b)); + + #print(new_seq) + return new_seq,nRotTriplets,nb + +def eiganalysis(A, ndof2, ndof1): + # this line has to be the first line for this function + # to get the number of function arguments + nargin=len(locals()) + + mbc={} + m, ns = A.shape; + if(m!=ns): + print('**ERROR: the state-space matrix is not a square matrix.'); + + if nargin == 1: + ndof1 = 0; + ndof2 = ns/2; + + if np.mod(ns,2) != 0: + print('**ERROR: the input matrix is not of even order.'); + elif nargin == 2: + ndof1 = ns - 2*ndof2; + if ndof1 < 0: + print('**ERROR: ndof2 must be no larger than half the dimension of the state-space matrix.'); + else: + if ns != 2*ndof2 + ndof1: + print('**ERROR: the dimension of the state-space matrix must equal 2*ndof2 + ndof1.'); + + ndof = ndof2 + ndof1; + + origEvals, origEigenVects = np.linalg.eig(A); #,'nobalance' + # errorInSolution = norm(A * mbc.EigenVects - mbc.EigenVects* diag(mbc.EigenVals) ) + # these eigenvalues aren't sorted, so we just take the ones with + # positive imaginary parts to get the pairs for modes with damping < 1: + positiveImagEvals = np.argwhere( origEvals.imag > 0.0); + + mbc['Evals'] = origEvals[positiveImagEvals]; + row=np.array(list(range(0,ndof2))+list(range(ndof2*2+1,ns))) + col=positiveImagEvals + + mbc['EigenVects']=origEigenVects[row,col].transpose(); # save q2 and q1, throw away q2_dot + # print('GGGGGG ', row.shape,col.shape) + # with open('AAAA', "a") as f: + # np.savetxt(f,mbc['EigenVects'].imag,fmt='%5.4f') + # f.write('\n') + + EigenVects_save=origEigenVects[:,positiveImagEvals]; # save these for VTK visualization; + + #print('EigenVects_save shape ',EigenVects_save[:,:,0].shape, origEigenVects.shape) + + real_Evals = mbc['Evals'].real; + imag_Evals = mbc['Evals'].imag; + + mbc['NaturalFrequencies'] = np.sqrt( real_Evals**2 + imag_Evals**2 ); + mbc['DampRatios'] = -real_Evals/mbc['NaturalFrequencies'] + mbc['DampedFrequencies'] = imag_Evals; + + mbc['NumRigidBodyModes'] = ndof - len(positiveImagEvals); + + mbc['NaturalFreqs_Hz'] = mbc['NaturalFrequencies']/(2.0*np.pi) + mbc['DampedFreqs_Hz'] = mbc['DampedFrequencies']/(2.0*np.pi); + mbc['MagnitudeModes'] = np.abs(mbc['EigenVects']); + mbc['PhaseModes_deg'] = np.angle(mbc['EigenVects'])*180.0/np.pi; + + # print(real_Evals[0:10]) + # print(imag_Evals[0:10]) + # print(mbc['NaturalFrequencies'][0:10]) + # print(mbc['DampRatios'][0:10]) + # print(mbc['NaturalFreqs_Hz'][0:10]) + # print(mbc['DampedFreqs_Hz'][0:10]) + # print(mbc['MagnitudeModes'].shape) + # print(mbc['PhaseModes_deg'][0,0]) + + # with open('MagModes.txt', "a") as f: + # np.savetxt(f,mbc['MagnitudeModes'],fmt='%g') + # f.write('\n') + + # with open('PhsModes.txt', "a") as f: + # np.savetxt(f,mbc['PhaseModes_deg'],fmt='%g') + # f.write('\n') + + # with open('NFreqs_Hz.txt', "a") as f: + # np.savetxt(f,mbc['NaturalFreqs_Hz'],fmt='%g') + # f.write('\n') + # with open('DampRatios.txt', "a") as f: + # np.savetxt(f,mbc['DampRatios'],fmt='%g') + # f.write('\n') + # with open('DFreqs_Hz.txt', "a") as f: + # np.savetxt(f,mbc['DampedFreqs_Hz'],fmt='%g') + # f.write('\n') + + return mbc,EigenVects_save[:,:,0] + +def fx_mbc3(FileNames, verbose=True, removeTwrAzimuth=False): + """ + Original contribution by: Srinivasa B. Ramisett, ramisettisrinivas@yahoo.com, http://ramisetti.github.io + """ + MBC={} + matData, FAST_linData = gm.get_Mats(FileNames, verbose=verbose, removeTwrAzimuth=removeTwrAzimuth) + + # print('matData[Omega] ', matData['Omega']) + # print('matData[OmegaDot] ', matData['OmegaDot']) + + MBC['DescStates'] = matData['DescStates'] # save this in the MBC type for possible campbell_diagram processing later + MBC['ndof2'] = matData['ndof2'] + MBC['ndof1'] = matData['ndof1'] + MBC['RotSpeed_rpm'] = np.mean(matData['Omega'])*(30/np.pi); #rad/s to rpm + MBC['WindSpeed'] = np.mean(matData['WindSpeed']) # NOTE: might be NaN for old files + + # print('RotSpeed_rpm ',MBC['RotSpeed_rpm']) + # print('ndof1 ', MBC['ndof1']) + # print('ndof2 ', MBC['ndof2']) + # print(matData['RotTripletIndicesStates2']) + + # nb = 3; % number of blades required for MBC3 + # ---------- Multi-Blade-Coordinate transformation ------------------------------------------- + new_seq_dof2, dummy, nb = get_new_seq(matData['RotTripletIndicesStates2'],matData['ndof2']); # these are the first ndof2 states (not "first time derivative" states); these values are used to calculate matrix transformations + new_seq_dof1, dummy, nb2 = get_new_seq(matData['RotTripletIndicesStates1'],matData['ndof1']); # these are the first-order ndof1 states; these values are used to calculate matrix transformations + + # print('new_seq_dof2 ', new_seq_dof2) + # print('new_seq_dof1 ', new_seq_dof1) + # print('dummy ', dummy, ' nb ', nb) + #nb = max(nb,nb2); + #if (nb==0): + # print('*** fx_mbc3: no states were found, so assuming turbine has 3 blades. ***') + # nb = 3 + + + new_seq_states=np.concatenate((new_seq_dof2, new_seq_dof2+matData['ndof2'])) + if new_seq_dof1.size!=0: + new_seq_states=np.concatenate((new_seq_states,new_seq_dof1+matData['NumStates2'])) + + #new_seq_states = [new_seq_dof2; new_seq_dof2+matData['ndof2']; new_seq_dof1+matData['NumStates2']]; # combine the second-order states, including "first time derivatives", with first-order states (assumes ordering of displacements and velocities in state matrices); these values are used to calculate matrix transformations + # second-order NonRotating q2, second-order Rotating q2, + # second-order NonRotating q2_dot, second-order Rotating q2_dot, + # first-order NonRotating q1, first-order Rotating q1 + + + if nb == 3: + MBC['performedTransformation'] = True; + + if matData['n_RotTripletStates2'] + matData['n_RotTripletStates1'] < 1: + print('*** There are no rotating states. MBC transformation, therefore, cannot be performed.'); + # perhaps just warn and perform eigenanalysis anyway? + elif (matData['n_RotTripletStates2']*nb > matData['ndof2']): + print('**ERROR: the rotating second-order dof exceeds the total num of second-order dof'); + elif (matData['n_RotTripletStates1']*nb > matData['ndof1']): + print('**ERROR: the rotating first-order dof exceeds the total num of first-order dof'); + + new_seq_inp,dummy,dummy = get_new_seq(matData['RotTripletIndicesCntrlInpt'],matData['NumInputs']); + new_seq_out,dummy,dummy = get_new_seq(matData['RotTripletIndicesOutput'],matData['NumOutputs']); + + n_FixFrameStates2 = matData['ndof2'] - matData['n_RotTripletStates2']*nb; # fixed-frame second-order dof + n_FixFrameStates1 = matData['ndof1'] - matData['n_RotTripletStates1']*nb; # fixed-frame first-order dof + n_FixFrameInputs = matData['NumInputs'] - matData['n_RotTripletInputs']*nb; # fixed-frame control inputs + n_FixFrameOutputs = matData['NumOutputs'] - matData['n_RotTripletOutputs']*nb; # fixed-frame outputs + + #print(n_FixFrameOutputs,n_FixFrameInputs, n_FixFrameStates1, n_FixFrameStates2) + + if ( len(matData['Omega']) != matData['NAzimStep']): + print('**ERROR: the size of Omega vector must equal matData.NAzimStep, the num of azimuth steps') + if ( len(matData['OmegaDot']) != matData['NAzimStep']): + print('**ERROR: the size of OmegaDot vector must equal matData.NAzimStep, the num of azimuth steps'); + + + nLin = matData['A'].shape[-1] + MBC['A'] = np.zeros(matData['A'].shape) + MBC['B'] = np.zeros((len(new_seq_states),len(new_seq_inp),matData['NAzimStep'])) + if 'C' in matData.keys(): + MBC['C']=np.zeros(matData['C'].shape) + else: + MBC['C']=np.zeros((0,0,nLin)) + if 'D' in matData.keys(): + MBC['D']=np.zeros(matData['D'].shape) + else: + MBC['D']=np.zeros((0,0,nLin)) + + # print('new_seq_inp ',new_seq_inp) + # print('new_seq_out ',new_seq_out) + # print('new_seq_states ', new_seq_states) + + # begin azimuth loop + for iaz in reversed(range(matData['NAzimStep'])): + #(loop backwards so we don't reallocate memory each time [i.e. variables with iaz index aren't getting larger each time]) + + temp=np.arange(nb) + # compute azimuth positions of blades: + az = matData['Azimuth'][iaz]*np.pi/180.0 + 2*np.pi/nb* temp ; # Eq. 1, azimuth in radians + + # get rotor speed squared + OmegaSquared = matData['Omega'][iaz]**2; + + #print(OmegaSquared) + + # compute transformation matrices + cos_col = np.cos(az); + sin_col = np.sin(az); + + tt=np.column_stack((np.ones(3),cos_col,sin_col)) # Eq. 9, t_tilde + ttv = get_tt_inverse(sin_col, cos_col); # inverse of tt (computed analytically in function below) + tt2 = np.column_stack((np.zeros(3), -sin_col, cos_col)) # Eq. 16 a, t_tilde_2 + tt3 = np.column_stack((np.zeros(3), -cos_col, -sin_col)) # Eq. 16 b, t_tilde_3 + + #--- + T1 = np.eye(n_FixFrameStates2); # Eq. 11 for second-order states only + #print('B ',T1, n_FixFrameStates2, matData['n_RotTripletStates2']) + for ii in range(matData['n_RotTripletStates2']): + T1 = scp.block_diag(T1,tt) + + T1v = np.eye(n_FixFrameStates2); # inverse of T1 + for ii in range(matData['n_RotTripletStates2']): + T1v = scp.block_diag(T1v, ttv); + + T2 = np.zeros([n_FixFrameStates2,n_FixFrameStates2]); # Eq. 14 for second-order states only + for ii in range(matData['n_RotTripletStates2']): + T2 = scp.block_diag(T2, tt2); + + #print('T1, T1v, T2 ',T1.shape, T1v.shape, T2.shape) + #--- + T1q = np.eye(n_FixFrameStates1); # Eq. 11 for first-order states (eq. 8 in MBC3 Update document) + for ii in range(matData['n_RotTripletStates1']): + T1q = scp.block_diag(T1q, tt); + + T1qv = np.eye(n_FixFrameStates1); # inverse of T1q + for ii in range(matData['n_RotTripletStates1']): + T1qv = scp.block_diag(T1qv, ttv); + + T2q = np.zeros([n_FixFrameStates1,n_FixFrameStates1]); # Eq. 14 for first-order states (eq. 9 in MBC3 Update document) + for ii in range(matData['n_RotTripletStates1']): + T2q = scp.block_diag(T2q, tt2); + + #print('T1q, T1qv, T2q ',T1q.shape, T1qv.shape, T2q.shape) + # T1qc = np.eye(matData.NumHDInputs); # inverse of T1q + + #--- + T3 = np.zeros([n_FixFrameStates2,n_FixFrameStates2]); # Eq. 15 + for ii in range(matData['n_RotTripletStates2']): + T3 = scp.block_diag(T3, tt3); + + #--- + T1c = np.eye(n_FixFrameInputs); # Eq. 21 + for ii in range(matData['n_RotTripletInputs']): + T1c = scp.block_diag(T1c, tt) + + T1ov = np.eye(n_FixFrameOutputs); # inverse of Tlo (Eq. 23) + for ii in range(matData['n_RotTripletOutputs']): + T1ov = scp.block_diag(T1ov, ttv); + + #print('T3, T1c, T1ov ',T3.shape, T1c.shape, T1ov.shape, matData['A'].shape) + # mbc transformation of first-order matrices + # if ( MBC.EqnsOrder == 1 ) # activate later + + #print('Before ',T1c) + + if 'A' in matData: + # Eq. 29 + L1=np.concatenate((T1, np.zeros([matData['ndof2'],matData['ndof2']]), np.zeros([matData['ndof2'], matData['ndof1']])), axis=1) + L2=np.concatenate((matData['Omega'][iaz]*T2,T1,np.zeros([matData['ndof2'], matData['ndof1']])), axis=1) + L3=np.concatenate((np.zeros([matData['ndof1'], matData['ndof2']]),np.zeros([matData['ndof1'], matData['ndof2']]), T1q), axis=1) + L=np.matmul(matData['A'][new_seq_states[:,None],new_seq_states,iaz],np.concatenate((L1,L2,L3),axis=0)) + + R1=np.concatenate((matData['Omega'][iaz]*T2, np.zeros([matData['ndof2'],matData['ndof2']]), np.zeros([matData['ndof2'], matData['ndof1']])), axis=1) + R2=np.concatenate((OmegaSquared*T3 + matData['OmegaDot'][iaz]*T2, 2*matData['Omega'][iaz]*T2, np.zeros([matData['ndof2'], matData['ndof1']])),axis=1) + R3=np.concatenate((np.zeros([matData['ndof1'], matData['ndof2']]), np.zeros([matData['ndof1'], matData['ndof2']]), matData['Omega'][iaz]*T2q), axis=1) + + R=np.concatenate((R1,R2,R3),axis=0) + + MBC['A'][new_seq_states[:,None],new_seq_states,iaz]=np.matmul(scp.block_diag(T1v, T1v, T1qv),(L-R)) + + # ffname='AAA'+str(iaz)+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['A'][:,:,iaz],fmt='%5.4f') + # f.write('\n') + + if 'B' in matData: + # Eq. 30 + MBC['B'][new_seq_states[:,None],new_seq_inp,iaz]=np.matmul(np.matmul(scp.block_diag(T1v, T1v, T1qv), matData['B'][new_seq_states[:,None],new_seq_inp,iaz]),T1c) + + # ffname='BBB'+str(iaz)+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['B'][:,:,iaz],fmt='%5.4f') + # f.write('\n') + + if 'C' in matData: + # Eq. 31 + + L1=np.concatenate((T1, np.zeros([matData['ndof2'],matData['ndof2']]), np.zeros([matData['ndof2'], matData['ndof1']])),axis=1) + L2=np.concatenate((matData['Omega'][iaz]*T2, T1, np.zeros([matData['ndof2'], matData['ndof1']])), axis=1) + L3=np.concatenate((np.zeros([matData['ndof1'], matData['ndof2']]), np.zeros([matData['ndof1'], matData['ndof2']]), T1q), axis=1) + + MBC['C'][new_seq_out[:,None], new_seq_states,iaz]=np.matmul(np.matmul(T1ov,matData['C'][new_seq_out[:,None],new_seq_states,iaz]),np.concatenate((L1,L2,L3),axis=0)) + + # ffname='CCC'+str(iaz)+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['C'][:,:,iaz],fmt='%5.4f') + # f.write('\n') + + if 'D' in matData: + # Eq. 32 + MBC['D'][new_seq_out[:,None],new_seq_inp,iaz] = np.matmul(np.matmul(T1ov,matData['D'][new_seq_out[:,None],new_seq_inp,iaz]), T1c) + + # ffname='DDD'+str(iaz)+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['D'][:,:,iaz],fmt='%5.4f') + # f.write('\n') + + # end # end of azimuth loop + else: + print(' fx_mbc3 WARNING: Number of blades is ', str(nb), ' not 3. MBC transformation was not performed.') + MBC['performedTransformation'] = False; + + # initialize matrices + if 'A' in matData: + MBC['A'] = matData['A'] # initalize matrix + if 'B' in matData: + MBC['B'] = matData['B'] # initalize matrix + if 'C' in matData: + MBC['C'] = matData['C'] # initalize matrix + if 'D' in matData: + MBC['D'] = matData['D'] # initalize matrix + + # ------------- Eigensolution and Azimuth Averages ------------------------- + if 'A' in MBC: + MBC['AvgA'] = np.mean(MBC['A'],axis=2); # azimuth-average of azimuth-dependent MBC.A matrices + MBC['eigSol'], EigenVects_save = eiganalysis(MBC['AvgA'],matData['ndof2'], matData['ndof1']); + + # ffname='AAA_avg'+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['AvgA'],fmt='%5.4f') + # f.write('\n') + + + # save eigenvectors (doing inverse of MBC3) for VTK visualization in FAST + # if nargout > 3 or nargin > 1: + # [VTK] = GetDataForVTK(MBC, matData, nb, EigenVects_save); + # if nargin > 1 + # WriteDataForVTK(VTK, ModeVizFileName) + + if 'B' in MBC: + MBC['AvgB'] = np.mean(MBC['B'],axis=2); # azimuth-average of azimuth-dependent MBC.B matrices + # ffname='BBB_avg'+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['AvgB'],fmt='%5.4f') + # f.write('\n') + + if 'C' in MBC: + MBC['AvgC'] = np.mean(MBC['C'],axis=2); # azimuth-average of azimuth-dependent MBC.C matrices + # ffname='CCC_avg'+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['AvgC'],fmt='%5.4f') + # f.write('\n') + + if 'D' in MBC: + MBC['AvgD'] = np.mean(MBC['D'],axis=2); # azimuth-average of azimuth-dependent MBC.D matrices + # ffname='DDD_avg'+'.txt' + # with open(ffname, "a") as f: + # np.savetxt(f,MBC['AvgD'],fmt='%5.4f') + # f.write('\n') + + return MBC, matData, FAST_linData + + +def runMBC(FileNames, NLinTimes=None, removeTwrAzimuth=False): + ''' + FileNames are .fst files + ''' + CampbellData={} + HubRad=None;TipRad=None; + BladeLen=None; TowerHt=None + dataFound=False; + for i in range(len(FileNames)): + basename=os.path.splitext(os.path.basename(FileNames[i]))[0] + dirname = os.path.dirname(FileNames[i]) + with open(FileNames[i]) as f: + datafile = f.readlines() + + if dataFound==False: + for line in datafile: + if 'EDFile' in line: + EDFile=line.split()[0].replace('"','') + with open(os.path.join(dirname,EDFile)) as edfile: + for edline in edfile: + if 'HubRad' in edline: + HubRad=float(edline.split()[0]) + elif 'TipRad' in edline: + TipRad=float(edline.split()[0]) + elif 'TowerHt' in edline: + TowerHt=float(edline.split()[0]) + + if((TipRad!=None and HubRad!=None) or TowerHt!=None): + BladeLen=HubRad-TipRad + dataFound=True + if(TowerHt==None or BladeLen==None): + print('TowerHt and BladeLen are not available!'); + sys.exit() + + if NLinTimes==None: + found=False + for line in datafile: + if found==False and 'NLinTimes' in line: + NLinTimes=int(line.split()[0]) + found=True + if NLinTimes<1: + print('NLinTimes should be greater than 0!') + sys.exit() + + linFileNames=[os.path.join(dirname,f'{basename}.{x:d}.lin') for x in range(1,NLinTimes+1)] + + print('Processing ', FileNames[i], ' file!') + MBC_data,getMatData,FAST_linData=fx_mbc3(linFileNames, removeTwrAzimuth=removeTwrAzimuth) + print('Multi-Blade Coordinate transformation completed!'); + print(' '); + CampbellData[i]=campbell_diagram_data(MBC_data,BladeLen,TowerHt) + + return CampbellData + + + +if __name__=='__main__': + pass + + # FileNames=['5MW_Land_ModeShapes-1.fst', '5MW_Land_ModeShapes-2.fst', '5MW_Land_ModeShapes-3.fst', '5MW_Land_ModeShapes-6.fst', '5MW_Land_ModeShapes-7.fst']; + #FileNames=['5MW_Land_BD_Linear-1.fst', '5MW_Land_BD_Linear-2.fst', '5MW_Land_BD_Linear-3.fst', '5MW_Land_BD_Linear-6.fst', '5MW_Land_BD_Linear-7.fst']; + + #FileNames=['5MW_Land_BD_Linear-1.fst']; + + #FileNames=['DLC-1.1/5MW_Land_BD_Linear-7.1.lin', 'DLC-1.1/5MW_Land_BD_Linear-7.2.lin'] + #FileNames=['/Users/sramiset/Desktop/OpenFAST/5MW_Land_BD_Linear/5MW_Land_BD_Linear-1.1.lin','/Users/sramiset/Desktop/OpenFAST/5MW_Land_BD_Linear/5MW_Land_BD_Linear-1.2.lin'] + # CampbellData=runMBC(FileNames) + # print('Preparing campbell diagram data!'); + # # TO DO read x-axis for wind speed or rotor speed from csv file + # #op_csv=pd.read_csv('input.csv', sep=',') + # OP=[2,4,6,8,10] + + # modeID_table,modesDesc=IdentifyModes(CampbellData) + + # #print(modesDesc) + + # nModes=modeID_table.shape[0] + # nRuns=modeID_table.shape[1] + # cols=[item[0] for item in list(modesDesc.values())] + # #cols.append('1P');cols.append('3P');cols.append('6P') + # #cols.append('9P');cols.append('12P') + # frequency=pd.DataFrame(np.nan, index=np.arange(nRuns), columns=cols) + # dampratio=pd.DataFrame(np.nan, index=np.arange(nRuns), columns=cols) + # FreqPlotData=np.zeros((nRuns,nModes)) + # DampPlotData=np.zeros((nRuns,nModes)) + # for i in range(nRuns): + # for modeID in range(len(modesDesc)): # list of modes we want to identify + # idx=int(modeID_table[modeID,i]) + # FreqPlotData[i,modeID]=CampbellData[i]['Modes'][idx]['NaturalFreq_Hz'] + # DampPlotData[i,modeID]=CampbellData[i]['Modes'][idx]['DampingRatio'] + # #print(i,modeID,modesDesc[modeID][0],FreqPlotData[i,modeID]) + # frequency.iloc[i,:]=FreqPlotData[i,:] + # dampratio.iloc[i,:]=DampPlotData[i,:] + + # for i in range(len(OP)): + # # for 15 DOF + # frequency.index.values[i]=OP[i] + # dampratio.index.values[i]=OP[i] + + # # import openpyxl + # # xfile = openpyxl.load_workbook('/Users/sramiset/Desktop/OpenFAST/mbc3_py/CampbellDiagram_Template.xlsx') + + # pCD.plotCampbellData(OP,frequency,dampratio) + + # frequency['1P']=np.nan + # frequency['3P']=np.nan + # frequency['6P']=np.nan + # frequency['9P']=np.nan + # frequency['12P']=np.nan + + # print(nRuns) + # for i in range(nRuns): + # # for 1P,3P,6P,9P,and 12P harmonics + # tmp=OP[i]/60.0 + # print(i,tmp) + # LZ=15 + # frequency.iloc[i,LZ]=tmp + # frequency.iloc[i,LZ+1]=3*tmp + # frequency.iloc[i,LZ+2]=6*tmp + # frequency.iloc[i,LZ+3]=9*tmp + # frequency.iloc[i,LZ+4]=12*tmp + # print(frequency) + # frequency.transpose().to_excel(r'CampbellData.xlsx') diff --git a/ROSCO_toolbox/linear/robust_scheduling.py b/rosco/toolbox/linear/robust_scheduling.py similarity index 98% rename from ROSCO_toolbox/linear/robust_scheduling.py rename to rosco/toolbox/linear/robust_scheduling.py index 70bc418e..a6db2409 100644 --- a/ROSCO_toolbox/linear/robust_scheduling.py +++ b/rosco/toolbox/linear/robust_scheduling.py @@ -10,12 +10,12 @@ import matplotlib.pyplot as plt import pandas as pd import multiprocessing as mp -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.linear.linear_models import LinearTurbineModel -from ROSCO_toolbox.linear.lin_util import add_pcomp, smargin -from ROSCO_toolbox.inputs.validation import load_rosco_yaml -from ROSCO_toolbox.utilities import list_check +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.linear.linear_models import LinearTurbineModel +from rosco.toolbox.linear.lin_util import add_pcomp, smargin +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.utilities import list_check class RobustScheduling(om.ExplicitComponent): @@ -101,6 +101,9 @@ def setup(self): self.add_output('omega_opt', val=0.01, units='rad/s', desc='Maximized controller bandwidth') + def setup_partials(self): + self.declare_partials('*', '*') + def compute(self, inputs, outputs): ''' Computes the stability margin for a given controller bandwidth (omega) diff --git a/ROSCO_toolbox/ofTools/README.md b/rosco/toolbox/ofTools/README.md similarity index 100% rename from ROSCO_toolbox/ofTools/README.md rename to rosco/toolbox/ofTools/README.md diff --git a/ROSCO_toolbox/ofTools/fast_io/__init__.py b/rosco/toolbox/ofTools/__init__.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/__init__.py rename to rosco/toolbox/ofTools/__init__.py diff --git a/ROSCO_toolbox/ofTools/case_gen/CaseGen_General.py b/rosco/toolbox/ofTools/case_gen/CaseGen_General.py similarity index 98% rename from ROSCO_toolbox/ofTools/case_gen/CaseGen_General.py rename to rosco/toolbox/ofTools/case_gen/CaseGen_General.py index 8c46e522..040924fd 100644 --- a/ROSCO_toolbox/ofTools/case_gen/CaseGen_General.py +++ b/rosco/toolbox/ofTools/case_gen/CaseGen_General.py @@ -1,6 +1,6 @@ import os, itertools import numpy as np -from ROSCO_toolbox.ofTools.util.FileTools import save_yaml +from rosco.toolbox.ofTools.util.FileTools import save_yaml def save_case_matrix_direct(case_list, dir_matrix): ### assumes all elements of the list are dict for that case that has the same keys! @@ -54,7 +54,7 @@ def save_case_matrix(matrix_out, change_vars, dir_matrix): text_out.append(row_str) if not os.path.exists(dir_matrix): - os.makedirs(dir_matrix) + os.makedirs(dir_matrix) ofh = open(os.path.join(dir_matrix,'case_matrix.txt'),'w') for row in text_out: ofh.write(row) diff --git a/ROSCO_toolbox/ofTools/case_gen/CaseGen_IEC.py b/rosco/toolbox/ofTools/case_gen/CaseGen_IEC.py similarity index 98% rename from ROSCO_toolbox/ofTools/case_gen/CaseGen_IEC.py rename to rosco/toolbox/ofTools/case_gen/CaseGen_IEC.py index d8cdb4ec..d3552970 100644 --- a/ROSCO_toolbox/ofTools/case_gen/CaseGen_IEC.py +++ b/rosco/toolbox/ofTools/case_gen/CaseGen_IEC.py @@ -2,8 +2,8 @@ import os, sys, copy, itertools import multiprocessing as mp -from ROSCO_toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General, save_case_matrix, save_case_matrix_yaml -from ROSCO_toolbox.ofTools.fast_io.pyIECWind import pyIECWind_extreme, pyIECWind_turb +from rosco.toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General, save_case_matrix, save_case_matrix_yaml +from rosco.toolbox.ofTools.fast_io.pyIECWind import pyIECWind_extreme, pyIECWind_turb try: from mpi4py import MPI @@ -190,7 +190,6 @@ def execute(self, case_inputs={}): case_inputs_i[("ElastoDyn","BlPitch2")] = {'vals':[90.], 'group':0} case_inputs_i[("ElastoDyn","BlPitch3")] = {'vals':[90.], 'group':0} case_inputs_i[("ServoDyn","PCMode")] = {'vals':[0], 'group':0} - case_inputs_i[("AeroDyn15","AFAeroMod")]= {'vals':[1], 'group':0} elif dlc == 6.3: self.dlc_inputs['U'][i] = [V_1] self.dlc_inputs['Yaw'][i] = [-20.,20.] @@ -201,11 +200,9 @@ def execute(self, case_inputs={}): case_inputs_i[("ElastoDyn","BlPitch2")] = {'vals':[90.], 'group':0} case_inputs_i[("ElastoDyn","BlPitch3")] = {'vals':[90.], 'group':0} case_inputs_i[("ServoDyn","PCMode")] = {'vals':[0], 'group':0} - case_inputs_i[("AeroDyn15","AFAeroMod")]= {'vals':[1], 'group':0} else: self.dlc_inputs['Yaw'][i] = [0.] case_inputs_i[("ServoDyn","PCMode")] = {'vals':[5], 'group':0} - case_inputs_i[("AeroDyn15","AFAeroMod")]= {'vals':[2], 'group':0} case_inputs_i[("ElastoDyn","GenDOF")] = {'vals':["True"], 'group':0} diff --git a/ROSCO_toolbox/ofTools/case_gen/CaseLibrary.py b/rosco/toolbox/ofTools/case_gen/CaseLibrary.py similarity index 82% rename from ROSCO_toolbox/ofTools/case_gen/CaseLibrary.py rename to rosco/toolbox/ofTools/case_gen/CaseLibrary.py index e6aef0bf..f006ac21 100644 --- a/ROSCO_toolbox/ofTools/case_gen/CaseLibrary.py +++ b/rosco/toolbox/ofTools/case_gen/CaseLibrary.py @@ -1,20 +1,20 @@ import os, yaml import numpy as np -from ROSCO_toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General -from ROSCO_toolbox.ofTools.case_gen.CaseGen_IEC import CaseGen_IEC -from ROSCO_toolbox.ofTools.case_gen.HH_WindFile import HH_StepFile, HH_WindFile +from rosco.toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General +from rosco.toolbox.ofTools.case_gen.CaseGen_IEC import CaseGen_IEC +from rosco.toolbox.ofTools.case_gen.HH_WindFile import HH_StepFile, HH_WindFile # ROSCO -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox import utilities as ROSCO_utilities +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox import utilities as ROSCO_utilities -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.inputs.validation import load_rosco_yaml # Globals this_dir = os.path.dirname(os.path.abspath(__file__)) -tune_case_dir = os.path.realpath(os.path.join(this_dir,'../../../Tune_Cases')) +tune_case_dir = os.path.realpath(os.path.join(this_dir,'../../../../Examples/Tune_Cases')) def find_max_group(case_inputs): max_group = 0 @@ -34,7 +34,7 @@ def set_channels(): "NcIMUTAxs", "NcIMUTAys", "NcIMUTAzs", "NcIMURAxs", "NcIMURAys", "NcIMURAzs", \ "NacYaw", "Wind1VelX", "Wind1VelY", "Wind1VelZ", "LSSTipMxa","LSSTipMya",\ "LSSTipMza","LSSTipMxs","LSSTipMys","LSSTipMzs","LSShftFys","LSShftFzs", \ - "TipRDxr", "TipRDyr", "TipRDzr","RtVAvgxh","RtAeroFxh"]: + "TipRDxr", "TipRDyr", "TipRDzr","RtVAvgxh","RtAeroFxh", "RtTSR"]: channels[var] = True return channels @@ -106,20 +106,21 @@ def base_op_case(): case_inputs[('ServoDyn', 'YCMode')] = {'vals': [5], 'group': 0} # AeroDyn - case_inputs[("AeroDyn15", "WakeMod")] = {'vals': [1], 'group': 0} - case_inputs[("AeroDyn15", "AFAeroMod")] = {'vals': [2], 'group': 0} - case_inputs[("AeroDyn15", "TwrPotent")] = {'vals': [0], 'group': 0} - case_inputs[("AeroDyn15", "TwrShadow")] = {'vals': ['False'], 'group': 0} - case_inputs[("AeroDyn15", "TwrAero")] = {'vals': ['False'], 'group': 0} - case_inputs[("AeroDyn15", "SkewMod")] = {'vals': [1], 'group': 0} - case_inputs[("AeroDyn15", "TipLoss")] = {'vals': ['True'], 'group': 0} - case_inputs[("AeroDyn15", "HubLoss")] = {'vals': ['True'], 'group': 0} - case_inputs[("AeroDyn15", "TanInd")] = {'vals': ['True'], 'group': 0} - case_inputs[("AeroDyn15", "AIDrag")] = {'vals': ['True'], 'group': 0} - case_inputs[("AeroDyn15", "TIDrag")] = {'vals': ['True'], 'group': 0} - case_inputs[("AeroDyn15", "IndToler")] = {'vals': [1.e-5], 'group': 0} - case_inputs[("AeroDyn15", "MaxIter")] = {'vals': [5000], 'group': 0} - case_inputs[("AeroDyn15", "UseBlCm")] = {'vals': ['True'], 'group': 0} + if False: + case_inputs[("AeroDyn15", "WakeMod")] = {'vals': [1], 'group': 0} + case_inputs[("AeroDyn15", "AFAeroMod")] = {'vals': [2], 'group': 0} + case_inputs[("AeroDyn15", "TwrPotent")] = {'vals': [0], 'group': 0} + case_inputs[("AeroDyn15", "TwrShadow")] = {'vals': ['False'], 'group': 0} + case_inputs[("AeroDyn15", "TwrAero")] = {'vals': ['False'], 'group': 0} + case_inputs[("AeroDyn15", "SkewMod")] = {'vals': [1], 'group': 0} + case_inputs[("AeroDyn15", "TipLoss")] = {'vals': ['True'], 'group': 0} + case_inputs[("AeroDyn15", "HubLoss")] = {'vals': ['True'], 'group': 0} + case_inputs[("AeroDyn15", "TanInd")] = {'vals': ['True'], 'group': 0} + case_inputs[("AeroDyn15", "AIDrag")] = {'vals': ['True'], 'group': 0} + case_inputs[("AeroDyn15", "TIDrag")] = {'vals': ['True'], 'group': 0} + case_inputs[("AeroDyn15", "IndToler")] = {'vals': [1.e-5], 'group': 0} + case_inputs[("AeroDyn15", "MaxIter")] = {'vals': [5000], 'group': 0} + case_inputs[("AeroDyn15", "UseBlCm")] = {'vals': ['True'], 'group': 0} return case_inputs @@ -138,7 +139,10 @@ def power_curve(**wind_case_opts): else: # default # Run conditions U = np.arange(4,14.5,.5).tolist() - U = np.linspace(9.5,12,num=16) + U = np.linspace(3,25,num=16) + + if 'T_max' in wind_case_opts: + T_max = wind_case_opts['T_max'] case_inputs = base_op_case() @@ -155,25 +159,10 @@ def simp_step(**wind_case_opts): # Set up cases for FIW-JIP project # 3.x in controller tuning register - if 'T_Max' in wind_case_opts: - T_max = wind_case_opts['T_Max'] - else: #default - T_max = 300. - - if 'U_start' in wind_case_opts: - U_start = wind_case_opts['U_start'] - else: #default - U_start = [16] - - if 'U_end' in wind_case_opts: - U_end = wind_case_opts['U_end'] - else: #default - U_end = [17] - - if 'T_step' in wind_case_opts: - T_step = wind_case_opts['T_step'] - else: #default - T_step = 150 + TMax = wind_case_opts.get('TMax',300.) + T_step = wind_case_opts.get('TStep',150.) + U_start = wind_case_opts.get('U_start',[16.]) + U_end = wind_case_opts.get('U_end',[17.]) # Wind directory, default is run_dir wind_case_opts['wind_dir'] = wind_case_opts.get('wind_dir',wind_case_opts['run_dir']) @@ -182,7 +171,7 @@ def simp_step(**wind_case_opts): # Make Default step wind object hh_step = HH_StepFile() - hh_step.t_max = T_max + hh_step.t_max = TMax hh_step.t_step = T_step hh_step.wind_directory = wind_case_opts['wind_dir'] @@ -200,7 +189,7 @@ def simp_step(**wind_case_opts): case_inputs = base_op_case() # simulation settings - case_inputs[("Fst","TMax")] = {'vals':[T_max], 'group':0} + case_inputs[("Fst","TMax")] = {'vals':[TMax], 'group':0} # case_inputs[("Fst","DT")] = {'vals':[1/80], 'group':0} # wind inflow @@ -344,21 +333,26 @@ def user_hh(**wind_case_opts): ''' Uniform, hub-height wind file Expected inputs: - TMax TODO: someday make all TMaxs TMax - wind_inputs (list of string wind inputs filenames) + TMax (float or array) of simulation TMax + wind_filenames (list of string wind inputs filenames) ''' - if 'TMax' in wind_case_opts: - TMax = wind_case_opts['TMax'] - else: - TMax = 720 + # Default is 720 for all cases + TMax = wind_case_opts.get('TMax', 720) if 'wind_filenames' not in wind_case_opts: - raise Exception('Define wind_filenames when using turb_bts case generator') + raise Exception('Define wind_filenames when using user_hh case generator') + + # Make into array + if not hasattr(TMax,'__len__'): + TMax = len(wind_case_opts['wind_filenames']) * [TMax] + + + # wind inflow case_inputs = base_op_case() - case_inputs[("Fst","TMax")] = {'vals':[TMax], 'group':0} + case_inputs[("Fst","TMax")] = {'vals':TMax, 'group':1} case_inputs[("InflowWind","WindType")] = {'vals':[2], 'group':0} case_inputs[("InflowWind","Filename_Uni")] = {'vals':wind_case_opts['wind_filenames'], 'group':1} @@ -513,7 +507,7 @@ def sweep_ps_percent(start_group, **control_sweep_opts): turbine_params = inps['turbine_params'] controller_params = inps['controller_params'] - # make default controller, turbine objects for ROSCO_toolbox + # make default controller, turbine objects for rosco.toolbox turbine = ROSCO_turbine.Turbine(turbine_params) turbine.load_from_fast( path_params['FAST_InputFile'],path_params['FAST_directory']) @@ -546,6 +540,64 @@ def test_pitch_offset(start_group, **control_sweep_opts): case_inputs_control[('DISCON_in','PF_Offsets')] = {'vals': [[0,float(np.radians(2)),0]], 'group': start_group} return case_inputs_control +def sweep_yaml_input(start_group, **control_sweep_opts): + ''' + Sweep any single tuning yaml input + + control_sweep_opts: + control_param: name of parameter + param_values: values of parameter (1D array) + + ''' + + required_inputs = ['control_param', 'param_values'] + check_inputs(control_sweep_opts,required_inputs) + + # load default params + control_param_yaml = control_sweep_opts['tuning_yaml'] + inps = load_rosco_yaml(control_param_yaml) + path_params = inps['path_params'] + turbine_params = inps['turbine_params'] + + # make default controller, turbine objects for rosco.toolbox + turbine = ROSCO_turbine.Turbine(turbine_params) + yaml_dir = os.path.dirname(control_param_yaml) + turbine.load_from_fast( path_params['FAST_InputFile'],os.path.join(yaml_dir,path_params['FAST_directory'])) + + + case_inputs = {} + discon_lists = {} + + for param_value in control_sweep_opts['param_values']: + controller_params = control_sweep_opts['controller_params'].copy() + controller_params[control_sweep_opts['control_param']] = param_value + controller = ROSCO_controller.Controller(controller_params) + + # tune default controller + controller.tune_controller(turbine) + + discon_vt = ROSCO_utilities.DISCON_dict(turbine, controller, txt_filename=path_params['rotor_performance_filename']) + + for discon_input in discon_vt: + if discon_input not in discon_lists: # initialize + discon_lists[discon_input] = [] + discon_lists[discon_input].append(discon_vt[discon_input]) + + for discon_input, input in discon_lists.items(): + case_inputs[('DISCON_in',discon_input)] = {'vals': input, 'group': start_group+1} + + case_inputs_control = case_inputs + return case_inputs_control + + +def check_inputs(control_sweep_opts,required_inputs): + for ri in required_inputs: + if ri not in control_sweep_opts: + raise Exception(f'{ri} is required for this control sweep') + + + + @@ -557,7 +609,7 @@ def test_pitch_offset(start_group, **control_sweep_opts): # turbine_params = inps['turbine_params'] # controller_params = inps['controller_params'] -# # make default controller, turbine objects for ROSCO_toolbox +# # make default controller, turbine objects for rosco.toolbox # turbine = ROSCO_turbine.Turbine(turbine_params) # turbine.load_from_fast( path_params['FAST_InputFile'],path_params['FAST_directory']) diff --git a/ROSCO_toolbox/ofTools/case_gen/HH_WindFile.py b/rosco/toolbox/ofTools/case_gen/HH_WindFile.py similarity index 100% rename from ROSCO_toolbox/ofTools/case_gen/HH_WindFile.py rename to rosco/toolbox/ofTools/case_gen/HH_WindFile.py diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/__init__.py b/rosco/toolbox/ofTools/case_gen/__init__.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/__init__.py rename to rosco/toolbox/ofTools/case_gen/__init__.py diff --git a/ROSCO_toolbox/ofTools/case_gen/runFAST_pywrapper.py b/rosco/toolbox/ofTools/case_gen/runFAST_pywrapper.py similarity index 98% rename from ROSCO_toolbox/ofTools/case_gen/runFAST_pywrapper.py rename to rosco/toolbox/ofTools/case_gen/runFAST_pywrapper.py index 886d496b..e4ece622 100644 --- a/ROSCO_toolbox/ofTools/case_gen/runFAST_pywrapper.py +++ b/rosco/toolbox/ofTools/case_gen/runFAST_pywrapper.py @@ -8,9 +8,9 @@ import os, platform import multiprocessing as mp -from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST -from ROSCO_toolbox.ofTools.fast_io.FAST_writer import InputWriter_OpenFAST -from ROSCO_toolbox.ofTools.fast_io.FAST_wrapper import FAST_wrapper +from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST +from rosco.toolbox.ofTools.fast_io.FAST_writer import InputWriter_OpenFAST +from rosco.toolbox.ofTools.fast_io.FAST_wrapper import FAST_wrapper # TODO: import weis and use library, import pCrunch and re-enable post-processing features available here diff --git a/ROSCO_toolbox/ofTools/case_gen/run_FAST.py b/rosco/toolbox/ofTools/case_gen/run_FAST.py similarity index 71% rename from ROSCO_toolbox/ofTools/case_gen/run_FAST.py rename to rosco/toolbox/ofTools/case_gen/run_FAST.py index acff382f..49061f5b 100644 --- a/ROSCO_toolbox/ofTools/case_gen/run_FAST.py +++ b/rosco/toolbox/ofTools/case_gen/run_FAST.py @@ -6,21 +6,42 @@ Otherwise, the directories can be defined as attributes of the run_FAST_ROSCO """ - -from ROSCO_toolbox.ofTools.case_gen.runFAST_pywrapper import runFAST_pywrapper_batch -from ROSCO_toolbox.ofTools.case_gen.CaseGen_IEC import CaseGen_IEC -from ROSCO_toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General -from ROSCO_toolbox.ofTools.case_gen import CaseLibrary as cl -from wisdem.commonse.mpi_tools import MPI -import sys, os, platform +import sys +import os +import platform +#import pickle +import collections.abc import numpy as np -from ROSCO_toolbox import utilities as ROSCO_utilities -from ROSCO_toolbox.inputs.validation import load_rosco_yaml +from rosco import discon_lib_path +from rosco.toolbox import utilities as ROSCO_utilities +from rosco.toolbox.inputs.validation import load_rosco_yaml + +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine + +try: + from weis.aeroelasticse.runFAST_pywrapper import runFAST_pywrapper_batch + in_weis = True +except Exception: + from rosco.toolbox.ofTools.case_gen.runFAST_pywrapper import runFAST_pywrapper_batch + in_weis = False +#from rosco.toolbox.ofTools.case_gen.CaseGen_IEC import CaseGen_IEC +from rosco.toolbox.ofTools.case_gen.CaseGen_General import CaseGen_General +from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +from wisdem.commonse.mpi_tools import MPI -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine +# Globals +this_dir = os.path.dirname(os.path.abspath(__file__)) + +# https://stackoverflow.com/questions/3232943/update-value-of-a-nested-dictionary-of-varying-depth +def update_deep(d, u): + for k, v in u.items(): + if isinstance(v, collections.abc.Mapping): + d[k] = update_deep(d.get(k, {}), v) + else: + d[k] = v + return d -this_dir = os.path.dirname(os.path.abspath(__file__)) class run_FAST_ROSCO(): def __init__(self): @@ -44,15 +65,15 @@ def __init__(self): self.rosco_dir = '' self.save_dir = '' - def run_FAST(self): # handle directories, set defaults if not self.rosco_dir: - self.rosco_dir = os.path.realpath(os.path.join(this_dir,'../../..')) + # Top ROSCO directory of whole repo + self.rosco_dir = os.path.realpath(os.path.join(this_dir,'../../../..')) if not self.tune_case_dir: - self.tune_case_dir = os.path.realpath(os.path.join(self.rosco_dir,'Tune_Cases')) + self.tune_case_dir = os.path.realpath(os.path.join(self.rosco_dir,'Examples/Tune_Cases')) if not self.save_dir: self.save_dir = os.path.join(self.rosco_dir,'outputs') @@ -82,7 +103,7 @@ def run_FAST(self): controller_params = inps['controller_params'] # Update user-defined controller_params - controller_params.update(self.controller_params) + update_deep(controller_params,self.controller_params) # Instantiate turbine, controller, and file processing classes turbine = ROSCO_turbine.Turbine(turbine_params) @@ -92,7 +113,6 @@ def run_FAST(self): tune_yaml_dir = os.path.split(self.tuning_yaml)[0] cp_filename = os.path.join( tune_yaml_dir, - path_params['FAST_directory'], path_params['rotor_performance_filename'] ) turbine.load_from_fast( @@ -116,20 +136,15 @@ def run_FAST(self): case_inputs = self.wind_case_fcn(**self.wind_case_opts) case_inputs.update(control_base_case) - # Set up rosco_dll - if not self.rosco_dll: - if platform.system() == 'Windows': - rosco_dll = os.path.join(self.rosco_dir, 'ROSCO/build/libdiscon.dll') - elif platform.system() == 'Darwin': - rosco_dll = os.path.join(self.rosco_dir, 'ROSCO/build/libdiscon.dylib') - else: - rosco_dll = os.path.join(self.rosco_dir, 'ROSCO/build/libdiscon.so') + if not self.rosco_dll: + self.rosco_dll = discon_lib_path - case_inputs[('ServoDyn','DLL_FileName')] = {'vals': [rosco_dll], 'group': 0} + case_inputs[('ServoDyn','DLL_FileName')] = {'vals': [self.rosco_dll], 'group': 0} # Sweep control parameter if self.control_sweep_fcn: self.control_sweep_opts['tuning_yaml'] = self.tuning_yaml + self.control_sweep_opts['controller_params'] = controller_params case_inputs_control = self.control_sweep_fcn(cl.find_max_group(case_inputs)+1, **self.control_sweep_opts) sweep_name = self.control_sweep_fcn.__name__ case_inputs.update(case_inputs_control) @@ -171,9 +186,10 @@ def run_FAST(self): fastBatch.channels = channels fastBatch.FAST_runDirectory = run_dir fastBatch.case_list = case_list - fastBatch.case_name_list = case_name_list fastBatch.fst_vt = self.fst_vt + fastBatch.case_name_list = case_name_list fastBatch.FAST_exe = self.openfast_exe + fastBatch.use_exe = True if MPI: fastBatch.run_mpi(comm_map_down) @@ -198,7 +214,7 @@ def run_FAST(self): if __name__ == "__main__": # Simulation config - sim_config = 1 + sim_config = 8 r = run_FAST_ROSCO() @@ -208,8 +224,22 @@ def run_FAST(self): # FOCAL single wind speed testing r.tuning_yaml = 'IEA15MW.yaml' r.wind_case_fcn = cl.simp_step - r.sweep_mode = None r.save_dir = '/Users/dzalkind/Tools/ROSCO/outputs' + + elif sim_config == 3: + # IEA-22 fixed bottom + r.tuning_yaml = '/Users/dzalkind/Projects/IEA-22MW/IEA-22-280-RWT/OpenFAST/IEA-22-280-RWT-Monopile/IEA-22-280-RWT-Monopile.yaml' + r.wind_case_fcn = cl.power_curve + r.wind_case_opts = { + 'U': [6,9,12,15], + 'TMax': 100, + } + r.save_dir = '/Users/dzalkind/Projects/IEA-22MW/MonopileControl/outputs/1_const_power' + r.openfast_exe = '/Users/dzalkind/opt/anaconda3/envs/rosco-new/bin/openfast' + # rosco_dll = '/Users/dzalkind/Tools/ROSCO1/ROSCO/build/libdiscon.dylib' + r.case_inputs = {} + # r.case_inputs[('ServoDyn','DLL_FileName')] = {'vals': [rosco_dll], 'group': 0} + r.n_cores = 4 elif sim_config == 6: @@ -240,54 +270,23 @@ def run_FAST(self): elif sim_config == 8: - # RAAW IPC set up - r.tuning_yaml = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/ROSCO/RAAW_rosco_BD.yaml' - r.wind_case_fcn = cl.power_curve - r.wind_case_opts = { - 'U': [16], - } - r.save_dir = '/Users/dzalkind/Tools/ROSCO/outputs/offset_test' - r.control_sweep_fcn = cl.test_pitch_offset - - elif sim_config == 9: - - # RAAW FAD set up - r.tuning_yaml = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/ROSCO/RAAW_rosco_BD.yaml' - r.wind_case_fcn = cl.simp_step - r.wind_case_opts = { - 'U_start': [13], - 'U_end': [15], - 'wind_dir': '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/outputs/FAD_play' - } - r.save_dir = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/outputs/FAD_play' - r.control_sweep_fcn = cl.sweep_fad_gains - r.n_cores = 8 - - elif sim_config == 10: - - # RAAW FAD set up - r.tuning_yaml = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/ROSCO/RAAW_rosco_BD.yaml' - r.wind_case_fcn = cl.turb_bts + # FOCAL rated wind speed tuning + r.tuning_yaml = 'IEA15MW.yaml' + r.wind_case_fcn = cl.simp_step r.wind_case_opts = { - 'TMax': 720, - 'wind_filenames': ['/Users/dzalkind/Tools/WEIS-2/outputs/02_RAAW_IPC/wind/RAAW_NTM_U12.000000_Seed1693606511.0.bts'] + 'U_start': [7], + 'U_end': [9], } - r.save_dir = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/outputs/PS_BD' - r.control_sweep_fcn = cl.sweep_ps_percent - r.n_cores = 8 - - elif sim_config == 11: + r.sweep_mode = None + r.save_dir = '/Users/dzalkind/Tools/ROSCO1/outputs/VS_Mode_2' + r.control_sweep_fcn = cl.sweep_yaml_input + r.control_sweep_opts = { + 'control_param': 'VS_ControlMode', + 'param_values': [2,3] + } + # r.controller_params = {'VS_ControlMode': 3} - # RAAW FAD set up - r.tuning_yaml = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/ROSCO/RAAW_rosco_BD.yaml' - r.wind_case_fcn = cl.user_hh - r.wind_case_opts = { - 'TMax': 1000., - 'wind_filenames': ['/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/Performance/GE_P3_WindStep.asc'] - } - r.save_dir = '/Users/dzalkind/Projects/RAAW/RAAW_OpenFAST/outputs/PS_steps' - r.control_sweep_fcn = cl.sweep_ps_percent - r.n_cores = 4 + r.n_cores = 2 else: raise Exception('This simulation configuration is not supported.') diff --git a/ROSCO_toolbox/ofTools/fast_io/FAST_post.py b/rosco/toolbox/ofTools/fast_io/FAST_post.py similarity index 63% rename from ROSCO_toolbox/ofTools/fast_io/FAST_post.py rename to rosco/toolbox/ofTools/fast_io/FAST_post.py index adee1d5d..51295b88 100644 --- a/ROSCO_toolbox/ofTools/fast_io/FAST_post.py +++ b/rosco/toolbox/ofTools/fast_io/FAST_post.py @@ -1,13 +1,13 @@ from __future__ import print_function -from ROSCO_toolbox.ofTools.fast_io.output_processing import output_processing -import ROSCO_toolbox +from rosco.toolbox.ofTools.fast_io.output_processing import output_processing +import rosco.toolbox def FAST_IO_timeseries(fname): # interface to FAST_IO data load try: - test = ROSCO_toolbox.__file__ + test = rosco.toolbox.__file__ except: - print('WARNING: ROSCO_toolbox required for wisdem.aeroelasticse.FAST_post.FAST_IO_timeseries') + print('WARNING: rosco.toolbox required for wisdem.aeroelasticse.FAST_post.FAST_IO_timeseries') fast_out = output_processing.output_processing() fast_data = fast_out.load_fast_out(fname, verbose=True)[0] diff --git a/ROSCO_toolbox/ofTools/fast_io/FAST_reader.py b/rosco/toolbox/ofTools/fast_io/FAST_reader.py similarity index 94% rename from ROSCO_toolbox/ofTools/fast_io/FAST_reader.py rename to rosco/toolbox/ofTools/fast_io/FAST_reader.py index fe4fc0b5..1859f705 100644 --- a/ROSCO_toolbox/ofTools/fast_io/FAST_reader.py +++ b/rosco/toolbox/ofTools/fast_io/FAST_reader.py @@ -4,9 +4,9 @@ from functools import reduce import operator -from ROSCO_toolbox.ofTools.fast_io.FAST_vars_out import FstOutput -from ROSCO_toolbox.utilities import read_DISCON, load_from_txt -from ROSCO_toolbox import turbine as ROSCO_turbine +from rosco.toolbox.ofTools.fast_io.FAST_vars_out import FstOutput +from rosco.toolbox.utilities import read_DISCON, load_from_txt +from rosco.toolbox import turbine as ROSCO_turbine ROSCO = True def readline_filterComments(f): @@ -209,8 +209,8 @@ def read_MainInput(self): self.fst_vt['Fst']['TrimGain'] = f.readline().split()[0] self.fst_vt['Fst']['Twr_Kdmp'] = f.readline().split()[0] self.fst_vt['Fst']['Bld_Kdmp'] = f.readline().split()[0] - self.fst_vt['Fst']['NLinTimes'] = f.readline().split()[0] - self.fst_vt['Fst']['LinTimes'] = re.findall(r'[^,\s]+', f.readline())[0:2] + self.fst_vt['Fst']['NLinTimes'] = int_read(f.readline().split()[0]) + self.fst_vt['Fst']['LinTimes'] = read_array(f,max(1,self.fst_vt['Fst']['NLinTimes']),int) # read at least 1 self.fst_vt['Fst']['LinInputs'] = f.readline().split()[0] self.fst_vt['Fst']['LinOutputs'] = f.readline().split()[0] self.fst_vt['Fst']['LinOutJac'] = f.readline().split()[0] @@ -409,6 +409,30 @@ def read_ElastoDyn(self, ed_file): self.set_outlist(self.fst_vt['outlist']['ElastoDyn'], channel_list) data = f.readline() + + # ElastoDyn optional outlist + try: + f.readline() + self.fst_vt['ElastoDyn']['BldNd_BladesOut'] = int(f.readline().split()[0]) + self.fst_vt['ElastoDyn']['BldNd_BlOutNd'] = f.readline().split()[0] + + f.readline() + data = f.readline() + while data.split()[0] != 'END': + if data.find('"')>=0: + channels = data.split('"') + opt_channel_list = channels[1].split(',') + else: + row_string = data.split(',') + if len(row_string)==1: + opt_channel_list = row_string[0].split('\n')[0] + else: + opt_channel_list = row_string + self.set_outlist(self.fst_vt['outlist']['ElastoDyn_Nodes'], opt_channel_list) + data = f.readline() + except: + # The optinal outlist does not exist. + None f.close() @@ -601,15 +625,39 @@ def read_BeamDyn(self, bd_file): channel_list = channels[1].split(',') self.set_outlist(self.fst_vt['outlist']['BeamDyn'], channel_list) data = f.readline() + + # BeamDyn optional outlist + try: + f.readline() + # self.fst_vt['BeamDyn']['BldNd_BladesOut'] = int(f.readline().split()[0]) + self.fst_vt['BeamDyn']['BldNd_BlOutNd'] = f.readline().split()[0] + + f.readline() + data = f.readline() + while data.split()[0] != 'END': + if data.find('"')>=0: + channels = data.split('"') + opt_channel_list = channels[1].split(',') + else: + row_string = data.split(',') + if len(row_string)==1: + opt_channel_list = row_string[0].split('\n')[0] + else: + opt_channel_list = row_string + self.set_outlist(self.fst_vt['outlist']['BeamDyn_Nodes'], opt_channel_list) + data = f.readline() + except: + # The optinal outlist does not exist. + None f.close() - self.read_BeamDynBlade() + beamdyn_blade_file = os.path.join(os.path.dirname(bd_file), self.fst_vt['BeamDyn']['BldFile']) + self.read_BeamDynBlade(beamdyn_blade_file) - def read_BeamDynBlade(self): + def read_BeamDynBlade(self, beamdyn_blade_file): # BeamDyn Blade - beamdyn_blade_file = os.path.join(self.FAST_directory, self.fst_vt['BeamDyn']['BldFile']) f = open(beamdyn_blade_file) f.readline() @@ -661,6 +709,7 @@ def read_InflowWind(self): self.fst_vt['InflowWind']['WindType'] = int(f.readline().split()[0]) self.fst_vt['InflowWind']['PropagationDir'] = float_read(f.readline().split()[0]) self.fst_vt['InflowWind']['VFlowAng'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['VelInterpCubic'] = bool_read(f.readline().split()[0]) self.fst_vt['InflowWind']['NWindVel'] = int(f.readline().split()[0]) self.fst_vt['InflowWind']['WindVxiList'] = float_read(f.readline().split()[0]) self.fst_vt['InflowWind']['WindVyiList'] = float_read(f.readline().split()[0]) @@ -717,6 +766,21 @@ def read_InflowWind(self): self.fst_vt['InflowWind']['Z0'] = float_read(f.readline().split()[0]) self.fst_vt['InflowWind']['XOffset'] = float_read(f.readline().split()[0]) + # LIDAR parameters + f.readline() + self.fst_vt['InflowWind']['SensorType'] = int(f.readline().split()[0]) + self.fst_vt['InflowWind']['NumPulseGate'] = int(f.readline().split()[0]) + self.fst_vt['InflowWind']['PulseSpacing'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['NumBeam'] = int(f.readline().split()[0]) + self.fst_vt['InflowWind']['FocalDistanceX'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['FocalDistanceY'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['FocalDistanceZ'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['RotorApexOffsetPos'] = [idx.strip() for idx in f.readline().split('RotorApexOffsetPos')[0].split(',')] + self.fst_vt['InflowWind']['URefLid'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['MeasurementInterval'] = float_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['LidRadialVel'] = bool_read(f.readline().split()[0]) + self.fst_vt['InflowWind']['ConsiderHubMotion'] = int(f.readline().split()[0]) + # Inflow Wind Output Parameters (inflow_out_params) f.readline() self.fst_vt['InflowWind']['SumPrint'] = bool_read(f.readline().split()[0]) @@ -889,6 +953,30 @@ def read_AeroDyn15(self): self.set_outlist(self.fst_vt['outlist']['AeroDyn'], channel_list) data = f.readline() + # AeroDyn15 optional outlist + try: + f.readline() + self.fst_vt['AeroDyn15']['BldNd_BladesOut'] = int(f.readline().split()[0]) + self.fst_vt['AeroDyn15']['BldNd_BlOutNd'] = f.readline().split()[0] + + f.readline() + data = f.readline() + while data.split()[0] != 'END': + if data.find('"')>=0: + channels = data.split('"') + opt_channel_list = channels[1].split(',') + else: + row_string = data.split(',') + if len(row_string)==1: + opt_channel_list = row_string[0].split('\n')[0] + else: + opt_channel_list = row_string + self.set_outlist(self.fst_vt['outlist']['AeroDyn_Nodes'], opt_channel_list) + data = f.readline() + except: + # The optinal outlist does not exist. + None + f.close() self.read_AeroDyn15Blade() @@ -1082,11 +1170,11 @@ def read_AeroDyn15OLAF(self, olaf_filename): f.readline() self.fst_vt['AeroDyn15']['OLAF']['VelocityMethod'] = int_read(f.readline().split()[0]) self.fst_vt['AeroDyn15']['OLAF']['TreeBranchFactor']= float_read(f.readline().split()[0]) - self.fst_vt['AeroDyn15']['OLAF']['PartPerSegment'] = int(f.readline().split()[0]) + self.fst_vt['AeroDyn15']['OLAF']['PartPerSegment'] = int_read(f.readline().split()[0]) f.readline() f.readline() - self.fst_vt['AeroDyn15']['OLAF']['WrVTk'] = int(f.readline().split()[0]) - self.fst_vt['AeroDyn15']['OLAF']['nVTKBlades'] = int(f.readline().split()[0]) + self.fst_vt['AeroDyn15']['OLAF']['WrVTk'] = int_read(f.readline().split()[0]) + self.fst_vt['AeroDyn15']['OLAF']['nVTKBlades'] = int_read(f.readline().split()[0]) self.fst_vt['AeroDyn15']['OLAF']['VTKCoord'] = int_read(f.readline().split()[0]) self.fst_vt['AeroDyn15']['OLAF']['VTK_fps'] = float_read(f.readline().split()[0]) self.fst_vt['AeroDyn15']['OLAF']['nGridOut'] = int_read(f.readline().split()[0]) @@ -1555,7 +1643,7 @@ def read_StC(self,filename): return StC_vt def read_DISCON_in(self): - # Read the Bladed style Interface controller input file, intended for ROSCO https://github.com/NREL/ROSCO_toolbox + # Read the Bladed style Interface controller input file, intended for ROSCO https://github.com/NREL/rosco.toolbox discon_in_file = os.path.normpath(os.path.join(self.FAST_directory, self.fst_vt['ServoDyn']['DLL_InFile'])) @@ -1891,7 +1979,10 @@ def read_HydroDyn(self, hd_file): self.fst_vt['HydroDyn']['FillNumM'][i] = int(ln[0]) self.fst_vt['HydroDyn']['FillMList'][i] = [int(j) for j in ln[1:-2]] self.fst_vt['HydroDyn']['FillFSLoc'][i] = float(ln[-2]) - self.fst_vt['HydroDyn']['FillDens'][i] = float(ln[-1]) + if ln[-1] == 'DEFAULT': + self.fst_vt['HydroDyn']['FillDens'][i] = 'DEFAULT' + else: + self.fst_vt['HydroDyn']['FillDens'][i] = float(ln[-1]) #MARINE GROWTH f.readline() @@ -1973,7 +2064,7 @@ def read_SubDyn(self, sd_file): self.fst_vt['SubDyn']['NDiv'] = int_read(f.readline().split()[0]) self.fst_vt['SubDyn']['CBMod'] = bool_read(f.readline().split()[0]) self.fst_vt['SubDyn']['Nmodes'] = int_read(f.readline().split()[0]) - self.fst_vt['SubDyn']['JDampings'] = int_read(f.readline().split()[0]) + self.fst_vt['SubDyn']['JDampings'] = float_read(f.readline().split()[0]) self.fst_vt['SubDyn']['GuyanDampMod'] = int_read(f.readline().split()[0]) self.fst_vt['SubDyn']['RayleighDamp'] = [float(m.replace(',','')) for m in f.readline().split()[:2]] self.fst_vt['SubDyn']['GuyanDampSize'] = int_read(f.readline().split()[0]) @@ -2025,7 +2116,10 @@ def read_SubDyn(self, sd_file): self.fst_vt['SubDyn']['RctRDXss'][i] = int(ln[4]) self.fst_vt['SubDyn']['RctRDYss'][i] = int(ln[5]) self.fst_vt['SubDyn']['RctRDZss'][i] = int(ln[6]) - self.fst_vt['SubDyn']['Rct_SoilFile'][i] = ln[7] + if len(ln) == 8: + self.fst_vt['SubDyn']['Rct_SoilFile'][i] = ln[7] + else: + self.fst_vt['SubDyn']['Rct_SoilFile'][i] = 'None' f.readline() # INTERFACE JOINTS self.fst_vt['SubDyn']['NInterf'] = int_read(f.readline().split()[0]) diff --git a/ROSCO_toolbox/ofTools/fast_io/FAST_vars.py b/rosco/toolbox/ofTools/fast_io/FAST_vars.py similarity index 96% rename from ROSCO_toolbox/ofTools/fast_io/FAST_vars.py rename to rosco/toolbox/ofTools/fast_io/FAST_vars.py index a1b605df..8e5e89d1 100644 --- a/ROSCO_toolbox/ofTools/fast_io/FAST_vars.py +++ b/rosco/toolbox/ofTools/fast_io/FAST_vars.py @@ -1,6 +1,6 @@ from numpy import zeros, array import numpy as np -from ROSCO_toolbox.ofTools.fast_io.FAST_vars_out import FstOutput, Fst7Output +from rosco.toolbox.ofTools.fast_io.FAST_vars_out import FstOutput, Fst7Output # This variable tree contains all parameters required to create a FAST model # for FAST versions 7 and 8. @@ -619,7 +619,7 @@ ServoDyn['OutFmt'] = '' ServoDyn['TStart'] = 0.0 -# Bladed style Interface controller input file, intended for ROSCO https://github.com/NREL/ROSCO_toolbox +# Bladed style Interface controller input file, intended for ROSCO https://github.com/NREL/rosco.toolbox DISCON_in = {} DISCON_in['LoggingLevel'] = 0 DISCON_in['F_LPFType'] = 0 diff --git a/ROSCO_toolbox/ofTools/fast_io/FAST_vars_out.py b/rosco/toolbox/ofTools/fast_io/FAST_vars_out.py similarity index 83% rename from ROSCO_toolbox/ofTools/fast_io/FAST_vars_out.py rename to rosco/toolbox/ofTools/fast_io/FAST_vars_out.py index 358af810..91d1b4b3 100644 --- a/ROSCO_toolbox/ofTools/fast_io/FAST_vars_out.py +++ b/rosco/toolbox/ofTools/fast_io/FAST_vars_out.py @@ -414,6 +414,12 @@ ElastoDyn['YawAccel'] = False # (deg/s^2); Nacelle yaw angular acceleration; About the zn- and zp-axes # Tower-Top / Yaw Bearing Motions +ElastoDyn['TwrTpTDxi'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position) including all platform motions; Directed along the xi-axis +ElastoDyn['YawBrTDxi'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position) including all platform motions; Directed along the xi-axis +ElastoDyn['TwrTpTDyi'] = False # (m); Tower-top / yaw bearing side-to-side (translational) deflection (relative to the undeflected position) including all platform motions; Directed along the yi-axis +ElastoDyn['YawBrTDyi'] = False # (m); Tower-top / yaw bearing side-to-side (translational) deflection (relative to the undeflected position) including all platform motions; Directed along the yi-axis +ElastoDyn['TwrTpTDzi'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position) including all platform motions; Directed along the zi-axis +ElastoDyn['YawBrTDzi'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position) including all platform motions; Directed along the zi-axis ElastoDyn['YawBrTDxp'] = False # (m); Tower-top / yaw bearing fore-aft (translational) deflection (relative to the undeflected position); Directed along the xp-axis ElastoDyn['YawBrTDyp'] = False # (m); Tower-top / yaw bearing side-to-side (translational) deflection (relative to the undeflected position); Directed along the yp-axis ElastoDyn['YawBrTDzp'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zp-axis @@ -423,6 +429,9 @@ ElastoDyn['TTDspSS'] = False # (m); Tower-top / yaw bearing side-to-side (translation) deflection (relative to the undeflected position); Directed along the yt-axis ElastoDyn['YawBrTDzt'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zt-axis ElastoDyn['TTDspAx'] = False # (m); Tower-top / yaw bearing axial (translational) deflection (relative to the undeflected position); Directed along the zt-axis +ElastoDyn['YawBrTVxp'] = False # (m/s); Tower-top / yaw bearing fore-aft (translational) velocity (absolute); Directed along the xp-axis +ElastoDyn['YawBrTVyp'] = False # (m/s); Tower-top / yaw bearing side-to-side (translational) velocity (absolute); Directed along the yp-axis +ElastoDyn['YawBrTVzp'] = False # (m/s); Tower-top / yaw bearing axial (translational) velocity (absolute); Directed along the zp-axis ElastoDyn['YawBrTAxp'] = False # (m/s^2); Tower-top / yaw bearing fore-aft (translational) acceleration (absolute); Directed along the xp-axis ElastoDyn['YawBrTAyp'] = False # (m/s^2); Tower-top / yaw bearing side-to-side (translational) acceleration (absolute); Directed along the yp-axis ElastoDyn['YawBrTAzp'] = False # (m/s^2); Tower-top / yaw bearing axial (translational) acceleration (absolute); Directed along the zp-axis @@ -1426,17 +1435,519 @@ ServoDyn['YawMomCom'] = False # (kN m); Nacelle yaw moment command; About the zn- and zp-axes ServoDyn['YawMom'] = False # (kN m); Nacelle yaw moment command; About the zn- and zp-axes -# Nacelle Tuned Mass Damper (TMD) -ServoDyn['NTMD_XQ'] = False # (m); Nacelle X TMD position (displacement); Relative to rest position -ServoDyn['NTMD_XQD'] = False # (m/s); Nacelle X TMD velocity; Relative to nacelle -ServoDyn['NTMD_YQ'] = False # (m); Nacelle Y TMD position (displacement); Relative to rest position -ServoDyn['NTMD_YQD'] = False # (m/s); Nacelle Y TMD velocity; Relative to nacelle +# Nacelle Structural Control (StC) +ServoDyn['NStC1_XQ'] = False # (m); Nacelle StC #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC1_XQD'] = False # (m/s); Nacelle StC #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC1_YQ'] = False # (m); Nacelle StC #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC1_YQD'] = False # (m/s); Nacelle StC #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC1_ZQ'] = False # (m); Nacelle StC #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC1_ZQD'] = False # (m/s); Nacelle StC #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC1_Fxi'] = False # (kN); Nacelle StC #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['NStC1_Fyi'] = False # (kN); Nacelle StC #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['NStC1_Fzi'] = False # (kN); Nacelle StC #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['NStC1_Mxi'] = False # (kN-m); Nacelle StC #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['NStC1_Myi'] = False # (kN-m); Nacelle StC #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['NStC1_Mzi'] = False # (kN-m); Nacelle StC #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['NStC1_Fxl'] = False # (kN); Nacelle StC #1 -- X resulting force; Local StC coordinates +ServoDyn['NStC1_Fyl'] = False # (kN); Nacelle StC #1 -- Y resulting force; Local StC coordinates +ServoDyn['NStC1_Fzl'] = False # (kN); Nacelle StC #1 -- Z resulting force; Local StC coordinates +ServoDyn['NStC1_Mxl'] = False # (kN-m); Nacelle StC #1 -- X resulting moment; Local StC coordinates +ServoDyn['NStC1_Myl'] = False # (kN-m); Nacelle StC #1 -- Y resulting moment; Local StC coordinates +ServoDyn['NStC1_Mzl'] = False # (kN-m); Nacelle StC #1 -- Z resulting moment; Local StC coordinates +ServoDyn['NStC2_XQ'] = False # (m); Nacelle StC #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC2_XQD'] = False # (m/s); Nacelle StC #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC2_YQ'] = False # (m); Nacelle StC #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC2_YQD'] = False # (m/s); Nacelle StC #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC2_ZQ'] = False # (m); Nacelle StC #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC2_ZQD'] = False # (m/s); Nacelle StC #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC2_Fxi'] = False # (kN); Nacelle StC #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['NStC2_Fyi'] = False # (kN); Nacelle StC #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['NStC2_Fzi'] = False # (kN); Nacelle StC #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['NStC2_Mxi'] = False # (kN-m); Nacelle StC #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['NStC2_Myi'] = False # (kN-m); Nacelle StC #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['NStC2_Mzi'] = False # (kN-m); Nacelle StC #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['NStC2_Fxl'] = False # (kN); Nacelle StC #2 -- X resulting force; Local StC coordinates +ServoDyn['NStC2_Fyl'] = False # (kN); Nacelle StC #2 -- Y resulting force; Local StC coordinates +ServoDyn['NStC2_Fzl'] = False # (kN); Nacelle StC #2 -- Z resulting force; Local StC coordinates +ServoDyn['NStC2_Mxl'] = False # (kN-m); Nacelle StC #2 -- X resulting moment; Local StC coordinates +ServoDyn['NStC2_Myl'] = False # (kN-m); Nacelle StC #2 -- Y resulting moment; Local StC coordinates +ServoDyn['NStC2_Mzl'] = False # (kN-m); Nacelle StC #2 -- Z resulting moment; Local StC coordinates +ServoDyn['NStC3_XQ'] = False # (m); Nacelle StC #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC3_XQD'] = False # (m/s); Nacelle StC #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC3_YQ'] = False # (m); Nacelle StC #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC3_YQD'] = False # (m/s); Nacelle StC #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC3_ZQ'] = False # (m); Nacelle StC #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC3_ZQD'] = False # (m/s); Nacelle StC #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC3_Fxi'] = False # (kN); Nacelle StC #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['NStC3_Fyi'] = False # (kN); Nacelle StC #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['NStC3_Fzi'] = False # (kN); Nacelle StC #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['NStC3_Mxi'] = False # (kN-m); Nacelle StC #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['NStC3_Myi'] = False # (kN-m); Nacelle StC #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['NStC3_Mzi'] = False # (kN-m); Nacelle StC #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['NStC3_Fxl'] = False # (kN); Nacelle StC #3 -- X resulting force; Local StC coordinates +ServoDyn['NStC3_Fyl'] = False # (kN); Nacelle StC #3 -- Y resulting force; Local StC coordinates +ServoDyn['NStC3_Fzl'] = False # (kN); Nacelle StC #3 -- Z resulting force; Local StC coordinates +ServoDyn['NStC3_Mxl'] = False # (kN-m); Nacelle StC #3 -- X resulting moment; Local StC coordinates +ServoDyn['NStC3_Myl'] = False # (kN-m); Nacelle StC #3 -- Y resulting moment; Local StC coordinates +ServoDyn['NStC3_Mzl'] = False # (kN-m); Nacelle StC #3 -- Z resulting moment; Local StC coordinates +ServoDyn['NStC4_XQ'] = False # (m); Nacelle StC #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC4_XQD'] = False # (m/s); Nacelle StC #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC4_YQ'] = False # (m); Nacelle StC #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC4_YQD'] = False # (m/s); Nacelle StC #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC4_ZQ'] = False # (m); Nacelle StC #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['NStC4_ZQD'] = False # (m/s); Nacelle StC #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['NStC4_Fxi'] = False # (kN); Nacelle StC #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['NStC4_Fyi'] = False # (kN); Nacelle StC #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['NStC4_Fzi'] = False # (kN); Nacelle StC #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['NStC4_Mxi'] = False # (kN-m); Nacelle StC #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['NStC4_Myi'] = False # (kN-m); Nacelle StC #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['NStC4_Mzi'] = False # (kN-m); Nacelle StC #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['NStC4_Fxl'] = False # (kN); Nacelle StC #4 -- X resulting force; Local StC coordinates +ServoDyn['NStC4_Fyl'] = False # (kN); Nacelle StC #4 -- Y resulting force; Local StC coordinates +ServoDyn['NStC4_Fzl'] = False # (kN); Nacelle StC #4 -- Z resulting force; Local StC coordinates +ServoDyn['NStC4_Mxl'] = False # (kN-m); Nacelle StC #4 -- X resulting moment; Local StC coordinates +ServoDyn['NStC4_Myl'] = False # (kN-m); Nacelle StC #4 -- Y resulting moment; Local StC coordinates +ServoDyn['NStC4_Mzl'] = False # (kN-m); Nacelle StC #4 -- Z resulting moment; Local StC coordinates + +# Tower Structural Control (StC) +ServoDyn['TStC1_XQ'] = False # (m); Tower StC #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC1_XQD'] = False # (m/s); Tower StC #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC1_YQ'] = False # (m); Tower StC #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC1_YQD'] = False # (m/s); Tower StC #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC1_ZQ'] = False # (m); Tower StC #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC1_ZQD'] = False # (m/s); Tower StC #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC1_Fxi'] = False # (kN); Tower StC #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['TStC1_Fyi'] = False # (kN); Tower StC #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['TStC1_Fzi'] = False # (kN); Tower StC #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['TStC1_Mxi'] = False # (kN-m); Tower StC #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['TStC1_Myi'] = False # (kN-m); Tower StC #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['TStC1_Mzi'] = False # (kN-m); Tower StC #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['TStC1_Fxl'] = False # (kN); Tower StC #1 -- X resulting force; Local StC coordinates +ServoDyn['TStC1_Fyl'] = False # (kN); Tower StC #1 -- Y resulting force; Local StC coordinates +ServoDyn['TStC1_Fzl'] = False # (kN); Tower StC #1 -- Z resulting force; Local StC coordinates +ServoDyn['TStC1_Mxl'] = False # (kN-m); Tower StC #1 -- X resulting moment; Local StC coordinates +ServoDyn['TStC1_Myl'] = False # (kN-m); Tower StC #1 -- Y resulting moment; Local StC coordinates +ServoDyn['TStC1_Mzl'] = False # (kN-m); Tower StC #1 -- Z resulting moment; Local StC coordinates +ServoDyn['TStC2_XQ'] = False # (m); Tower StC #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC2_XQD'] = False # (m/s); Tower StC #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC2_YQ'] = False # (m); Tower StC #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC2_YQD'] = False # (m/s); Tower StC #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC2_ZQ'] = False # (m); Tower StC #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC2_ZQD'] = False # (m/s); Tower StC #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC2_Fxi'] = False # (kN); Tower StC #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['TStC2_Fyi'] = False # (kN); Tower StC #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['TStC2_Fzi'] = False # (kN); Tower StC #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['TStC2_Mxi'] = False # (kN-m); Tower StC #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['TStC2_Myi'] = False # (kN-m); Tower StC #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['TStC2_Mzi'] = False # (kN-m); Tower StC #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['TStC2_Fxl'] = False # (kN); Tower StC #2 -- X resulting force; Local StC coordinates +ServoDyn['TStC2_Fyl'] = False # (kN); Tower StC #2 -- Y resulting force; Local StC coordinates +ServoDyn['TStC2_Fzl'] = False # (kN); Tower StC #2 -- Z resulting force; Local StC coordinates +ServoDyn['TStC2_Mxl'] = False # (kN-m); Tower StC #2 -- X resulting moment; Local StC coordinates +ServoDyn['TStC2_Myl'] = False # (kN-m); Tower StC #2 -- Y resulting moment; Local StC coordinates +ServoDyn['TStC2_Mzl'] = False # (kN-m); Tower StC #2 -- Z resulting moment; Local StC coordinates +ServoDyn['TStC3_XQ'] = False # (m); Tower StC #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC3_XQD'] = False # (m/s); Tower StC #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC3_YQ'] = False # (m); Tower StC #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC3_YQD'] = False # (m/s); Tower StC #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC3_ZQ'] = False # (m); Tower StC #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC3_ZQD'] = False # (m/s); Tower StC #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC3_Fxi'] = False # (kN); Tower StC #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['TStC3_Fyi'] = False # (kN); Tower StC #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['TStC3_Fzi'] = False # (kN); Tower StC #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['TStC3_Mxi'] = False # (kN-m); Tower StC #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['TStC3_Myi'] = False # (kN-m); Tower StC #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['TStC3_Mzi'] = False # (kN-m); Tower StC #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['TStC3_Fxl'] = False # (kN); Tower StC #3 -- X resulting force; Local StC coordinates +ServoDyn['TStC3_Fyl'] = False # (kN); Tower StC #3 -- Y resulting force; Local StC coordinates +ServoDyn['TStC3_Fzl'] = False # (kN); Tower StC #3 -- Z resulting force; Local StC coordinates +ServoDyn['TStC3_Mxl'] = False # (kN-m); Tower StC #3 -- X resulting moment; Local StC coordinates +ServoDyn['TStC3_Myl'] = False # (kN-m); Tower StC #3 -- Y resulting moment; Local StC coordinates +ServoDyn['TStC3_Mzl'] = False # (kN-m); Tower StC #3 -- Z resulting moment; Local StC coordinates +ServoDyn['TStC4_XQ'] = False # (m); Tower StC #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC4_XQD'] = False # (m/s); Tower StC #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC4_YQ'] = False # (m); Tower StC #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC4_YQD'] = False # (m/s); Tower StC #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC4_ZQ'] = False # (m); Tower StC #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['TStC4_ZQD'] = False # (m/s); Tower StC #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['TStC4_Fxi'] = False # (kN); Tower StC #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['TStC4_Fyi'] = False # (kN); Tower StC #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['TStC4_Fzi'] = False # (kN); Tower StC #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['TStC4_Mxi'] = False # (kN-m); Tower StC #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['TStC4_Myi'] = False # (kN-m); Tower StC #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['TStC4_Mzi'] = False # (kN-m); Tower StC #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['TStC4_Fxl'] = False # (kN); Tower StC #4 -- X resulting force; Local StC coordinates +ServoDyn['TStC4_Fyl'] = False # (kN); Tower StC #4 -- Y resulting force; Local StC coordinates +ServoDyn['TStC4_Fzl'] = False # (kN); Tower StC #4 -- Z resulting force; Local StC coordinates +ServoDyn['TStC4_Mxl'] = False # (kN-m); Tower StC #4 -- X resulting moment; Local StC coordinates +ServoDyn['TStC4_Myl'] = False # (kN-m); Tower StC #4 -- Y resulting moment; Local StC coordinates +ServoDyn['TStC4_Mzl'] = False # (kN-m); Tower StC #4 -- Z resulting moment; Local StC coordinates + +# Blade Structural Control (StC) +ServoDyn['BStC1_B1_XQ'] = False # (m); Blade StC #1 Blade #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B1_XQD'] = False # (m/s); Blade StC #1 Blade #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B1_YQ'] = False # (m); Blade StC #1 Blade #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B1_YQD'] = False # (m/s); Blade StC #1 Blade #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B1_ZQ'] = False # (m); Blade StC #1 Blade #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B1_ZQD'] = False # (m/s); Blade StC #1 Blade #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B1_Fxi'] = False # (kN); Blade StC #1 Blade #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B1_Fyi'] = False # (kN); Blade StC #1 Blade #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B1_Fzi'] = False # (kN); Blade StC #1 Blade #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B1_Mxi'] = False # (kN-m); Blade StC #1 Blade #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B1_Myi'] = False # (kN-m); Blade StC #1 Blade #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B1_Mzi'] = False # (kN-m); Blade StC #1 Blade #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B1_Fxl'] = False # (kN); Blade StC #1 Blade #1 -- X resulting force; Local StC coordinates +ServoDyn['BStC1_B1_Fyl'] = False # (kN); Blade StC #1 Blade #1 -- Y resulting force; Local StC coordinates +ServoDyn['BStC1_B1_Fzl'] = False # (kN); Blade StC #1 Blade #1 -- Z resulting force; Local StC coordinates +ServoDyn['BStC1_B1_Mxl'] = False # (kN-m); Blade StC #1 Blade #1 -- X resulting moment; Local StC coordinates +ServoDyn['BStC1_B1_Myl'] = False # (kN-m); Blade StC #1 Blade #1 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC1_B1_Mzl'] = False # (kN-m); Blade StC #1 Blade #1 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC2_B1_XQ'] = False # (m); Blade StC #2 Blade #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B1_XQD'] = False # (m/s); Blade StC #2 Blade #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B1_YQ'] = False # (m); Blade StC #2 Blade #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B1_YQD'] = False # (m/s); Blade StC #2 Blade #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B1_ZQ'] = False # (m); Blade StC #2 Blade #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B1_ZQD'] = False # (m/s); Blade StC #2 Blade #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B1_Fxi'] = False # (kN); Blade StC #2 Blade #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B1_Fyi'] = False # (kN); Blade StC #2 Blade #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B1_Fzi'] = False # (kN); Blade StC #2 Blade #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B1_Mxi'] = False # (kN-m); Blade StC #2 Blade #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B1_Myi'] = False # (kN-m); Blade StC #2 Blade #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B1_Mzi'] = False # (kN-m); Blade StC #2 Blade #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B1_Fxl'] = False # (kN); Blade StC #2 Blade #1 -- X resulting force; Local StC coordinates +ServoDyn['BStC2_B1_Fyl'] = False # (kN); Blade StC #2 Blade #1 -- Y resulting force; Local StC coordinates +ServoDyn['BStC2_B1_Fzl'] = False # (kN); Blade StC #2 Blade #1 -- Z resulting force; Local StC coordinates +ServoDyn['BStC2_B1_Mxl'] = False # (kN-m); Blade StC #2 Blade #1 -- X resulting moment; Local StC coordinates +ServoDyn['BStC2_B1_Myl'] = False # (kN-m); Blade StC #2 Blade #1 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC2_B1_Mzl'] = False # (kN-m); Blade StC #2 Blade #1 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC3_B1_XQ'] = False # (m); Blade StC #3 Blade #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B1_XQD'] = False # (m/s); Blade StC #3 Blade #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B1_YQ'] = False # (m); Blade StC #3 Blade #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B1_YQD'] = False # (m/s); Blade StC #3 Blade #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B1_ZQ'] = False # (m); Blade StC #3 Blade #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B1_ZQD'] = False # (m/s); Blade StC #3 Blade #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B1_Fxi'] = False # (kN); Blade StC #3 Blade #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B1_Fyi'] = False # (kN); Blade StC #3 Blade #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B1_Fzi'] = False # (kN); Blade StC #3 Blade #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B1_Mxi'] = False # (kN-m); Blade StC #3 Blade #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B1_Myi'] = False # (kN-m); Blade StC #3 Blade #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B1_Mzi'] = False # (kN-m); Blade StC #3 Blade #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B1_Fxl'] = False # (kN); Blade StC #3 Blade #1 -- X resulting force; Local StC coordinates +ServoDyn['BStC3_B1_Fyl'] = False # (kN); Blade StC #3 Blade #1 -- Y resulting force; Local StC coordinates +ServoDyn['BStC3_B1_Fzl'] = False # (kN); Blade StC #3 Blade #1 -- Z resulting force; Local StC coordinates +ServoDyn['BStC3_B1_Mxl'] = False # (kN-m); Blade StC #3 Blade #1 -- X resulting moment; Local StC coordinates +ServoDyn['BStC3_B1_Myl'] = False # (kN-m); Blade StC #3 Blade #1 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC3_B1_Mzl'] = False # (kN-m); Blade StC #3 Blade #1 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC4_B1_XQ'] = False # (m); Blade StC #4 Blade #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B1_XQD'] = False # (m/s); Blade StC #4 Blade #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B1_YQ'] = False # (m); Blade StC #4 Blade #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B1_YQD'] = False # (m/s); Blade StC #4 Blade #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B1_ZQ'] = False # (m); Blade StC #4 Blade #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B1_ZQD'] = False # (m/s); Blade StC #4 Blade #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B1_Fxi'] = False # (kN); Blade StC #4 Blade #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B1_Fyi'] = False # (kN); Blade StC #4 Blade #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B1_Fzi'] = False # (kN); Blade StC #4 Blade #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B1_Mxi'] = False # (kN-m); Blade StC #4 Blade #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B1_Myi'] = False # (kN-m); Blade StC #4 Blade #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B1_Mzi'] = False # (kN-m); Blade StC #4 Blade #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B1_Fxl'] = False # (kN); Blade StC #4 Blade #1 -- X resulting force; Local StC coordinates +ServoDyn['BStC4_B1_Fyl'] = False # (kN); Blade StC #4 Blade #1 -- Y resulting force; Local StC coordinates +ServoDyn['BStC4_B1_Fzl'] = False # (kN); Blade StC #4 Blade #1 -- Z resulting force; Local StC coordinates +ServoDyn['BStC4_B1_Mxl'] = False # (kN-m); Blade StC #4 Blade #1 -- X resulting moment; Local StC coordinates +ServoDyn['BStC4_B1_Myl'] = False # (kN-m); Blade StC #4 Blade #1 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC4_B1_Mzl'] = False # (kN-m); Blade StC #4 Blade #1 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC1_B2_XQ'] = False # (m); Blade StC #1 Blade #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B2_XQD'] = False # (m/s); Blade StC #1 Blade #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B2_YQ'] = False # (m); Blade StC #1 Blade #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B2_YQD'] = False # (m/s); Blade StC #1 Blade #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B2_ZQ'] = False # (m); Blade StC #1 Blade #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B2_ZQD'] = False # (m/s); Blade StC #1 Blade #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B2_Fxi'] = False # (kN); Blade StC #1 Blade #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B2_Fyi'] = False # (kN); Blade StC #1 Blade #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B2_Fzi'] = False # (kN); Blade StC #1 Blade #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B2_Mxi'] = False # (kN-m); Blade StC #1 Blade #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B2_Myi'] = False # (kN-m); Blade StC #1 Blade #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B2_Mzi'] = False # (kN-m); Blade StC #1 Blade #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B2_Fxl'] = False # (kN); Blade StC #1 Blade #2 -- X resulting force; Local StC coordinates +ServoDyn['BStC1_B2_Fyl'] = False # (kN); Blade StC #1 Blade #2 -- Y resulting force; Local StC coordinates +ServoDyn['BStC1_B2_Fzl'] = False # (kN); Blade StC #1 Blade #2 -- Z resulting force; Local StC coordinates +ServoDyn['BStC1_B2_Mxl'] = False # (kN-m); Blade StC #1 Blade #2 -- X resulting moment; Local StC coordinates +ServoDyn['BStC1_B2_Myl'] = False # (kN-m); Blade StC #1 Blade #2 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC1_B2_Mzl'] = False # (kN-m); Blade StC #1 Blade #2 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC2_B2_XQ'] = False # (m); Blade StC #2 Blade #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B2_XQD'] = False # (m/s); Blade StC #2 Blade #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B2_YQ'] = False # (m); Blade StC #2 Blade #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B2_YQD'] = False # (m/s); Blade StC #2 Blade #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B2_ZQ'] = False # (m); Blade StC #2 Blade #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B2_ZQD'] = False # (m/s); Blade StC #2 Blade #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B2_Fxi'] = False # (kN); Blade StC #2 Blade #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B2_Fyi'] = False # (kN); Blade StC #2 Blade #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B2_Fzi'] = False # (kN); Blade StC #2 Blade #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B2_Mxi'] = False # (kN-m); Blade StC #2 Blade #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B2_Myi'] = False # (kN-m); Blade StC #2 Blade #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B2_Mzi'] = False # (kN-m); Blade StC #2 Blade #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B2_Fxl'] = False # (kN); Blade StC #2 Blade #2 -- X resulting force; Local StC coordinates +ServoDyn['BStC2_B2_Fyl'] = False # (kN); Blade StC #2 Blade #2 -- Y resulting force; Local StC coordinates +ServoDyn['BStC2_B2_Fzl'] = False # (kN); Blade StC #2 Blade #2 -- Z resulting force; Local StC coordinates +ServoDyn['BStC2_B2_Mxl'] = False # (kN-m); Blade StC #2 Blade #2 -- X resulting moment; Local StC coordinates +ServoDyn['BStC2_B2_Myl'] = False # (kN-m); Blade StC #2 Blade #2 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC2_B2_Mzl'] = False # (kN-m); Blade StC #2 Blade #2 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC3_B2_XQ'] = False # (m); Blade StC #3 Blade #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B2_XQD'] = False # (m/s); Blade StC #3 Blade #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B2_YQ'] = False # (m); Blade StC #3 Blade #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B2_YQD'] = False # (m/s); Blade StC #3 Blade #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B2_ZQ'] = False # (m); Blade StC #3 Blade #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B2_ZQD'] = False # (m/s); Blade StC #3 Blade #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B2_Fxi'] = False # (kN); Blade StC #3 Blade #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B2_Fyi'] = False # (kN); Blade StC #3 Blade #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B2_Fzi'] = False # (kN); Blade StC #3 Blade #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B2_Mxi'] = False # (kN-m); Blade StC #3 Blade #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B2_Myi'] = False # (kN-m); Blade StC #3 Blade #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B2_Mzi'] = False # (kN-m); Blade StC #3 Blade #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B2_Fxl'] = False # (kN); Blade StC #3 Blade #2 -- X resulting force; Local StC coordinates +ServoDyn['BStC3_B2_Fyl'] = False # (kN); Blade StC #3 Blade #2 -- Y resulting force; Local StC coordinates +ServoDyn['BStC3_B2_Fzl'] = False # (kN); Blade StC #3 Blade #2 -- Z resulting force; Local StC coordinates +ServoDyn['BStC3_B2_Mxl'] = False # (kN-m); Blade StC #3 Blade #2 -- X resulting moment; Local StC coordinates +ServoDyn['BStC3_B2_Myl'] = False # (kN-m); Blade StC #3 Blade #2 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC3_B2_Mzl'] = False # (kN-m); Blade StC #3 Blade #2 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC4_B2_XQ'] = False # (m); Blade StC #4 Blade #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B2_XQD'] = False # (m/s); Blade StC #4 Blade #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B2_YQ'] = False # (m); Blade StC #4 Blade #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B2_YQD'] = False # (m/s); Blade StC #4 Blade #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B2_ZQ'] = False # (m); Blade StC #4 Blade #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B2_ZQD'] = False # (m/s); Blade StC #4 Blade #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B2_Fxi'] = False # (kN); Blade StC #4 Blade #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B2_Fyi'] = False # (kN); Blade StC #4 Blade #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B2_Fzi'] = False # (kN); Blade StC #4 Blade #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B2_Mxi'] = False # (kN-m); Blade StC #4 Blade #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B2_Myi'] = False # (kN-m); Blade StC #4 Blade #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B2_Mzi'] = False # (kN-m); Blade StC #4 Blade #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B2_Fxl'] = False # (kN); Blade StC #4 Blade #2 -- X resulting force; Local StC coordinates +ServoDyn['BStC4_B2_Fyl'] = False # (kN); Blade StC #4 Blade #2 -- Y resulting force; Local StC coordinates +ServoDyn['BStC4_B2_Fzl'] = False # (kN); Blade StC #4 Blade #2 -- Z resulting force; Local StC coordinates +ServoDyn['BStC4_B2_Mxl'] = False # (kN-m); Blade StC #4 Blade #2 -- X resulting moment; Local StC coordinates +ServoDyn['BStC4_B2_Myl'] = False # (kN-m); Blade StC #4 Blade #2 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC4_B2_Mzl'] = False # (kN-m); Blade StC #4 Blade #2 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC1_B3_XQ'] = False # (m); Blade StC #1 Blade #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B3_XQD'] = False # (m/s); Blade StC #1 Blade #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B3_YQ'] = False # (m); Blade StC #1 Blade #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B3_YQD'] = False # (m/s); Blade StC #1 Blade #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B3_ZQ'] = False # (m); Blade StC #1 Blade #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B3_ZQD'] = False # (m/s); Blade StC #1 Blade #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B3_Fxi'] = False # (kN); Blade StC #1 Blade #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B3_Fyi'] = False # (kN); Blade StC #1 Blade #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B3_Fzi'] = False # (kN); Blade StC #1 Blade #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B3_Mxi'] = False # (kN-m); Blade StC #1 Blade #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B3_Myi'] = False # (kN-m); Blade StC #1 Blade #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B3_Mzi'] = False # (kN-m); Blade StC #1 Blade #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B3_Fxl'] = False # (kN); Blade StC #1 Blade #3 -- X resulting force; Local StC coordinates +ServoDyn['BStC1_B3_Fyl'] = False # (kN); Blade StC #1 Blade #3 -- Y resulting force; Local StC coordinates +ServoDyn['BStC1_B3_Fzl'] = False # (kN); Blade StC #1 Blade #3 -- Z resulting force; Local StC coordinates +ServoDyn['BStC1_B3_Mxl'] = False # (kN-m); Blade StC #1 Blade #3 -- X resulting moment; Local StC coordinates +ServoDyn['BStC1_B3_Myl'] = False # (kN-m); Blade StC #1 Blade #3 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC1_B3_Mzl'] = False # (kN-m); Blade StC #1 Blade #3 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC2_B3_XQ'] = False # (m); Blade StC #2 Blade #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B3_XQD'] = False # (m/s); Blade StC #2 Blade #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B3_YQ'] = False # (m); Blade StC #2 Blade #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B3_YQD'] = False # (m/s); Blade StC #2 Blade #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B3_ZQ'] = False # (m); Blade StC #2 Blade #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B3_ZQD'] = False # (m/s); Blade StC #2 Blade #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B3_Fxi'] = False # (kN); Blade StC #2 Blade #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B3_Fyi'] = False # (kN); Blade StC #2 Blade #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B3_Fzi'] = False # (kN); Blade StC #2 Blade #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B3_Mxi'] = False # (kN-m); Blade StC #2 Blade #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B3_Myi'] = False # (kN-m); Blade StC #2 Blade #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B3_Mzi'] = False # (kN-m); Blade StC #2 Blade #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B3_Fxl'] = False # (kN); Blade StC #2 Blade #3 -- X resulting force; Local StC coordinates +ServoDyn['BStC2_B3_Fyl'] = False # (kN); Blade StC #2 Blade #3 -- Y resulting force; Local StC coordinates +ServoDyn['BStC2_B3_Fzl'] = False # (kN); Blade StC #2 Blade #3 -- Z resulting force; Local StC coordinates +ServoDyn['BStC2_B3_Mxl'] = False # (kN-m); Blade StC #2 Blade #3 -- X resulting moment; Local StC coordinates +ServoDyn['BStC2_B3_Myl'] = False # (kN-m); Blade StC #2 Blade #3 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC2_B3_Mzl'] = False # (kN-m); Blade StC #2 Blade #3 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC3_B3_XQ'] = False # (m); Blade StC #3 Blade #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B3_XQD'] = False # (m/s); Blade StC #3 Blade #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B3_YQ'] = False # (m); Blade StC #3 Blade #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B3_YQD'] = False # (m/s); Blade StC #3 Blade #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B3_ZQ'] = False # (m); Blade StC #3 Blade #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B3_ZQD'] = False # (m/s); Blade StC #3 Blade #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B3_Fxi'] = False # (kN); Blade StC #3 Blade #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B3_Fyi'] = False # (kN); Blade StC #3 Blade #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B3_Fzi'] = False # (kN); Blade StC #3 Blade #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B3_Mxi'] = False # (kN-m); Blade StC #3 Blade #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B3_Myi'] = False # (kN-m); Blade StC #3 Blade #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B3_Mzi'] = False # (kN-m); Blade StC #3 Blade #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B3_Fxl'] = False # (kN); Blade StC #3 Blade #3 -- X resulting force; Local StC coordinates +ServoDyn['BStC3_B3_Fyl'] = False # (kN); Blade StC #3 Blade #3 -- Y resulting force; Local StC coordinates +ServoDyn['BStC3_B3_Fzl'] = False # (kN); Blade StC #3 Blade #3 -- Z resulting force; Local StC coordinates +ServoDyn['BStC3_B3_Mxl'] = False # (kN-m); Blade StC #3 Blade #3 -- X resulting moment; Local StC coordinates +ServoDyn['BStC3_B3_Myl'] = False # (kN-m); Blade StC #3 Blade #3 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC3_B3_Mzl'] = False # (kN-m); Blade StC #3 Blade #3 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC4_B3_XQ'] = False # (m); Blade StC #4 Blade #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B3_XQD'] = False # (m/s); Blade StC #4 Blade #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B3_YQ'] = False # (m); Blade StC #4 Blade #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B3_YQD'] = False # (m/s); Blade StC #4 Blade #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B3_ZQ'] = False # (m); Blade StC #4 Blade #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B3_ZQD'] = False # (m/s); Blade StC #4 Blade #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B3_Fxi'] = False # (kN); Blade StC #4 Blade #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B3_Fyi'] = False # (kN); Blade StC #4 Blade #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B3_Fzi'] = False # (kN); Blade StC #4 Blade #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B3_Mxi'] = False # (kN-m); Blade StC #4 Blade #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B3_Myi'] = False # (kN-m); Blade StC #4 Blade #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B3_Mzi'] = False # (kN-m); Blade StC #4 Blade #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B3_Fxl'] = False # (kN); Blade StC #4 Blade #3 -- X resulting force; Local StC coordinates +ServoDyn['BStC4_B3_Fyl'] = False # (kN); Blade StC #4 Blade #3 -- Y resulting force; Local StC coordinates +ServoDyn['BStC4_B3_Fzl'] = False # (kN); Blade StC #4 Blade #3 -- Z resulting force; Local StC coordinates +ServoDyn['BStC4_B3_Mxl'] = False # (kN-m); Blade StC #4 Blade #3 -- X resulting moment; Local StC coordinates +ServoDyn['BStC4_B3_Myl'] = False # (kN-m); Blade StC #4 Blade #3 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC4_B3_Mzl'] = False # (kN-m); Blade StC #4 Blade #3 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC1_B4_XQ'] = False # (m); Blade StC #1 Blade #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B4_XQD'] = False # (m/s); Blade StC #1 Blade #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B4_YQ'] = False # (m); Blade StC #1 Blade #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B4_YQD'] = False # (m/s); Blade StC #1 Blade #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B4_ZQ'] = False # (m); Blade StC #1 Blade #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC1_B4_ZQD'] = False # (m/s); Blade StC #1 Blade #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC1_B4_Fxi'] = False # (kN); Blade StC #1 Blade #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B4_Fyi'] = False # (kN); Blade StC #1 Blade #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B4_Fzi'] = False # (kN); Blade StC #1 Blade #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC1_B4_Mxi'] = False # (kN-m); Blade StC #1 Blade #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B4_Myi'] = False # (kN-m); Blade StC #1 Blade #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B4_Mzi'] = False # (kN-m); Blade StC #1 Blade #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC1_B4_Fxl'] = False # (kN); Blade StC #1 Blade #4 -- X resulting force; Local StC coordinates +ServoDyn['BStC1_B4_Fyl'] = False # (kN); Blade StC #1 Blade #4 -- Y resulting force; Local StC coordinates +ServoDyn['BStC1_B4_Fzl'] = False # (kN); Blade StC #1 Blade #4 -- Z resulting force; Local StC coordinates +ServoDyn['BStC1_B4_Mxl'] = False # (kN-m); Blade StC #1 Blade #4 -- X resulting moment; Local StC coordinates +ServoDyn['BStC1_B4_Myl'] = False # (kN-m); Blade StC #1 Blade #4 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC1_B4_Mzl'] = False # (kN-m); Blade StC #1 Blade #4 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC2_B4_XQ'] = False # (m); Blade StC #2 Blade #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B4_XQD'] = False # (m/s); Blade StC #2 Blade #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B4_YQ'] = False # (m); Blade StC #2 Blade #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B4_YQD'] = False # (m/s); Blade StC #2 Blade #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B4_ZQ'] = False # (m); Blade StC #2 Blade #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC2_B4_ZQD'] = False # (m/s); Blade StC #2 Blade #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC2_B4_Fxi'] = False # (kN); Blade StC #2 Blade #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B4_Fyi'] = False # (kN); Blade StC #2 Blade #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B4_Fzi'] = False # (kN); Blade StC #2 Blade #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC2_B4_Mxi'] = False # (kN-m); Blade StC #2 Blade #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B4_Myi'] = False # (kN-m); Blade StC #2 Blade #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B4_Mzi'] = False # (kN-m); Blade StC #2 Blade #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC2_B4_Fxl'] = False # (kN); Blade StC #2 Blade #4 -- X resulting force; Local StC coordinates +ServoDyn['BStC2_B4_Fyl'] = False # (kN); Blade StC #2 Blade #4 -- Y resulting force; Local StC coordinates +ServoDyn['BStC2_B4_Fzl'] = False # (kN); Blade StC #2 Blade #4 -- Z resulting force; Local StC coordinates +ServoDyn['BStC2_B4_Mxl'] = False # (kN-m); Blade StC #2 Blade #4 -- X resulting moment; Local StC coordinates +ServoDyn['BStC2_B4_Myl'] = False # (kN-m); Blade StC #2 Blade #4 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC2_B4_Mzl'] = False # (kN-m); Blade StC #2 Blade #4 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC3_B4_XQ'] = False # (m); Blade StC #3 Blade #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B4_XQD'] = False # (m/s); Blade StC #3 Blade #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B4_YQ'] = False # (m); Blade StC #3 Blade #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B4_YQD'] = False # (m/s); Blade StC #3 Blade #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B4_ZQ'] = False # (m); Blade StC #3 Blade #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC3_B4_ZQD'] = False # (m/s); Blade StC #3 Blade #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC3_B4_Fxi'] = False # (kN); Blade StC #3 Blade #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B4_Fyi'] = False # (kN); Blade StC #3 Blade #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B4_Fzi'] = False # (kN); Blade StC #3 Blade #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC3_B4_Mxi'] = False # (kN-m); Blade StC #3 Blade #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B4_Myi'] = False # (kN-m); Blade StC #3 Blade #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B4_Mzi'] = False # (kN-m); Blade StC #3 Blade #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC3_B4_Fxl'] = False # (kN); Blade StC #3 Blade #4 -- X resulting force; Local StC coordinates +ServoDyn['BStC3_B4_Fyl'] = False # (kN); Blade StC #3 Blade #4 -- Y resulting force; Local StC coordinates +ServoDyn['BStC3_B4_Fzl'] = False # (kN); Blade StC #3 Blade #4 -- Z resulting force; Local StC coordinates +ServoDyn['BStC3_B4_Mxl'] = False # (kN-m); Blade StC #3 Blade #4 -- X resulting moment; Local StC coordinates +ServoDyn['BStC3_B4_Myl'] = False # (kN-m); Blade StC #3 Blade #4 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC3_B4_Mzl'] = False # (kN-m); Blade StC #3 Blade #4 -- Z resulting moment; Local StC coordinates +ServoDyn['BStC4_B4_XQ'] = False # (m); Blade StC #4 Blade #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B4_XQD'] = False # (m/s); Blade StC #4 Blade #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B4_YQ'] = False # (m); Blade StC #4 Blade #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B4_YQD'] = False # (m/s); Blade StC #4 Blade #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B4_ZQ'] = False # (m); Blade StC #4 Blade #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['BStC4_B4_ZQD'] = False # (m/s); Blade StC #4 Blade #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['BStC4_B4_Fxi'] = False # (kN); Blade StC #4 Blade #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B4_Fyi'] = False # (kN); Blade StC #4 Blade #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B4_Fzi'] = False # (kN); Blade StC #4 Blade #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['BStC4_B4_Mxi'] = False # (kN-m); Blade StC #4 Blade #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B4_Myi'] = False # (kN-m); Blade StC #4 Blade #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B4_Mzi'] = False # (kN-m); Blade StC #4 Blade #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['BStC4_B4_Fxl'] = False # (kN); Blade StC #4 Blade #4 -- X resulting force; Local StC coordinates +ServoDyn['BStC4_B4_Fyl'] = False # (kN); Blade StC #4 Blade #4 -- Y resulting force; Local StC coordinates +ServoDyn['BStC4_B4_Fzl'] = False # (kN); Blade StC #4 Blade #4 -- Z resulting force; Local StC coordinates +ServoDyn['BStC4_B4_Mxl'] = False # (kN-m); Blade StC #4 Blade #4 -- X resulting moment; Local StC coordinates +ServoDyn['BStC4_B4_Myl'] = False # (kN-m); Blade StC #4 Blade #4 -- Y resulting moment; Local StC coordinates +ServoDyn['BStC4_B4_Mzl'] = False # (kN-m); Blade StC #4 Blade #4 -- Z resulting moment; Local StC coordinates + +# Substructure Structural Control (StC) +ServoDyn['SStC1_XQ'] = False # (m); Substructure StC #1 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC1_XQD'] = False # (m/s); Substructure StC #1 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC1_YQ'] = False # (m); Substructure StC #1 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC1_YQD'] = False # (m/s); Substructure StC #1 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC1_ZQ'] = False # (m); Substructure StC #1 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC1_ZQD'] = False # (m/s); Substructure StC #1 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC1_Fxi'] = False # (kN); Substructure StC #1 -- X resulting force; Inertial (global) coordinates +ServoDyn['SStC1_Fyi'] = False # (kN); Substructure StC #1 -- Y resulting force; Inertial (global) coordinates +ServoDyn['SStC1_Fzi'] = False # (kN); Substructure StC #1 -- Z resulting force; Inertial (global) coordinates +ServoDyn['SStC1_Mxi'] = False # (kN-m); Substructure StC #1 -- X resulting moment; Inertial (global) coordinates +ServoDyn['SStC1_Myi'] = False # (kN-m); Substructure StC #1 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['SStC1_Mzi'] = False # (kN-m); Substructure StC #1 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['SStC1_Fxl'] = False # (kN); Substructure StC #1 -- X resulting force; Local StC coordinates +ServoDyn['SStC1_Fyl'] = False # (kN); Substructure StC #1 -- Y resulting force; Local StC coordinates +ServoDyn['SStC1_Fzl'] = False # (kN); Substructure StC #1 -- Z resulting force; Local StC coordinates +ServoDyn['SStC1_Mxl'] = False # (kN-m); Substructure StC #1 -- X resulting moment; Local StC coordinates +ServoDyn['SStC1_Myl'] = False # (kN-m); Substructure StC #1 -- Y resulting moment; Local StC coordinates +ServoDyn['SStC1_Mzl'] = False # (kN-m); Substructure StC #1 -- Z resulting moment; Local StC coordinates +ServoDyn['SStC2_XQ'] = False # (m); Substructure StC #2 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC2_XQD'] = False # (m/s); Substructure StC #2 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC2_YQ'] = False # (m); Substructure StC #2 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC2_YQD'] = False # (m/s); Substructure StC #2 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC2_ZQ'] = False # (m); Substructure StC #2 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC2_ZQD'] = False # (m/s); Substructure StC #2 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC2_Fxi'] = False # (kN); Substructure StC #2 -- X resulting force; Inertial (global) coordinates +ServoDyn['SStC2_Fyi'] = False # (kN); Substructure StC #2 -- Y resulting force; Inertial (global) coordinates +ServoDyn['SStC2_Fzi'] = False # (kN); Substructure StC #2 -- Z resulting force; Inertial (global) coordinates +ServoDyn['SStC2_Mxi'] = False # (kN-m); Substructure StC #2 -- X resulting moment; Inertial (global) coordinates +ServoDyn['SStC2_Myi'] = False # (kN-m); Substructure StC #2 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['SStC2_Mzi'] = False # (kN-m); Substructure StC #2 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['SStC2_Fxl'] = False # (kN); Substructure StC #2 -- X resulting force; Local StC coordinates +ServoDyn['SStC2_Fyl'] = False # (kN); Substructure StC #2 -- Y resulting force; Local StC coordinates +ServoDyn['SStC2_Fzl'] = False # (kN); Substructure StC #2 -- Z resulting force; Local StC coordinates +ServoDyn['SStC2_Mxl'] = False # (kN-m); Substructure StC #2 -- X resulting moment; Local StC coordinates +ServoDyn['SStC2_Myl'] = False # (kN-m); Substructure StC #2 -- Y resulting moment; Local StC coordinates +ServoDyn['SStC2_Mzl'] = False # (kN-m); Substructure StC #2 -- Z resulting moment; Local StC coordinates +ServoDyn['SStC3_XQ'] = False # (m); Substructure StC #3 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC3_XQD'] = False # (m/s); Substructure StC #3 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC3_YQ'] = False # (m); Substructure StC #3 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC3_YQD'] = False # (m/s); Substructure StC #3 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC3_ZQ'] = False # (m); Substructure StC #3 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC3_ZQD'] = False # (m/s); Substructure StC #3 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC3_Fxi'] = False # (kN); Substructure StC #3 -- X resulting force; Inertial (global) coordinates +ServoDyn['SStC3_Fyi'] = False # (kN); Substructure StC #3 -- Y resulting force; Inertial (global) coordinates +ServoDyn['SStC3_Fzi'] = False # (kN); Substructure StC #3 -- Z resulting force; Inertial (global) coordinates +ServoDyn['SStC3_Mxi'] = False # (kN-m); Substructure StC #3 -- X resulting moment; Inertial (global) coordinates +ServoDyn['SStC3_Myi'] = False # (kN-m); Substructure StC #3 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['SStC3_Mzi'] = False # (kN-m); Substructure StC #3 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['SStC3_Fxl'] = False # (kN); Substructure StC #3 -- X resulting force; Local StC coordinates +ServoDyn['SStC3_Fyl'] = False # (kN); Substructure StC #3 -- Y resulting force; Local StC coordinates +ServoDyn['SStC3_Fzl'] = False # (kN); Substructure StC #3 -- Z resulting force; Local StC coordinates +ServoDyn['SStC3_Mxl'] = False # (kN-m); Substructure StC #3 -- X resulting moment; Local StC coordinates +ServoDyn['SStC3_Myl'] = False # (kN-m); Substructure StC #3 -- Y resulting moment; Local StC coordinates +ServoDyn['SStC3_Mzl'] = False # (kN-m); Substructure StC #3 -- Z resulting moment; Local StC coordinates +ServoDyn['SStC4_XQ'] = False # (m); Substructure StC #4 -- X position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC4_XQD'] = False # (m/s); Substructure StC #4 -- X velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC4_YQ'] = False # (m); Substructure StC #4 -- Y position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC4_YQD'] = False # (m/s); Substructure StC #4 -- Y velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC4_ZQ'] = False # (m); Substructure StC #4 -- Z position (displacement); Relative to rest position in StC reference frame +ServoDyn['SStC4_ZQD'] = False # (m/s); Substructure StC #4 -- Z velocity; Relative to nacelle in StC reference frame +ServoDyn['SStC4_Fxi'] = False # (kN); Substructure StC #4 -- X resulting force; Inertial (global) coordinates +ServoDyn['SStC4_Fyi'] = False # (kN); Substructure StC #4 -- Y resulting force; Inertial (global) coordinates +ServoDyn['SStC4_Fzi'] = False # (kN); Substructure StC #4 -- Z resulting force; Inertial (global) coordinates +ServoDyn['SStC4_Mxi'] = False # (kN-m); Substructure StC #4 -- X resulting moment; Inertial (global) coordinates +ServoDyn['SStC4_Myi'] = False # (kN-m); Substructure StC #4 -- Y resulting moment; Inertial (global) coordinates +ServoDyn['SStC4_Mzi'] = False # (kN-m); Substructure StC #4 -- Z resulting moment; Inertial (global) coordinates +ServoDyn['SStC4_Fxl'] = False # (kN); Substructure StC #4 -- X resulting force; Local StC coordinates +ServoDyn['SStC4_Fyl'] = False # (kN); Substructure StC #4 -- Y resulting force; Local StC coordinates +ServoDyn['SStC4_Fzl'] = False # (kN); Substructure StC #4 -- Z resulting force; Local StC coordinates +ServoDyn['SStC4_Mxl'] = False # (kN-m); Substructure StC #4 -- X resulting moment; Local StC coordinates +ServoDyn['SStC4_Myl'] = False # (kN-m); Substructure StC #4 -- Y resulting moment; Local StC coordinates +ServoDyn['SStC4_Mzl'] = False # (kN-m); Substructure StC #4 -- Z resulting moment; Local StC coordinates + -# Tower Tuned Mass Damper (TMD) -ServoDyn['TTMD_XQ'] = False # (m); Tower X TMD position (displacement); Relative to rest position -ServoDyn['TTMD_XQD'] = False # (m/s); Tower X TMD velocity; Relative to tower -ServoDyn['TTMD_YQ'] = False # (m); Tower Y TMD position (displacement); Relative to rest position -ServoDyn['TTMD_YQD'] = False # (m/s); Tower Y TMD velocity; Relative to tower # Flap outputs ServoDyn['BLFLAP1'] = False # (m/s); Tower Y TMD velocity; Relative to tower @@ -1563,6 +2074,60 @@ AeroDyn['B1Pitch'] = False # (deg); Pitch angle of blade 1; AeroDyn['B2Pitch'] = False # (deg); Pitch angle of blade 2; AeroDyn['B3Pitch'] = False # (deg); Pitch angle of blade 3; +AeroDyn['B1AeroFx'] = False # (N); Total blade aerodynamic load for blade 1 (force in x-direction); blade root coordinate system +AeroDyn['B1AeroFy'] = False # (N); Total blade aerodynamic load for blade 1 (force in y-direction); blade root coordinate system +AeroDyn['B1AeroFz'] = False # (N); Total blade aerodynamic load for blade 1 (force in z-direction); blade root coordinate system +AeroDyn['B1AeroMx'] = False # (N-m); Total blade aerodynamic load for blade 1 (moment in x-direction); blade root coordinate system +AeroDyn['B1AeroMy'] = False # (N-m); Total blade aerodynamic load for blade 1 (moment in y-direction); blade root coordinate system +AeroDyn['B1AeroMz'] = False # (N-m); Total blade aerodynamic load for blade 1 (moment in z-direction); blade root coordinate system +AeroDyn['B1AeroPwr'] = False # (W); Total aerodynamic power from blade 1; +AeroDyn['B2AeroFx'] = False # (N); Total blade aerodynamic load for blade 2 (force in x-direction); blade root coordinate system +AeroDyn['B2AeroFy'] = False # (N); Total blade aerodynamic load for blade 2 (force in y-direction); blade root coordinate system +AeroDyn['B2AeroFz'] = False # (N); Total blade aerodynamic load for blade 2 (force in z-direction); blade root coordinate system +AeroDyn['B2AeroMx'] = False # (N-m); Total blade aerodynamic load for blade 2 (moment in x-direction); blade root coordinate system +AeroDyn['B2AeroMy'] = False # (N-m); Total blade aerodynamic load for blade 2 (moment in y-direction); blade root coordinate system +AeroDyn['B2AeroMz'] = False # (N-m); Total blade aerodynamic load for blade 2 (moment in z-direction); blade root coordinate system +AeroDyn['B2AeroPwr'] = False # (W); Total aerodynamic power from blade 2; +AeroDyn['B3AeroFx'] = False # (N); Total blade aerodynamic load for blade 3 (force in x-direction); blade root coordinate system +AeroDyn['B3AeroFy'] = False # (N); Total blade aerodynamic load for blade 3 (force in y-direction); blade root coordinate system +AeroDyn['B3AeroFz'] = False # (N); Total blade aerodynamic load for blade 3 (force in z-direction); blade root coordinate system +AeroDyn['B3AeroMx'] = False # (N-m); Total blade aerodynamic load for blade 3 (moment in x-direction); blade root coordinate system +AeroDyn['B3AeroMy'] = False # (N-m); Total blade aerodynamic load for blade 3 (moment in y-direction); blade root coordinate system +AeroDyn['B3AeroMz'] = False # (N-m); Total blade aerodynamic load for blade 3 (moment in z-direction); blade root coordinate system +AeroDyn['B3AeroPwr'] = False # (W); Total aerodynamic power from blade 3; +AeroDyn['B4AeroFx'] = False # (N); Total blade aerodynamic load for blade 4 (force in x-direction); blade root coordinate system +AeroDyn['B4AeroFy'] = False # (N); Total blade aerodynamic load for blade 4 (force in y-direction); blade root coordinate system +AeroDyn['B4AeroFz'] = False # (N); Total blade aerodynamic load for blade 4 (force in z-direction); blade root coordinate system +AeroDyn['B4AeroMx'] = False # (N-m); Total blade aerodynamic load for blade 4 (moment in x-direction); blade root coordinate system +AeroDyn['B4AeroMy'] = False # (N-m); Total blade aerodynamic load for blade 4 (moment in y-direction); blade root coordinate system +AeroDyn['B4AeroMz'] = False # (N-m); Total blade aerodynamic load for blade 4 (moment in z-direction); blade root coordinate system +AeroDyn['B4AeroPwr'] = False # (W); Total aerodynamic power from blade 4; +AeroDyn['B1AeroFxg'] = False # (N); Total blade aerodynamic load for blade 1 (force in x-direction); global coordinate system +AeroDyn['B1AeroFyg'] = False # (N); Total blade aerodynamic load for blade 1 (force in y-direction); global coordinate system +AeroDyn['B1AeroFzg'] = False # (N); Total blade aerodynamic load for blade 1 (force in z-direction); global coordinate system +AeroDyn['B1AeroMxg'] = False # (N-m); Total blade aerodynamic load for blade 1 (moment in x-direction); global coordinate system +AeroDyn['B1AeroMyg'] = False # (N-m); Total blade aerodynamic load for blade 1 (moment in y-direction); global coordinate system +AeroDyn['B1AeroMzg'] = False # (N-m); Total blade aerodynamic load for blade 1 (moment in z-direction); global coordinate system +AeroDyn['B2AeroFxg'] = False # (N); Total blade aerodynamic load for blade 2 (force in x-direction); global coordinate system +AeroDyn['B2AeroFyg'] = False # (N); Total blade aerodynamic load for blade 2 (force in y-direction); global coordinate system +AeroDyn['B2AeroFzg'] = False # (N); Total blade aerodynamic load for blade 2 (force in z-direction); global coordinate system +AeroDyn['B2AeroMxg'] = False # (N-m); Total blade aerodynamic load for blade 2 (moment in x-direction); global coordinate system +AeroDyn['B2AeroMyg'] = False # (N-m); Total blade aerodynamic load for blade 2 (moment in y-direction); global coordinate system +AeroDyn['B2AeroMzg'] = False # (N-m); Total blade aerodynamic load for blade 2 (moment in z-direction); global coordinate system +AeroDyn['B3AeroFxg'] = False # (N); Total blade aerodynamic load for blade 3 (force in x-direction); global coordinate system +AeroDyn['B3AeroFyg'] = False # (N); Total blade aerodynamic load for blade 3 (force in y-direction); global coordinate system +AeroDyn['B3AeroFzg'] = False # (N); Total blade aerodynamic load for blade 3 (force in z-direction); global coordinate system +AeroDyn['B3AeroMxg'] = False # (N-m); Total blade aerodynamic load for blade 3 (moment in x-direction); global coordinate system +AeroDyn['B3AeroMyg'] = False # (N-m); Total blade aerodynamic load for blade 3 (moment in y-direction); global coordinate system +AeroDyn['B3AeroMzg'] = False # (N-m); Total blade aerodynamic load for blade 3 (moment in z-direction); global coordinate system +AeroDyn['B4AeroFxg'] = False # (N); Total blade aerodynamic load for blade 4 (force in x-direction); global coordinate system +AeroDyn['B4AeroFyg'] = False # (N); Total blade aerodynamic load for blade 4 (force in y-direction); global coordinate system +AeroDyn['B4AeroFzg'] = False # (N); Total blade aerodynamic load for blade 4 (force in z-direction); global coordinate system +AeroDyn['B4AeroMxg'] = False # (N-m); Total blade aerodynamic load for blade 4 (moment in x-direction); global coordinate system +AeroDyn['B4AeroMyg'] = False # (N-m); Total blade aerodynamic load for blade 4 (moment in y-direction); global coordinate system +AeroDyn['B4AeroMzg'] = False # (N-m); Total blade aerodynamic load for blade 4 (moment in z-direction); global coordinate system + +# Blade Nodal outputs AeroDyn['B1N1VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 1; local blade coordinate system AeroDyn['B1N2VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 2; local blade coordinate system AeroDyn['B1N3VUndx'] = False # (m/s); x-component of undisturbed wind velocity at Blade 1, Node 3; local blade coordinate system @@ -2535,6 +3100,114 @@ AeroDyn['B3N7Clrnc'] = False # (m); Tower clearance at Blade 3, Node 7 (based on the absolute distance to the nearest point in the tower from B3N7 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N7 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output; AeroDyn['B3N8Clrnc'] = False # (m); Tower clearance at Blade 3, Node 8 (based on the absolute distance to the nearest point in the tower from B3N8 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N8 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output; AeroDyn['B3N9Clrnc'] = False # (m); Tower clearance at Blade 3, Node 9 (based on the absolute distance to the nearest point in the tower from B3N9 minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when B3N9 is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output; +AeroDyn['B1N1Cpmin'] = False # (-); Pressure coefficient blade 1 node 1; +AeroDyn['B1N2Cpmin'] = False # (-); Pressure coefficient blade 1 node 2; +AeroDyn['B1N3Cpmin'] = False # (-); Pressure coefficient blade 1 node 3; +AeroDyn['B1N4Cpmin'] = False # (-); Pressure coefficient blade 1 node 4; +AeroDyn['B1N5Cpmin'] = False # (-); Pressure coefficient blade 1 node 5; +AeroDyn['B1N6Cpmin'] = False # (-); Pressure coefficient blade 1 node 6; +AeroDyn['B1N7Cpmin'] = False # (-); Pressure coefficient blade 1 node 7; +AeroDyn['B1N8Cpmin'] = False # (-); Pressure coefficient blade 1 node 8; +AeroDyn['B1N9Cpmin'] = False # (-); Pressure coefficient blade 1 node 9; +AeroDyn['B2N1Cpmin'] = False # (-); Pressure coefficient blade 2 node 1; +AeroDyn['B2N2Cpmin'] = False # (-); Pressure coefficient blade 2 node 2; +AeroDyn['B2N3Cpmin'] = False # (-); Pressure coefficient blade 2 node 3; +AeroDyn['B2N4Cpmin'] = False # (-); Pressure coefficient blade 2 node 4; +AeroDyn['B2N5Cpmin'] = False # (-); Pressure coefficient blade 2 node 5; +AeroDyn['B2N6Cpmin'] = False # (-); Pressure coefficient blade 2 node 6; +AeroDyn['B2N7Cpmin'] = False # (-); Pressure coefficient blade 2 node 7; +AeroDyn['B2N8Cpmin'] = False # (-); Pressure coefficient blade 2 node 8; +AeroDyn['B2N9Cpmin'] = False # (-); Pressure coefficient blade 2 node 9; +AeroDyn['B3N1Cpmin'] = False # (-); Pressure coefficient blade 3 node 1; +AeroDyn['B3N2Cpmin'] = False # (-); Pressure coefficient blade 3 node 2; +AeroDyn['B3N3Cpmin'] = False # (-); Pressure coefficient blade 3 node 3; +AeroDyn['B3N4Cpmin'] = False # (-); Pressure coefficient blade 3 node 4; +AeroDyn['B3N5Cpmin'] = False # (-); Pressure coefficient blade 3 node 5; +AeroDyn['B3N6Cpmin'] = False # (-); Pressure coefficient blade 3 node 6; +AeroDyn['B3N7Cpmin'] = False # (-); Pressure coefficient blade 3 node 7; +AeroDyn['B3N8Cpmin'] = False # (-); Pressure coefficient blade 3 node 8; +AeroDyn['B3N9Cpmin'] = False # (-); Pressure coefficient blade 3 node 9; +AeroDyn['B1N1SigCr'] = False # (-); Critical cavitation number blade 1 node 1; +AeroDyn['B1N2SigCr'] = False # (-); Critical cavitation number blade 1 node 2; +AeroDyn['B1N3SigCr'] = False # (-); Critical cavitation number blade 1 node 3; +AeroDyn['B1N4SigCr'] = False # (-); Critical cavitation number blade 1 node 4; +AeroDyn['B1N5SigCr'] = False # (-); Critical cavitation number blade 1 node 5; +AeroDyn['B1N6SigCr'] = False # (-); Critical cavitation number blade 1 node 6; +AeroDyn['B1N7SigCr'] = False # (-); Critical cavitation number blade 1 node 7; +AeroDyn['B1N8SigCr'] = False # (-); Critical cavitation number blade 1 node 8; +AeroDyn['B1N9SigCr'] = False # (-); Critical cavitation number blade 1 node 9; +AeroDyn['B2N1SigCr'] = False # (-); Critical cavitation number blade 2 node 1; +AeroDyn['B2N2SigCr'] = False # (-); Critical cavitation number blade 2 node 2; +AeroDyn['B2N3SigCr'] = False # (-); Critical cavitation number blade 2 node 3; +AeroDyn['B2N4SigCr'] = False # (-); Critical cavitation number blade 2 node 4; +AeroDyn['B2N5SigCr'] = False # (-); Critical cavitation number blade 2 node 5; +AeroDyn['B2N6SigCr'] = False # (-); Critical cavitation number blade 2 node 6; +AeroDyn['B2N7SigCr'] = False # (-); Critical cavitation number blade 2 node 7; +AeroDyn['B2N8SigCr'] = False # (-); Critical cavitation number blade 2 node 8; +AeroDyn['B2N9SigCr'] = False # (-); Critical cavitation number blade 2 node 9; +AeroDyn['B3N1SigCr'] = False # (-); Critical cavitation number blade 3 node 1; +AeroDyn['B3N2SigCr'] = False # (-); Critical cavitation number blade 3 node 2; +AeroDyn['B3N3SigCr'] = False # (-); Critical cavitation number blade 3 node 3; +AeroDyn['B3N4SigCr'] = False # (-); Critical cavitation number blade 3 node 4; +AeroDyn['B3N5SigCr'] = False # (-); Critical cavitation number blade 3 node 5; +AeroDyn['B3N6SigCr'] = False # (-); Critical cavitation number blade 3 node 6; +AeroDyn['B3N7SigCr'] = False # (-); Critical cavitation number blade 3 node 7; +AeroDyn['B3N8SigCr'] = False # (-); Critical cavitation number blade 3 node 8; +AeroDyn['B3N9SigCr'] = False # (-); Critical cavitation number blade 3 node 9; +AeroDyn['B1N1SgCav'] = False # (-); Cavitation number blade 1 node 1; +AeroDyn['B1N2SgCav'] = False # (-); Cavitation number blade 1 node 2; +AeroDyn['B1N3SgCav'] = False # (-); Cavitation number blade 1 node 3; +AeroDyn['B1N4SgCav'] = False # (-); Cavitation number blade 1 node 4; +AeroDyn['B1N5SgCav'] = False # (-); Cavitation number blade 1 node 5; +AeroDyn['B1N6SgCav'] = False # (-); Cavitation number blade 1 node 6; +AeroDyn['B1N7SgCav'] = False # (-); Cavitation number blade 1 node 7; +AeroDyn['B1N8SgCav'] = False # (-); Cavitation number blade 1 node 8; +AeroDyn['B1N9SgCav'] = False # (-); Cavitation number blade 1 node 9; +AeroDyn['B2N1SgCav'] = False # (-); Cavitation number blade 2 node 1; +AeroDyn['B2N2SgCav'] = False # (-); Cavitation number blade 2 node 2; +AeroDyn['B2N3SgCav'] = False # (-); Cavitation number blade 2 node 3; +AeroDyn['B2N4SgCav'] = False # (-); Cavitation number blade 2 node 4; +AeroDyn['B2N5SgCav'] = False # (-); Cavitation number blade 2 node 5; +AeroDyn['B2N6SgCav'] = False # (-); Cavitation number blade 2 node 6; +AeroDyn['B2N7SgCav'] = False # (-); Cavitation number blade 2 node 7; +AeroDyn['B2N8SgCav'] = False # (-); Cavitation number blade 2 node 8; +AeroDyn['B2N9SgCav'] = False # (-); Cavitation number blade 2 node 9; +AeroDyn['B3N1SgCav'] = False # (-); Cavitation number blade 3 node 1; +AeroDyn['B3N2SgCav'] = False # (-); Cavitation number blade 3 node 2; +AeroDyn['B3N3SgCav'] = False # (-); Cavitation number blade 3 node 3; +AeroDyn['B3N4SgCav'] = False # (-); Cavitation number blade 3 node 4; +AeroDyn['B3N5SgCav'] = False # (-); Cavitation number blade 3 node 5; +AeroDyn['B3N6SgCav'] = False # (-); Cavitation number blade 3 node 6; +AeroDyn['B3N7SgCav'] = False # (-); Cavitation number blade 3 node 7; +AeroDyn['B3N8SgCav'] = False # (-); Cavitation number blade 3 node 8; +AeroDyn['B3N9SgCav'] = False # (-); Cavitation number blade 3 node 9; +AeroDyn['B1N1Gam'] = False # (m^2/s); Circulation on blade 1 at node 1; +AeroDyn['B1N2Gam'] = False # (m^2/s); Circulation on blade 1 at node 2; +AeroDyn['B1N3Gam'] = False # (m^2/s); Circulation on blade 1 at node 3; +AeroDyn['B1N4Gam'] = False # (m^2/s); Circulation on blade 1 at node 4; +AeroDyn['B1N5Gam'] = False # (m^2/s); Circulation on blade 1 at node 5; +AeroDyn['B1N6Gam'] = False # (m^2/s); Circulation on blade 1 at node 6; +AeroDyn['B1N7Gam'] = False # (m^2/s); Circulation on blade 1 at node 7; +AeroDyn['B1N8Gam'] = False # (m^2/s); Circulation on blade 1 at node 8; +AeroDyn['B1N9Gam'] = False # (m^2/s); Circulation on blade 1 at node 9; +AeroDyn['B2N1Gam'] = False # (m^2/s); Circulation on blade 2 at node 1; +AeroDyn['B2N2Gam'] = False # (m^2/s); Circulation on blade 2 at node 2; +AeroDyn['B2N3Gam'] = False # (m^2/s); Circulation on blade 2 at node 3; +AeroDyn['B2N4Gam'] = False # (m^2/s); Circulation on blade 2 at node 4; +AeroDyn['B2N5Gam'] = False # (m^2/s); Circulation on blade 2 at node 5; +AeroDyn['B2N6Gam'] = False # (m^2/s); Circulation on blade 2 at node 6; +AeroDyn['B2N7Gam'] = False # (m^2/s); Circulation on blade 2 at node 7; +AeroDyn['B2N8Gam'] = False # (m^2/s); Circulation on blade 2 at node 8; +AeroDyn['B2N9Gam'] = False # (m^2/s); Circulation on blade 2 at node 9; +AeroDyn['B3N1Gam'] = False # (m^2/s); Circulation on blade 3 at node 1; +AeroDyn['B3N2Gam'] = False # (m^2/s); Circulation on blade 3 at node 2; +AeroDyn['B3N3Gam'] = False # (m^2/s); Circulation on blade 3 at node 3; +AeroDyn['B3N4Gam'] = False # (m^2/s); Circulation on blade 3 at node 4; +AeroDyn['B3N5Gam'] = False # (m^2/s); Circulation on blade 3 at node 5; +AeroDyn['B3N6Gam'] = False # (m^2/s); Circulation on blade 3 at node 6; +AeroDyn['B3N7Gam'] = False # (m^2/s); Circulation on blade 3 at node 7; +AeroDyn['B3N8Gam'] = False # (m^2/s); Circulation on blade 3 at node 8; +AeroDyn['B3N9Gam'] = False # (m^2/s); Circulation on blade 3 at node 9; # Rotor AeroDyn['RtSpeed'] = False # (rpm); Rotor speed; @@ -2555,6 +3228,267 @@ AeroDyn['RtFldCq'] = False # (-); Rotor aerodynamic torque coefficient; AeroDyn['RtFldCt'] = False # (-); Rotor aerodynamic thrust coefficient; +""" ElastoDyn_Nodes """ +ElastoDyn_Nodes = {} + +# Local Span Motions +ElastoDyn_Nodes['ALx'] = False # (m/s^2); local flapwise acceleration (absolute) of node; Directed along the local xb-axis +ElastoDyn_Nodes['Ax'] = False # (m/s^2); local flapwise acceleration (absolute) of node; Directed along the local xb-axis +ElastoDyn_Nodes['ALy'] = False # (m/s^2); local flapwise acceleration (absolute) of node; Directed along the local yb-axis +ElastoDyn_Nodes['Ay'] = False # (m/s^2); local flapwise acceleration (absolute) of node; Directed along the local yb-axis +ElastoDyn_Nodes['ALz'] = False # (m/s^2); local flapwise acceleration (absolute) of node; Directed along the local zb-axis +ElastoDyn_Nodes['Az'] = False # (m/s^2); local flapwise acceleration (absolute) of node; Directed along the local zb-axis +ElastoDyn_Nodes['TDx'] = False # (m); local flapwise (translational) deflection (relative to the undeflected position) of node; Directed along the xb-axis +ElastoDyn_Nodes['UxB'] = False # (m); local flapwise (translational) deflection (relative to the undeflected position) of node; Directed along the xb-axis +ElastoDyn_Nodes['TDy'] = False # (m); local edgewise (translational) deflection (relative to the undeflected position) of node; Directed along the yb-axis +ElastoDyn_Nodes['UyB'] = False # (m); local edgewise (translational) deflection (relative to the undeflected position) of node; Directed along the yb-axis +ElastoDyn_Nodes['TDz'] = False # (m); local axial (translational) deflection (relative to the undeflected position) of node; Directed along the zb-axis +ElastoDyn_Nodes['UzB'] = False # (m); local axial (translational) deflection (relative to the undeflected position) of node; Directed along the zb-axis +ElastoDyn_Nodes['RDx'] = False # (deg); Local rotational displacement about x-axis (relative to undeflected); About the local xb-axis +ElastoDyn_Nodes['Rx'] = False # (deg); Local rotational displacement about x-axis (relative to undeflected); About the local xb-axis +ElastoDyn_Nodes['RDy'] = False # (deg); Local rotational displacement about y-axis (relative to undeflected); About the local yb-axis +ElastoDyn_Nodes['Ry'] = False # (deg); Local rotational displacement about y-axis (relative to undeflected); About the local yb-axis +ElastoDyn_Nodes['RDz'] = False # (deg); Local rotational displacement about z-axis (relative to undeflected); About the local zb-axis +ElastoDyn_Nodes['Rz'] = False # (deg); Local rotational displacement about z-axis (relative to undeflected); About the local zb-axis + +# Local Span Loads +ElastoDyn_Nodes['MLx'] = False # (kN-m); local edgewise moment at node; About the local xb-axis +ElastoDyn_Nodes['Mx'] = False # (kN-m); local edgewise moment at node; About the local xb-axis +ElastoDyn_Nodes['MLy'] = False # (kN-m); local flapwise moment at node; About the local yb-axis +ElastoDyn_Nodes['My'] = False # (kN-m); local flapwise moment at node; About the local yb-axis +ElastoDyn_Nodes['MLz'] = False # (kN-m); local pitching moment at node; About the local zb-axis +ElastoDyn_Nodes['MLzNT'] = False # (kN-m); local pitching moment at node; About the local zb-axis +ElastoDyn_Nodes['MzL'] = False # (kN-m); local pitching moment at node; About the local zb-axis +ElastoDyn_Nodes['Mz'] = False # (kN-m); local pitching moment at node; About the local zb-axis +ElastoDyn_Nodes['FLx'] = False # (kN); local flapwise shear force at node; Directed along the local xb-axis +ElastoDyn_Nodes['Fx'] = False # (kN); local flapwise shear force at node; Directed along the local xb-axis +ElastoDyn_Nodes['FLy'] = False # (kN); local edgewise shear force at node; Directed along the local yb-axis +ElastoDyn_Nodes['Fy'] = False # (kN); local edgewise shear force at node; Directed along the local yb-axis +ElastoDyn_Nodes['FLz'] = False # (kN); local axial force at node; Directed along the local zb-axis +ElastoDyn_Nodes['FLzNT'] = False # (kN); local axial force at node; Directed along the local zb-axis +ElastoDyn_Nodes['FzL'] = False # (kN); local axial force at node; Directed along the local zb-axis +ElastoDyn_Nodes['Fz'] = False # (kN); local axial force at node; Directed along the local zb-axis +ElastoDyn_Nodes['MLxNT'] = False # (kN-m); Edgewise moment in local coordinate system (initial structural twist removed); About the local xb-axis +ElastoDyn_Nodes['MxL'] = False # (kN-m); Edgewise moment in local coordinate system (initial structural twist removed); About the local xb-axis +ElastoDyn_Nodes['MlyNT'] = False # (kN-m); Flapwise shear moment in local coordinate system (initial structural twist removed); About the local yb-axis +ElastoDyn_Nodes['MyL'] = False # (kN-m); Flapwise shear moment in local coordinate system (initial structural twist removed); About the local yb-axis +ElastoDyn_Nodes['FLxNT'] = False # (kN); Flapwise shear force in local coordinate system (initial structural twist removed); Directed along the local xb-axis +ElastoDyn_Nodes['FxL'] = False # (kN); Flapwise shear force in local coordinate system (initial structural twist removed); Directed along the local xb-axis +ElastoDyn_Nodes['FlyNT'] = False # (kN); Edgewise shear force in local coordinate system (initial structural twist removed); Directed along the local yb-axis +ElastoDyn_Nodes['FyL'] = False # (kN); Edgewise shear force in local coordinate system (initial structural twist removed); Directed along the local yb-axis + + +""" BeamDyn_Nodes """ +BeamDyn_Nodes = {} + +# Sectional Loads +BeamDyn_Nodes['FxL'] = False # (N); Sectional force resultants at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FyL'] = False # (N); Sectional force resultants at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FzL'] = False # (N); Sectional force resultants at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MxL'] = False # (N-m); Sectional moment resultants at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MyL'] = False # (N-m); Sectional moment resultants at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MzL'] = False # (N-m); Sectional moment resultants at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['Fxr'] = False # (N); Sectional force resultants at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['Fyr'] = False # (N); Sectional force resultants at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['Fzr'] = False # (N); Sectional force resultants at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['Mxr'] = False # (N-m); Sectional moment resultants at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['Myr'] = False # (N-m); Sectional moment resultants at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['Mzr'] = False # (N-m); Sectional moment resultants at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system + +# Sectional Motions +BeamDyn_Nodes['TDxr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TDyr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TDzr'] = False # (m); Sectional translational deflection (relative to the undeflected position) at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RDxr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RDyr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RDzr'] = False # (-); Sectional angular/rotational deflection Wiener-Milenkovic parameter (relative to the undeflected orientation) at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['AbsXg'] = False # (m); Node position in X (global coordinate) ; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['AbsYg'] = False # (m); Node position in Y (global coordinate) ; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['AbsZg'] = False # (m); Node position in Z (global coordinate) ; g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['AbsXr'] = False # (m); Node position in X (relative to root) ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['AbsYr'] = False # (m); Node position in Y (relative to root) ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['AbsZr'] = False # (m); Node position in Z (relative to root) ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TVxg'] = False # (m/s); Sectional translational velocities (absolute); g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['TVyg'] = False # (m/s); Sectional translational velocities (absolute); g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['TVzg'] = False # (m/s); Sectional translational velocities (absolute); g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['TVxl'] = False # (m/s); Sectional translational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['TVyl'] = False # (m/s); Sectional translational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['TVzl'] = False # (m/s); Sectional translational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['TVxr'] = False # (m/s); Sectional translational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TVyr'] = False # (m/s); Sectional translational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TVzr'] = False # (m/s); Sectional translational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RVxg'] = False # (deg/s); Sectional angular/rotational velocities (absolute); g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['RVyg'] = False # (deg/s); Sectional angular/rotational velocities (absolute); g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['RVzg'] = False # (deg/s); Sectional angular/rotational velocities (absolute); g: the global inertial frame coordinate system; when coupled to FAST, this is equivalent to FAST s global inertial frame (i) coordinate system +BeamDyn_Nodes['RVxl'] = False # (deg/s); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['RVyl'] = False # (deg/s); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['RVzl'] = False # (deg/s); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['RVxr'] = False # (deg/s); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RVyr'] = False # (deg/s); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RVzr'] = False # (deg/s); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TAxl'] = False # (m/s^2); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['TAyl'] = False # (m/s^2); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['TAzl'] = False # (m/s^2); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['TAxr'] = False # (m/s^2); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TAyr'] = False # (m/s^2); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['TAzr'] = False # (m/s^2); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RAxl'] = False # (deg/s^2); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['RAyl'] = False # (deg/s^2); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['RAzl'] = False # (deg/s^2); Sectional angular/rotational velocities (absolute); l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['RAxr'] = False # (deg/s^2); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RAyr'] = False # (deg/s^2); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['RAzr'] = False # (deg/s^2); Sectional angular/rotational velocities (absolute); r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system + +# Applied Loads +BeamDyn_Nodes['PFxL'] = False # (N); Applied point forces at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['PFyL'] = False # (N); Applied point forces at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['PFzL'] = False # (N); Applied point forces at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['PMxL'] = False # (N-m); Applied point moments at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['PMyL'] = False # (N-m); Applied point moments at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['PMzL'] = False # (N-m); Applied point moments at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DFxL'] = False # (N/m); Applied distributed forces at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DFyL'] = False # (N/m); Applied distributed forces at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DFzL'] = False # (N/m); Applied distributed forces at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DMxL'] = False # (N-m/m); Applied distributed moments at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DMyL'] = False # (N-m/m); Applied distributed moments at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DMzL'] = False # (N-m/m); Applied distributed moments at each node expressed in l; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['DFxR'] = False # (N/m); Applied distributed forces at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['DFyR'] = False # (N/m); Applied distributed forces at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['DFzR'] = False # (N/m); Applied distributed forces at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['DMxR'] = False # (N-m/m); Applied distributed forces at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['DMyR'] = False # (N-m/m); Applied distributed forces at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['DMzR'] = False # (N-m/m); Applied distributed forces at each node expressed in r; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system + +# Sectional Partial Loads (debugging) +BeamDyn_Nodes['FFbxl'] = False # (N); Gyroscopic force x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFbyl'] = False # (N); Gyroscopic force y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFbzl'] = False # (N); Gyroscopic force z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFbxr'] = False # (N); Gyroscopic force x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFbyr'] = False # (N); Gyroscopic force y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFbzr'] = False # (N); Gyroscopic force z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFbxl'] = False # (N-m); Gyroscopic moment about x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFbyl'] = False # (N-m); Gyroscopic moment about y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFbzl'] = False # (N-m); Gyroscopic moment about z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFbxr'] = False # (N-m); Gyroscopic moment about x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFbyr'] = False # (N-m); Gyroscopic moment about y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFbzr'] = False # (N-m); Gyroscopic moment about z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFcxl'] = False # (N); Elastic restoring force Fc x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFcyl'] = False # (N); Elastic restoring force Fc y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFczl'] = False # (N); Elastic restoring force Fc z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFcxr'] = False # (N); Elastic restoring force Fc x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFcyr'] = False # (N); Elastic restoring force Fc y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFczr'] = False # (N); Elastic restoring force Fc z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFcxl'] = False # (N-m); Elastic restoring moment Fc about x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFcyl'] = False # (N-m); Elastic restoring moment Fc about y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFczl'] = False # (N-m); Elastic restoring moment Fc about z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFcxr'] = False # (N-m); Elastic restoring moment Fc about x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFcyr'] = False # (N-m); Elastic restoring moment Fc about y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFczr'] = False # (N-m); Elastic restoring moment Fc about z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFdxl'] = False # (N); Elastic restoring force Fd x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFdyl'] = False # (N); Elastic restoring force Fd y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFdzl'] = False # (N); Elastic restoring force Fd z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFdxr'] = False # (N); Elastic restoring force Fd x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFdyr'] = False # (N); Elastic restoring force Fd y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFdzr'] = False # (N); Elastic restoring force Fd z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFdxl'] = False # (N-m); Elastic restoring moment Fd about x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFdyl'] = False # (N-m); Elastic restoring moment Fd about y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFdzl'] = False # (N-m); Elastic restoring moment Fd about z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFdxr'] = False # (N-m); Elastic restoring moment Fd about x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFdyr'] = False # (N-m); Elastic restoring moment Fd about y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFdzr'] = False # (N-m); Elastic restoring moment Fd about z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFgxl'] = False # (N); Gravity force x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFgyl'] = False # (N); Gravity force y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFgzl'] = False # (N); Gravity force z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFgxr'] = False # (N); Gravity force x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFgyr'] = False # (N); Gravity force y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFgzr'] = False # (N); Gravity force z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFgxl'] = False # (N-m); Gravity moment about x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFgyl'] = False # (N-m); Gravity moment about y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFgzl'] = False # (N-m); Gravity moment about z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFgxr'] = False # (N-m); Gravity moment about x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFgyr'] = False # (N-m); Gravity moment about y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFgzr'] = False # (N-m); Gravity moment about z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFixl'] = False # (N); Inertial force x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFiyl'] = False # (N); Inertial force y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFizl'] = False # (N); Inertial force z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['FFixr'] = False # (N); Inertial force x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFiyr'] = False # (N); Inertial force y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['FFizr'] = False # (N); Inertial force z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFixl'] = False # (N-m); Inertial moment about x ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFiyl'] = False # (N-m); Inertial moment about y ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFizl'] = False # (N-m); Inertial moment about z ; l: a floating coordinate system local to the deflected beam +BeamDyn_Nodes['MFixr'] = False # (N-m); Inertial moment about x ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFiyr'] = False # (N-m); Inertial moment about y ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system +BeamDyn_Nodes['MFizr'] = False # (N-m); Inertial moment about z ; r: a floating reference coordinate system fixed to the root of the moving beam; when coupled to FAST for blades, this is equivalent to the IEC blade (b) coordinate system + + +""" AeroDyn_Nodes """ +AeroDyn_Nodes = {} + +# Blade +AeroDyn_Nodes['VUndx'] = False # (m/s); x-component of undisturbed wind velocity at each node; local blade coordinate system +AeroDyn_Nodes['VUndy'] = False # (m/s); y-component of undisturbed wind velocity at each node; local blade coordinate system +AeroDyn_Nodes['VUndz'] = False # (m/s); z-component of undisturbed wind velocity at each node; local blade coordinate system +AeroDyn_Nodes['Vundxi'] = False # (m/s); x-component of undisturbed wind velocity at each node; inertial/global coordinate system +AeroDyn_Nodes['Vundyi'] = False # (m/s); y-component of undisturbed wind velocity at each node; inertial/global coordinate system +AeroDyn_Nodes['Vundzi'] = False # (m/s); z-component of undisturbed wind velocity at each node; inertial/global coordinate system +AeroDyn_Nodes['VDisx'] = False # (m/s); x-component of disturbed wind velocity at each node; local blade coordinate system +AeroDyn_Nodes['VDisy'] = False # (m/s); y-component of disturbed wind velocity at each node; local blade coordinate system +AeroDyn_Nodes['VDisz'] = False # (m/s); z-component of disturbed wind velocity at each node; local blade coordinate system +AeroDyn_Nodes['STVx'] = False # (m/s); x-component of structural translational velocity at each node; local blade coordinate system +AeroDyn_Nodes['STVy'] = False # (m/s); y-component of structural translational velocity at each node; local blade coordinate system +AeroDyn_Nodes['STVz'] = False # (m/s); z-component of structural translational velocity at each node; local blade coordinate system +AeroDyn_Nodes['VRel'] = False # (m/s); Relvative wind speed at each node; +AeroDyn_Nodes['DynP'] = False # (Pa); Dynamic pressure at each node; +AeroDyn_Nodes['Re'] = False # (-); Reynolds number (in millions) at each node; +AeroDyn_Nodes['M'] = False # (-); Mach number at each node; +AeroDyn_Nodes['Vindx'] = False # (m/s); Axial induced wind velocity at each node; +AeroDyn_Nodes['Vindy'] = False # (m/s); Tangential induced wind velocity at each node; +AeroDyn_Nodes['AxInd'] = False # (-); Axial induction factor at each node; +AeroDyn_Nodes['TnInd'] = False # (-); Tangential induction factor at each node; +AeroDyn_Nodes['Alpha'] = False # (deg); Angle of attack at each node; +AeroDyn_Nodes['Theta'] = False # (deg); Pitch+Twist angle at each node; +AeroDyn_Nodes['Phi'] = False # (deg); Inflow angle at each node; +AeroDyn_Nodes['Curve'] = False # (deg); Curvature angle at each node; +AeroDyn_Nodes['Cl'] = False # (-); Lift force coefficient at each node, including unsteady effects; +AeroDyn_Nodes['Cd'] = False # (-); Drag force coefficient at each node, including unsteady effects; +AeroDyn_Nodes['Cm'] = False # (-); Pitching moment coefficient at each node, including unsteady effects; +AeroDyn_Nodes['Cx'] = False # (-); Normal force (to plane) coefficient at each node; +AeroDyn_Nodes['Cy'] = False # (-); Tangential force (to plane) coefficient at each node; +AeroDyn_Nodes['Cn'] = False # (-); Normal force (to chord) coefficient at each node; +AeroDyn_Nodes['Ct'] = False # (-); Tangential force (to chord) coefficient at each node; +AeroDyn_Nodes['Fl'] = False # (N/m); Lift force per unit length at each node; +AeroDyn_Nodes['Fd'] = False # (N/m); Drag force per unit length at each node; +AeroDyn_Nodes['Mm'] = False # (N-m/m); Pitching moment per unit length at each node; +AeroDyn_Nodes['Fx'] = False # (N/m); Normal force (to plane) per unit length at each node; +AeroDyn_Nodes['Fy'] = False # (N/m); Tangential force (to plane) per unit length at each node; +AeroDyn_Nodes['Fn'] = False # (N/m); Normal force (to chord) per unit length at each node; +AeroDyn_Nodes['Ft'] = False # (N/m); Tangential force (to chord) per unit length at each node; +AeroDyn_Nodes['Clrnc'] = False # (m); Tower clearance at each node (based on the absolute distance to the nearest point in the tower from blade node B#N# minus the local tower radius, in the deflected configuration); please note that this clearance is only approximate because the calculation assumes that the blade is a line with no volume (however, the calculation does use the local tower radius); when blade node B#N# is above the tower top (or below the tower base), the absolute distance to the tower top (or base) minus the local tower radius, in the deflected configuration, is output; +AeroDyn_Nodes['Vx'] = False # (m/s); Local axial velocity; +AeroDyn_Nodes['Vy'] = False # (m/s); Local tangential velocity; +AeroDyn_Nodes['GeomPhi'] = False # (1/0); Geometric phi? If phi was solved using normal BEMT equations, GeomPhi = 1; otherwise, if it was solved geometrically, GeomPhi = 0.; +AeroDyn_Nodes['Chi'] = False # (deg); Skew angle (used in skewed wake correction); +AeroDyn_Nodes['UA_Flag'] = False # (-); Flag indicating if UA is turned on for this node.; +AeroDyn_Nodes['UA_x1'] = False # (rad); time-history of wake vorticity contributing to effective angle of attack; +AeroDyn_Nodes['UA_x2'] = False # (rad); time-history of wake vorticity contributing to effective angle of attack; +AeroDyn_Nodes['UA_x3'] = False # (-); dimension of cl (UAMod4) or cn (UAMod5); lagging the fully-attached coefficient; +AeroDyn_Nodes['UA_x4'] = False # (-); UAMod4 and 5 separation factor; +AeroDyn_Nodes['UA_x5'] = False # (-); UAMod5 vortex term; +AeroDyn_Nodes['Debug1'] = False # (-); Placeholders for debugging channels; +AeroDyn_Nodes['Debug2'] = False # (-); Placeholders for debugging channels; +AeroDyn_Nodes['Debug3'] = False # (-); Placeholders for debugging channels; +AeroDyn_Nodes['CpMin'] = False # (-); Pressure coefficient; +AeroDyn_Nodes['SgCav'] = False # (-); Cavitation number; +AeroDyn_Nodes['SigCr'] = False # (-); Critical cavitation number; +AeroDyn_Nodes['Gam'] = False # (m^2/s); Gamma -- circulation on blade; +AeroDyn_Nodes['Cl_Static'] = False # (-); Static portion of lift force coefficient at each node, without unsteady effects; +AeroDyn_Nodes['Cd_Static'] = False # (-); Static portion of drag force coefficient at each node, without unsteady effects; +AeroDyn_Nodes['Cm_Static'] = False # (-); Static portion of pitching moment coefficient at each node, without unsteady effects; +AeroDyn_Nodes['Uin'] = False # (m/s); Axial induced velocity in rotating hub coordinates. Axial aligned with hub axis.; rotor plane polar hub rotating coordinates +AeroDyn_Nodes['Uit'] = False # (m/s); Tangential induced velocity in rotating hub coordinates. Tangential to the rotation plane. Perpendicular to blade aziumth.; rotor plane polar hub rotating coordinates +AeroDyn_Nodes['Uir'] = False # (m/s); Radial induced velocity in rotating hub coordinates. Radial outwards in rotation plane. Aligned with blade azimuth.; rotor plane polar hub rotating coordinates + """ InflowWind """ InflowWind = {} @@ -2588,6 +3522,35 @@ InflowWind['Wind9VelY'] = False # (m/s); Y component of wind at user selected wind point 9; Directed along the yi-axis InflowWind['Wind9VelZ'] = False # (m/s); Z component of wind at user selected wind point 9; Directed along the zi-axis +# Wind Magnitude and Direction +InflowWind['Wind1VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 1; +InflowWind['Wind2VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 2; +InflowWind['Wind3VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 3; +InflowWind['Wind4VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 4; +InflowWind['Wind5VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 5; +InflowWind['Wind6VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 6; +InflowWind['Wind7VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 7; +InflowWind['Wind8VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 8; +InflowWind['Wind9VelXY'] = False # (m/s); XY (horizontal) wind magnitude at user selected wind point 9; +InflowWind['Wind1VelMag'] = False # (m/s); wind magnitude at user selected wind point 1; +InflowWind['Wind2VelMag'] = False # (m/s); wind magnitude at user selected wind point 2; +InflowWind['Wind3VelMag'] = False # (m/s); wind magnitude at user selected wind point 3; +InflowWind['Wind4VelMag'] = False # (m/s); wind magnitude at user selected wind point 4; +InflowWind['Wind5VelMag'] = False # (m/s); wind magnitude at user selected wind point 5; +InflowWind['Wind6VelMag'] = False # (m/s); wind magnitude at user selected wind point 6; +InflowWind['Wind7VelMag'] = False # (m/s); wind magnitude at user selected wind point 7; +InflowWind['Wind8VelMag'] = False # (m/s); wind magnitude at user selected wind point 8; +InflowWind['Wind9VelMag'] = False # (m/s); wind magnitude at user selected wind point 9; +InflowWind['Wind1AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 1; +InflowWind['Wind2AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 2; +InflowWind['Wind3AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 3; +InflowWind['Wind4AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 4; +InflowWind['Wind5AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 5; +InflowWind['Wind6AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 6; +InflowWind['Wind7AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 7; +InflowWind['Wind8AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 8; +InflowWind['Wind9AngXY'] = False # (deg); Angle between X and Y wind velocity components at user selected wind point 9; + # Wind Sensor Measurements InflowWind['WindMeas1'] = False # (m/s); Wind measurement at sensor 1; Defined by sensor InflowWind['WindMeas2'] = False # (m/s); Wind measurement at sensor 2; Defined by sensor @@ -2641,52 +3604,552 @@ """ HydroDyn """ HydroDyn = {} -# Forces due to additional preload, stiffness, and damping -HydroDyn['AddFxi'] = False # (N); ; -HydroDyn['AddFyi'] = False # (N); ; -HydroDyn['AddFzi'] = False # (N); ; -HydroDyn['AddMxi'] = False # (N m); ; -HydroDyn['AddMyi'] = False # (N m); ; -HydroDyn['AddMzi'] = False # (N m); ; - -# Integrated hydrodynamic loads at the WAMIT reference point -HydroDyn['HydroFxi'] = False # (N); ; -HydroDyn['HydroFyi'] = False # (N); ; -HydroDyn['HydroFzi'] = False # (N); ; -HydroDyn['HydroMxi'] = False # (N m); ; -HydroDyn['HydroMyi'] = False # (N m); ; -HydroDyn['HydroMzi'] = False # (N m); ; +# Integrated Hydrodynamic Loads at (0,0,0) +HydroDyn['HydroFxi'] = False # (N); Total integrated hydrodynamic load along the global x-direction from both potential flow and strip theory at (0,0,0); +HydroDyn['HydroFyi'] = False # (N); Total integrated hydrodynamic load along the global y-direction from both potential flow and strip theory at (0,0,0); +HydroDyn['HydroFzi'] = False # (N); Total integrated hydrodynamic load along the global z-direction from both potential flow and strip theory at (0,0,0); +HydroDyn['HydroMxi'] = False # (N-m); Total integrated hydrodynamic moment about the global x-axis from both potential flow and strip theory at (0,0,0); +HydroDyn['HydroMyi'] = False # (N-m); Total integrated hydrodynamic moment about the global y-axis from both potential flow and strip theory at (0,0,0); +HydroDyn['HydroMzi'] = False # (N-m); Total integrated hydrodynamic moment about the global z-axis from both potential flow and strip theory at (0,0,0); + +# PRP Body Kinematics +HydroDyn['PRPSurge'] = False # (m); Displacement of the PRP (principal reference point) along the global x-axis; +HydroDyn['PRPSway'] = False # (m); Displacement of the PRP (principal reference point) along the global y-axis; +HydroDyn['PRPHeave'] = False # (m); Displacement of the PRP (principal reference point) along the global z-axis; +HydroDyn['PRPRoll'] = False # (rad); Rotation of the PRP (principal reference point) about the global x-axis at the PRP; +HydroDyn['PRPPitch'] = False # (rad); Rotation of the PRP (principal reference point) about the global y-axis at the PRP; +HydroDyn['PRPYaw'] = False # (rad); Rotation of the PRP (principal reference point) about the global z-axis at the PRP; +HydroDyn['PRPTVxi'] = False # (m/s); Translational velocity of the PRP (principal reference point) along the global x-axis; +HydroDyn['PRPTVyi'] = False # (m/s); Translational velocity of the PRP (principal reference point) along the global y-axis; +HydroDyn['PRPTVzi'] = False # (m/s); Translational velocity of the PRP (principal reference point) along the global z-axis; +HydroDyn['PRPRVxi'] = False # (rad/s); Rotation velocity of the PRP (principal reference point) about the global x-axis at the PRP; +HydroDyn['PRPRVyi'] = False # (rad/s); Rotation velocity of the PRP (principal reference point) about the global y-axis at the PRP; +HydroDyn['PRPRVzi'] = False # (rad/s); Rotation velocity of the PRP (principal reference point) about the global z-axis at the PRP; +HydroDyn['PRPTAxi'] = False # (m/s^2); Translational acceleration of the PRP (principal reference point) along the global x-axis; +HydroDyn['PRPTAyi'] = False # (m/s^2); Translational acceleration of the PRP (principal reference point) along the global y-axis; +HydroDyn['PRPTAzi'] = False # (m/s^2); Translational acceleration of the PRP (principal reference point) along the global z-axis; +HydroDyn['PRPRAxi'] = False # (rad/s^2); Rotation acceleration of the PRP (principal reference point) about the global x-axis at the PRP; +HydroDyn['PRPRAyi'] = False # (rad/s^2); Rotation acceleration of the PRP (principal reference point) about the global y-axis at the PRP; +HydroDyn['PRPRAzi'] = False # (rad/s^2); Rotation acceleration of the PRP (principal reference point) about the global z-axis at the PRP; + +# WAMIT Body Kinematics +HydroDyn['B1Surge'] = False # (m); Displacement of the 1st WAMIT body along the global x-axis; +HydroDyn['B1Sway'] = False # (m); Displacement of the 1st WAMIT body along the global y-axis; +HydroDyn['B1Heave'] = False # (m); Displacement of the 1st WAMIT body along the global z-axis; +HydroDyn['B1Roll'] = False # (rad); Rotation of the 1st WAMIT body about the global x-axis at the 1st WAMIT body's reference point; +HydroDyn['B1Pitch'] = False # (rad); Rotation of the 1st WAMIT body about the global y-axis at the 1st WAMIT body's reference point; +HydroDyn['B1Yaw'] = False # (rad); Rotation of the 1st WAMIT body about the global z-axis at the 1st WAMIT body's reference point; +HydroDyn['B1TVxi'] = False # (m/s); Translational velocity of the 1st WAMIT body along the global x-axis; +HydroDyn['B1TVyi'] = False # (m/s); Translational velocity of the 1st WAMIT body along the global y-axis; +HydroDyn['B1TVzi'] = False # (m/s); Translational velocity of the 1st WAMIT body along the global z-axis; +HydroDyn['B1RVxi'] = False # (rad/s); Rotational velocity of the 1st WAMIT body about the global x-axis at the 1st WAMIT body's reference point; +HydroDyn['B1RVyi'] = False # (rad/s); Rotational velocity of the 1st WAMIT body about the global y-axis at the 1st WAMIT body's reference point; +HydroDyn['B1RVzi'] = False # (rad/s); Rotational velocity of the 1st WAMIT body about the global z-axis at the 1st WAMIT body's reference point; +HydroDyn['B1TAxi'] = False # (m/s^2); Translational acceleration of the 1st WAMIT body along the global x-axis; +HydroDyn['B1TAyi'] = False # (m/s^2); Translational acceleration of the 1st WAMIT body along the global y-axis; +HydroDyn['B1TAzi'] = False # (m/s^2); Translational acceleration of the 1st WAMIT body along the global z-axis; +HydroDyn['B1RAxi'] = False # (rad/s^2); Rotational acceleration of the 1st WAMIT body about the global x-axis at the 1st WAMIT body's reference point; +HydroDyn['B1RAyi'] = False # (rad/s^2); Rotational acceleration of the 1st WAMIT body about the global y-axis at the 1st WAMIT body's reference point; +HydroDyn['B1RAzi'] = False # (rad/s^2); Rotational acceleration of the 1st WAMIT body about the global z-axis at the 1st WAMIT body's reference point; +HydroDyn['B2Surge'] = False # (m); Displacement of the 2nd WAMIT body along the global x-axis; +HydroDyn['B2Sway'] = False # (m); Displacement of the 2nd WAMIT body along the global y-axis; +HydroDyn['B2Heave'] = False # (m); Displacement of the 2nd WAMIT body along the global z-axis; +HydroDyn['B2Roll'] = False # (rad); Rotation of the 2nd WAMIT body about the global x-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2Pitch'] = False # (rad); Rotation of the 2nd WAMIT body about the global y-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2Yaw'] = False # (rad); Rotation of the 2nd WAMIT body about the global z-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2TVxi'] = False # (m/s); Translational velocity of the 2nd WAMIT body along the global x-axis; +HydroDyn['B2TVyi'] = False # (m/s); Translational velocity of the 2nd WAMIT body along the global y-axis; +HydroDyn['B2TVzi'] = False # (m/s); Translational velocity of the 2nd WAMIT body along the global z-axis; +HydroDyn['B2RVxi'] = False # (rad/s); Rotational velocity of the 2nd WAMIT body about the global x-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2RVyi'] = False # (rad/s); Rotational velocity of the 2nd WAMIT body about the global y-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2RVzi'] = False # (rad/s); Rotational velocity of the 2nd WAMIT body about the global z-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2TAxi'] = False # (m/s^2); Translational acceleration of the 2nd WAMIT body along the global x-axis; +HydroDyn['B2TAyi'] = False # (m/s^2); Translational acceleration of the 2nd WAMIT body along the global y-axis; +HydroDyn['B2TAzi'] = False # (m/s^2); Translational acceleration of the 2nd WAMIT body along the global z-axis; +HydroDyn['B2RAxi'] = False # (rad/s^2); Rotational acceleration of the 2nd WAMIT body about the global x-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2RAyi'] = False # (rad/s^2); Rotational acceleration of the 2nd WAMIT body about the global y-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2RAzi'] = False # (rad/s^2); Rotational acceleration of the 2nd WAMIT body about the global z-axis at the 2nd WAMIT body's reference point; +HydroDyn['B3Surge'] = False # (m); Displacement of the 3rd WAMIT body along the global x-axis; +HydroDyn['B3Sway'] = False # (m); Displacement of the 3rd WAMIT body along the global y-axis; +HydroDyn['B3Heave'] = False # (m); Displacement of the 3rd WAMIT body along the global z-axis; +HydroDyn['B3Roll'] = False # (rad); Rotation of the 3rd WAMIT body about the global x-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3Pitch'] = False # (rad); Rotation of the 3rd WAMIT body about the global y-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3Yaw'] = False # (rad); Rotation of the 3rd WAMIT body about the global z-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3TVxi'] = False # (m/s); Translational velocity of the 3rd WAMIT body along the global x-axis; +HydroDyn['B3TVyi'] = False # (m/s); Translational velocity of the 3rd WAMIT body along the global y-axis; +HydroDyn['B3TVzi'] = False # (m/s); Translational velocity of the 3rd WAMIT body along the global z-axis; +HydroDyn['B3RVxi'] = False # (rad/s); Rotational velocity of the 3rd WAMIT body about the global x-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3RVyi'] = False # (rad/s); Rotational velocity of the 3rd WAMIT body about the global y-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3RVzi'] = False # (rad/s); Rotational velocity of the 3rd WAMIT body about the global z-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3TAxi'] = False # (m/s^2); Translational acceleration of the 3rd WAMIT body along the global x-axis; +HydroDyn['B3TAyi'] = False # (m/s^2); Translational acceleration of the 3rd WAMIT body along the global y-axis; +HydroDyn['B3TAzi'] = False # (m/s^2); Translational acceleration of the 3rd WAMIT body along the global z-axis; +HydroDyn['B3RAxi'] = False # (rad/s^2); Rotational acceleration of the 3rd WAMIT body about the global x-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3RAyi'] = False # (rad/s^2); Rotational acceleration of the 3rd WAMIT body about the global y-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3RAzi'] = False # (rad/s^2); Rotational acceleration of the 3rd WAMIT body about the global z-axis at the 3rd WAMIT body's reference point; +HydroDyn['B4Surge'] = False # (m); Displacement of the 4th WAMIT body along the global x-axis; +HydroDyn['B4Sway'] = False # (m); Displacement of the 4th WAMIT body along the global y-axis; +HydroDyn['B4Heave'] = False # (m); Displacement of the 4th WAMIT body along the global z-axis; +HydroDyn['B4Roll'] = False # (rad); Rotation of the 4th WAMIT body about the global x-axis at the 4th WAMIT body's reference point; +HydroDyn['B4Pitch'] = False # (rad); Rotation of the 4th WAMIT body about the global y-axis at the 4th WAMIT body's reference point; +HydroDyn['B4Yaw'] = False # (rad); Rotation of the 4th WAMIT body about the global z-axis at the 4th WAMIT body's reference point; +HydroDyn['B4TVxi'] = False # (m/s); Translational velocity of the 4th WAMIT body along the global x-axis; +HydroDyn['B4TVyi'] = False # (m/s); Translational velocity of the 4th WAMIT body along the global y-axis; +HydroDyn['B4TVzi'] = False # (m/s); Translational velocity of the 4th WAMIT body along the global z-axis; +HydroDyn['B4RVxi'] = False # (rad/s); Rotational velocity of the 4th WAMIT body about the global x-axis at the 4th WAMIT body's reference point; +HydroDyn['B4RVyi'] = False # (rad/s); Rotational velocity of the 4th WAMIT body about the global y-axis at the 4th WAMIT body's reference point; +HydroDyn['B4RVzi'] = False # (rad/s); Rotational velocity of the 4th WAMIT body about the global z-axis at the 4th WAMIT body's reference point; +HydroDyn['B4TAxi'] = False # (m/s^2); Translational acceleration of the 4th WAMIT body along the global x-axis; +HydroDyn['B4TAyi'] = False # (m/s^2); Translational acceleration of the 4th WAMIT body along the global y-axis; +HydroDyn['B4TAzi'] = False # (m/s^2); Translational acceleration of the 4th WAMIT body along the global z-axis; +HydroDyn['B4RAxi'] = False # (rad/s^2); Rotational acceleration of the 4th WAMIT body about the global x-axis at the 4th WAMIT body's reference point; +HydroDyn['B4RAyi'] = False # (rad/s^2); Rotational acceleration of the 4th WAMIT body about the global y-axis at the 4th WAMIT body's reference point; +HydroDyn['B4RAzi'] = False # (rad/s^2); Rotational acceleration of the 4th WAMIT body about the global z-axis at the 4th WAMIT body's reference point; +HydroDyn['B5Surge'] = False # (m); Displacement of the 5th WAMIT body along the global x-axis; +HydroDyn['B5Sway'] = False # (m); Displacement of the 5th WAMIT body along the global y-axis; +HydroDyn['B5Heave'] = False # (m); Displacement of the 5th WAMIT body along the global z-axis; +HydroDyn['B5Roll'] = False # (rad); Rotation of the 5th WAMIT body about the global x-axis at the 5th WAMIT body's reference point; +HydroDyn['B5Pitch'] = False # (rad); Rotation of the 5th WAMIT body about the global y-axis at the 5th WAMIT body's reference point; +HydroDyn['B5Yaw'] = False # (rad); Rotation of the 5th WAMIT body about the global z-axis at the 5th WAMIT body's reference point; +HydroDyn['B5TVxi'] = False # (m/s); Translational velocity of the 5th WAMIT body along the global x-axis; +HydroDyn['B5TVyi'] = False # (m/s); Translational velocity of the 5th WAMIT body along the global y-axis; +HydroDyn['B5TVzi'] = False # (m/s); Translational velocity of the 5th WAMIT body along the global z-axis; +HydroDyn['B5RVxi'] = False # (rad/s); Rotational velocity of the 5th WAMIT body about the global x-axis at the 5th WAMIT body's reference point; +HydroDyn['B5RVyi'] = False # (rad/s); Rotational velocity of the 5th WAMIT body about the global y-axis at the 5th WAMIT body's reference point; +HydroDyn['B5RVzi'] = False # (rad/s); Rotational velocity of the 5th WAMIT body about the global z-axis at the 5th WAMIT body's reference point; +HydroDyn['B5TAxi'] = False # (m/s^2); Translational acceleration of the 5th WAMIT body along the global x-axis; +HydroDyn['B5TAyi'] = False # (m/s^2); Translational acceleration of the 5th WAMIT body along the global y-axis; +HydroDyn['B5TAzi'] = False # (m/s^2); Translational acceleration of the 5th WAMIT body along the global z-axis; +HydroDyn['B5RAxi'] = False # (rad/s^2); Rotational acceleration of the 5th WAMIT body about the global x-axis at the 5th WAMIT body's reference point; +HydroDyn['B5RAyi'] = False # (rad/s^2); Rotational acceleration of the 5th WAMIT body about the global y-axis at the 5th WAMIT body's reference point; +HydroDyn['B5RAzi'] = False # (rad/s^2); Rotational acceleration of the 5th WAMIT body about the global z-axis at the 5th WAMIT body's reference point; +HydroDyn['B6Surge'] = False # (m); Displacement of the 6th WAMIT body along the global x-axis; +HydroDyn['B6Sway'] = False # (m); Displacement of the 6th WAMIT body along the global y-axis; +HydroDyn['B6Heave'] = False # (m); Displacement of the 6th WAMIT body along the global z-axis; +HydroDyn['B6Roll'] = False # (rad); Rotation of the 6th WAMIT body about the global x-axis at the 6th WAMIT body's reference point; +HydroDyn['B6Pitch'] = False # (rad); Rotation of the 6th WAMIT body about the global y-axis at the 6th WAMIT body's reference point; +HydroDyn['B6Yaw'] = False # (rad); Rotation of the 6th WAMIT body about the global z-axis at the 6th WAMIT body's reference point; +HydroDyn['B6TVxi'] = False # (m/s); Translational velocity of the 6th WAMIT body along the global x-axis; +HydroDyn['B6TVyi'] = False # (m/s); Translational velocity of the 6th WAMIT body along the global y-axis; +HydroDyn['B6TVzi'] = False # (m/s); Translational velocity of the 6th WAMIT body along the global z-axis; +HydroDyn['B6RVxi'] = False # (rad/s); Rotational velocity of the 6th WAMIT body about the global x-axis at the 6th WAMIT body's reference point; +HydroDyn['B6RVyi'] = False # (rad/s); Rotational velocity of the 6th WAMIT body about the global y-axis at the 6th WAMIT body's reference point; +HydroDyn['B6RVzi'] = False # (rad/s); Rotational velocity of the 6th WAMIT body about the global z-axis at the 6th WAMIT body's reference point; +HydroDyn['B6TAxi'] = False # (m/s^2); Translational acceleration of the 6th WAMIT body along the global x-axis; +HydroDyn['B6TAyi'] = False # (m/s^2); Translational acceleration of the 6th WAMIT body along the global y-axis; +HydroDyn['B6TAzi'] = False # (m/s^2); Translational acceleration of the 6th WAMIT body along the global z-axis; +HydroDyn['B6RAxi'] = False # (rad/s^2); Rotational acceleration of the 6th WAMIT body about the global x-axis at the 6th WAMIT body's reference point; +HydroDyn['B6RAyi'] = False # (rad/s^2); Rotational acceleration of the 6th WAMIT body about the global y-axis at the 6th WAMIT body's reference point; +HydroDyn['B6RAzi'] = False # (rad/s^2); Rotational acceleration of the 6th WAMIT body about the global z-axis at the 6th WAMIT body's reference point; +HydroDyn['B7Surge'] = False # (m); Displacement of the 7th WAMIT body along the global x-axis; +HydroDyn['B7Sway'] = False # (m); Displacement of the 7th WAMIT body along the global y-axis; +HydroDyn['B7Heave'] = False # (m); Displacement of the 7th WAMIT body along the global z-axis; +HydroDyn['B7Roll'] = False # (rad); Rotation of the 7th WAMIT body about the global x-axis at the 7th WAMIT body's reference point; +HydroDyn['B7Pitch'] = False # (rad); Rotation of the 7th WAMIT body about the global y-axis at the 7th WAMIT body's reference point; +HydroDyn['B7Yaw'] = False # (rad); Rotation of the 7th WAMIT body about the global z-axis at the 7th WAMIT body's reference point; +HydroDyn['B7TVxi'] = False # (m/s); Translational velocity of the 7th WAMIT body along the global x-axis; +HydroDyn['B7TVyi'] = False # (m/s); Translational velocity of the 7th WAMIT body along the global y-axis; +HydroDyn['B7TVzi'] = False # (m/s); Translational velocity of the 7th WAMIT body along the global z-axis; +HydroDyn['B7RVxi'] = False # (rad/s); Rotational velocity of the 7th WAMIT body about the global x-axis at the 7th WAMIT body's reference point; +HydroDyn['B7RVyi'] = False # (rad/s); Rotational velocity of the 7th WAMIT body about the global y-axis at the 7th WAMIT body's reference point; +HydroDyn['B7RVzi'] = False # (rad/s); Rotational velocity of the 7th WAMIT body about the global z-axis at the 7th WAMIT body's reference point; +HydroDyn['B7TAxi'] = False # (m/s^2); Translational acceleration of the 7th WAMIT body along the global x-axis; +HydroDyn['B7TAyi'] = False # (m/s^2); Translational acceleration of the 7th WAMIT body along the global y-axis; +HydroDyn['B7TAzi'] = False # (m/s^2); Translational acceleration of the 7th WAMIT body along the global z-axis; +HydroDyn['B7RAxi'] = False # (rad/s^2); Rotational acceleration of the 7th WAMIT body about the global x-axis at the 7th WAMIT body's reference point; +HydroDyn['B7RAyi'] = False # (rad/s^2); Rotational acceleration of the 7th WAMIT body about the global y-axis at the 7th WAMIT body's reference point; +HydroDyn['B7RAzi'] = False # (rad/s^2); Rotational acceleration of the 7th WAMIT body about the global z-axis at the 7th WAMIT body's reference point; +HydroDyn['B8Surge'] = False # (m); Displacement of the 8th WAMIT body along the global x-axis; +HydroDyn['B8Sway'] = False # (m); Displacement of the 8th WAMIT body along the global y-axis; +HydroDyn['B8Heave'] = False # (m); Displacement of the 8th WAMIT body along the global z-axis; +HydroDyn['B8Roll'] = False # (rad); Rotation of the 8th WAMIT body about the global x-axis at the 8th WAMIT body's reference point; +HydroDyn['B8Pitch'] = False # (rad); Rotation of the 8th WAMIT body about the global y-axis at the 8th WAMIT body's reference point; +HydroDyn['B8Yaw'] = False # (rad); Rotation of the 8th WAMIT body about the global z-axis at the 8th WAMIT body's reference point; +HydroDyn['B8TVxi'] = False # (m/s); Translational velocity of the 8th WAMIT body along the global x-axis; +HydroDyn['B8TVyi'] = False # (m/s); Translational velocity of the 8th WAMIT body along the global y-axis; +HydroDyn['B8TVzi'] = False # (m/s); Translational velocity of the 8th WAMIT body along the global z-axis; +HydroDyn['B8RVxi'] = False # (rad/s); Rotational velocity of the 8th WAMIT body about the global x-axis at the 8th WAMIT body's reference point; +HydroDyn['B8RVyi'] = False # (rad/s); Rotational velocity of the 8th WAMIT body about the global y-axis at the 8th WAMIT body's reference point; +HydroDyn['B8RVzi'] = False # (rad/s); Rotational velocity of the 8th WAMIT body about the global z-axis at the 8th WAMIT body's reference point; +HydroDyn['B8TAxi'] = False # (m/s^2); Translational acceleration of the 8th WAMIT body along the global x-axis; +HydroDyn['B8TAyi'] = False # (m/s^2); Translational acceleration of the 8th WAMIT body along the global y-axis; +HydroDyn['B8TAzi'] = False # (m/s^2); Translational acceleration of the 8th WAMIT body along the global z-axis; +HydroDyn['B8RAxi'] = False # (rad/s^2); Rotational acceleration of the 8th WAMIT body about the global x-axis at the 8th WAMIT body's reference point; +HydroDyn['B8RAyi'] = False # (rad/s^2); Rotational acceleration of the 8th WAMIT body about the global y-axis at the 8th WAMIT body's reference point; +HydroDyn['B8RAzi'] = False # (rad/s^2); Rotational acceleration of the 8th WAMIT body about the global z-axis at the 8th WAMIT body's reference point; +HydroDyn['B9Surge'] = False # (m); Displacement of the 9th WAMIT body along the global x-axis; +HydroDyn['B9Sway'] = False # (m); Displacement of the 9th WAMIT body along the global y-axis; +HydroDyn['B9Heave'] = False # (m); Displacement of the 9th WAMIT body along the global z-axis; +HydroDyn['B9Roll'] = False # (rad); Rotation of the 9th WAMIT body about the global x-axis at the 9th WAMIT body's reference point; +HydroDyn['B9Pitch'] = False # (rad); Rotation of the 9th WAMIT body about the global y-axis at the 9th WAMIT body's reference point; +HydroDyn['B9Yaw'] = False # (rad); Rotation of the 9th WAMIT body about the global z-axis at the 9th WAMIT body's reference point; +HydroDyn['B9TVxi'] = False # (m/s); Translational velocity of the 9th WAMIT body along the global x-axis; +HydroDyn['B9TVyi'] = False # (m/s); Translational velocity of the 9th WAMIT body along the global y-axis; +HydroDyn['B9TVzi'] = False # (m/s); Translational velocity of the 9th WAMIT body along the global z-axis; +HydroDyn['B9RVxi'] = False # (rad/s); Rotational velocity of the 9th WAMIT body about the global x-axis at the 9th WAMIT body's reference point; +HydroDyn['B9RVyi'] = False # (rad/s); Rotational velocity of the 9th WAMIT body about the global y-axis at the 9th WAMIT body's reference point; +HydroDyn['B9RVzi'] = False # (rad/s); Rotational velocity of the 9th WAMIT body about the global z-axis at the 9th WAMIT body's reference point; +HydroDyn['B9TAxi'] = False # (m/s^2); Translational acceleration of the 9th WAMIT body along the global x-axis; +HydroDyn['B9TAyi'] = False # (m/s^2); Translational acceleration of the 9th WAMIT body along the global y-axis; +HydroDyn['B9TAzi'] = False # (m/s^2); Translational acceleration of the 9th WAMIT body along the global z-axis; +HydroDyn['B9RAxi'] = False # (rad/s^2); Rotational acceleration of the 9th WAMIT body about the global x-axis at the 9th WAMIT body's reference point; +HydroDyn['B9RAyi'] = False # (rad/s^2); Rotational acceleration of the 9th WAMIT body about the global y-axis at the 9th WAMIT body's reference point; +HydroDyn['B9RAzi'] = False # (rad/s^2); Rotational acceleration of the 9th WAMIT body about the global z-axis at the 9th WAMIT body's reference point; -# Wave Motions -HydroDyn['Wave1Elev'] = False # (m); ; -HydroDyn['Wave2Elev'] = False # (m); ; -HydroDyn['Wave3Elev'] = False # (m); ; -HydroDyn['Wave4Elev'] = False # (m); ; -HydroDyn['Wave5Elev'] = False # (m); ; -HydroDyn['Wave6Elev'] = False # (m); ; -HydroDyn['Wave7Elev'] = False # (m); ; -HydroDyn['Wave8Elev'] = False # (m); ; -HydroDyn['Wave9Elev'] = False # (m); ; - -# WRP Motions -HydroDyn['WRPSurge'] = False # (m); ; -HydroDyn['WRPSway'] = False # (m); ; -HydroDyn['WRPHeave'] = False # (m); ; -HydroDyn['WRPRoll'] = False # (rad); ; -HydroDyn['WRPPitch'] = False # (rad); ; -HydroDyn['WRPYaw'] = False # (rad); ; -HydroDyn['WRPTVxi'] = False # (m/s); ; -HydroDyn['WRPTVyi'] = False # (m/s); ; -HydroDyn['WRPTVzi'] = False # (m/s); ; -HydroDyn['WRPRVxi'] = False # (rad/s); ; -HydroDyn['WRPRVyi'] = False # (rad/s); ; -HydroDyn['WRPRVzi'] = False # (rad/s); ; -HydroDyn['WRPTAxi'] = False # (m/s^2); ; -HydroDyn['WRPTAyi'] = False # (m/s^2); ; -HydroDyn['WRPTAzi'] = False # (m/s^2); ; -HydroDyn['WRPRAxi'] = False # (rad/s^2); ; -HydroDyn['WRPRAyi'] = False # (rad/s^2); ; -HydroDyn['WRPRAzi'] = False # (rad/s^2); ; +# WAMIT Body Forces +HydroDyn['B1AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 1st WAMIT body ; +HydroDyn['B1AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 1st WAMIT body ; +HydroDyn['B1AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 1st WAMIT body ; +HydroDyn['B1AddMxi'] = False # (N-m); Moment about the global x-axis at of the 1st WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B1AddMyi'] = False # (N-m); Moment about the global y-axis at of the 1st WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B1AddMzi'] = False # (N-m); Moment about the global z-axis at of the 1st WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B1WvsF1xi'] = False # (N); First-order wave-excitation force at the 1st WAMIT body from diffraction along the global x-axis; +HydroDyn['B1WvsF1yi'] = False # (N); First-order wave-excitation force at the 1st WAMIT body from diffraction along the global y-axis; +HydroDyn['B1WvsF1zi'] = False # (N); First-order wave-excitation force at the 1st WAMIT body from diffraction along the global z-axis; +HydroDyn['B1WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B1WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B1WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B1WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 1st WAMIT body from diffraction along the global x-axis; +HydroDyn['B1WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 1st WAMIT body from diffraction along the global y-axis; +HydroDyn['B1WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 1st WAMIT body from diffraction along the global z-axis; +HydroDyn['B1WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B1WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B1WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B1HdSFxi'] = False # (N); Hydrostatic force from the 1st WAMIT body along the global x-axis; +HydroDyn['B1HdSFyi'] = False # (N); Hydrostatic force from the 1st WAMIT body along the global y-axis; +HydroDyn['B1HdSFzi'] = False # (N); Hydrostatic force from the 1st WAMIT body along the global z-axis; +HydroDyn['B1HdSMxi'] = False # (N-m); Hydrostatic moment from the 1st WAMIT body about the global x-axis at the 1st WAMT body reference point; +HydroDyn['B1HdSMyi'] = False # (N-m); Hydrostatic moment from the 1st WAMIT body about the global y-axis at the 1st WAMT body reference point; +HydroDyn['B1HdSMzi'] = False # (N-m); Hydrostatic moment from the 1st WAMIT body about the global z-axis at the 1st WAMT body reference point; +HydroDyn['B1RdtFxi'] = False # (N); Wave-radiation force at the 1st WAMIT body along the global x-axis; +HydroDyn['B1RdtFyi'] = False # (N); Wave-radiation force at the 1st WAMIT body along the global y-axis; +HydroDyn['B1RdtFzi'] = False # (N); Wave-radiation force at the 1st WAMIT body along the global z-axis; +HydroDyn['B1RdtMxi'] = False # (N-m); Wave-radiation moment at the 1st WAMIT body about the global x-axis at the 1st WAMIT body's reference point; +HydroDyn['B1RdtMyi'] = False # (N-m); Wave-radiation moment at the 1st WAMIT body about the global y-axis at the 1st WAMIT body's reference point; +HydroDyn['B1RdtMzi'] = False # (N-m); Wave-radiation moment at the 1st WAMIT body about the global z-axis at the 1st WAMIT body's reference point; +HydroDyn['B2AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 2nd WAMIT body ; +HydroDyn['B2AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 2nd WAMIT body ; +HydroDyn['B2AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 2nd WAMIT body ; +HydroDyn['B2AddMxi'] = False # (N-m); Moment about the global x-axis at of the 2nd WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B2AddMyi'] = False # (N-m); Moment about the global y-axis at of the 2nd WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B2AddMzi'] = False # (N-m); Moment about the global z-axis at of the 2nd WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B2WvsF1xi'] = False # (N); First-order wave-excitation force at the 2nd WAMIT body from diffraction along the global x-axis; +HydroDyn['B2WvsF1yi'] = False # (N); First-order wave-excitation force at the 2nd WAMIT body from diffraction along the global y-axis; +HydroDyn['B2WvsF1zi'] = False # (N); First-order wave-excitation force at the 2nd WAMIT body from diffraction along the global z-axis; +HydroDyn['B2WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B2WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B2WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B2WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 2nd WAMIT body from diffraction along the global x-axis; +HydroDyn['B2WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 2nd WAMIT body from diffraction along the global y-axis; +HydroDyn['B2WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 2nd WAMIT body from diffraction along the global z-axis; +HydroDyn['B2WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B2WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B2WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B2HdSFxi'] = False # (N); Hydrostatic force from the 2nd WAMIT body along the global x-axis; +HydroDyn['B2HdSFyi'] = False # (N); Hydrostatic force from the 2nd WAMIT body along the global y-axis; +HydroDyn['B2HdSFzi'] = False # (N); Hydrostatic force from the 2nd WAMIT body along the global z-axis; +HydroDyn['B2HdSMxi'] = False # (N-m); Hydrostatic moment from the 2nd WAMIT body about the global x-axis at the 2nd WAMT body reference point; +HydroDyn['B2HdSMyi'] = False # (N-m); Hydrostatic moment from the 2nd WAMIT body about the global y-axis at the 2nd WAMT body reference point; +HydroDyn['B2HdSMzi'] = False # (N-m); Hydrostatic moment from the 2nd WAMIT body about the global z-axis at the 2nd WAMT body reference point; +HydroDyn['B2RdtFxi'] = False # (N); Wave-radiation force at the 2nd WAMIT body along the global x-axis; +HydroDyn['B2RdtFyi'] = False # (N); Wave-radiation force at the 2nd WAMIT body along the global y-axis; +HydroDyn['B2RdtFzi'] = False # (N); Wave-radiation force at the 2nd WAMIT body along the global z-axis; +HydroDyn['B2RdtMxi'] = False # (N-m); Wave-radiation moment at the 2nd WAMIT body about the global x-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2RdtMyi'] = False # (N-m); Wave-radiation moment at the 2nd WAMIT body about the global y-axis at the 2nd WAMIT body's reference point; +HydroDyn['B2RdtMzi'] = False # (N-m); Wave-radiation moment at the 2nd WAMIT body about the global z-axis at the 2nd WAMIT body's reference point; +HydroDyn['B3AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 3rd WAMIT body ; +HydroDyn['B3AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 3rd WAMIT body ; +HydroDyn['B3AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 3rd WAMIT body ; +HydroDyn['B3AddMxi'] = False # (N-m); Moment about the global x-axis at of the 3rd WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B3AddMyi'] = False # (N-m); Moment about the global y-axis at of the 3rd WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B3AddMzi'] = False # (N-m); Moment about the global z-axis at of the 3rd WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B3WvsF1xi'] = False # (N); First-order wave-excitation force at the 3rd WAMIT body from diffraction along the global x-axis; +HydroDyn['B3WvsF1yi'] = False # (N); First-order wave-excitation force at the 3rd WAMIT body from diffraction along the global y-axis; +HydroDyn['B3WvsF1zi'] = False # (N); First-order wave-excitation force at the 3rd WAMIT body from diffraction along the global z-axis; +HydroDyn['B3WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B3WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B3WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B3WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 3rd WAMIT body from diffraction along the global x-axis; +HydroDyn['B3WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 3rd WAMIT body from diffraction along the global y-axis; +HydroDyn['B3WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 3rd WAMIT body from diffraction along the global z-axis; +HydroDyn['B3WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B3WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B3WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B3HdSFxi'] = False # (N); Hydrostatic force from the 3rd WAMIT body along the global x-axis; +HydroDyn['B3HdSFyi'] = False # (N); Hydrostatic force from the 3rd WAMIT body along the global y-axis; +HydroDyn['B3HdSFzi'] = False # (N); Hydrostatic force from the 3rd WAMIT body along the global z-axis; +HydroDyn['B3HdSMxi'] = False # (N-m); Hydrostatic moment from the 3rd WAMIT body about the global x-axis at the 3rd WAMT body reference point; +HydroDyn['B3HdSMyi'] = False # (N-m); Hydrostatic moment from the 3rd WAMIT body about the global y-axis at the 3rd WAMT body reference point; +HydroDyn['B3HdSMzi'] = False # (N-m); Hydrostatic moment from the 3rd WAMIT body about the global z-axis at the 3rd WAMT body reference point; +HydroDyn['B3RdtFxi'] = False # (N); Wave-radiation force at the 3rd WAMIT body along the global x-axis; +HydroDyn['B3RdtFyi'] = False # (N); Wave-radiation force at the 3rd WAMIT body along the global y-axis; +HydroDyn['B3RdtFzi'] = False # (N); Wave-radiation force at the 3rd WAMIT body along the global z-axis; +HydroDyn['B3RdtMxi'] = False # (N-m); Wave-radiation moment at the 3rd WAMIT body about the global x-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3RdtMyi'] = False # (N-m); Wave-radiation moment at the 3rd WAMIT body about the global y-axis at the 3rd WAMIT body's reference point; +HydroDyn['B3RdtMzi'] = False # (N-m); Wave-radiation moment at the 3rd WAMIT body about the global z-axis at the 3rd WAMIT body's reference point; +HydroDyn['B4AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 4th WAMIT body ; +HydroDyn['B4AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 4th WAMIT body ; +HydroDyn['B4AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 4th WAMIT body ; +HydroDyn['B4AddMxi'] = False # (N-m); Moment about the global x-axis at of the 4th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B4AddMyi'] = False # (N-m); Moment about the global y-axis at of the 4th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B4AddMzi'] = False # (N-m); Moment about the global z-axis at of the 4th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B4WvsF1xi'] = False # (N); First-order wave-excitation force at the 4th WAMIT body from diffraction along the global x-axis; +HydroDyn['B4WvsF1yi'] = False # (N); First-order wave-excitation force at the 4th WAMIT body from diffraction along the global y-axis; +HydroDyn['B4WvsF1zi'] = False # (N); First-order wave-excitation force at the 4th WAMIT body from diffraction along the global z-axis; +HydroDyn['B4WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B4WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B4WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B4WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 4th WAMIT body from diffraction along the global x-axis; +HydroDyn['B4WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 4th WAMIT body from diffraction along the global y-axis; +HydroDyn['B4WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 4th WAMIT body from diffraction along the global z-axis; +HydroDyn['B4WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B4WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B4WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B4HdSFxi'] = False # (N); Hydrostatic force from the 4th WAMIT body along the global x-axis; +HydroDyn['B4HdSFyi'] = False # (N); Hydrostatic force from the 4th WAMIT body along the global y-axis; +HydroDyn['B4HdSFzi'] = False # (N); Hydrostatic force from the 4th WAMIT body along the global z-axis; +HydroDyn['B4HdSMxi'] = False # (N-m); Hydrostatic moment from the 4th WAMIT body about the global x-axis at the 4th WAMT body reference point; +HydroDyn['B4HdSMyi'] = False # (N-m); Hydrostatic moment from the 4th WAMIT body about the global y-axis at the 4th WAMT body reference point; +HydroDyn['B4HdSMzi'] = False # (N-m); Hydrostatic moment from the 4th WAMIT body about the global z-axis at the 4th WAMT body reference point; +HydroDyn['B4RdtFxi'] = False # (N); Wave-radiation force at the 4th WAMIT body along the global x-axis; +HydroDyn['B4RdtFyi'] = False # (N); Wave-radiation force at the 4th WAMIT body along the global y-axis; +HydroDyn['B4RdtFzi'] = False # (N); Wave-radiation force at the 4th WAMIT body along the global z-axis; +HydroDyn['B4RdtMxi'] = False # (N-m); Wave-radiation moment at the 4th WAMIT body about the global x-axis at the 4th WAMIT body's reference point; +HydroDyn['B4RdtMyi'] = False # (N-m); Wave-radiation moment at the 4th WAMIT body about the global y-axis at the 4th WAMIT body's reference point; +HydroDyn['B4RdtMzi'] = False # (N-m); Wave-radiation moment at the 4th WAMIT body about the global z-axis at the 4th WAMIT body's reference point; +HydroDyn['B5AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 5th WAMIT body ; +HydroDyn['B5AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 5th WAMIT body ; +HydroDyn['B5AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 5th WAMIT body ; +HydroDyn['B5AddMxi'] = False # (N-m); Moment about the global x-axis at of the 5th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B5AddMyi'] = False # (N-m); Moment about the global y-axis at of the 5th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B5AddMzi'] = False # (N-m); Moment about the global z-axis at of the 5th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B5WvsF1xi'] = False # (N); First-order wave-excitation force at the 5th WAMIT body from diffraction along the global x-axis; +HydroDyn['B5WvsF1yi'] = False # (N); First-order wave-excitation force at the 5th WAMIT body from diffraction along the global y-axis; +HydroDyn['B5WvsF1zi'] = False # (N); First-order wave-excitation force at the 5th WAMIT body from diffraction along the global z-axis; +HydroDyn['B5WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B5WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B5WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B5WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 5th WAMIT body from diffraction along the global x-axis; +HydroDyn['B5WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 5th WAMIT body from diffraction along the global y-axis; +HydroDyn['B5WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 5th WAMIT body from diffraction along the global z-axis; +HydroDyn['B5WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B5WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B5WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B5HdSFxi'] = False # (N); Hydrostatic force from the 5th WAMIT body along the global x-axis; +HydroDyn['B5HdSFyi'] = False # (N); Hydrostatic force from the 5th WAMIT body along the global y-axis; +HydroDyn['B5HdSFzi'] = False # (N); Hydrostatic force from the 5th WAMIT body along the global z-axis; +HydroDyn['B5HdSMxi'] = False # (N-m); Hydrostatic moment from the 5th WAMIT body about the global x-axis at the 5th WAMT body reference point; +HydroDyn['B5HdSMyi'] = False # (N-m); Hydrostatic moment from the 5th WAMIT body about the global y-axis at the 5th WAMT body reference point; +HydroDyn['B5HdSMzi'] = False # (N-m); Hydrostatic moment from the 5th WAMIT body about the global z-axis at the 5th WAMT body reference point; +HydroDyn['B5RdtFxi'] = False # (N); Wave-radiation force at the 5th WAMIT body along the global x-axis; +HydroDyn['B5RdtFyi'] = False # (N); Wave-radiation force at the 5th WAMIT body along the global y-axis; +HydroDyn['B5RdtFzi'] = False # (N); Wave-radiation force at the 5th WAMIT body along the global z-axis; +HydroDyn['B5RdtMxi'] = False # (N-m); Wave-radiation moment at the 5th WAMIT body about the global x-axis at the 5th WAMIT body's reference point; +HydroDyn['B5RdtMyi'] = False # (N-m); Wave-radiation moment at the 5th WAMIT body about the global y-axis at the 5th WAMIT body's reference point; +HydroDyn['B5RdtMzi'] = False # (N-m); Wave-radiation moment at the 5th WAMIT body about the global z-axis at the 5th WAMIT body's reference point; +HydroDyn['B6AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 6th WAMIT body ; +HydroDyn['B6AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 6th WAMIT body ; +HydroDyn['B6AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 6th WAMIT body ; +HydroDyn['B6AddMxi'] = False # (N-m); Moment about the global x-axis at of the 6th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B6AddMyi'] = False # (N-m); Moment about the global y-axis at of the 6th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B6AddMzi'] = False # (N-m); Moment about the global z-axis at of the 6th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B6WvsF1xi'] = False # (N); First-order wave-excitation force at the 6th WAMIT body from diffraction along the global x-axis; +HydroDyn['B6WvsF1yi'] = False # (N); First-order wave-excitation force at the 6th WAMIT body from diffraction along the global y-axis; +HydroDyn['B6WvsF1zi'] = False # (N); First-order wave-excitation force at the 6th WAMIT body from diffraction along the global z-axis; +HydroDyn['B6WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B6WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B6WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B6WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 6th WAMIT body from diffraction along the global x-axis; +HydroDyn['B6WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 6th WAMIT body from diffraction along the global y-axis; +HydroDyn['B6WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 6th WAMIT body from diffraction along the global z-axis; +HydroDyn['B6WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B6WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B6WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B6HdSFxi'] = False # (N); Hydrostatic force from the 6th WAMIT body along the global x-axis; +HydroDyn['B6HdSFyi'] = False # (N); Hydrostatic force from the 6th WAMIT body along the global y-axis; +HydroDyn['B6HdSFzi'] = False # (N); Hydrostatic force from the 6th WAMIT body along the global z-axis; +HydroDyn['B6HdSMxi'] = False # (N-m); Hydrostatic moment from the 6th WAMIT body about the global x-axis at the 6th WAMT body reference point; +HydroDyn['B6HdSMyi'] = False # (N-m); Hydrostatic moment from the 6th WAMIT body about the global y-axis at the 6th WAMT body reference point; +HydroDyn['B6HdSMzi'] = False # (N-m); Hydrostatic moment from the 6th WAMIT body about the global z-axis at the 6th WAMT body reference point; +HydroDyn['B6RdtFxi'] = False # (N); Wave-radiation force at the 6th WAMIT body along the global x-axis; +HydroDyn['B6RdtFyi'] = False # (N); Wave-radiation force at the 6th WAMIT body along the global y-axis; +HydroDyn['B6RdtFzi'] = False # (N); Wave-radiation force at the 6th WAMIT body along the global z-axis; +HydroDyn['B6RdtMxi'] = False # (N-m); Wave-radiation moment at the 6th WAMIT body about the global x-axis at the 6th WAMIT body's reference point; +HydroDyn['B6RdtMyi'] = False # (N-m); Wave-radiation moment at the 6th WAMIT body about the global y-axis at the 6th WAMIT body's reference point; +HydroDyn['B6RdtMzi'] = False # (N-m); Wave-radiation moment at the 6th WAMIT body about the global z-axis at the 6th WAMIT body's reference point; +HydroDyn['B7AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 7th WAMIT body ; +HydroDyn['B7AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 7th WAMIT body ; +HydroDyn['B7AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 7th WAMIT body ; +HydroDyn['B7AddMxi'] = False # (N-m); Moment about the global x-axis at of the 7th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B7AddMyi'] = False # (N-m); Moment about the global y-axis at of the 7th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B7AddMzi'] = False # (N-m); Moment about the global z-axis at of the 7th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B7WvsF1xi'] = False # (N); First-order wave-excitation force at the 7th WAMIT body from diffraction along the global x-axis; +HydroDyn['B7WvsF1yi'] = False # (N); First-order wave-excitation force at the 7th WAMIT body from diffraction along the global y-axis; +HydroDyn['B7WvsF1zi'] = False # (N); First-order wave-excitation force at the 7th WAMIT body from diffraction along the global z-axis; +HydroDyn['B7WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B7WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B7WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B7WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 7th WAMIT body from diffraction along the global x-axis; +HydroDyn['B7WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 7th WAMIT body from diffraction along the global y-axis; +HydroDyn['B7WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 7th WAMIT body from diffraction along the global z-axis; +HydroDyn['B7WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B7WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B7WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B7HdSFxi'] = False # (N); Hydrostatic force from the 7th WAMIT body along the global x-axis; +HydroDyn['B7HdSFyi'] = False # (N); Hydrostatic force from the 7th WAMIT body along the global y-axis; +HydroDyn['B7HdSFzi'] = False # (N); Hydrostatic force from the 7th WAMIT body along the global z-axis; +HydroDyn['B7HdSMxi'] = False # (N-m); Hydrostatic moment from the 7th WAMIT body about the global x-axis at the 7th WAMT body reference point; +HydroDyn['B7HdSMyi'] = False # (N-m); Hydrostatic moment from the 7th WAMIT body about the global y-axis at the 7th WAMT body reference point; +HydroDyn['B7HdSMzi'] = False # (N-m); Hydrostatic moment from the 7th WAMIT body about the global z-axis at the 7th WAMT body reference point; +HydroDyn['B7RdtFxi'] = False # (N); Wave-radiation force at the 7th WAMIT body along the global x-axis; +HydroDyn['B7RdtFyi'] = False # (N); Wave-radiation force at the 7th WAMIT body along the global y-axis; +HydroDyn['B7RdtFzi'] = False # (N); Wave-radiation force at the 7th WAMIT body along the global z-axis; +HydroDyn['B7RdtMxi'] = False # (N-m); Wave-radiation moment at the 7th WAMIT body about the global x-axis at the 7th WAMIT body's reference point; +HydroDyn['B7RdtMyi'] = False # (N-m); Wave-radiation moment at the 7th WAMIT body about the global y-axis at the 7th WAMIT body's reference point; +HydroDyn['B7RdtMzi'] = False # (N-m); Wave-radiation moment at the 7th WAMIT body about the global z-axis at the 7th WAMIT body's reference point; +HydroDyn['B8AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 8th WAMIT body ; +HydroDyn['B8AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 8th WAMIT body ; +HydroDyn['B8AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 8th WAMIT body ; +HydroDyn['B8AddMxi'] = False # (N-m); Moment about the global x-axis at of the 8th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B8AddMyi'] = False # (N-m); Moment about the global y-axis at of the 8th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B8AddMzi'] = False # (N-m); Moment about the global z-axis at of the 8th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B8WvsF1xi'] = False # (N); First-order wave-excitation force at the 8th WAMIT body from diffraction along the global x-axis; +HydroDyn['B8WvsF1yi'] = False # (N); First-order wave-excitation force at the 8th WAMIT body from diffraction along the global y-axis; +HydroDyn['B8WvsF1zi'] = False # (N); First-order wave-excitation force at the 8th WAMIT body from diffraction along the global z-axis; +HydroDyn['B8WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B8WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B8WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B8WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 8th WAMIT body from diffraction along the global x-axis; +HydroDyn['B8WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 8th WAMIT body from diffraction along the global y-axis; +HydroDyn['B8WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 8th WAMIT body from diffraction along the global z-axis; +HydroDyn['B8WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B8WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B8WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B8HdSFxi'] = False # (N); Hydrostatic force from the 8th WAMIT body along the global x-axis; +HydroDyn['B8HdSFyi'] = False # (N); Hydrostatic force from the 8th WAMIT body along the global y-axis; +HydroDyn['B8HdSFzi'] = False # (N); Hydrostatic force from the 8th WAMIT body along the global z-axis; +HydroDyn['B8HdSMxi'] = False # (N-m); Hydrostatic moment from the 8th WAMIT body about the global x-axis at the 8th WAMT body reference point; +HydroDyn['B8HdSMyi'] = False # (N-m); Hydrostatic moment from the 8th WAMIT body about the global y-axis at the 8th WAMT body reference point; +HydroDyn['B8HdSMzi'] = False # (N-m); Hydrostatic moment from the 8th WAMIT body about the global z-axis at the 8th WAMT body reference point; +HydroDyn['B8RdtFxi'] = False # (N); Wave-radiation force at the 8th WAMIT body along the global x-axis; +HydroDyn['B8RdtFyi'] = False # (N); Wave-radiation force at the 8th WAMIT body along the global y-axis; +HydroDyn['B8RdtFzi'] = False # (N); Wave-radiation force at the 8th WAMIT body along the global z-axis; +HydroDyn['B8RdtMxi'] = False # (N-m); Wave-radiation moment at the 8th WAMIT body about the global x-axis at the 8th WAMIT body's reference point; +HydroDyn['B8RdtMyi'] = False # (N-m); Wave-radiation moment at the 8th WAMIT body about the global y-axis at the 8th WAMIT body's reference point; +HydroDyn['B8RdtMzi'] = False # (N-m); Wave-radiation moment at the 8th WAMIT body about the global z-axis at the 8th WAMIT body's reference point; +HydroDyn['B9AddFxi'] = False # (N); Force along the global x-axis due to additional preload, stiffness, and damping of the 9th WAMIT body ; +HydroDyn['B9AddFyi'] = False # (N); Force along the global y-axis due to additional preload, stiffness, and damping of the 9th WAMIT body ; +HydroDyn['B9AddFzi'] = False # (N); Force along the global z-axis due to additional preload, stiffness, and damping of the 9th WAMIT body ; +HydroDyn['B9AddMxi'] = False # (N-m); Moment about the global x-axis at of the 9th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B9AddMyi'] = False # (N-m); Moment about the global y-axis at of the 9th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B9AddMzi'] = False # (N-m); Moment about the global z-axis at of the 9th WAMIT body's reference point due to additional preload, stiffness, and damping ; +HydroDyn['B9WvsF1xi'] = False # (N); First-order wave-excitation force at the 9th WAMIT body from diffraction along the global x-axis; +HydroDyn['B9WvsF1yi'] = False # (N); First-order wave-excitation force at the 9th WAMIT body from diffraction along the global y-axis; +HydroDyn['B9WvsF1zi'] = False # (N); First-order wave-excitation force at the 9th WAMIT body from diffraction along the global z-axis; +HydroDyn['B9WvsM1xi'] = False # (N-m); First-order wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B9WvsM1yi'] = False # (N-m); First-order wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B9WvsM1zi'] = False # (N-m); First-order wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B9WvsFxi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 9th WAMIT body from diffraction along the global x-axis; +HydroDyn['B9WvsFyi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 9th WAMIT body from diffraction along the global y-axis; +HydroDyn['B9WvsFzi'] = False # (N); Total (first-order plus second-order) wave-excitation force at the 9th WAMIT body from diffraction along the global z-axis; +HydroDyn['B9WvsMxi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B9WvsMyi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B9WvsMzi'] = False # (N-m); Total (first-order plus second-order) wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B9HdSFxi'] = False # (N); Hydrostatic force from the 9th WAMIT body along the global x-axis; +HydroDyn['B9HdSFyi'] = False # (N); Hydrostatic force from the 9th WAMIT body along the global y-axis; +HydroDyn['B9HdSFzi'] = False # (N); Hydrostatic force from the 9th WAMIT body along the global z-axis; +HydroDyn['B9HdSMxi'] = False # (N-m); Hydrostatic moment from the 9th WAMIT body about the global x-axis at the 9th WAMT body reference point; +HydroDyn['B9HdSMyi'] = False # (N-m); Hydrostatic moment from the 9th WAMIT body about the global y-axis at the 9th WAMT body reference point; +HydroDyn['B9HdSMzi'] = False # (N-m); Hydrostatic moment from the 9th WAMIT body about the global z-axis at the 9th WAMT body reference point; +HydroDyn['B9RdtFxi'] = False # (N); Wave-radiation force at the 9th WAMIT body along the global x-axis; +HydroDyn['B9RdtFyi'] = False # (N); Wave-radiation force at the 9th WAMIT body along the global y-axis; +HydroDyn['B9RdtFzi'] = False # (N); Wave-radiation force at the 9th WAMIT body along the global z-axis; +HydroDyn['B9RdtMxi'] = False # (N-m); Wave-radiation moment at the 9th WAMIT body about the global x-axis at the 9th WAMIT body's reference point; +HydroDyn['B9RdtMyi'] = False # (N-m); Wave-radiation moment at the 9th WAMIT body about the global y-axis at the 9th WAMIT body's reference point; +HydroDyn['B9RdtMzi'] = False # (N-m); Wave-radiation moment at the 9th WAMIT body about the global z-axis at the 9th WAMIT body's reference point; +HydroDyn['B1WvsF2xi'] = False # (N); Second-order wave-excitation force at the 1st WAMIT body from diffraction along the global x-axis; +HydroDyn['B1WvsF2yi'] = False # (N); Second-order wave-excitation force at the 1st WAMIT body from diffraction along the global y-axis; +HydroDyn['B1WvsF2zi'] = False # (N); Second-order wave-excitation force at the 1st WAMIT body from diffraction along the global z-axis; +HydroDyn['B1WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B1WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B1WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 1st WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B2WvsF2xi'] = False # (N); Second-order wave-excitation force at the 2nd WAMIT body from diffraction along the global x-axis; +HydroDyn['B2WvsF2yi'] = False # (N); Second-order wave-excitation force at the 2nd WAMIT body from diffraction along the global y-axis; +HydroDyn['B2WvsF2zi'] = False # (N); Second-order wave-excitation force at the 2nd WAMIT body from diffraction along the global z-axis; +HydroDyn['B2WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B2WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B2WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 2nd WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B3WvsF2xi'] = False # (N); Second-order wave-excitation force at the 3rd WAMIT body from diffraction along the global x-axis; +HydroDyn['B3WvsF2yi'] = False # (N); Second-order wave-excitation force at the 3rd WAMIT body from diffraction along the global y-axis; +HydroDyn['B3WvsF2zi'] = False # (N); Second-order wave-excitation force at the 3rd WAMIT body from diffraction along the global z-axis; +HydroDyn['B3WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B3WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B3WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 3rd WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B4WvsF2xi'] = False # (N); Second-order wave-excitation force at the 4th WAMIT body from diffraction along the global x-axis; +HydroDyn['B4WvsF2yi'] = False # (N); Second-order wave-excitation force at the 4th WAMIT body from diffraction along the global y-axis; +HydroDyn['B4WvsF2zi'] = False # (N); Second-order wave-excitation force at the 4th WAMIT body from diffraction along the global z-axis; +HydroDyn['B4WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B4WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B4WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 4th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B5WvsF2xi'] = False # (N); Second-order wave-excitation force at the 5th WAMIT body from diffraction along the global x-axis; +HydroDyn['B5WvsF2yi'] = False # (N); Second-order wave-excitation force at the 5th WAMIT body from diffraction along the global y-axis; +HydroDyn['B5WvsF2zi'] = False # (N); Second-order wave-excitation force at the 5th WAMIT body from diffraction along the global z-axis; +HydroDyn['B5WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B5WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B5WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 5th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B6WvsF2xi'] = False # (N); Second-order wave-excitation force at the 6th WAMIT body from diffraction along the global x-axis; +HydroDyn['B6WvsF2yi'] = False # (N); Second-order wave-excitation force at the 6th WAMIT body from diffraction along the global y-axis; +HydroDyn['B6WvsF2zi'] = False # (N); Second-order wave-excitation force at the 6th WAMIT body from diffraction along the global z-axis; +HydroDyn['B6WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B6WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B6WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 6th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B7WvsF2xi'] = False # (N); Second-order wave-excitation force at the 7th WAMIT body from diffraction along the global x-axis; +HydroDyn['B7WvsF2yi'] = False # (N); Second-order wave-excitation force at the 7th WAMIT body from diffraction along the global y-axis; +HydroDyn['B7WvsF2zi'] = False # (N); Second-order wave-excitation force at the 7th WAMIT body from diffraction along the global z-axis; +HydroDyn['B7WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B7WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B7WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 7th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B8WvsF2xi'] = False # (N); Second-order wave-excitation force at the 8th WAMIT body from diffraction along the global x-axis; +HydroDyn['B8WvsF2yi'] = False # (N); Second-order wave-excitation force at the 8th WAMIT body from diffraction along the global y-axis; +HydroDyn['B8WvsF2zi'] = False # (N); Second-order wave-excitation force at the 8th WAMIT body from diffraction along the global z-axis; +HydroDyn['B8WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B8WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B8WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 8th WAMIT body reference point from diffraction about the global z-axis; +HydroDyn['B9WvsF2xi'] = False # (N); Second-order wave-excitation force at the 9th WAMIT body from diffraction along the global x-axis; +HydroDyn['B9WvsF2yi'] = False # (N); Second-order wave-excitation force at the 9th WAMIT body from diffraction along the global y-axis; +HydroDyn['B9WvsF2zi'] = False # (N); Second-order wave-excitation force at the 9th WAMIT body from diffraction along the global z-axis; +HydroDyn['B9WvsM2xi'] = False # (N-m); Second-order wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global x-axis; +HydroDyn['B9WvsM2yi'] = False # (N-m); Second-order wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global y-axis; +HydroDyn['B9WvsM2zi'] = False # (N-m); Second-order wave-excitation moment at the 9th WAMIT body reference point from diffraction about the global z-axis; + +# Wave Elevations +HydroDyn['Wave1Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 1st user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave2Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 2nd user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave3Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 3rd user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave4Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 4th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave5Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 5th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave6Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 6th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave7Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 7th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave8Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 8th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave9Elev'] = False # (m); Total (first-order plus second-order) wave elevation (global Z height) at the 9th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave1Elv1'] = False # (m); First-order wave elevation (global Z height) at the 1st user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave2Elv1'] = False # (m); First-order wave elevation (global Z height) at the 2nd user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave3Elv1'] = False # (m); First-order wave elevation (global Z height) at the 3rd user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave4Elv1'] = False # (m); First-order wave elevation (global Z height) at the 4th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave5Elv1'] = False # (m); First-order wave elevation (global Z height) at the 5th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave6Elv1'] = False # (m); First-order wave elevation (global Z height) at the 6th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave7Elv1'] = False # (m); First-order wave elevation (global Z height) at the 7th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave8Elv1'] = False # (m); First-order wave elevation (global Z height) at the 8th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave9Elv1'] = False # (m); First-order wave elevation (global Z height) at the 9th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave1Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 1st user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave2Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 2nd user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave3Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 3rd user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave4Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 4th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave5Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 5th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave6Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 6th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave7Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 7th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave8Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 8th user-requested location (location is specified in the global coordinate system); +HydroDyn['Wave9Elv2'] = False # (m); Second-order wave elevation (global Z height) at the 9th user-requested location (location is specified in the global coordinate system); """ Morison """ @@ -9421,6 +10884,9 @@ FstOutput['SubDyn'] = SubDyn FstOutput['BeamDyn'] = BeamDyn FstOutput['MoorDyn'] = MoorDyn +FstOutput['AeroDyn_Nodes'] = AeroDyn_Nodes +FstOutput['ElastoDyn_Nodes'] = ElastoDyn_Nodes +FstOutput['BeamDyn_Nodes'] = BeamDyn_Nodes """ Generated from FAST OutListParameters.xlsx files with AeroelasticSE/src/AeroelasticSE/Util/create_output_vars.py """ diff --git a/ROSCO_toolbox/ofTools/fast_io/FAST_wrapper.py b/rosco/toolbox/ofTools/fast_io/FAST_wrapper.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/FAST_wrapper.py rename to rosco/toolbox/ofTools/fast_io/FAST_wrapper.py diff --git a/ROSCO_toolbox/ofTools/fast_io/FAST_writer.py b/rosco/toolbox/ofTools/fast_io/FAST_writer.py similarity index 94% rename from ROSCO_toolbox/ofTools/fast_io/FAST_writer.py rename to rosco/toolbox/ofTools/fast_io/FAST_writer.py index 8dd91db3..93c26c48 100644 --- a/ROSCO_toolbox/ofTools/fast_io/FAST_writer.py +++ b/rosco/toolbox/ofTools/fast_io/FAST_writer.py @@ -4,10 +4,9 @@ import numpy as np from functools import reduce -from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST -from ROSCO_toolbox.ofTools.fast_io.FAST_vars import FstModel +from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST -from ROSCO_toolbox.utilities import write_rotor_performance, write_DISCON +from rosco.toolbox.utilities import write_rotor_performance, write_DISCON ROSCO = True @@ -411,6 +410,20 @@ def write_ElastoDyn(self): f.write('"' + channel_list[i] + '"\n') f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)\n') + + # Optional nodal output section + if 'BldNd_BladesOut' in self.fst_vt['ElastoDyn']: + f.write('====== Outputs for all blade stations (same ending as above for B1N1.... =========================== [optional section]\n') + f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['ElastoDyn']['BldNd_BladesOut'], 'BldNd_BladesOut', '- Number of blades to output all node information at. Up to number of blades on turbine. (-)\n')) + f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['ElastoDyn']['BldNd_BlOutNd'], 'BldNd_BlOutNd', '- Future feature will allow selecting a portion of the nodes to output. Not implemented yet. (-)\n')) + f.write(' OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx, ElastoDyn_Nodes tab for a listing of available output channels, (-)\n') + + opt_outlist = self.get_outlist(self.fst_vt['outlist'], ['ElastoDyn_Nodes']) + for opt_channel_list in opt_outlist: + for i in range(len(opt_channel_list)): + f.write('"' + opt_channel_list[i] + '"\n') + f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)\n') + f.write('---------------------------------------------------------------------------------------\n') f.close() @@ -586,7 +599,21 @@ def write_BeamDyn(self): for channel_list in outlist: for i in range(len(channel_list)): f.write('"' + channel_list[i] + '"\n') - f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)') + f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)\n') + + # Optional nodal output section + if 'BldNd_BlOutNd' in self.fst_vt['BeamDyn']: + f.write('====== Outputs for all blade stations (same ending as above for B1N1.... =========================== [optional section]\n') + # f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['BeamDyn']['BldNd_BladesOut'], 'BldNd_BladesOut', '- Number of blades to output all node information at. Up to number of blades on turbine. (-)\n')) + f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['BeamDyn']['BldNd_BlOutNd'], 'BldNd_BlOutNd', '- Future feature will allow selecting a portion of the nodes to output. Not implemented yet. (-)\n')) + f.write(' OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx, BeamDyn_Nodes tab for a listing of available output channels, (-)\n') + + opt_outlist = self.get_outlist(self.fst_vt['outlist'], ['BeamDyn_Nodes']) + for opt_channel_list in opt_outlist: + for i in range(len(opt_channel_list)): + f.write('"' + opt_channel_list[i] + '"\n') + f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)\n') + f.write('---------------------------------------------------------------------------------------') f.close() @@ -639,6 +666,7 @@ def write_InflowWind(self): f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['WindType'], 'WindType', '- switch for wind file type (1=steady; 2=uniform; 3=binary TurbSim FF; 4=binary Bladed-style FF; 5=HAWC format; 6=User defined; 7=native Bladed FF)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['PropagationDir'], 'PropagationDir', '- Direction of wind propagation (meteoroligical rotation from aligned with X (positive rotates towards -Y) -- degrees)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['VFlowAng'], 'VFlowAng', '- Upflow angle (degrees) (not used for native Bladed format WindType=7)\n')) + f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['VelInterpCubic'], 'VelInterpCubic', '- Use cubic interpolation for velocity in time (false=linear, true=cubic) [Used with WindType=2,3,4,5,7]\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['NWindVel'], 'NWindVel', '- Number of points to output the wind velocity (0 to 9)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['WindVxiList'], 'WindVxiList', '- List of coordinates in the inertial X direction (m)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['WindVyiList'], 'WindVyiList', '- List of coordinates in the inertial Y direction (m)\n')) @@ -681,6 +709,19 @@ def write_InflowWind(self): f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['PLExp_Hawc'], 'PLExp_Hawc', '- Power law exponent (-) (used for PL wind profile type only)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['Z0'], 'Z0', '- Surface roughness length (m) (used for LG wind profile type only)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['XOffset'], 'XOffset', '- Initial offset in +x direction (shift of wind box) (-)\n')) + f.write('------------- LIDAR Parameters --------------------------------------------------------------------------\n') + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['SensorType'], 'SensorType', '- Switch for lidar configuration (0 = None, 1 = Single Point Beam(s), 2 = Continuous, 3 = Pulsed)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['NumPulseGate'], 'NumPulseGate', '- Number of lidar measurement gates (used when SensorType = 3)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['PulseSpacing'], 'PulseSpacing', '- Distance between range gates (m) (used when SensorType = 3)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['NumBeam'], 'NumBeam', '- Number of lidar measurement beams (0-5)(used when SensorType = 1)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['FocalDistanceX'], 'FocalDistanceX', '- Focal distance co-ordinates of the lidar beam in the x direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['FocalDistanceY'], 'FocalDistanceY', '- Focal distance co-ordinates of the lidar beam in the y direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['FocalDistanceZ'], 'FocalDistanceZ', '- Focal distance co-ordinates of the lidar beam in the z direction (relative to hub height) (only first coordinate used for SensorType 2 and 3) (m)\n')) + f.write('{:<22} {:<11} {:}'.format(', '.join(np.array(self.fst_vt['InflowWind']['RotorApexOffsetPos'], dtype=str)), 'RotorApexOffsetPos', '- Offset of the lidar from hub height (m)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['URefLid'], 'URefLid', '- Reference average wind speed for the lidar[m/s]\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['MeasurementInterval'], 'MeasurementInterval', '- Time between each measurement [s]\n')) + f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['LidRadialVel'], 'LidRadialVel', '- TRUE => return radial component, FALSE => return x direction estimate\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['ConsiderHubMotion'], 'ConsiderHubMotion', '- Flag whether to consider the hub motions impact on Lidar measurements\n')) f.write('====================== OUTPUT ==================================================\n') f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['InflowWind']['SumPrint'], 'SumPrint', '- Print summary data to .IfW.sum (flag)\n')) f.write('OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-)\n') @@ -807,6 +848,20 @@ def write_AeroDyn15(self): for i in range(len(channel_list)): f.write('"' + channel_list[i] + '"\n') f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)\n') + + # Optional nodal output section + if 'BldNd_BladesOut' in self.fst_vt['AeroDyn15']: + f.write('====== Outputs for all blade stations (same ending as above for B1N1.... =========================== [optional section]\n') + f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['BldNd_BladesOut'], 'BldNd_BladesOut', '- Number of blades to output all node information at. Up to number of blades on turbine. (-)\n')) + f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['BldNd_BlOutNd'], 'BldNd_BlOutNd', '- Future feature will allow selecting a portion of the nodes to output. Not implemented yet. (-)\n')) + f.write(' OutList - The next line(s) contains a list of output parameters. See OutListParameters.xlsx, AeroDyn_Nodes tab for a listing of available output channels, (-)\n') + + opt_outlist = self.get_outlist(self.fst_vt['outlist'], ['AeroDyn_Nodes']) + for opt_channel_list in opt_outlist: + for i in range(len(opt_channel_list)): + f.write('"' + opt_channel_list[i] + '"\n') + f.write('END of input file (the word "END" must appear in the first 3 columns of this last OutList line)\n') + f.write('---------------------------------------------------------------------------------------\n') f.close() @@ -1161,25 +1216,25 @@ def write_OLAF(self): f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['nFWPanelsFree'], 'nFWPanelsFree','- Number of free far-wake panels (-) {default: nFWPanels}\n')) f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['FWShedVorticity'], 'FWShedVorticity','- Include shed vorticity in the far wake {default: False}\n')) f.write('------------------- WAKE REGULARIZATIONS AND DIFFUSION -----------------------------------------\n') - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['DiffusionMethod'], 'DiffusionMethod','- Diffusion method to account for viscous effects {0: None, 1: Core Spreading, "default": 0}\n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['RegDeterMethod'], 'RegDeterMethod','- Method to determine the regularization parameters {0: Manual, 1: Optimized, 2: Chord, 3: Span, default: 0 }\n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['RegFunction'], 'RegFunction','- Viscous diffusion function {0: None, 1: Rankine, 2: LambOseen, 3: Vatistas, 4: Denominator, "default": 3} (switch)\n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['WakeRegMethod'], 'WakeRegMethod','- Wake regularization method {1: Constant, 2: Stretching, 3: Age, default: 3} (switch)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['DiffusionMethod'], 'DiffusionMethod','- Diffusion method to account for viscous effects {0: None, 1: Core Spreading, "default": 0}\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['RegDeterMethod'], 'RegDeterMethod','- Method to determine the regularization parameters {0: Manual, 1: Optimized, 2: Chord, 3: Span, default: 0 }\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['RegFunction'], 'RegFunction','- Viscous diffusion function {0: None, 1: Rankine, 2: LambOseen, 3: Vatistas, 4: Denominator, "default": 3} (switch)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['WakeRegMethod'], 'WakeRegMethod','- Wake regularization method {1: Constant, 2: Stretching, 3: Age, default: 3} (switch)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['WakeRegFactor'], 'WakeRegFactor','- Wake regularization factor (m)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['WingRegFactor'], 'WingRegFactor','- Wing regularization factor (m)\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['CoreSpreadEddyVisc'], 'CoreSpreadEddyVisc','- Eddy viscosity in core spreading methods, typical values 1-1000\n')) f.write('------------------- WAKE TREATMENT OPTIONS ---------------------------------------------------\n') f.write('{!s:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['TwrShadowOnWake'], 'TwrShadowOnWake','- Include tower flow disturbance effects on wake convection {default:false} [only if TwrPotent or TwrShadow]\n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['ShearModel'], 'ShearModel','- Shear Model {0: No treatment, 1: Mirrored vorticity, default: 0}\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['ShearModel'], 'ShearModel','- Shear Model {0: No treatment, 1: Mirrored vorticity, default: 0}\n')) f.write('------------------- SPEEDUP OPTIONS -----------------------------------------------------------\n') f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['VelocityMethod'], 'VelocityMethod','- Method to determine the velocity {1:Segment N^2, 2:Particle tree, 3:Particle N^2, 4:Segment tree, default: 2}\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['TreeBranchFactor'], 'TreeBranchFactor','- Branch radius fraction above which a multipole calculation is used {default: 1.5} [only if VelocityMethod=2,4]\n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['PartPerSegment'], 'PartPerSegment','- Number of particles per segment {default: 1} [only if VelocityMethod=2,3]\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['PartPerSegment'], 'PartPerSegment','- Number of particles per segment {default: 1} [only if VelocityMethod=2,3]\n')) f.write('===============================================================================================\n') f.write('--------------------------- OUTPUT OPTIONS ---------------------------------------------------\n') - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['WrVTk'], 'WrVTk','- Outputs Visualization Toolkit (VTK) (independent of .fst option) {0: NoVTK, 1: Write VTK at VTK_fps, 2: Write VTK at init and final, default: 0} (flag)\n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['nVTKBlades'], 'nVTKBlades','- Number of blades for which VTK files are exported {0: No VTK per blade, n: VTK for blade 1 to n, default: 0} (-) \n')) - f.write('{:<22d} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['VTKCoord'], 'VTKCoord','- Coordinate system used for VTK export. {1: Global, 2: Hub, 3: Both, default: 1} \n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['WrVTk'], 'WrVTk','- Outputs Visualization Toolkit (VTK) (independent of .fst option) {0: NoVTK, 1: Write VTK at VTK_fps, 2: Write VTK at init and final, default: 0} (flag)\n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['nVTKBlades'], 'nVTKBlades','- Number of blades for which VTK files are exported {0: No VTK per blade, n: VTK for blade 1 to n, default: 0} (-) \n')) + f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['VTKCoord'], 'VTKCoord','- Coordinate system used for VTK export. {1: Global, 2: Hub, 3: Both, default: 1} \n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['VTK_fps'], 'VTK_fps','- Frame rate for VTK output (frames per second) {"all" for all glue code timesteps, "default" for all OLAF timesteps} [only if WrVTK=1]\n')) f.write('{:<22} {:<11} {:}'.format(self.fst_vt['AeroDyn15']['OLAF']['nGridOut'], 'nGridOut','- Number of grid outputs\n')) f.write('GridName GridType TStart TEnd DTGrid XStart XEnd nX YStart YEnd nY ZStart ZEnd nZ\n') @@ -1319,7 +1374,7 @@ def write_ServoDyn(self): f.close() def write_DISCON_in(self): - # Generate Bladed style Interface controller input file, intended for ROSCO https://github.com/NREL/ROSCO_toolbox + # Generate Bladed style Interface controller input file, intended for ROSCO https://github.com/NREL/rosco.toolbox # Fill controller and turbine objects for ROSCO # - controller @@ -1450,8 +1505,11 @@ def write_HydroDyn(self): for j in range(6): if type(self.fst_vt['HydroDyn']['AddF0'][j]) == float: ln = '{:14} '.format(self.fst_vt['HydroDyn']['AddF0'][j]) - elif type(self.fst_vt['HydroDyn']['AddF0'][j]) == list: + elif type(self.fst_vt['HydroDyn']['AddF0'][j]) in [list, np.ndarray]: ln = '{:14} '.format(' '.join([f'{val}' for val in self.fst_vt['HydroDyn']['AddF0'][j]])) + else: + raise Exception("Check type of self.fst_vt['HydroDyn']['AddF0']") + if j == 0: ln = ln + 'AddF0 - Additional preload (N, N-m) [If NBodyMod=1, one size 6*NBody x 1 vector; if NBodyMod>1, NBody size 6 x 1 vectors]\n' else: @@ -1939,15 +1997,15 @@ def write_MoorDyn(self): for i in range(len(self.fst_vt['MoorDyn']['Name'])): ln = [] ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Name'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Diam'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['MassDen'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['EA'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['BA_zeta'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['EI'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Cd'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Ca'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['CdAx'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['CaAx'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['Diam'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['MassDen'][i])) + ln.append('{:^11.4e}'.format(self.fst_vt['MoorDyn']['EA'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['BA_zeta'][i])) + ln.append('{:^11.4e}'.format(self.fst_vt['MoorDyn']['EI'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['Cd'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['Ca'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['CdAx'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['CaAx'][i])) f.write(" ".join(ln) + '\n') f.write('---------------------- POINTS --------------------------------\n') f.write(" ".join(['{:^11s}'.format(i) for i in ['ID', 'Attachment', 'X', 'Y', 'Z', 'M', 'V', 'CdA', 'CA']])+'\n') @@ -1956,13 +2014,13 @@ def write_MoorDyn(self): ln = [] ln.append('{:^11d}'.format(self.fst_vt['MoorDyn']['Point_ID'][i])) ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Attachment'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['X'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Y'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Z'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['M'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['V'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['CdA'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['CA'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['X'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['Y'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['Z'][i])) + ln.append('{:^11.4e}'.format(self.fst_vt['MoorDyn']['M'][i])) + ln.append('{:^11.4e}'.format(self.fst_vt['MoorDyn']['V'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['CdA'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['CA'][i])) f.write(" ".join(ln) + '\n') f.write('---------------------- LINES --------------------------------------\n') f.write(" ".join(['{:^11s}'.format(i) for i in ['Line', 'LineType', 'AttachA', 'AttachB', 'UnstrLen', 'NumSegs', 'Outputs']])+'\n') @@ -1973,7 +2031,7 @@ def write_MoorDyn(self): ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['LineType'][i])) ln.append('{:^11d}'.format(self.fst_vt['MoorDyn']['AttachA'][i])) ln.append('{:^11d}'.format(self.fst_vt['MoorDyn']['AttachB'][i])) - ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['UnstrLen'][i])) + ln.append('{:^11.4f}'.format(self.fst_vt['MoorDyn']['UnstrLen'][i])) ln.append('{:^11d}'.format(self.fst_vt['MoorDyn']['NumSegs'][i])) ln.append('{:^11}'.format(self.fst_vt['MoorDyn']['Outputs'][i])) f.write(" ".join(ln) + '\n') diff --git a/ROSCO_toolbox/ofTools/util/__init__.py b/rosco/toolbox/ofTools/fast_io/__init__.py similarity index 100% rename from ROSCO_toolbox/ofTools/util/__init__.py rename to rosco/toolbox/ofTools/fast_io/__init__.py diff --git a/ROSCO_toolbox/ofTools/fast_io/file.py b/rosco/toolbox/ofTools/fast_io/file.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/file.py rename to rosco/toolbox/ofTools/fast_io/file.py diff --git a/ROSCO_toolbox/ofTools/fast_io/output_processing.py b/rosco/toolbox/ofTools/fast_io/output_processing.py similarity index 99% rename from ROSCO_toolbox/ofTools/fast_io/output_processing.py rename to rosco/toolbox/ofTools/fast_io/output_processing.py index ef3684b1..bafe84bf 100644 --- a/ROSCO_toolbox/ofTools/fast_io/output_processing.py +++ b/rosco/toolbox/ofTools/fast_io/output_processing.py @@ -17,7 +17,7 @@ import struct import multiprocessing as mp -from ROSCO_toolbox.ofTools.util import spectral +from rosco.toolbox.ofTools.util import spectral class output_processing(): ''' diff --git a/ROSCO_toolbox/ofTools/fast_io/plot_FAST.ipynb b/rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb similarity index 99% rename from ROSCO_toolbox/ofTools/fast_io/plot_FAST.ipynb rename to rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb index 52fe840c..edf7715d 100644 --- a/ROSCO_toolbox/ofTools/fast_io/plot_FAST.ipynb +++ b/rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb @@ -28,9 +28,9 @@ "# from weis.aeroelasticse.Util import FileTools\n", "\n", "# Instantiate fast_IO\n", - "from ROSCO_toolbox.ofTools.fast_io import output_processing\n", + "from rosco.toolbox.ofTools.fast_io import output_processing\n", "\n", - "from ROSCO_toolbox.ofTools.util import spectral\n", + "from rosco.toolbox.ofTools.util import spectral\n", "\n", "\n", "import pandas as pd\n", @@ -71,7 +71,7 @@ "outputs": [ { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -198,7 +198,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -418,7 +418,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] @@ -486,7 +486,7 @@ }, { "data": { - "image/png": "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\n", + "image/png": "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", "text/plain": [ "
" ] diff --git a/ROSCO_toolbox/ofTools/fast_io/pyIECWind.py b/rosco/toolbox/ofTools/fast_io/pyIECWind.py similarity index 99% rename from ROSCO_toolbox/ofTools/fast_io/pyIECWind.py rename to rosco/toolbox/ofTools/fast_io/pyIECWind.py index 3cc899bb..f254c624 100644 --- a/ROSCO_toolbox/ofTools/fast_io/pyIECWind.py +++ b/rosco/toolbox/ofTools/fast_io/pyIECWind.py @@ -2,9 +2,9 @@ import os, sys # import matplotlib.pyplot as plt -from ROSCO_toolbox.ofTools.fast_io.turbsim_io.turbsim_writer import TurbsimBuilder -from ROSCO_toolbox.ofTools.fast_io.turbsim_io.turbsim_wrapper import Turbsim_wrapper -from ROSCO_toolbox.ofTools.fast_io.turbsim_io.turbsim_vartrees import turbsiminputs +from rosco.toolbox.ofTools.fast_io.turbsim_io.turbsim_writer import TurbsimBuilder +from rosco.toolbox.ofTools.fast_io.turbsim_io.turbsim_wrapper import Turbsim_wrapper +from rosco.toolbox.ofTools.fast_io.turbsim_io.turbsim_vartrees import turbsiminputs # from AeroelasticSE.Turbsim_mdao.pyturbsim_wrapper import pyTurbsim_wrapper diff --git a/rosco/toolbox/ofTools/fast_io/turbsim_io/__init__.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_reader.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_reader.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_reader.py rename to rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_reader.py diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_vartrees.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_vartrees.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_vartrees.py rename to rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_vartrees.py diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_wrapper.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_wrapper.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_wrapper.py rename to rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_wrapper.py diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_writer.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_writer.py similarity index 98% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_writer.py rename to rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_writer.py index 167ebf5e..4b7c6ecb 100644 --- a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbsim_writer.py +++ b/rosco/toolbox/ofTools/fast_io/turbsim_io/turbsim_writer.py @@ -1,6 +1,6 @@ -from ROSCO_toolbox.ofTools.fast_io.turbsim_io.turbsim_vartrees import turbsiminputs -from ROSCO_toolbox.ofTools.fast_io.turbsim_io.turbulence_spectrum import turb_specs -from ROSCO_toolbox.ofTools.fast_io.turbsim_io.wind_profile_writer import write_wind +from rosco.toolbox.ofTools.fast_io.turbsim_io.turbsim_vartrees import turbsiminputs +from rosco.toolbox.ofTools.fast_io.turbsim_io.turbulence_spectrum import turb_specs +from rosco.toolbox.ofTools.fast_io.turbsim_io.wind_profile_writer import write_wind import os import numpy as np import random diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbulence_spectrum.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/turbulence_spectrum.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/turbulence_spectrum.py rename to rosco/toolbox/ofTools/fast_io/turbsim_io/turbulence_spectrum.py diff --git a/ROSCO_toolbox/ofTools/fast_io/turbsim_io/wind_profile_writer.py b/rosco/toolbox/ofTools/fast_io/turbsim_io/wind_profile_writer.py similarity index 100% rename from ROSCO_toolbox/ofTools/fast_io/turbsim_io/wind_profile_writer.py rename to rosco/toolbox/ofTools/fast_io/turbsim_io/wind_profile_writer.py diff --git a/ROSCO_toolbox/ofTools/fast_io/update_discons.py b/rosco/toolbox/ofTools/fast_io/update_discons.py similarity index 63% rename from ROSCO_toolbox/ofTools/fast_io/update_discons.py rename to rosco/toolbox/ofTools/fast_io/update_discons.py index 6c8b6271..a1604b50 100644 --- a/ROSCO_toolbox/ofTools/fast_io/update_discons.py +++ b/rosco/toolbox/ofTools/fast_io/update_discons.py @@ -1,8 +1,8 @@ import os # ROSCO toolbox modules -from ROSCO_toolbox.utilities import write_DISCON -from ROSCO_toolbox.tune import yaml_to_objs +from rosco.toolbox.utilities import write_DISCON +from rosco.toolbox.tune import yaml_to_objs def update_discons(tune_to_test_map): # Update a set of discon files @@ -15,10 +15,16 @@ def update_discons(tune_to_test_map): if not isinstance(tune_to_test_map[tuning_yaml],list): tune_to_test_map[tuning_yaml] = [tune_to_test_map[tuning_yaml]] + # Handle relative directory to Cp file + yaml_dir = os.path.dirname(tuning_yaml) + cp_filename = os.path.relpath( + os.path.join(yaml_dir,path_params['rotor_performance_filename']), + os.path.join(yaml_dir,path_params['FAST_directory'])) + discon_in_files = [f for f in tune_to_test_map[tuning_yaml]] for discon in discon_in_files: write_DISCON( turbine,controller, param_file=discon, - txt_filename=path_params['rotor_performance_filename'] + txt_filename=cp_filename ) diff --git a/ROSCO_toolbox/ofTools/util/FileTools.py b/rosco/toolbox/ofTools/util/FileTools.py similarity index 100% rename from ROSCO_toolbox/ofTools/util/FileTools.py rename to rosco/toolbox/ofTools/util/FileTools.py diff --git a/rosco/toolbox/ofTools/util/__init__.py b/rosco/toolbox/ofTools/util/__init__.py new file mode 100644 index 00000000..e69de29b diff --git a/ROSCO_toolbox/ofTools/util/spectral.py b/rosco/toolbox/ofTools/util/spectral.py similarity index 100% rename from ROSCO_toolbox/ofTools/util/spectral.py rename to rosco/toolbox/ofTools/util/spectral.py diff --git a/ROSCO_toolbox/sim.py b/rosco/toolbox/sim.py similarity index 99% rename from ROSCO_toolbox/sim.py rename to rosco/toolbox/sim.py index 39ab71f6..2c845ca7 100644 --- a/ROSCO_toolbox/sim.py +++ b/rosco/toolbox/sim.py @@ -10,7 +10,7 @@ # speROSCO_cific language governing permissions and limitations under the License. import numpy as np -from ROSCO_toolbox import turbine as ROSCO_turbine +from rosco.toolbox import turbine as ROSCO_turbine import matplotlib.pyplot as plt import sys diff --git a/ROSCO_toolbox/tune.py b/rosco/toolbox/tune.py similarity index 54% rename from ROSCO_toolbox/tune.py rename to rosco/toolbox/tune.py index e4d5392c..fa121247 100644 --- a/ROSCO_toolbox/tune.py +++ b/rosco/toolbox/tune.py @@ -10,10 +10,10 @@ # specific language governing permissions and limitations under the License. import os -from ROSCO_toolbox import controller as ROSCO_controller -from ROSCO_toolbox import turbine as ROSCO_turbine -from ROSCO_toolbox.inputs.validation import load_rosco_yaml -from ROSCO_toolbox.utilities import read_DISCON, write_DISCON, DISCON_dict +from rosco.toolbox import controller as ROSCO_controller +from rosco.toolbox import turbine as ROSCO_turbine +from rosco.toolbox.inputs.validation import load_rosco_yaml +from rosco.toolbox.utilities import read_DISCON, write_DISCON, DISCON_dict def yaml_to_objs(tuning_yaml): @@ -36,7 +36,7 @@ def yaml_to_objs(tuning_yaml): path_params['FAST_InputFile'], os.path.join(yaml_dir,path_params['FAST_directory']), rot_source='txt', - txt_filename=os.path.join(yaml_dir,path_params['FAST_directory'],path_params['rotor_performance_filename']) + txt_filename=os.path.join(yaml_dir,path_params['rotor_performance_filename']) ) # Tune controller @@ -58,7 +58,7 @@ def update_discon_version(file,tuning_yaml,new_discon_filename): ] # Read original DISCON - discon_vt = read_DISCON(file) + original_vt = read_DISCON(file) # Tune dummy controller to get objects controller, turbine, _ = yaml_to_objs(tuning_yaml) @@ -66,17 +66,54 @@ def update_discon_version(file,tuning_yaml,new_discon_filename): # Load default inputs discon_defaults = DISCON_dict(turbine,controller) - # A simple update doesn't handle type changes + # If no value in old discon, set default to start. Note: a simple update doesn't handle type changes new_discon = {} for param in discon_defaults: # If the value is in the original DISCON and not excluded, use the original - if (param in discon_vt) and (param not in exclude_list): - new_discon[param] = discon_vt[param] + if (param in original_vt) and (param not in exclude_list): + new_discon[param] = original_vt[param] # Otherwise, use the new default else: new_discon[param] = discon_defaults[param] + # Now handle edge cases + + # Torque control: broken into 2 input modes after 2.9.0 + # For newer versions, where VS_ConstPower is not an option, don't do this + if 'VS_ConstPower' not in original_vt: + if original_vt['VS_ControlMode'] == 0: + new_discon['VS_ControlMode'] = 1 + new_discon['VS_ConstPower'] = 0 + elif original_vt['VS_ControlMode'] == 1: + new_discon['VS_ControlMode'] = 1 + new_discon['VS_ConstPower'] = 1 + elif original_vt['VS_ControlMode'] == 2: + new_discon['VS_ControlMode'] = 2 + new_discon['VS_ConstPower'] = 0 + elif original_vt['VS_ControlMode'] == 3: + new_discon['VS_ControlMode'] = 2 + new_discon['VS_ConstPower'] = 1 + + # Notch filters + if 'F_NumNotchFilts' not in original_vt: + if original_vt['F_NotchType'] == 0: + new_discon['F_NumNotchFilts'] = 0 + else: + new_discon['F_NumNotchFilts'] = 1 + new_discon['F_NotchFreqs'] = [original_vt['F_NotchCornerFreq']] + new_discon['F_NotchBetaNum'] = [original_vt['F_NotchBetaNumDen'][0]] + new_discon['F_NotchBetaDen'] = [original_vt['F_NotchBetaNumDen'][1]] + + if original_vt['F_NotchType'] == 1 or original_vt['F_NotchType'] == 3: + new_discon['F_GenSpdNotch_N'] = 1 + new_discon['F_GenSpdNotch_Ind'] = [1] + + if original_vt['F_NotchType'] == 2 or original_vt['F_NotchType'] == 3: + new_discon['F_TwrTopNotch_N'] = 1 + new_discon['F_TwrTopNotch_Ind'] = [1] + + # Make the DISCON write_DISCON( turbine, diff --git a/ROSCO_toolbox/turbine.py b/rosco/toolbox/turbine.py similarity index 93% rename from ROSCO_toolbox/turbine.py rename to rosco/toolbox/turbine.py index 9aa61932..73965285 100644 --- a/ROSCO_toolbox/turbine.py +++ b/rosco/toolbox/turbine.py @@ -18,16 +18,16 @@ import matplotlib.pyplot as plt import pandas as pd -from ROSCO_toolbox.utilities import load_from_txt +from rosco.toolbox.utilities import load_from_txt # Load OpenFAST readers try: import weis.aeroelasticse use_weis = True - print('Using weis.aeroelasticse in ROSCO_toolbox...') + print('Using weis.aeroelasticse in rosco.toolbox...') except: use_weis = False - print('Using ofTools in ROSCO_toolbox...') + print('Using ofTools in rosco.toolbox...') # Some useful constants @@ -86,6 +86,7 @@ def __init__(self, turbine_params): self.bld_edgewise_freq = turbine_params['bld_edgewise_freq'] self.TSR_operational = turbine_params['TSR_operational'] self.bld_flapwise_freq = turbine_params['bld_flapwise_freq'] + self.turbine_params = turbine_params # Allow print out of class @@ -157,7 +158,7 @@ def load_from_fast( if use_weis: from weis.aeroelasticse.FAST_reader import InputReader_OpenFAST else: - from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST + from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST # Load OpenFAST model using the FAST_reader print('Loading FAST model: %s ' % FAST_InputFile) @@ -177,8 +178,11 @@ def load_from_fast( fast.read_AeroDyn15() - fast.read_ServoDyn() - fast.read_DISCON_in() + if fast.fst_vt['Fst']['CompServo']: + fast.read_ServoDyn() + fast.read_DISCON_in() + else: + fast.fst_vt['ServoDyn']['GenEff'] = 1.0 if fast.fst_vt['Fst']['CompHydro'] == 1: # SubDyn not yet implimented @@ -202,11 +206,19 @@ def load_from_fast( self.NumBl = fast.fst_vt['ElastoDyn']['NumBl'] self.TowerHt = fast.fst_vt['ElastoDyn']['TowerHt'] self.shearExp = 0.2 #NOTE: HARD CODED + + # Fluid density if 'default' in str(fast.fst_vt['AeroDyn15']['AirDens']): - fast.fst_vt['AeroDyn15']['AirDens'] = 1.225 + if fast.fst_vt['Fst']['MHK']: + fast.fst_vt['AeroDyn15']['AirDens'] = fast.fst_vt['Fst']['WtrDens'] + else: + fast.fst_vt['AeroDyn15']['AirDens'] = fast.fst_vt['Fst']['AirDens'] self.rho = fast.fst_vt['AeroDyn15']['AirDens'] + + # Kinematic viscosity if 'default' in str(fast.fst_vt['AeroDyn15']['KinVisc']): - fast.fst_vt['AeroDyn15']['KinVisc'] = 1.460e-5 + fast.fst_vt['AeroDyn15']['KinVisc'] = fast.fst_vt['Fst']['KinVisc'] + self.mu = fast.fst_vt['AeroDyn15']['KinVisc'] self.Ng = fast.fst_vt['ElastoDyn']['GBRatio'] self.GenEff = fast.fst_vt['ServoDyn']['GenEff'] @@ -339,8 +351,8 @@ def generate_rotperf_fast(self, openfast_path, FAST_runDirectory=None, run_BeamD from weis.aeroelasticse import runFAST_pywrapper, CaseGen_General from weis.aeroelasticse.Util import FileTools else: - from ROSCO_toolbox.ofTools.case_gen import runFAST_pywrapper, CaseGen_General - from ROSCO_toolbox.ofTools.util import FileTools + from rosco.toolbox.ofTools.case_gen import runFAST_pywrapper, CaseGen_General + from rosco.toolbox.ofTools.util import FileTools # Load pCrunch tools from pCrunch import Processing @@ -524,7 +536,7 @@ def load_blade_info(self): if use_weis: from weis.aeroelasticse.FAST_reader import InputReader_OpenFAST else: - from ROSCO_toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST + from rosco.toolbox.ofTools.fast_io.FAST_reader import InputReader_OpenFAST from wisdem.ccblade.ccblade import CCAirfoil, CCBlade # Create CC-Blade Rotor @@ -538,16 +550,24 @@ def load_blade_info(self): # Read OpenFAST Airfoil data, assumes AeroDyn > v15.03 and associated polars > v1.01 af_dict = {} for i, section in enumerate(self.fast.fst_vt['AeroDyn15']['af_data']): - Alpha = section[0]['Alpha'] if section[0]['NumTabs'] > 1: # sections with multiple airfoil tables - ref_tab = int(np.floor(section[0]['NumTabs']/2)) # get information from "center" table - Re = np.array([section[ref_tab]['Re']])*1e6 + reynolds_ref = self.turbine_params['reynolds_ref'] + if reynolds_ref: # default is 0 + # find closest table to reynolds_ref, interpolate someday, approximate is probably okay + Res_in_table = np.array([sec['Re'] for sec in section]) + ref_tab = np.abs(Res_in_table - reynolds_ref).argmin() + else: + print("ROSCO Warning: No Reynolds number provided and airfoils have multiple tables, using center table") + ref_tab = int(np.floor(section[0]['NumTabs']/2)) # get information from "center" table + Alpha = section[ref_tab]['Alpha'] + Re = np.array([section[ref_tab]['Re']]) Cl = section[ref_tab]['Cl'] Cd = section[ref_tab]['Cd'] Cm = section[ref_tab]['Cm'] af_dict[i] = CCAirfoil(Alpha, Re, Cl, Cd, Cm) - else: # sections without multiple airfoil tables - Re = np.array([section[0]['Re']])*1e6 + else: + Alpha = section[0]['Alpha'] # sections without multiple airfoil tables + Re = np.array([section[0]['Re']]) Cl = section[0]['Cl'] Cd = section[0]['Cd'] Cm = section[0]['Cm'] @@ -613,7 +633,7 @@ def __init__(self,performance_table, pitch_initial_rad, TSR_initial): # If there is more than one max pitch angle: if len(self.max_ind[1]) > 1: - print('ROSCO_toolbox Warning: repeated maximum values in a performance table and the last one @ pitch = {} rad. was taken...'.format(self.pitch_opt[-1])) + print('rosco.toolbox Warning: repeated maximum values in a performance table and the last one @ pitch = {} rad. was taken...'.format(self.pitch_opt[-1])) # Find TSR that maximizes Cx at fine pitch # - TSR to satisfy: max( Cx(TSR, \beta_fine) ) = TSR_opt @@ -623,7 +643,7 @@ def __init__(self,performance_table, pitch_initial_rad, TSR_initial): f_performance = interpolate.interp1d(TSR_initial,performance_beta_max,bounds_error='False',kind='quadratic') # interpolate function for Cx(tsr) values performance_fine = f_performance(TSR_fine_ind) # Cx values at fine pitch performance_max_ind = np.where(performance_fine == np.max(performance_fine)) # Find max performance at fine pitch - self.TSR_opt = float(TSR_fine[performance_max_ind[0]]) # TSR to maximize Cx at fine pitch + self.TSR_opt = float(TSR_fine[performance_max_ind[0]][0]) # TSR to maximize Cx at fine pitch def interp_surface(self,pitch,TSR): ''' diff --git a/ROSCO_toolbox/utilities.py b/rosco/toolbox/utilities.py similarity index 72% rename from ROSCO_toolbox/utilities.py rename to rosco/toolbox/utilities.py index cf7f3218..15e4d550 100644 --- a/ROSCO_toolbox/utilities.py +++ b/rosco/toolbox/utilities.py @@ -26,10 +26,11 @@ import os import numpy as np import subprocess -import ROSCO_toolbox +import rosco.toolbox from wisdem.inputs import load_yaml from wisdem.inputs import load_yaml +from rosco.toolbox.ofTools.util.FileTools import remove_numpy # Some useful constants now = datetime.datetime.now() @@ -84,54 +85,64 @@ def write_DISCON(turbine, controller, param_file='DISCON.IN', txt_filename='Cp_C # Should be obvious what's going on here... file = open(param_file,'w') file.write('! Controller parameter input file for the %s wind turbine\n' % turbine.TurbineName) - file.write('! - File written using ROSCO version {} controller tuning logic on {}\n'.format(ROSCO_toolbox.__version__, now.strftime('%m/%d/%y'))) + file.write('! - File written using ROSCO version {} controller tuning logic on {}\n'.format(rosco.toolbox.__version__, now.strftime('%m/%d/%y'))) file.write('\n') - file.write('!------- DEBUG ------------------------------------------------------------\n') - file.write('{0:<12d} ! LoggingLevel - (0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3))\n'.format(int(rosco_vt['LoggingLevel']))) + file.write('!------- SIMULATION CONTROL ------------------------------------------------------------\n') + file.write('{0:<12d} ! LoggingLevel - {{0: write no debug files, 1: write standard output .dbg-file, 2: LoggingLevel 1 + ROSCO LocalVars (.dbg2) 3: LoggingLevel 2 + complete avrSWAP-array (.dbg3)}}\n'.format(int(rosco_vt['LoggingLevel']))) + file.write('{} ! DT_Out - {{Time step to output .dbg* files, or 0 to match sampling period of OpenFAST}}\n'.format(rosco_vt['DT_Out'])) + file.write('{:<11d} ! Ext_Interface - ({})\n'.format(int(rosco_vt['Ext_Interface']), input_descriptions['Ext_Interface'])) file.write('{:<11d} ! Echo - ({})\n'.format(int(rosco_vt['Echo']), input_descriptions['Echo'])) file.write('\n') file.write('!------- CONTROLLER FLAGS -------------------------------------------------\n') - file.write('{0:<12d} ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals\n'.format(int(rosco_vt['F_LPFType']))) - file.write('{0:<12d} ! F_NotchType - Notch on the measured generator speed and/or tower fore-aft motion (for floating) {{0: disable, 1: generator speed, 2: tower-top fore-aft motion, 3: generator speed and tower-top fore-aft motion}}\n'.format(int(rosco_vt['F_NotchType']))) + file.write('{0:<12d} ! F_LPFType - (1: first-order low-pass filter, 2: second-order low-pass filter), [rad/s] (currently filters generator speed and pitch control signals\n'.format(int(rosco_vt['F_LPFType']))) file.write('{0:<12d} ! IPC_ControlMode - Turn Individual Pitch Control (IPC) for fatigue load reductions (pitch contribution) {{0: off, 1: 1P reductions, 2: 1P+2P reductions}}\n'.format(int(rosco_vt['IPC_ControlMode']))) - file.write('{0:<12d} ! VS_ControlMode - Generator torque control mode in above rated conditions {{0: constant torque, 1: constant power, 2: TSR tracking PI control with constant torque, 3: TSR tracking PI control with constant power}}\n'.format(int(rosco_vt['VS_ControlMode']))) - file.write('{0:<12d} ! PC_ControlMode - Blade pitch control mode {{0: No pitch, fix to fine pitch, 1: active PI blade pitch control}}\n'.format(int(rosco_vt['PC_ControlMode']))) - file.write('{0:<12d} ! Y_ControlMode - Yaw control mode {{0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC}}\n'.format(int(rosco_vt['Y_ControlMode']))) - file.write('{0:<12d} ! SS_Mode - Setpoint Smoother mode {{0: no setpoint smoothing, 1: introduce setpoint smoothing}}\n'.format(int(rosco_vt['SS_Mode']))) - file.write('{0:<12d} ! WE_Mode - Wind speed estimator mode {{0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter}}\n'.format(int(rosco_vt['WE_Mode']))) - file.write('{0:<12d} ! PS_Mode - Pitch saturation mode {{0: no pitch saturation, 1: implement pitch saturation}}\n'.format(int(rosco_vt['PS_Mode']))) - file.write('{0:<12d} ! SD_Mode - Shutdown mode {{0: no shutdown procedure, 1: pitch to max pitch at shutdown}}\n'.format(int(rosco_vt['SD_Mode']))) - file.write('{0:<12d} ! Fl_Mode - Floating specific feedback mode {{0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty}}\n'.format(int(rosco_vt['Fl_Mode']))) - file.write('{0:<12d} ! TD_Mode - Tower damper mode {{0: no tower damper, 1: feed back translational nacelle accelleration to pitch angle}}\n'.format(int(rosco_vt['TD_Mode']))) - file.write('{0:<12d} ! Flp_Mode - Flap control mode {{0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control}}\n'.format(int(rosco_vt['Flp_Mode']))) - file.write('{0:<12d} ! OL_Mode - Open loop control mode {{0: no open loop control, 1: open loop control vs. time}}\n'.format(int(rosco_vt['OL_Mode']))) - file.write('{0:<12d} ! PA_Mode - Pitch actuator mode {{0 - not used, 1 - first order filter, 2 - second order filter}}\n'.format(int(rosco_vt['PA_Mode']))) - file.write('{0:<12d} ! PF_Mode - Pitch fault mode {{0 - not used, 1 - constant offset on one or more blades}}\n'.format(int(rosco_vt['PF_Mode']))) - file.write('{0:<12d} ! AWC_Mode - Active wake control {{0 - not used, 1 - complex number method, 2 - Coleman transform method}}\n'.format(int(rosco_vt['AWC_Mode']))) - file.write('{0:<12d} ! Ext_Mode - External control mode {{0 - not used, 1 - call external dynamic library}}\n'.format(int(rosco_vt['Ext_Mode']))) - file.write('{0:<12d} ! ZMQ_Mode - Fuse ZeroMQ interface {{0: unused, 1: Yaw Control}}\n'.format(int(rosco_vt['ZMQ_Mode']))) - file.write('{:<12d} ! CC_Mode - {}\n'.format(int(rosco_vt['CC_Mode']),mode_descriptions['CC_Mode'])) - file.write('{:<12d} ! StC_Mode - {}\n'.format(int(rosco_vt['StC_Mode']),mode_descriptions['StC_Mode'])) + file.write('{0:<12d} ! VS_ControlMode - Generator torque control mode in above rated conditions (0- no torque control, 1- k*omega^2 with PI transitions, 2- WSE TSR Tracking, 3- Power-based TSR Tracking)}}\n'.format(int(rosco_vt['VS_ControlMode']))) + file.write('{0:<12d} ! VS_ConstPower - Do constant power torque control, where above rated torque varies, 0 for constant torque}}\n'.format(int(rosco_vt['VS_ConstPower']))) + file.write('{0:<12d} ! PC_ControlMode - Blade pitch control mode {{0: No pitch, fix to fine pitch, 1: active PI blade pitch control}}\n'.format(int(rosco_vt['PC_ControlMode']))) + file.write('{0:<12d} ! Y_ControlMode - Yaw control mode {{0: no yaw control, 1: yaw rate control, 2: yaw-by-IPC}}\n'.format(int(rosco_vt['Y_ControlMode']))) + file.write('{0:<12d} ! SS_Mode - Setpoint Smoother mode {{0: no setpoint smoothing, 1: introduce setpoint smoothing}}\n'.format(int(rosco_vt['SS_Mode']))) + file.write('{0:<12d} ! PRC_Mode - Power reference tracking mode{{0: use standard rotor speed set points, 1: use PRC rotor speed setpoints}}\n'.format(int(rosco_vt['PRC_Mode']))) + file.write('{0:<12d} ! WE_Mode - Wind speed estimator mode {{0: One-second low pass filtered hub height wind speed, 1: Immersion and Invariance Estimator, 2: Extended Kalman Filter}}\n'.format(int(rosco_vt['WE_Mode']))) + file.write('{0:<12d} ! PS_Mode - Pitch saturation mode {{0: no pitch saturation, 1: implement pitch saturation}}\n'.format(int(rosco_vt['PS_Mode']))) + file.write('{0:<12d} ! SD_Mode - Shutdown mode {{0: no shutdown procedure, 1: pitch to max pitch at shutdown}}\n'.format(int(rosco_vt['SD_Mode']))) + file.write('{0:<12d} ! Fl_Mode - Floating specific feedback mode {{0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational veloicty}}\n'.format(int(rosco_vt['Fl_Mode']))) + file.write('{:<12d} ! TD_Mode - {}\n'.format(int(rosco_vt['TD_Mode']),mode_descriptions['TD_Mode'])) + file.write('{:<12d} ! TRA_Mode - {}\n'.format(int(rosco_vt['TRA_Mode']),mode_descriptions['TRA_Mode'])) + file.write('{0:<12d} ! Flp_Mode - Flap control mode {{0: no flap control, 1: steady state flap angle, 2: Proportional flap control, 2: Cyclic (1P) flap control}}\n'.format(int(rosco_vt['Flp_Mode']))) + file.write('{0:<12d} ! OL_Mode - Open loop control mode {{0: no open loop control, 1: open loop control vs. time, 2: rotor position control}}\n'.format(int(rosco_vt['OL_Mode']))) + file.write('{0:<12d} ! PA_Mode - Pitch actuator mode {{0 - not used, 1 - first order filter, 2 - second order filter}}\n'.format(int(rosco_vt['PA_Mode']))) + file.write('{0:<12d} ! PF_Mode - Pitch fault mode {{0 - not used, 1 - constant offset on one or more blades}}\n'.format(int(rosco_vt['PF_Mode']))) + file.write('{0:<12d} ! AWC_Mode - Active wake control {{0 - not used, 1 - complex number method, 2 - Coleman transform method}}\n'.format(int(rosco_vt['AWC_Mode']))) + file.write('{0:<12d} ! Ext_Mode - External control mode {{0 - not used, 1 - call external dynamic library}}\n'.format(int(rosco_vt['Ext_Mode']))) + file.write('{0:<12d} ! ZMQ_Mode - Fuse ZeroMQ interface {{0: unused, 1: Yaw Control}}\n'.format(int(rosco_vt['ZMQ_Mode']))) + file.write('{:<12d} ! CC_Mode - {}\n'.format(int(rosco_vt['CC_Mode']),mode_descriptions['CC_Mode'])) + file.write('{:<12d} ! StC_Mode - {}\n'.format(int(rosco_vt['StC_Mode']),mode_descriptions['StC_Mode'])) file.write('\n') file.write('!------- FILTERS ----------------------------------------------------------\n') - file.write('{:<13.5f} ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s]\n'.format(rosco_vt['F_LPFCornerFreq'])) - file.write('{:<13.5f} ! F_LPFDamping - Damping coefficient {{used only when F_FilterType = 2}} [-]\n'.format(rosco_vt['F_LPFDamping'])) - file.write('{:<13.5f} ! F_NotchCornerFreq - Natural frequency of the notch filter, [rad/s]\n'.format(rosco_vt['F_NotchCornerFreq'])) - file.write('{}! F_NotchBetaNumDen - Two notch damping values (numerator and denominator, resp) - determines the width and depth of the notch, [-]\n'.format(''.join('{:<4.6f} '.format(rosco_vt['F_NotchBetaNumDen'][i]) for i in range(len(rosco_vt['F_NotchBetaNumDen']))))) + file.write('{:<13.5f} ! F_LPFCornerFreq - Corner frequency (-3dB point) in the low-pass filters, [rad/s]\n'.format(rosco_vt['F_LPFCornerFreq'])) + file.write('{:<13.5f} ! F_LPFDamping - Damping coefficient {{used only when F_FilterType = 2}} [-]\n'.format(rosco_vt['F_LPFDamping'])) + file.write('{:<12d} ! F_NumNotchFilts - {}\n'.format(int(rosco_vt["F_NumNotchFilts"]), input_descriptions["F_NumNotchFilts"])) + file.write('{} ! F_NotchFreqs - {}\n'.format(write_array(rosco_vt["F_NotchFreqs"]), input_descriptions["F_NotchFreqs"])) + file.write('{} ! F_NotchBetaNum - {}\n'.format(write_array(rosco_vt['F_NotchBetaNum']), input_descriptions["F_NotchBetaNum"])) + file.write('{} ! F_NotchBetaDen - {}\n'.format(write_array(rosco_vt['F_NotchBetaDen']), input_descriptions["F_NotchBetaDen"])) + file.write('{:<12d} ! F_GenSpdNotch_N - {}\n'.format(int(rosco_vt['F_GenSpdNotch_N']), input_descriptions["F_GenSpdNotch_N"])) + file.write('{} ! F_GenSpdNotch_Ind - {}\n'.format(write_array(rosco_vt['F_GenSpdNotch_Ind'],'d'), input_descriptions["F_GenSpdNotch_Ind"])) + file.write('{:<12d} ! F_TwrTopNotch_N - {}\n'.format(int(rosco_vt['F_TwrTopNotch_N']), input_descriptions["F_TwrTopNotch_N"])) + file.write('{} ! F_TwrTopNotch_Ind - {}\n'.format(write_array(rosco_vt['F_TwrTopNotch_Ind'],'d'), input_descriptions["F_TwrTopNotch_Ind"])) file.write('{:<13.5f} ! F_SSCornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the setpoint smoother, [rad/s].\n'.format(rosco_vt['F_SSCornerFreq'])) file.write('{:<13.5f} ! F_WECornerFreq - Corner frequency (-3dB point) in the first order low pass filter for the wind speed estimate [rad/s].\n'.format(rosco_vt['F_WECornerFreq'])) file.write('{:<13.5f} ! F_YawErr - Low pass filter corner frequency for yaw controller [rad/s].\n'.format(rosco_vt['F_YawErr'])) file.write('{}! F_FlCornerFreq - Natural frequency and damping in the second order low pass filter of the tower-top fore-aft motion for floating feedback control [rad/s, -].\n'.format(''.join('{:<4.6f} '.format(rosco_vt['F_FlCornerFreq'][i]) for i in range(len(rosco_vt['F_FlCornerFreq']))))) - file.write('{:<13.5f} ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s].\n'.format(rosco_vt['F_FlHighPassFreq'])) - file.write('{}! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control [rad/s, -].\n'.format(''.join('{:<4.6f} '.format(rosco_vt['F_FlpCornerFreq'][i]) for i in range(len(rosco_vt['F_FlpCornerFreq']))))) + file.write('{:<13.5f} ! F_FlHighPassFreq - Natural frequency of first-order high-pass filter for nacelle fore-aft motion [rad/s].\n'.format(rosco_vt['F_FlHighPassFreq'])) + file.write('{} ! F_FlpCornerFreq - {}\n'.format(write_array(rosco_vt["F_FlpCornerFreq"]), input_descriptions["F_FlpCornerFreq"])) file.write('\n') file.write('!------- BLADE PITCH CONTROL ----------------------------------------------\n') file.write('{:<11d} ! PC_GS_n - Amount of gain-scheduling table entries\n'.format(int(rosco_vt['PC_GS_n']))) file.write('{} ! PC_GS_angles - Gain-schedule table: pitch angles [rad].\n'.format(''.join('{:<4.6f} '.format(rosco_vt['PC_GS_angles'][i]) for i in range(len(rosco_vt['PC_GS_angles']))))) file.write('{} ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s].\n'.format(''.join('{:<4.6f} '.format(rosco_vt['PC_GS_KP'][i]) for i in range(len(rosco_vt['PC_GS_KP']))))) - file.write('{} ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-].\n'.format(''.join('{:<4.6f} '.format(rosco_vt['PC_GS_KI'][i]) for i in range(len(rosco_vt['PC_GS_KI']))))) + file.write('{} ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-].\n'.format(''.join('{:<4.6f} '.format(rosco_vt['PC_GS_KI'][i]) for i in range(len(rosco_vt['PC_GS_KI'])))))# file.write('{} ! PC_GS_KD - Gain-schedule table: pitch controller kd gains\n'.format(''.join('{:<4.6f} '.format(rosco_vt['PC_GS_KD'][i]) for i in range(len(rosco_vt['PC_GS_KD']))))) file.write('{} ! PC_GS_TF - Gain-schedule table: pitch controller tf gains (derivative filter)\n'.format(''.join('{:<4.6f} '.format(rosco_vt['PC_GS_TF'][i]) for i in range(len(rosco_vt['PC_GS_TF']))))) file.write('{:<014.5f} ! PC_MaxPit - Maximum physical pitch limit, [rad].\n'.format(rosco_vt['PC_MaxPit'])) @@ -158,26 +169,33 @@ def write_DISCON(turbine, controller, param_file='DISCON.IN', txt_filename='Cp_C file.write('{:<014.5f} ! VS_MaxTq - Maximum generator torque in Region 3 (HSS side), [Nm].\n'.format(rosco_vt['VS_MaxTq'])) file.write('{:<014.5f} ! VS_MinTq - Minimum generator torque (HSS side), [Nm].\n'.format(rosco_vt['VS_MinTq'])) file.write('{:<014.5f} ! VS_MinOMSpd - Minimum generator speed [rad/s]\n'.format(rosco_vt['VS_MinOMSpd'])) - file.write('{:<014.5f} ! VS_Rgn2K - Generator torque constant in Region 2 (HSS side), [Nm/(rad/s)^2]\n'.format(rosco_vt['VS_Rgn2K'])) + file.write('{:<014.5f} ! VS_Rgn2K - {}\n'.format(float(rosco_vt['VS_Rgn2K']),input_descriptions['VS_Rgn2K'])) file.write('{:<014.5f} ! VS_RtPwr - Wind turbine rated power [W]\n'.format(rosco_vt['VS_RtPwr'])) file.write('{:<014.5f} ! VS_RtTq - Rated torque, [Nm].\n'.format(rosco_vt['VS_RtTq'])) file.write('{:<014.5f} ! VS_RefSpd - Rated generator speed [rad/s]\n'.format(rosco_vt['VS_RefSpd'])) file.write('{:<11d} ! VS_n - Number of generator PI torque controller gains\n'.format(int(rosco_vt['VS_n']))) file.write('{:<014.5f} ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2)\n'.format(rosco_vt['VS_KP'])) file.write('{:<014.5f} ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2)\n'.format(rosco_vt['VS_KI'])) - file.write('{:<13.2f} ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio [rad].\n'.format(rosco_vt['VS_TSRopt'])) + file.write('{:<13.2f} ! VS_TSRopt - {}\n'.format(float(rosco_vt['VS_TSRopt']),input_descriptions['VS_TSRopt'])) + file.write('{:<014.5f} ! VS_PwrFiltF - {}\n'.format(float(rosco_vt['VS_PwrFiltF']),input_descriptions['VS_PwrFiltF'])) file.write('\n') file.write('!------- SETPOINT SMOOTHER ---------------------------------------------\n') file.write('{:<13.5f} ! SS_VSGain - Variable speed torque controller setpoint smoother gain, [-].\n'.format(rosco_vt['SS_VSGain'])) file.write('{:<13.5f} ! SS_PCGain - Collective pitch controller setpoint smoother gain, [-].\n'.format(rosco_vt['SS_PCGain'])) file.write('\n') + file.write('!------- POWER REFERENCE TRACKING --------------------------------------\n') + file.write('{:<11d} ! PRC_n - Number of elements in PRC_WindSpeeds and PRC_GenSpeeds array\n'.format(int(rosco_vt['PRC_n']))) + file.write('{:<13.5f} ! PRC_LPF_Freq - {}\n'.format(float(rosco_vt['PRC_LPF_Freq']), input_descriptions["PRC_LPF_Freq"])) + file.write('{} ! PRC_WindSpeeds - {}\n'.format(write_array(rosco_vt["PRC_WindSpeeds"]), input_descriptions["PRC_WindSpeeds"])) + file.write('{} ! PRC_GenSpeeds - {}\n'.format(write_array(rosco_vt["PRC_GenSpeeds"]), input_descriptions["PRC_GenSpeeds"])) + file.write('\n') file.write('!------- WIND SPEED ESTIMATOR ---------------------------------------------\n') file.write('{:<13.3f} ! WE_BladeRadius - Blade length (distance from hub center to blade tip), [m]\n'.format(rosco_vt['WE_BladeRadius'])) file.write('{:<11d} ! WE_CP_n - Amount of parameters in the Cp array\n'.format(int(rosco_vt['WE_CP_n']))) file.write('{:<13.1f} ! WE_CP - Parameters that define the parameterized CP(lambda) function\n'.format(rosco_vt['WE_CP'])) - file.write('{:<13.1f} ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad]\n'.format(rosco_vt['WE_Gamma'])) + file.write('{:<13.1f} ! WE_Gamma - Adaption gain of the wind speed estimator algorithm [m/rad]\n'.format(rosco_vt['WE_Gamma'])) file.write('{:<13.1f} ! WE_GearboxRatio - Gearbox ratio [>=1], [-]\n'.format(rosco_vt['WE_GearboxRatio'])) - file.write('{:<14.5f} ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2]\n'.format(rosco_vt['WE_Jtot'])) + file.write('{:<14.5f} ! WE_Jtot - Total drivetrain inertia, including blades, hub and casted generator inertia to LSS, [kg m^2]\n'.format(rosco_vt['WE_Jtot'])) file.write('{:<13.3f} ! WE_RhoAir - Air density, [kg m^-3]\n'.format(rosco_vt['WE_RhoAir'])) file.write( '"{}" ! PerfFileName - File containing rotor performance tables (Cp,Ct,Cq) (absolute path or relative to this file)\n'.format(rosco_vt['PerfFileName'])) file.write('{:<7d} {:<10d} ! PerfTableSize - Size of rotor performance tables, first number refers to number of blade pitch angles, second number referse to number of tip-speed ratios\n'.format(int(rosco_vt['PerfTableSize'][0]),int(rosco_vt['PerfTableSize'][1]))) @@ -194,15 +212,18 @@ def write_DISCON(turbine, controller, param_file='DISCON.IN', txt_filename='Cp_C file.write('{:<13.5f} ! Y_IPC_KP - Yaw-by-IPC proportional controller gain Kp\n'.format(rosco_vt['Y_IPC_KP'])) file.write('{:<13.5f} ! Y_IPC_KI - Yaw-by-IPC integral controller gain Ki\n'.format(rosco_vt['Y_IPC_KI'])) file.write('\n') - file.write('!------- TOWER FORE-AFT DAMPING -------------------------------------------\n') - file.write('{:<13.5f} ! FA_KI - Integral gain for the fore-aft tower damper controller [rad s/m]\n'.format(rosco_vt['FA_KI'] )) - file.write('{:<13.1f} ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s]\n'.format(rosco_vt['FA_HPFCornerFreq'] )) - file.write('{:<13.1f} ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad]\n'.format(rosco_vt['FA_IntSat'] )) + file.write('!------- TOWER CONTROL ------------------------------------------------------\n') + file.write('{:<13.5f} ! TRA_ExclSpeed - {}\n'.format(rosco_vt['TRA_ExclSpeed'], input_descriptions['TRA_ExclSpeed'] )) + file.write('{:<13.5f} ! TRA_ExclBand - {}\n'.format(rosco_vt['TRA_ExclBand'], input_descriptions['TRA_ExclBand'] )) + file.write('{:<13.5e} ! TRA_RateLimit - {}\n'.format(rosco_vt['TRA_RateLimit'], input_descriptions['TRA_RateLimit'] )) + file.write('{:<13.5f} ! FA_KI - Integral gain for the fore-aft tower damper controller, [rad*s/m]\n'.format(rosco_vt['FA_KI'] )) + file.write('{:<13.5f} ! FA_HPFCornerFreq - Corner frequency (-3dB point) in the high-pass filter on the fore-aft acceleration signal [rad/s]\n'.format(rosco_vt['FA_HPFCornerFreq'] )) + file.write('{:<13.5f} ! FA_IntSat - Integrator saturation (maximum signal amplitude contribution to pitch from FA damper), [rad]\n'.format(rosco_vt['FA_IntSat'] )) file.write('\n') file.write('!------- MINIMUM PITCH SATURATION -------------------------------------------\n') file.write('{:<11d} ! PS_BldPitchMin_N - Number of values in minimum blade pitch lookup table (should equal number of values in PS_WindSpeeds and PS_BldPitchMin)\n'.format(int(rosco_vt['PS_BldPitchMin_N']))) - file.write('{} ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s]\n'.format(''.join('{:<4.4f} '.format(rosco_vt['PS_WindSpeeds'][i]) for i in range(len(rosco_vt['PS_WindSpeeds']))))) - file.write('{} ! PS_BldPitchMin - Minimum blade pitch angles [rad]\n'.format(''.join('{:<10.8f} '.format(rosco_vt['PS_BldPitchMin'][i]) for i in range(len(rosco_vt['PS_BldPitchMin']))))) + file.write('{} ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s]\n'.format(''.join('{:<4.3f} '.format(rosco_vt['PS_WindSpeeds'][i]) for i in range(len(rosco_vt['PS_WindSpeeds']))))) + file.write('{} ! PS_BldPitchMin - Minimum blade pitch angles [rad]\n'.format(''.join('{:<10.3f} '.format(rosco_vt['PS_BldPitchMin'][i]) for i in range(len(rosco_vt['PS_BldPitchMin']))))) file.write('\n') file.write('!------- SHUTDOWN -----------------------------------------------------------\n') file.write('{:<014.5f} ! SD_MaxPit - Maximum blade pitch angle to initiate shutdown, [rad]\n'.format(rosco_vt['SD_MaxPit'])) @@ -213,7 +234,9 @@ def write_DISCON(turbine, controller, param_file='DISCON.IN', txt_filename='Cp_C floatstr = 'pitching' else: floatstr = 'velocity' - file.write('{:<014.5f} ! Fl_Kp - Nacelle {} proportional feedback gain [s]\n'.format(rosco_vt['Fl_Kp'], floatstr)) + file.write('{:<11d} ! Fl_n - Number of Fl_Kp gains in gain scheduling, optional with default of 1\n'.format(int(rosco_vt['Fl_n']))) + file.write('{} ! Fl_Kp - Nacelle {} proportional feedback gain [s]\n'.format(write_array(rosco_vt['Fl_Kp'],'<6.4f'), floatstr)) + file.write('{} ! Fl_U - Wind speeds for scheduling Fl_Kp, optional if Fl_Kp is single value [m/s]\n'.format(write_array(rosco_vt['Fl_U'],'<6.4f'))) file.write('\n') file.write('!------- FLAP ACTUATION -----------------------------------------------------\n') file.write('{:<014.5f} ! Flp_Angle - Initial or steady state flap angle [rad]\n'.format(rosco_vt['Flp_Angle'])) @@ -224,26 +247,28 @@ def write_DISCON(turbine, controller, param_file='DISCON.IN', txt_filename='Cp_C file.write('!------- Open Loop Control -----------------------------------------------------\n') file.write('"{}" ! OL_Filename - Input file with open loop timeseries (absolute path or relative to this file)\n'.format(rosco_vt['OL_Filename'])) file.write('{0:<12d} ! Ind_Breakpoint - The column in OL_Filename that contains the breakpoint (time if OL_Mode = 1)\n'.format(int(rosco_vt['Ind_Breakpoint']))) - file.write('{0:<12d} ! Ind_BldPitch - The column in OL_Filename that contains the blade pitch input in rad\n'.format(int(rosco_vt['Ind_BldPitch']))) + file.write('{} ! Ind_BldPitch - The columns in OL_Filename that contains the blade pitch (1,2,3) inputs in rad [array]\n'.format(' '.join([f'{int(ipb):3d}' for ipb in rosco_vt['Ind_BldPitch']]))) file.write('{0:<12d} ! Ind_GenTq - The column in OL_Filename that contains the generator torque in Nm\n'.format(int(rosco_vt['Ind_GenTq']))) - file.write('{0:<12d} ! Ind_YawRate - The column in OL_Filename that contains the nacelle yaw rate rad/s\n'.format(int(rosco_vt['Ind_YawRate']))) - file.write('{} ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N]\n'.format(write_array(rosco_vt['Ind_CableControl'],'<4d'))) - file.write('{} ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N]\n'.format(write_array(rosco_vt['Ind_StructControl'],'<4d'))) + file.write('{0:<12d} ! Ind_YawRate - The column in OL_Filename that contains the yaw rate in rad/s\n'.format(int(rosco_vt['Ind_YawRate']))) + file.write('{:<12d} ! Ind_Azimuth - {}\n'.format(int(rosco_vt["Ind_Azimuth"]), input_descriptions["Ind_Azimuth"])) + file.write('{} ! {} - {}\n'.format(' '.join([f'{g:02.4f}' for g in rosco_vt["RP_Gains"]]),"RP_Gains",input_descriptions["RP_Gains"])) + file.write('{} ! Ind_CableControl - The column(s) in OL_Filename that contains the cable control inputs in m [Used with CC_Mode = 2, must be the same size as CC_Group_N]\n'.format(write_array(rosco_vt['Ind_CableControl'],'<4d'))) + file.write('{} ! Ind_StructControl - The column(s) in OL_Filename that contains the structural control inputs [Used with StC_Mode = 2, must be the same size as StC_Group_N]\n'.format(write_array(rosco_vt['Ind_StructControl'],'<4d'))) file.write('\n') file.write('!------- Pitch Actuator Model -----------------------------------------------------\n') - file.write('{:<014.5f} ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s]\n'.format(rosco_vt['PA_CornerFreq'])) - file.write('{:<014.5f} ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1]\n'.format(rosco_vt['PA_Damping'])) + file.write('{:<014.5f} ! PA_CornerFreq - Pitch actuator bandwidth/cut-off frequency [rad/s]\n'.format(rosco_vt['PA_CornerFreq'])) + file.write('{:<014.5f} ! PA_Damping - Pitch actuator damping ratio [-, unused if PA_Mode = 1]\n'.format(rosco_vt['PA_Damping'])) file.write('\n') file.write('!------- Pitch Actuator Faults -----------------------------------------------------\n') file.write('{} ! PF_Offsets - Constant blade pitch offsets for blades 1-3 [rad]\n'.format(''.join('{:<10.8f} '.format(rosco_vt['PF_Offsets'][i]) for i in range(3)))) file.write('\n') file.write('!------- Active Wake Control -----------------------------------------------------\n') - file.write('{0:<12d} ! AWC_NumModes - Number of user-defined AWC forcing modes \n'.format(int(rosco_vt['AWC_NumModes']))) - file.write('{} ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure)\n'.format(write_array(rosco_vt['AWC_n'],'<4d'))) - file.write('{} ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2)\n'.format(write_array(rosco_vt['AWC_harmonic'],'<4d'))) - file.write('{} ! AWC_freq - Frequency(s) of forcing mode(s) [Hz]\n'.format(write_array(rosco_vt['AWC_freq'],'<6.4f'))) - file.write('{} ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg]\n'.format(write_array(rosco_vt['AWC_amp'],'<6.4f'))) - file.write('{} ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg]\n'.format(write_array(rosco_vt['AWC_clockangle'],'<6.4f'))) + file.write('{0:<12d} ! AWC_NumModes - Number of user-defined AWC forcing modes \n'.format(int(rosco_vt['AWC_NumModes']))) + file.write('{} ! AWC_n - Azimuthal mode number(s) (i.e., the number and direction of the lobes of the wake structure)\n'.format(write_array(rosco_vt['AWC_n'],'<4d'))) + file.write('{} ! AWC_harmonic - Harmonic(s) to apply in the AWC Inverse Coleman Transformation (only used when AWC_Mode = 2)\n'.format(write_array(rosco_vt['AWC_harmonic'],'<4d'))) + file.write('{} ! AWC_freq - Frequency(s) of forcing mode(s) [Hz]\n'.format(write_array(rosco_vt['AWC_freq'],'<6.4f'))) + file.write('{} ! AWC_amp - Pitch amplitude(s) of individual forcing mode(s) [deg]\n'.format(write_array(rosco_vt['AWC_amp'],'<6.4f'))) + file.write('{} ! AWC_clockangle - Initial angle(s) of forcing mode(s) [deg]\n'.format(write_array(rosco_vt['AWC_clockangle'],'<6.4f'))) file.write('\n') file.write('!------- External Controller Interface -----------------------------------------------------\n') file.write('"{}" ! DLL_FileName - Name/location of the dynamic library in the Bladed-DLL format\n'.format(rosco_vt['DLL_FileName'])) @@ -251,17 +276,18 @@ def write_DISCON(turbine, controller, param_file='DISCON.IN', txt_filename='Cp_C file.write('"{}" ! DLL_ProcName - Name of procedure in DLL to be called (-) \n'.format(rosco_vt['DLL_ProcName'])) file.write('\n') file.write('!------- ZeroMQ Interface ---------------------------------------------------------\n') - file.write('"{}" ! ZMQ_CommAddress - Communication address for ZMQ server, (e.g. "tcp://localhost:5555") \n'.format(rosco_vt['ZMQ_CommAddress'])) - file.write('{:<11d} ! ZMQ_UpdatePeriod - Call ZeroMQ every [x] seconds, [s]\n'.format(int(rosco_vt['ZMQ_UpdatePeriod']))) + file.write('"{}" ! ZMQ_CommAddress - {} \n'.format(rosco_vt['ZMQ_CommAddress'],input_descriptions['ZMQ_CommAddress'])) + file.write('{:<11f} ! ZMQ_UpdatePeriod - {}\n'.format(rosco_vt['ZMQ_UpdatePeriod'],input_descriptions['ZMQ_UpdatePeriod'])) + file.write('{:<11d} ! ZMQ_ID - {}\n'.format(int(rosco_vt['ZMQ_ID']),input_descriptions['ZMQ_ID'])) file.write('\n') file.write('!------- Cable Control ---------------------------------------------------------\n') file.write('{:<11d} ! CC_Group_N - {}\n'.format(len(rosco_vt['CC_GroupIndex']), input_descriptions['CC_Group_N'])) - file.write('{:^11s} ! CC_GroupIndex - {}\n'.format(write_array(rosco_vt['CC_GroupIndex'],'<6d'), input_descriptions['CC_GroupIndex'])) + file.write('{:^11s} ! CC_GroupIndex - {}\n'.format(write_array(rosco_vt['CC_GroupIndex'],'<6d'), input_descriptions['CC_GroupIndex'])) file.write('{:<11f} ! CC_ActTau - {}\n'.format(rosco_vt['CC_ActTau'], input_descriptions['CC_ActTau'] )) file.write('\n') file.write('!------- Structural Controllers ---------------------------------------------------------\n') file.write('{:<11d} ! StC_Group_N - {}\n'.format(len(rosco_vt['StC_GroupIndex']), input_descriptions['StC_Group_N'])) - file.write('{:^11s} ! StC_GroupIndex - {}\n'.format(write_array(rosco_vt['StC_GroupIndex'],'<6d'), input_descriptions['StC_GroupIndex'])) + file.write('{:^11s} ! StC_GroupIndex - {}\n'.format(write_array(rosco_vt['StC_GroupIndex'],'<6d'), input_descriptions['StC_GroupIndex'])) file.close() @@ -294,7 +320,7 @@ def read_DISCON(DISCON_filename): if (line.split()[1] != '!'): # Array valued entries array_length = line.split().index('!') param = line.split()[array_length+1] - values = np.array( [float(x) for x in line.split()[:array_length]] ) + values = [float(x) for x in line.split()[:array_length]] DISCON_in[param] = values else: # All other entries param = line.split()[2] @@ -302,6 +328,8 @@ def read_DISCON(DISCON_filename): # Remove printed quotations if string is in quotes if (value[0] == '"') or (value[0] == "'"): value = value[1:-1] + elif value == 'DEFAULT': + pass else: value = float(value) DISCON_in[param] = value @@ -444,14 +472,17 @@ def DISCON_dict(turbine, controller, txt_filename=None): DISCON_dict['F_NotchType'] = int(controller.F_NotchType) DISCON_dict['IPC_ControlMode'] = int(controller.IPC_ControlMode) DISCON_dict['VS_ControlMode'] = int(controller.VS_ControlMode) + DISCON_dict['VS_ConstPower'] = int(controller.VS_ConstPower) DISCON_dict['PC_ControlMode'] = int(controller.PC_ControlMode) DISCON_dict['Y_ControlMode'] = int(controller.Y_ControlMode) DISCON_dict['SS_Mode'] = int(controller.SS_Mode) + DISCON_dict['PRC_Mode'] = 0 DISCON_dict['WE_Mode'] = int(controller.WE_Mode) DISCON_dict['PS_Mode'] = int(controller.PS_Mode > 0) DISCON_dict['SD_Mode'] = int(controller.SD_Mode) DISCON_dict['Fl_Mode'] = int(controller.Fl_Mode) DISCON_dict['TD_Mode'] = int(controller.TD_Mode) + DISCON_dict['TRA_Mode'] = int(controller.TRA_Mode) DISCON_dict['Flp_Mode'] = int(controller.Flp_Mode) DISCON_dict['OL_Mode'] = int(controller.OL_Mode) DISCON_dict['PF_Mode'] = int(controller.PF_Mode) @@ -464,12 +495,14 @@ def DISCON_dict(turbine, controller, txt_filename=None): # ------- FILTERS ------- DISCON_dict['F_LPFCornerFreq'] = turbine.bld_edgewise_freq * 1/4 DISCON_dict['F_LPFDamping'] = controller.F_LPFDamping - if controller.Flp_Mode > 0: - DISCON_dict['F_NotchCornerFreq'] = turbine.bld_flapwise_freq - DISCON_dict['F_NotchBetaNumDen'] = [0.0, 0.5] - else: - DISCON_dict['F_NotchCornerFreq'] = controller.twr_freq - DISCON_dict['F_NotchBetaNumDen'] = [0.0, 0.25] + DISCON_dict['F_NumNotchFilts'] = len(controller.f_notch_freqs) + DISCON_dict['F_NotchFreqs'] = controller.f_notch_freqs if controller.f_notch_freqs else [0.0] + DISCON_dict['F_NotchBetaNum'] = controller.f_notch_beta_nums if controller.f_notch_beta_nums else [0.0] + DISCON_dict['F_NotchBetaDen'] = controller.f_notch_beta_dens if controller.f_notch_beta_dens else [0.0] + DISCON_dict['F_GenSpdNotch_N'] = len(controller.f_notch_gen_inds) + DISCON_dict['F_GenSpdNotch_Ind'] = controller.f_notch_gen_inds if controller.f_notch_gen_inds else [0] + DISCON_dict['F_TwrTopNotch_N'] = len(controller.f_notch_twr_inds) + DISCON_dict['F_TwrTopNotch_Ind'] = controller.f_notch_twr_inds if controller.f_notch_twr_inds else [0] DISCON_dict['F_WECornerFreq'] = controller.f_we_cornerfreq DISCON_dict['F_SSCornerFreq'] = controller.f_ss_cornerfreq DISCON_dict['F_FlHighPassFreq'] = controller.f_fl_highpassfreq @@ -487,6 +520,8 @@ def DISCON_dict(turbine, controller, txt_filename=None): DISCON_dict['PC_GS_KI'] = controller.pc_gain_schedule.Ki DISCON_dict['PC_GS_KD'] = [0.0 for i in range(len(controller.pc_gain_schedule.Ki))] DISCON_dict['PC_GS_TF'] = [0.0 for i in range(len(controller.pc_gain_schedule.Ki))] + + # DISCON_dict['PC_MaxPit'] = controller.max_pitch DISCON_dict['PC_MinPit'] = controller.min_pitch DISCON_dict['PC_MaxRat'] = turbine.max_pitch_rate @@ -520,6 +555,11 @@ def DISCON_dict(turbine, controller, txt_filename=None): # ------- SETPOINT SMOOTHER ------- DISCON_dict['SS_VSGain'] = controller.ss_vsgain DISCON_dict['SS_PCGain'] = controller.ss_pcgain + # -------- POWER REFERENCE TRACKING ------ + DISCON_dict['PRC_n'] = 2 + DISCON_dict['PRC_WindSpeeds'] = [3,25] + DISCON_dict['PRC_GenSpeeds'] = [rpm2RadSec * 7.56] * 2 + # ------- WIND SPEED ESTIMATOR ------- DISCON_dict['WE_BladeRadius'] = turbine.rotor_radius DISCON_dict['WE_CP_n'] = 1 @@ -542,9 +582,9 @@ def DISCON_dict(turbine, controller, txt_filename=None): DISCON_dict['Y_IPC_KP'] = 0.0 DISCON_dict['Y_IPC_KI'] = 0.0 # ------- TOWER FORE-AFT DAMPING ------- - DISCON_dict['FA_KI'] = -1 + DISCON_dict['FA_KI'] = 0.0 DISCON_dict['FA_HPFCornerFreq'] = 0.0 - DISCON_dict['FA_IntSat'] = 0.0 + DISCON_dict['FA_IntSat'] = 0.0 # ------- MINIMUM PITCH SATURATION ------- DISCON_dict['PS_BldPitchMin_N'] = len(controller.ps_min_bld_pitch) DISCON_dict['PS_WindSpeeds'] = controller.v @@ -553,7 +593,9 @@ def DISCON_dict(turbine, controller, txt_filename=None): DISCON_dict['SD_MaxPit'] = controller.sd_maxpit DISCON_dict['SD_CornerFreq'] = controller.f_sd_cornerfreq # ------- Floating ------- + DISCON_dict['Fl_n'] = len(controller.Kp_float) DISCON_dict['Fl_Kp'] = controller.Kp_float + DISCON_dict['Fl_U'] = controller.U_Fl # ------- FLAP ACTUATION ------- DISCON_dict['Flp_Angle'] = controller.flp_angle DISCON_dict['Flp_Kp'] = controller.Kp_flap[-1] @@ -567,20 +609,21 @@ def DISCON_dict(turbine, controller, txt_filename=None): DISCON_dict['Ind_YawRate'] = controller.OL_Ind_YawRate DISCON_dict['Ind_CableControl'] = controller.OL_Ind_CableControl DISCON_dict['Ind_StructControl'] = controller.OL_Ind_StructControl + DISCON_dict['Ind_Azimuth'] = controller.OL_Ind_Azimuth + # ------- Pitch Actuator ------- DISCON_dict['PA_Mode'] = controller.PA_Mode DISCON_dict['PA_CornerFreq'] = controller.PA_CornerFreq DISCON_dict['PA_Damping'] = controller.PA_Damping # ------- Pitch Actuator Fault ------- DISCON_dict['PF_Offsets'] = [0.,0.,0.] - # ------- Zero-MQ ------- - DISCON_dict['ZMQ_CommAddress'] = "tcp://localhost:5555" - DISCON_dict['ZMQ_UpdatePeriod'] = 2 # Add pass through here for param, value in controller.controller_params['DISCON'].items(): DISCON_dict[param] = value + # Make all lists, not numpy + DISCON_dict = remove_numpy(DISCON_dict) return DISCON_dict @@ -663,7 +706,7 @@ def list_check(x, return_bool=True): else: return y -def write_array(array,format='<.4f'): +def write_array(array,format='<.4f',line_width=12): if not hasattr(array,'__len__'): #not an array array = [array] @@ -672,4 +715,4 @@ def write_array(array,format='<.4f'): if 'd' in format and type(array[0]) != int: array = [int(a) for a in array] - return ''.join(['{:{}} '.format(item,format) for item in array]) + return ''.join(['{:{}} '.format(item,format) for item in array]).ljust(line_width) diff --git a/setup.py b/setup.py index 3af0995a..9f3c886d 100644 --- a/setup.py +++ b/setup.py @@ -1,196 +1,68 @@ -# Copyright 2019 NREL - -# Licensed under the Apache License, Version 2.0 (the "License"); you may not use -# this file except in compliance with the License. You may obtain a copy of the -# License at http://www.apache.org/licenses/LICENSE-2.0 - -# Unless required by applicable law or agreed to in writing, software distributed -# under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR -# CONDITIONS OF ANY KIND, either express or implied. See the License for the -# specific language governing permissions and limitations under the License. - -"""The setup script.""" - -# This setup file was made to mimic the setup.py script for https://github.com/NREL/floris/ -# Accessed on January 9, 2020 - -# Note: To use the 'upload' functionality of this file, you must: -# $ pip install twine - -import io import os import sys -from shutil import rmtree, copy -import glob +from pathlib import Path import platform -from setuptools import find_packages, setup, Command, Extension -from setuptools.command.build_ext import build_ext -from setuptools.command.install import install as _install - -from io import open - -# Package meta-data. -NAME = 'rosco' -DESCRIPTION = 'A reference open source controller toolset for wind turbine applications.' -URL = 'https://github.com/NREL/ROSCO' -EMAIL = 'daniel.zalkind@nrel.gov' -AUTHOR = 'NREL, National Wind Technology Center' -REQUIRES_PYTHON = '>=3.8' -VERSION = '2.7.0' - -# These packages are required for all of the code to be executed. -# - Maybe you can get away with older versions... -REQUIRED = [ - 'matplotlib', - 'numpy', - #'pytest', - 'scipy', - 'pyYAML', - #'future', - 'pandas' -] - - -# For the CMake Extensions -this_directory = os.path.abspath(os.path.dirname(__file__)) - -class CMakeExtension(Extension): - - def __init__(self, name, sourcedir='', **kwa): - Extension.__init__(self, name, sources=[], **kwa) - self.sourcedir = os.path.abspath(sourcedir) - -class CMakeBuildExt(build_ext): - - def copy_extensions_to_source(self): - newext = [] - for ext in self.extensions: - if isinstance(ext, CMakeExtension): continue - newext.append( ext ) - self.extensions = newext - super().copy_extensions_to_source() - - def build_extension(self, ext): - if not isinstance(ext, CMakeExtension): - super().build_extension(ext) - - else: - # Ensure that CMake is present and working - try: - self.spawn(['cmake', '--version']) - except OSError: - raise RuntimeError('Cannot find CMake executable') - - # Refresh build directory - localdir = os.path.join(this_directory, 'ROSCO','install') - os.makedirs(localdir, exist_ok=True) - - cmake_args = ['-DBUILD_SHARED_LIBS=OFF'] - cmake_args += ['-DCMAKE_Fortran_FLAGS=-ffree-line-length-0'] - cmake_args += ['-DCMAKE_INSTALL_PREFIX={}'.format(localdir)] - - if platform.system() == 'Windows': - if "gfortran" in os.environ["FC"].lower(): - cmake_args += ['-G', 'MinGW Makefiles'] - elif self.compiler.compiler_type == 'msvc': - cmake_args += ['-DCMAKE_GENERATOR_PLATFORM=x64'] - else: - raise ValueError("Unable to find the system's Fortran compiler.") - - self.build_temp = os.path.join( os.path.dirname( os.path.realpath(__file__) ), 'ROSCO', 'build') - os.makedirs(localdir, exist_ok=True) - # Need fresh build directory for CMake - os.makedirs(self.build_temp, exist_ok=True) - self.spawn(['cmake', '-S', ext.sourcedir, '-B', self.build_temp] + cmake_args) - self.spawn(['cmake', '--build', self.build_temp, '--target', 'install', '--config', 'Release']) +import cmake_build_extension +import setuptools +# Extra options passed to the CI/CD pipeline that uses cibuildwheel +CIBW_CMAKE_OPTIONS = [] +if "CIBUILDWHEEL" in os.environ and os.environ["CIBUILDWHEEL"] == "1": + # The manylinux variant runs in Debian Stretch and it uses lib64 folder + if sys.platform == "linux": + CIBW_CMAKE_OPTIONS += ["-DCMAKE_INSTALL_LIBDIR=lib"] -# All of the extensions -roscoExt = CMakeExtension('rosco','ROSCO') - -# The rest you shouldn't have to touch too much :) -# ------------------------------------------------ -# Except, perhaps the License and Trove Classifiers! -# If you do change the License, remember to change the Trove Classifier for that! - -here = os.path.abspath(os.path.dirname(__file__)) - -# Import the README and use it as the long-description. -try: - with io.open(os.path.join(here, 'README.md'), encoding='utf-8') as f: - long_description = '\n' + f.read() -except FileNotFoundError: - long_description = DESCRIPTION - -# Load the package's __version__.py module as a dictionary. -about = {} -if not VERSION: - project_slug = NAME.lower().replace("-", "_").replace(" ", "_") - with open(os.path.join(here, project_slug, '__version__.py')) as f: - exec(f.read(), about) +# Set Cmake options +if "CMAKE_ARGS" in os.environ: + cmake_args = [m for m in os.environ["CMAKE_ARGS"].split()] + user_flag = True else: - about['__version__'] = VERSION - - -class UploadCommand(Command): - """Support setup.py upload.""" - - description = 'Build and publish the package.' - user_options = [] - - @staticmethod - def status(s): - """Prints things in bold.""" - print('\033[1m{0}\033[0m'.format(s)) - - def initialize_options(self): - pass + user_flag = False + cmake_args = [] - def finalize_options(self): - pass +# Always build shared libraries +cmake_args += [f"-DPython3_ROOT_DIR={Path(sys.prefix)}", + "-DCALL_FROM_SETUP_PY:BOOL=ON", + "-DBUILD_SHARED_LIBS=ON"] - def run(self): - try: - self.status('Removing previous builds...') - rmtree(os.path.join(here, 'dist')) - except OSError: - pass - - self.status('Building Source and Wheel (universal) distribution...') - os.system('{0} setup.py sdist bdist_wheel --universal'.format(sys.executable)) - - self.status('Uploading the package to PyPI via Twine...') - os.system('twine upload dist/*') - - self.status('Pushing git tags...') - os.system('git tag v{0}'.format(about['__version__'])) - os.system('git push --tags') +# Append fortran flags +if not user_flag or "-DCMAKE_Fortran_FLAGS" not in os.environ["CMAKE_ARGS"]: + cmake_args += ['-DCMAKE_Fortran_FLAGS=-ffree-line-length-0'] +else: + for im, m in enumerate(cmake_args): + if m.find("-DCMAKE_Fortran_FLAGS") >= 0: + cmake_args[im] += ' -ffree-line-length-0' + +# Set if unset +#if not user_flag or "-DCMAKE_INSTALL_PREFIX" not in os.environ["CMAKE_ARGS"]: +# cmake_args += [f'-DCMAKE_INSTALL_PREFIX={this_directory}/rosco'] + +# Set if unset +#if not user_flag or "-DCMAKE_PREFIX_PATH" not in os.environ["CMAKE_ARGS"]: +# python_root = os.path.dirname( os.path.dirname( sysconfig.get_path('stdlib') ) ) +# cmake_args += [f'-DCMAKE_PREFIX_PATH={python_root}'] + +if platform.system() == 'Windows': + if "FC" not in os.environ: + os.environ["FC"] = "gfortran" + + #if "gfortran" in os.environ["FC"].lower(): + # cmake_args += ['-G', 'MinGW Makefiles'] + #else: + # cmake_args += ['-DCMAKE_GENERATOR_PLATFORM=x64'] - sys.exit() - - - -metadata = dict( - name = NAME, - version = about['__version__'], - description = DESCRIPTION, - long_description = long_description, - long_description_content_type = 'text/markdown', - author = AUTHOR, - author_email = EMAIL, - url = URL, - install_requires = REQUIRED, - python_requires = REQUIRES_PYTHON, - packages = find_packages(exclude=["tests", "*.tests", "*.tests.*", "tests.*"]), - package_data = {'': ['*.yaml']}, - license = 'Apache License, Version 2.0', - cmdclass = {'build_ext': CMakeBuildExt, 'upload': UploadCommand}, - zip_safe = False, +setuptools.setup( + ext_modules=[ + cmake_build_extension.CMakeExtension( + # This could be anything you like, it is used to create build folders + name="rosco", + install_prefix="rosco", + # Selects the folder where the main CMakeLists.txt is stored + source_dir=os.path.join('rosco','controller'), + cmake_configure_options=cmake_args + CIBW_CMAKE_OPTIONS, + ), + ], + cmdclass={'build_ext': cmake_build_extension.BuildExtension}, ) -if "--compile-rosco" in sys.argv: - metadata['ext_modules'] = [roscoExt] - sys.argv.remove("--compile-rosco") - -setup(**metadata)