diff --git a/.github/workflows/CI_rosco-compile.yml b/.github/workflows/CI_rosco-compile.yml index 39a13875b..5d6f96d66 100644 --- a/.github/workflows/CI_rosco-compile.yml +++ b/.github/workflows/CI_rosco-compile.yml @@ -150,7 +150,7 @@ jobs: - name: Conda Install ROSCO run: | - python -m pip install -e . --no-build-isolation + python -m pip install -e . --no-build-isolation --no-deps - name: Generate Registry run: | diff --git a/Examples/17c_zeromq_fastfarm.py b/Examples/17c_zeromq_fastfarm.py index d96b58a69..5014920bc 100644 --- a/Examples/17c_zeromq_fastfarm.py +++ b/Examples/17c_zeromq_fastfarm.py @@ -142,7 +142,7 @@ def write_openfast_1(): r.wind_case_fcn = cl.power_curve r.wind_case_opts = { "U": [8], - "TMax": 25, + "TMax": 20, } run_dir = os.path.join(EXAMPLE_OUT_DIR, "17c_FASTFarm_OF1") r.controller_params = {} @@ -173,7 +173,7 @@ def write_openfast_2(): r.wind_case_fcn = cl.power_curve r.wind_case_opts = { "U": [8], - "TMax": 25, + "TMax": 20, } run_dir = os.path.join(EXAMPLE_OUT_DIR, "17c_FASTFarm_OF2") r.save_dir = run_dir diff --git a/Examples/23_structural_control.py b/Examples/23_structural_control.py index 031f302c4..2ba632cbb 100644 --- a/Examples/23_structural_control.py +++ b/Examples/23_structural_control.py @@ -23,6 +23,8 @@ from rosco.toolbox.inputs.validation import load_rosco_yaml from rosco.toolbox.controller import OpenLoopControl +TEST_MODE = True # set to False to run full simulation, True runs a short test case for debugging + def main(): #directories this_dir = os.path.dirname(os.path.abspath(__file__)) @@ -95,7 +97,7 @@ def main(): r.wind_case_fcn = cl.power_curve r.wind_case_opts = { 'U': [9], - 'TMax': t_max, + 'TMax': t_max if not TEST_MODE else 10, } r.case_inputs = {} r.fst_vt = reader.fst_vt diff --git a/Examples/26_marine_hydro.py b/Examples/26_marine_hydro.py index 46cb4fbb4..874e2696b 100644 --- a/Examples/26_marine_hydro.py +++ b/Examples/26_marine_hydro.py @@ -8,6 +8,7 @@ from rosco.toolbox.ofTools.case_gen.run_FAST import run_FAST_ROSCO from rosco.toolbox.ofTools.case_gen import CaseLibrary as cl +TEST_RUN = True def main(): #directories @@ -21,22 +22,20 @@ def main(): 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 + if TEST_RUN: + r.wind_case_opts['TMax'] = 1.0 + r.save_dir = run_dir r.rosco_dir = rosco_dir - # r.rosco_dll = '/Users/dzalkind/Tools/ROSCO-PRC/rosco/controller/build/libdiscon.dylib' + r.n_cores = 1 r.run_FAST() diff --git a/Examples/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst b/Examples/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst index 330860366..d6e813971 100644 --- a/Examples/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst +++ b/Examples/Test_Cases/5MW_Land_Simulink/5MW_Land_Simulink.fst @@ -1,71 +1,79 @@ -------- OpenFAST example INPUT FILE ------------------------------------------- -FAST Certification Test #18: NREL 5.0 MW Baseline Wind Turbine (Onshore) ----------------------- SIMULATION CONTROL -------------------------------------- -True Echo - Echo input data to .ech (flag) -"FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} - 60 TMax - Total run time (s) - 0.0125 DT - Recommended module time step (s) - 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} - 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} - 99999 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} - 0 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} - 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} - 0 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} - 0 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 WtrDens - Water density (kg/m^3) - 1.464E-05 KinVisc - Kinematic viscosity of working fluid (m^2/s) - 335 SpdSound - Speed of sound in working fluid (m/s) - 103500 Patm - Atmospheric pressure (Pa) [used only for an MHK turbine cavitation check] - 1700 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 --------------------------------------------- -"../NREL-5MW/NRELOffshrBsline5MW_Onshore_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) -"../NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat" InflowFile - Name of file containing inflow wind input parameters (quoted string) -"../NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat" AeroFile - Name of file containing aerodynamic input parameters (quoted string) -"NRELOffshrBsline5MW_Onshore_ServoDyn.dat" ServoFile - Name of file containing control and electrical-drive input parameters (quoted string) -"unused" HydroFile - Name of file containing hydrodynamic input parameters (quoted string) -"unused" SubFile - Name of file containing sub-structural input parameters (quoted string) -"unused" 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) {1: text file [.out], 2: binary file [.outb], 3: both} -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) - 3 TrimCase - Controller parameter to be trimmed {1:yaw; 2:torque; 3:pitch} [used only if CalcSteady=True] (-) - 0.001 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)) - 2 NLinTimes - Number of times to linearize (-) [>=1] [unused if Linearize=False] - 30, 60 LinTimes - List of times at which to linearize (s) [1 to NLinTimes] [unused if Linearize=False] - 1 LinInputs - Inputs included in linearization (switch) {0=none; 1=standard; 2=all module inputs (debug)} [unused if Linearize=False] - 1 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} - 1 VTK_type - Type of VTK visualization data: (switch) {1=surfaces; 2=basic meshes (lines/points); 3=all meshes (debug)} [unused if WrVTK=0] -true VTK_fields - Write mesh fields to VTK data files? (flag) {true/false} [unused if WrVTK=0] - 15 VTK_fps - Frame rate for VTK output (frames per second){will use closest integer multiple of DT} [used only if WrVTK=2] +------- OpenFAST example INPUT FILE ------------------------------------------- +FAST Certification Test #18: NREL 5.0 MW Baseline Wind Turbine (Onshore) +---------------------- SIMULATION CONTROL -------------------------------------- +True Echo - Echo input data to .ech (flag) +"FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} + 60 TMax - Total run time (s) + 0.0125 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} + 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} + 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) + 99999 DT_UJac - Time between calls to get Jacobians (s) + 1E+06 UJacSclFact - Scaling factor used in Jacobians (-) +---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 NRotors - Number of rotors in turbine (-) + 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} + 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} + 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} + 1 CompServo - Compute control and electrical-drive dynamics (switch) {0=None; 1=ServoDyn} + 0 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} + 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} + 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} + 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} +---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- + 9.80665 Gravity - Gravitational acceleration (m/s^2) + 1.225 AirDens - Air density (kg/m^3) + 1025 WtrDens - Water density (kg/m^3) + 1.464E-05 KinVisc - Kinematic viscosity of working fluid (m^2/s) + 335 SpdSound - Speed of sound in working fluid (m/s) + 103500 Patm - Atmospheric pressure (Pa) [used only for an MHK turbine cavitation check] + 1700 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 --------------------------------------------- +"../NREL-5MW/NRELOffshrBsline5MW_Onshore_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) +"../NREL-5MW/NRELOffshrBsline5MW_InflowWind.dat" InflowFile - Name of file containing inflow wind input parameters (quoted string) +"../NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat" AeroFile - Name of file containing aerodynamic input parameters (quoted string) +"NRELOffshrBsline5MW_Onshore_ServoDyn.dat" ServoFile - Name of file containing control and electrical-drive input parameters (quoted string) +"unused" HydroFile - Name of file containing hydrodynamic input parameters (quoted string) +"unused" SubFile - Name of file containing sub-structural input parameters (quoted string) +"unused" MooringFile - Name of file containing mooring system input parameters (quoted string) +"unused" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn 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) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} +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) + 3 TrimCase - Controller parameter to be trimmed {1:yaw; 2:torque; 3:pitch} [used only if CalcSteady=True] (-) + 0.001 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)) + 2 NLinTimes - Number of times to linearize (-) [>=1] [unused if Linearize=False] + 30, 60 LinTimes - List of times at which to linearize (s) [1 to NLinTimes] [unused if Linearize=False] + 1 LinInputs - Inputs included in linearization (switch) {0=none; 1=standard; 2=all module inputs (debug)} [unused if Linearize=False] + 1 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} + 1 VTK_type - Type of VTK visualization data: (switch) {1=surfaces; 2=basic meshes (lines/points); 3=all meshes (debug)} [unused if WrVTK=0] +true VTK_fields - Write mesh fields to VTK data files? (flag) {true/false} [unused if WrVTK=0] + 15 VTK_fps - Frame rate for VTK output (frames per second){will use closest integer multiple of DT} [used only if WrVTK=2] diff --git a/Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat b/Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat index 3c235956b..dcd5b5ede 100644 --- a/Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat +++ b/Examples/Test_Cases/5MW_Land_Simulink/NRELOffshrBsline5MW_Onshore_ServoDyn.dat @@ -1,110 +1,119 @@ -------- 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 ------------------------------------------- - 4 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 ---------------------------- - 4 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) - 1 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] (%) -False 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) - 1 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 ---------------------------------- - 4 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 ------------------------------------- - 4 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] -"../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] -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 - Cuttoff 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] - 0 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 -END of input file (the word "END" must appear in the first 3 columns of this last OutList line) ---------------------------------------------------------------------------------------- +------- 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 ------------------------------------------- + 4 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] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) + 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 ---------------------------- + 4 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) + 1 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] (%) +False 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) + 1 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 ---------------------------------- + 4 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 ------------------------------------- + 4 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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] +"../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] +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 - Cuttoff 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] + 0 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 +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/BAR_10/BAR_10.fst b/Examples/Test_Cases/BAR_10/BAR_10.fst index 7da06d39a..debe3df8a 100644 --- a/Examples/Test_Cases/BAR_10/BAR_10.fst +++ b/Examples/Test_Cases/BAR_10/BAR_10.fst @@ -5,21 +5,28 @@ True Echo - Echo input data to .ech (flag) "FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} 10.0 TMax - Total run time (s) 0.01 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 99999.0 DT_UJac - Time between calls to get Jacobians (s) 1000000.0 UJacSclFact - Scaling factor used in Jacobians (-) ---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ -2 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 NRotors - Number of rotors in turbine (-) +2 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} +1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} +2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} 1 CompServo - Compute control and electrical-drive dynamics (switch) {0=None; 1=ServoDyn} 0 CompSeaSt - Compute sea state information (switch) {0=None; 1=SeaState} 0 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.80665 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ True Echo - Echo input data to .ech (flag) "unused" SubFile - Name of file containing sub-structural input parameters (quoted string) "unused" MooringFile - Name of file containing mooring system input parameters (quoted string) "unused" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn input parameters (quoted string) ---------------------- OUTPUT -------------------------------------------------- True SumPrint - Print summary data to ".sum" (flag) 5.0 SttsTime - Amount of time between screen status messages (s) 99999.0 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) "default" DT_Out - Time step for tabular output (s) (or "default") 0.0 TStart - Time to begin tabular output (s) -2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both} +2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat b/Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat index 6ccc0921e..c837241c9 100644 --- a/Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat +++ b/Examples/Test_Cases/BAR_10/BAR_10_AeroDyn15.dat @@ -8,7 +8,6 @@ False Echo - Echo the input to ".AD.ech"? (fl 0 TwrShadow - Calculate tower influence on wind based on downstream tower shadow? (flag) True TwrAero - Calculate tower aerodynamic loads? (flag) False CavitCheck - Perform cavitation check? (flag) TRUE will turn off unsteady aerodynamics -False Buoyancy - Include buoyancy effects? (flag) False NacelleDrag - Include Nacelle Drag effects? (flag) False CompAA Flag to compute AeroAcoustics calculation [only used when WakeMod=1 or 2] "AeroAcousticsInput.dat" AA_InputFile - Aeroacoustics input file @@ -94,10 +93,10 @@ True UseBlCm - Include aerodynamic pitching moment in calc "BAR_10_AeroDyn15_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) "BAR_10_AeroDyn15_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] "BAR_10_AeroDyn15_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] -====== Hub Properties ============================================================================== [used only when Buoyancy=True] +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] 0.0 VolHub - Hub volume (m^3) 0.0 HubCenBx - Hub center of buoyancy x direction offset (m) -====== Nacelle Properties ========================================================================== [used only when Buoyancy=True or NacelleDrag=True] +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] 0 VolNac - Nacelle volume (m^3) 0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) 0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) @@ -106,20 +105,20 @@ True UseBlCm - Include aerodynamic pitching moment in calc ====== 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=True, or TwrAero=True] -9 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow=True, or TwrAero=True] -TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True -(m) (m) (-) (-) (-) - 2.740e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 - 4.110e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 - 5.480e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 - 6.850e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 - 8.220e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 - 9.590e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 - 1.096e+02 6.00000e+00 1.0e+00 1.0e-1 0.0 - 1.233e+02 5.89079e+00 1.0e+00 1.0e-1 0.0 - 1.370e+02 5.53032e+00 1.0e+00 1.0e-1 0.0 -====== Tower Influence and Aerodynamics ============================================================= [used only when TwrPotent/=0, TwrShadow=True, or TwrAero=True] +====== Tower Influence and Aerodynamics ============================================================= [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +9 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +2.740e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +4.110e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +5.480e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +6.850e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +8.220e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +9.590e+01 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +1.096e+02 6.00000e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +1.233e+02 5.89079e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +1.370e+02 5.53032e+00 1.0e+00 1.0e-1 0.0 0.0000000E+00 0.0000000E+00 +====== Tower Influence and Aerodynamics ============================================================= [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] 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] (-) 4, 7, 10, 13, 16, 18, 21, 24, 27 BlOutNd - Blade nodes whose values will be output (-) diff --git a/Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN b/Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN index fdecfcfd2..49be8061b 100644 --- a/Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN +++ b/Examples/Test_Cases/BAR_10/BAR_10_DISCON.IN @@ -1,5 +1,5 @@ ! Controller parameter input file for the BAR_10 wind turbine -! - File written using ROSCO version 2.10.1 controller tuning logic on 11/26/25 +! - File written using ROSCO version 2.10.6 controller tuning logic on 06/09/26 !------- 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) @@ -189,8 +189,8 @@ !------- FLAP ACTUATION ----------------------------------------------------- 0.000000000000 ! Flp_Angle - Initial or steady state flap angle [rad] -1.46450132e-08 ! Flp_Kp - Blade root bending moment proportional gain for flap control [s] -1.46450132e-09 ! Flp_Ki - Flap displacement integral gain for flap control [-] +1.46476122e-08 ! Flp_Kp - Blade root bending moment proportional gain for flap control [s] +1.46476122e-09 ! Flp_Ki - Flap displacement integral gain for flap control [-] 0.174500000000 ! Flp_MaxPit - Maximum (and minimum) flap pitch angle [rad] !------- Open Loop Control ----------------------------------------------------- diff --git a/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat b/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat index 723f968dd..bdfee293c 100644 --- a/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat +++ b/Examples/Test_Cases/BAR_10/BAR_10_ElastoDyn.dat @@ -8,6 +8,7 @@ False Echo - Echo input data to ".ech" (flag) True FlapDOF1 - First flapwise blade mode DOF (flag) True FlapDOF2 - Second flapwise blade mode DOF (flag) True EdgeDOF - First edgewise blade mode DOF (flag) +False PitchDOF - Blade pitch DOF (flag) False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] False DrTrDOF - Drivetrain rotational-flexibility DOF (flag) True GenDOF - Generator DOF (flag) @@ -66,11 +67,19 @@ False PtfmYDOF - Platform yaw rotation DOF (flag) 0.0 PtfmCMxt - Downwind distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) 0.0 PtfmCMyt - Lateral distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) 0.0 PtfmCMzt - Vertical distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) + 0 PtfmRefxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) 0.0 PtfmRefzt - Vertical distance from the ground level [onshore] or MSL [offshore] to the platform reference point (meters) ---------------------- MASS AND INERTIA ---------------------------------------- 0.0 TipMass(1) - Tip-brake mass, blade 1 (kg) 0.0 TipMass(2) - Tip-brake mass, blade 2 (kg) 0.0 TipMass(3) - Tip-brake mass, blade 3 (kg) [unused for 2 blades] + 0 PBrIner(1) - Pitch bearing inertia, blade 1 (kg m^2) + 0 PBrIner(2) - Pitch bearing inertia, blade 2 (kg m^2) + 0 PBrIner(3) - Pitch bearing inertia, blade 3 (kg m^2) [unused for 2 blades] + 0 BlPIner(1) - Blade pitch inertia, blade 1 (kg m^2) + 0 BlPIner(2) - Blade pitch inertia, blade 2 (kg m^2) + 0 BlPIner(3) - Blade pitch inertia, blade 3 (kg m^2) [unused for 2 blades] 119991.18553379682 HubMass - Hub mass (kg) 894745.0292084403 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) diff --git a/Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat b/Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat index d095227bb..5b6829c67 100644 --- a/Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat +++ b/Examples/Test_Cases/BAR_10/BAR_10_ServoDyn.dat @@ -6,6 +6,15 @@ False Echo - Echo input data to .ech (flag) ---------------------- 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) 0.0 TPCOn - Time to enable active pitch control (s) [unused when PCMode=0] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) 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] @@ -74,7 +83,7 @@ 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] -"../../../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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] "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/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile.fst b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile.fst index 82cb9ed68..d1719e048 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile.fst +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile.fst @@ -3,13 +3,18 @@ IEA 15 MW offshore reference model monopile configuration ---------------------- SIMULATION CONTROL -------------------------------------- False Echo - Echo input data to .ech (flag) "FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} -300.0 TMax - Total run time (s) +100.0 TMax - Total run time (s) 0.005 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 99999.0 DT_UJac - Time between calls to get Jacobians (s) 1000000.0 UJacSclFact - Scaling factor used in Jacobians (-) ---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 NRotors - Number of rotors in turbine (-) 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} @@ -19,7 +24,9 @@ False Echo - Echo input data to .ech (flag) 1 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.81 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ False Echo - Echo input data to .ech (flag) "IEA-15-240-RWT-Monopile_SubDyn.dat" SubFile - Name of file containing sub-structural input parameters (quoted string) "none" MooringFile - Name of file containing mooring system input parameters (quoted string) "none" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn input parameters (quoted string) ---------------------- OUTPUT -------------------------------------------------- False SumPrint - Print summary data to ".sum" (flag) 10.0 SttsTime - Amount of time between screen status messages (s) 99999.0 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) "default" DT_Out - Time step for tabular output (s) (or "default") 0.0 TStart - Time to begin tabular output (s) -2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb, 5: both 1 and 4} +2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_AeroDyn15.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_AeroDyn15.dat index e282ada55..516cacd6b 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_AeroDyn15.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_AeroDyn15.dat @@ -8,7 +8,6 @@ Default DTAero - Time interval for aerodynamic calculations 1 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 CavitCheck - Perform cavitation check? (flag) [UA_Mod must be 0 when CavitCheck=true] -False Buoyancy - Include buoyancy effects? (flag) False NacelleDrag - Include Nacelle Drag effects? (flag) False CompAA - Flag to compute AeroAcoustics calculation [used only when Wake_Mod = 1 or 2] AeroAcousticsInput.dat AA_InputFile - AeroAcoustics input file [used only when CompAA=true] @@ -114,10 +113,10 @@ True UseBlCm - Include aerodynamic pitching moment in calc "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] -====== Hub Properties ============================================================================== [used only when Buoyancy=True] +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] 0 VolHub - Hub volume (m^3) 0 HubCenBx - Hub center of buoyancy x direction offset (m) -====== Nacelle Properties ========================================================================== [used only when Buoyancy=True or NacelleDrag=True] +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] 0 VolNac - Nacelle volume (m^3) 0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) 0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) @@ -126,30 +125,30 @@ True UseBlCm - Include aerodynamic pitching moment in calc ====== 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] -20 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, or TwrAero=True] -TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True -(m) (m) (-) (-) (-) - 15.000 10.000 0.5 0.1 0.0 - 28.000 10.000 0.5 0.1 0.0 - 28.001 10.000 0.5 0.1 0.0 - 41.000 9.926 0.5 0.1 0.0 - 41.001 9.926 0.5 0.1 0.0 - 54.000 9.443 0.5 0.1 0.0 - 54.001 9.443 0.5 0.1 0.0 - 67.000 8.833 0.5 0.1 0.0 - 67.001 8.833 0.5 0.1 0.0 - 80.000 8.151 0.5 0.1 0.0 - 80.001 8.151 0.5 0.1 0.0 - 93.000 7.390 0.5 0.1 0.0 - 93.001 7.390 0.5 0.1 0.0 - 106.000 6.909 0.5 0.1 0.0 - 106.001 6.909 0.5 0.1 0.0 - 119.000 6.748 0.5 0.1 0.0 - 119.001 6.748 0.5 0.1 0.0 - 132.000 6.572 0.5 0.1 0.0 - 132.001 6.572 0.5 0.1 0.0 - 144.386 6.500 0.5 0.1 0.0 +====== Tower Influence and Aerodynamics ============================================================ [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +20 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +15.000 10.000 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +28.000 10.000 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +28.001 10.000 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +41.000 9.926 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +41.001 9.926 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +54.000 9.443 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +54.001 9.443 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +67.000 8.833 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +67.001 8.833 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +80.000 8.151 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +80.001 8.151 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +93.000 7.390 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +93.001 7.390 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +106.000 6.909 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +106.001 6.909 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +119.000 6.748 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +119.001 6.748 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +132.000 6.572 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +132.001 6.572 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +144.386 6.500 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 ====== Outputs ==================================================================================== False SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) 9 NBlOuts - Number of blade node outputs [0 - 9] (-) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_DISCON.IN b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_DISCON.IN index 285fe422f..4cc22b597 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_DISCON.IN +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_DISCON.IN @@ -1,5 +1,5 @@ ! Controller parameter input file for the IEA-15-240-RWT-Monopile wind turbine -! - File written using ROSCO version 2.10.1 controller tuning logic on 11/26/25 +! - File written using ROSCO version 2.10.6 controller tuning logic on 06/09/26 !------- 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) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ElastoDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ElastoDyn.dat index 4ddd358a4..e8baacc00 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ElastoDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ElastoDyn.dat @@ -8,6 +8,7 @@ Default DT - Integration time step (s) True FlapDOF1 - First flapwise blade mode DOF (flag) True FlapDOF2 - Second flapwise blade mode DOF (flag) True EdgeDOF - First edgewise blade mode DOF (flag) +False PitchDOF - Blade pitch DOF (flag) False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] False DrTrDOF - Drivetrain rotational-flexibility DOF (flag) True GenDOF - Generator DOF (flag) @@ -66,11 +67,19 @@ True PtfmYDOF - Platform yaw rotation DOF (flag) 0.0 PtfmCMxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) 0.0 PtfmCMyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) 15. PtfmCMzt - Vertical distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) + 0 PtfmRefxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) 15. 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 ---------------------------------------- 0.0 TipMass(1) - Tip-brake mass, blade 1 (kg) 0.0 TipMass(2) - Tip-brake mass, blade 2 (kg) 0.0 TipMass(3) - Tip-brake mass, blade 3 (kg) [unused for 2 blades] + 0 PBrIner(1) - Pitch bearing inertia, blade 1 (kg m^2) + 0 PBrIner(2) - Pitch bearing inertia, blade 2 (kg m^2) + 0 PBrIner(3) - Pitch bearing inertia, blade 3 (kg m^2) [unused for 2 blades] + 0 BlPIner(1) - Blade pitch inertia, blade 1 (kg m^2) + 0 BlPIner(2) - Blade pitch inertia, blade 2 (kg m^2) + 0 BlPIner(3) - Blade pitch inertia, blade 3 (kg m^2) [unused for 2 blades] 69131 HubMass - Hub mass (kg) 969952 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ServoDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ServoDyn.dat index 303e20b5b..29b8a01e7 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ServoDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_ServoDyn.dat @@ -6,6 +6,15 @@ False Echo - Echo input data to .ech (flag) ---------------------- 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) 0.0 TPCOn - Time to enable active pitch control (s) [unused when PCMode=0] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) 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] @@ -74,7 +83,7 @@ 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-defineAfC_phased from Bladed-style DLL} ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"/home/runner/miniconda3/envs/test/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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] "IEA-15-240-RWT-Monopile_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/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_SubDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_SubDyn.dat index a52acedac..f0b8cf749 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_SubDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_SubDyn.dat @@ -19,6 +19,10 @@ True SttcSolve - Solve dynamics about static equilibrium point 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 +------- INITIAL RIGID-BODY POSITION [used only for floating structure with more than one transition pieces] ------- +RBSurge RBSway RBHeave RBRoll RBPitch RBYaw + (m) (m) (m) (deg) (deg) (deg) + 0.0 0.0 0.0 0.0 0.0 0.0 ---- STRUCTURE JOINTS: joints connect structure members (~Hydrodyn Input File) -------- 19 NJoints - Number of joints (-) JointID JointXss JointYss JointZss JointType JointDirX JointDirY JointDirZ JointStiff ![Coordinates of Member joints in SS-Coordinate System][JointType={1:cantilever, 2:universal joint, 3:revolute joint, 4:spherical joint}] @@ -49,9 +53,9 @@ True SttcSolve - Solve dynamics about static equilibrium point 1 1 1 1 1 1 1 "" ------- INTERFACE JOINTS: 1/0 for Locked (to the TP)/Free DOF @each Interface Joint (only Locked-to-TP implemented thus far (=rigid TP)) --------- 1 NInterf - Number of interface joints locked to the Transition Piece (TP): be sure to remove all rigid motion dofs -IJointID ItfTDXss ItfTDYss ItfTDZss ItfRDXss ItfRDYss ItfRDZss [Global Coordinate System] - (-) (flag) (flag) (flag) (flag) (flag) (flag) - 19 1 1 1 1 1 1 +IJointID TPID ItfTDXss ItfTDYss ItfTDZss ItfRDXss ItfRDYss ItfRDZss [Global Coordinate System] + (-) (-) (flag) (flag) (flag) (flag) (flag) (flag) + 19 1 1 1 1 1 1 1 ----------------------------------- MEMBERS -------------------------------------- 18 NMembers - Number of frame members MemberID MJointID1 MJointID2 MPropSetID1 MPropSetID2 MType MSpin/COSMID ![MType={1c:beam circ., 1r:beam rect., 2:cable, 3:rigid, 4:beam arb., 5:spring}. COMSID={-1:none}] diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_ServoDyn_wDTUcontroller.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_ServoDyn_wDTUcontroller.dat index 1c4c8c48a..0f966caac 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_ServoDyn_wDTUcontroller.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_ServoDyn_wDTUcontroller.dat @@ -6,6 +6,15 @@ False Echo - Echo input data to .ech (flag) ---------------------- 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) 0.0 TPCOn - Time to enable active pitch control (s) [unused when PCMode=0] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) 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] @@ -74,7 +83,7 @@ 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-defineAfC_phased from Bladed-style DLL} ---------------------- BLADED INTERFACE ---------------------------------------- [used only with Bladed Interface] -"control/DTUWEC_for_OpenFAST.so" DLL_FileName - Name/location of the dynamic library {.dll [Windows] or .so [Linux]} in the Bladed-DLL format (-) [used only with Bladed Interface] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] "control/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] 0.01 DLL_DT - Communication interval for dynamic library (s) (or "default") [used only with Bladed Interface] diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_wDTUcontroller.fst b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_wDTUcontroller.fst index 251b5e4b1..4f0b47c36 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_wDTUcontroller.fst +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-Monopile_wDTUcontroller/IEA-15-240-RWT-Monopile_wDTUcontroller.fst @@ -5,11 +5,16 @@ False Echo - Echo input data to .ech (flag) "FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} 300.0 TMax - Total run time (s) 0.01 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 99999.0 DT_UJac - Time between calls to get Jacobians (s) 1000000.0 UJacSclFact - Scaling factor used in Jacobians (-) ---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 NRotors - Number of rotors in turbine (-) 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} @@ -19,7 +24,9 @@ False Echo - Echo input data to .ech (flag) 1 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.81 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ False Echo - Echo input data to .ech (flag) "../IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_SubDyn.dat" SubFile - Name of file containing sub-structural input parameters (quoted string) "none" MooringFile - Name of file containing mooring system input parameters (quoted string) "none" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn input parameters (quoted string) ---------------------- OUTPUT -------------------------------------------------- False SumPrint - Print summary data to ".sum" (flag) 10.0 SttsTime - Amount of time between screen status messages (s) 99999.0 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) "default" DT_Out - Time step for tabular output (s) (or "default") 0.0 TStart - Time to begin tabular output (s) -2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb, 5: both 1 and 4} +2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_AeroDyn15.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_AeroDyn15.dat index 6d044199b..6077d53d1 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_AeroDyn15.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_AeroDyn15.dat @@ -8,7 +8,6 @@ Default DTAero - Time interval for aerodynamic calculations 1 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 CavitCheck - Perform cavitation check? (flag) [UA_Mod must be 0 when CavitCheck=true] -False Buoyancy - Include buoyancy effects? (flag) False NacelleDrag - Include Nacelle Drag effects? (flag) False CompAA - Flag to compute AeroAcoustics calculation [used only when Wake_Mod = 1 or 2] AeroAcousticsInput.dat AA_InputFile - AeroAcoustics input file [used only when CompAA=true] @@ -114,10 +113,10 @@ True UseBlCm - Include aerodynamic pitching moment in calc "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] -====== Hub Properties ============================================================================== [used only when Buoyancy=True] +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] 0 VolHub - Hub volume (m^3) 0 HubCenBx - Hub center of buoyancy x direction offset (m) -====== Nacelle Properties ========================================================================== [used only when Buoyancy=True or NacelleDrag=True] +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] 0 VolNac - Nacelle volume (m^3) 0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) 0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) @@ -126,21 +125,21 @@ True UseBlCm - Include aerodynamic pitching moment in calc ====== 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] -11 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, or TwrAero=True] -TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True -(m) (m) (-) (-) (-) - 15. 10. 0.5 0.1 0.0 - 28. 10. 0.5 0.1 0.0 - 41. 9.926 0.5 0.1 0.0 - 54. 9.443 0.5 0.1 0.0 - 67. 8.833 0.5 0.1 0.0 - 80. 8.151 0.5 0.1 0.0 - 93. 7.39 0.5 0.1 0.0 - 106. 6.909 0.5 0.1 0.0 - 119. 6.748 0.5 0.1 0.0 - 132. 6.572 0.5 0.1 0.0 - 144.386 6.5 0.5 0.1 0.0 +====== Tower Influence and Aerodynamics ============================================================ [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +11 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +15. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +28. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +41. 9.926 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +54. 9.443 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +67. 8.833 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +80. 8.151 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +93. 7.39 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +106. 6.909 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +119. 6.748 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +132. 6.572 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +144.386 6.5 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 ====== Outputs ==================================================================================== False SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) 9 NBlOuts - Number of blade node outputs [0 - 9] (-) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_OLAF.fst b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_OLAF.fst index 1fe24d62c..b2c4c4b90 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_OLAF.fst +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-OLAF/IEA-15-240-RWT_OLAF.fst @@ -5,11 +5,16 @@ False Echo - Echo input data to .ech (flag) "FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} 300.0 TMax - Total run time (s) 0.005 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 99999.0 DT_UJac - Time between calls to get Jacobians (s) 1000000.0 UJacSclFact - Scaling factor used in Jacobians (-) ---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 NRotors - Number of rotors in turbine (-) 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} @@ -19,7 +24,9 @@ False Echo - Echo input data to .ech (flag) 1 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.81 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ False Echo - Echo input data to .ech (flag) "../IEA-15-240-RWT-Monopile/IEA-15-240-RWT-Monopile_SubDyn.dat" SubFile - Name of file containing sub-structural input parameters (quoted string) "none" MooringFile - Name of file containing mooring system input parameters (quoted string) "none" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn input parameters (quoted string) ---------------------- OUTPUT -------------------------------------------------- False SumPrint - Print summary data to ".sum" (flag) 10.0 SttsTime - Amount of time between screen status messages (s) 99999.0 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) "default" DT_Out - Time step for tabular output (s) (or "default") 0.0 TStart - Time to begin tabular output (s) -2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb, 5: both 1 and 4} +2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst index c00ef7775..b454b7f44 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi.fst @@ -5,11 +5,16 @@ False Echo - Echo input data to .ech (flag) "FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} 10.0 TMax - Total run time (s) 0.025 DT - Integration time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 99999.0 DT_UJac - Time between calls to get Jacobians (s) 1000000.0 UJacSclFact - Scaling factor used in Jacobians (-) ---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 NRotors - Number of rotors in turbine (-) 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} @@ -19,7 +24,9 @@ False Echo - Echo input data to .ech (flag) 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.81 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ False Echo - Echo input data to .ech (flag) "none" SubFile - Name of file containing sub-structural input parameters (quoted string) "IEA-15-240-RWT-UMaineSemi_MoorDyn.dat" MooringFile - Name of file containing mooring system input parameters (quoted string) "none" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn input parameters (quoted string) ---------------------- OUTPUT -------------------------------------------------- False SumPrint - Print summary data to ".sum" (flag) 10.0 SttsTime - Amount of time between screen status messages (s) 99999.0 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) "default" DT_Out - Time step for tabular output (s) (or "default") 0.0 TStart - Time to begin tabular output (s) -2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb, 5: both 1 and 4} +2 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_AeroDyn15.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_AeroDyn15.dat index 2a7d1ff39..9f9cc428d 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_AeroDyn15.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_AeroDyn15.dat @@ -8,7 +8,6 @@ Default DTAero - Time interval for aerodynamic calculations 1 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 CavitCheck - Perform cavitation check? (flag) [UA_Mod must be 0 when CavitCheck=true] -False Buoyancy - Include buoyancy effects? (flag) False NacelleDrag - Include Nacelle Drag effects? (flag) False CompAA - Flag to compute AeroAcoustics calculation [used only when Wake_Mod = 1 or 2] AeroAcousticsInput.dat AA_InputFile - AeroAcoustics input file [used only when CompAA=true] @@ -114,10 +113,10 @@ True UseBlCm - Include aerodynamic pitching moment in calc "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] "../IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] -====== Hub Properties ============================================================================== [used only when Buoyancy=True] +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] 0 VolHub - Hub volume (m^3) 0 HubCenBx - Hub center of buoyancy x direction offset (m) -====== Nacelle Properties ========================================================================== [used only when Buoyancy=True or NacelleDrag=True] +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] 0 VolNac - Nacelle volume (m^3) 0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) 0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) @@ -126,21 +125,21 @@ True UseBlCm - Include aerodynamic pitching moment in calc ====== 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] -11 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, or TwrAero=True] -TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True -(m) (m) (-) (-) (-) - 15. 10. 0.5 0.1 0.0 - 28. 10. 0.5 0.1 0.0 - 41. 10. 0.5 0.1 0.0 - 54. 10. 0.5 0.1 0.0 - 67. 10. 0.5 0.1 0.0 - 80. 10. 0.5 0.1 0.0 - 93. 10. 0.5 0.1 0.0 - 106. 10. 0.5 0.1 0.0 - 119. 10. 0.5 0.1 0.0 - 132. 10. 0.5 0.1 0.0 - 144.386 6.5 0.5 0.1 0.0 +====== Tower Influence and Aerodynamics ============================================================ [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +11 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +15. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +28. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +41. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +54. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +67. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +80. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +93. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +106. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +119. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +132. 10. 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 +144.386 6.5 0.5 0.1 0.0 0.0000000E+00 0.0000000E+00 ====== Outputs ==================================================================================== False SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) 9 NBlOuts - Number of blade node outputs [0 - 9] (-) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_DISCON.IN b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_DISCON.IN index 06da1ccf7..05b0219d8 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_DISCON.IN +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_DISCON.IN @@ -1,5 +1,5 @@ ! Controller parameter input file for the IEA-15-240-RWT-UMaineSemi wind turbine -! - File written using ROSCO version 2.10.1 controller tuning logic on 11/26/25 +! - File written using ROSCO version 2.10.6 controller tuning logic on 06/09/26 !------- 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) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat index c74c110c2..43eeccc08 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ElastoDyn.dat @@ -8,6 +8,7 @@ False Echo - Echo input data to ".ech" (flag) True FlapDOF1 - First flapwise blade mode DOF (flag) True FlapDOF2 - Second flapwise blade mode DOF (flag) True EdgeDOF - First edgewise blade mode DOF (flag) +False PitchDOF - Blade pitch DOF (flag) False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] False DrTrDOF - Drivetrain rotational-flexibility DOF (flag) True GenDOF - Generator DOF (flag) @@ -66,11 +67,19 @@ True PtfmYDOF - Platform yaw rotation DOF (flag) 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) -14.400 PtfmCMzt - Vertical distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform CM (meters) + 0 PtfmRefxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (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] + 0 PBrIner(1) - Pitch bearing inertia, blade 1 (kg m^2) + 0 PBrIner(2) - Pitch bearing inertia, blade 2 (kg m^2) + 0 PBrIner(3) - Pitch bearing inertia, blade 3 (kg m^2) [unused for 2 blades] + 0 BlPIner(1) - Blade pitch inertia, blade 1 (kg m^2) + 0 BlPIner(2) - Blade pitch inertia, blade 2 (kg m^2) + 0 BlPIner(3) - Blade pitch inertia, blade 3 (kg m^2) [unused for 2 blades] 69131 HubMass - Hub mass (kg) 969952 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat index 1cc29687f..66adb7318 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_HydroDyn.dat @@ -24,6 +24,7 @@ False Echo - Echo the input file data (flag) 20206.34889 PtfmVol0 - 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] + 0 NAddDOF - Number of additional generalized DOF of each WAMIT body (-) [1 to NBody] [>=0; =0 if NBody>1; 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] @@ -57,6 +58,7 @@ False Echo - Echo the input file data (flag) ---------------------- STRIP THEORY OPTIONS -------------------------------------- 0 WaveDisp - Method of computing Wave Kinematics {0: use undisplaced position, 1: use displaced position) } (switch) 0 AMMod - Method of computing distributed added-mass force. (0: Only and always on nodes below SWL at the undisplaced position. 2: Up to the instantaneous free surface) [overwrite to 0 when WaveMod = 0 or 6 or when WaveStMod = 0 in SeaState] + 1 HstMod - Method of computing hydrostatic loads. (0: Up to the still water level. 1: Up to the instantaneous free surface) [overwrite to 0 when WaveStMod = 0 in SeaState] ---------------------- AXIAL COEFFICIENTS -------------------------------------- 1 NAxCoef - Number of axial coefficients (-) AxCoefID AxCd AxCa AxCp AxFDMod AxVnCOff AxFDLoFSc diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_SeaState.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_SeaState.dat index 08797b7a6..567329074 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_SeaState.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_SeaState.dat @@ -15,6 +15,7 @@ False Echo - Echo the input file data (flag) ---------------------- WAVES --------------------------------------------------- 2 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] + 0 WvCrntMod - Combined wave-current modeling option {0: simple superposition, 1: include Doppler effect, 2: include both Doppler effect and wave amplitude/spectrum scaling} (switch) [unused when WaveMod=0 or WaveMod=6. Also unused when there is no current from SeaState (CurrMod=0) or from InflowWind if MHK.] 850.00 WaveTMax - Analysis time for incident wave calculations (sec) [unused when WaveMod=0; determines WaveDOmega=2Pi/WaveTMax in the IFFT] 0.25 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] 1.10 WaveHs - Significant wave height of incident waves (meters) [used only when WaveMod=1 or 2] diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat index d5174e178..c05dba195 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA-15-240-RWT-UMaineSemi_ServoDyn.dat @@ -6,6 +6,15 @@ False Echo - Echo input data to .ech (flag) ---------------------- 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) 0.0 TPCOn - Time to enable active pitch control (s) [unused when PCMode=0] +0.0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) +0.0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) +0.0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) +0.0 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) +0.0 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) +0.0 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) +0.0 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) +0.0 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) +0.0 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) 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] @@ -74,7 +83,7 @@ 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] -"/home/runner/miniconda3/envs/test/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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] "IEA-15-240-RWT-UMaineSemi_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/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat index 1857ef2d6..645e7bcfb 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_AeroDyn15_blade.dat @@ -2,55 +2,55 @@ IEA 15 MW Offshore Reference Turbine ====== Blade Properties ================================================================= 50 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) - 0.000000000000000e+00 -6.354122360450852e-03 -2.276626484469566e-02 9.291281525327398e-01 1.559455301971172e+01 5.200000000000000e+00 1 0.0 0.0 0.0 - 2.387753704536792e+00 3.236481948738088e-02 5.005748522338992e-02 8.707285997270117e-01 1.558773861176889e+01 5.208839941579524e+00 2 0.0 0.0 0.0 - 4.775507409073585e+00 6.621685687511680e-02 8.694386659281718e-02 6.376768648563605e-01 1.541083467878359e+01 5.237887092263203e+00 3 0.0 0.0 0.0 - 7.163261113610377e+00 8.551302257769909e-02 5.307191353698237e-02 3.623009655957606e-01 1.494855563474368e+01 5.293325313383697e+00 4 0.0 0.0 0.0 - 9.551014818147170e+00 9.641383525966472e-02 -2.834268227993915e-02 2.309264254802593e-01 1.425845480678574e+01 5.367339854814920e+00 5 0.0 0.0 0.0 - 1.193876852268396e+01 1.047603018628692e-01 -1.352768396731961e-01 2.332510218907787e-01 1.339714163725627e+01 5.452092684226667e+00 6 0.0 0.0 0.0 - 1.432652222722075e+01 1.158548641787537e-01 -2.434441389056812e-01 3.537684475592492e-01 1.242201947682708e+01 5.540031728503847e+00 7 0.0 0.0 0.0 - 1.671427593175755e+01 1.342461230233627e-01 -3.188598483871042e-01 5.253284774395157e-01 1.139457131628079e+01 5.621824261194381e+00 8 0.0 0.0 0.0 - 1.910202963629434e+01 1.596395008211909e-01 -3.469958526716618e-01 5.163676654488634e-01 1.037097608496841e+01 5.692531175149338e+00 9 0.0 0.0 0.0 - 2.148978334083113e+01 1.772839218313782e-01 -3.819068650570526e-01 3.195122177856614e-01 9.403999874823057e+00 5.742610890726970e+00 10 0.0 0.0 0.0 - 2.387753704536793e+01 1.862701718402896e-01 -4.162773967965841e-01 1.573444757446643e-01 8.551522201182079e+00 5.764836827022541e+00 11 0.0 0.0 0.0 - 2.626529074990471e+01 1.903983042803929e-01 -4.350341475278324e-01 1.228376274409489e-01 7.833153039627247e+00 5.756119529852528e+00 12 0.0 0.0 0.0 - 2.865304445444151e+01 1.965084748280304e-01 -4.192878615908359e-01 1.576642896749325e-01 7.191354972096501e+00 5.703098512750650e+00 13 0.0 0.0 0.0 - 3.104079815897830e+01 2.035393425849667e-01 -3.833468507053414e-01 1.405642801253589e-01 6.551629060916145e+00 5.604676021602162e+00 14 0.0 0.0 0.0 - 3.342855186351510e+01 2.082242607643353e-01 -3.520562387211776e-01 8.721579968330176e-02 5.933995702189942e+00 5.471559126660524e+00 15 0.0 0.0 0.0 - 3.581630556805188e+01 2.108086308339459e-01 -3.258680587010861e-01 4.014233748419024e-02 5.346089613189348e+00 5.322778014171772e+00 16 0.0 0.0 0.0 - 3.820405927258868e+01 2.115700571915651e-01 -3.029463320739354e-01 3.930870169461698e-03 4.796333947019595e+00 5.166482288167050e+00 17 0.0 0.0 0.0 - 4.059181297712547e+01 2.111362622888833e-01 -2.833278558945826e-01 -4.892583209487279e-02 4.296593562725417e+00 5.019421327310202e+00 18 0.0 0.0 0.0 - 4.297956668166226e+01 2.074921713986668e-01 -2.650005898111198e-01 -1.798131144321642e-01 3.846955194686785e+00 4.885807888739599e+00 19 0.0 0.0 0.0 - 4.536732038619906e+01 1.961491644965832e-01 -2.468940178014830e-01 -4.025738645322033e-01 3.445342056797746e+00 4.767959675121795e+00 20 0.0 0.0 0.0 - 4.775507409073585e+01 1.739385890780780e-01 -2.286827195540772e-01 -6.993213833205466e-01 3.076913909773020e+00 4.654566079625438e+00 21 0.0 0.0 0.0 - 5.014282779527264e+01 1.378633438394944e-01 -2.108533280970962e-01 -1.003820922690407e+00 2.733562457425842e+00 4.541031051711910e+00 22 0.0 0.0 0.0 - 5.253058149980943e+01 9.027607400369848e-02 -1.945396261857828e-01 -1.240747486362836e+00 2.412234674442038e+00 4.428175577624730e+00 23 0.0 0.0 0.0 - 5.491833520434623e+01 3.445719810261592e-02 -1.805730451752768e-01 -1.415897080086006e+00 2.111690772172129e+00 4.316958876583997e+00 24 0.0 0.0 0.0 - 5.730608890888303e+01 -2.772456879271226e-02 -1.686917049154445e-01 -1.531449532522348e+00 1.828396455235506e+00 4.207880735790049e+00 25 0.0 0.0 0.0 - 5.969384261341982e+01 -9.317136122682015e-02 -1.591120396576385e-01 -1.615739264090502e+00 1.558783420877334e+00 4.101646187027423e+00 26 0.0 0.0 0.0 - 6.208159631795661e+01 -1.623758862177225e-01 -1.520171259813259e-01 -1.803740515356404e+00 1.302436869719713e+00 3.998712335312356e+00 27 0.0 0.0 0.0 - 6.446935002249339e+01 -2.434852854714629e-01 -1.475340510338809e-01 -2.116796821704133e+00 1.064427371073839e+00 3.899408676051565e+00 28 0.0 0.0 0.0 - 6.685710372703018e+01 -3.387672278625571e-01 -1.442863764849721e-01 -2.460770245763826e+00 8.434461662411673e-01 3.803172543681295e+00 29 0.0 0.0 0.0 - 6.924485743156698e+01 -4.485233220920201e-01 -1.428866903746157e-01 -2.765261934448337e+00 6.365641868417889e-01 3.709389453654426e+00 30 0.0 0.0 0.0 - 7.163261113610376e+01 -5.691577197429315e-01 -1.431497271870684e-01 -2.996072070835783e+00 4.370289000217617e-01 3.617111741572532e+00 31 0.0 0.0 0.0 - 7.402036484064057e+01 -6.981271306483475e-01 -1.449404201922671e-01 -3.157880132952910e+00 2.396567933387980e-01 3.525634918177657e+00 32 0.0 0.0 0.0 - 7.640811854517736e+01 -8.322285121101992e-01 -1.477133050470215e-01 -3.257754925092921e+00 3.967768814723920e-02 3.434082670567315e+00 33 0.0 0.0 0.0 - 7.879587224971415e+01 -9.695092756948377e-01 -1.511924136895065e-01 -3.310385437884317e+00 -1.728281243479747e-01 3.341933111457596e+00 34 0.0 0.0 0.0 - 8.118362595425094e+01 -1.107990118373343e+00 -1.552313867559904e-01 -3.406275737267048e+00 -4.070838313820219e-01 3.248678447761413e+00 35 0.0 0.0 0.0 - 8.357137965878775e+01 -1.253249451921619e+00 -1.595783390433831e-01 -3.595872363726422e+00 -6.803776144613040e-01 3.156109679927359e+00 36 0.0 0.0 0.0 - 8.595913336332453e+01 -1.407503356114155e+00 -1.641610599715335e-01 -3.796088457251112e+00 -9.992936104276490e-01 3.064580004833834e+00 37 0.0 0.0 0.0 - 8.834688706786133e+01 -1.569415649792242e+00 -1.685371839122368e-01 -3.975750664517341e+00 -1.320525255517711e+00 2.972992647082487e+00 38 0.0 0.0 0.0 - 9.073464077239812e+01 -1.738609665373033e+00 -1.724347024248264e-01 -4.134012556120940e+00 -1.623298762065715e+00 2.880705106690617e+00 39 0.0 0.0 0.0 - 9.312239447693490e+01 -1.913679799182830e+00 -1.755139986377293e-01 -4.262892683845840e+00 -1.884368146311783e+00 2.786969376686517e+00 40 0.0 0.0 0.0 - 9.551014818147171e+01 -2.093586929140116e+00 -1.785402748061612e-01 -4.382890604985165e+00 -2.086230093232373e+00 2.691030938627057e+00 41 0.0 0.0 0.0 - 9.789790188600848e+01 -2.278630233534075e+00 -1.818549476382104e-01 -4.504426990591778e+00 -2.163998201705838e+00 2.591965555977676e+00 42 0.0 0.0 0.0 - 1.002856555905453e+02 -2.468636765792445e+00 -1.856271589973350e-01 -4.656240428293554e+00 -2.175841166085000e+00 2.489323647505217e+00 43 0.0 0.0 0.0 - 1.026734092950821e+02 -2.666293052105629e+00 -1.892782116779622e-01 -4.835653360509453e+00 -2.155303774975188e+00 2.383917231097341e+00 44 0.0 0.0 0.0 - 1.050611629996189e+02 -2.871202075032245e+00 -1.924886839011192e-01 -5.008509113472641e+00 -2.102909521958467e+00 2.275923816206998e+00 45 0.0 0.0 0.0 - 1.074489167041557e+02 -3.083212464328674e+00 -1.950287058969190e-01 -5.174877006858174e+00 -2.018403421317624e+00 2.165466732053696e+00 46 0.0 0.0 0.0 - 1.098366704086924e+02 -3.301933250165787e+00 -1.970581013607374e-01 -5.340902805961378e+00 -1.896743213972770e+00 2.052625082558482e+00 47 0.0 0.0 0.0 - 1.122244241132292e+02 -3.527723381568596e+00 -1.989581851179342e-01 -5.490470005410412e+00 -1.724325762660474e+00 1.937753326819164e+00 48 0.0 0.0 0.0 - 1.146121778177661e+02 -3.758854692855718e+00 -2.002555383444301e-01 -5.660129840633894e+00 -1.508125114401624e+00 1.819662967336163e+00 49 0.0 0.0 0.0 - 1.169999315223028e+02 -3.998718787548573e+00 -5.907701779748526e-02 -5.765427375220712e+00 -1.242387706272970e+00 4.999999999999998e-01 50 0.0 0.0 0.0 + BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID t_c BlCb BlCenBn BlCenBt 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45 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.074489167041557e+02 -3.083212464328674e+00 -1.950287058969190e-01 -5.174877006858174e+00 -2.018403421317624e+00 2.165466732053696e+00 46 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.098366704086924e+02 -3.301933250165787e+00 -1.970581013607374e-01 -5.340902805961378e+00 -1.896743213972770e+00 2.052625082558482e+00 47 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.122244241132292e+02 -3.527723381568596e+00 -1.989581851179342e-01 -5.490470005410412e+00 -1.724325762660474e+00 1.937753326819164e+00 48 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.146121778177661e+02 -3.758854692855718e+00 -2.002555383444301e-01 -5.660129840633894e+00 -1.508125114401624e+00 1.819662967336163e+00 49 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.169999315223028e+02 -3.998718787548573e+00 -5.907701779748526e-02 -5.765427375220712e+00 -1.242387706272970e+00 4.999999999999998e-01 50 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_BeamDyn_blade.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_BeamDyn_blade.dat index 6eba1aa3a..8baf1e49a 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_BeamDyn_blade.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_BeamDyn_blade.dat @@ -2,11 +2,14 @@ IEA 15 MW Offshore Reference Turbine ---------------------- BLADE PARAMETERS -------------------------------------- 26 station_total - Number of blade input stations (-) - 1 damp_type - Damping type: 0: no damping; 1: damped +1 damp_type - Damping type (switch) {0: none, 1: stiffness-proportional, 2: modal} ---------------------- DAMPING COEFFICIENT------------------------------------ mu1 mu2 mu3 mu4 mu5 mu6 (-) (-) (-) (-) (-) (-) 0.00299005 0.00218775 0.00084171 0.00218775 0.00299005 0.00084171 +------ Modal Damping [used only if damp_type=2] -------------------------------- +6 n_modes - Number of modal damping coefficients (-) +0.01 0.01 0.01 0.01 0.01 0.01 zeta - Damping coefficients for mode 1 through n_modes ---------------------- DISTRIBUTED PROPERTIES--------------------------------- 0.000000 6.7403759942007923e+09 2.6537385919261174e+06 0.0000000000000000e+00 0.0000000000000000e+00 0.0000000000000000e+00 1.4844668300814739e+08 diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_ElastoDyn_blade.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_ElastoDyn_blade.dat index aaf8200ab..139caa816 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_ElastoDyn_blade.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_ElastoDyn_blade.dat @@ -12,58 +12,58 @@ IEA 15 MW Offshore Reference Turbine 1.0 AdjFlSt - Factor to adjust blade flap stiffness (-) 1.0 AdjEdSt - Factor to adjust blade edge stiffness (-) ---------------------- DISTRIBUTED BLADE PROPERTIES ---------------------------- - BlFract PitchAxis StrcTwst BMassDen FlpStff EdgStff - (-) (-) (deg) (kg/m) (Nm^2) (Nm^2) - 0.000000000000000e+00 5.045454545454545e-01 1.559455301971172e+01 3.189145281139312e+03 1.525338961805330e+11 1.524792338826398e+11 - 2.040816326530612e-02 4.900186808012221e-01 1.558773861176889e+01 2.848491671981893e+03 1.388018747118786e+11 1.376398889340311e+11 - 4.081632653061224e-02 4.727001828454839e-01 1.541083467878359e+01 2.506316641079376e+03 1.222825651460343e+11 1.231043838261023e+11 - 6.122448979591835e-02 4.540147730610375e-01 1.494855563474368e+01 2.126327323268820e+03 9.721429241691763e+10 1.030038838221780e+11 - 8.163265306122448e-02 4.346477825919650e-01 1.425845480678574e+01 1.774273076643545e+03 7.473181210448022e+10 8.415417285570142e+10 - 1.020408163265306e-01 4.156278851950606e-01 1.339714163725627e+01 1.675415347578921e+03 5.670713863723486e+10 7.500334758775418e+10 - 1.224489795918367e-01 3.979378721273935e-01 1.242201947682708e+01 1.375372123508623e+03 4.333119910067368e+10 6.386874980164800e+10 - 1.428571428571428e-01 3.812996074561740e-01 1.139457131628079e+01 1.126877435288510e+03 3.488129485677473e+10 5.587550052530811e+10 - 1.632653061224490e-01 3.654920515699109e-01 1.037097608496841e+01 9.166967416567660e+02 3.074062953585106e+10 4.850443135202483e+10 - 1.836734693877551e-01 3.516078083447283e-01 9.403999874823057e+00 7.581128920505105e+02 2.769326286737285e+10 4.229417836732529e+10 - 2.040816326530612e-01 3.400844312876912e-01 8.551522201182079e+00 6.498201551435592e+02 2.461968089847847e+10 3.778979262471266e+10 - 2.244897959183673e-01 3.310670675965599e-01 7.833153039627247e+00 5.816598121783463e+02 2.139033204354521e+10 3.460539129185500e+10 - 2.448979591836735e-01 3.241031342163746e-01 7.191354972096501e+00 5.388110041072538e+02 1.869243518353476e+10 3.222839700500914e+10 - 2.653061224489796e-01 3.188472934612394e-01 6.551629060916145e+00 5.093885171950960e+02 1.631285343544707e+10 3.032117609748821e+10 - 2.857142857142857e-01 3.146895762675238e-01 5.933995702189942e+00 4.927842041149214e+02 1.479141128967237e+10 2.866882577015823e+10 - 3.061224489795917e-01 3.114888979953550e-01 5.346089613189348e+00 4.867795863196560e+02 1.408157287855375e+10 2.719211554338738e+10 - 3.265306122448979e-01 3.088429219529899e-01 4.796333947019595e+00 4.822296506379602e+02 1.340519691354671e+10 2.562551820076299e+10 - 3.469387755102040e-01 3.066054031112312e-01 4.296593562725417e+00 4.761842241246758e+02 1.213013620583955e+10 2.406788400839622e+10 - 3.673469387755101e-01 3.043613335231313e-01 3.846955194686785e+00 4.677912755581858e+02 1.057564915543031e+10 2.263018568852713e+10 - 3.877551020408163e-01 3.018756624023877e-01 3.445342056797746e+00 4.591296592557296e+02 9.428937598688459e+09 2.140687114823070e+10 - 4.081632653061223e-01 2.992017656131912e-01 3.076913909773020e+00 4.508379097619292e+02 8.679373622305126e+09 2.030554785264042e+10 - 4.285714285714285e-01 2.964858149953292e-01 2.733562457425842e+00 4.421998847689325e+02 8.090790463396826e+09 1.925965509911081e+10 - 4.489795918367346e-01 2.939711939970447e-01 2.412234674442038e+00 4.326008561862743e+02 7.430721516569722e+09 1.820271939373449e+10 - 4.693877551020408e-01 2.918571873240831e-01 2.111690772172129e+00 4.219773745307401e+02 6.532916397780468e+09 1.716666216090269e+10 - 4.897959183673469e-01 2.901098902886204e-01 1.828396455235506e+00 4.112534584982077e+02 5.635458983738827e+09 1.616806219912397e+10 - 5.102040816326531e-01 2.888065997994461e-01 1.558783420877334e+00 4.012473583789823e+02 4.924729531561621e+09 1.522285575052025e+10 - 5.306122448979592e-01 2.880263439811507e-01 1.302436869719713e+00 3.920469572984427e+02 4.401845320349272e+09 1.433708564071317e+10 - 5.510204081632651e-01 2.878415104462351e-01 1.064427371073839e+00 3.826675398780939e+02 3.941076638277167e+09 1.344497171773862e+10 - 5.714285714285713e-01 2.879425361453937e-01 8.434461662411673e-01 3.612661153435752e+02 3.426333092367449e+09 1.138100415398959e+10 - 5.918367346938775e-01 2.885226494115666e-01 6.365641868417889e-01 3.398659172619289e+02 2.966680532868500e+09 9.471654091893534e+09 - 6.122448979591835e-01 2.895768507455962e-01 4.370289000217617e-01 3.173247964654917e+02 2.598972931031398e+09 7.598070333791522e+09 - 6.326530612244897e-01 2.911108045758606e-01 2.396567933387980e-01 2.941148966103120e+02 2.299604180699598e+09 5.805653973761759e+09 - 6.530612244897959e-01 2.930139151081327e-01 3.967768814723920e-02 2.719321532357653e+02 2.026456858897451e+09 4.285716699307380e+09 - 6.734693877551020e-01 2.952412111444283e-01 -1.728281243479747e-01 2.563144169585100e+02 1.750494448194900e+09 3.539638690389050e+09 - 6.938775510204080e-01 2.977841397364215e-01 -4.070838313820219e-01 2.393766504954643e+02 1.480634479348676e+09 2.858341744436661e+09 - 7.142857142857143e-01 3.005652867249930e-01 -6.803776144613040e-01 2.221564960620647e+02 1.225755456624930e+09 2.411448232374817e+09 - 7.346938775510203e-01 3.035753776130124e-01 -9.992936104276490e-01 2.021377424119976e+02 9.915617242298139e+08 2.059272895765558e+09 - 7.551020408163265e-01 3.067044645878453e-01 -1.320525255517711e+00 1.805543988230305e+02 7.965115478517663e+08 1.711553935321545e+09 - 7.755102040816326e-01 3.098825376429916e-01 -1.623298762065715e+00 1.576606284996616e+02 6.379451447840538e+08 1.344077335734445e+09 - 7.959183673469387e-01 3.130107259708016e-01 -1.884368146311783e+00 1.354839722001807e+02 5.016030937142348e+08 1.013798041821079e+09 - 8.163265306122449e-01 3.163904276665285e-01 -2.086230093232373e+00 1.120816430883252e+02 3.837872963500269e+08 7.818269647609487e+08 - 8.367346938775508e-01 3.202110918982503e-01 -2.163998201705838e+00 9.428716335486106e+01 2.922152544706123e+08 6.257356863909814e+08 - 8.571428571428570e-01 3.246231171496712e-01 -2.175841166085000e+00 7.800953847011847e+01 2.234419323778142e+08 4.853089503492516e+08 - 8.775510204081634e-01 3.294541887849720e-01 -2.155303774975188e+00 6.432912305900471e+01 1.655441909972637e+08 3.752666314364563e+08 - 8.979591836734692e-01 3.346330641302447e-01 -2.102909521958467e+00 5.344190109844552e+01 1.178503801821035e+08 2.918966298394187e+08 - 9.183673469387755e-01 3.401190402144396e-01 -2.018403421317624e+00 4.450335078883321e+01 7.916644695614292e+07 2.239967950809962e+08 - 9.387755102040815e-01 3.460555975714659e-01 -1.896743213972770e+00 3.669679320964971e+01 4.921992371612750e+07 1.631692262693548e+08 - 9.591836734693876e-01 3.527211856428439e-01 -1.724325762660474e+00 2.687365619764821e+01 2.743282717773140e+07 1.064318616320310e+08 - 9.795918367346939e-01 3.600890296396286e-01 -1.508125114401624e+00 2.157201084316552e+01 1.296677095760643e+07 6.715371720843673e+07 - 1.000000000000000e+00 3.681818181818181e-01 -1.242387706272970e+00 5.767382468564499e+00 1.862011072702549e+05 1.663313892259768e+06 + BlFract StrcTwst BMassDen FlpStff EdgStff + (-) (deg) (kg/m) (Nm^2) (Nm^2) + 0.000000000000000e+00 1.559455301971172e+01 3.189145281139312e+03 1.525338961805330e+11 1.524792338826398e+11 + 2.040816326530612e-02 1.558773861176889e+01 2.848491671981893e+03 1.388018747118786e+11 1.376398889340311e+11 + 4.081632653061224e-02 1.541083467878359e+01 2.506316641079376e+03 1.222825651460343e+11 1.231043838261023e+11 + 6.122448979591835e-02 1.494855563474368e+01 2.126327323268820e+03 9.721429241691763e+10 1.030038838221780e+11 + 8.163265306122448e-02 1.425845480678574e+01 1.774273076643545e+03 7.473181210448022e+10 8.415417285570142e+10 + 1.020408163265306e-01 1.339714163725627e+01 1.675415347578921e+03 5.670713863723486e+10 7.500334758775418e+10 + 1.224489795918367e-01 1.242201947682708e+01 1.375372123508623e+03 4.333119910067368e+10 6.386874980164800e+10 + 1.428571428571428e-01 1.139457131628079e+01 1.126877435288510e+03 3.488129485677473e+10 5.587550052530811e+10 + 1.632653061224490e-01 1.037097608496841e+01 9.166967416567660e+02 3.074062953585106e+10 4.850443135202483e+10 + 1.836734693877551e-01 9.403999874823057e+00 7.581128920505105e+02 2.769326286737285e+10 4.229417836732529e+10 + 2.040816326530612e-01 8.551522201182079e+00 6.498201551435592e+02 2.461968089847847e+10 3.778979262471266e+10 + 2.244897959183673e-01 7.833153039627247e+00 5.816598121783463e+02 2.139033204354521e+10 3.460539129185500e+10 + 2.448979591836735e-01 7.191354972096501e+00 5.388110041072538e+02 1.869243518353476e+10 3.222839700500914e+10 + 2.653061224489796e-01 6.551629060916145e+00 5.093885171950960e+02 1.631285343544707e+10 3.032117609748821e+10 + 2.857142857142857e-01 5.933995702189942e+00 4.927842041149214e+02 1.479141128967237e+10 2.866882577015823e+10 + 3.061224489795917e-01 5.346089613189348e+00 4.867795863196560e+02 1.408157287855375e+10 2.719211554338738e+10 + 3.265306122448979e-01 4.796333947019595e+00 4.822296506379602e+02 1.340519691354671e+10 2.562551820076299e+10 + 3.469387755102040e-01 4.296593562725417e+00 4.761842241246758e+02 1.213013620583955e+10 2.406788400839622e+10 + 3.673469387755101e-01 3.846955194686785e+00 4.677912755581858e+02 1.057564915543031e+10 2.263018568852713e+10 + 3.877551020408163e-01 3.445342056797746e+00 4.591296592557296e+02 9.428937598688459e+09 2.140687114823070e+10 + 4.081632653061223e-01 3.076913909773020e+00 4.508379097619292e+02 8.679373622305126e+09 2.030554785264042e+10 + 4.285714285714285e-01 2.733562457425842e+00 4.421998847689325e+02 8.090790463396826e+09 1.925965509911081e+10 + 4.489795918367346e-01 2.412234674442038e+00 4.326008561862743e+02 7.430721516569722e+09 1.820271939373449e+10 + 4.693877551020408e-01 2.111690772172129e+00 4.219773745307401e+02 6.532916397780468e+09 1.716666216090269e+10 + 4.897959183673469e-01 1.828396455235506e+00 4.112534584982077e+02 5.635458983738827e+09 1.616806219912397e+10 + 5.102040816326531e-01 1.558783420877334e+00 4.012473583789823e+02 4.924729531561621e+09 1.522285575052025e+10 + 5.306122448979592e-01 1.302436869719713e+00 3.920469572984427e+02 4.401845320349272e+09 1.433708564071317e+10 + 5.510204081632651e-01 1.064427371073839e+00 3.826675398780939e+02 3.941076638277167e+09 1.344497171773862e+10 + 5.714285714285713e-01 8.434461662411673e-01 3.612661153435752e+02 3.426333092367449e+09 1.138100415398959e+10 + 5.918367346938775e-01 6.365641868417889e-01 3.398659172619289e+02 2.966680532868500e+09 9.471654091893534e+09 + 6.122448979591835e-01 4.370289000217617e-01 3.173247964654917e+02 2.598972931031398e+09 7.598070333791522e+09 + 6.326530612244897e-01 2.396567933387980e-01 2.941148966103120e+02 2.299604180699598e+09 5.805653973761759e+09 + 6.530612244897959e-01 3.967768814723920e-02 2.719321532357653e+02 2.026456858897451e+09 4.285716699307380e+09 + 6.734693877551020e-01 -1.728281243479747e-01 2.563144169585100e+02 1.750494448194900e+09 3.539638690389050e+09 + 6.938775510204080e-01 -4.070838313820219e-01 2.393766504954643e+02 1.480634479348676e+09 2.858341744436661e+09 + 7.142857142857143e-01 -6.803776144613040e-01 2.221564960620647e+02 1.225755456624930e+09 2.411448232374817e+09 + 7.346938775510203e-01 -9.992936104276490e-01 2.021377424119976e+02 9.915617242298139e+08 2.059272895765558e+09 + 7.551020408163265e-01 -1.320525255517711e+00 1.805543988230305e+02 7.965115478517663e+08 1.711553935321545e+09 + 7.755102040816326e-01 -1.623298762065715e+00 1.576606284996616e+02 6.379451447840538e+08 1.344077335734445e+09 + 7.959183673469387e-01 -1.884368146311783e+00 1.354839722001807e+02 5.016030937142348e+08 1.013798041821079e+09 + 8.163265306122449e-01 -2.086230093232373e+00 1.120816430883252e+02 3.837872963500269e+08 7.818269647609487e+08 + 8.367346938775508e-01 -2.163998201705838e+00 9.428716335486106e+01 2.922152544706123e+08 6.257356863909814e+08 + 8.571428571428570e-01 -2.175841166085000e+00 7.800953847011847e+01 2.234419323778142e+08 4.853089503492516e+08 + 8.775510204081634e-01 -2.155303774975188e+00 6.432912305900471e+01 1.655441909972637e+08 3.752666314364563e+08 + 8.979591836734692e-01 -2.102909521958467e+00 5.344190109844552e+01 1.178503801821035e+08 2.918966298394187e+08 + 9.183673469387755e-01 -2.018403421317624e+00 4.450335078883321e+01 7.916644695614292e+07 2.239967950809962e+08 + 9.387755102040815e-01 -1.896743213972770e+00 3.669679320964971e+01 4.921992371612750e+07 1.631692262693548e+08 + 9.591836734693876e-01 -1.724325762660474e+00 2.687365619764821e+01 2.743282717773140e+07 1.064318616320310e+08 + 9.795918367346939e-01 -1.508125114401624e+00 2.157201084316552e+01 1.296677095760643e+07 6.715371720843673e+07 + 1.000000000000000e+00 -1.242387706272970e+00 5.767382468564499e+00 1.862011072702549e+05 1.663313892259768e+06 ---------------------- BLADE MODE SHAPES --------------------------------------- -0.01520658920198625 BldFl1Sh(2) - Flap mode 1, coeff of x^2 2.420976935410554 BldFl1Sh(3) - , coeff of x^3 diff --git a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_InflowFile.dat b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_InflowFile.dat index b6c9be878..6d66c034f 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_InflowFile.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/IEA-15-240-RWT/IEA-15-240-RWT_InflowFile.dat @@ -11,7 +11,7 @@ False VelInterpCubic - Use cubic interpolation for velocity in 0.0 WindVyiList - List of coordinates in the inertial Y direction (m) 150.0 WindVziList - List of coordinates in the inertial Z direction (m) ================== Parameters for Steady Wind Conditions [used only for WindType = 1] ========================= -10.0 HWindSpeed - Horizontal windspeed (m/s) +15.0 HWindSpeed - Horizontal windspeed (m/s) 150.0 RefHt - Reference height for horizontal wind speed (m) 0.12 PLexp - Power law exponent (-) ================== Parameters for Uniform wind file [used only for WindType = 2] ============================ diff --git a/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col1.dat b/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col1.dat index c35e51c98..ddb13f7d3 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col1.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/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: Force determined by external DLL} + 7 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] diff --git a/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col2.dat b/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col2.dat index 768c74a88..ee58c1420 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col2.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/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: Force determined by external DLL} + 7 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] diff --git a/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col3.dat b/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col3.dat index c9c5bc66c..e53100add 100644 --- a/Examples/Test_Cases/IEA-15-240-RWT/StC-Force-Col3.dat +++ b/Examples/Test_Cases/IEA-15-240-RWT/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: Force determined by external DLL} + 7 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] diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat index 29c7548a6..5f2f72a9f 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_AeroDyn15_Blade.dat @@ -2,37 +2,37 @@ 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 +BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID t_c BlCb BlCenBn BlCenBt BlCpn BlCpt BlCan BlCat BlCam +(m) (m) (m) (deg) (deg) (m) (-) (-) (-) (m) (m) (-) (-) (-) (-) (-) +0.000 0.00 0.00 0.00 12.86 0.800 1 1.0000 0.9956 0.0000 0.00000 1.0 1.0 1.0 1.0 1.0 +0.150 0.00 0.00 0.00 12.86 0.800 1 1.0000 0.9956 0.0000 0.00000 1.0 1.0 1.0 1.0 1.0 +0.450 0.00 0.00 0.00 12.86 0.894 2 0.8651 0.8572 0.0023 0.01458 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +0.750 0.00 0.00 0.00 12.86 1.118 3 0.6293 0.6118 0.0082 0.05128 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +1.050 0.00 0.00 0.00 12.86 1.386 4 0.4447 0.4145 0.0153 0.12252 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +1.350 0.00 0.00 0.00 12.86 1.610 5 0.3291 0.2873 0.0217 0.16820 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +1.650 0.00 0.00 0.00 12.86 1.704 6 0.2770 0.2287 0.0250 0.17802 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +1.950 0.00 0.00 0.00 11.54 1.662 7 0.2604 0.2099 0.0250 0.15896 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +2.250 0.00 0.00 0.00 10.44 1.619 8 0.2488 0.1966 0.0247 0.14317 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +2.550 0.00 0.00 0.00 9.50 1.577 9 0.2398 0.1870 0.0245 0.12821 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +2.850 0.00 0.00 0.00 8.71 1.534 9 0.2398 0.1870 0.0238 0.12472 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +3.150 0.00 0.00 0.00 8.02 1.492 9 0.2398 0.1870 0.0232 0.12136 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +3.450 0.00 0.00 0.00 7.43 1.450 9 0.2398 0.1870 0.0225 0.11790 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +3.750 0.00 0.00 0.00 6.91 1.407 9 0.2398 0.1870 0.0218 0.11441 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +4.050 0.00 0.00 0.00 6.45 1.365 9 0.2398 0.1870 0.0212 0.11105 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +4.350 0.00 0.00 0.00 6.04 1.322 9 0.2398 0.1870 0.0205 0.10756 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +4.650 0.00 0.00 0.00 5.68 1.279 9 0.2398 0.1870 0.0198 0.10397 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +4.950 0.00 0.00 0.00 5.35 1.235 9 0.2398 0.1870 0.0192 0.10045 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +5.250 0.00 0.00 0.00 5.05 1.192 9 0.2398 0.1870 0.0185 0.09696 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +5.550 0.00 0.00 0.00 4.77 1.148 9 0.2398 0.1870 0.0178 0.09334 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +5.850 0.00 0.00 0.00 4.51 1.103 9 0.2398 0.1870 0.0171 0.08969 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +6.150 0.00 0.00 0.00 4.26 1.058 9 0.2398 0.1870 0.0164 0.08604 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +6.450 0.00 0.00 0.00 4.03 1.012 9 0.2398 0.1870 0.0157 0.08226 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +6.750 0.00 0.00 0.00 3.80 0.966 9 0.2398 0.1870 0.0150 0.07858 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +7.050 0.00 0.00 0.00 3.57 0.920 9 0.2398 0.1870 0.0143 0.07480 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +7.350 0.00 0.00 0.00 3.35 0.872 9 0.2398 0.1870 0.0135 0.07096 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +7.650 0.00 0.00 0.00 3.13 0.824 9 0.2398 0.1870 0.0128 0.06702 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +7.950 0.00 0.00 0.00 2.90 0.776 9 0.2398 0.1870 0.0120 0.06308 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +8.250 0.00 0.00 0.00 2.67 0.726 9 0.2398 0.1870 0.0113 0.05908 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +8.550 0.00 0.00 0.00 2.43 0.676 9 0.2398 0.1870 0.0105 0.05498 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +8.850 0.00 0.00 0.00 2.18 0.626 9 0.2398 0.1870 0.0097 0.05088 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 +9.000 0.00 0.00 0.00 2.18 0.626 9 0.2398 0.1870 0.0097 0.05088 1.0 1.0 6.8459E+00 5.4605E-01 5.5180E-02 \ No newline at end of file diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN b/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN index 2cdd0429c..8b47be58a 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_DISCON.IN @@ -1,5 +1,5 @@ ! Controller parameter input file for the MHK_RM1_Floating wind turbine -! - File written using ROSCO version 2.10.1 controller tuning logic on 11/26/25 +! - File written using ROSCO version 2.10.6 controller tuning logic on 06/09/26 !------- 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) @@ -18,7 +18,7 @@ 1 ! SS_Mode - Setpoint Smoother mode (0: no setpoint smoothing, 1: introduce setpoint smoothing) 0 ! PRC_Mode - Power reference tracking mode (0: power control disabled, 1: lookup table from wind speed to generator speed setpoints, 2: change speed, torque, pitch to control power) 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) +1 ! PS_Mode - Pitch saturation mode (0: no pitch saturation, 1: implement pitch saturation) 0 ! SU_Mode - Startup mode (0: no startup procedure, 1: startup enabled) 0 ! SD_Mode - Shutdown mode (0: no shutdown procedure, 1: shutdown enabled) 1 ! Fl_Mode - Floating specific feedback mode (0: no nacelle velocity feedback, 1: feed back translational velocity, 2: feed back rotational velocity) @@ -48,16 +48,16 @@ 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]. -0.6613 1.0000 ! 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]. +0.4000 1.0000 ! 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]. 0.0000 1.0000 ! F_FlpCornerFreq - Corner frequency and damping in the second order low pass filter of the blade root bending moment for flap control 0.20944 ! F_VSRefSpdCornerFreq - Corner frequency (-3dB point) in the first order low pass filter of the generator speed reference used for TSR tracking torque control [rad/s]. !------- BLADE PITCH CONTROL ---------------------------------------------- 30 ! PC_GS_n - Amount of gain-scheduling table entries 0.030 0.049 0.064 0.076 0.087 0.097 0.107 0.115 0.124 0.131 0.139 0.146 0.153 0.160 0.166 0.173 0.179 0.185 0.191 0.197 0.202 0.208 0.214 0.219 0.224 0.230 0.235 0.240 0.245 0.250 ! PC_GS_angles - Gain-schedule table: pitch angles [rad]. --1.022e-02 -8.820e-03 -7.664e-03 -6.693e-03 -5.865e-03 -5.150e-03 -4.528e-03 -3.981e-03 -3.496e-03 -3.064e-03 -2.676e-03 -2.325e-03 -2.007e-03 -1.718e-03 -1.453e-03 -1.209e-03 -9.849e-04 -7.774e-04 -5.850e-04 -4.060e-04 -2.392e-04 -8.329e-05 6.273e-05 1.998e-04 3.286e-04 4.501e-04 5.646e-04 6.729e-04 7.755e-04 8.727e-04 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. --5.286e-03 -4.785e-03 -4.370e-03 -4.022e-03 -3.725e-03 -3.469e-03 -3.246e-03 -3.050e-03 -2.876e-03 -2.721e-03 -2.581e-03 -2.456e-03 -2.342e-03 -2.238e-03 -2.143e-03 -2.056e-03 -1.975e-03 -1.901e-03 -1.832e-03 -1.768e-03 -1.708e-03 -1.652e-03 -1.599e-03 -1.550e-03 -1.504e-03 -1.461e-03 -1.419e-03 -1.381e-03 -1.344e-03 -1.309e-03 ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-]. +-2.407e-02 -2.136e-02 -1.912e-02 -1.724e-02 -1.563e-02 -1.424e-02 -1.304e-02 -1.197e-02 -1.103e-02 -1.020e-02 -9.442e-03 -8.763e-03 -8.146e-03 -7.584e-03 -7.070e-03 -6.597e-03 -6.162e-03 -5.760e-03 -5.386e-03 -5.039e-03 -4.715e-03 -4.413e-03 -4.130e-03 -3.864e-03 -3.614e-03 -3.378e-03 -3.156e-03 -2.946e-03 -2.747e-03 -2.558e-03 ! PC_GS_KP - Gain-schedule table: pitch controller kp gains [s]. +-3.864e-03 -3.498e-03 -3.195e-03 -2.940e-03 -2.723e-03 -2.536e-03 -2.372e-03 -2.229e-03 -2.102e-03 -1.989e-03 -1.887e-03 -1.795e-03 -1.712e-03 -1.636e-03 -1.566e-03 -1.503e-03 -1.444e-03 -1.389e-03 -1.339e-03 -1.292e-03 -1.248e-03 -1.207e-03 -1.169e-03 -1.133e-03 -1.099e-03 -1.068e-03 -1.038e-03 -1.009e-03 -9.822e-04 -9.568e-04 ! PC_GS_KI - Gain-schedule table: pitch controller ki gains [-]. 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 ! PC_GS_KD - Gain-schedule table: pitch controller kd gains 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 0.000e+00 ! PC_GS_TF - Gain-schedule table: pitch controller tf gains (derivative filter) 1.570000000000 ! PC_MaxPit - Maximum physical pitch limit, [rad]. @@ -89,8 +89,8 @@ 8.30034e+03 ! VS_RtTq - Rated torque, [Nm]. 63.81200 ! VS_RefSpd - Rated generator speed [rad/s] 1 ! VS_n - Number of generator PI torque controller gains --7.38377e+01 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) --8.44329e+01 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) +-2.54753e+02 ! VS_KP - Proportional gain for generator PI torque controller [-]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) +-7.49531e+01 ! VS_KI - Integral gain for generator PI torque controller [s]. (Only used in the transitional 2.5 region if VS_ControlMode =/ 2) 7.00000 ! VS_TSRopt - Power-maximizing region 2 tip-speed-ratio. Only used in VS_ControlMode = 2. !------- FIXED PITCH REGION 3 TORQUE CONTROL ------------------------------------------------ @@ -122,13 +122,13 @@ 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] +2339369.00000 ! 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 49 ! 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 0.500 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 ! WE_FOPoles_v - Wind speeds corresponding to first-order system poles [m/s] --1.448e-01 -1.598e-01 -1.748e-01 -1.897e-01 -2.047e-01 -2.197e-01 -2.347e-01 -2.497e-01 -2.646e-01 -2.796e-01 -2.946e-01 -3.096e-01 -3.246e-01 -3.395e-01 -3.545e-01 -3.695e-01 -3.845e-01 -3.995e-01 -4.144e-01 -4.294e-01 -4.444e-01 -4.594e-01 -4.743e-01 -4.893e-01 -5.053e-01 -5.210e-01 -5.342e-01 -5.444e-01 -5.515e-01 -5.550e-01 1.819e-01 1.531e-01 1.112e-01 6.086e-02 2.881e-03 -5.311e-02 -1.162e-01 -1.778e-01 -2.452e-01 -3.098e-01 -3.809e-01 -4.481e-01 -5.198e-01 -5.927e-01 -6.644e-01 -7.410e-01 -8.151e-01 -8.908e-01 -9.708e-01 -1.047e+00 -1.126e+00 -1.208e+00 -1.287e+00 -1.368e+00 -1.452e+00 -1.535e+00 -1.616e+00 -1.701e+00 -1.789e+00 -1.872e+00 ! WE_FOPoles - First order system poles [1/s] +-2.996e-02 -3.306e-02 -3.616e-02 -3.926e-02 -4.236e-02 -4.546e-02 -4.856e-02 -5.166e-02 -5.475e-02 -5.785e-02 -6.095e-02 -6.405e-02 -6.715e-02 -7.025e-02 -7.335e-02 -7.645e-02 -7.955e-02 -8.265e-02 -8.575e-02 -8.885e-02 -9.195e-02 -9.505e-02 -9.814e-02 -1.012e-01 -1.045e-01 -1.078e-01 -1.105e-01 -1.126e-01 -1.141e-01 -1.148e-01 3.763e-02 3.168e-02 2.301e-02 1.259e-02 5.960e-04 -1.099e-02 -2.403e-02 -3.679e-02 -5.073e-02 -6.410e-02 -7.882e-02 -9.271e-02 -1.075e-01 -1.226e-01 -1.375e-01 -1.533e-01 -1.687e-01 -1.843e-01 -2.009e-01 -2.166e-01 -2.329e-01 -2.499e-01 -2.663e-01 -2.830e-01 -3.004e-01 -3.175e-01 -3.344e-01 -3.520e-01 -3.701e-01 -3.872e-01 ! 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] @@ -150,7 +150,7 @@ !------- 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) 0.5000 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 ! PS_WindSpeeds - Wind speeds corresponding to minimum blade pitch angles [m/s] -0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 ! PS_BldPitchMin - Minimum blade pitch angles [rad] +0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0000 0.0077 0.0181 0.0276 0.0368 0.0456 0.0543 0.0597 0.0650 0.0703 0.0754 0.0805 0.0857 0.0906 0.0955 0.1004 0.1053 0.1100 0.1148 0.1195 0.1242 0.1288 0.1334 0.1380 0.1425 0.1470 0.1515 0.1560 0.1604 0.1648 0.1691 0.1736 0.1778 0.1821 0.1864 0.1907 0.1950 ! PS_BldPitchMin - Minimum blade pitch angles [rad] !------- STARTUP ----------------------------------------------------------- 120.0000000000 ! SU_StartTime - Time to start startup routine [s] diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat index df6ab8c87..b0c7ef72b 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Blade.dat @@ -12,83 +12,83 @@ Floating MHK turbine structural blade input properties, based on the RM1 tidal c 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 + BlFract StrcTwst BMassDen FlpStff EdgStff + (-) (deg) (kg/m) (Nm^2) (Nm^2) + 0.000000000000000E+00 1.286000000000000E+01 8.186799999999999E+02 2.430000000000000E+14 2.520000000000000E+14 + 8.300000000000000E-03 1.286000000000000E+01 8.336000000000000E+02 2.470000000000000E+14 2.690000000000000E+14 + 1.670000000000000E-02 1.286000000000000E+01 8.464400000000001E+02 2.470000000000000E+14 2.840000000000000E+14 + 2.500000000000000E-02 1.286000000000000E+01 8.586799999999999E+02 2.460000000000000E+14 3.000000000000000E+14 + 3.330000000000000E-02 1.286000000000000E+01 8.703200000000001E+02 2.440000000000000E+14 3.150000000000000E+14 + 4.170000000000000E-02 1.286000000000000E+01 9.006400000000000E+02 2.500000000000000E+14 3.590000000000000E+14 + 5.000000000000000E-02 1.286000000000000E+01 9.326400000000000E+02 2.490000000000000E+14 4.030000000000000E+14 + 5.830000000000000E-02 1.286000000000000E+01 6.813200000000001E+02 1.700000000000000E+14 1.120000000000000E+14 + 6.670000000000000E-02 1.286000000000000E+01 6.280000000000000E+02 1.480000000000000E+14 1.110000000000000E+14 + 7.500000000000000E-02 1.286000000000000E+01 5.752800000000000E+02 1.300000000000000E+14 1.100000000000000E+14 + 8.330000000000000E-02 1.286000000000000E+01 5.289600000000000E+02 1.120000000000000E+14 1.070000000000000E+14 + 9.170000000000000E-02 1.286000000000000E+01 4.589200000000000E+02 8.820000000000000E+13 9.560000000000000E+13 + 1.000000000000000E-01 1.286000000000000E+01 4.016000000000000E+02 6.720000000000000E+13 8.550000000000000E+13 + 1.083000000000000E-01 1.286000000000000E+01 4.111600000000000E+02 6.450000000000000E+13 9.150000000000000E+13 + 1.167000000000000E-01 1.286000000000000E+01 4.102800000000000E+02 6.000000000000000E+13 9.530000000000000E+13 + 1.250000000000000E-01 1.286000000000000E+01 4.153600000000000E+02 5.620000000000000E+13 1.010000000000000E+14 + 1.333000000000000E-01 1.286000000000000E+01 4.210000000000000E+02 5.170000000000000E+13 1.060000000000000E+14 + 1.417000000000000E-01 1.286000000000000E+01 4.212800000000000E+02 4.940000000000000E+13 1.080000000000000E+14 + 1.500000000000000E-01 1.286000000000000E+01 4.214000000000000E+02 4.700000000000000E+13 1.100000000000000E+14 + 1.583000000000000E-01 1.286000000000000E+01 4.249600000000000E+02 4.450000000000000E+13 1.120000000000000E+14 + 1.667000000000000E-01 1.286000000000000E+01 4.354800000000000E+02 4.300000000000000E+13 1.160000000000000E+14 + 1.750000000000000E-01 1.253000000000000E+01 4.284000000000000E+02 4.090000000000000E+13 1.130000000000000E+14 + 1.833000000000000E-01 1.220000000000000E+01 4.238800000000000E+02 3.890000000000000E+13 1.100000000000000E+14 + 1.917000000000000E-01 1.187000000000000E+01 4.356800000000000E+02 3.840000000000000E+13 1.150000000000000E+14 + 2.000000000000000E-01 1.154000000000000E+01 4.306000000000000E+02 3.620000000000000E+13 1.120000000000000E+14 + 2.083000000000000E-01 1.126500000000000E+01 4.345200000000000E+02 3.570000000000000E+13 1.110000000000000E+14 + 2.167000000000000E-01 1.099000000000000E+01 4.302800000000000E+02 3.410000000000000E+13 1.090000000000000E+14 + 2.250000000000000E-01 1.071500000000000E+01 4.260400000000000E+02 3.260000000000000E+13 1.060000000000000E+14 + 2.333000000000000E-01 1.044000000000000E+01 4.218400000000000E+02 3.110000000000000E+13 1.030000000000000E+14 + 2.500000000000000E-01 9.970000000000001E+00 4.150000000000000E+02 2.910000000000000E+13 9.840000000000000E+13 + 2.667000000000000E-01 9.500000000000000E+00 4.112000000000000E+02 2.720000000000000E+13 9.540000000000000E+13 + 2.833000000000000E-01 9.105000000000000E+00 3.958800000000000E+02 2.540000000000000E+13 8.960000000000000E+13 + 3.000000000000000E-01 8.710000000000001E+00 3.904000000000000E+02 2.430000000000000E+13 8.590000000000000E+13 + 3.167000000000000E-01 8.365000000000000E+00 3.778400000000000E+02 2.260000000000000E+13 8.060000000000000E+13 + 3.333000000000000E-01 8.020000000000000E+00 3.624400000000000E+02 2.150000000000000E+13 7.340000000000000E+13 + 3.500000000000000E-01 7.725000000000000E+00 3.474800000000000E+02 2.000000000000000E+13 6.870000000000000E+13 + 3.667000000000000E-01 7.430000000000000E+00 3.356000000000000E+02 1.850000000000000E+13 6.420000000000000E+13 + 3.833000000000000E-01 7.170000000000000E+00 3.306400000000000E+02 1.770000000000000E+13 6.140000000000000E+13 + 4.000000000000000E-01 6.910000000000000E+00 3.189600000000000E+02 1.630000000000000E+13 5.720000000000000E+13 + 4.167000000000000E-01 6.680000000000000E+00 3.028400000000000E+02 1.500000000000000E+13 5.330000000000000E+13 + 4.333000000000000E-01 6.450000000000000E+00 2.982400000000000E+02 1.430000000000000E+13 5.090000000000000E+13 + 4.500000000000000E-01 6.245000000000000E+00 2.871200000000000E+02 1.320000000000000E+13 4.730000000000000E+13 + 4.667000000000000E-01 6.040000000000000E+00 2.672400000000000E+02 1.190000000000000E+13 4.120000000000000E+13 + 4.833000000000000E-01 5.860000000000000E+00 2.566800000000000E+02 1.090000000000000E+13 3.810000000000000E+13 + 5.000000000000000E-01 5.680000000000000E+00 2.499600000000000E+02 1.040000000000000E+13 3.620000000000000E+13 + 5.167000000000000E-01 5.515000000000000E+00 2.396800000000000E+02 9.420000000000000E+12 3.330000000000000E+13 + 5.333000000000000E-01 5.350000000000000E+00 2.277600000000000E+02 8.540000000000000E+12 3.060000000000000E+13 + 5.500000000000000E-01 5.200000000000000E+00 2.156400000000000E+02 7.730000000000000E+12 2.810000000000000E+13 + 5.667000000000000E-01 5.050000000000000E+00 2.061600000000000E+02 6.970000000000000E+12 2.580000000000000E+13 + 5.833000000000000E-01 4.910000000000000E+00 1.888000000000000E+02 6.170000000000000E+12 2.170000000000000E+13 + 6.000000000000000E-01 4.770000000000000E+00 1.798000000000000E+02 5.510000000000000E+12 1.970000000000000E+13 + 6.167000000000000E-01 4.640000000000000E+00 1.762800000000000E+02 5.190000000000000E+12 1.850000000000000E+13 + 6.333000000000000E-01 4.510000000000000E+00 1.653200000000000E+02 4.610000000000000E+12 1.680000000000000E+13 + 6.500000000000000E-01 4.385000000000000E+00 1.568000000000000E+02 4.070000000000000E+12 1.510000000000000E+13 + 6.667000000000000E-01 4.260000000000000E+00 1.448800000000000E+02 3.570000000000000E+12 1.360000000000000E+13 + 6.833000000000000E-01 4.145000000000000E+00 1.368000000000000E+02 3.110000000000000E+12 1.210000000000000E+13 + 7.000000000000000E-01 4.030000000000000E+00 1.289200000000000E+02 2.690000000000000E+12 1.080000000000000E+13 + 7.167000000000000E-01 3.915000000000000E+00 1.193600000000000E+02 2.310000000000000E+12 9.550000000000000E+12 + 7.333000000000000E-01 3.800000000000000E+00 1.119600000000000E+02 1.960000000000000E+12 8.420000000000000E+12 + 7.500000000000000E-01 3.685000000000000E+00 1.030000000000000E+02 1.650000000000000E+12 7.390000000000000E+12 + 7.667000000000000E-01 3.570000000000000E+00 9.472000000000000E+01 1.370000000000000E+12 6.450000000000000E+12 + 7.833000000000000E-01 3.460000000000000E+00 8.795999999999999E+01 1.120000000000000E+12 5.570000000000000E+12 + 8.000000000000000E-01 3.350000000000000E+00 7.976000000000001E+01 8.910000000000000E+11 4.770000000000000E+12 + 8.167000000000000E-01 3.240000000000000E+00 7.352000000000000E+01 6.930000000000000E+11 4.050000000000000E+12 + 8.333000000000000E-01 3.130000000000000E+00 7.144000000000000E+01 6.360000000000000E+11 3.720000000000000E+12 + 8.500000000000000E-01 3.015000000000000E+00 6.400000000000000E+01 4.760000000000000E+11 3.110000000000000E+12 + 8.667000000000000E-01 2.900000000000000E+00 5.724000000000000E+01 3.380000000000000E+11 2.560000000000000E+12 + 8.833000000000000E-01 2.785000000000000E+00 5.036000000000000E+01 2.190000000000000E+11 2.040000000000000E+12 + 9.000000000000000E-01 2.670000000000000E+00 4.868000000000000E+01 1.980000000000000E+11 1.840000000000000E+12 + 9.167000000000000E-01 2.550000000000000E+00 4.700000000000000E+01 1.780000000000000E+11 1.660000000000000E+12 + 9.333000000000000E-01 2.430000000000000E+00 4.532000000000000E+01 1.590000000000000E+11 1.490000000000000E+12 + 9.500000000000000E-01 2.305000000000000E+00 4.676000000000000E+01 1.980000000000000E+11 1.510000000000000E+12 + 9.667000000000000E-01 2.180000000000000E+00 4.404000000000000E+01 1.760000000000000E+11 1.340000000000000E+12 + 9.833000000000000E-01 2.060000000000000E+00 4.228000000000000E+01 1.560000000000000E+11 1.190000000000000E+12 + 1.000000000000000E+00 2.060000000000000E+00 4.228000000000000E+01 1.560000000000000E+11 1.190000000000000E+12 ---------------------- BLADE MODE SHAPES --------------------------------------- 1.88070 BldFl1Sh(2) - Flap mode 1, coeff of x^2 -1.44580 BldFl1Sh(3) - , coeff of x^3 diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat index 3c04a12f8..513d8e6b0 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ElastoDyn_Tower.dat @@ -1,7 +1,7 @@ ------- 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 + 5 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 (%) @@ -12,41 +12,35 @@ Floating MHK turbine structural tower input properties, based on the RM1 tidal c 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 + 1 AdjFASt - Factor to adjust tower fore-aft stiffness (-) + 1 AdjSSSt - Factor to adjust tower side-to-side stiffness (-) +---------------------- DISTRIBUTED TOWER PROPERTIES ---------------------------- +HtFract TMassDen TwFAStif TwSSStif +(-) (kg/m) (Nm^2) (Nm^2) +0.00 652.34 5.62E+09 5.66E+08 +0.25 652.34 5.62E+09 5.66E+08 +0.50 652.34 5.62E+09 5.66E+08 +0.75 652.34 5.62E+09 5.66E+08 +1.00 652.34 5.62E+09 5.66E+08 +---------------------- TOWER FORE-AFT MODE SHAPES ------------------------------ + 1.4869000 TwFAM1Sh(2) - Mode 1, coefficient of x^2 term + -0.4901000 TwFAM1Sh(3) - , coefficient of x^3 term + 0.0024004 TwFAM1Sh(4) - , coefficient of x^4 term + -0.0014264 TwFAM1Sh(5) - , coefficient of x^5 term + 0.0022151 TwFAM1Sh(6) - , coefficient of x^6 term + 47.3126000 TwFAM2Sh(2) - Mode 2, coefficient of x^2 term + -47.0099000 TwFAM2Sh(3) - , coefficient of x^3 term + -6.1018000 TwFAM2Sh(4) - , coefficient of x^4 term + 8.9324000 TwFAM2Sh(5) - , coefficient of x^5 term + -2.1333000 TwFAM2Sh(6) - , coefficient of x^6 term +---------------------- TOWER SIDE-TO-SIDE MODE SHAPES -------------------------- + 1.5007000 TwSSM1Sh(2) - Mode 1, coefficient of x^2 term + -0.4979700 TwSSM1Sh(3) - , coefficient of x^3 term + -0.0116500 TwSSM1Sh(4) - , coefficient of x^4 term + 0.0104020 TwSSM1Sh(5) - , coefficient of x^5 term + -0.0014532 TwSSM1Sh(6) - , coefficient of x^6 term + 408.3002000 TwSSM2Sh(2) - Mode 2, coefficient of x^2 term +-420.2848000 TwSSM2Sh(3) - , coefficient of x^3 term +-111.0241000 TwSSM2Sh(4) - , coefficient of x^4 term + 166.6788000 TwSSM2Sh(5) - , coefficient of x^5 term + -42.6701000 TwSSM2Sh(6) - , coefficient of x^6 term \ 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 index 4b8fefdc1..15df8ca63 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.fst +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating.fst @@ -5,21 +5,28 @@ 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) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 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} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 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 NRotors - Number of rotors in turbine (-) + 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} + 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} + 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} 1 CompServo - Compute control and electrical-drive dynamics (switch) {0=None; 1=ServoDyn} 1 CompSeaSt - Compute sea state information (switch) {0=None; 1=SeaState} 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 2 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.80665 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ False Echo - Echo input data to .ech (flag) "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) +"unused" SoilFile - Name of the file containing the SoilDyn 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} + 3 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat index 86ee6ba96..712b2f719 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_AeroDyn15.dat @@ -7,8 +7,7 @@ False Echo - Echo the input to ".AD.ech"? (flag 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) -True CavitCheck - Perform cavitation check? (flag) [AFAeroMod must be 1 when CavitCheck=true] -True Buoyancy - Include buoyancy effects? (flag) +False CavitCheck - Perform cavitation check? (flag) [AFAeroMod must be 1 when CavitCheck=true] False NacelleDrag - Include Nacelle Drag 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] @@ -45,7 +44,7 @@ default SectAvgPsiFwd - Forward azimuth relative to blade where t ====== 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] ====== Unsteady Airfoil Aerodynamics Options ==================================================== -True AoA34 - Sample the angle of attack (AoA) at the 3/4 chord or the AC point {default=True} [always used] +False AoA34 - Sample the angle of attack (AoA) at the 3/4 chord or the AC point {default=True} [always used] 0 UA_Mod - Unsteady Aero Model Switch (switch) {0=Quasi-steady (no UA), 2=B-L Gonzalez, 3=B-L Minnema/Pierce, 4=B-L HGM 4-states, 5=B-L HGM+vortex 5 states, 6=Oye, 7=Boeing-Vertol} 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 UA_Mod>0] 3 IntegrationMethod - Switch to indicate which integration method UA uses (1=RK4, 2=AB4, 3=ABM4, 4=BDF2) @@ -73,68 +72,73 @@ False UseBlCm - Include aerodynamic pitching moment in calcul "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 or NacelleDrag=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) -, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) -0, 0, 0 NacCd - Drag coefficient for the nacelle areas defined above (-) -0, 0, 0 NacDragAC - Position of aerodynamic center of nacelle drag in nacelle coordinates (m) +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] +0.01 VolHub - Hub volume (m^3) +0 HubCenBx - Hub center of buoyancy x direction offset (m) +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] +0 VolNac - Nacelle volume (m^3) +0, 0, 0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) +0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) +0, 0, 0 NacCd - Drag coefficient for the nacelle areas defined above (-) +0, 0, 0 NacDragAC - Position of aerodynamic center of nacelle drag 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 +====== Tower Influence and Aerodynamics ============================================================ [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +4 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +-9.0000000E+00 3.2530000E-01 2.0000000E-01 0.0000000E+00 0.0000000E+00 0.0000000E+00 0.0000000E+00 +-1.4000000E+01 3.2530000E-01 2.0000000E-01 0.0000000E+00 0.0000000E+00 0.0000000E+00 0.0000000E+00 +-1.9000000E+01 3.2530000E-01 2.0000000E-01 0.0000000E+00 0.0000000E+00 0.0000000E+00 0.0000000E+00 +-2.2800000E+01 3.2530000E-01 2.0000000E-01 0.0000000E+00 0.0000000E+00 0.0000000E+00 0.0000000E+00 ====== 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) ------------------------------------------------------------------------------------------------------ +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 OutList section (the word "END" must appear in the first 3 columns of the last OutList line) +---------------------- NODE OUTPUTS -------------------------------------------- +1 BldNd_BladesOut - Number of blades to output all node information at. Up to number of blades on turbine. (-) +ALL BldNd_BlOutNd - Specify a portion of the nodes to output. {"ALL", "Tip", "Root", or a list of node numbers} (-) + OutList_Nodal - The next line(s) contains a list of output parameters. See OutListParameters.xlsx for a listing of available output channels, (-) +END (the word "END" must appear in the first 3 columns of this last OutList line in the optional nodal output section) +==================================================================================================== diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat index ab940ac65..f5e32b24f 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_ElastoDyn.dat @@ -8,6 +8,7 @@ False Echo - Echo input data to ".ech" (flag) 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 PitchDOF - Blade pitch DOF (flag) False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] False DrTrDOF - Drivetrain rotational-flexibility DOF (flag) True GenDOF - Generator DOF (flag) @@ -25,16 +26,16 @@ 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) - 0 BlPitch(1) - Blade 1 initial pitch (degrees) - 0 BlPitch(2) - Blade 2 initial pitch (degrees) - 0 BlPitch(3) - Blade 3 initial pitch (degrees) [unused for 2 blades] + 7 BlPitch(1) - Blade 1 initial pitch (degrees) + 7 BlPitch(2) - Blade 2 initial pitch (degrees) + 7 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) + 2 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) @@ -61,20 +62,28 @@ True PtfmYDOF - Platform yaw rotation DOF (flag) 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) + -22.8 TowerHt - Height of tower relative to ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] (meters) + -9 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 PtfmRefxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (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] + 0 PBrIner(1) - Pitch bearing inertia, blade 1 (kg m^2) + 0 PBrIner(2) - Pitch bearing inertia, blade 2 (kg m^2) + 0 PBrIner(3) - Pitch bearing inertia, blade 3 (kg m^2) [unused for 2 blades] + 0 BlPIner(1) - Blade pitch inertia, blade 1 (kg m^2) + 0 BlPIner(2) - Blade pitch inertia, blade 2 (kg m^2) + 0 BlPIner(3) - Blade pitch inertia, blade 3 (kg m^2) [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) - 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) - 139.50 GenIner - Generator inertia about HSS (kg m^2) + 72.69 HubIner - Hub inertia about rotor axis (2 or 3-blades) (kg m^2) + 79.6 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) + 800.0 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) diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat index 05228c7e7..efec31f03 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_HydroDyn.dat @@ -4,7 +4,7 @@ False Echo - Echo the input file data (flag) ---------------------- 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] - 0 ExctnDisp - Method of computing Wave Excitation {0: use undisplaced position, 1: use displaced position, 2: use low-pass filtered displaced position) [only used when PotMod=1 and ExctnMod>0 and SeaState's WaveMod>0]} (switch) + 1 ExctnDisp - Method of computing Wave Excitation {0: use undisplaced position, 1: use displaced position, 2: use low-pass filtered displaced position) [only used when PotMod=1 and ExctnMod>0 and SeaState's WaveMod>0]} (switch) 0 ExctnCutOff - Cutoff (corner) frequency of the low-pass time-filtered displaced position (Hz) [>0.0] [used only when PotMod=1, ExctnMod>0, and ExctnDisp=2]) [only used when PotMod=1 and ExctnMod>0 and SeaState's WaveMod>0]} (switch) 0 PtfmYMod - Model for large platform yaw offset {0: Static reference yaw offset based on PtfmRefY, 1: dynamic reference yaw offset based on low-pass filtering the PRP yaw motion with cutoff frequency PtfmYCutOff} (switch) 0 PtfmRefY - Constant (if PtfmYMod=0) or initial (if PtfmYMod=1) platform reference yaw offset (deg) @@ -24,6 +24,7 @@ False Echo - Echo the input file data (flag) 2671.85 PtfmVol0 - 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] + 0 NAddDOF - Number of additional generalized DOF of each WAMIT body (-) [1 to NBody] [>=0; =0 if NBody>1; 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] @@ -55,14 +56,15 @@ False Echo - Echo the input file data (flag) 0 0 0 0 0 0 0 0 0 0 0 0 ---------------------- STRIP THEORY OPTIONS -------------------------------------- - 0 WaveDisp - Method of computing Wave Kinematics {0: use undisplaced position, 1: use displaced position) } (switch) - 0 AMMod - Method of computing distributed added-mass force. (0: Only and always on nodes below SWL at the undisplaced position. 2: Up to the instantaneous free surface) [overwrite to 0 when WaveMod = 0 or 6 or when WaveStMod = 0 in SeaState] + 1 WaveDisp - Method of computing Wave Kinematics {0: use undisplaced position, 1: use displaced position) } (switch) + 0 AMMod - Method of computing distributed added-mass force. (0: Only and always on nodes below SWL at the undisplaced position. 1: Up to the instantaneous free surface) [overwrite to 0 when WaveStMod = 0 in SeaState] + 1 HstMod - Method of computing hydrostatic loads. (0: Up to the still water level. 1: Up to the instantaneous free surface) [overwrite to 0 when WaveStMod = 0 in SeaState] ---------------------- AXIAL COEFFICIENTS -------------------------------------- 2 NAxCoef - Number of axial coefficients (-) AxCoefID AxCd AxCa AxCp AxFDMod AxVnCOff AxFDLoFSc - (-) (-) (-) (-) (-) (-) (-) + (-) (-) (-) (-) (switch) (Hz) (-) 1 0.00 0.00 0.00 0 -1.00 1.00 ! Columns / Braces (no exposed member ends) - 2 1.00 1.00 1.00 0 -1.00 1.00 ! Heave Plates + 2 8.00 0.00 0.00 0 -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] @@ -100,66 +102,66 @@ JointID Jointxi Jointyi Jointzi JointAxID JointOvrlp [JointOvrlp= 30 -28.00000 0.00000 -10.50000 2 0 31 0.00000 -12.00000 -10.50000 2 0 32 0.00000 12.00000 -10.50000 2 0 ----------------------- CYLINDRICAL MEMBER CROSS-SECTION PROPERTIES ------------------------- - 4 NPropSets - Number of member property sets (-) +---------------- CYLINDRICAL MEMBER CROSS-SECTION PROPERTIES ------------------- + 4 NPropSetsCyl - Number of cylindrical member property sets (-) PropSetID PropD PropThck (-) (m) (m) 0 8.00000 0.02000 ! Columns 1 2.00000 0.02000 ! Braces 2 2.00000 0.08100 ! Flooded Braces (not flooded in hydrodyn) 3 12.00000 0.39250 ! Flooded Heave Plates (not flooded in hydrodyn) ----------------------- RECTANGULAR MEMBER CROSS-SECTION PROPERTIES ------------------------- -0 NPropSetsRec - Number of member property sets (-) - PropSetID PropD PropThck - (-) (m) (m) ----------------------- SIMPLE CYLINDRICAL-MEMBER HYDRODYNAMIC COEFFICIENTS (model 1) -------------- +---------------- RECTANGULAR MEMBER CROSS-SECTION PROPERTIES ------------------- + 0 NPropSetsRec - Number of rectangular member property sets (-) +MPropSetID PropA PropB PropThck + (-) (m) (m) (m) +-------- SIMPLE CYLINDRICAL-MEMBER HYDRODYNAMIC COEFFICIENTS (model 1) --------- SimplCd SimplCdMG SimplCa SimplCaMG SimplCp SimplCpMG SimplAxCd SimplAxCdMG SimplAxCa SimplAxCaMG SimplAxCp SimplAxCpMG SimplCb SimplCbMG (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) - 1.20 0.00 1.00 0.00 1.00 1.00 0.00 0.00 0.00 0.00 1.00 1.00 1.00 1.00 + 1.20 1.20 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 0.00 1.00 1.00 ---------------------- SIMPLE RECTANGULAR-MEMBER HYDRODYNAMIC COEFFICIENTS (model 1) -------------- SimplCdA SimplCdAMG SimplCdB SimplCdBMG SimplCaA SimplCaAMG SimplCaB SimplCaBMG SimplCp SimplCpMG SimplAxCd SimplAxCdMG SimplAxCa SimplAxCaMG SimplAxCp SimplAxCpMG SimplCb SimplCbMG (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) - 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 ----------------------- DEPTH-BASED CYLINDRICAL-MEMBER HYDRODYNAMIC COEFFICIENTS (model 2) --------- + 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 1.0 1.0 +------ DEPTH-BASED CYLINDRICAL-MEMBER HYDRODYNAMIC COEFFICIENTS (model 2) ------- 0 NCoefDpthCyl - Number of depth-dependent cylindrical member coefficients (-) Dpth DpthCd DpthCdMG DpthCa DpthCaMG DpthCp DpthCpMG DpthAxCd DpthAxCdMG DpthAxCa DpthAxCaMG DpthAxCp DpthAxCpMG DpthCb DpthCbMG (m) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) ----------------------- DEPTH-BASED RECTANGULAR-MEMBER HYDRODYNAMIC COEFFICIENTS (model 2) --------- +------ DEPTH-BASED RECTANGULAR-MEMBER HYDRODYNAMIC COEFFICIENTS (model 2) ------- 0 NCoefDpthRec - Number of depth-dependent rectangular member coefficients (-) Dpth DpthCdA DpthCdAMG DpthCdB DpthCdBMG DpthCaA DpthCaAMG DpthCaB DpthCaBMG DpthCp DpthCpMG DpthAxCd DpthAxCdMG DpthAxCa DpthAxCaMG DpthAxCp DpthAxCpMG DpthCb DpthCbMG (m) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) ----------------------- MEMBER-BASED CYLINDRICAL-MEMBER HYDRODYNAMIC COEFFICIENTS (model 3) -------- - 0 NCoefMembersCyl - Number of member-based cylindrical member coefficients (-) +------ MEMBER-BASED CYLINDRICAL-MEMBER HYDRODYNAMIC COEFFICIENTS (model 3) ------ + 0 NCoefMembersCyl - Number of member-based cylindrical member 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 MemberCb1 MemberCb2 MemberCbMG1 MemberCbMG2 (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) ----------------------- MEMBER-BASED RECTANGULAR-MEMBER HYDRODYNAMIC COEFFICIENTS (model 3) -------- +------ MEMBER-BASED RECTANGULAR-MEMBER HYDRODYNAMIC COEFFICIENTS (model 3) ------ 0 NCoefMembersRec - Number of member-based rectangular member coefficients (-) MemberID MemberCdA1 MemberCdA2 MemberCdAMG1 MemberCdAMG2 MemberCdB1 MemberCdB2 MemberCdBMG1 MemberCdBMG2 MemberCaA1 MemberCaA2 MemberCaAMG1 MemberCaAMG2 MemberCaB1 MemberCaB2 MemberCaBMG1 MemberCaBMG2 MemberCp1 MemberCp2 MemberCpMG1 MemberCpMG2 MemberAxCd1 MemberAxCd2 MemberAxCdMG1 MemberAxCdMG2 MemberAxCa1 MemberAxCa2 MemberAxCaMG1 MemberAxCaMG2 MemberAxCp1 MemberAxCp2 MemberAxCpMG1 MemberAxCpMG2 MemberCb1 MemberCb2 MemberCbMG1 MemberCbMG2 (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) (-) -------------------- MEMBERS ------------------------------------------------- 20 NMembers - Number of members (-) - MemberID MJointID1 MJointID2 MPropSetID1 MPropSetID2 MSecGeom MSpinOrient MDivSize MCoefMod MHstLMod 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] - (-) (-) (-) (-) (-) (switch) (deg) (m) (switch) (switch) (flag) - 0 0 1 0 0 1 0.0 0.1000 1 1 TRUE ! Columns - 1 2 3 0 0 1 0.0 0.1000 1 1 TRUE - 2 4 5 0 0 1 0.0 0.1000 1 1 TRUE - 3 6 7 0 0 1 0.0 0.1000 1 1 TRUE - 4 8 9 1 1 1 0.0 0.1000 1 1 TRUE ! Upper Braces - 5 10 11 1 1 1 0.0 0.1000 1 1 TRUE - 6 12 13 1 1 1 0.0 0.1000 1 1 TRUE - 7 14 15 1 1 1 0.0 0.1000 1 1 TRUE - 8 16 17 2 2 1 0.0 0.1000 1 1 TRUE ! Lower Braces - 9 18 19 2 2 1 0.0 0.1000 1 1 TRUE - 10 20 21 2 2 1 0.0 0.1000 1 1 TRUE - 11 22 23 2 2 1 0.0 0.1000 1 1 TRUE - 12 24 25 1 1 1 0.0 0.1000 1 1 TRUE ! Tower Braces - 13 26 27 1 1 1 0.0 0.1000 1 1 TRUE - 14 24 28 1 1 1 0.0 0.1000 1 1 TRUE - 15 25 28 1 1 1 0.0 0.1000 1 1 TRUE - 16 0 29 3 3 1 0.0 0.1000 1 1 TRUE ! Heave Plates - 17 2 30 3 3 1 0.0 0.1000 1 1 TRUE - 18 4 31 3 3 1 0.0 0.1000 1 1 TRUE - 19 6 32 3 3 1 0.0 0.1000 1 1 TRUE +MemberID MJointID1 MJointID2 MPropSetID1 MPropSetID2 MSecGeom MSpinOrient MDivSize MCoefMod MHstLMod 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] + (-) (-) (-) (-) (-) (switch) (deg) (m) (switch) (switch) (flag) + 0 0 1 0 0 1 0 2.0000 1 1 TRUE ! Columns + 1 2 3 0 0 1 0 2.0000 1 1 TRUE + 2 4 5 0 0 1 0 2.0000 1 1 TRUE + 3 6 7 0 0 1 0 2.0000 1 1 TRUE + 4 8 9 1 1 1 0 2.0000 1 1 TRUE ! Upper Braces + 5 10 11 1 1 1 0 2.0000 1 1 TRUE + 6 12 13 1 1 1 0 2.0000 1 1 TRUE + 7 14 15 1 1 1 0 2.0000 1 1 TRUE + 8 16 17 2 2 1 0 2.0000 1 1 TRUE ! Lower Braces + 9 18 19 2 2 1 0 2.0000 1 1 TRUE + 10 20 21 2 2 1 0 2.0000 1 1 TRUE + 11 22 23 2 2 1 0 2.0000 1 1 TRUE + 12 24 25 1 1 1 0 2.0000 1 1 TRUE ! Tower Braces + 13 26 27 1 1 1 0 2.0000 1 1 TRUE + 14 24 28 1 1 1 0 2.0000 1 1 TRUE + 15 25 28 1 1 1 0 2.0000 1 1 TRUE + 16 0 29 3 3 1 0 2.0000 1 1 TRUE ! Heave Plates + 17 2 30 3 3 1 0 2.0000 1 1 TRUE + 18 4 31 3 3 1 0 2.0000 1 1 TRUE + 19 6 32 3 3 1 0 2.0000 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 @@ -179,11 +181,11 @@ MemberID NOutLoc NodeLocs [NOutLoc < 10; node locations are normalized dist 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!] +"G0" 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) \ No newline at end of file +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 index 73c0b2f76..71f753746 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_InflowWind.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_InflowWind.dat @@ -9,11 +9,11 @@ False VelInterpCubic - Use cubic interpolation for velocity in tim 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] ======================= + 26.0 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 (-) + 26.0 RefHt - Reference height for horizontal wind speed (m) + 0.1429 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) diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat index 89e416dc7..3d529dabf 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_MoorDyn.dat @@ -1,58 +1,52 @@ --------------------- 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 - +Generated with OpenFAST_IO +Comments from seed file have been dropped. Output Channels are not yet fully supported +NOTE: MoorDyn does not use ECHO, instead use WriteLog of 0, 1, 2, or 3 in the options list +----------------------- LINE TYPES ------------------------------------------ +Name Diam MassDen EA BA/-zeta EI Cd Ca CdAx CaAx Cl (optional) dF (optional) cF (optional) +(-) (m) (kg/m) (N) (N-s/-) (N-m^2) (-) (-) (-) (-) (-) (-) (-) +main 0.1502 139.1800 595700000.0000 -0.8000 8.0000e-01 2.4000 1.0000 1.1500 0.5000 +---------------------- POINTS -------------------------------- +ID Attachment X Y Z M V CdA CA +(-) (-) (m) (m) (m) (kg) (m^3) (m^2) (-) +1 Fixed -341.9900 -112.4400 -50.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +2 Fixed -341.9900 112.4400 -50.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +3 Fixed 341.9900 -112.4400 -50.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +4 Fixed 341.9900 112.4400 -50.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +5 Vessel -34.0000 0.0000 -10.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +6 Vessel -34.0000 0.0000 -10.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +7 Vessel 34.0000 0.0000 -10.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +8 Vessel 34.0000 0.0000 -10.0000 0.0000e+00 0.0000e+00 0.0000 0.0000 +---------------------- LINES -------------------------------------- +Line LineType AttachA AttachB UnstrLen NumSegs Outputs +(-) (-) (-) (-) (m) (-) (-) +1 main 1 5 335.1000 40 - +2 main 2 6 335.1000 40 - +3 main 3 7 335.1000 40 - +4 main 4 8 335.1000 40 - ---------------------- 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 (-) + 0.001000 DTM - time step to use in mooring integration (s) + 3000000.000000 KBOT - bottom stiffness (Pa/m) + 300000.000000 CBOT - bottom damping (Pa-s/m) + 1.000000 DTIC - time interval for analyzing convergence during IC gen (s) + 10.000000 TMAXIC - max time for ic gen (s) + 1.000000 CDSCALEIC - factor by which to scale drag coefficients during dynamic relaxation (-) + 0.100000 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 +FairTen1 FairTen2 FairTen3 FairTen4 +AnchTen1 AnchTen2 AnchTen3 AnchTen4 +Con1fX Con1fY Con1fZ +Con2fX Con2fY Con2fZ +Con3fX Con3fY Con3fZ +Con4fX Con4fY Con4fZ +Con5fX Con5fY Con5fZ Con5pX Con5pY Con5pZ +Con6fX Con6fY Con6fZ Con6pX Con6pY Con6pZ +Con7fX Con7fY Con7fZ Con7pX Con7pY Con7pZ +Con8fX Con8fY Con8fZ Con8pX Con8pY Con8pZ +Con9pX Con9pY Con9pZ +Con10pX Con10pY Con10pZ +Con11pX Con11pY Con11pZ +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 L1N31pZ L1N32pZ L1N33pZ L1N34pZ L1N35pZ L1N36pZ L1N37pZ L1N38pZ L1N39pZ L1N40pZ +L3N1pZ L3N2pZ L3N3pZ L3N4pZ L3N5pZ L3N6pZ L3N7pZ L3N8pZ L3N9pZ L3N10pZ L3N11pZ L3N12pZ L3N13pZ L3N14pZ L3N15pZ L3N16pZ L3N17pZ L3N18pZ L3N19pZ L3N20pZ L3N21pZ L3N22pZ L3N23pZ L3N24pZ L3N25pZ L3N26pZ L3N27pZ L3N28pZ L3N29pZ L3N30pZ L3N31pZ L3N32pZ L3N33pZ L3N34pZ L3N35pZ L3N36pZ L3N37pZ L3N38pZ L3N39pZ L3N40pZ END ------------------------- need this line ------------------------------------ diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_SeaState.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_SeaState.dat index b85faeeaa..e59bb3746 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_SeaState.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_Floating_SeaState.dat @@ -14,7 +14,8 @@ False Echo - Echo the input file data (flag) 10 NZ – Number of nodes in the Z direction (-) [>=2] ---------------------- WAVES --------------------------------------------------- 1 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, 7: wave frequency components [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] + 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) + 0 WvCrntMod - Combined wave-current modeling option {0: simple superposition, 1: include Doppler effect, 2: include both Doppler effect and wave amplitude/spectrum scaling} (switch) [unused when WaveMod=0 or WaveMod=6. Also unused when there is no current from SeaState (CurrMod=0) or from InflowWind if MHK.] 600 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 or 7; 0.1<=WaveDT<=1.0 recommended; determines WaveOmegaMax=Pi/WaveDT in the IFFT] 2.0 WaveHs - Significant wave height of incident waves (meters) [used only when WaveMod=1, 2, or 3] @@ -23,7 +24,7 @@ False Echo - Echo the input file data (flag) 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, 6, or 7] 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, 6, or 7] 0 WaveDir - Incident wave propagation heading direction (degrees) [unused when WaveMod=0, 6 or 7] - 0 WaveDirMod - Directional spreading function {0: none, 1: COS2S} (-) [only used when WaveMod=2,3, or 4] + 0 WaveDirMod - Directional spreading function {0: none, 1: COS2S} (-) [only used when WaveMod=2,3, or 4; must be 0 if WvCrntMod/=0] 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] @@ -45,13 +46,13 @@ FALSE WvSumQTF - Full summation-frequency 2nd-order wave kinem 0 CrestXi - X-position of the crest (m) [unused when ConstWaveMod=0] 0 CrestYi - Y-position of the crest (m) [unused when ConstWaveMod=0] ---------------------- CURRENT ------------------------------------------------- [unused with WaveMod=6] - 1 CurrMod - Current profile model {0: none=no current, 1: standard, 2: user-defined from routine UserCurrent} (switch) + 0 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 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 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] ---------------------- MacCamy-Fuchs diffraction model ------------------------- 0 MCFD - MacCamy-Fuchs member radius (ignored if radius <= 0) [must be 0 when WaveMod 0 or 6] diff --git a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat index c41f6a555..b6ade3794 100644 --- a/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat +++ b/Examples/Test_Cases/MHK_RM1/MHK_RM1_ServoDyn.dat @@ -1,111 +1,120 @@ -------- 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) ---------------------------------------------------------------------------------------- +------- 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] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) + 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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] +"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/Examples/Test_Cases/NREL-5MW/DISCON.IN b/Examples/Test_Cases/NREL-5MW/DISCON.IN index 55446a809..0a74b9c94 100644 --- a/Examples/Test_Cases/NREL-5MW/DISCON.IN +++ b/Examples/Test_Cases/NREL-5MW/DISCON.IN @@ -1,5 +1,5 @@ ! Controller parameter input file for the NREL-5MW wind turbine -! - File written using ROSCO version 2.10.1 controller tuning logic on 11/26/25 +! - File written using ROSCO version 2.10.6 controller tuning logic on 06/09/26 !------- 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) diff --git a/Examples/Test_Cases/NREL-5MW/NREL-5MW.fst b/Examples/Test_Cases/NREL-5MW/NREL-5MW.fst index 0eda355ca..e3888aca3 100644 --- a/Examples/Test_Cases/NREL-5MW/NREL-5MW.fst +++ b/Examples/Test_Cases/NREL-5MW/NREL-5MW.fst @@ -1,73 +1,81 @@ -------- OpenFAST example INPUT FILE ------------------------------------------- -FAST Certification Test #18: NREL 5.0 MW Baseline Wind Turbine (Onshore) ----------------------- SIMULATION CONTROL -------------------------------------- -True Echo - Echo input data to .ech (flag) -"FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} - 60 TMax - Total run time (s) - 0.00625 DT - Recommended module time step (s) - 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} - 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} - 99999 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} - 0 CompSeaSt - Compute sea state information (switch) {0=None; 1=SeaState} - 0 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} - 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} - 0 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} - 0 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 WtrDens - Water density (kg/m^3) - 1.464E-05 KinVisc - Kinematic viscosity of working fluid (m^2/s) - 335 SpdSound - Speed of sound in working fluid (m/s) - 103500 Patm - Atmospheric pressure (Pa) [used only for an MHK turbine cavitation check] - 1700 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 --------------------------------------------- -"NRELOffshrBsline5MW_Onshore_ElastoDyn.dat" EDFile - Name of file containing ElastoDyn input parameters (quoted string) -"NRELOffshrBsline5MW_BeamDyn.dat" BDBldFile(1) - Name of file containing BeamDyn input parameters for blade 1 (quoted string) -"NRELOffshrBsline5MW_BeamDyn.dat" BDBldFile(2) - Name of file containing BeamDyn input parameters for blade 2 (quoted string) -"NRELOffshrBsline5MW_BeamDyn.dat" BDBldFile(3) - Name of file containing BeamDyn input parameters for blade 3 (quoted string) -"NRELOffshrBsline5MW_InflowWind.dat" InflowFile - Name of file containing inflow wind input parameters (quoted string) -"NRELOffshrBsline5MW_Onshore_AeroDyn15.dat" AeroFile - Name of file containing aerodynamic input parameters (quoted string) -"NRELOffshrBsline5MW_Onshore_ServoDyn.dat" ServoFile - Name of file containing control and electrical-drive input parameters (quoted string) -"unused" SeaStFile - Name of file containing sea state input parameters (quoted string) -"unused" HydroFile - Name of file containing hydrodynamic input parameters (quoted string) -"unused" SubFile - Name of file containing sub-structural input parameters (quoted string) -"unused" 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) - 0 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) - 3 TrimCase - Controller parameter to be trimmed {1:yaw; 2:torque; 3:pitch} [used only if CalcSteady=True] (-) - 0.001 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)) - 2 NLinTimes - Number of times to linearize (-) [>=1] [unused if Linearize=False] - 30, 60 LinTimes - List of times at which to linearize (s) [1 to NLinTimes] [used only when Linearize=True and CalcSteady=False] - 1 LinInputs - Inputs included in linearization (switch) {0=none; 1=standard; 2=all module inputs (debug)} [unused if Linearize=False] - 1 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] -true VTK_fields - Write mesh fields to VTK data files? (flag) {true/false} [unused if WrVTK=0] - 15 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] +------- OpenFAST example INPUT FILE ------------------------------------------- +FAST Certification Test #18: NREL 5.0 MW Baseline Wind Turbine (Onshore) +---------------------- SIMULATION CONTROL -------------------------------------- +True Echo - Echo input data to .ech (flag) +"FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} + 60 TMax - Total run time (s) + 0.00625 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} + 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} + 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) + 99999 DT_UJac - Time between calls to get Jacobians (s) + 1E+06 UJacSclFact - Scaling factor used in Jacobians (-) +---------------------- FEATURE SWITCHES AND FLAGS ------------------------------ + 1 NRotors - Number of rotors in turbine (-) + 1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} + 1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} + 2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} + 1 CompServo - Compute control and electrical-drive dynamics (switch) {0=None; 1=ServoDyn} + 0 CompSeaSt - Compute sea state information (switch) {0=None; 1=SeaState} + 0 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} + 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} + 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} + 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} +---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- + 9.80665 Gravity - Gravitational acceleration (m/s^2) + 1.225 AirDens - Air density (kg/m^3) + 1025 WtrDens - Water density (kg/m^3) + 1.464E-05 KinVisc - Kinematic viscosity of working fluid (m^2/s) + 335 SpdSound - Speed of sound in working fluid (m/s) + 103500 Patm - Atmospheric pressure (Pa) [used only for an MHK turbine cavitation check] + 1700 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 --------------------------------------------- +"NRELOffshrBsline5MW_Onshore_ElastoDyn.dat" EDFile - Name of file containing ElastoDyn input parameters (quoted string) +"NRELOffshrBsline5MW_BeamDyn.dat" BDBldFile(1) - Name of file containing BeamDyn input parameters for blade 1 (quoted string) +"NRELOffshrBsline5MW_BeamDyn.dat" BDBldFile(2) - Name of file containing BeamDyn input parameters for blade 2 (quoted string) +"NRELOffshrBsline5MW_BeamDyn.dat" BDBldFile(3) - Name of file containing BeamDyn input parameters for blade 3 (quoted string) +"NRELOffshrBsline5MW_InflowWind.dat" InflowFile - Name of file containing inflow wind input parameters (quoted string) +"NRELOffshrBsline5MW_Onshore_AeroDyn15.dat" AeroFile - Name of file containing aerodynamic input parameters (quoted string) +"NRELOffshrBsline5MW_Onshore_ServoDyn.dat" ServoFile - Name of file containing control and electrical-drive input parameters (quoted string) +"unused" SeaStFile - Name of file containing sea state input parameters (quoted string) +"unused" HydroFile - Name of file containing hydrodynamic input parameters (quoted string) +"unused" SubFile - Name of file containing sub-structural input parameters (quoted string) +"unused" MooringFile - Name of file containing mooring system input parameters (quoted string) +"unused" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn 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) + 0 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} +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) + 3 TrimCase - Controller parameter to be trimmed {1:yaw; 2:torque; 3:pitch} [used only if CalcSteady=True] (-) + 0.001 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)) + 2 NLinTimes - Number of times to linearize (-) [>=1] [unused if Linearize=False] + 30, 60 LinTimes - List of times at which to linearize (s) [1 to NLinTimes] [used only when Linearize=True and CalcSteady=False] + 1 LinInputs - Inputs included in linearization (switch) {0=none; 1=standard; 2=all module inputs (debug)} [unused if Linearize=False] + 1 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] +true VTK_fields - Write mesh fields to VTK data files? (flag) {true/false} [unused if WrVTK=0] + 15 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/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat index a8d17522c..cf0a60830 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_AeroDyn_blade.dat @@ -2,27 +2,27 @@ NREL 5.0 MW offshore baseline aerodynamic blade input properties; note that we need to add the aerodynamic center to this file ====== Blade Properties ================================================================= 19 NumBlNds - Number of blade nodes used in the analysis (-) - BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID - (m) (m) (m) (deg) (deg) (m) (-) -0.0000000E+00 0.0000000E+00 0.0000000E+00 0.0000000E+00 1.3308000E+01 3.5420000E+00 1 -1.3667000E+00 -8.1531745E-04 -3.4468858E-03 0.0000000E+00 1.3308000E+01 3.5420000E+00 1 -4.1000000E+00 -2.4839790E-02 -1.0501421E-01 0.0000000E+00 1.3308000E+01 3.8540000E+00 1 -6.8333000E+00 -5.9469375E-02 -2.5141635E-01 0.0000000E+00 1.3308000E+01 4.1670000E+00 2 -1.0250000E+01 -1.0909141E-01 -4.6120149E-01 0.0000000E+00 1.3308000E+01 4.5570000E+00 3 -1.4350000E+01 -1.1573354E-01 -5.6986665E-01 0.0000000E+00 1.1480000E+01 4.6520000E+00 4 -1.8450000E+01 -9.8316709E-02 -5.4850833E-01 0.0000000E+00 1.0162000E+01 4.4580000E+00 4 -2.2550000E+01 -8.3186967E-02 -5.2457001E-01 0.0000000E+00 9.0110000E+00 4.2490000E+00 5 -2.6650000E+01 -6.7933232E-02 -4.9624675E-01 0.0000000E+00 7.7950000E+00 4.0070000E+00 6 -3.0750000E+01 -5.3393159E-02 -4.6544755E-01 0.0000000E+00 6.5440000E+00 3.7480000E+00 6 -3.4850000E+01 -4.0899260E-02 -4.3583519E-01 0.0000000E+00 5.3610000E+00 3.5020000E+00 7 -3.8950000E+01 -2.9722933E-02 -4.0591323E-01 0.0000000E+00 4.1880000E+00 3.2560000E+00 7 -4.3050000E+01 -2.0511081E-02 -3.7569051E-01 0.0000000E+00 3.1250000E+00 3.0100000E+00 8 -4.7150000E+01 -1.3980013E-02 -3.4521705E-01 0.0000000E+00 2.3190000E+00 2.7640000E+00 8 -5.1250000E+01 -8.3819737E-03 -3.1463837E-01 0.0000000E+00 1.5260000E+00 2.5180000E+00 8 -5.4666700E+01 -4.3546914E-03 -2.8909220E-01 0.0000000E+00 8.6300000E-01 2.3130000E+00 8 -5.7400000E+01 -1.6838383E-03 -2.6074456E-01 0.0000000E+00 3.7000000E-01 2.0860000E+00 8 -6.0133300E+01 -3.2815226E-04 -1.7737470E-01 0.0000000E+00 1.0600000E-01 1.4190000E+00 8 -6.1499900E+01 -3.2815226E-04 -1.7737470E-01 0.0000000E+00 1.0600000E-01 1.4190000E+00 8 + BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID t_c BlCb BlCenBn BlCenBt BlCpn BlCpt BlCan BlCat BlCam + (m) (m) (m) (deg) (deg) (m) (-) (-) (-) (m) (m) (-) (-) (-) (-) (-) +0.0000000E+00 0.0000000E+00 0.0000000E+00 0.0000000E+00 1.3308000E+01 3.5420000E+00 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +1.3667000E+00 -8.1531745E-04 -3.4468858E-03 0.0000000E+00 1.3308000E+01 3.5420000E+00 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +4.1000000E+00 -2.4839790E-02 -1.0501421E-01 0.0000000E+00 1.3308000E+01 3.8540000E+00 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +6.8333000E+00 -5.9469375E-02 -2.5141635E-01 0.0000000E+00 1.3308000E+01 4.1670000E+00 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +1.0250000E+01 -1.0909141E-01 -4.6120149E-01 0.0000000E+00 1.3308000E+01 4.5570000E+00 3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +1.4350000E+01 -1.1573354E-01 -5.6986665E-01 0.0000000E+00 1.1480000E+01 4.6520000E+00 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +1.8450000E+01 -9.8316709E-02 -5.4850833E-01 0.0000000E+00 1.0162000E+01 4.4580000E+00 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +2.2550000E+01 -8.3186967E-02 -5.2457001E-01 0.0000000E+00 9.0110000E+00 4.2490000E+00 5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +2.6650000E+01 -6.7933232E-02 -4.9624675E-01 0.0000000E+00 7.7950000E+00 4.0070000E+00 6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +3.0750000E+01 -5.3393159E-02 -4.6544755E-01 0.0000000E+00 6.5440000E+00 3.7480000E+00 6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +3.4850000E+01 -4.0899260E-02 -4.3583519E-01 0.0000000E+00 5.3610000E+00 3.5020000E+00 7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +3.8950000E+01 -2.9722933E-02 -4.0591323E-01 0.0000000E+00 4.1880000E+00 3.2560000E+00 7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +4.3050000E+01 -2.0511081E-02 -3.7569051E-01 0.0000000E+00 3.1250000E+00 3.0100000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +4.7150000E+01 -1.3980013E-02 -3.4521705E-01 0.0000000E+00 2.3190000E+00 2.7640000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +5.1250000E+01 -8.3819737E-03 -3.1463837E-01 0.0000000E+00 1.5260000E+00 2.5180000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +5.4666700E+01 -4.3546914E-03 -2.8909220E-01 0.0000000E+00 8.6300000E-01 2.3130000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +5.7400000E+01 -1.6838383E-03 -2.6074456E-01 0.0000000E+00 3.7000000E-01 2.0860000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +6.0133300E+01 -3.2815226E-04 -1.7737470E-01 0.0000000E+00 1.0600000E-01 1.4190000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 +6.1499900E+01 -3.2815226E-04 -1.7737470E-01 0.0000000E+00 1.0600000E-01 1.4190000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 !bjj: because of precision in the BD-AD coupling, 61.5m didn't work, so I changed it to 61.4999m -6.1500000E+01 -3.2815226E-04 -1.7737470E-01 0.0000000E+00 1.0600000E-01 1.4190000E+00 8 +6.1500000E+01 -3.2815226E-04 -1.7737470E-01 0.0000000E+00 1.0600000E-01 1.4190000E+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 diff --git a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat index 55db767f3..7c3304ed6 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn.dat @@ -75,11 +75,6 @@ True RotStates - Orient states in the rotating frame during line 5 order_elem - Order of interpolation (basis) function (-) ---------------------- MATERIAL PARAMETER -------------------------------------- "NRELOffshrBsline5MW_BeamDyn_Blade.dat" BldFile - Name of file containing properties for blade (quoted string) ----------------------- PITCH ACTUATOR PARAMETERS ------------------------------- -False UsePitchAct - Whether a pitch actuator should be used (flag) - 200 PitchJ - Pitch actuator inertia (kg-m^2) [used only when UsePitchAct is true] - 2E+07 PitchK - Pitch actuator stiffness (kg-m^2/s^2) [used only when UsePitchAct is true] - 500000 PitchC - Pitch actuator damping (kg-m^2/s) [used only when UsePitchAct is true] ---------------------- OUTPUTS ------------------------------------------------- True SumPrint - Print summary data to ".sum" (flag) "ES10.3E2" OutFmt - Format used for text tabular output, excluding the time channel. diff --git a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat index ee1f89bd6..c7fb7d737 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_BeamDyn_Blade.dat @@ -1,13 +1,16 @@ ------- BEAMDYN V1.00.* INDIVIDUAL BLADE INPUT FILE -------------------------- Test Format 1 - ---------------------- BLADE PARAMETERS -------------------------------------- -49 station_total - Number of blade input stations (-) - 1 damp_type - Damping type: 0: no damping; 1: damped - ---------------------- DAMPING COEFFICIENT------------------------------------ +------ Blade Parameters -------------------------------------------------------- +49 station_total - Number of blade input stations (-) +1 damp_type - Damping type (switch) {0: none, 1: stiffness-proportional, 2: modal} +------ Stiffness-Proportional Damping [used only if damp_type=1] --------------- mu1 mu2 mu3 mu4 mu5 mu6 (-) (-) (-) (-) (-) (-) 1.0E-03 1.0E-03 1.0E-03 0.0014 0.0022 0.0022 - ---------------------- DISTRIBUTED PROPERTIES--------------------------------- +------ Modal Damping [used only if damp_type=2] -------------------------------- +4 n_modes - Number of modal damping coefficients (-) +0.01 0.02 0.03 0.04 zeta - Damping coefficients for mode 1 through n_modes +------ Distributed Properties -------------------------------------------------- 0.000000 9.729480E+08 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 9.729480E+08 0.000000E+00 0.000000E+00 0.000000E+00 0.000000E+00 diff --git a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat index 4ceba92c3..333e4694c 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Blade.dat @@ -12,57 +12,57 @@ NREL 5.0 MW offshore baseline blade input properties. 1 AdjFlSt - Factor to adjust blade flap stiffness (-) 1 AdjEdSt - Factor to adjust blade edge stiffness (-) ---------------------- DISTRIBUTED BLADE PROPERTIES ---------------------------- - BlFract PitchAxis StrcTwst BMassDen FlpStff EdgStff - (-) (-) (deg) (kg/m) (Nm^2) (Nm^2) -0.0000000E+00 2.5000000E-01 1.3308000E+01 6.7893500E+02 1.8110000E+10 1.8113600E+10 -3.2500000E-03 2.5000000E-01 1.3308000E+01 6.7893500E+02 1.8110000E+10 1.8113600E+10 -1.9510000E-02 2.5049000E-01 1.3308000E+01 7.7336300E+02 1.9424900E+10 1.9558600E+10 -3.5770000E-02 2.5490000E-01 1.3308000E+01 7.4055000E+02 1.7455900E+10 1.9497800E+10 -5.2030000E-02 2.6716000E-01 1.3308000E+01 7.4004200E+02 1.5287400E+10 1.9788800E+10 -6.8290000E-02 2.7941000E-01 1.3308000E+01 5.9249600E+02 1.0782400E+10 1.4858500E+10 -8.4550000E-02 2.9167000E-01 1.3308000E+01 4.5027500E+02 7.2297200E+09 1.0220600E+10 -1.0081000E-01 3.0392000E-01 1.3308000E+01 4.2405400E+02 6.3095400E+09 9.1447000E+09 -1.1707000E-01 3.1618000E-01 1.3308000E+01 4.0063800E+02 5.5283600E+09 8.0631600E+09 -1.3335000E-01 3.2844000E-01 1.3308000E+01 3.8206200E+02 4.9800600E+09 6.8844400E+09 -1.4959000E-01 3.4069000E-01 1.3308000E+01 3.9965500E+02 4.9368400E+09 7.0091800E+09 -1.6585000E-01 3.5294000E-01 1.3308000E+01 4.2632100E+02 4.6916600E+09 7.1676800E+09 -1.8211000E-01 3.6519000E-01 1.3181000E+01 4.1682000E+02 3.9494600E+09 7.2716600E+09 -1.9837000E-01 3.7500000E-01 1.2848000E+01 4.0618600E+02 3.3865200E+09 7.0817000E+09 -2.1465000E-01 3.7500000E-01 1.2192000E+01 3.8142000E+02 2.9337400E+09 6.2445300E+09 -2.3089000E-01 3.7500000E-01 1.1561000E+01 3.5282200E+02 2.5689600E+09 5.0489600E+09 -2.4715000E-01 3.7500000E-01 1.1072000E+01 3.4947700E+02 2.3886500E+09 4.9484900E+09 -2.6341000E-01 3.7500000E-01 1.0792000E+01 3.4653800E+02 2.2719900E+09 4.8080200E+09 -2.9595000E-01 3.7500000E-01 1.0232000E+01 3.3933300E+02 2.0500500E+09 4.5014000E+09 -3.2846000E-01 3.7500000E-01 9.6720000E+00 3.3000400E+02 1.8282500E+09 4.2440700E+09 -3.6098000E-01 3.7500000E-01 9.1100000E+00 3.2199000E+02 1.5887100E+09 3.9952800E+09 -3.9350000E-01 3.7500000E-01 8.5340000E+00 3.1382000E+02 1.3619300E+09 3.7507600E+09 -4.2602000E-01 3.7500000E-01 7.9320000E+00 2.9473400E+02 1.1023800E+09 3.4471400E+09 -4.5855000E-01 3.7500000E-01 7.3210000E+00 2.8712000E+02 8.7580000E+08 3.1390700E+09 -4.9106000E-01 3.7500000E-01 6.7110000E+00 2.6334300E+02 6.8130000E+08 2.7342400E+09 -5.2358000E-01 3.7500000E-01 6.1220000E+00 2.5320700E+02 5.3472000E+08 2.5548700E+09 -5.5610000E-01 3.7500000E-01 5.5460000E+00 2.4166600E+02 4.0890000E+08 2.3340300E+09 -5.8862000E-01 3.7500000E-01 4.9710000E+00 2.2063800E+02 3.1454000E+08 1.8287300E+09 -6.2115000E-01 3.7500000E-01 4.4010000E+00 2.0029300E+02 2.3863000E+08 1.5841000E+09 -6.5366000E-01 3.7500000E-01 3.8340000E+00 1.7940400E+02 1.7588000E+08 1.3233600E+09 -6.8618000E-01 3.7500000E-01 3.3320000E+00 1.6509400E+02 1.2601000E+08 1.1836800E+09 -7.1870000E-01 3.7500000E-01 2.8900000E+00 1.5441100E+02 1.0726000E+08 1.0201600E+09 -7.5122000E-01 3.7500000E-01 2.5030000E+00 1.3893500E+02 9.0880000E+07 7.9781000E+08 -7.8376000E-01 3.7500000E-01 2.1160000E+00 1.2955500E+02 7.6310000E+07 7.0961000E+08 -8.1626000E-01 3.7500000E-01 1.7300000E+00 1.0726400E+02 6.1050000E+07 5.1819000E+08 -8.4878000E-01 3.7500000E-01 1.3420000E+00 9.8776000E+01 4.9480000E+07 4.5487000E+08 -8.8130000E-01 3.7500000E-01 9.5400000E-01 9.0248000E+01 3.9360000E+07 3.9512000E+08 -8.9756000E-01 3.7500000E-01 7.6000000E-01 8.3001000E+01 3.4670000E+07 3.5372000E+08 -9.1382000E-01 3.7500000E-01 5.7400000E-01 7.2906000E+01 3.0410000E+07 3.0473000E+08 -9.3008000E-01 3.7500000E-01 4.0400000E-01 6.8772000E+01 2.6520000E+07 2.8142000E+08 -9.3821000E-01 3.7500000E-01 3.1900000E-01 6.6264000E+01 2.3840000E+07 2.6171000E+08 -9.4636000E-01 3.7500000E-01 2.5300000E-01 5.9340000E+01 1.9630000E+07 1.5881000E+08 -9.5447000E-01 3.7500000E-01 2.1600000E-01 5.5914000E+01 1.6000000E+07 1.3788000E+08 -9.6260000E-01 3.7500000E-01 1.7800000E-01 5.2484000E+01 1.2830000E+07 1.1879000E+08 -9.7073000E-01 3.7500000E-01 1.4000000E-01 4.9114000E+01 1.0080000E+07 1.0163000E+08 -9.7886000E-01 3.7500000E-01 1.0100000E-01 4.5818000E+01 7.5500000E+06 8.5070000E+07 -9.8699000E-01 3.7500000E-01 6.2000000E-02 4.1669000E+01 4.6000000E+06 6.4260000E+07 -9.9512000E-01 3.7500000E-01 2.3000000E-02 1.1453000E+01 2.5000000E+05 6.6100000E+06 -1.0000000E+00 3.7500000E-01 0.0000000E+00 1.0319000E+01 1.7000000E+05 5.0100000E+06 + BlFract StrcTwst BMassDen FlpStff EdgStff + (-) (deg) (kg/m) (Nm^2) (Nm^2) + 0.000000000000000E+00 1.330800000000000E+01 6.789349999999999E+02 1.811000000000000E+10 1.811360000000000E+10 + 3.250000000000000E-03 1.330800000000000E+01 6.789349999999999E+02 1.811000000000000E+10 1.811360000000000E+10 + 1.951000000000000E-02 1.330800000000000E+01 7.733630000000001E+02 1.942490000000000E+10 1.955860000000000E+10 + 3.577000000000000E-02 1.330800000000000E+01 7.405500000000000E+02 1.745590000000000E+10 1.949780000000000E+10 + 5.203000000000000E-02 1.330800000000000E+01 7.400420000000000E+02 1.528740000000000E+10 1.978880000000000E+10 + 6.829000000000000E-02 1.330800000000000E+01 5.924960000000000E+02 1.078240000000000E+10 1.485850000000000E+10 + 8.455000000000000E-02 1.330800000000000E+01 4.502750000000000E+02 7.229720000000000E+09 1.022060000000000E+10 + 1.008100000000000E-01 1.330800000000000E+01 4.240540000000000E+02 6.309540000000000E+09 9.144700000000000E+09 + 1.170700000000000E-01 1.330800000000000E+01 4.006380000000000E+02 5.528360000000000E+09 8.063160000000000E+09 + 1.333500000000000E-01 1.330800000000000E+01 3.820620000000000E+02 4.980060000000000E+09 6.884440000000000E+09 + 1.495900000000000E-01 1.330800000000000E+01 3.996550000000000E+02 4.936840000000000E+09 7.009180000000000E+09 + 1.658500000000000E-01 1.330800000000000E+01 4.263210000000000E+02 4.691660000000000E+09 7.167680000000000E+09 + 1.821100000000000E-01 1.318100000000000E+01 4.168200000000000E+02 3.949460000000000E+09 7.271660000000000E+09 + 1.983700000000000E-01 1.284800000000000E+01 4.061860000000000E+02 3.386520000000000E+09 7.081700000000000E+09 + 2.146500000000000E-01 1.219200000000000E+01 3.814200000000000E+02 2.933740000000000E+09 6.244530000000000E+09 + 2.308900000000000E-01 1.156100000000000E+01 3.528220000000000E+02 2.568960000000000E+09 5.048960000000000E+09 + 2.471500000000000E-01 1.107200000000000E+01 3.494770000000000E+02 2.388650000000000E+09 4.948490000000000E+09 + 2.634100000000000E-01 1.079200000000000E+01 3.465380000000000E+02 2.271990000000000E+09 4.808020000000000E+09 + 2.959500000000000E-01 1.023200000000000E+01 3.393330000000000E+02 2.050050000000000E+09 4.501400000000000E+09 + 3.284600000000000E-01 9.672000000000000E+00 3.300040000000000E+02 1.828250000000000E+09 4.244070000000000E+09 + 3.609800000000000E-01 9.110000000000000E+00 3.219900000000000E+02 1.588710000000000E+09 3.995280000000000E+09 + 3.935000000000000E-01 8.534000000000000E+00 3.138200000000000E+02 1.361930000000000E+09 3.750760000000000E+09 + 4.260200000000000E-01 7.932000000000000E+00 2.947340000000000E+02 1.102380000000000E+09 3.447140000000000E+09 + 4.585500000000000E-01 7.321000000000000E+00 2.871200000000000E+02 8.758000000000000E+08 3.139070000000000E+09 + 4.910600000000000E-01 6.711000000000000E+00 2.633430000000000E+02 6.813000000000000E+08 2.734240000000000E+09 + 5.235800000000000E-01 6.122000000000000E+00 2.532070000000000E+02 5.347200000000000E+08 2.554870000000000E+09 + 5.561000000000000E-01 5.546000000000000E+00 2.416660000000000E+02 4.089000000000000E+08 2.334030000000000E+09 + 5.886200000000000E-01 4.971000000000000E+00 2.206380000000000E+02 3.145400000000000E+08 1.828730000000000E+09 + 6.211500000000000E-01 4.401000000000000E+00 2.002930000000000E+02 2.386300000000000E+08 1.584100000000000E+09 + 6.536600000000000E-01 3.834000000000000E+00 1.794040000000000E+02 1.758800000000000E+08 1.323360000000000E+09 + 6.861800000000000E-01 3.332000000000000E+00 1.650940000000000E+02 1.260100000000000E+08 1.183680000000000E+09 + 7.187000000000000E-01 2.890000000000000E+00 1.544110000000000E+02 1.072600000000000E+08 1.020160000000000E+09 + 7.512200000000000E-01 2.503000000000000E+00 1.389350000000000E+02 9.088000000000000E+07 7.978100000000000E+08 + 7.837600000000000E-01 2.116000000000000E+00 1.295550000000000E+02 7.631000000000000E+07 7.096100000000000E+08 + 8.162600000000000E-01 1.730000000000000E+00 1.072640000000000E+02 6.105000000000000E+07 5.181900000000000E+08 + 8.487800000000000E-01 1.342000000000000E+00 9.877600000000000E+01 4.948000000000000E+07 4.548700000000000E+08 + 8.813000000000000E-01 9.540000000000000E-01 9.024800000000000E+01 3.936000000000000E+07 3.951200000000000E+08 + 8.975600000000000E-01 7.600000000000000E-01 8.300100000000000E+01 3.467000000000000E+07 3.537200000000000E+08 + 9.138200000000000E-01 5.740000000000000E-01 7.290600000000000E+01 3.041000000000000E+07 3.047300000000000E+08 + 9.300800000000000E-01 4.040000000000000E-01 6.877200000000000E+01 2.652000000000000E+07 2.814200000000000E+08 + 9.382100000000000E-01 3.190000000000000E-01 6.626400000000000E+01 2.384000000000000E+07 2.617100000000000E+08 + 9.463600000000000E-01 2.530000000000000E-01 5.934000000000000E+01 1.963000000000000E+07 1.588100000000000E+08 + 9.544700000000000E-01 2.160000000000000E-01 5.591400000000000E+01 1.600000000000000E+07 1.378800000000000E+08 + 9.626000000000000E-01 1.780000000000000E-01 5.248400000000000E+01 1.283000000000000E+07 1.187900000000000E+08 + 9.707300000000000E-01 1.400000000000000E-01 4.911400000000000E+01 1.008000000000000E+07 1.016300000000000E+08 + 9.788600000000000E-01 1.010000000000000E-01 4.581800000000000E+01 7.550000000000000E+06 8.507000000000000E+07 + 9.869900000000000E-01 6.200000000000000E-02 4.166900000000000E+01 4.600000000000000E+06 6.426000000000000E+07 + 9.951200000000000E-01 2.300000000000000E-02 1.145300000000000E+01 2.500000000000000E+05 6.610000000000000E+06 + 1.000000000000000E+00 0.000000000000000E+00 1.031900000000000E+01 1.700000000000000E+05 5.010000000000000E+06 ---------------------- BLADE MODE SHAPES --------------------------------------- 0.0622 BldFl1Sh(2) - Flap mode 1, coeff of x^2 1.7254 BldFl1Sh(3) - , coeff of x^3 diff --git a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat index ebbbdc08f..f1b3579b4 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_AeroDyn15.dat @@ -1,123 +1,122 @@ -------- AERODYN v15 for OpenFAST INPUT FILE ----------------------------------------------- -NREL 5.0 MW offshore baseline aerodynamic input properties. -====== General Options ============================================================================ -False Echo - Echo the input to ".AD.ech"? (flag) -"default" DTAero - Time interval for aerodynamic calculations {or "default"} (s) - 1 Wake_Mod - Type of wake/induction model (switch) {0=none, 1=BEMT, 2=DBEMT, 3=OLAF} [WakeMod cannot be 2 or 3 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? (flag) -True TwrAero - Calculate tower aerodynamic loads? (flag) -False CavitCheck - Perform cavitation check? (flag) [AFAeroMod must be 1 when CavitCheck=true] -False Buoyancy - Include buoyancy effects? (flag) -False NacelleDrag - Include Nacelle Drag effects? (flag) -False CompAA - Flag to compute AeroAcoustics calculation [only used when WakeMod=1 or 2] -"unused" AA_InputFile - Aeroacoustics input file -====== Environmental Conditions =================================================================== - 1.225 AirDens - Air density (kg/m^3) - 1.464E-05 KinVisc - Kinematic air viscosity (m^2/s) - 335 SpdSound - Speed of sound (m/s) - 103500 Patm - Atmospheric pressure (Pa) [used only when CavitCheck=True] - 1700 Pvap - Vapour pressure of fluid (Pa) [used only when CavitCheck=True] -====== Blade-Element/Momentum Theory Options ====================================================== [unused when Wake_Mod=0 or 3, except for BEM_Mod] -1 BEM_Mod - BEM model {1=legacy NoSweepPitchTwist, 2=polar} (switch) [used for all Wake_Mod to determine output coordinate system] ---- Skew correction -1 Skew_Mod - Skew model {0=No skew model, -1=Remove non-normal component for linearization, 1=skew model active} -False SkewMomCorr - Turn the skew momentum correction on or off [used only when Skew_Mod=1] -default SkewRedistr_Mod - Type of skewed-wake correction model (switch) {0=no redistribution, 1=Glauert/Pitt/Peters, default=1} [used only when Skew_Mod=1] -"default" SkewRedistrFactor - Constant used in Pitt/Peters skewed wake model {or "default" is 15/32*pi} (-) [used only when Skew_Mod=1 and SkewRedistr_Mod=1] ---- BEM algorithm -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] -False AIDrag - Include the drag term in the axial-induction calculation? (flag) [unused when WakeMod=0 or 3] -False 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] - 100 MaxIter - Maximum number of iteration steps (-) [unused when WakeMod=0] ---- Shear correction -False SectAvg - Use sector averaging (flag) -1 SectAvgWeighting - Weighting function for sector average {1=Uniform, default=1} within a sector centered on the blade (switch) [used only when SectAvg=True] -default SectAvgNPoints - Number of points per sectors (-) {default=5} [used only when SectAvg=True] -default SectAvgPsiBwd - Backward azimuth relative to blade where the sector starts (<=0) {default=-60} (deg) [used only when SectAvg=True] -default SectAvgPsiFwd - Forward azimuth relative to blade where the sector ends (>=0) {default=60} (deg) [used only when SectAvg=True] ---- Dynamic wake/inflow - 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 Wake_Mod=3] -"unused" OLAFInputFileName - Input file for OLAF [used only when WakeMod=3] -====== Unsteady Airfoil Aerodynamics Options ==================================================== -True AoA34 - Sample the angle of attack (AoA) at the 3/4 chord or the AC point {default=True} [always used] -3 UA_Mod - Unsteady Aero Model Switch (switch) {0=Quasi-steady (no UA), 2=B-L Gonzalez, 3=B-L Minnema/Pierce, 4=B-L HGM 4-states, 5=B-L HGM+vortex 5 states, 6=Oye, 7=Boeing-Vertol} -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 UA_Mod>0] -3 IntegrationMethod - Switch to indicate which integration method UA uses (1=RK4, 2=AB4, 3=ABM4, 4=BDF2) -0 UAStartRad - Starting radius for dynamic stall (fraction of rotor radius [0.0,1.0]) [used only when UA_Mod>0; if line is missing UAStartRad=0] -1 UAEndRad - Ending radius for dynamic stall (fraction of rotor radius [0.0,1.0]) [used only when UA_Mod>0; if line is missing UAEndRad=1] -====== Airfoil Information ========================================================================= - 1 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 (-) - 4 InCol_Cm - The column in the airfoil tables that contains the pitching-moment coefficient; use zero if there is no Cm column (-) - 0 InCol_Cpmin - The column in the airfoil tables that contains the Cpmin coefficient; use zero if there is no Cpmin column (-) - 8 NumAFfiles - Number of airfoil files used (-) -"Airfoils/Cylinder1.dat" AFNames - Airfoil file names (NumAFfiles lines) (quoted strings) -"Airfoils/Cylinder2.dat" -"Airfoils/DU40_A17.dat" -"Airfoils/DU35_A17.dat" -"Airfoils/DU30_A17.dat" -"Airfoils/DU25_A17.dat" -"Airfoils/DU21_A17.dat" -"Airfoils/NACA64_A17.dat" -====== Rotor/Blade Properties ===================================================================== -True UseBlCm - Include aerodynamic pitching moment in calculations? (flag) -"NRELOffshrBsline5MW_AeroDyn_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) -"NRELOffshrBsline5MW_AeroDyn_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] -"NRELOffshrBsline5MW_AeroDyn_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] -====== Hub Properties ============================================================================== [used only when Buoyancy=True] -0.0 VolHub - Hub volume (m^3) -0.0 HubCenBx - Hub center of buoyancy x direction offset (m) -====== Nacelle Properties ========================================================================== [used only when Buoyancy=True or NacelleDrag=True] -0 VolNac - Nacelle volume (m^3) -0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) -0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) -0, 0, 0 NacCd - Drag coefficient for the nacelle areas defined above (-) -0, 0, 0 NacDragAC - Position of aerodynamic center of nacelle drag 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=True, or TwrAero=True] - 12 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow=True, or TwrAero=True] -TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True -(m) (m) (-) (-) (-) -0.0000000E+00 6.0000000E+00 1.0000000E+00 1.000000E-01 0.0 -8.5261000E+00 5.7870000E+00 1.0000000E+00 1.000000E-01 0.0 -1.7053000E+01 5.5740000E+00 1.0000000E+00 1.000000E-01 0.0 -2.5579000E+01 5.3610000E+00 1.0000000E+00 1.000000E-01 0.0 -3.4105000E+01 5.1480000E+00 1.0000000E+00 1.000000E-01 0.0 -4.2633000E+01 4.9350000E+00 1.0000000E+00 1.000000E-01 0.0 -5.1158000E+01 4.7220000E+00 1.0000000E+00 1.000000E-01 0.0 -5.9685000E+01 4.5090000E+00 1.0000000E+00 1.000000E-01 0.0 -6.8211000E+01 4.2960000E+00 1.0000000E+00 1.000000E-01 0.0 -7.6738000E+01 4.0830000E+00 1.0000000E+00 1.000000E-01 0.0 -8.5268000E+01 3.8700000E+00 1.0000000E+00 1.000000E-01 0.0 -8.7600000E+01 3.8700000E+00 1.0000000E+00 1.000000E-01 0.0 -====== Outputs ==================================================================================== -True SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) - 0 NBlOuts - Number of blade node outputs [0 - 9] (-) - 1, 9, 19 BlOutNd - Blade nodes whose values will be output (-) - 0 NTwOuts - Number of tower node outputs [0 - 9] (-) - 1, 2, 6 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, (-) -"RtFldFxh" -"RtFldFyh" -"RtFldFzh" -"RtFldMxh" -"RtFldMyh" -"RtFldMzh" -"RtVAvgxh" -"RtFldCp" -"RtFldCt" -"RtArea" -"RtSpeed" -"RtTSR" -END of input file (the word "END" must appear in the first 3 columns of this last OutList line) ---------------------------------------------------------------------------------------- +------- AERODYN v15 for OpenFAST INPUT FILE ----------------------------------------------- +NREL 5.0 MW offshore baseline aerodynamic input properties. +====== General Options ============================================================================ +False Echo - Echo the input to ".AD.ech"? (flag) +"default" DTAero - Time interval for aerodynamic calculations {or "default"} (s) + 1 Wake_Mod - Type of wake/induction model (switch) {0=none, 1=BEMT, 2=DBEMT, 3=OLAF} [WakeMod cannot be 2 or 3 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? (flag) +True TwrAero - Calculate tower aerodynamic loads? (flag) +False CavitCheck - Perform cavitation check? (flag) [AFAeroMod must be 1 when CavitCheck=true] +False NacelleDrag - Include Nacelle Drag effects? (flag) +False CompAA - Flag to compute AeroAcoustics calculation [only used when WakeMod=1 or 2] +"unused" AA_InputFile - Aeroacoustics input file +====== Environmental Conditions =================================================================== + 1.225 AirDens - Air density (kg/m^3) + 1.464E-05 KinVisc - Kinematic air viscosity (m^2/s) + 335 SpdSound - Speed of sound (m/s) + 103500 Patm - Atmospheric pressure (Pa) [used only when CavitCheck=True] + 1700 Pvap - Vapour pressure of fluid (Pa) [used only when CavitCheck=True] +====== Blade-Element/Momentum Theory Options ====================================================== [unused when Wake_Mod=0 or 3, except for BEM_Mod] +1 BEM_Mod - BEM model {1=legacy NoSweepPitchTwist, 2=polar} (switch) [used for all Wake_Mod to determine output coordinate system] +--- Skew correction +1 Skew_Mod - Skew model {0=No skew model, -1=Remove non-normal component for linearization, 1=skew model active} +False SkewMomCorr - Turn the skew momentum correction on or off [used only when Skew_Mod=1] +default SkewRedistr_Mod - Type of skewed-wake correction model (switch) {0=no redistribution, 1=Glauert/Pitt/Peters, default=1} [used only when Skew_Mod=1] +"default" SkewRedistrFactor - Constant used in Pitt/Peters skewed wake model {or "default" is 15/32*pi} (-) [used only when Skew_Mod=1 and SkewRedistr_Mod=1] +--- BEM algorithm +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] +False AIDrag - Include the drag term in the axial-induction calculation? (flag) [unused when WakeMod=0 or 3] +False 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] + 100 MaxIter - Maximum number of iteration steps (-) [unused when WakeMod=0] +--- Shear correction +False SectAvg - Use sector averaging (flag) +1 SectAvgWeighting - Weighting function for sector average {1=Uniform, default=1} within a sector centered on the blade (switch) [used only when SectAvg=True] +default SectAvgNPoints - Number of points per sectors (-) {default=5} [used only when SectAvg=True] +default SectAvgPsiBwd - Backward azimuth relative to blade where the sector starts (<=0) {default=-60} (deg) [used only when SectAvg=True] +default SectAvgPsiFwd - Forward azimuth relative to blade where the sector ends (>=0) {default=60} (deg) [used only when SectAvg=True] +--- Dynamic wake/inflow + 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 Wake_Mod=3] +"unused" OLAFInputFileName - Input file for OLAF [used only when WakeMod=3] +====== Unsteady Airfoil Aerodynamics Options ==================================================== +True AoA34 - Sample the angle of attack (AoA) at the 3/4 chord or the AC point {default=True} [always used] +3 UA_Mod - Unsteady Aero Model Switch (switch) {0=Quasi-steady (no UA), 2=B-L Gonzalez, 3=B-L Minnema/Pierce, 4=B-L HGM 4-states, 5=B-L HGM+vortex 5 states, 6=Oye, 7=Boeing-Vertol} +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 UA_Mod>0] +3 IntegrationMethod - Switch to indicate which integration method UA uses (1=RK4, 2=AB4, 3=ABM4, 4=BDF2) +0 UAStartRad - Starting radius for dynamic stall (fraction of rotor radius [0.0,1.0]) [used only when UA_Mod>0; if line is missing UAStartRad=0] +1 UAEndRad - Ending radius for dynamic stall (fraction of rotor radius [0.0,1.0]) [used only when UA_Mod>0; if line is missing UAEndRad=1] +====== Airfoil Information ========================================================================= + 1 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 (-) + 4 InCol_Cm - The column in the airfoil tables that contains the pitching-moment coefficient; use zero if there is no Cm column (-) + 0 InCol_Cpmin - The column in the airfoil tables that contains the Cpmin coefficient; use zero if there is no Cpmin column (-) + 8 NumAFfiles - Number of airfoil files used (-) +"Airfoils/Cylinder1.dat" AFNames - Airfoil file names (NumAFfiles lines) (quoted strings) +"Airfoils/Cylinder2.dat" +"Airfoils/DU40_A17.dat" +"Airfoils/DU35_A17.dat" +"Airfoils/DU30_A17.dat" +"Airfoils/DU25_A17.dat" +"Airfoils/DU21_A17.dat" +"Airfoils/NACA64_A17.dat" +====== Rotor/Blade Properties ===================================================================== +True UseBlCm - Include aerodynamic pitching moment in calculations? (flag) +"NRELOffshrBsline5MW_AeroDyn_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) +"NRELOffshrBsline5MW_AeroDyn_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] +"NRELOffshrBsline5MW_AeroDyn_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] +0.0 VolHub - Hub volume (m^3) +0.0 HubCenBx - Hub center of buoyancy x direction offset (m) +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] +0 VolNac - Nacelle volume (m^3) +0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) +0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) +0, 0, 0 NacCd - Drag coefficient for the nacelle areas defined above (-) +0, 0, 0 NacDragAC - Position of aerodynamic center of nacelle drag 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 MHK=1 or 2] + 12 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +0.0000000E+00 6.0000000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +8.5261000E+00 5.7870000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +1.7053000E+01 5.5740000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +2.5579000E+01 5.3610000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +3.4105000E+01 5.1480000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +4.2633000E+01 4.9350000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +5.1158000E+01 4.7220000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +5.9685000E+01 4.5090000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +6.8211000E+01 4.2960000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +7.6738000E+01 4.0830000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +8.5268000E+01 3.8700000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +8.7600000E+01 3.8700000E+00 1.0000000E+00 1.000000E-01 0.0 0.0000000E+00 0.0000000E+00 +====== Outputs ==================================================================================== +True SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) + 0 NBlOuts - Number of blade node outputs [0 - 9] (-) + 1, 9, 19 BlOutNd - Blade nodes whose values will be output (-) + 0 NTwOuts - Number of tower node outputs [0 - 9] (-) + 1, 2, 6 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, (-) +"RtFldFxh" +"RtFldFyh" +"RtFldFzh" +"RtFldMxh" +"RtFldMyh" +"RtFldMzh" +"RtVAvgxh" +"RtFldCp" +"RtFldCt" +"RtArea" +"RtSpeed" +"RtTSR" +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/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat index 58efa7f73..b18afff5d 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ElastoDyn.dat @@ -1,175 +1,184 @@ -------- ELASTODYN for OpenFAST 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) - 3 Method - Integration method: {1: RK4, 2: AB4, or 3: ABM4} (-) -"DEFAULT" DT - Integration time step (s) ----------------------- DEGREES OF FREEDOM -------------------------------------- -True FlapDOF1 - First flapwise blade mode DOF (flag) -True FlapDOF2 - Second flapwise blade mode DOF (flag) -True EdgeDOF - First edgewise blade mode DOF (flag) -False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] -True DrTrDOF - Drivetrain rotational-flexibility DOF (flag) -True GenDOF - Generator DOF (flag) -True YawDOF - Yaw DOF (flag) -True TwFADOF1 - First fore-aft tower bending-mode DOF (flag) -True TwFADOF2 - Second fore-aft tower bending-mode DOF (flag) -True TwSSDOF1 - First side-to-side tower bending-mode DOF (flag) -True TwSSDOF2 - Second side-to-side tower bending-mode DOF (flag) -False PtfmSgDOF - Platform horizontal surge translation DOF (flag) -False PtfmSwDOF - Platform horizontal sway translation DOF (flag) -False PtfmHvDOF - Platform vertical heave translation DOF (flag) -False PtfmRDOF - Platform roll tilt rotation DOF (flag) -False PtfmPDOF - Platform pitch tilt rotation DOF (flag) -False 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) - 0 BlPitch(1) - Blade 1 initial pitch (degrees) - 0 BlPitch(2) - Blade 2 initial pitch (degrees) - 0 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) - 12.1 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) - 0 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 ----------------------------------- - 3 NumBl - Number of blades (-) - 63 TipRad - The distance from the rotor apex to the blade tip (meters) - 1.5 HubRad - The distance from the rotor apex to the blade root (meters) - -2.5 PreCone(1) - Blade 1 cone angle (degrees) - -2.5 PreCone(2) - Blade 2 cone angle (degrees) - -2.5 PreCone(3) - Blade 3 cone angle (degrees) [unused for 2 blades] - 0 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) - -5.0191 OverHang - Distance from yaw axis to rotor apex [3 blades] or teeter pin [2 blades] (meters) - 1.912 ShftGagL - Distance from rotor apex [3 blades] or teeter pin [2 blades] to shaft strain gages [positive for upwind rotors] (meters) - -5 ShftTilt - Rotor shaft tilt angle (degrees) - 1.9 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) - 1.75 NacCMzn - Vertical distance from the tower-top to the nacelle CM (meters) - -3.09528 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) - 2.23336 NcIMUzn - Vertical distance from the tower-top to the nacelle IMU (meters) - 1.96256 Twr2Shft - Vertical distance from the tower-top to the rotor shaft (meters) - 87.6 TowerHt - Height of tower above ground level [onshore] or MSL [offshore] (meters) - 0 TowerBsHt - Height of tower base above ground level [onshore] or MSL [offshore] (meters) - 0 PtfmCMxt - Downwind distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) - 0 PtfmCMyt - Lateral distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) - 0 PtfmCMzt - Vertical distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) - 0 PtfmRefzt - Vertical distance from the ground level [onshore] or MSL [offshore] 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] - 56780 HubMass - Hub mass (kg) - 115926 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) - 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) - 534.116 GenIner - Generator inertia about HSS (kg m^2) - 240000 NacMass - Nacelle mass (kg) -2.60789E+06 NacYIner - Nacelle inertia about yaw axis (kg m^2) - 0 YawBrMass - Yaw bearing mass (kg) - 0 PtfmMass - Platform mass (kg) - 0 PtfmRIner - Platform inertia for roll tilt rotation about the platform CM (kg m^2) - 0 PtfmPIner - Platform inertia for pitch tilt rotation about the platform CM (kg m^2) - 0 PtfmYIner - Platform inertia for yaw rotation about the platform CM (kg m^2) - 0 PtfmXYIner - Platform xy moment of inertia about the platform CM (=-int(xydm)) (kg m^2) - 0 PtfmYZIner - Platform yz moment of inertia about the platform CM (=-int(yzdm)) (kg m^2) - 0 PtfmXZIner - Platform xz moment of inertia about the platform CM (=-int(xzdm)) (kg m^2) ----------------------- BLADE --------------------------------------------------- - 17 BldNodes - Number of blade nodes (per blade) used for analysis (-) -"NRELOffshrBsline5MW_Blade.dat" BldFile(1) - Name of file containing properties for blade 1 (quoted string) -"NRELOffshrBsline5MW_Blade.dat" BldFile(2) - Name of file containing properties for blade 2 (quoted string) -"NRELOffshrBsline5MW_Blade.dat" 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] ----------------------- YAW-FRICTION -------------------------------------------- - 0 YawFrctMod - Yaw-friction model {0: none, 1: friction independent of yaw-bearing force and bending moment, 2: friction with Coulomb terms depending on yaw-bearing force and bending moment, 3: user defined model} (switch) - 300 M_CSmax - Maximum static Coulomb friction torque (N-m) [M_CSmax when YawFrctMod=1; |Fz|*M_CSmax when YawFrctMod=2 and Fz<0] - 0 M_FCSmax - Maximum static Coulomb friction torque proportional to yaw bearing shear force (N-m) [sqrt(Fx^2+Fy^2)*M_FCSmax; only used when YawFrctMod=2] - 0 M_MCSmax - Maximum static Coulomb friction torque proportional to yaw bearing bending moment (N-m) [sqrt(Mx^2+My^2)*M_MCSmax; only used when YawFrctMod=2] - 40 M_CD - Dynamic Coulomb friction moment (N-m) [M_CD when YawFrctMod=1; |Fz|*M_CD when YawFrctMod=2 and Fz<0] - 0 M_FCD - Dynamic Coulomb friction moment proportional to yaw bearing shear force (N-m) [sqrt(Fx^2+Fy^2)*M_FCD; only used when YawFrctMod=2] - 0 M_MCD - Dynamic Coulomb friction moment proportional to yaw bearing bending moment (N-m) [sqrt(Mx^2+My^2)*M_MCD; only used when YawFrctMod=2] - 0 sig_v - Linear viscous friction coefficient (N-m/(rad/s)) - 0 sig_v2 - Quadratic viscous friction coefficient (N-m/(rad/s)^2) - 0 OmgCut - Yaw angular velocity cutoff below which viscous friction is linearized (rad/s) ----------------------- DRIVETRAIN ---------------------------------------------- - 100 GBoxEff - Gearbox efficiency (%) - 97 GBRatio - Gearbox ratio (-) -8.67637E+08 DTTorSpr - Drivetrain torsional spring (N-m/rad) - 6.215E+06 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 --------------------------------------------------- - 20 TwrNodes - Number of tower nodes used for analysis (-) -"NRELOffshrBsline5MW_Onshore_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] (-) - 10, 19, 28 TwrGagNd - List of tower nodes that have strain gages [1 to TwrNodes] (-) [unused if NTwGages=0] - 3 NBlGages - Number of blade nodes that have strain gages for output [0 to 9] (-) - 5, 9, 13 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, (-) -"OoPDefl1" - Blade 1 out-of-plane and in-plane deflections and tip twist -"IPDefl1" - Blade 1 out-of-plane and in-plane deflections and tip twist -"TwstDefl1" - Blade 1 out-of-plane and in-plane deflections and tip twist -"BldPitch1" - Blade 1 pitch angle -"Azimuth" - Blade 1 azimuth angle -"RotSpeed" - Low-speed shaft and high-speed shaft speeds -"GenSpeed" - Low-speed shaft and high-speed shaft speeds -"TTDspFA" - Tower fore-aft and side-to-side displacements and top twist -"TTDspSS" - Tower fore-aft and side-to-side displacements and top twist -"TTDspTwst" - Tower fore-aft and side-to-side displacements and top twist -"Spn2MLxb1" - Blade 1 local edgewise and flapwise bending moments at span station 2 (approx. 50% span) -"Spn2MLyb1" - Blade 1 local edgewise and flapwise bending moments at span station 2 (approx. 50% span) -"RootFxb1" - Out-of-plane shear, in-plane shear, and axial forces at the root of blade 1 -"RootFyb1" - Out-of-plane shear, in-plane shear, and axial forces at the root of blade 1 -"RootFzb1" - Out-of-plane shear, in-plane shear, and axial forces at the root of blade 1 -"RootMxb1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 -"RootMyb1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 -"RootMyc1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 -"RootMyc2" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 -"RootMyc3" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 -"RootMzb1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 -"RotTorq" - Rotor torque and low-speed shaft 0- and 90-bending moments at the main bearing -"LSSGagMya" - Rotor torque and low-speed shaft 0- and 90-bending moments at the main bearing -"LSSGagMza" - Rotor torque and low-speed shaft 0- and 90-bending moments at the main bearing -"YawBrFxp" - Fore-aft shear, side-to-side shear, and vertical forces at the top of the tower (not rotating with nacelle yaw) -"YawBrFyp" - Fore-aft shear, side-to-side shear, and vertical forces at the top of the tower (not rotating with nacelle yaw) -"YawBrFzp" - Fore-aft shear, side-to-side shear, and vertical forces at the top of the tower (not rotating with nacelle yaw) -"YawBrMxp" - Side-to-side bending, fore-aft bending, and yaw moments at the top of the tower (not rotating with nacelle yaw) -"YawBrMyp" - Side-to-side bending, fore-aft bending, and yaw moments at the top of the tower (not rotating with nacelle yaw) -"YawBrMzp" - Side-to-side bending, fore-aft bending, and yaw moments at the top of the tower (not rotating with nacelle yaw) -"TwrBsFxt" - Fore-aft shear, side-to-side shear, and vertical forces at the base of the tower (mudline) -"TwrBsFyt" - Fore-aft shear, side-to-side shear, and vertical forces at the base of the tower (mudline) -"TwrBsFzt" - Fore-aft shear, side-to-side shear, and vertical forces at the base of the tower (mudline) -"TwrBsMxt" - Side-to-side bending, fore-aft bending, and yaw moments at the base of the tower (mudline) -"TwrBsMyt" - Side-to-side bending, fore-aft bending, and yaw moments at the base of the tower (mudline) -"TwrBsMzt" - Side-to-side bending, fore-aft bending, and yaw moments at the base of the tower (mudline) -"NcIMURAys" - Nacelle IMU rotational acceleration in the nodding direction -"NcIMUTAxs" - Nacelle IMU translational acceleration in the streamwise direction -END of input file (the word "END" must appear in the first 3 columns of this last OutList line) ---------------------------------------------------------------------------------------- +------- ELASTODYN for OpenFAST 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) + 3 Method - Integration method: {1: RK4, 2: AB4, or 3: ABM4} (-) +"DEFAULT" DT - Integration time step (s) +---------------------- DEGREES OF FREEDOM -------------------------------------- +True FlapDOF1 - First flapwise blade mode DOF (flag) +True FlapDOF2 - Second flapwise blade mode DOF (flag) +True EdgeDOF - First edgewise blade mode DOF (flag) +False PitchDOF - Blade pitch DOF (flag) +False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] +True DrTrDOF - Drivetrain rotational-flexibility DOF (flag) +True GenDOF - Generator DOF (flag) +True YawDOF - Yaw DOF (flag) +True TwFADOF1 - First fore-aft tower bending-mode DOF (flag) +True TwFADOF2 - Second fore-aft tower bending-mode DOF (flag) +True TwSSDOF1 - First side-to-side tower bending-mode DOF (flag) +True TwSSDOF2 - Second side-to-side tower bending-mode DOF (flag) +False PtfmSgDOF - Platform horizontal surge translation DOF (flag) +False PtfmSwDOF - Platform horizontal sway translation DOF (flag) +False PtfmHvDOF - Platform vertical heave translation DOF (flag) +False PtfmRDOF - Platform roll tilt rotation DOF (flag) +False PtfmPDOF - Platform pitch tilt rotation DOF (flag) +False 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) + 0 BlPitch(1) - Blade 1 initial pitch (degrees) + 0 BlPitch(2) - Blade 2 initial pitch (degrees) + 0 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) + 12.1 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) + 0 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 ----------------------------------- + 3 NumBl - Number of blades (-) + 63 TipRad - The distance from the rotor apex to the blade tip (meters) + 1.5 HubRad - The distance from the rotor apex to the blade root (meters) + -2.5 PreCone(1) - Blade 1 cone angle (degrees) + -2.5 PreCone(2) - Blade 2 cone angle (degrees) + -2.5 PreCone(3) - Blade 3 cone angle (degrees) [unused for 2 blades] + 0 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) + -5.0191 OverHang - Distance from yaw axis to rotor apex [3 blades] or teeter pin [2 blades] (meters) + 1.912 ShftGagL - Distance from rotor apex [3 blades] or teeter pin [2 blades] to shaft strain gages [positive for upwind rotors] (meters) + -5 ShftTilt - Rotor shaft tilt angle (degrees) + 1.9 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) + 1.75 NacCMzn - Vertical distance from the tower-top to the nacelle CM (meters) + -3.09528 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) + 2.23336 NcIMUzn - Vertical distance from the tower-top to the nacelle IMU (meters) + 1.96256 Twr2Shft - Vertical distance from the tower-top to the rotor shaft (meters) + 87.6 TowerHt - Height of tower above ground level [onshore] or MSL [offshore] (meters) + 0 TowerBsHt - Height of tower base above ground level [onshore] or MSL [offshore] (meters) + 0 PtfmCMxt - Downwind distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) + 0 PtfmCMyt - Lateral distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) + 0 PtfmCMzt - Vertical distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) + 0 PtfmRefxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefzt - Vertical distance from the ground level [onshore] or MSL [offshore] 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] + 0 PBrIner(1) - Pitch bearing inertia, blade 1 (kg m^2) + 0 PBrIner(2) - Pitch bearing inertia, blade 2 (kg m^2) + 0 PBrIner(3) - Pitch bearing inertia, blade 3 (kg m^2) [unused for 2 blades] + 0 BlPIner(1) - Blade pitch inertia, blade 1 (kg m^2) + 0 BlPIner(2) - Blade pitch inertia, blade 2 (kg m^2) + 0 BlPIner(3) - Blade pitch inertia, blade 3 (kg m^2) [unused for 2 blades] + 56780 HubMass - Hub mass (kg) + 115926 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) + 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) + 534.116 GenIner - Generator inertia about HSS (kg m^2) + 240000 NacMass - Nacelle mass (kg) +2.60789E+06 NacYIner - Nacelle inertia about yaw axis (kg m^2) + 0 YawBrMass - Yaw bearing mass (kg) + 0 PtfmMass - Platform mass (kg) + 0 PtfmRIner - Platform inertia for roll tilt rotation about the platform CM (kg m^2) + 0 PtfmPIner - Platform inertia for pitch tilt rotation about the platform CM (kg m^2) + 0 PtfmYIner - Platform inertia for yaw rotation about the platform CM (kg m^2) + 0 PtfmXYIner - Platform xy moment of inertia about the platform CM (=-int(xydm)) (kg m^2) + 0 PtfmYZIner - Platform yz moment of inertia about the platform CM (=-int(yzdm)) (kg m^2) + 0 PtfmXZIner - Platform xz moment of inertia about the platform CM (=-int(xzdm)) (kg m^2) +---------------------- BLADE --------------------------------------------------- + 17 BldNodes - Number of blade nodes (per blade) used for analysis (-) +"NRELOffshrBsline5MW_Blade.dat" BldFile(1) - Name of file containing properties for blade 1 (quoted string) +"NRELOffshrBsline5MW_Blade.dat" BldFile(2) - Name of file containing properties for blade 2 (quoted string) +"NRELOffshrBsline5MW_Blade.dat" 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] +---------------------- YAW-FRICTION -------------------------------------------- + 0 YawFrctMod - Yaw-friction model {0: none, 1: friction independent of yaw-bearing force and bending moment, 2: friction with Coulomb terms depending on yaw-bearing force and bending moment, 3: user defined model} (switch) + 300 M_CSmax - Maximum static Coulomb friction torque (N-m) [M_CSmax when YawFrctMod=1; |Fz|*M_CSmax when YawFrctMod=2 and Fz<0] + 0 M_FCSmax - Maximum static Coulomb friction torque proportional to yaw bearing shear force (N-m) [sqrt(Fx^2+Fy^2)*M_FCSmax; only used when YawFrctMod=2] + 0 M_MCSmax - Maximum static Coulomb friction torque proportional to yaw bearing bending moment (N-m) [sqrt(Mx^2+My^2)*M_MCSmax; only used when YawFrctMod=2] + 40 M_CD - Dynamic Coulomb friction moment (N-m) [M_CD when YawFrctMod=1; |Fz|*M_CD when YawFrctMod=2 and Fz<0] + 0 M_FCD - Dynamic Coulomb friction moment proportional to yaw bearing shear force (N-m) [sqrt(Fx^2+Fy^2)*M_FCD; only used when YawFrctMod=2] + 0 M_MCD - Dynamic Coulomb friction moment proportional to yaw bearing bending moment (N-m) [sqrt(Mx^2+My^2)*M_MCD; only used when YawFrctMod=2] + 0 sig_v - Linear viscous friction coefficient (N-m/(rad/s)) + 0 sig_v2 - Quadratic viscous friction coefficient (N-m/(rad/s)^2) + 0 OmgCut - Yaw angular velocity cutoff below which viscous friction is linearized (rad/s) +---------------------- DRIVETRAIN ---------------------------------------------- + 100 GBoxEff - Gearbox efficiency (%) + 97 GBRatio - Gearbox ratio (-) +8.67637E+08 DTTorSpr - Drivetrain torsional spring (N-m/rad) + 6.215E+06 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 --------------------------------------------------- + 20 TwrNodes - Number of tower nodes used for analysis (-) +"NRELOffshrBsline5MW_Onshore_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] (-) + 10, 19, 28 TwrGagNd - List of tower nodes that have strain gages [1 to TwrNodes] (-) [unused if NTwGages=0] + 3 NBlGages - Number of blade nodes that have strain gages for output [0 to 9] (-) + 5, 9, 13 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, (-) +"OoPDefl1" - Blade 1 out-of-plane and in-plane deflections and tip twist +"IPDefl1" - Blade 1 out-of-plane and in-plane deflections and tip twist +"TwstDefl1" - Blade 1 out-of-plane and in-plane deflections and tip twist +"BldPitch1" - Blade 1 pitch angle +"Azimuth" - Blade 1 azimuth angle +"RotSpeed" - Low-speed shaft and high-speed shaft speeds +"GenSpeed" - Low-speed shaft and high-speed shaft speeds +"TTDspFA" - Tower fore-aft and side-to-side displacements and top twist +"TTDspSS" - Tower fore-aft and side-to-side displacements and top twist +"TTDspTwst" - Tower fore-aft and side-to-side displacements and top twist +"Spn2MLxb1" - Blade 1 local edgewise and flapwise bending moments at span station 2 (approx. 50% span) +"Spn2MLyb1" - Blade 1 local edgewise and flapwise bending moments at span station 2 (approx. 50% span) +"RootFxb1" - Out-of-plane shear, in-plane shear, and axial forces at the root of blade 1 +"RootFyb1" - Out-of-plane shear, in-plane shear, and axial forces at the root of blade 1 +"RootFzb1" - Out-of-plane shear, in-plane shear, and axial forces at the root of blade 1 +"RootMxb1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 +"RootMyb1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 +"RootMyc1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 +"RootMyc2" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 +"RootMyc3" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 +"RootMzb1" - In-plane bending, out-of-plane bending, and pitching moments at the root of blade 1 +"RotTorq" - Rotor torque and low-speed shaft 0- and 90-bending moments at the main bearing +"LSSGagMya" - Rotor torque and low-speed shaft 0- and 90-bending moments at the main bearing +"LSSGagMza" - Rotor torque and low-speed shaft 0- and 90-bending moments at the main bearing +"YawBrFxp" - Fore-aft shear, side-to-side shear, and vertical forces at the top of the tower (not rotating with nacelle yaw) +"YawBrFyp" - Fore-aft shear, side-to-side shear, and vertical forces at the top of the tower (not rotating with nacelle yaw) +"YawBrFzp" - Fore-aft shear, side-to-side shear, and vertical forces at the top of the tower (not rotating with nacelle yaw) +"YawBrMxp" - Side-to-side bending, fore-aft bending, and yaw moments at the top of the tower (not rotating with nacelle yaw) +"YawBrMyp" - Side-to-side bending, fore-aft bending, and yaw moments at the top of the tower (not rotating with nacelle yaw) +"YawBrMzp" - Side-to-side bending, fore-aft bending, and yaw moments at the top of the tower (not rotating with nacelle yaw) +"TwrBsFxt" - Fore-aft shear, side-to-side shear, and vertical forces at the base of the tower (mudline) +"TwrBsFyt" - Fore-aft shear, side-to-side shear, and vertical forces at the base of the tower (mudline) +"TwrBsFzt" - Fore-aft shear, side-to-side shear, and vertical forces at the base of the tower (mudline) +"TwrBsMxt" - Side-to-side bending, fore-aft bending, and yaw moments at the base of the tower (mudline) +"TwrBsMyt" - Side-to-side bending, fore-aft bending, and yaw moments at the base of the tower (mudline) +"TwrBsMzt" - Side-to-side bending, fore-aft bending, and yaw moments at the base of the tower (mudline) +"NcIMURAys" - Nacelle IMU rotational acceleration in the nodding direction +"NcIMUTAxs" - Nacelle IMU translational acceleration in the streamwise direction +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/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat index 416278438..d73947f5a 100644 --- a/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat +++ b/Examples/Test_Cases/NREL-5MW/NRELOffshrBsline5MW_Onshore_ServoDyn.dat @@ -1,110 +1,119 @@ -------- 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] -"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 -END of input file (the word "END" must appear in the first 3 columns of this last OutList line) ---------------------------------------------------------------------------------------- +------- 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] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) + 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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] +"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 +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/NREL_2p8_127/NREL-2p8-127.fst b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127.fst index 7500cc4d4..5fe1b50af 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127.fst +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127.fst @@ -5,21 +5,28 @@ False Echo - Echo input data to .ech (flag) "FATAL" AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} 300.0 TMax - Total run time (s) 0.005 DT - Recommended module time step (s) + 1 ModCoupling - Module coupling method (switch) {1=loose; 2=tight with fixed Jacobian updates (DT_UJac); 3=tight with automatic Jacobian updates} 2 InterpOrder - Interpolation order for input/output time history (-) {1=linear, 2=quadratic} 0 NumCrctn - Number of correction iterations (-) {0=explicit calculation, i.e., no corrections} + 0.0 RhoInf - Numerical damping parameter for tight coupling generalized-alpha integrator (-) [0.0 to 1.0] + 1e-4 ConvTol - Convergence iteration error tolerance for tight coupling generalized alpha integrator (-) + 6 MaxConvIter - Maximum number of convergence iterations for tight coupling generalized alpha integrator (-) 99999.0 DT_UJac - Time between calls to get Jacobians (s) 1000000.0 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 NRotors - Number of rotors in turbine (-) +1 CompElast - Compute structural dynamics (switch) {1=ElastoDyn; 2=ElastoDyn + BeamDyn for blades; 3=Simplified ElastoDyn} +1 CompInflow - Compute inflow wind velocities (switch) {0=still air; 1=InflowWind; 2=external from ExtInflow} +2 CompAero - Compute aerodynamic loads (switch) {0=None; 1=AeroDisk; 2=AeroDyn; 3=ExtLoads} 1 CompServo - Compute control and electrical-drive dynamics (switch) {0=None; 1=ServoDyn} 0 CompSeaSt - Compute sea state information (switch) {0=None; 1=SeaState} 0 CompHydro - Compute hydrodynamic loads (switch) {0=None; 1=HydroDyn} 0 CompSub - Compute sub-structural dynamics (switch) {0=None; 1=SubDyn; 2=External Platform MCKF} 0 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} + 0 CompSoil - Compute soil-structural dynamics (switch) {0=None; 1=SoilDyn} 0 MHK - MHK turbine type (switch) {0=Not an MHK turbine; 1=Fixed MHK turbine; 2=Floating MHK turbine} + F MirrorRotor - Flag to reverse rotor rotation direction [1 to NRotors] {F=Normal, T=Mirror} ---------------------- ENVIRONMENTAL CONDITIONS -------------------------------- 9.80665 Gravity - Gravitational acceleration (m/s^2) 1.225 AirDens - Air density (kg/m^3) @@ -43,13 +50,14 @@ False Echo - Echo input data to .ech (flag) "none" SubFile - Name of file containing sub-structural input parameters (quoted string) "none" MooringFile - Name of file containing mooring system input parameters (quoted string) "none" IceFile - Name of file containing ice input parameters (quoted string) +"unused" SoilFile - Name of the file containing the SoilDyn input parameters (quoted string) ---------------------- OUTPUT -------------------------------------------------- False SumPrint - Print summary data to ".sum" (flag) 10.0 SttsTime - Amount of time between screen status messages (s) 99999.0 ChkptTime - Amount of time between creating checkpoint files for potential restart (s) default DT_Out - Time step for tabular output (s) (or "default") 0.0 TStart - Time to begin tabular output (s) -1 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both} +1 OutFileFmt - Format for tabular (time-marching) output file (switch) {1: text file [.out], 2: binary file [.outb], 3: both 1 and 2, 4: uncompressed binary [.outb], 5: both 1 and 4} 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 ------------------------------------------- diff --git a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat index 72af369cf..eced24b96 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15.dat @@ -8,7 +8,6 @@ default DTAero - Time interval for aerodynamic calculations 0 TwrShadow - Calculate tower influence on wind based on downstream tower shadow (switch) {0=none, 1=Powles model, 2=Eames model} False TwrAero - Calculate tower aerodynamic loads? (flag) False CavitCheck - Perform cavitation check? (flag) [AFAeroMod must be 1 when CavitCheck=true] -False Buoyancy - Include buoyancy effects? (flag) False NacelleDrag - Include Nacelle Drag effects? (flag) False CompAA - Flag to compute AeroAcoustics calculation [only used when WakeMod=1 or 2] AeroAcousticsInput.dat AA_InputFile - AeroAcoustics input file [used only when CompAA=true] @@ -94,10 +93,10 @@ True UseBlCm - Include aerodynamic pitching moment in calc "NREL-2p8-127_AeroDyn15_blade.dat" ADBlFile(1) - Name of file containing distributed aerodynamic properties for Blade #1 (-) "NREL-2p8-127_AeroDyn15_blade.dat" ADBlFile(2) - Name of file containing distributed aerodynamic properties for Blade #2 (-) [unused if NumBl < 2] "NREL-2p8-127_AeroDyn15_blade.dat" ADBlFile(3) - Name of file containing distributed aerodynamic properties for Blade #3 (-) [unused if NumBl < 3] -====== Hub Properties ============================================================================== [used only when Buoyancy=True] +====== Hub Properties ============================================================================== [used only when MHK=1 or 2] 0.0 VolHub - Hub volume (m^3) 0.0 HubCenBx - Hub center of buoyancy x direction offset (m) -====== Nacelle Properties ========================================================================== [used only when Buoyancy=True] +====== Nacelle Properties ========================================================================== [used only when MHK=1 or 2 or when NacelleDrag=True] 0 VolNac - Nacelle volume (m^3) 0.0, 0.0, 0.0 NacCenB - Position of nacelle center of buoyancy from yaw bearing in nacelle coordinates (m) 0, 0, 0 NacArea - Projected area of the nacelle in X, Y, Z in the nacelle coordinate system (m^2) @@ -106,20 +105,20 @@ True UseBlCm - Include aerodynamic pitching moment in calc ====== 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, or TwrAero=True] -10 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, or TwrAero=True] -TwrElev TwrDiam TwrCd TwrTI TwrCb !TwrTI used only with TwrShadow=2, TwrCb used only with Buoyancy=True -(m) (m) (-) (-) (-) - 8.650000000000000e+00 3.999999999999999e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 1.730800925925926e+01 4.000000000000000e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 2.595800925925926e+01 4.000000000000000e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 3.461601851851852e+01 3.953273204469021e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 4.326601851851852e+01 3.712118013878008e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 5.191601851851851e+01 3.433099970059946e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 6.057402777777778e+01 3.130385763598736e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 6.922402777777778e+01 2.796113422345067e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 7.787402777777778e+01 2.382646880140990e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 - 8.650000000000000e+01 2.324880163918676e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 +====== Tower Influence and Aerodynamics ============================================================= [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +10 NumTwrNds - Number of tower nodes used in the analysis (-) [used only when TwrPotent/=0, TwrShadow/=0, TwrAero=True, or MHK=1 or 2] +TwrElev TwrDiam TwrCd TwrTI TwrCb TwrCp TwrCa !TwrTI used only with TwrShadow=2, TwrCb/TwrCp/TwrCa used only with MHK=1 or 2 +(m) (m) (-) (-) (-) (-) (-) +8.650000000000000e+00 3.999999999999999e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +1.730800925925926e+01 4.000000000000000e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +2.595800925925926e+01 4.000000000000000e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +3.461601851851852e+01 3.953273204469021e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +4.326601851851852e+01 3.712118013878008e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +5.191601851851851e+01 3.433099970059946e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +6.057402777777778e+01 3.130385763598736e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +6.922402777777778e+01 2.796113422345067e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +7.787402777777778e+01 2.382646880140990e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 +8.650000000000000e+01 2.324880163918676e+00 5.000000000000000e-01 1.000000000000000e-01 0.0 0.0000000E+00 0.0000000E+00 ====== Outputs ==================================================================================== False SumPrint - Generate a summary file listing input options and interpolated properties to ".AD.sum"? (flag) 0 NBlOuts - Number of blade node outputs [0 - 9] (-) diff --git a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat index fd4b728fe..1bbb8f735 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_AeroDyn15_blade.dat @@ -2,35 +2,35 @@ Generated with AeroElasticSE FAST driver ====== Blade Properties ================================================================= 30 NumBlNds - Number of blade nodes used in the analysis (-) - BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID - (m) (m) (m) (deg) (deg) (m) (-) - 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.999622705006573e+01 2.565746018075444e+00 1 - 2.119199517912653e+00 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.931018243810786e+01 3.361938565422448e+00 2 - 4.238399035825307e+00 0.000000000000000e+00 0.000000000000000e+00 -2.621743302803628e-03 1.831714953780435e+01 4.045185045024725e+00 3 - 6.357598553737958e+00 -1.939408866995070e-04 0.000000000000000e+00 -6.412784123456707e-02 1.708763041181490e+01 4.534861529323176e+00 4 - 8.476798071650611e+00 -4.743793103448273e-03 0.000000000000000e+00 -1.978684279841359e-01 1.569212712279918e+01 4.750344090758699e+00 5 - 1.059599758956327e+01 -1.483103448275862e-02 0.000000000000000e+00 -3.150569530999122e-01 1.382289586770404e+01 4.737620755206947e+00 6 - 1.271519710747592e+01 -2.804970443349753e-02 0.000000000000000e+00 -4.200820236296363e-01 1.124554309027298e+01 4.683448688307037e+00 7 - 1.483439662538857e+01 -4.590591133004925e-02 0.000000000000000e+00 -5.312359339597873e-01 8.602632953470145e+00 4.602338372007760e+00 8 - 1.695359614330122e+01 -6.734679802955665e-02 0.000000000000000e+00 -6.413089831677180e-01 6.549224739725965e+00 4.505595976960268e+00 9 - 1.907279566121387e+01 -9.334512315270936e-02 0.000000000000000e+00 -7.594874026577699e-01 5.408188380153923e+00 4.380463162058345e+00 10 - 2.119199517912653e+01 -1.235274876847291e-01 0.000000000000000e+00 -8.814019981123943e-01 4.552816793256156e+00 4.183546777131121e+00 11 - 2.331119469703918e+01 -1.585433990147783e-01 0.000000000000000e+00 -1.022348344095032e+00 3.850103071189125e+00 3.945902894366683e+00 12 - 2.543039421495183e+01 -1.991506896551724e-01 0.000000000000000e+00 -1.183293448295596e+00 3.210053831367405e+00 3.702763428157307e+00 13 - 2.754959373286449e+01 -2.460701477832512e-01 0.000000000000000e+00 -1.342781789240282e+00 2.548277995517243e+00 3.476193009639851e+00 14 - 2.966879325077715e+01 -2.984725615763546e-01 0.000000000000000e+00 -1.515812813319435e+00 1.868987870564891e+00 3.235485886652345e+00 15 - 3.178799276868979e+01 -3.581878325123153e-01 0.000000000000000e+00 -1.698337241682368e+00 1.247026288989173e+00 2.994660335764964e+00 16 - 3.390719228660245e+01 -4.240869950738916e-01 0.000000000000000e+00 -1.908238044665007e+00 7.591906266374636e-01 2.774705218558286e+00 17 - 3.602639180451509e+01 -4.993217733990146e-01 0.000000000000000e+00 -2.133886441082087e+00 4.659000465949885e-01 2.591930205580583e+00 18 - 3.814559132242776e+01 -5.819026600985221e-01 0.000000000000000e+00 -2.384324918476038e+00 2.731580237682558e-01 2.424912635092513e+00 19 - 4.026479084034041e+01 -6.756489655172412e-01 0.000000000000000e+00 -2.659453831887105e+00 1.231485664729688e-01 2.273929330687443e+00 20 - 4.238399035825307e+01 -7.785625123152710e-01 0.000000000000000e+00 -2.957313507988756e+00 -1.889923787502366e-02 2.146862384202469e+00 21 - 4.450318987616572e+01 -8.943162068965517e-01 0.000000000000000e+00 -3.294896483624423e+00 -1.841259535939614e-01 2.051800999525918e+00 22 - 4.662238939407835e+01 -1.022164926108374e+00 0.000000000000000e+00 -3.676725314021781e+00 -3.432314804149588e-01 1.991284282831078e+00 23 - 4.874158891199102e+01 -1.166111724137931e+00 0.000000000000000e+00 -4.102651579820645e+00 -5.034899071419768e-01 1.944879951099011e+00 24 - 5.086078842990366e+01 -1.325395270935961e+00 0.000000000000000e+00 -4.585680344442696e+00 -6.944182383563149e-01 1.888109521438915e+00 25 - 5.297998794781633e+01 -1.504970886699507e+00 0.000000000000000e+00 -5.166689492052464e+00 -9.464479611794926e-01 1.795137265041130e+00 26 - 5.509918746572898e+01 -1.707078275862069e+00 0.000000000000000e+00 -5.829761241403034e+00 -1.331448785580028e+00 1.572950482786750e+00 27 - 5.721838698364163e+01 -1.935478029556650e+00 0.000000000000000e+00 -6.607040906671076e+00 -1.857716459023805e+00 1.205686533770803e+00 28 - 5.933758650155428e+01 -2.194745172413793e+00 0.000000000000000e+00 -7.654100340223317e+00 -2.493070572147947e+00 7.343636341297369e-01 29 - 6.145678601946693e+01 -2.500000000000000e+00 0.000000000000000e+00 -8.281837270494590e+00 -3.205330715589577e+00 1.999999999999999e-01 30 + BlSpn BlCrvAC BlSwpAC BlCrvAng BlTwist BlChord BlAFID t_c BlCb BlCenBn BlCenBt BlCpn BlCpt BlCan BlCat BlCam + (m) (m) (m) (deg) (deg) (m) (-) (-) (-) (m) (m) (-) (-) (-) (-) (-) + 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.999622705006573e+01 2.565746018075444e+00 1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 2.119199517912653e+00 0.000000000000000e+00 0.000000000000000e+00 0.000000000000000e+00 1.931018243810786e+01 3.361938565422448e+00 2 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 4.238399035825307e+00 0.000000000000000e+00 0.000000000000000e+00 -2.621743302803628e-03 1.831714953780435e+01 4.045185045024725e+00 3 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 6.357598553737958e+00 -1.939408866995070e-04 0.000000000000000e+00 -6.412784123456707e-02 1.708763041181490e+01 4.534861529323176e+00 4 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 8.476798071650611e+00 -4.743793103448273e-03 0.000000000000000e+00 -1.978684279841359e-01 1.569212712279918e+01 4.750344090758699e+00 5 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.059599758956327e+01 -1.483103448275862e-02 0.000000000000000e+00 -3.150569530999122e-01 1.382289586770404e+01 4.737620755206947e+00 6 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.271519710747592e+01 -2.804970443349753e-02 0.000000000000000e+00 -4.200820236296363e-01 1.124554309027298e+01 4.683448688307037e+00 7 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.483439662538857e+01 -4.590591133004925e-02 0.000000000000000e+00 -5.312359339597873e-01 8.602632953470145e+00 4.602338372007760e+00 8 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.695359614330122e+01 -6.734679802955665e-02 0.000000000000000e+00 -6.413089831677180e-01 6.549224739725965e+00 4.505595976960268e+00 9 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 1.907279566121387e+01 -9.334512315270936e-02 0.000000000000000e+00 -7.594874026577699e-01 5.408188380153923e+00 4.380463162058345e+00 10 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 2.119199517912653e+01 -1.235274876847291e-01 0.000000000000000e+00 -8.814019981123943e-01 4.552816793256156e+00 4.183546777131121e+00 11 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 2.331119469703918e+01 -1.585433990147783e-01 0.000000000000000e+00 -1.022348344095032e+00 3.850103071189125e+00 3.945902894366683e+00 12 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 2.543039421495183e+01 -1.991506896551724e-01 0.000000000000000e+00 -1.183293448295596e+00 3.210053831367405e+00 3.702763428157307e+00 13 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 2.754959373286449e+01 -2.460701477832512e-01 0.000000000000000e+00 -1.342781789240282e+00 2.548277995517243e+00 3.476193009639851e+00 14 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 2.966879325077715e+01 -2.984725615763546e-01 0.000000000000000e+00 -1.515812813319435e+00 1.868987870564891e+00 3.235485886652345e+00 15 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 3.178799276868979e+01 -3.581878325123153e-01 0.000000000000000e+00 -1.698337241682368e+00 1.247026288989173e+00 2.994660335764964e+00 16 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 3.390719228660245e+01 -4.240869950738916e-01 0.000000000000000e+00 -1.908238044665007e+00 7.591906266374636e-01 2.774705218558286e+00 17 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 3.602639180451509e+01 -4.993217733990146e-01 0.000000000000000e+00 -2.133886441082087e+00 4.659000465949885e-01 2.591930205580583e+00 18 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 3.814559132242776e+01 -5.819026600985221e-01 0.000000000000000e+00 -2.384324918476038e+00 2.731580237682558e-01 2.424912635092513e+00 19 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 4.026479084034041e+01 -6.756489655172412e-01 0.000000000000000e+00 -2.659453831887105e+00 1.231485664729688e-01 2.273929330687443e+00 20 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 4.238399035825307e+01 -7.785625123152710e-01 0.000000000000000e+00 -2.957313507988756e+00 -1.889923787502366e-02 2.146862384202469e+00 21 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 4.450318987616572e+01 -8.943162068965517e-01 0.000000000000000e+00 -3.294896483624423e+00 -1.841259535939614e-01 2.051800999525918e+00 22 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 4.662238939407835e+01 -1.022164926108374e+00 0.000000000000000e+00 -3.676725314021781e+00 -3.432314804149588e-01 1.991284282831078e+00 23 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 4.874158891199102e+01 -1.166111724137931e+00 0.000000000000000e+00 -4.102651579820645e+00 -5.034899071419768e-01 1.944879951099011e+00 24 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 5.086078842990366e+01 -1.325395270935961e+00 0.000000000000000e+00 -4.585680344442696e+00 -6.944182383563149e-01 1.888109521438915e+00 25 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 5.297998794781633e+01 -1.504970886699507e+00 0.000000000000000e+00 -5.166689492052464e+00 -9.464479611794926e-01 1.795137265041130e+00 26 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 5.509918746572898e+01 -1.707078275862069e+00 0.000000000000000e+00 -5.829761241403034e+00 -1.331448785580028e+00 1.572950482786750e+00 27 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 5.721838698364163e+01 -1.935478029556650e+00 0.000000000000000e+00 -6.607040906671076e+00 -1.857716459023805e+00 1.205686533770803e+00 28 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 5.933758650155428e+01 -2.194745172413793e+00 0.000000000000000e+00 -7.654100340223317e+00 -2.493070572147947e+00 7.343636341297369e-01 29 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 + 6.145678601946693e+01 -2.500000000000000e+00 0.000000000000000e+00 -8.281837270494590e+00 -3.205330715589577e+00 1.999999999999999e-01 30 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 diff --git a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN index f8cd243f0..e50f61bd8 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_DISCON.IN @@ -1,5 +1,5 @@ ! Controller parameter input file for the NREL-2p8-127 wind turbine -! - File written using ROSCO version 2.10.1 controller tuning logic on 11/26/25 +! - File written using ROSCO version 2.10.6 controller tuning logic on 06/09/26 !------- 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) diff --git a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat index bc16fc80f..6289d5c93 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn.dat @@ -8,6 +8,7 @@ default DT Integration time step (s) True FlapDOF1 - First flapwise blade mode DOF (flag) True FlapDOF2 - Second flapwise blade mode DOF (flag) True EdgeDOF - First edgewise blade mode DOF (flag) +False PitchDOF - Blade pitch DOF (flag) False TeetDOF - Rotor-teeter DOF (flag) [unused for 3 blades] False DrTrDOF - Drivetrain rotational-flexibility DOF (flag) True GenDOF - Generator DOF (flag) @@ -66,11 +67,19 @@ False PtfmYDOF - Platform yaw rotation DOF (flag) 0.0 PtfmCMxt - Downwind distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) 0.0 PtfmCMyt - Lateral distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) 0.0 PtfmCMzt - Vertical distance from the ground level [onshore] or MSL [offshore] to the platform CM (meters) + 0 PtfmRefxt - Downwind distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) + 0 PtfmRefyt - Lateral distance from the ground level [onshore], MSL [offshore wind or floating MHK], or seabed [fixed MHK] to the platform reference point (meters) 0.0 PtfmRefzt - Vertical distance from the ground level [onshore] or MSL [offshore] to the platform reference point (meters) ---------------------- MASS AND INERTIA ---------------------------------------- 0.0 TipMass(1) - Tip-brake mass, blade 1 (kg) 0.0 TipMass(2) - Tip-brake mass, blade 2 (kg) 0.0 TipMass(3) - Tip-brake mass, blade 3 (kg) [unused for 2 blades] + 0 PBrIner(1) - Pitch bearing inertia, blade 1 (kg m^2) + 0 PBrIner(2) - Pitch bearing inertia, blade 2 (kg m^2) + 0 PBrIner(3) - Pitch bearing inertia, blade 3 (kg m^2) [unused for 2 blades] + 0 BlPIner(1) - Blade pitch inertia, blade 1 (kg m^2) + 0 BlPIner(2) - Blade pitch inertia, blade 2 (kg m^2) + 0 BlPIner(3) - Blade pitch inertia, blade 3 (kg m^2) [unused for 2 blades] 7482.264184443234 HubMass - Hub mass (kg) 28639.287453422658 HubIner - Hub inertia about rotor axis [3 blades] or teeter axis [2 blades] (kg m^2) 0 HubIner_Teeter - Hub inertia about teeter axis (2-blades) (kg m^2) diff --git a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat index 662c3af1d..ad165fbe5 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ElastoDyn_blade.dat @@ -12,38 +12,38 @@ Generated with AeroElasticSE FAST driver 1.0 AdjFlSt - Factor to adjust blade flap stiffness (-) 1.0 AdjEdSt - Factor to adjust blade edge stiffness (-) ---------------------- DISTRIBUTED BLADE PROPERTIES ---------------------------- - BlFract PitchAxis StrcTwst BMassDen FlpStff EdgStff - (-) (-) (deg) (kg/m) (Nm^2) (Nm^2) - 0.000000000000000e+00 5.000000000000000e-01 1.999622705006573e+01 9.710303775720137e+02 8.916645581889803e+09 8.916996828171421e+09 - 3.448275862068966e-02 4.797651657064801e-01 1.931018243810786e+01 9.360384963432447e+02 1.473326655503917e+10 1.503401326999529e+10 - 6.896551724137932e-02 4.100052021425268e-01 1.831714953780435e+01 7.384411481979697e+02 1.350641277548294e+10 1.668758117393011e+10 - 1.034482758620690e-01 3.512493343557562e-01 1.708763041181490e+01 5.242503736808504e+02 7.750625550591639e+09 1.313891689544163e+10 - 1.379310344827586e-01 3.110092285118687e-01 1.569212712279918e+01 4.095720481213451e+02 4.517970071596079e+09 1.065397599903997e+10 - 1.724137931034483e-01 2.834806852225638e-01 1.382289586770404e+01 2.986034040547503e+02 2.639603257135735e+09 7.691984348826207e+09 - 2.068965517241379e-01 2.649028377616424e-01 1.124554309027298e+01 2.242709960488304e+02 1.722995952419500e+09 5.352469758607450e+09 - 2.413793103448276e-01 2.524820938264642e-01 8.602632953470145e+00 2.129606273581960e+02 1.483184105878141e+09 4.327677642529569e+09 - 2.758620689655172e-01 2.449189056667618e-01 6.549224739725965e+00 2.091698491908484e+02 1.365990134494710e+09 3.614205549153540e+09 - 3.103448275862069e-01 2.413757812153578e-01 5.408188380153923e+00 1.968505270832688e+02 1.161884350732890e+09 3.059348888224575e+09 - 3.448275862068965e-01 2.409997816578705e-01 4.552816793256156e+00 1.840381495123537e+02 9.314103670023195e+08 2.635487762688528e+09 - 3.793103448275861e-01 2.438939371115084e-01 3.850103071189125e+00 1.707777565800272e+02 7.316000308334582e+08 2.188136539118910e+09 - 4.137931034482759e-01 2.495413982689942e-01 3.210053831367405e+00 1.577448933617357e+02 5.813400904874783e+08 1.847593613150510e+09 - 4.482758620689655e-01 2.579313748558032e-01 2.548277995517243e+00 1.472572881966913e+02 4.757592505107988e+08 1.631226610849327e+09 - 4.827586206896552e-01 2.680075313847211e-01 1.868987870564891e+00 1.385288690289785e+02 3.862376543475163e+08 1.405932074273394e+09 - 5.172413793103448e-01 2.786890302281694e-01 1.247026288989173e+00 1.303134456935171e+02 3.086236872618167e+08 1.086079003669758e+09 - 5.517241379310345e-01 2.889455550381649e-01 7.591906266374636e-01 1.214132928926456e+02 2.441246000330141e+08 7.279449241103762e+08 - 5.862068965517241e-01 2.981867550411185e-01 4.659000465949885e-01 1.130051988362277e+02 1.889011712485603e+08 4.718010458987974e+08 - 6.206896551724138e-01 3.061372927610646e-01 2.731580237682558e-01 1.057369028682480e+02 1.426024838771875e+08 3.311232129595062e+08 - 6.551724137931035e-01 3.119763987397355e-01 1.231485664729688e-01 9.974549711305480e+01 1.081121588014881e+08 2.531064287089206e+08 - 6.896551724137934e-01 3.154698036179193e-01 -1.889923787502366e-02 9.455111640202743e+01 8.496507419955346e+07 1.976683193694704e+08 - 7.241379310344830e-01 3.174252972719749e-01 -1.841259535939614e-01 8.918927437076574e+01 6.699354322582775e+07 1.803010747112424e+08 - 7.586206896551723e-01 3.157084507688791e-01 -3.432314804149588e-01 8.015835414506564e+01 5.106806818035772e+07 1.739724378313888e+08 - 7.931034482758621e-01 3.095467116664537e-01 -5.034899071419768e-01 7.140526341375902e+01 3.929235153694874e+07 1.684420237335510e+08 - 8.275862068965517e-01 2.996558060513167e-01 -6.944182383563149e-01 5.563937030326857e+01 2.849850000919442e+07 7.873543089740016e+07 - 8.620689655172414e-01 2.881116856742882e-01 -9.464479611794926e-01 4.591127859162181e+01 1.982854313004774e+07 6.415110790287662e+07 - 8.965517241379312e-01 2.777712184636389e-01 -1.331448785580028e+00 3.521480844524145e+01 1.075138794875714e+07 4.514001039735875e+07 - 9.310344827586208e-01 2.706279229199988e-01 -1.857716459023805e+00 2.414179066974884e+01 3.638232945365374e+06 2.616242592743580e+07 - 9.655172413793103e-01 2.665260978643628e-01 -2.493070572147947e+00 3.678240377890068e+00 8.650778718250984e+04 1.574666086617074e+06 - 1.000000000000000e+00 2.500000000000000e-01 -3.205330715589577e+00 1.002353815775734e+00 1.628296293397697e+03 3.168732291579445e+04 + BlFract StrcTwst BMassDen FlpStff EdgStff + (-) (deg) (kg/m) (Nm^2) (Nm^2) + 0.000000000000000e+00 1.999622705006573e+01 9.710303775720137e+02 8.916645581889803e+09 8.916996828171421e+09 + 3.448275862068966e-02 1.931018243810786e+01 9.360384963432447e+02 1.473326655503917e+10 1.503401326999529e+10 + 6.896551724137932e-02 1.831714953780435e+01 7.384411481979697e+02 1.350641277548294e+10 1.668758117393011e+10 + 1.034482758620690e-01 1.708763041181490e+01 5.242503736808504e+02 7.750625550591639e+09 1.313891689544163e+10 + 1.379310344827586e-01 1.569212712279918e+01 4.095720481213451e+02 4.517970071596079e+09 1.065397599903997e+10 + 1.724137931034483e-01 1.382289586770404e+01 2.986034040547503e+02 2.639603257135735e+09 7.691984348826207e+09 + 2.068965517241379e-01 1.124554309027298e+01 2.242709960488304e+02 1.722995952419500e+09 5.352469758607450e+09 + 2.413793103448276e-01 8.602632953470145e+00 2.129606273581960e+02 1.483184105878141e+09 4.327677642529569e+09 + 2.758620689655172e-01 6.549224739725965e+00 2.091698491908484e+02 1.365990134494710e+09 3.614205549153540e+09 + 3.103448275862069e-01 5.408188380153923e+00 1.968505270832688e+02 1.161884350732890e+09 3.059348888224575e+09 + 3.448275862068965e-01 4.552816793256156e+00 1.840381495123537e+02 9.314103670023195e+08 2.635487762688528e+09 + 3.793103448275861e-01 3.850103071189125e+00 1.707777565800272e+02 7.316000308334582e+08 2.188136539118910e+09 + 4.137931034482759e-01 3.210053831367405e+00 1.577448933617357e+02 5.813400904874783e+08 1.847593613150510e+09 + 4.482758620689655e-01 2.548277995517243e+00 1.472572881966913e+02 4.757592505107988e+08 1.631226610849327e+09 + 4.827586206896552e-01 1.868987870564891e+00 1.385288690289785e+02 3.862376543475163e+08 1.405932074273394e+09 + 5.172413793103448e-01 1.247026288989173e+00 1.303134456935171e+02 3.086236872618167e+08 1.086079003669758e+09 + 5.517241379310345e-01 7.591906266374636e-01 1.214132928926456e+02 2.441246000330141e+08 7.279449241103762e+08 + 5.862068965517241e-01 4.659000465949885e-01 1.130051988362277e+02 1.889011712485603e+08 4.718010458987974e+08 + 6.206896551724138e-01 2.731580237682558e-01 1.057369028682480e+02 1.426024838771875e+08 3.311232129595062e+08 + 6.551724137931035e-01 1.231485664729688e-01 9.974549711305480e+01 1.081121588014881e+08 2.531064287089206e+08 + 6.896551724137934e-01 -1.889923787502366e-02 9.455111640202743e+01 8.496507419955346e+07 1.976683193694704e+08 + 7.241379310344830e-01 -1.841259535939614e-01 8.918927437076574e+01 6.699354322582775e+07 1.803010747112424e+08 + 7.586206896551723e-01 -3.432314804149588e-01 8.015835414506564e+01 5.106806818035772e+07 1.739724378313888e+08 + 7.931034482758621e-01 -5.034899071419768e-01 7.140526341375902e+01 3.929235153694874e+07 1.684420237335510e+08 + 8.275862068965517e-01 -6.944182383563149e-01 5.563937030326857e+01 2.849850000919442e+07 7.873543089740016e+07 + 8.620689655172414e-01 -9.464479611794926e-01 4.591127859162181e+01 1.982854313004774e+07 6.415110790287662e+07 + 8.965517241379312e-01 -1.331448785580028e+00 3.521480844524145e+01 1.075138794875714e+07 4.514001039735875e+07 + 9.310344827586208e-01 -1.857716459023805e+00 2.414179066974884e+01 3.638232945365374e+06 2.616242592743580e+07 + 9.655172413793103e-01 -2.493070572147947e+00 3.678240377890068e+00 8.650778718250984e+04 1.574666086617074e+06 + 1.000000000000000e+00 -3.205330715589577e+00 1.002353815775734e+00 1.628296293397697e+03 3.168732291579445e+04 ---------------------- BLADE MODE SHAPES --------------------------------------- 0.004521475330089924 BldFl1Sh(2) - Flap mode 1, coeff of x^2 1.0698094815587011 BldFl1Sh(3) - , coeff of x^3 diff --git a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat index 078bd87f7..e3d26db06 100644 --- a/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat +++ b/Examples/Test_Cases/NREL_2p8_127/NREL-2p8-127_ServoDyn.dat @@ -6,6 +6,15 @@ default DT - Communication interval for controllers (s) ---------------------- 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) 0.0 TPCOn - Time to enable active pitch control (s) [unused when PCMode=0] + 0 PitNeut(1) - Blade 1 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(2) - Blade 2 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 0 PitNeut(3) - Blade 3 neutral pitch position--pitch spring moment is zero at this pitch (degrees) + 7.0e8 PitSpr(1) - Blade 1 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(2) - Blade 2 pitch spring constant (N-m/rad) + 7.0e8 PitSpr(3) - Blade 3 pitch spring constant (N-m/rad) + 2.3e5 PitDamp(1) - Blade 1 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(2) - Blade 2 pitch damping constant (N-m/(rad/s)) + 2.3e5 PitDamp(3) - Blade 3 pitch damping constant (N-m/(rad/s)) 99999.0 TPitManS(1) - Time to start override pitch maneuver for blade 1 and end standard pitch control (s) 99999.0 TPitManS(2) - Time to start override pitch maneuver for blade 2 and end standard pitch control (s) 99999.0 TPitManS(3) - Time to start override pitch maneuver for blade 3 and end standard pitch control (s) [unused for 2 blades] @@ -74,7 +83,7 @@ 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/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] +"/Users/dzalkind/Tools/ROSCO-main/rosco/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] "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/Examples/Tune_Cases/RM1_MHK.yaml b/Examples/Tune_Cases/RM1_MHK.yaml index b0cbfde30..4262abc46 100644 --- a/Examples/Tune_Cases/RM1_MHK.yaml +++ b/Examples/Tune_Cases/RM1_MHK.yaml @@ -38,24 +38,24 @@ controller_params: 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} + PS_Mode: 1 # 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] + U_pc: [1.5, 2, 2.5] + # interp_type: sigma + zeta_pc: [1., 1, 1] # Pitch controller desired damping ratio [-] + omega_pc: [0.35, 0.35, 0.35] # 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] + omega_vs: 0.3 # 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) + ptfm_freq: 0.4 # 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 + Kp_float: -1 max_torque_factor: 1.5 DISCON: F_NumNotchFilts: 2 @@ -67,4 +67,4 @@ controller_params: F_TwrTopNotch_N: 2 F_TwrTopNotch_Ind: [1,2] F_NotchCornerFreq_GS: [2.42] - F_FlHighPassFreq: 1.5 + # F_FlHighPassFreq: 1.5 diff --git a/Examples/Tune_Cases/RM1_MHK_FBP.yaml b/Examples/Tune_Cases/RM1_MHK_FBP.yaml index e3fc4f9c2..de6bca870 100644 --- a/Examples/Tune_Cases/RM1_MHK_FBP.yaml +++ b/Examples/Tune_Cases/RM1_MHK_FBP.yaml @@ -43,12 +43,12 @@ controller_params: 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: 1.0 # Torque controller desired damping ratio [-] - omega_vs: 0.8 # Torque controller desired natural frequency [rad/s] + U_pc: [1.5, 2, 2.5] + # interp_type: sigma + zeta_pc: [1., 1, 1] # Pitch controller desired damping ratio [-] + omega_pc: [0.35, 0.35, 0.35] # Pitch controller desired natural frequency [rad/s] + zeta_vs: 0.7 # Torque controller desired damping ratio [-] + omega_vs: 0.3 # 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) diff --git a/Examples/example_inputs/FASTFarm.fstf b/Examples/example_inputs/FASTFarm.fstf index 51f745d9a..f79cdaa0d 100644 --- a/Examples/example_inputs/FASTFarm.fstf +++ b/Examples/example_inputs/FASTFarm.fstf @@ -3,7 +3,7 @@ FAST.Farm input file, using two turbines separated by 3D downstream and an offse --- SIMULATION CONTROL --- False Echo - Echo input data to .ech? (flag) FATAL AbortLevel - Error level when simulation should abort (string) {"WARNING", "SEVERE", "FATAL"} -60.0 TMax - Total run time (s) [>=0.0] +20.0 TMax - Total run time (s) [>=0.0] 2 Mod_AmbWind - Ambient wind model (-) (switch) {1: high-fidelity precursor in VTK format, 2: one InflowWind module, 3: multiple instances of InflowWind module} 1 Mod_WaveField - Wave field handling (-) (switch) {1: use individual HydroDyn inputs without adjustment, 2: adjust wave phases based on turbine offsets from farm origin} 0 Mod_SharedMooring - Shared mooring system model (switch) {0: None, 3=MoorDyn}} @@ -32,6 +32,11 @@ False ChkWndFiles - Check all the ambient wind files for dat 16 NY_High - Number of high-resolution spatial nodes in Y direction for wind data interpolation (-) [>=2] 16 NZ_High - Number of high-resolution spatial nodes in Z direction for wind data interpolation (-) [>=2] "17c_FASTFarm_IW.dat" InflowFile - Name of file containing InflowWind module input parameters (quoted string) +--- AMBIENT WIND: AMReX MODULE --- [used only for Mod_AmbWind=4] +"data/subvolume" WindDirPrefix - Directory prefix of AMReX wind sub-volumes {0=low-res, 1+=high-res} (quoted string) +24 DirStartIndex - AMReX sub-volume directory suffix to consider as time=0 (quoted string) +4.0 DT_Low-AMReX - Time step for low -resolution wind data interpolation; will be used as the global FAST.Farm time step (s) [>0.0] +0.5 DT_High-AMReX - Time step for high-resolution wind data interpolation (s) [>0.0] --- WIND TURBINES --- 2 NumTurbines - Number of wind turbines (-) [>=1] [last 6 columns below used only for Mod_AmbWind=2 or 3] WT_X WT_Y WT_Z WT_FASTInFile X0_High Y0_High Z0_High dX_High dY_High dZ_High @@ -43,8 +48,9 @@ WT_X WT_Y WT_Z WT_FASTInFile X0_High Y0_High Z0_High dX_High dY_H 125 RotorDiamRef - Reference turbine rotor diameter for wake calculations (m) [>0.0] 5.0 dr - Radial increment of radial finite-difference grid (m) [>0.0] 40 NumRadii - Number of radii in the radial finite-difference grid (-) [>=2] -136 NumPlanes - Number of wake planes (-) [>=2] -0.17 f_c - Cutoff (corner) frequency of the low-pass time-filter for the wake advection, deflection, and meandering model [recommended=1.28*U0/R] (Hz) [>0.0] or DEFAULT [DEFAULT=12.5/R, R estimated from dr and NumRadii, not recommended] +DEFAULT NumDFull - Distance of full wake propagation, expressed as a multiple of RotorDiamRef [>0.0] or DEFAULT [DEFAULT=15] +DEFAULT NumDBuff - Length of wake propagation buffer region, expressed as a multiple of RotorDiamRef [>=0.0] or DEFAULT [DEFAULT=5] +0.14 f_c - Cutoff (corner) frequency of the low-pass time-filter for the wake advection, deflection, and meandering model [recommended=1.28*U0/R] (Hz) [>0.0] or DEFAULT [DEFAULT=12.5/R, R estimated from dr and NumRadii, not recommended] DEFAULT C_HWkDfl_O - Calibrated parameter in the correction for wake deflection defining the horizontal offset at the rotor (m ) or DEFAULT [DEFAULT= 0.0 ] DEFAULT C_HWkDfl_OY - Calibrated parameter in the correction for wake deflection defining the horizontal offset at the rotor scaled with yaw error (m/deg) or DEFAULT [DEFAULT= 0.0 if Mod_Wake is 2, 0.3 otherwise] DEFAULT C_HWkDfl_x - Calibrated parameter in the correction for wake deflection defining the horizontal offset scaled with downstream distance (- ) or DEFAULT [DEFAULT= 0.0 ] diff --git a/README.md b/README.md index 49b12259c..26ed52899 100644 --- a/README.md +++ b/README.md @@ -42,6 +42,49 @@ The currently compatible version can be found in the ``environment.yml`` file. OpenFAST inputs used in the controller tuning process should be consistent with that version. +## Precompiled ROSCO Libraries (No Compilation Required) +If you do not want to compile the ROSCO controller from source, you can extract precompiled shared libraries from the ROSCO conda package on conda-forge. + +### Finding the Package +1. Go to the [ROSCO conda-forge page](https://anaconda.org/conda-forge/rosco/files) and find the version you need. +2. Select the `.conda` file for your platform: + - **Linux:** `linux-64` + - **macOS (Intel):** `osx-64` + - **macOS (Apple Silicon):** `osx-arm64` + - **Windows:** `win-64` + +### Extracting the Library +A `.conda` file is a ZIP archive. To extract the shared library: + +```bash +# Download the .conda file (example for linux-64) +# Unzip the outer .conda archive +unzip rosco-*.conda -d rosco_conda + +# Inside, unzip pkg-rosco-*.tar.zst (or use tar if available) +cd rosco_conda +tar --use-compress-program=unzstd -xf pkg-rosco-*.tar.zst + +# The shared library will be located under lib/ +# Linux: lib/libdiscon.so +# macOS: lib/libdiscon.dylib +# Windows: Library/bin/libdiscon.dll +``` + +On macOS or Linux, you may need to install `zstd` to decompress the inner archive: +```bash +# conda +conda install zstd +# or brew (macOS) +brew install zstd +``` + +On Windows, tools like [7-Zip](https://www.7-zip.org/) can open both the `.conda` (ZIP) and `.tar.zst` archives directly. + +### Usage +Once extracted, point your OpenFAST `ServoDyn` input file's `DLL_FileName` to the path of the extracted `libdiscon` library. + + ## Contributing If it wasn't obvious from _open-source_ being in the title of the tool-set, this is an open-source code base that we would love for the community to contribute to. If you find yourself fixing any bugs, writing new routines, or even making small typo changes, please submit a [pull request](https://github.com/NREL/ROSCO/pulls). diff --git a/environment.yml b/environment.yml index 060965c11..9c38af30a 100644 --- a/environment.yml +++ b/environment.yml @@ -20,7 +20,7 @@ dependencies: - treon - wisdem >=3.16 - zeromq - - openfast=4.2 - - openfast-io=4.2 + - openfast=5.0 + - openfast-io=5.0 - pip: - control diff --git a/pyproject.toml b/pyproject.toml index d63a66938..2457977b9 100644 --- a/pyproject.toml +++ b/pyproject.toml @@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta" [project] name = "rosco" -version = "2.10.4" +version = "2.10.6" description = "A reference open source controller toolset for wind turbine applications." readme = "README.md" requires-python = ">=3.9" @@ -53,7 +53,7 @@ dependencies = [ "pyzmq", "wisdem", "ruamel.yaml", - "openfast_io~=4.2", + "openfast_io~=5.0", ] # List additional groups of dependencies here (e.g. development diff --git a/rosco/controller/src/ROSCO_IO.f90 b/rosco/controller/src/ROSCO_IO.f90 index 73e57df38..491b1f57c 100644 --- a/rosco/controller/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 v2.10.1 +! This file is automatically generated by write_registry.py using ROSCO v2.10.6 ! For any modification to the registry, please edit the rosco_types.yaml accordingly MODULE ROSCO_IO diff --git a/rosco/controller/src/ROSCO_Types.f90 b/rosco/controller/src/ROSCO_Types.f90 index a843a04cf..bbbb55dc0 100644 --- a/rosco/controller/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 v2.10.1 +! This file is automatically generated by write_registry.py using ROSCO v2.10.6 ! For any modification to the registry, please edit the rosco_types.yaml accordingly MODULE ROSCO_Types @@ -7,7 +7,7 @@ MODULE ROSCO_Types USE Constants IMPLICIT NONE -Character(*), PARAMETER :: rosco_version = '2.10.1' ! ROSCO version +Character(*), PARAMETER :: rosco_version = '2.10.6' ! ROSCO version TYPE, PUBLIC :: ControlParameters INTEGER(IntKi) :: ZMQ_ID ! 0000 - 9999, Identifier of the rosco, used for zeromq interface only diff --git a/rosco/toolbox/ofTools/case_gen/CaseLibrary.py b/rosco/toolbox/ofTools/case_gen/CaseLibrary.py index b6d81f9b2..a1d563752 100644 --- a/rosco/toolbox/ofTools/case_gen/CaseLibrary.py +++ b/rosco/toolbox/ofTools/case_gen/CaseLibrary.py @@ -71,7 +71,7 @@ def base_op_case(): case_inputs[("Fst","OutFileFmt")] = {'vals':[3], 'group':0} # DOFs - case_inputs[("ElastoDyn","GenDOF")] = {'vals':['True'], 'group':0} + # case_inputs[("ElastoDyn","GenDOF")] = {'vals':['True'], 'group':0} if False: case_inputs[("ElastoDyn","YawDOF")] = {'vals':['True'], 'group':0} case_inputs[("ElastoDyn","FlapDOF1")] = {'vals':['False'], 'group':0} @@ -555,7 +555,7 @@ def sweep_yaml_input(start_group, **control_sweep_opts): ''' - required_inputs = ['control_param', 'param_values'] + required_inputs = [('control_param','discon_param'), 'param_values'] check_inputs(control_sweep_opts,required_inputs) # load default params @@ -575,7 +575,11 @@ def sweep_yaml_input(start_group, **control_sweep_opts): 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 + + if 'control_param' in control_sweep_opts: + controller_params[control_sweep_opts['control_param']] = param_value + elif 'discon_param' in control_sweep_opts: + controller_params['DISCON'][control_sweep_opts['discon_param']] = param_value controller = ROSCO_controller.Controller(controller_params) # tune default controller @@ -597,8 +601,16 @@ def sweep_yaml_input(start_group, **control_sweep_opts): 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') + if type(ri) == str: + if ri not in control_sweep_opts: + raise Exception(f'{ri} is required for this control sweep') + else: + have_a_req_input = False + for rk in ri: + if rk in control_sweep_opts: + have_a_req_input = True + if not have_a_req_input: + raise Exception(f'One of {ri} is required for this control sweep') diff --git a/rosco/toolbox/ofTools/fast_io/output_processing.py b/rosco/toolbox/ofTools/fast_io/output_processing.py index 9eff7829d..f728480df 100644 --- a/rosco/toolbox/ofTools/fast_io/output_processing.py +++ b/rosco/toolbox/ofTools/fast_io/output_processing.py @@ -365,8 +365,16 @@ def load_ascii_output(filename): info['channels'] = l.split() info['attribute_units'] = [unit[1:-1] for unit in f.readline().split()] - # Data, up to end of file or empty line (potential comment line at the end) - data = np.array([l.strip().split() for l in takewhile(lambda x: len(x.strip())>0, f.readlines())]).astype(np.float64) + # Read lines until a blank line (trailing comments may follow) + lines = takewhile(lambda x: len(x.strip()) > 0, f.readlines()) + + # Split each line into tokens, padding/truncating rows with wrong column count with nan + n_cols = len(info['channels']) + rows = [line.strip().split() for line in lines] + rows = [row if len(row) == n_cols else row[:n_cols] + ['nan'] * (n_cols - len(row)) for row in rows] + + # Convert to numeric array + data = np.array(rows, dtype=np.float64) return data, info diff --git a/rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb b/rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb index 6bed304ca..593c0dbbc 100644 --- a/rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb +++ b/rosco/toolbox/ofTools/fast_io/plot_FAST.ipynb @@ -9,7 +9,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 6, "metadata": {}, "outputs": [], "source": [ @@ -36,7 +36,7 @@ "import pandas as pd\n", "\n", "import matplotlib.pyplot as plt\n", - "# %matplotlib\n", + "%matplotlib ipympl\n", "\n", "i_fig = 0" ] @@ -50,7 +50,7 @@ }, { "cell_type": "code", - "execution_count": 13, + "execution_count": 40, "metadata": {}, "outputs": [], "source": [ @@ -58,7 +58,43 @@ " # '/Users/dzalkind/Tools/ROSCO3/Examples/examples_out/12_ipc_sim/NREL2p8/ramp/base/NREL2p8_0.out',\n", " # '/Users/dzalkind/Tools/ROSCO3/Examples/examples_out/12_ipc_sim/NREL2p8/ramp/base/NREL2p8_1.out',\n", " # '/Users/dzalkind/Tools/ROSCO3/Examples/examples_out/12_ipc_sim/NREL2p8/ramp/base/NREL2p8_2.out',\n", - " '/Users/dzalkind/Tools/ROSCO3/Examples/examples_out/12_ipc_sim/NREL2p8/ramp/base/NREL2p8_3.out',\n", + " # '/Users/dzalkind/Tools/ROSCO3/Examples/examples_out/12_ipc_sim/NREL2p8/ramp/base/NREL2p8_3.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/12_ipc_sim/NREL2p8_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/0_baseline/RM1_MHK_0.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/1_const_torque/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/2_startup/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/3_sweep_fl_gain/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/3_sweep_fl_gain/RM1_MHK_2.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/3_sweep_fl_gain/RM1_MHK_4.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/4_sweep_omega_pc/RM1_MHK_0.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/4_sweep_omega_pc/RM1_MHK_1.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/4_sweep_omega_pc/RM1_MHK_2.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/4_sweep_omega_pc/RM1_MHK_3.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/5_remove_filters/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/6_sweep_kp/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/6_sweep_kp/RM1_MHK_2.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/6_sweep_kp/RM1_MHK_4.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/7_try_high_kp_low_om/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/8_sweep_freq/RM1_MHK_0.out', # This was a good one\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/8_sweep_freq/RM1_MHK_1.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/8_sweep_freq/RM1_MHK_2.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/9_no_gen/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/10_no_ptfm/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/11_update_hydro/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/12_update_moor/RM1_MHK_0.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/14_no_gen/RM1_MHK_0.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/15_new_model_ic/RM1_MHK_0.outb',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/16_check_cycle/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/17_cook_setup/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/18_no_cavit/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/19_long_run/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/20_subset_no_waves/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/21_slow_control/RM1_MHK_0.out',\n", + " '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/22_peak_shaving/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/24_speed_up/RM1_MHK_0.out',\n", + " '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/25_fast_const_pwr/RM1_MHK_0.out',\n", + " # '/Users/dzalkind/Tools/ROSCO-main/Examples/examples_out/26_MHK/23_const_torque/RM1_MHK_0.out',\n", + "\n", "]\n", "\n", "# outfiles" @@ -66,19 +102,57 @@ }, { "cell_type": "code", - "execution_count": 25, + "execution_count": 41, "metadata": {}, "outputs": [ { "data": { - "image/png": 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", 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", + "text/html": [ + "\n", + "
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\n", + " " + ], + "text/plain": [ + "Canvas(toolbar=Toolbar(toolitems=[('Home', 'Reset original view', 'home', 'home'), ('Back', 'Back to previous …" + ] }, + "metadata": {}, "output_type": "display_data" } ], @@ -86,19 +160,20 @@ "output_ext = '.out'\n", "plt.rcParams[\"figure.figsize\"] = [9,12]\n", "\n", - "ROSCO = True\n", - "ROSCO2 = True\n", + "ROSCO = False\n", + "ROSCO2 = False\n", "\n", "# Define Plot cases \n", "cases = {}\n", "# cases['Gen. Speed Sigs.'] = ['Wind1VelX', 'BldPitch1', 'GenTq', 'GenSpeed','TwrBsMyt','GenPwr','RootMyb1']#,'PtfmPitch','PtfmYaw','NacYaw']\n", - "cases['Gen. Speed Sigs.'] = ['Wind1VelX','BldPitch1', 'GenTq', 'GenSpeed','TwrBsMyt','GenPwr','RootMyb1']#,'PtfmPitch','PtfmYaw','NacYaw']\n", + "cases['Gen. Speed Sigs.'] = ['Wind1VelX','BldPitch1', 'GenTq', 'RotSpeed','RootMyb1','GenPwr','PtfmPitch']#,'','PtfmYaw','NacYaw']\n", "# # cases['Debug'] = ['IPDefl1','OoPDefl1','Azimuth','RotTorq']#,'PtfmPitch','PtfmYaw','NacYaw']\n", "# cases['Plt. Control Sigs.'] = ['Fl_PitCom', 'PC_MinPit']\n", - "# cases['Platform Motion'] = ['PtfmSurge', 'PtfmSway', 'PtfmHeave', 'PtfmPitch','PtfmRoll','PtfmYaw']\n", + "cases['Platform Motion'] = ['Wave1Elev','PtfmSurge', 'PtfmSway', 'PtfmHeave', 'PtfmPitch','PtfmRoll','PtfmYaw']\n", "# # cases['Tower Loads'] = ['TwrBsFxt','TwrBsFyt', 'TwrBsFzt', 'TwrBsMxt', 'TwrBsMyt','TwrBsMzt']\n", "# # cases['Rot Thrust'] = ['RtVAvgxh','BldPitch1','RotThrust']\n", - "# cases['IPC'] = ['PitCom','PitComAct']\n", + "# cases['IPC'] = [('PC_PitComT','BlPitchCMeas'),'PitComAct']\n", + "# cases['SPS'] = ['SS_DelOmega','PC_RefSpd','VS_RefSpd','GenSpeed']\n", "# # cases['IPC'] = ['PtfmYaw','YawBrMzp','YawBrMyp']\n", "\n", "# cases['Gen. Speed Sigs.'] = ['Wind1VelX', 'GenPwr', 'RotSpeed', 'GenSpeed', 'GenTq', 'BldPitch1','B1RootMyr'] #, 'PtfmPitch','PtfmYaw'] #,'PtfmPitch','PtfmYaw','NacYaw']\n", @@ -159,56 +234,173 @@ }, { "cell_type": "code", - "execution_count": 70, + "execution_count": 9, + "metadata": {}, + "outputs": [], + "source": [ + "# Create hub height wind speed for RM1 that's half a cycle\n", + "\n", + "period = 43200 * 2\n", + "\n", + "t = np.arange(0,period/2,0.1)\n", + "max_speed = 4\n", + "\n", + "uu = max_speed * (np.sin(2*np.pi*t/period))\n", + "\n", + "plt.plot(t, uu)\n", + "\n", + "from rosco.toolbox.ofTools.case_gen import HH_WindFile\n", + "\n", + "hh_wind = HH_WindFile.HH_WindFile(**{\n", + " 'TMax': period / 2,\n", + " 'dt': t[1]-t[0]\n", + "})\n", + "hh_wind.wind_speed = uu\n", + "hh_wind.time = t\n", + "hh_wind.resample()\n", + "\n", + "hh_wind.filename = f'/Users/dzalkind/Tools/ROSCO-main/Examples/26_MHK/RM1_HH_WindFile_p{period}_u{max_speed}.txt'\n", + "\n", + "hh_wind.write()\n", + "\n", + "\n", + "\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "# Read the Cook Inlet file\n", + "cook_inlet_file = '/Users/dzalkind/Tools/ROSCO-main/Examples/26_MHK/Cook_Inlet.txt'\n", + "\n", + "# Read the data\n", + "# cook_data = pd.read_csv(cook_inlet_file, delim_whitespace=True, skip_rows=12,\n", + "# names=['Time', 'Wind_Speed','Wind_dir','Vert_speed','Horiz_shear','P_vert_shear','L_vert_shear','Gust_speed','Upflow'])\n", + "\n", + "# # Display basic info about the data\n", + "# print(f\"Cook Inlet data shape: {cook_data.shape}\")\n", + "# print(f\"Time range: {cook_data['Time'].min():.1f} to {cook_data['Time'].max():.1f} seconds\")\n", + "# print(f\"Wind speed range: {cook_data['Wind_Speed'].min():.3f} to {cook_data['Wind_Speed'].max():.3f} m/s\")\n", + "\n", + "# # Plot the Cook Inlet data\n", + "# plt.figure(figsize=(12, 6))\n", + "# plt.plot(cook_data['Time'], cook_data['Wind_Speed'])\n", + "# plt.xlabel('Time (s)')\n", + "# plt.ylabel('Wind Speed (m/s)')\n", + "# plt.title('Cook Inlet Wind Speed Time Series')\n", + "# plt.grid(True)\n", + "# plt.show()\n", + "\n", + "# ! Time Wind Wind Vertical Horiz. Pwr.Law Lin.Vert. Gust Upflow \n", + "# ! Speed Dir Speed Shear Vert.Shr Shear Speed Angle \n", + "\n", + "# cook_data.columns = ['Time', 'Wind_Speed','Wind_dir','Vert_speed','Horiz_shear','P_vert_shear','L_vert_shear','Gust_speed','Upflow']\n", + "# cook_data.head()\n", + "# 1+1\n", + "\n", + "cook_data\n", + "\n" + ] + }, + { + "cell_type": "code", + "execution_count": 20, "metadata": {}, "outputs": [ { - "data": { - "text/plain": [ - "array([14.97, 15. , 15.02, ..., 90. , 90. , 90. ])" - ] - }, - "execution_count": 70, - "metadata": {}, - "output_type": "execute_result" + "name": "stdout", + "output_type": "stream", + "text": [ + "Subset data written to: /Users/dzalkind/Tools/ROSCO-main/Examples/26_MHK/Cook_Inlet_subset.txt\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "/var/folders/hy/62hqjp8d0msbfgf6r6jvj5cw3rr_2y/T/ipykernel_63012/852128302.py:6: FutureWarning: The 'delim_whitespace' keyword in pd.read_csv is deprecated and will be removed in a future version. Use ``sep='\\s+'`` instead\n", + " cook_data = pd.read_csv(cook_inlet_file, delim_whitespace=True, skiprows=header_lines,\n", + "/var/folders/hy/62hqjp8d0msbfgf6r6jvj5cw3rr_2y/T/ipykernel_63012/852128302.py:14: SettingWithCopyWarning: \n", + "A value is trying to be set on a copy of a slice from a DataFrame.\n", + "Try using .loc[row_indexer,col_indexer] = value instead\n", + "\n", + "See the caveats in the documentation: https://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy\n", + " new_cd['Time'] = new_cd['Time'] - time_subset[0]\n" + ] } ], "source": [ - "fast_out[1]['PtfmHeave'].mean()\n", + "cook_inlet_file = '/Users/dzalkind/Tools/ROSCO-main/Examples/26_MHK/Cook_Inlet.txt'\n", "\n", - "fast_out[0]['BldPitch1']" + "header_lines = 13\n", + "time_subset = [6000, 7000] # seconds\n", + "\n", + "cook_data = pd.read_csv(cook_inlet_file, delim_whitespace=True, skiprows=header_lines,\n", + "names=['Time', 'Wind_Speed','Wind_dir','Vert_speed','Horiz_shear','P_vert_shear','L_vert_shear','Gust_speed','Upflow'])\n", + "\n", + "cook_data\n", + "\n", + "inds = np.bitwise_and(cook_data['Time'] >= time_subset[0], cook_data['Time'] <= time_subset[1])\n", + "\n", + "new_cd = cook_data.loc[inds]\n", + "new_cd['Time'] = new_cd['Time'] - time_subset[0]\n", + "\n", + "new_cd\n", + "\n", + "# Write the new data back to a file with the same header\n", + "output_file = '/Users/dzalkind/Tools/ROSCO-main/Examples/26_MHK/Cook_Inlet_subset.txt'\n", + "\n", + "# Read the original header (first header_lines lines)\n", + "with open(cook_inlet_file, 'r') as f:\n", + " header_lines = [f.readline() for _ in range(header_lines)]\n", + "\n", + "# Write the new file with original header and subset data\n", + "with open(output_file, 'w') as f:\n", + " # Write header\n", + " for line in header_lines:\n", + " f.write(line)\n", + " \n", + " # Write the subset data\n", + " new_cd.to_csv(f, sep='\\t', index=False, header=False, float_format='%12.6f')\n", + "\n", + "print(f\"Subset data written to: {output_file}\")\n", + "\n" + ] + }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "2 * np.pi / 10" ] }, { "cell_type": "code", - "execution_count": 16, + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "60 / 12" + ] + }, + { + "cell_type": "code", + "execution_count": null, "metadata": { "tags": [] }, - "outputs": [ - { - "data": { - "text/plain": [ - "[]" - ] - }, - "execution_count": 16, - "metadata": {}, - "output_type": "execute_result" - }, - { - "data": { - "image/png": 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" - ], - "text/plain": [ - " fq_0 psd_0 fq_1 psd_1 fq_2 \\\n", - "0 0.000000 1.671551e+10 0.000000 1.965097e+10 0.000000 \n", - "1 0.000153 6.689014e+09 0.000153 7.170768e+09 0.000153 \n", - "2 0.000305 3.124308e+07 0.000305 1.730212e+06 0.000305 \n", - "3 0.000458 4.563406e+07 0.000458 6.438544e+06 0.000458 \n", - "4 0.000610 3.262825e+07 0.000610 4.078779e+06 0.000610 \n", - "... ... ... ... ... ... \n", - "262140 39.999390 9.375684e-05 39.999390 2.434349e-04 39.999390 \n", - "262141 39.999542 1.289097e-05 39.999542 8.927871e-05 39.999542 \n", - "262142 39.999695 5.578019e-05 39.999695 6.308301e-05 39.999695 \n", - "262143 39.999847 6.688827e-05 39.999847 9.410833e-05 39.999847 \n", - "262144 40.000000 6.043648e-07 40.000000 5.951048e-05 40.000000 \n", - "\n", - " psd_2 \n", - "0 1.081063e+10 \n", - "1 3.754186e+09 \n", - "2 4.290867e+06 \n", - "3 1.180544e+06 \n", - "4 7.362297e+05 \n", - "... ... \n", - "262140 1.894379e-04 \n", - "262141 3.235635e-04 \n", - "262142 2.832569e-05 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# plot thrust spectra\n", "\n", @@ -473,30 +473,9 @@ }, { "cell_type": "code", - "execution_count": 11, + "execution_count": null, "metadata": {}, - "outputs": [ - { - "name": "stdout", - "output_type": "stream", - "text": [ - "(PtfmYaw,0) max period = 150.00041666666667\n", - "(PtfmYaw,1) max period = 85.71452380952381\n" - ] - }, - { - "data": { - "image/png": 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", - "text/plain": [ - "
" - ] - }, - "metadata": { - "needs_background": "light" - }, - "output_type": "display_data" - } - ], + "outputs": [], "source": [ "# Plot Spectral\n", "\n", @@ -512,13 +491,40 @@ "\n", "# op" ] + }, + { + "cell_type": "code", + "execution_count": 29, + "metadata": {}, + "outputs": [ + { + "data": { + "text/plain": [ + "np.float64(3.1111608275603704)" + ] + }, + "execution_count": 29, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "np.degrees(0.0543)" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [] } ], "metadata": { "kernelspec": { - "display_name": "weis-env3", + "display_name": "rosco-main", "language": "python", - "name": "weis-env3" + "name": "python3" }, "language_info": { "codemirror_mode": { @@ -530,7 +536,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.8.13" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/rosco/toolbox/turbine.py b/rosco/toolbox/turbine.py index d2a7ea5c1..d37790740 100644 --- a/rosco/toolbox/turbine.py +++ b/rosco/toolbox/turbine.py @@ -169,20 +169,8 @@ def load_from_fast( fast.read_MainInput() - # file - ed_file = os.path.join(fast.FAST_directory, fast.fst_vt['Fst']['EDFile']) + ed_file = os.path.realpath(os.path.join(fast.FAST_directory, fast.fst_vt['Fst']['EDFile'])) fast.read_ElastoDyn(ed_file) - ed_blade_file = os.path.join(os.path.dirname(ed_file), fast.fst_vt['ElastoDyn']['BldFile1']) - - if fast.fst_vt['Fst']['CompElast'] ==1: - fast.read_ElastoDynBlade(ed_blade_file) - elif fast.fst_vt['Fst']['CompElast'] ==2: - bd_file = os.path.join(fast.FAST_directory, fast.fst_vt['Fst']['BDBldFile(1)']) - fast.read_BeamDyn(bd_file) - bd_blade_file = os.path.join(os.path.dirname(bd_file), fast.fst_vt['BeamDyn'][0]['BldFile']) - fast.read_BeamDynBlade(bd_blade_file) - else: - Warning('No ElastoDyn or BeamDyn files were provided') fast.read_AeroDyn() @@ -581,11 +569,6 @@ def load_blade_info(self): self.chord = chord self.twist = theta - if self.fast.fst_vt['Fst']['CompElast'] ==1: - self.bld_flapwise_damp = self.fast.fst_vt['ElastoDynBlade'][0]['BldFlDmp1']/100 - elif self.fast.fst_vt['Fst']['CompElast'] ==2: - self.bld_flapwise_damp = self.fast.fst_vt['BeamDynBlade'][0]['mu5'] - class RotorPerformance(): ''' Class RotorPerformance used to find details from rotor performance