RAFT DOE to create Surrogate Model (updated)

.gitignore

@@ -78,6 +78,8 @@ nosetests.xml
 *.log
 *.sql
 *.sqlite
+*.err
+*.smt
 
 # OS generated files #
 ######################

examples/15_RAFT_Studies/README.md

@@ -22,4 +22,25 @@ To optimize the UMaine semi using raft, run
  Two options are provided in this example: `../06_IEA-15-240-RWT/IEA-15-240-RWT_VolturnUS-S.yaml` (original) and `raft_opt_out.yaml`, the optimized output.
 
 
+# RAFT Surrogate Model Training with Design of Experiment
+To create the surrogate model with RAFT simulations, run
+ ```
+ python weis_driver_level1_doe.py
+ ```
+ If parallel execution is possible (e.g., HPC) use slurm script to run with MPI across large number of cpus/nodes
+ ```
+ sbatch weis_driver_level1_doe.sh
+ ```
+ or MPI directly for cpus in a local computer
+ ```
+ mpirun -np 4 python weis_driver_level1_doe.py
+ ```
+
+ In `analysis_options_level1_doe.yaml`, the design variables (control and plant), driver (optimization:flag: False, design_of_experiments:flag: True), and recorder (flag: True, includes: ['*']) can be set up. Variables marked as design_variables (flag: True) are used as inputs, while all other variables are used as outputs of the surrogate model. Not all parameters are supported at this moment. Seven control parameters, diameters of floating platform members, joint locations, rotor diameter are currently implemented.
+
+ Once design of experiment is completed, a surrogate model for each output variable will be trained (in parallel if MPI is used), and recorder file_name.smt (log_opt.smt in the tutorial case) will be created.
+
+ At this moment, surrogate model training is not stable with large number of samples.
+
+ Further design coupling studies and/or surrogate-based optimization studies can be done in separate script files to be developed.
 

examples/15_RAFT_Studies/analysis_options_level1_doe.yaml

@@ -0,0 +1,136 @@
+general:
+    folder_output: outputs/level1_doe
+    fname_output: refturb_output
+
+design_variables:
+  control:
+    ps_percent: #Peak shaving #defalt: 0.85
+      flag: False
+      lower_bound: 0.75
+      upper_bound: 1.0
+    servo:
+      pitch_control:
+        omega: #rad/s  #default: 0.2 
+          flag: True
+          min: 0.1
+          max: 0.7
+        zeta: #rad/s  #default:  1.0
+          flag: True
+          min: 0.7
+          max: 1.5
+        Kp_float: #s  #default:  -10.0
+          flag: True
+          min: -20.0 #-100.0
+          max: 0.0
+        ptfm_freq:  #rad/s default: 0.2
+          flag: True
+          min: 0.1 #0.00001
+          max: 1.5
+      torque_control:
+        omega: #rad/s  #default: 0.12 
+          flag: False
+          min: 0.1
+          max: 0.7
+        zeta: #rad/s  #default: 0.85
+          flag: False
+          min: 0.7
+          max: 1.5
+  floating:
+    members:
+      flag: False
+      groups:
+        - names: [main_column] # Platform sizing: diameter (Center Column)
+          diameter:
+            lower_bound: 6.0 #default: 10
+            upper_bound: 14.0
+            constant: True
+        - names: [column1, column2, column3] # Platform sizing: diameter (Side Columns)
+          diameter:
+            lower_bound: 10.5 #11.0 #10.7 #8.5 # default: 12.5
+            upper_bound: 14.5 #14.5 #16.5
+            constant: True
+        - names: [Y_pontoon_upper1, Y_pontoon_upper2, Y_pontoon_upper3] # Platform sizing: Pantoon upper diameter
+          diameter:
+            lower_bound: 0.71 # default: 0.91
+            upper_bound: 1.11
+            constant: True
+        - names: [Y_pontoon_lower1, Y_pontoon_lower2, Y_pontoon_lower3] # Platform sizing: Pantoon lower diameter
+          diameter:
+            lower_bound: 6.6148 #7.6148 # default: 9.6148
+            upper_bound: 13.6148 #11.6148
+            constant: True
+    joints:
+      flag: False
+      z_coordinate:
+        - names: [main_keel, col1_keel, col2_keel, col3_keel] #Platform sizing: form -20 (keel) to 15 (freeboard)
+          lower_bound: -24.0 #default -20
+          upper_bound: -16.0
+        - names: [main_freeboard, col1_freeboard, col2_freeboard, col3_freeboard] #Platform sizing: form -20 (keel) to 15 (freeboard)
+          lower_bound: 7.0 #default 15
+          upper_bound: 21.0
+      r_coordinate:
+        - names: [col1_keel, col1_freeboard, col2_keel, col2_freeboard, col3_keel, col3_freeboard] #Platform sizing: Spacing
+          lower_bound: 41.57 #51.57 #48.57 #63.57 #42.57 # default: 51.57
+          upper_bound: 61.57 #72.57 #63.57 #60.0
+  rotor_diameter:
+    flag: True
+    minimum: 235.0 #242.23775645
+    maximum: 250.0
+  tower: # does not work for design coupling analysis
+    outer_diameter:
+      flag: False
+      lower_bound: 6.0 # 6.5[m]
+      upper_bound: 7.0
+    section_height:
+      flag: False
+      lower_bound: 13.0 # 5.0[m] I think in default it has 10 sections: 10 *15=150==hub height
+      upper_bound: 18.0
+
+constraints:
+  control:
+    Max_PtfmPitch:
+      flag: True
+      max:  6.757845 #6.74303  #deg
+    Std_PtfmPitch:
+      flag: True
+      max: 2.0 #deg
+    nacelle_acceleration:
+      flag: True
+      max: 3.2667 # m/s^2
+  tower:
+    height_constraint:
+      flag: False
+      lower_bound: 0.1
+      upper_bound: 5.0
+    frequency_1:
+      flag: True
+      lower_bound: 0.35
+      upper_bound: 0.51
+    slope:
+      flag: False
+
+merit_figure: platform_mass  # Merit figure of the optimization problem. The options are 'AEP' - 'LCOE' - 'Cp' - 'blade_mass' - 'blade_tip_deflection'
+
+driver:
+  optimization:
+    flag: False           # Flag to enable optimization
+    solver: COBYLA #LN_COBYLA         # Optimization solver. Other options are 'SLSQP' - 'CONMIN'
+    tol: 1.e-3            # Optimality tolerance
+    max_iter: 300         # Maximum number of iterations (SLSQP)
+  design_of_experiments:
+    flag: True            # Flag to enable design of experiments
+    run_parallel: True    # Flag to run using parallel processing
+    seed: 2
+    generator: LatinHypercube #Uniform #LatinHypercube #FullFact    # Type of input generator. (Uniform)
+    num_samples: 50     # number of samples for (Uniform only)
+    levels: 1
+    skip_doe_if_results_exist: True
+    skip_smt_if_results_exist: True
+    train_surrogate_model: True
+
+recorder:
+  flag: True              # Flag to activate OpenMDAO recorder
+  file_name: log_opt.sql  # Name of OpenMDAO recorder
+  includes: ['*'] #['*raft*','*floating*','*platform*']
+
+

examples/15_RAFT_Studies/modeling_options_level1.yaml

@@ -0,0 +1,119 @@
+General:
+  verbosity: False  # When set to True, the code prints to screen many infos
+  openfast_configuration:
+    use_exe: True
+    allow_fails: True
+    fail_value: 9999
+
+WISDEM:
+  RotorSE:
+    flag: True
+    spar_cap_ss: Spar_Cap_SS
+    spar_cap_ps: Spar_Cap_PS
+    te_ss: TE_reinforcement_SS
+    te_ps: TE_reinforcement_PS
+  TowerSE:
+    flag: True
+  DriveSE:
+    flag: True
+  FloatingSE:
+    flag: True
+  # BOS:
+    # flag: True
+
+Level3: # Options for WEIS fidelity level 3 = nonlinear time domain
+  flag: False
+  simulation:
+    DT: 0.01
+    CompElast: 1
+    CompInflow: 1
+    CompAero: 2
+    CompServo: 1
+    CompHydro: 1
+    CompSub: 0
+    CompMooring: 3
+    CompIce: 0
+    OutFileFmt: 3
+  linearization:
+    Linearize: False
+  ElastoDyn:
+    FlapDOF1: True
+    FlapDOF2: True
+    EdgeDOF: True
+    TeetDOF: False
+    DrTrDOF: False 
+    GenDOF: True
+    YawDOF: False  
+    TwFADOF1 : True
+    TwFADOF2 : True
+    TwSSDOF1 : True
+    TwSSDOF2 : True
+    PtfmSgDOF: True
+    PtfmSwDOF: True
+    PtfmHvDOF: True
+    PtfmRDOF : True
+    PtfmPDOF : True
+    PtfmYDOF : True
+  HydroDyn:
+    WvLowCOff: 0.15708
+    WvHiCOff: 3.2
+    WaveSeed1: 123456789
+    AddBQuad1: [9.23e5, 0.0, 0.0, 0.0, -8.92e6, 0.0]
+    AddBQuad2: [0.0, 9.23e5, 0.0, 8.92e6, 0.0, 0.0]
+    AddBQuad3: [0.0, 0.0, 2.3e6, 0.0, 0.0, 0.0]
+    AddBQuad4: [0.0, 8.92e6, 0.0, 1.68e10, 0.0, 0.0]
+    AddBQuad5: [-8.92e6, 0.0, 0.0, 0.0, 1.68e10, 0.0]
+    AddBQuad6: [0.0, 0.0, 0.0, 0.0, 0.0, 4.8e10]
+    PotMod: 1
+    # WaveMod: 0
+
+Level1:
+  flag: True
+  potential_model_override: 0
+  trim_ballast: 2
+  heave_tol: 1
+  save_designs: True
+
+ROSCO:
+  flag: True
+  SD_Mode: 0
+  PS_Mode: 1
+  ps_percent: 0.85
+  F_LPFType: 2
+  F_NotchType: 2
+  Fl_Mode: 2 
+  tuning_yaml: ../01_aeroelasticse/OpenFAST_models/IEA-15-240-RWT/IEA-15-240-RWT-UMaineSemi/IEA15MW-UMaineSemi.yaml
+  zeta_pc: [1]
+  omega_pc: [0.2]
+  U_pc: [12]
+  zeta_vs: 0.85                     # Torque controller desired damping ratio [-]
+  omega_vs: 0.12  
+  twr_freq: 3.2
+  ptfm_freq: 0.2
+  Kp_float: -10
+
+DLC_driver:
+  metocean_conditions:
+    wind_speed: [4., 6., 8., 10., 12., 14., 16., 18., 20., 22., 24.]
+    wave_height_NSS: [0.83, 0.88, 0.94, 1.03, 1.16, 1.34, 1.57, 1.86, 2.22, 2.62, 3.07]
+    wave_period_NSS: [6.9, 6.96, 7.02, 7.12, 7.25, 7.43, 7.66, 7.94, 8.27, 8.63, 9.01]
+    wave_height_SSS: [6.3, 8, 8, 8.1, 8.5, 8.5, 9.8, 9.8, 9.8, 9.8, 9.9]
+    wave_period_SSS: [11.5, 12.7, 12.7, 12.8, 13.1, 13.1, 14.1, 14.1, 14.1, 14.1, 14.1]
+    wave_height1: 6.98
+    wave_period1: 11.7
+    wave_height50: 10.68
+    wave_period50: 14.2
+  DLCs:
+    - DLC: "1.1"
+      n_seeds: 1
+    # - DLC: "1.3"
+      #   n_seeds: 6
+    - DLC: "1.4"
+    - DLC: "1.5"
+    - DLC: "1.6"
+      n_seeds: 1
+    - DLC: "6.1"
+      n_seeds: 1
+    # - DLC: "6.3"
+      #   n_seeds: 6
+

examples/15_RAFT_Studies/weis_driver_level1_doe.py

@@ -0,0 +1,25 @@
+import os
+import time
+import sys
+
+from weis.glue_code.runWEIS     import run_weis
+from openmdao.utils.mpi  import MPI
+
+run_dir                = os.path.dirname( os.path.realpath(__file__) ) + os.sep
+fname_wt_input         = os.path.join(run_dir,"..","06_IEA-15-240-RWT", "IEA-15-240-RWT_VolturnUS-S.yaml")
+fname_modeling_options = run_dir + "modeling_options_level1.yaml"
+fname_analysis_options = run_dir + "analysis_options_level1_doe.yaml"
+overridden_values = {}
+
+tt = time.time()
+wt_opt, modeling_options, opt_options = run_weis(fname_wt_input, fname_modeling_options, fname_analysis_options, overridden_values)
+
+if MPI:
+    rank = MPI.COMM_WORLD.Get_rank()
+else:
+    rank = 0
+if rank == 0:
+    print('Run time: %f'%(time.time()-tt))
+    sys.stdout.flush()
+
+print('rank = {:}, exiting'.format(rank))

weis/glue_code/runWEIS.py

@@ -11,6 +11,7 @@
 from weis.control.tmd                 import assign_TMD_values
 from weis.aeroelasticse.FileTools     import save_yaml
 from wisdem.inputs.validation         import simple_types
+from weis.surrogate.WTsurrogate       import WindTurbineDOE2SM
 
 fd_methods = ['SLSQP','SNOPT', 'LD_MMA']
 evolutionary_methods = ['DE', 'NSGA2']
@@ -114,6 +115,7 @@ def run_weis(fname_wt_input, fname_modeling_options, fname_opt_options, geometry
     else:
         color_i = 0
         rank = 0
+        max_cores = 1
 
     # make the folder_output relative to the input, if it's a relative path
     analysis_input_dir = os.path.dirname(opt_options['fname_input_analysis'])
@@ -211,13 +213,42 @@ def run_weis(fname_wt_input, fname_modeling_options, fname_opt_options, geometry
                 checks = wt_opt.check_partials(compact_print=True)
 
         sys.stdout.flush()
+
+        # DOE and SMT skip logics
+        SKIP_DRIVER = False
+        SKIP_SMT = False
+        sm_filename = os.path.join(folder_output, os.path.splitext(opt_options['recorder']['file_name'])[0] + '.smt')
+        sql_filename = os.path.join(folder_output, opt_options['recorder']['file_name'])
+        if MPI and max_cores>1:
+            sql_filename += '_{:}'.format(rank)
+        if opt_options['opt_flag'] and opt_options['driver']['design_of_experiments']['flag']: # if DOE enabled
+            # Skip DOE Driver if SQL file exists
+            if opt_options['driver']['design_of_experiments']['skip_doe_if_results_exist']: # if DOE skip flag set
+                if MPI:
+                    doe_file_exist = MPI.COMM_WORLD.gather(os.path.isfile(sql_filename), root=0)
+                    doe_file_exist = MPI.COMM_WORLD.bcast(doe_file_exist, root=0)
+                else:
+                    doe_file_exist = [os.path.isfile(sql_filename)]
+                # If sql files exist for all MPI ranks, and no additional sql file exists outside of MPI size, set skip flag
+                if all(doe_file_exist) and not os.path.isfile(os.path.join(folder_output, opt_options['recorder']['file_name']) + '_{:}'.format(max_cores)):
+                    SKIP_DRIVER = True
+                    if (not MPI) or (MPI and rank == 0):
+                        print('File {:} exists. Skipping the design of experiments.'.format(sql_filename))
+            # Skip SM Training if SMT file exists
+            if opt_options['driver']['design_of_experiments']['skip_smt_if_results_exist']: # if SMT skip flag set
+                if os.path.isfile(sm_filename):
+                    SKIP_SMT = True
+                    if (not MPI) or (MPI and rank == 0):
+                        print('File {:} exists. Skipping the design of experiments.'.format(sm_filename))
+
         # Run openmdao problem
         if opt_options['opt_flag']:
-            wt_opt.run_driver()
+            if not SKIP_DRIVER:
+                wt_opt.run_driver()
         else:
             wt_opt.run_model()
 
-        if (not MPI) or (MPI and rank == 0):
+        if ((not MPI) or (MPI and rank == 0)) and (not SKIP_DRIVER):
             # Save data coming from openmdao to an output yaml file
             froot_out = os.path.join(folder_output, opt_options['general']['fname_output'])
             # Remove the fst_vt key from the dictionary and write out the modeling options
@@ -255,6 +286,16 @@ def run_weis(fname_wt_input, fname_modeling_options, fname_opt_options, geometry
     if MPI and color_i < 1000000:
         MPI.COMM_WORLD.Barrier()
 
+    # If design_of_experiment, recorder flag, train_surrogate_model are all True,
+    # collect sql files and create smt object
+    if opt_options['opt_flag'] and (not SKIP_SMT):
+        if opt_options['driver']['design_of_experiments']['flag'] and opt_options['recorder']['flag']:
+            if opt_options['driver']['design_of_experiments']['train_surrogate_model']:
+                WTSM = WindTurbineDOE2SM()
+                WTSM.read_doe(sql_filename, modeling_options, opt_options) # Parallel reading if MPI
+                WTSM.train_sm() # Parallel training if MPI
+                WTSM.write_sm(sm_filename) # Saving will be done in rank=0
+
     if rank == 0:
         return wt_opt, modeling_options, opt_options
     else: