Accept Element Callbacks with TACS and ESP/CAPS + Blade Stiffener Example (#308)

* Blade stiffened callback example with new TACS component write-outs from ESP/CAPS

Author: sean-engelstad

examples/framework/tacs_oneway_naca_wing/1_tacs_sizing_opt.py

@@ -132,8 +132,8 @@
     model=f2f_model,
     comm=comm,
     nprocs=1,
-    bdf_file=tacs_aim.dat_file_path,
-    prefix=tacs_aim.analysis_dir,
+    bdf_file=tacs_aim.root_dat_file_path,
+    prefix=tacs_aim.root_analysis_dir,
 )
 solvers.flow.copy_struct_mesh()
 null_driver = NullDriver(solvers, model=f2f_model, transfer_settings=None)

examples/framework/tacs_oneway_naca_wing/2_tacs_sizing_and_shape_opt.py

@@ -143,8 +143,8 @@
     model=f2f_model,
     comm=comm,
     nprocs=1,
-    bdf_file=tacs_aim.dat_file_path,
-    prefix=tacs_aim.analysis_dir,
+    bdf_file=tacs_aim.root_dat_file_path,
+    prefix=tacs_aim.root_analysis_dir,
 )
 solvers.flow.copy_struct_mesh()
 null_driver = NullDriver(solvers, model=f2f_model, transfer_settings=None)

examples/framework/tacs_oneway_naca_wing/3_tacs_sizing_opt_stringer.py examples/framework/tacs_oneway_naca_wing/3_tacs_blade_stiffened.py

@@ -2,13 +2,17 @@
 Sean Engelstad, May 2023
 GT SMDO Lab, Dr. Graeme Kennedy
 OnewayStructDriver example
+
+Source for callback: Alasdair Christison Gray
 """
 
 from funtofem import *
 from tacs import caps2tacs
 import openmdao.api as om
 from mpi4py import MPI
 
+from _blade_callback import blade_elemCallBack
+
 # --------------------------------------------------------------#
 # Setup CAPS Problem and FUNtoFEM model - NOTE: not complete, needs stringer PR
 # --------------------------------------------------------------#
@@ -31,50 +35,32 @@
 )
 tacs_aim = tacs_model.tacs_aim
 
-aluminum = caps2tacs.Isotropic.aluminum()
-aluminum_stringer = caps2tacs.Orthotropic.smeared_stringer(
-    aluminum, area_ratio=0.5
-).register_to(tacs_model)
-
 # setup the thickness design variables + automatic shell properties
 # using Composite functions, this part has to go after all funtofem variables are defined...
 nribs = int(tacs_model.get_config_parameter("nribs"))
 nspars = int(tacs_model.get_config_parameter("nspars"))
 nOML = int(tacs_aim.get_output_parameter("nOML"))
 
+null_material = caps2tacs.Orthotropic.null().register_to(tacs_model)
+
 init_thickness = 0.08
 for irib in range(1, nribs + 1):
     name = f"rib{irib}"
-    caps2tacs.CompositeProperty.one_ply(
-        caps_group=name,
-        material=aluminum_stringer,
-        thickness=init_thickness,
-        ply_angle=0,
-    ).register_to(tacs_model)
+    caps2tacs.CompositeProperty.null(name, null_material).register_to(tacs_model)
     Variable.structural(name, value=init_thickness).set_bounds(
         lower=0.01, upper=0.2, scale=100.0
     ).register_to(wing)
 
 for ispar in range(1, nspars + 1):
     name = f"spar{ispar}"
-    caps2tacs.CompositeProperty.one_ply(
-        caps_group=name,
-        material=aluminum_stringer,
-        thickness=init_thickness,
-        ply_angle=0,
-    ).register_to(tacs_model)
+    caps2tacs.CompositeProperty.null(name, null_material).register_to(tacs_model)
     Variable.structural(name, value=init_thickness).set_bounds(
         lower=0.01, upper=0.2, scale=100.0
     ).register_to(wing)
 
 for iOML in range(1, nOML + 1):
     name = f"OML{iOML}"
-    caps2tacs.CompositeProperty.one_ply(
-        caps_group=name,
-        material=aluminum_stringer,
-        thickness=init_thickness,
-        ply_angle=0,
-    ).register_to(tacs_model)
+    caps2tacs.CompositeProperty.null(name, null_material).register_to(tacs_model)
     Variable.structural(name, value=init_thickness).set_bounds(
         lower=0.01, upper=0.2, scale=100.0
     ).register_to(wing)
@@ -91,51 +77,52 @@
 
 # make the scenario(s)
 tacs_scenario = Scenario.steady("tacs", steps=100)
-Function.mass().optimize(scale=1.0e-2, objective=True, plot=True).register_to(
-    tacs_scenario
-)
 Function.ksfailure(ks_weight=10.0).optimize(
     scale=30.0, upper=0.267, objective=False, plot=True
 ).register_to(tacs_scenario)
+Function.mass().optimize(scale=1.0e-2, objective=True, plot=True).register_to(
+    tacs_scenario
+)
 tacs_scenario.register_to(f2f_model)
 
 # make the composite functions for adjacency constraints
 variables = f2f_model.get_variables()
-adjacency_ratio = 2.0
+adj_value = 0.002
 adjacency_scale = 10.0
 for irib in range(
     1, nribs
 ):  # not (1, nribs+1) bc we want to do one less since we're doing nribs-1 pairs
     left_rib = f2f_model.get_variables(names=f"rib{irib}")
     right_rib = f2f_model.get_variables(names=f"rib{irib+1}")
     # make a composite function for relative diff in rib thicknesses
-    adjacency_rib_constr = (left_rib - right_rib) / left_rib
+    adjacency_rib_constr = left_rib - right_rib
     adjacency_rib_constr.set_name(f"rib{irib}-{irib+1}").optimize(
-        lower=-adjacency_ratio, upper=adjacency_ratio, scale=1.0, objective=False
+        lower=-adj_value, upper=adj_value, scale=1.0, objective=False
     ).register_to(f2f_model)
 
 for ispar in range(1, nspars):
     left_spar = f2f_model.get_variables(names=f"spar{ispar}")
     right_spar = f2f_model.get_variables(names=f"spar{ispar+1}")
     # make a composite function for relative diff in spar thicknesses
-    adjacency_spar_constr = (left_spar - right_spar) / left_spar
+    adjacency_spar_constr = left_spar - right_spar
     adjacency_spar_constr.set_name(f"spar{ispar}-{ispar+1}").optimize(
-        lower=-adjacency_ratio, upper=adjacency_ratio, scale=1.0, objective=False
+        lower=-adj_value, upper=adj_value, scale=1.0, objective=False
     ).register_to(f2f_model)
 
 for iOML in range(1, nOML):
     left_OML = f2f_model.get_variables(names=f"OML{iOML}")
     right_OML = f2f_model.get_variables(names=f"OML{iOML+1}")
     # make a composite function for relative diff in OML thicknesses
-    adj_OML_constr = (left_OML - right_OML) / left_OML
+    adj_OML_constr = left_OML - right_OML
     adj_OML_constr.set_name(f"OML{iOML}-{iOML+1}").optimize(
-        lower=-adjacency_ratio, upper=adjacency_ratio, scale=1.0, objective=False
+        lower=-adj_value, upper=adj_value, scale=1.0, objective=False
     ).register_to(f2f_model)
 
 # make the BDF and DAT file for TACS structural analysis
 tacs_aim.setup_aim()
 tacs_aim.pre_analysis()
 
+
 # build the solver manager, no tacs interface since built for each new shape
 # in the tacs driver
 solvers = SolverManager(comm)
@@ -144,56 +131,15 @@
     model=f2f_model,
     comm=comm,
     nprocs=1,
-    bdf_file=tacs_aim.dat_file_path,
-    prefix=tacs_aim.analysis_dir,
+    bdf_file=tacs_aim.root_dat_file,
+    prefix=tacs_aim.root_analysis_dir,
+    callback=blade_elemCallBack,
 )
 solvers.flow.copy_struct_mesh()
 null_driver = NullDriver(solvers, model=f2f_model, transfer_settings=None)
 
 # build the tacs oneway driver
 tacs_driver = OnewayStructDriver.prime_loads(driver=null_driver)
 
-# --------------------------------------------------------------------------#
-# Setup OpenMDAO Problem and Perform Sizing Optimization on the Wing
-# --------------------------------------------------------------------------#
-
-# setup the OpenMDAO Problem object
-prob = om.Problem()
-
-# Create the OpenMDAO component using the built-in Funtofem component
-design_out_file = "design-test.txt"
-f2f_subsystem = FuntofemComponent(
-    driver=tacs_driver, write_dir=tacs_aim.analysis_dir, design_out_file=design_out_file
-)
-prob.model.add_subsystem("f2fSystem", f2f_subsystem)
-f2f_subsystem.register_to_model(prob.model, "f2fSystem")
-
-# setup the optimizer settings # COBYLA for auto-FDing
-optimizer = "scipy"
-if optimizer == "scipy":
-    prob.driver = om.ScipyOptimizeDriver(optimizer="SLSQP", tol=1.0e-9, disp=True)
-elif optimizer == "pyoptsparse":
-    prob.driver = om.pyOptSparseDriver(optimizer="SNOPT")
-    # prob.driver.opt_settings['Major feasibility tolerance'] = 1e-5 # lower tolerance to prevent tight oscillations
-
-# Start the optimization
-print("\n==> Starting optimization...")
-prob.setup()
-
-debug = False
-if debug:
-    print("Checking partials...", flush=True)
-    prob.check_partials(compact_print=True)
-
-else:
-    prob.run_driver()
-
-    # report the final optimal design
-    design_hdl = f2f_subsystem._design_hdl
-    for var in f2f_model.get_variables():
-        opt_value = prob.get_val(f"f2fSystem.{var.name}")
-        design_hdl.write(f"\t{var.name} = {opt_value}")
-
-    prob.cleanup()
-    # close the design hdl file
-    f2f_subsystem.cleanup()
+tacs_driver.solve_forward()
+# tacs_driver.solve_adjoint()