Add ability to animate shape variables to a gif in caps2tacs

examples/caps_wing/7_animate_shape_vars.py

@@ -0,0 +1,74 @@
+"""
+Sean Engelstad, November 2023
+GT SMDO Lab, Dr. Graeme Kennedy
+Caps to TACS example
+
+The purpose of this file is to show how to animate shape variables in the structure.
+Once you run this script it will generate .f5 files in the capsStruct/Scratch/tacs work directory.
+You'll need to use f5tovtk to convert to *.vtk files and open up each group of shape_var_..vtk files
+using the .. shortcut which opens up a group of files at once. For each of these groups of vtk files,
+click file -> save animation and save all the png files in a subfolder. Then, either use the GifWriter in the
+caps2tacs module or copy the GifWriter script into that directory and use it to make a gif. Repeat for each shape variable.
+"""
+
+from tacs import caps2tacs
+from mpi4py import MPI
+import openmdao.api as om
+
+# --------------------------------------------------------------#
+# Setup CAPS Problem
+# --------------------------------------------------------------#
+comm = MPI.COMM_WORLD
+tacs_model = caps2tacs.TacsModel.build(csm_file="large_naca_wing.csm", comm=comm)
+tacs_model.mesh_aim.set_mesh(  # need a refined-enough mesh for the derivative test to pass
+    edge_pt_min=15,
+    edge_pt_max=20,
+    global_mesh_size=0.01,
+    max_surf_offset=0.01,
+    max_dihedral_angle=5,
+).register_to(
+    tacs_model
+)
+
+aluminum = caps2tacs.Isotropic.aluminum().register_to(tacs_model)
+
+# setup the thickness design variables + automatic shell properties
+nribs = int(tacs_model.get_config_parameter("nribs"))
+nspars = int(tacs_model.get_config_parameter("nspars"))
+nOML = nribs - 1
+for irib in range(1, nribs + 1):
+    caps2tacs.ThicknessVariable(
+        caps_group=f"rib{irib}", value=0.03, material=aluminum
+    ).register_to(tacs_model)
+for ispar in range(1, nspars + 1):
+    caps2tacs.ThicknessVariable(
+        caps_group=f"spar{ispar}", value=0.03, material=aluminum
+    ).register_to(tacs_model)
+for iOML in range(1, nOML + 1):
+    caps2tacs.ThicknessVariable(
+        caps_group=f"OML{iOML}", value=0.1, material=aluminum
+    ).register_to(tacs_model)
+
+# register one shape variable rib_a1
+rib_a1 = caps2tacs.ShapeVariable("rib_a1", value=1.0).register_to(tacs_model)
+caps2tacs.ShapeVariable("rib_a2", value=0.0).register_to(tacs_model)
+spar_a1 = caps2tacs.ShapeVariable("spar_a1", value=1.0).register_to(tacs_model)
+caps2tacs.ShapeVariable("spar_a2", value=0.0).register_to(tacs_model)
+
+# add constraints and loads
+caps2tacs.PinConstraint("root").register_to(tacs_model)
+caps2tacs.GridForce("OML", direction=[0, 0, 1.0], magnitude=10.0).register_to(
+    tacs_model
+)
+
+# add analysis functions to the model
+caps2tacs.AnalysisFunction.mass().register_to(tacs_model)
+
+# run the pre analysis to build tacs input files
+tacs_model.setup(include_aim=True)
+
+shape_var_dict = {
+    rib_a1: [_ * 0.1 for _ in range(6, 14)],
+    spar_a1: [_ * 0.1 for _ in range(6, 14)],
+}
+tacs_model.animate_shape_vars(shape_var_dict)

tacs/caps2tacs/__init__.py

@@ -19,6 +19,7 @@
 if openmdao_loader is not None:
     from .tacs_component import *
 
+from .gif_writer import *
 from .analysis_function import *
 from .constraints import *
 from .egads_aim import *

tacs/caps2tacs/gif_writer.py

@@ -0,0 +1,31 @@
+__all__ = ["GifWriter"]
+import imageio, os
+
+
+class GifWriter:
+    """
+    module to write gifs from a set of pngs
+    """
+
+    def __init__(self, frames_per_second: int = 4):
+        self._fps = frames_per_second
+
+    def __call__(self, gif_filename: str, path: str):
+        """
+        call on current path to create gif of given filename
+        """
+        gif_filepath = os.path.join(path, gif_filename)
+        with imageio.get_writer(gif_filepath, mode="I", fps=self._fps) as writer:
+            path_dir = os.listdir(path)
+            path_dir = sorted(path_dir)
+            for image_file in path_dir:
+                print(image_file)
+                if ".png" in image_file:
+                    image = imageio.imread(image_file)
+                    writer.append_data(image)
+
+
+# example of how to use the GifWriter
+# if __name__ == "__main__":
+#    my_writer = GifWriter(frames_per_second=4)
+#    my_writer("sizing1.gif", os.getcwd())

tacs/caps2tacs/materials.py

@@ -180,7 +180,7 @@ def aluminum(cls):
             cp=903,
             kappa=237,
         )
-    
+
     @classmethod
     def titanium(cls):
         return cls(
@@ -282,8 +282,8 @@ def carbon_fiber(cls):
             alpha1=-0.3e-6,
             alpha2=28e-6,
             rho=1.6e3,
-            kappa1=14.5, #W/m-K
-            kappa2=4.8, #W/m-K
-            kappa3=4.8, #W/m-K
-            cp=1130.0 # J / kg-K
+            kappa1=14.5,  # W/m-K
+            kappa2=4.8,  # W/m-K
+            kappa3=4.8,  # W/m-K
+            cp=1130.0,  # J / kg-K
         )

tacs/caps2tacs/tacs_model.py

@@ -273,6 +273,59 @@ def createTACSProbs(self, addFunctions: bool = True):
                     )
         return self.SPs
 
+    def animate_shape_vars(self, shape_vars_dict: dict):
+        """
+        Animate the shape variables in ESP/CAPS.
+
+        Parameters
+        ----------
+        shape_vars_dict: dict[ShapeVariable : list[float]]
+            dict of the list of values for each shape variable to take
+
+        e.g. if you wish to animate over the ShapeVariable objects var1, and var2
+        create the following shape_vars_dict
+        shape_vars_dict = {
+          var1 : [_*0.1 for _ in range(1,4)],
+          var2 : [_*0.05 for _ in range(-3,4)],
+        }
+        """
+        # make an analysis function if none have been made
+        if len(self.analysis_functions) == 0:
+            if self.comm.rank == 0:
+                print(
+                    "Adding mass analysis function to enable caps2tacs postAnalysis for animating shape variables..."
+                )
+            AnalysisFunction.mass().register_to(self)
+
+        # initialize all function and derivatives as zero
+
+        for shape_var in shape_vars_dict:
+            value_list = shape_vars_dict[shape_var]
+            for i, value in enumerate(value_list):
+                shape_var.value = value
+                self.geometry.despmtr[shape_var.name].value = value
+
+                self.tacs_aim.pre_analysis()
+                self.SPs = self.createTACSProbs(addFunctions=True)
+                for caseID in self.SPs:
+                    # note we don't solve the forward / adjoint analysis here
+                    # as we only care about visualizing the change in the structural shape / mesh
+                    # not the actual structural analysis results
+
+                    self.SPs[caseID].writeSolution(
+                        baseName=shape_var.name,
+                        outputDir=self.tacs_aim.analysis_dir,
+                        number=i,
+                    )
+                    self.SPs[caseID].writeDummySensFile(
+                        tacsAim=self.tacs_aim,
+                    )
+                self.tacs_aim.post_analysis()
+        print(
+            f"Done animating caps2tacs shape variables.. the f5 files are found in {self.tacs_aim.analysis_dir}."
+        )
+        print("Use the GifWriter script in examples/caps_wing/archive to ")
+
     def pre_analysis(self):
         """
         call tacs aim pre_analysis to build TACS input files and mesh

tacs/problems/base.py

@@ -935,3 +935,46 @@ class which handles the sensitivity file writing for ESP/CAPS shape derivatives
                                 hdl.write("1\n")
                                 hdl.write(f"{struct_sens[idx].real}\n")
             return
+
+    def writeDummySensFile(self, tacsAim):
+        """
+        write a blank / dummy SensFile for caps2tacs to enable animating shape variables
+        using GIF animations (without having to run an analysis just building each mesh)
+
+        Parameters
+        ----------
+        tacsAim : tacs.caps2tacs.TacsAIM
+            class which handles the sensitivity file writing for ESP/CAPS shape derivatives
+
+        """
+
+        num_funcs = 1
+        assert tacsAim is not None
+        num_struct_dvs = len(tacsAim.thickness_variables)
+        num_nodes = self.meshLoader.bdfInfo.nnodes
+
+        if self.comm.rank == 0:
+            # open the sens file nastran_CAPS.sens and write coordinate derivatives
+            # and any other struct derivatives to it
+            with open(tacsAim.sens_file_path, "w") as hdl:
+                for func_name in ["mass"]:
+                    hdl.write(f"{num_funcs} {num_struct_dvs}\n")
+
+                    # write the func name, value and nnodes
+                    hdl.write(f"{func_name}\n")
+                    hdl.write(f"{0.0}\n")
+                    hdl.write(f"{num_nodes}\n")
+
+                    # write the coordinate derivatives for the given function
+                    for bdf_ind in range(num_nodes):
+                        nastran_node = bdf_ind + 1
+                        hdl.write(f"{nastran_node} 0.0 0.0 0.0\n")
+
+                    # write any struct derivatives if there are struct derivatives
+                    if num_struct_dvs > 0:
+                        for idx, thick_var in enumerate(tacsAim.thickness_variables):
+                            # assumes these are sorted in tacs aim wrapper
+                            hdl.write(f"{thick_var.name}\n")
+                            hdl.write("1\n")
+                            hdl.write("0.0\n")
+            return