def InitializeOptimizationLoop(self):
self.model_part_controller.Initialize()
self.analyzer.InitializeBeforeOptimizationLoop()
self.design_surface = self.model_part_controller.GetDesignSurface()
self.mapper = mapper_factory.CreateMapper(self.design_surface,
self.design_surface,
self.mapper_settings)
self.mapper.Initialize()
self.data_logger = data_logger_factory.CreateDataLogger(
self.model_part_controller, self.communicator,
self.optimization_settings)
self.data_logger.InitializeDataLogging()
self.optimization_utilities = KSO.OptimizationUtilities(
self.design_surface, self.optimization_settings)
def InitializeOptimizationLoop(self):
self.model_part_controller.Initialize()
self.model_part_controller.SetMinimalBufferSize(2)
self.analyzer.InitializeBeforeOptimizationLoop()
self.design_surface = self.model_part_controller.GetDesignSurface()
self.mapper = mapper_factory.CreateMapper(self.design_surface,
self.design_surface,
self.mapper_settings)
self.mapper.Initialize()
if self.filter_penalty_term:
penalty_filter_radius = self.algorithm_settings[
"penalty_filter_radius"].GetDouble()
filter_radius = self.mapper_settings["filter_radius"].GetDouble()
if abs(filter_radius - penalty_filter_radius) > 1e-9:
penalty_filter_settings = self.mapper_settings.Clone()
penalty_filter_settings["filter_radius"].SetDouble(
self.algorithm_settings["penalty_filter_radius"].GetDouble(
))
self.penalty_filter = mapper_factory.CreateMapper(
self.design_surface, self.design_surface,
penalty_filter_settings)
self.penalty_filter.Initialize()
else:
self.penalty_filter = self.mapper
self.data_logger = data_logger_factory.CreateDataLogger(
self.model_part_controller, self.communicator,
self.optimization_settings)
self.data_logger.InitializeDataLogging()
self.optimization_utilities = KSO.OptimizationUtilities(
self.design_surface, self.optimization_settings)
# Identify fixed design areas
KM.VariableUtils().SetFlag(KM.BOUNDARY, False,
self.optimization_model_part.Nodes)
radius = self.mapper_settings["filter_radius"].GetDouble()
search_based_functions = KSO.SearchBasedFunctions(self.design_surface)
for itr in range(self.algorithm_settings["fix_boundaries"].size()):
sub_model_part_name = self.algorithm_settings["fix_boundaries"][
itr].GetString()
node_set = self.optimization_model_part.GetSubModelPart(
sub_model_part_name).Nodes
search_based_functions.FlagNodesInRadius(node_set, KM.BOUNDARY,
radius)
# Specify bounds and assign starting values for ALPHA
if self.bead_side == "positive":
KM.VariableUtils().SetScalarVar(KSO.ALPHA, 0.5,
self.design_surface.Nodes,
KM.BOUNDARY, False)
self.lower_bound = 0.0
self.upper_bound = 1.0
elif self.bead_side == "negative":
KM.VariableUtils().SetScalarVar(KSO.ALPHA, -0.5,
self.design_surface.Nodes,
KM.BOUNDARY, False)
self.lower_bound = -1.0
self.upper_bound = 0.0
elif self.bead_side == "both":
KM.VariableUtils().SetScalarVar(KSO.ALPHA, 0.0,
self.design_surface.Nodes,
KM.BOUNDARY, False)
self.lower_bound = -1.0
self.upper_bound = 1.0
else:
raise RuntimeError("Specified bead direction mode not supported!")
# Initialize ALPHA_MAPPED according to initial ALPHA values
self.mapper.Map(KSO.ALPHA, KSO.ALPHA_MAPPED)
# Specify bead direction
bead_direction = self.algorithm_settings["bead_direction"].GetVector()
if len(bead_direction) == 0:
self.model_part_controller.ComputeUnitSurfaceNormals()
for node in self.design_surface.Nodes:
normalized_normal = node.GetSolutionStepValue(
KSO.NORMALIZED_SURFACE_NORMAL)
node.SetValue(KSO.BEAD_DIRECTION, normalized_normal)
elif len(bead_direction) == 3:
norm = math.sqrt(bead_direction[0]**2 + bead_direction[1]**2 +
bead_direction[2]**2)
normalized_bead_direction = [
value / norm for value in bead_direction
]
KM.VariableUtils().SetNonHistoricalVectorVar(
KSO.BEAD_DIRECTION, normalized_bead_direction,
self.design_surface.Nodes)
else:
raise RuntimeError(
"Wrong definition of bead direction. Options are: 1) [] -> takes surface normal, 2) [x.x,x.x,x.x] -> takes specified vector."
)