How do I calculate linearized stress (Membrane, Bending and Peak) using DPF?
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import mech_dpf import Ans.DataProcessing as dpf path = ExtAPI.DataModel.GetObjectsByName("Path")[0] x_0 = path.StartXCoordinate.Value y_0 = path.StartYCoordinate.Value z_0 = path.StartZCoordinate.Value x_1 = path.EndXCoordinate.Value y_1 = path.EndYCoordinate.Value z_1 = path.EndZCoordinate.Value path_length = ((x_1  x_0) ** 2 + (y_1  y_0) ** 2 + (z_1  z_0) ** 2) ** 0.5 n_points = path.DiscretizationPoints + 2 delta = path_length / (n_points  1) line_unit_vector = [(x_1  x_0) / path_length, (y_1  y_0) / path_length, (z_1  z_0) / path_length] # Line equation fx = lambda t: x_0 + line_unit_vector[0] * t fy = lambda t: y_0 + line_unit_vector[1] * t fz = lambda t: z_0 + line_unit_vector[2] * t coordinates = [[fx(t * delta), fy(t * delta), fz(t * delta)] for t in range(n_points)] flat_coordinates = [entry for data in coordinates for entry in data] field_coord = dpf.FieldsFactory.Create3DVectorField(n_points) field_coord.Data = flat_coordinates field_coord.Scoping.Ids = list(range(1, n_points + 1)) model = dpf.Model(Model.Analyses[0].ResultFileName) ts = dpf.Scoping() ts.Ids = [2] # SX s = model.CreateOperator("SX") s.inputs.requested_location.Connect("Nodal") s.inputs.time_scoping.Connect(ts) s2_f = s.outputs.fields_container.GetData() mapping_operator = dpf.operators.mapping.on_coordinates( fields_container=s2_f, coordinates=field_coord, create_support=True, mesh=model.Mesh ) fields_mapped = mapping_operator.outputs.fields_container.GetData() ls = list(fields_mapped[0].Data) # Membrane Stress membrane_stress = (ls[0] / 2 + ls[1] / 2 + sum(ls[1:1])) / (n_points  1) # Bending stress path_1 = 1 * path_length / 2 path_n = path_length / 2 path_range = [path_1 + delta * i for i in range(n_points)] path_range_field = dpf.FieldsFactory.CreateScalarField(numEntities=n_points, location=dpf.locations.nodal) path_range_field.Data = path_range path_range_field.ScopingIds = range(1, 50) # Function to be integrated stress_scaled = dpf.operators.math.scale_by_field(fieldA=fields_mapped[0], fieldB=path_range_field) stress_scaled_data = list(stress_scaled.outputs.field.GetData().Data) # Use extended Simpson's rule for Numerical Integration of `stress_scaled_data` stress_scaled_integral = (17 * stress_scaled_data[0] + 59 * stress_scaled_data[1] + 43 * stress_scaled_data[2] + 49 * stress_scaled_data[3] + 48 * sum(stress_scaled_data[4:4]) + 49 * stress_scaled_data[ n_points  4] + 43 * stress_scaled_data[n_points  3] + 59 * stress_scaled_data[ n_points  2] + 17 * stress_scaled_data[n_points  1]) / 48.0 b1 = stress_scaled_integral * (6.0 / path_length) / 48.0 b2 = (1.0) * b1 <?WORD FLAGGED?>_bending = (b2  b1) / (path_length) fb = lambda t: b1 + <?WORD FLAGGED?>_bending * t bending_stress = [fb(t * delta) for t in range(n_points)] bend_f = dpf.FieldsFactory.CreateScalarField(numEntities=49, location=dpf.locations.nodal) bend_f.Data = bending_stress bend_f.Scoping.Ids = list(range(1, n_points + 1)) # Add Membrane and Bending Stress bend_mem_f = dpf.operators.math.add_constant(field=bend_f, ponderation=membrane_stress) bend_mem_f_neg = dpf.operators.math.scale(field=bend_mem_f, ponderation=1.0) # Peak stress ps = dpf.operators.math.add(fieldA=fields_mapped[0], fieldB=bend_mem_f_neg)
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Hello Ayush,
Thanks for this comprehensive example. I wonder if there is a way to solve the reversed task: find elements of the model whose results were used for mapping to path points. Maybe there is another option rather than screening over the whole mesh and finding elements whose centroids are situated in the path direction.
Regards
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Hi @dafedin,
That information is not provided as an output of the operator at the moment.
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Is there a more efficient way than looping where we could get these results (bending and membrane) for ALL timepoints? Most of our DPF examples focus on a single time point, but one of the big benefits of DPF is the ability to process multiple timepoints simultaneously. All of these calculations use fields_mapped[0].Data how can we use all the data in the fields_mapped container?
Also how can I use this in a Python Result and plot the path results on the path. If I send bend_f to the dpf_workflow.Add I get an error.
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Is there a more efficient way than looping where we could get these results (bending and membrane) for ALL timepoints? Most of our DPF examples focus on a single time point, but one of the big benefits of DPF is the ability to process multiple timepoints simultaneously. All of these calculations use fields_mapped[0].Data how can we use all the data in the fields_mapped container?
Also how can I use this in a Python Result and plot the path results on the path. If I send bend_f to the dpf_workflow.Add I get an error.
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@Ayush Kumar a few more questions on this. 1. What does the math.scale_by_field operator do? I do not see it documented anywhere.
2. Do the field coordinates input into the mapping operator need to be in SI?0 
@Jim Kosloski
1. As most of the calculation is done on the Client side, I don't see a DPF way to calculate for all timesteps at once (in Mechanical DPF). For PyDPF, NumPy can be used for vectorized operations.
2. You can try forwarding the field to an operator (dpf.operators.utility.forward()) and then pass that operator to workflow. Also make sure you have the new mesh defined using SetOutputMesh(...).
3. scale_by_field: https://dpf.docs.pyansys.com/version/stable/api/ansys.dpf.core.operators.math.scale_by_field.html
4. Coordinate field input in the mapping operator is not unit dependent.0