.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples\06-plotting\02-solution_combination.py" .. LINE NUMBERS ARE GIVEN BELOW. .. only:: html .. note:: :class: sphx-glr-download-link-note :ref:`Go to the end ` to download the full example code .. rst-class:: sphx-glr-example-title .. _sphx_glr_examples_06-plotting_02-solution_combination.py: .. _solution_combination: Load case combination for principal stress ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ This example shows how to get a principal stress load case combination using DPF And highlight min/max values in the plot. .. GENERATED FROM PYTHON SOURCE LINES 14-16 Import the ``ansys.dpf.core`` module, included examples file, and the ``DpfPlotter`` module. .. GENERATED FROM PYTHON SOURCE LINES 16-20 .. code-block:: Python from ansys.dpf import core as dpf from ansys.dpf.core import examples from ansys.dpf.core.plotter import DpfPlotter .. GENERATED FROM PYTHON SOURCE LINES 21-33 Open an example and print the ``Model`` object. The :class:`Model ` class helps to organize access methods for the result by keeping track of the operators and data sources used by the result file. Printing the model displays this metadata: - Analysis type - Available results - Size of the mesh - Number of results .. GENERATED FROM PYTHON SOURCE LINES 33-36 .. code-block:: Python model = dpf.Model(examples.find_msup_transient()) print(model) .. rst-class:: sphx-glr-script-out .. code-block:: none DPF Model ------------------------------ Transient analysis Unit system: MKS: m, kg, N, s, V, A, degC Physics Type: Mechanical Available results: - displacement: Nodal Displacement - velocity: Nodal Velocity - acceleration: Nodal Acceleration - reaction_force: Nodal Force - stress: ElementalNodal Stress - elemental_volume: Elemental Volume - stiffness_matrix_energy: Elemental Energy-stiffness matrix - artificial_hourglass_energy: Elemental Hourglass Energy - thermal_dissipation_energy: Elemental thermal dissipation energy - kinetic_energy: Elemental Kinetic Energy - co_energy: Elemental co-energy - incremental_energy: Elemental incremental energy - elastic_strain: ElementalNodal Strain ------------------------------ DPF Meshed Region: 393 nodes 40 elements Unit: m With solid (3D) elements ------------------------------ DPF Time/Freq Support: Number of sets: 20 Cumulative Time (s) LoadStep Substep 1 0.010000 1 1 2 0.020000 1 2 3 0.030000 1 3 4 0.040000 1 4 5 0.050000 1 5 6 0.060000 1 6 7 0.070000 1 7 8 0.080000 1 8 9 0.090000 1 9 10 0.100000 1 10 11 0.110000 1 11 12 0.120000 1 12 13 0.130000 1 13 14 0.140000 1 14 15 0.150000 1 15 16 0.160000 1 16 17 0.170000 1 17 18 0.180000 1 18 19 0.190000 1 19 20 0.200000 1 20 .. GENERATED FROM PYTHON SOURCE LINES 37-41 Get the stress tensor and ``connect`` time scoping. Make sure that you define ``dpf.locations.nodal`` as the scoping location because labels are supported only for nodal results. .. GENERATED FROM PYTHON SOURCE LINES 41-47 .. code-block:: Python stress_tensor = model.results.stress() time_scope = dpf.Scoping() time_scope.ids = [1, 2] stress_tensor.inputs.time_scoping.connect(time_scope) stress_tensor.inputs.requested_location.connect(dpf.locations.nodal) .. GENERATED FROM PYTHON SOURCE LINES 48-51 This code performs solution combination on two load cases, LC1 and LC2. You can access individual load cases as the fields of a fields container for the stress tensor. .. GENERATED FROM PYTHON SOURCE LINES 51-57 .. code-block:: Python field_lc1 = stress_tensor.outputs.fields_container()[0] field_lc2 = stress_tensor.outputs.fields_container()[1] # Scale LC2 to -1. stress_tensor_lc2_sc = dpf.operators.math.scale(field=field_lc2, ponderation=-1.0) .. GENERATED FROM PYTHON SOURCE LINES 58-59 Add load cases. .. GENERATED FROM PYTHON SOURCE LINES 59-61 .. code-block:: Python stress_tensor_combi = dpf.operators.math.add(fieldA=field_lc1, fieldB=stress_tensor_lc2_sc) .. GENERATED FROM PYTHON SOURCE LINES 62-65 Principal stresses are the Eigenvalues of the stress tensor. Use principal invariants to get S1, S2, and S3. .. GENERATED FROM PYTHON SOURCE LINES 65-68 .. code-block:: Python p_inv = dpf.operators.invariant.principal_invariants() p_inv.inputs.field.connect(stress_tensor_combi) .. GENERATED FROM PYTHON SOURCE LINES 69-71 Print S1 (maximum principal stress). .. GENERATED FROM PYTHON SOURCE LINES 71-73 .. code-block:: Python print(p_inv.outputs.field_eig_1().data) .. rst-class:: sphx-glr-script-out .. code-block:: none [ 9.89969387e+05 9.86979842e+05 6.46045019e+05 6.48932208e+05 1.56976611e+04 2.38335566e+03 2.41021560e+03 1.55569949e+04 6.46045018e+05 9.86979841e+05 2.41021536e+03 2.38335517e+03 1.40298687e+06 1.40006022e+06 1.51284404e+04 2.32609985e+03 1.40006022e+06 2.32609969e+03 1.88584658e+06 1.88308883e+06 1.40245029e+04 2.28989834e+03 1.88308883e+06 2.28989838e+03 2.43323154e+06 2.43097276e+06 1.13710605e+04 1.92191439e+03 2.43097276e+06 1.92191428e+03 3.03740836e+06 3.03544790e+06 8.36913086e+03 5.11051169e+03 3.03544790e+06 5.11051165e+03 3.68414662e+06 3.68923438e+06 -4.49507141e+03 -3.86970389e+03 3.68923438e+06 -3.86970407e+03 4.37493535e+06 4.36801081e+06 4.62750323e+04 6.45366758e+04 4.36801080e+06 6.45366739e+04 5.00024912e+06 5.15363818e+06 -1.72558410e+05 -1.68506344e+05 5.15363818e+06 -1.68506347e+05 5.34040385e+06 6.25295625e+06 9.15169741e+05 5.86694135e+05 6.25295625e+06 5.86694135e+05 8.19942478e+06 5.11230070e+06 -3.42443463e+06 -1.72869110e+06 5.11230070e+06 -1.72869110e+06 3.07108105e+03 4.85742708e+02 2.08121801e+03 4.51329102e+03 1.15257484e+04 1.08729694e+04 1.48084273e+02 6.58067584e+01 2.08121700e+03 4.85743242e+02 1.48084276e+02 1.08729663e+04 3.99734802e+02 2.84198603e+02 3.98308935e+04 3.99596263e+04 2.84199027e+02 3.99596267e+04 8.05592976e+00 7.63702585e+01 7.02630967e+04 7.11528217e+04 7.63704604e+01 7.11528219e+04 4.08416639e+00 8.37761486e+01 8.97598110e+04 9.14268559e+04 8.37761220e+01 9.14268560e+04 5.48381675e+00 1.42362400e+02 8.58241342e+04 8.84204337e+04 1.42362254e+02 8.84204335e+04 1.36280987e+01 1.13419159e+03 4.68127641e+04 5.12948274e+04 1.13419050e+03 5.12948265e+04 3.78823067e+04 3.90599658e+04 1.20048086e+04 5.25881723e+03 3.90599642e+04 5.25881571e+03 1.77336944e+05 1.75477888e+05 1.36475040e+04 2.76759779e+03 1.75477887e+05 2.76759705e+03 3.79160579e+05 3.76590414e+05 1.48577178e+04 2.47204930e+03 3.76590413e+05 2.47204876e+03 9.87954234e+05 8.16487441e+05 6.46963602e+05 8.19450620e+05 8.32083289e+03 2.37183132e+03 8.24629107e+03 1.56273280e+04 4.22633967e+03 2.09163879e+04 1.69460011e+04 3.38679027e+03 6.46963601e+05 8.16487441e+05 9.87954234e+05 8.24629092e+03 2.37183096e+03 8.32083271e+03 1.69460004e+04 2.09163879e+04 1.40100768e+06 1.19350278e+06 1.19647800e+06 8.06338005e+03 2.33617878e+03 1.54130508e+04 5.06746339e+03 2.48394848e+04 1.19350278e+06 1.40100768e+06 2.33617846e+03 8.06337997e+03 2.48394841e+04 1.88395758e+06 1.64156177e+06 1.64441663e+06 7.53335722e+03 2.29511028e+03 1.45764717e+04 5.88761468e+03 2.85398928e+04 1.64156177e+06 1.88395758e+06 2.29511022e+03 7.53335719e+03 2.85398937e+04 2.43161333e+06 2.15701918e+06 2.15953899e+06 6.20773016e+03 2.02784724e+03 1.26977817e+04 6.67395032e+03 3.18340564e+04 2.15701918e+06 2.43161333e+06 2.02784721e+03 6.20773009e+03 3.18340564e+04 3.03594055e+06 2.73320351e+06 2.73531989e+06 5.60676164e+03 2.72710830e+03 9.87009570e+03 7.46575696e+03 3.45048447e+04 2.73320351e+06 3.03594055e+06 2.72710810e+03 5.60676149e+03 3.45048427e+04 3.68631143e+06 3.36231959e+06 3.36077747e+06 -4.64521947e+03 -4.02685627e+00 1.93702972e+03 8.47413202e+03 3.63891780e+04 3.36231959e+06 3.68631143e+06 -4.02705347e+00 -4.64521954e+03 3.63891782e+04 4.37097945e+06 4.02861843e+06 4.02954094e+06 5.48856888e+04 2.66267135e+04 1.70544403e+04 9.30881824e+03 3.76058067e+04 4.02861843e+06 4.37097945e+06 2.66267128e+04 5.48856879e+04 3.76058038e+04 5.07685002e+06 4.75984186e+06 4.68757240e+06 -1.70825434e+05 -5.92324427e+04 -6.58878990e+04 3.01483062e+04 2.40997043e+04 4.75984186e+06 5.07685002e+06 -5.92324444e+04 -1.70825436e+05 2.40996713e+04 5.79541432e+06 5.70261123e+06 5.17030113e+06 7.41483955e+05 1.80559706e+05 3.68553935e+05 1.21181294e+04 5.77464735e+04 5.70261123e+06 5.79541432e+06 1.80559705e+05 7.41483955e+05 5.77464732e+04 6.76007838e+06 6.55138588e+06 5.60950676e+06 -1.27232574e+06 -2.58721655e+06 -6.39421513e+05 4.13265031e+05 4.45501864e+05 5.60950676e+06 6.55138588e+06 -6.39421513e+05 -2.58721655e+06 4.45501864e+05 1.61943216e+03 3.10965572e+02 2.25636060e+03 3.79218604e+03 1.10854389e+04 4.53912469e+03 9.07955770e+01 4.93947446e+03 3.68349703e+02 1.18342832e+03 3.42938262e+01 4.05442820e+01 2.25636052e+03 3.10965881e+02 1.61943240e+03 9.07956839e+01 4.53912372e+03 1.10854373e+04 3.42939134e+01 1.18342850e+03 2.65656153e+02 3.16995504e+02 1.73540793e+03 3.98371654e+04 2.53482084e+04 2.56765725e+04 4.87884515e+02 1.64634854e+03 3.16995859e+02 2.65656367e+02 2.53482069e+04 3.98371655e+04 1.64634882e+03 1.20868138e+01 1.53332553e+02 8.34477875e+00 7.06858860e+04 5.55323220e+04 5.50465228e+04 4.32272090e+02 1.40242459e+03 1.53332839e+02 1.20867966e+01 5.55323222e+04 7.06858860e+04 1.40242520e+03 6.52978300e+00 6.11437148e+01 5.82177773e+00 9.05926824e+04 8.12697662e+04 8.00112056e+04 2.33592980e+02 4.52921390e+02 6.11437305e+01 6.52982809e+00 8.12697663e+04 9.05926824e+04 4.52922199e+02 1.01781946e+01 1.06177194e+02 4.46460174e+00 8.70987991e+04 8.98867421e+04 8.77916532e+04 1.04133938e+02 1.18550598e+03 1.06177120e+02 1.01781534e+01 8.98867421e+04 8.70987990e+04 1.18550523e+03 8.92616048e+01 3.61429147e+02 7.74169288e+00 4.88073415e+04 6.96187475e+04 6.63166348e+04 5.69214730e+02 3.42490749e+03 3.61428542e+02 8.92614996e+01 6.96187470e+04 4.88073411e+04 3.42490700e+03 3.71947352e+04 7.66384058e+03 1.66212838e+02 7.00641342e+03 1.58464803e+04 1.09997182e+04 1.14790002e+03 6.21377392e+03 7.66383803e+03 3.71947343e+04 1.58464779e+04 7.00641255e+03 6.21377387e+03 1.75780678e+05 1.06374478e+05 1.07603370e+05 7.35047360e+03 3.11936342e+03 1.28261563e+04 1.82375472e+03 9.46675704e+03 1.06374477e+05 1.75780677e+05 3.11936250e+03 7.35047326e+03 9.46675639e+03 3.77331700e+05 2.75920917e+05 2.78248027e+05 7.90102104e+03 2.50682872e+03 1.42526109e+04 2.57757172e+03 1.30834902e+04 2.75920916e+05 3.77331700e+05 2.50682813e+03 7.90102076e+03 1.30834897e+04 5.11273760e+05 5.14046095e+05 2.39727952e+03 1.52073563e+04 5.11273759e+05 2.39727916e+03] .. GENERATED FROM PYTHON SOURCE LINES 74-76 Get the meshed region. .. GENERATED FROM PYTHON SOURCE LINES 76-78 .. code-block:: Python mesh_set = model.metadata.meshed_region .. GENERATED FROM PYTHON SOURCE LINES 79-83 Plot the results on the mesh. The ``label_text_size`` and ``label_point_size`` arguments control the font size of the label. .. GENERATED FROM PYTHON SOURCE LINES 83-90 .. code-block:: Python plot = DpfPlotter() plot.add_field(p_inv.outputs.field_eig_1(), meshed_region=mesh_set) # You can set the camera positions using the ``cpos`` argument. # The three tuples in the list for the ``cpos`` argument represent the camera # position, focal point, and view respectively. plot.show_figure(show_axes=True) .. image-sg:: /examples/06-plotting/images/sphx_glr_02-solution_combination_001.png :alt: 02 solution combination :srcset: /examples/06-plotting/images/sphx_glr_02-solution_combination_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 0.688 seconds) .. _sphx_glr_download_examples_06-plotting_02-solution_combination.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: 02-solution_combination.ipynb <02-solution_combination.ipynb>` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: 02-solution_combination.py <02-solution_combination.py>` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_