.. DO NOT EDIT. .. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY. .. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE: .. "examples/topology_optimization/plot_topology_optimization_short_cantilever.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_topology_optimization_plot_topology_optimization_short_cantilever.py: Solve a 2D short cantilever topology optimization problem ========================================================= .. GENERATED FROM PYTHON SOURCE LINES 23-31 .. code-block:: Python from __future__ import annotations from gemseo import create_scenario from gemseo.problems.topology_optimization.topopt_initialize import ( initialize_design_space_and_discipline_to, ) .. GENERATED FROM PYTHON SOURCE LINES 32-35 Setup the topology optimization problem --------------------------------------- Define the target volume fraction: .. GENERATED FROM PYTHON SOURCE LINES 35-37 .. code-block:: Python volume_fraction = 0.3 .. GENERATED FROM PYTHON SOURCE LINES 38-39 Define the problem type: .. GENERATED FROM PYTHON SOURCE LINES 39-41 .. code-block:: Python problem_name = "Short_Cantilever" .. GENERATED FROM PYTHON SOURCE LINES 42-43 Define the number of elements in the x- and y- directions: .. GENERATED FROM PYTHON SOURCE LINES 43-46 .. code-block:: Python n_x = 50 n_y = 25 .. GENERATED FROM PYTHON SOURCE LINES 47-48 Define the full material Young's modulus and Poisson's ratio: .. GENERATED FROM PYTHON SOURCE LINES 48-51 .. code-block:: Python e0 = 1 nu = 0.3 .. GENERATED FROM PYTHON SOURCE LINES 52-53 Define the penalty of the SIMP approach: .. GENERATED FROM PYTHON SOURCE LINES 53-55 .. code-block:: Python penalty = 3 .. GENERATED FROM PYTHON SOURCE LINES 56-57 Define the minimum member size in the solution: .. GENERATED FROM PYTHON SOURCE LINES 57-59 .. code-block:: Python min_member_size = 1.5 .. GENERATED FROM PYTHON SOURCE LINES 60-61 Instantiate the :class:`.DesignSpace` and the disciplines: .. GENERATED FROM PYTHON SOURCE LINES 61-73 .. code-block:: Python design_space, disciplines = initialize_design_space_and_discipline_to( problem=problem_name, n_x=n_x, n_y=n_y, e0=e0, nu=nu, penalty=penalty, min_member_size=min_member_size, vf0=volume_fraction, ) .. GENERATED FROM PYTHON SOURCE LINES 74-77 Solve the topology optimization problem --------------------------------------- Generate an :class:`.MDOScenario`: .. GENERATED FROM PYTHON SOURCE LINES 77-84 .. code-block:: Python scenario = create_scenario( disciplines, "compliance", design_space, formulation_name="DisciplinaryOpt", ) .. GENERATED FROM PYTHON SOURCE LINES 85-86 Add the volume fraction constraint to the scenario: .. GENERATED FROM PYTHON SOURCE LINES 86-90 .. code-block:: Python scenario.add_constraint( "volume fraction", constraint_type="ineq", value=volume_fraction ) .. GENERATED FROM PYTHON SOURCE LINES 91-92 Generate the XDSM: .. GENERATED FROM PYTHON SOURCE LINES 92-94 .. code-block:: Python scenario.xdsmize(save_html=False) .. raw:: html


.. GENERATED FROM PYTHON SOURCE LINES 95-96 Execute the scenario: .. GENERATED FROM PYTHON SOURCE LINES 96-98 .. code-block:: Python scenario.execute(algo_name="NLOPT_MMA", max_iter=200) .. rst-class:: sphx-glr-script-out .. code-block:: none INFO - 16:13:46: *** Start MDOScenario execution *** INFO - 16:13:46: MDOScenario INFO - 16:13:46: Disciplines: DensityFilter FiniteElementAnalysis MaterialModelInterpolation VolumeFraction INFO - 16:13:46: MDO formulation: DisciplinaryOpt INFO - 16:13:46: Optimization problem: INFO - 16:13:46: minimize compliance(x) INFO - 16:13:46: with respect to x INFO - 16:13:46: under the inequality constraints INFO - 16:13:46: volume fraction(x) <= 0.3 INFO - 16:13:46: Solving optimization problem with algorithm NLOPT_MMA: INFO - 16:13:46: 1%| | 2/200 [00:00<00:05, 37.95 it/sec, feas=True, obj=1.46e+3] INFO - 16:13:46: 2%|▏ | 3/200 [00:00<00:04, 41.09 it/sec, feas=True, obj=1.45e+3] INFO - 16:13:46: 2%|▏ | 4/200 [00:00<00:04, 43.15 it/sec, feas=True, obj=1.45e+3] INFO - 16:13:46: 2%|▎ | 5/200 [00:00<00:04, 43.68 it/sec, feas=True, obj=1.45e+3] INFO - 16:13:46: 3%|▎ | 6/200 [00:00<00:04, 44.11 it/sec, feas=True, obj=1.43e+3] INFO - 16:13:46: 4%|▎ | 7/200 [00:00<00:04, 44.65 it/sec, feas=True, obj=1.4e+3] INFO - 16:13:46: 4%|▍ | 8/200 [00:00<00:04, 44.75 it/sec, feas=True, obj=1.36e+3] INFO - 16:13:46: 4%|▍ | 9/200 [00:00<00:04, 44.75 it/sec, feas=True, obj=1.2e+3] INFO - 16:13:46: 5%|▌ | 10/200 [00:00<00:04, 45.05 it/sec, feas=True, obj=1.01e+3] INFO - 16:13:46: 6%|▌ | 11/200 [00:00<00:04, 45.31 it/sec, feas=True, obj=756] INFO - 16:13:46: 6%|▌ | 12/200 [00:00<00:04, 45.49 it/sec, feas=True, obj=573] INFO - 16:13:46: 6%|▋ | 13/200 [00:00<00:04, 45.73 it/sec, feas=True, obj=509] INFO - 16:13:46: 7%|▋ | 14/200 [00:00<00:04, 45.95 it/sec, feas=True, obj=448] INFO - 16:13:46: 8%|▊ | 15/200 [00:00<00:04, 46.17 it/sec, feas=True, obj=399] INFO - 16:13:46: 8%|▊ | 16/200 [00:00<00:03, 46.38 it/sec, feas=True, obj=360] INFO - 16:13:46: 8%|▊ | 17/200 [00:00<00:03, 46.57 it/sec, feas=True, obj=329] INFO - 16:13:46: 9%|▉ | 18/200 [00:00<00:03, 46.71 it/sec, feas=True, obj=304] INFO - 16:13:46: 10%|▉ | 19/200 [00:00<00:03, 47.04 it/sec, feas=True, obj=278] INFO - 16:13:46: 10%|█ | 20/200 [00:00<00:03, 47.22 it/sec, feas=True, obj=251] INFO - 16:13:46: 10%|█ | 21/200 [00:00<00:03, 47.43 it/sec, feas=True, obj=231] INFO - 16:13:46: 11%|█ | 22/200 [00:00<00:03, 47.61 it/sec, feas=True, obj=213] INFO - 16:13:46: 12%|█▏ | 23/200 [00:00<00:03, 47.71 it/sec, feas=True, obj=193] INFO - 16:13:46: 12%|█▏ | 24/200 [00:00<00:03, 47.84 it/sec, feas=True, obj=175] INFO - 16:13:46: 12%|█▎ | 25/200 [00:00<00:03, 47.99 it/sec, feas=True, obj=161] INFO - 16:13:46: 13%|█▎ | 26/200 [00:00<00:03, 48.17 it/sec, feas=True, obj=153] INFO - 16:13:46: 14%|█▎ | 27/200 [00:00<00:03, 48.36 it/sec, feas=True, obj=148] INFO - 16:13:46: 14%|█▍ | 28/200 [00:00<00:03, 48.51 it/sec, feas=True, obj=145] INFO - 16:13:46: 14%|█▍ | 29/200 [00:00<00:03, 48.70 it/sec, feas=True, obj=143] INFO - 16:13:46: 15%|█▌ | 30/200 [00:00<00:03, 48.88 it/sec, feas=True, obj=142] INFO - 16:13:46: 16%|█▌ | 31/200 [00:00<00:03, 49.04 it/sec, feas=True, obj=141] INFO - 16:13:47: 16%|█▌ | 32/200 [00:00<00:03, 49.18 it/sec, feas=True, obj=140] INFO - 16:13:47: 16%|█▋ | 33/200 [00:00<00:03, 49.29 it/sec, feas=True, obj=140] INFO - 16:13:47: 17%|█▋ | 34/200 [00:00<00:03, 49.44 it/sec, feas=True, obj=140] INFO - 16:13:47: 18%|█▊ | 35/200 [00:00<00:03, 49.63 it/sec, feas=True, obj=139] INFO - 16:13:47: 18%|█▊ | 36/200 [00:00<00:03, 49.79 it/sec, feas=True, obj=139] INFO - 16:13:47: 18%|█▊ | 37/200 [00:00<00:03, 49.92 it/sec, feas=True, obj=139] INFO - 16:13:47: 19%|█▉ | 38/200 [00:00<00:03, 50.08 it/sec, feas=True, obj=139] INFO - 16:13:47: 20%|█▉ | 39/200 [00:00<00:03, 50.25 it/sec, feas=True, obj=139] INFO - 16:13:47: 20%|██ | 40/200 [00:00<00:03, 50.40 it/sec, feas=True, obj=139] INFO - 16:13:47: 20%|██ | 41/200 [00:00<00:03, 50.55 it/sec, feas=True, obj=139] INFO - 16:13:47: 21%|██ | 42/200 [00:00<00:03, 50.65 it/sec, feas=True, obj=138] INFO - 16:13:47: 22%|██▏ | 43/200 [00:00<00:03, 50.77 it/sec, feas=True, obj=138] INFO - 16:13:47: 22%|██▏ | 44/200 [00:00<00:03, 50.89 it/sec, feas=True, obj=138] INFO - 16:13:47: 22%|██▎ | 45/200 [00:00<00:03, 51.03 it/sec, feas=True, obj=138] INFO - 16:13:47: 23%|██▎ | 46/200 [00:00<00:03, 51.17 it/sec, feas=True, obj=138] INFO - 16:13:47: 24%|██▎ | 47/200 [00:00<00:02, 51.26 it/sec, feas=True, obj=138] INFO - 16:13:47: 24%|██▍ | 48/200 [00:00<00:02, 51.36 it/sec, feas=True, obj=138] INFO - 16:13:47: 24%|██▍ | 49/200 [00:00<00:02, 51.48 it/sec, feas=True, obj=138] INFO - 16:13:47: 25%|██▌ | 50/200 [00:00<00:02, 51.57 it/sec, feas=True, obj=138] INFO - 16:13:47: 26%|██▌ | 51/200 [00:00<00:02, 51.66 it/sec, feas=True, obj=138] INFO - 16:13:47: 26%|██▌ | 52/200 [00:01<00:02, 51.72 it/sec, feas=True, obj=138] INFO - 16:13:47: 26%|██▋ | 53/200 [00:01<00:02, 51.80 it/sec, feas=True, obj=138] INFO - 16:13:47: 27%|██▋ | 54/200 [00:01<00:02, 51.84 it/sec, feas=True, obj=137] INFO - 16:13:47: 28%|██▊ | 55/200 [00:01<00:02, 51.92 it/sec, feas=True, obj=137] INFO - 16:13:47: 28%|██▊ | 56/200 [00:01<00:02, 52.01 it/sec, feas=True, obj=137] INFO - 16:13:47: 28%|██▊ | 57/200 [00:01<00:02, 52.09 it/sec, feas=True, obj=137] INFO - 16:13:47: 29%|██▉ | 58/200 [00:01<00:02, 52.17 it/sec, feas=True, obj=137] INFO - 16:13:47: 30%|██▉ | 59/200 [00:01<00:02, 52.24 it/sec, feas=True, obj=137] INFO - 16:13:47: 30%|███ | 60/200 [00:01<00:02, 52.34 it/sec, feas=True, obj=137] INFO - 16:13:47: 30%|███ | 61/200 [00:01<00:02, 52.41 it/sec, feas=True, obj=137] INFO - 16:13:47: 31%|███ | 62/200 [00:01<00:02, 52.49 it/sec, feas=True, obj=137] INFO - 16:13:47: 32%|███▏ | 63/200 [00:01<00:02, 52.58 it/sec, feas=True, obj=137] INFO - 16:13:47: 32%|███▏ | 64/200 [00:01<00:02, 52.66 it/sec, feas=True, obj=137] INFO - 16:13:47: 32%|███▎ | 65/200 [00:01<00:02, 52.74 it/sec, feas=True, obj=137] INFO - 16:13:47: 33%|███▎ | 66/200 [00:01<00:02, 52.79 it/sec, feas=True, obj=137] INFO - 16:13:47: 34%|███▎ | 67/200 [00:01<00:02, 52.90 it/sec, feas=True, obj=137] INFO - 16:13:47: 34%|███▍ | 68/200 [00:01<00:02, 52.95 it/sec, feas=True, obj=137] INFO - 16:13:47: 34%|███▍ | 69/200 [00:01<00:02, 53.01 it/sec, feas=True, obj=137] INFO - 16:13:47: 35%|███▌ | 70/200 [00:01<00:02, 53.04 it/sec, feas=True, obj=137] INFO - 16:13:47: 36%|███▌ | 71/200 [00:01<00:02, 53.07 it/sec, feas=True, obj=137] INFO - 16:13:47: 36%|███▌ | 72/200 [00:01<00:02, 53.11 it/sec, feas=True, obj=137] INFO - 16:13:47: 36%|███▋ | 73/200 [00:01<00:02, 53.13 it/sec, feas=True, obj=137] INFO - 16:13:47: 37%|███▋ | 74/200 [00:01<00:02, 53.12 it/sec, feas=True, obj=137] INFO - 16:13:47: 38%|███▊ | 75/200 [00:01<00:02, 53.16 it/sec, feas=True, obj=137] INFO - 16:13:47: 38%|███▊ | 76/200 [00:01<00:02, 53.22 it/sec, feas=True, obj=137] INFO - 16:13:47: 38%|███▊ | 77/200 [00:01<00:02, 53.26 it/sec, feas=True, obj=137] INFO - 16:13:47: 39%|███▉ | 78/200 [00:01<00:02, 53.27 it/sec, feas=True, obj=137] INFO - 16:13:47: 40%|███▉ | 79/200 [00:01<00:02, 53.29 it/sec, feas=True, obj=137] INFO - 16:13:47: 40%|████ | 80/200 [00:01<00:02, 53.32 it/sec, feas=True, obj=137] INFO - 16:13:47: 40%|████ | 81/200 [00:01<00:02, 53.36 it/sec, feas=True, obj=137] INFO - 16:13:47: 41%|████ | 82/200 [00:01<00:02, 53.40 it/sec, feas=True, obj=137] INFO - 16:13:47: 42%|████▏ | 83/200 [00:01<00:02, 53.44 it/sec, feas=True, obj=137] INFO - 16:13:47: 42%|████▏ | 84/200 [00:01<00:02, 53.48 it/sec, feas=True, obj=137] INFO - 16:13:47: 42%|████▎ | 85/200 [00:01<00:02, 53.51 it/sec, feas=True, obj=137] INFO - 16:13:47: 43%|████▎ | 86/200 [00:01<00:02, 53.53 it/sec, feas=True, obj=137] INFO - 16:13:47: 44%|████▎ | 87/200 [00:01<00:02, 53.54 it/sec, feas=True, obj=137] INFO - 16:13:48: 44%|████▍ | 88/200 [00:01<00:02, 53.57 it/sec, feas=True, obj=137] INFO - 16:13:48: 44%|████▍ | 89/200 [00:01<00:02, 53.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 45%|████▌ | 90/200 [00:01<00:02, 53.60 it/sec, feas=True, obj=137] INFO - 16:13:48: 46%|████▌ | 91/200 [00:01<00:02, 53.63 it/sec, feas=True, obj=137] INFO - 16:13:48: 46%|████▌ | 92/200 [00:01<00:02, 53.68 it/sec, feas=True, obj=137] INFO - 16:13:48: 46%|████▋ | 93/200 [00:01<00:01, 53.73 it/sec, feas=True, obj=137] INFO - 16:13:48: 47%|████▋ | 94/200 [00:01<00:01, 53.74 it/sec, feas=True, obj=137] INFO - 16:13:48: 48%|████▊ | 95/200 [00:01<00:01, 53.78 it/sec, feas=True, obj=137] INFO - 16:13:48: 48%|████▊ | 96/200 [00:01<00:01, 53.78 it/sec, feas=True, obj=137] INFO - 16:13:48: 48%|████▊ | 97/200 [00:01<00:01, 53.83 it/sec, feas=True, obj=137] INFO - 16:13:48: 49%|████▉ | 98/200 [00:01<00:01, 53.86 it/sec, feas=True, obj=137] INFO - 16:13:48: 50%|████▉ | 99/200 [00:01<00:01, 53.87 it/sec, feas=True, obj=137] INFO - 16:13:48: 50%|█████ | 100/200 [00:01<00:01, 53.87 it/sec, feas=True, obj=137] INFO - 16:13:48: 50%|█████ | 101/200 [00:01<00:01, 53.87 it/sec, feas=True, obj=137] INFO - 16:13:48: 51%|█████ | 102/200 [00:01<00:01, 53.90 it/sec, feas=True, obj=137] INFO - 16:13:48: 52%|█████▏ | 103/200 [00:01<00:01, 53.94 it/sec, feas=True, obj=137] INFO - 16:13:48: 52%|█████▏ | 104/200 [00:01<00:01, 53.98 it/sec, feas=True, obj=137] INFO - 16:13:48: 52%|█████▎ | 105/200 [00:01<00:01, 54.00 it/sec, feas=True, obj=137] INFO - 16:13:48: 53%|█████▎ | 106/200 [00:01<00:01, 54.02 it/sec, feas=True, obj=137] INFO - 16:13:48: 54%|█████▎ | 107/200 [00:01<00:01, 54.06 it/sec, feas=True, obj=137] INFO - 16:13:48: 54%|█████▍ | 108/200 [00:01<00:01, 54.07 it/sec, feas=True, obj=137] INFO - 16:13:48: 55%|█████▍ | 109/200 [00:02<00:01, 54.11 it/sec, feas=True, obj=137] INFO - 16:13:48: 55%|█████▌ | 110/200 [00:02<00:01, 54.14 it/sec, feas=True, obj=137] INFO - 16:13:48: 56%|█████▌ | 111/200 [00:02<00:01, 54.16 it/sec, feas=True, obj=137] INFO - 16:13:48: 56%|█████▌ | 112/200 [00:02<00:01, 54.19 it/sec, feas=True, obj=137] INFO - 16:13:48: 56%|█████▋ | 113/200 [00:02<00:01, 54.22 it/sec, feas=True, obj=137] INFO - 16:13:48: 57%|█████▋ | 114/200 [00:02<00:01, 54.25 it/sec, feas=True, obj=137] INFO - 16:13:48: 57%|█████▊ | 115/200 [00:02<00:01, 54.26 it/sec, feas=True, obj=137] INFO - 16:13:48: 58%|█████▊ | 116/200 [00:02<00:01, 54.28 it/sec, feas=True, obj=137] INFO - 16:13:48: 58%|█████▊ | 117/200 [00:02<00:01, 54.28 it/sec, feas=True, obj=137] INFO - 16:13:48: 59%|█████▉ | 118/200 [00:02<00:01, 54.32 it/sec, feas=True, obj=137] INFO - 16:13:48: 60%|█████▉ | 119/200 [00:02<00:01, 54.36 it/sec, feas=True, obj=137] INFO - 16:13:48: 60%|██████ | 120/200 [00:02<00:01, 54.39 it/sec, feas=True, obj=137] INFO - 16:13:48: 60%|██████ | 121/200 [00:02<00:01, 54.43 it/sec, feas=True, obj=137] INFO - 16:13:48: 61%|██████ | 122/200 [00:02<00:01, 54.47 it/sec, feas=True, obj=137] INFO - 16:13:48: 62%|██████▏ | 123/200 [00:02<00:01, 54.52 it/sec, feas=True, obj=137] INFO - 16:13:48: 62%|██████▏ | 124/200 [00:02<00:01, 54.54 it/sec, feas=True, obj=137] INFO - 16:13:48: 62%|██████▎ | 125/200 [00:02<00:01, 54.55 it/sec, feas=True, obj=137] INFO - 16:13:48: 63%|██████▎ | 126/200 [00:02<00:01, 54.56 it/sec, feas=True, obj=137] INFO - 16:13:48: 64%|██████▎ | 127/200 [00:02<00:01, 54.58 it/sec, feas=True, obj=137] INFO - 16:13:48: 64%|██████▍ | 128/200 [00:02<00:01, 54.58 it/sec, feas=True, obj=137] INFO - 16:13:48: 64%|██████▍ | 129/200 [00:02<00:01, 54.57 it/sec, feas=True, obj=137] INFO - 16:13:48: 65%|██████▌ | 130/200 [00:02<00:01, 54.56 it/sec, feas=True, obj=137] INFO - 16:13:48: 66%|██████▌ | 131/200 [00:02<00:01, 54.56 it/sec, feas=True, obj=137] INFO - 16:13:48: 66%|██████▌ | 132/200 [00:02<00:01, 54.60 it/sec, feas=True, obj=137] INFO - 16:13:48: 66%|██████▋ | 133/200 [00:02<00:01, 54.60 it/sec, feas=True, obj=137] INFO - 16:13:48: 67%|██████▋ | 134/200 [00:02<00:01, 54.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 68%|██████▊ | 135/200 [00:02<00:01, 54.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 68%|██████▊ | 136/200 [00:02<00:01, 54.60 it/sec, feas=True, obj=137] INFO - 16:13:48: 68%|██████▊ | 137/200 [00:02<00:01, 54.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 69%|██████▉ | 138/200 [00:02<00:01, 54.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 70%|██████▉ | 139/200 [00:02<00:01, 54.60 it/sec, feas=True, obj=137] INFO - 16:13:48: 70%|███████ | 140/200 [00:02<00:01, 54.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 70%|███████ | 141/200 [00:02<00:01, 54.58 it/sec, feas=True, obj=137] INFO - 16:13:48: 71%|███████ | 142/200 [00:02<00:01, 54.59 it/sec, feas=True, obj=137] INFO - 16:13:48: 72%|███████▏ | 143/200 [00:02<00:01, 54.60 it/sec, feas=True, obj=137] INFO - 16:13:48: 72%|███████▏ | 144/200 [00:02<00:01, 54.62 it/sec, feas=True, obj=137] INFO - 16:13:49: 72%|███████▎ | 145/200 [00:02<00:01, 54.63 it/sec, feas=True, obj=137] INFO - 16:13:49: 73%|███████▎ | 146/200 [00:02<00:00, 54.64 it/sec, feas=True, obj=137] INFO - 16:13:49: 74%|███████▎ | 147/200 [00:02<00:00, 54.66 it/sec, feas=True, obj=137] INFO - 16:13:49: 74%|███████▍ | 148/200 [00:02<00:00, 54.68 it/sec, feas=True, obj=137] INFO - 16:13:49: 74%|███████▍ | 149/200 [00:02<00:00, 54.69 it/sec, feas=True, obj=137] INFO - 16:13:49: 75%|███████▌ | 150/200 [00:02<00:00, 54.69 it/sec, feas=True, obj=137] INFO - 16:13:49: 76%|███████▌ | 151/200 [00:02<00:00, 54.69 it/sec, feas=True, obj=137] INFO - 16:13:49: 76%|███████▌ | 152/200 [00:02<00:00, 54.70 it/sec, feas=True, obj=137] INFO - 16:13:49: 76%|███████▋ | 153/200 [00:02<00:00, 54.70 it/sec, feas=True, obj=137] INFO - 16:13:49: 77%|███████▋ | 154/200 [00:02<00:00, 54.72 it/sec, feas=True, obj=137] INFO - 16:13:49: 78%|███████▊ | 155/200 [00:02<00:00, 54.73 it/sec, feas=True, obj=137] INFO - 16:13:49: 78%|███████▊ | 156/200 [00:02<00:00, 54.73 it/sec, feas=True, obj=137] INFO - 16:13:49: 78%|███████▊ | 157/200 [00:02<00:00, 54.73 it/sec, feas=True, obj=137] INFO - 16:13:49: 79%|███████▉ | 158/200 [00:02<00:00, 54.72 it/sec, feas=True, obj=137] INFO - 16:13:49: 80%|███████▉ | 159/200 [00:02<00:00, 54.76 it/sec, feas=True, obj=137] INFO - 16:13:49: 80%|████████ | 160/200 [00:02<00:00, 54.78 it/sec, feas=True, obj=137] INFO - 16:13:49: 80%|████████ | 161/200 [00:02<00:00, 54.81 it/sec, feas=True, obj=137] INFO - 16:13:49: 81%|████████ | 162/200 [00:02<00:00, 54.85 it/sec, feas=True, obj=137] INFO - 16:13:49: 82%|████████▏ | 163/200 [00:02<00:00, 54.87 it/sec, feas=True, obj=137] INFO - 16:13:49: 82%|████████▏ | 164/200 [00:02<00:00, 54.86 it/sec, feas=True, obj=137] INFO - 16:13:49: 82%|████████▎ | 165/200 [00:03<00:00, 54.87 it/sec, feas=True, obj=137] INFO - 16:13:49: 83%|████████▎ | 166/200 [00:03<00:00, 54.88 it/sec, feas=True, obj=137] INFO - 16:13:49: 84%|████████▎ | 167/200 [00:03<00:00, 54.89 it/sec, feas=True, obj=137] INFO - 16:13:49: 84%|████████▍ | 168/200 [00:03<00:00, 54.90 it/sec, feas=True, obj=137] INFO - 16:13:49: 84%|████████▍ | 169/200 [00:03<00:00, 54.91 it/sec, feas=True, obj=137] INFO - 16:13:49: 85%|████████▌ | 170/200 [00:03<00:00, 54.93 it/sec, feas=True, obj=137] INFO - 16:13:49: 86%|████████▌ | 171/200 [00:03<00:00, 54.97 it/sec, feas=True, obj=137] INFO - 16:13:49: 86%|████████▌ | 172/200 [00:03<00:00, 54.97 it/sec, feas=True, obj=137] INFO - 16:13:49: 86%|████████▋ | 173/200 [00:03<00:00, 55.00 it/sec, feas=True, obj=137] INFO - 16:13:49: 87%|████████▋ | 174/200 [00:03<00:00, 55.00 it/sec, feas=True, obj=137] INFO - 16:13:49: 88%|████████▊ | 175/200 [00:03<00:00, 55.03 it/sec, feas=True, obj=137] INFO - 16:13:49: 88%|████████▊ | 176/200 [00:03<00:00, 55.03 it/sec, feas=True, obj=137] INFO - 16:13:49: 88%|████████▊ | 177/200 [00:03<00:00, 55.05 it/sec, feas=True, obj=137] INFO - 16:13:49: 89%|████████▉ | 178/200 [00:03<00:00, 55.05 it/sec, feas=True, obj=137] INFO - 16:13:49: 90%|████████▉ | 179/200 [00:03<00:00, 55.06 it/sec, feas=True, obj=137] INFO - 16:13:49: 90%|█████████ | 180/200 [00:03<00:00, 55.09 it/sec, feas=True, obj=137] INFO - 16:13:49: 90%|█████████ | 181/200 [00:03<00:00, 55.09 it/sec, feas=True, obj=137] INFO - 16:13:49: 91%|█████████ | 182/200 [00:03<00:00, 55.12 it/sec, feas=True, obj=137] INFO - 16:13:49: 92%|█████████▏| 183/200 [00:03<00:00, 55.14 it/sec, feas=True, obj=137] INFO - 16:13:49: 92%|█████████▏| 184/200 [00:03<00:00, 55.16 it/sec, feas=True, obj=137] INFO - 16:13:49: 92%|█████████▎| 185/200 [00:03<00:00, 55.19 it/sec, feas=True, obj=137] INFO - 16:13:49: 93%|█████████▎| 186/200 [00:03<00:00, 55.20 it/sec, feas=True, obj=137] INFO - 16:13:49: 94%|█████████▎| 187/200 [00:03<00:00, 55.22 it/sec, feas=True, obj=137] INFO - 16:13:49: 94%|█████████▍| 188/200 [00:03<00:00, 55.25 it/sec, feas=True, obj=137] INFO - 16:13:49: 94%|█████████▍| 189/200 [00:03<00:00, 55.28 it/sec, feas=True, obj=137] INFO - 16:13:49: 95%|█████████▌| 190/200 [00:03<00:00, 55.31 it/sec, feas=True, obj=137] INFO - 16:13:49: 96%|█████████▌| 191/200 [00:03<00:00, 55.34 it/sec, feas=True, obj=137] INFO - 16:13:49: 96%|█████████▌| 192/200 [00:03<00:00, 55.35 it/sec, feas=True, obj=137] INFO - 16:13:49: 96%|█████████▋| 193/200 [00:03<00:00, 55.36 it/sec, feas=True, obj=137] INFO - 16:13:49: 97%|█████████▋| 194/200 [00:03<00:00, 55.39 it/sec, feas=True, obj=137] INFO - 16:13:49: 98%|█████████▊| 195/200 [00:03<00:00, 55.39 it/sec, feas=True, obj=137] INFO - 16:13:49: 98%|█████████▊| 196/200 [00:03<00:00, 55.41 it/sec, feas=True, obj=137] INFO - 16:13:49: 98%|█████████▊| 197/200 [00:03<00:00, 55.44 it/sec, feas=True, obj=137] INFO - 16:13:49: 99%|█████████▉| 198/200 [00:03<00:00, 55.46 it/sec, feas=True, obj=137] INFO - 16:13:49: 100%|█████████▉| 199/200 [00:03<00:00, 55.47 it/sec, feas=True, obj=137] INFO - 16:13:49: 100%|██████████| 200/200 [00:03<00:00, 55.50 it/sec, feas=True, obj=137] INFO - 16:13:49: Optimization result: INFO - 16:13:49: Optimizer info: INFO - 16:13:49: Status: None INFO - 16:13:49: Message: Maximum number of iterations reached. GEMSEO stopped the driver. INFO - 16:13:49: Solution: INFO - 16:13:49: The solution is feasible. INFO - 16:13:49: Objective: 136.5606526095802 INFO - 16:13:49: Standardized constraints: INFO - 16:13:49: [volume fraction-0.3] = 1.0310935563140333e-06 INFO - 16:13:49: *** End MDOScenario execution *** .. GENERATED FROM PYTHON SOURCE LINES 99-102 Results ------- Post-process the optimization history: .. GENERATED FROM PYTHON SOURCE LINES 102-106 .. code-block:: Python scenario.post_process( post_name="BasicHistory", variable_names=["compliance"], show=True, save=False ) .. image-sg:: /examples/topology_optimization/images/sphx_glr_plot_topology_optimization_short_cantilever_001.png :alt: History plot :srcset: /examples/topology_optimization/images/sphx_glr_plot_topology_optimization_short_cantilever_001.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none .. GENERATED FROM PYTHON SOURCE LINES 107-108 Plot the solution .. GENERATED FROM PYTHON SOURCE LINES 108-109 .. code-block:: Python scenario.post_process(post_name="TopologyView", n_x=n_x, n_y=n_y, show=True, save=False) .. image-sg:: /examples/topology_optimization/images/sphx_glr_plot_topology_optimization_short_cantilever_002.png :alt: plot topology optimization short cantilever :srcset: /examples/topology_optimization/images/sphx_glr_plot_topology_optimization_short_cantilever_002.png :class: sphx-glr-single-img .. rst-class:: sphx-glr-script-out .. code-block:: none .. rst-class:: sphx-glr-timing **Total running time of the script:** (0 minutes 4.778 seconds) .. _sphx_glr_download_examples_topology_optimization_plot_topology_optimization_short_cantilever.py: .. only:: html .. container:: sphx-glr-footer sphx-glr-footer-example .. container:: sphx-glr-download sphx-glr-download-jupyter :download:`Download Jupyter notebook: plot_topology_optimization_short_cantilever.ipynb ` .. container:: sphx-glr-download sphx-glr-download-python :download:`Download Python source code: plot_topology_optimization_short_cantilever.py ` .. container:: sphx-glr-download sphx-glr-download-zip :download:`Download zipped: plot_topology_optimization_short_cantilever.zip ` .. only:: html .. rst-class:: sphx-glr-signature `Gallery generated by Sphinx-Gallery `_