.. DO NOT EDIT.
.. THIS FILE WAS AUTOMATICALLY GENERATED BY SPHINX-GALLERY.
.. TO MAKE CHANGES, EDIT THE SOURCE PYTHON FILE:
.. "examples/topology_optimization/topology_optimization_short_cantilever.py"
.. LINE NUMBERS ARE GIVEN BELOW.

.. only:: html

    .. note::
        :class: sphx-glr-download-link-note

        :ref:`Go to the end <sphx_glr_download_examples_topology_optimization_topology_optimization_short_cantilever.py>`
        to download the full example code

.. rst-class:: sphx-glr-example-title

.. _sphx_glr_examples_topology_optimization_topology_optimization_short_cantilever.py:


Solve a 2D short cantilever topology optimization problem
=========================================================

.. GENERATED FROM PYTHON SOURCE LINES 23-32

.. code-block:: default

    from __future__ import annotations

    from gemseo import configure_logger
    from gemseo import create_scenario
    from gemseo.problems.topo_opt.topopt_initialize import (
        initialize_design_space_and_discipline_to,
    )

    configure_logger()

.. GENERATED FROM PYTHON SOURCE LINES 33-36

Setup the topology optimization problem
---------------------------------------
Define the target volume fraction:

.. GENERATED FROM PYTHON SOURCE LINES 36-38

.. code-block:: default

    volume_fraction = 0.3


.. GENERATED FROM PYTHON SOURCE LINES 39-40

Define the problem type:

.. GENERATED FROM PYTHON SOURCE LINES 40-42

.. code-block:: default

    problem_name = "Short_Cantilever"


.. GENERATED FROM PYTHON SOURCE LINES 43-44

Define the number of elements in the x- and y- directions:

.. GENERATED FROM PYTHON SOURCE LINES 44-47

.. code-block:: default

    n_x = 50
    n_y = 25


.. GENERATED FROM PYTHON SOURCE LINES 48-49

Define the full material Young's modulus and Poisson's ratio:

.. GENERATED FROM PYTHON SOURCE LINES 49-52

.. code-block:: default

    e0 = 1
    nu = 0.3


.. GENERATED FROM PYTHON SOURCE LINES 53-54

Define the penalty of the SIMP approach:

.. GENERATED FROM PYTHON SOURCE LINES 54-56

.. code-block:: default

    penalty = 3


.. GENERATED FROM PYTHON SOURCE LINES 57-58

Define the minimum member size in the solution:

.. GENERATED FROM PYTHON SOURCE LINES 58-60

.. code-block:: default

    min_memeber_size = 1.5


.. GENERATED FROM PYTHON SOURCE LINES 61-62

Instantiate the :class:`.DesignSpace` and the disciplines:

.. GENERATED FROM PYTHON SOURCE LINES 62-74

.. code-block:: default


    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_memeber_size,
        vf0=volume_fraction,
    )


.. GENERATED FROM PYTHON SOURCE LINES 75-78

Solve the topology optimization problem
---------------------------------------
Generate a :class:`.MDOScenario`:

.. GENERATED FROM PYTHON SOURCE LINES 78-85

.. code-block:: default

    scenario = create_scenario(
        disciplines,
        formulation="DisciplinaryOpt",
        objective_name="compliance",
        design_space=design_space,
    )


.. GENERATED FROM PYTHON SOURCE LINES 86-87

Add the volume fraction constraint to the scenario:

.. GENERATED FROM PYTHON SOURCE LINES 87-89

.. code-block:: default

    scenario.add_constraint("volume fraction", "ineq", value=volume_fraction)


.. GENERATED FROM PYTHON SOURCE LINES 90-91

Generate the XDSM:

.. GENERATED FROM PYTHON SOURCE LINES 91-93

.. code-block:: default

    scenario.xdsmize()


.. GENERATED FROM PYTHON SOURCE LINES 94-95

Execute the scenario:

.. GENERATED FROM PYTHON SOURCE LINES 95-97

.. code-block:: default

    scenario.execute(input_data={"max_iter": 200, "algo": "NLOPT_MMA"})


.. GENERATED FROM PYTHON SOURCE LINES 98-101

Results
-------
Post-process the optimization history:

.. GENERATED FROM PYTHON SOURCE LINES 101-106

.. code-block:: default

    scenario.post_process(
        "BasicHistory",
        variable_names=["compliance"],
        file_name=f"{problem_name}_history.png",
    )

.. GENERATED FROM PYTHON SOURCE LINES 107-108

Plot the solution:

.. GENERATED FROM PYTHON SOURCE LINES 108-114

.. code-block:: default

    scenario.post_process(
        "TopologyView",
        n_x=n_x,
        n_y=n_y,
        file_name=f"{problem_name}_solution.png",
    )


.. rst-class:: sphx-glr-timing

   **Total running time of the script:** ( 0 minutes  0.000 seconds)


.. _sphx_glr_download_examples_topology_optimization_topology_optimization_short_cantilever.py:

.. only:: html

  .. container:: sphx-glr-footer sphx-glr-footer-example




    .. container:: sphx-glr-download sphx-glr-download-python

      :download:`Download Python source code: topology_optimization_short_cantilever.py <topology_optimization_short_cantilever.py>`

    .. container:: sphx-glr-download sphx-glr-download-jupyter

      :download:`Download Jupyter notebook: topology_optimization_short_cantilever.ipynb <topology_optimization_short_cantilever.ipynb>`


.. only:: html

 .. rst-class:: sphx-glr-signature

    `Gallery generated by Sphinx-Gallery <https://sphinx-gallery.github.io>`_