.. TopOpt documentation master file

TopOpt --- Topology Optimization in Python
==========================================

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- **Free Software**: MIT License
- **Github Repository**: https://github.com/zfergus/topopt

.. warning::
    This library is in early stages of development and consequently the API may
    change to better improve usability.

`Topology optimization
<https://en.wikipedia.org/wiki/Topology_optimization>`_ is a form of structure
optimization where the design variable is the topology of the structure.
Topological changes are achieved by optimizing the material distribution within
a given design space.

TopOpt is a python library for topology optimization. TopOpt contains common
design problems (e.g. minimum compliance) solved using advanced methods
(e.g. Method of Moving Asymptotes (MMA)). Using TopOpt we can optimize the
classic Messerschmitt–Bölkow–Blohm (MBB) beam in a few lines of code:

.. code-block:: python

    import numpy
    from topopt.boundary_conditions import MBBBeamBoundaryConditions
    from topopt.problems import ComplianceProblem
    from topopt.solvers import TopOptSolver
    from topopt.filters import DensityBasedFilter
    from topopt.guis import GUI

    nelx, nely = 180, 60  # Number of elements in the x and y
    volfrac = 0.4  # Volume fraction for constraints
    penal = 3.0  # Penalty for SIMP
    rmin = 5.4  # Filter radius

    # Initial solution
    x = volfrac * numpy.ones(nely * nelx, dtype=float)

    # Boundary conditions defining the loads and fixed points
    bc = MBBBeamBoundaryConditions(nelx, nely)

    # Problem to optimize given objective and constraints
    problem = ComplianceProblem(bc, penal)
    gui = GUI(problem, "Topology Optimization Example")
    topopt_filter = DensityBasedFilter(nelx, nely, rmin)
    solver = TopOptSolver(problem, volfrac, topopt_filter, gui)
    x_opt = solver.optimize(x)

    input("Press enter...")

**Output:**

.. image:: ../../assets/imgs/mmb-beam-example.png
    :alt: TopOpt Example
    :align: center

.. .. literalinclude:: ../../topopt/mechanisms/boundary_conditions.py
..     :language: python
..     :pyobject: DisplacementInverterBoundaryConditions

.. toctree::
    :hidden:
    :maxdepth: 2
    :caption: General

    installation
    concepts
    examples
    changelog

.. .. toctree::
..     :hidden:
..     :maxdepth: 2
..     :caption: Developers
..
..     contributing

.. toctree::
    :hidden:
    :maxdepth: 2
    :caption: API Documentation

    api/topopt.problems
    api/topopt.solvers
    api/topopt.boundary_conditions
    api/topopt.filters
    api/topopt.mechanisms
    api/topopt.guis
    api/topopt.cli

Development Status
------------------

TopOpt is in early stages of development and only features a limited set of
finite element mesh options, optimization problems, and solvers. The following
is a list of current and future features of TopOpt:

Meshes
~~~~~~
- ✅ 2D regular grid
- ⬜ 2D general mesh
    + ⬜ triangle mesh
    + ⬜ quadrilateral mesh
- ⬜ 3D regular grid
- ⬜ 3D general mesh
    + ⬜ tetrahedron mesh
    + ⬜ hexahedron mesh

Problems
~~~~~~~~
- ⬜ compliance
    - ✅ linear elasticity
    - ⬜ non-linear elasticity
- ⬜ stress
- ⬜ thermal conductivity
- ⬜ fluid flow

Solvers
~~~~~~~
- ⬜ `optimality criterion <https://en.wikipedia.org/wiki/Optimality_criterion>`_
- ✅ method of moving asymptotes (MMA)
- ⬜  `genetic algorithms <https://en.wikipedia.org/wiki/Genetic_algorithm>`_


Indices and tables
------------------

- :ref:`genindex`
- :ref:`modindex`
- :ref:`search`