solidsp


Namesolidsp JSON
Version 0.1 PyPI version JSON
download
home_pagehttps://github.com/AppliedMechanics-EAFIT/SolidsPy
SummaryA simple Finite Element program
upload_time2023-11-03 17:37:52
maintainer
docs_urlNone
authorNicolas Guarin-Zapata <nguarinz@eafit.edu.co>, Juan Gomez <jgomezc1@eafit.edu.co>
requires_python
licenseMIT
keywords finite-elements fem scientific-computing
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            ---

title: "SolidsPy: 2D-Finite Element Analysis with Python"

---



![](https://raw.githubusercontent.com/AppliedMechanics-EAFIT/SolidsPy/master/docs/img/wrench.png)



[![PyPI download](https://img.shields.io/pypi/v/solidspy.svg)](https://pypi.python.org/pypi/continuum_mechanics)



[![Documentation Status](https://readthedocs.org/projects/solidspy/badge/?version=latest)](https://solidspy.readthedocs.io/en/latest/)



[![Downloads frequency](https://img.shields.io/pypi/dm/solidspy)](https://pypistats.org/packages/solidspy)



[![image](https://zenodo.org/badge/48294591.svg)](https://zenodo.org/badge/latestdoi/48294591)



A simple finite element analysis code for 2D elasticity problems. The

code uses as input simple-to-create text files defining a model in terms

of nodal, element, material and load data.



-   Documentation: <http://solidspy.readthedocs.io>

-   GitHub: <https://github.com/AppliedMechanics-EAFIT/SolidsPy>

-   PyPI: <https://pypi.org/project/solidspy/>

-   Free and open source software: [MIT

    license](http://en.wikipedia.org/wiki/MIT_License)



# Features



-   It is based on an open-source environment.

-   It is easy to use.

-   The code allows to find displacement, strain and stress solutions

    for arbitrary two-dimensional domains discretized into finite

    elements and subject to point loads.

-   The code is organized in independent modules for pre-processing,

    assembly and post-processing allowing the user to easily modify it

    or add features like new elements or analyses pipelines.

-   It was created with academic and research purposes.

-   It has been used to tech the following courses:

    -   Computational Modeling.

    -   Introduction to the Finite Element Methods.



# Installation



The code is written in Python and it depends on `numpy`, and `scipy`

and. It has been tested under Windows, Mac, Linux and Android.



To install *SolidsPy* open a terminal and type:



    pip install solidspy



To specify through a GUI the folder where the input files are stored you

will need to install

[easygui](http://easygui.readthedocs.org/en/master/).



To easily generate the required SolidsPy text files out of a

[Gmsh](http://gmsh.info/) model you will need

[meshio](https://github.com/nschloe/meshio).



These two can be installed with:



    pip install easygui

    pip install meshio



# How to run a simple model



For further explanation check the

[docs](http://solidspy.readthedocs.io/en/latest/).



Let\'s suppose that we have a simple model represented by the following

files (see [tutorials/square

example](http://solidspy.readthedocs.io/en/latest/tutorials/square_example.html)

for further explanation).



-   `nodes.txt`



```{=html}

<!-- -->

```

    0  0.00  0.00   0  -1

    1  2.00  0.00   0  -1

    2  2.00  2.00   0   0

    3  0.00  2.00   0   0

    4  1.00  0.00  -1  -1

    5  2.00  1.00   0   0

    6  1.00  2.00   0   0

    7  0.00  1.00   0   0

    8  1.00  1.00   0   0



-   `eles.txt`



```{=html}

<!-- -->

```

    0   1   0   0   4   8   7

    1   1   0   4   1   5   8

    2   1   0   7   8   6   3

    3   1   0   8   5   2   6



-   `mater.txt`



```{=html}

<!-- -->

```

    1.0  0.3



-   `loads.txt`



```{=html}

<!-- -->

```

    3  0.0  1.0

    6  0.0  2.0

    2  0.0  1.0



Run it in Python as follows:



``` python

import matplotlib.pyplot as plt  # load matplotlib

from solidspy import solids_GUI  # import our package

disp = solids_GUI()  # run the Finite Element Analysis

plt.show()    # plot contours

```



For Mac users it is suggested to use an IPython console to run the

example.



# License



This project is licensed under the [MIT

license](http://en.wikipedia.org/wiki/MIT_License). The documents are

licensed under [Creative Commons Attribution

License](http://creativecommons.org/licenses/by/4.0/).



# Citation



To cite SolidsPy in publications use



> Nicolás Guarín-Zapata, Juan Gomez (2020). SolidsPy: Version 1.0.16

> (Version v1.0.16). Zenodo. <http://doi.org/10.5281/zenodo.4029270>



A BibTeX entry for LaTeX users is



``` bibtex

@software{solidspy,

 title = {SolidsPy: 2D-Finite Element Analysis with Python},

 version = {1.0.16},

 author = {Guarín-Zapata, Nicolás and Gómez, Juan},

 year = 2020,

 keywords = {Python, Finite elements, Scientific computing, Computational mechanics},

 abstract = {SolidsPy is a simple finite element analysis code for

   2D elasticity problems. The code uses as input simple-to-create text

   files defining a model in terms of nodal, element, material and

   load data.},

 url = {https://github.com/AppliedMechanics-EAFIT/SolidsPy},

 doi = {http://doi.org/10.5281/zenodo.4029270}

}

```


            

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The\r\r\ncode uses as input simple-to-create text files defining a model in terms\r\r\nof nodal, element, material and load data.\r\r\n\r\r\n-   Documentation: <http://solidspy.readthedocs.io>\r\r\n-   GitHub: <https://github.com/AppliedMechanics-EAFIT/SolidsPy>\r\r\n-   PyPI: <https://pypi.org/project/solidspy/>\r\r\n-   Free and open source software: [MIT\r\r\n    license](http://en.wikipedia.org/wiki/MIT_License)\r\r\n\r\r\n# Features\r\r\n\r\r\n-   It is based on an open-source environment.\r\r\n-   It is easy to use.\r\r\n-   The code allows to find displacement, strain and stress solutions\r\r\n    for arbitrary two-dimensional domains discretized into finite\r\r\n    elements and subject to point loads.\r\r\n-   The code is organized in independent modules for pre-processing,\r\r\n    assembly and post-processing allowing the user to easily modify it\r\r\n    or add features like new elements or analyses pipelines.\r\r\n-   It was created with academic and research purposes.\r\r\n-   It has been used to tech the following courses:\r\r\n    -   Computational Modeling.\r\r\n    -   Introduction to the Finite Element Methods.\r\r\n\r\r\n# Installation\r\r\n\r\r\nThe code is written in Python and it depends on `numpy`, and `scipy`\r\r\nand. 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