SigmaEpsilon.Solid.Material - Classes and algorithms for solids in Python#
Version: 2.3.0
Useful links: Getting started | User Guide | Gallery | API Reference | Source Repository
The sigmaepsilon.solid.material is a set of tools to handle problems to related to solid mechanics, namely those with questions of stiffness and strength of materials.
The implementations in the library all rely on fast and efficient algorithms provided by the goodies of NumPy, SciPy and the likes. Where necessary, computationally intensive parts of the code are written using Numba. Some evaluators also support calculating on the GPU (mostly on NVIDIA), for which we are using CuPy and Numba. Symbolic calculations are done with SymPy.
Highlights#
Classes to handle linear elastic materials of all kinds.
Elastic stiffness calculations for all kinds of models like Uflyand-Mindlin shells, Kirchhoff-Love shells, Timoshenko-Ehrenfest and Euler-Bernoulli beams, 3d bodies, etc.
Utilization calculations.
Fitting of failure models to observed data.
NumPy-compilant data classes to handle stiffness, strains and stresses.
Fast and efficient code with GPU support.
Installation#
You can install the project from PyPI with pip:
$ pip install sigmaepsilon.solid.material
If want to execute on the GPU, you need to manually install the necessary requirements. Numba is a direct dependency, so even in this case you have to care about having the prover version of the cuda toolkit installed. For this, you need to know the version of the cuda compute engine, which depends on the version of GPU card you are having.
Contents#
Getting Started
The getting started guide contains a basic introduction to the main concepts through simple examples.
User Guide
The user guide provides a more detailed walkthrough of the library, touching the key features with useful background information and explanation.
API Reference
The reference guide contains a detailed description of the functions, modules, and objects included in the library. The reference describes how the methods work and which parameters can be used. It assumes that you have an understanding of the key concepts.
Examples Gallery
A gallery of examples that illustrate uses cases that involve some kind of visualization.