SigmaEpsilon.Solid.Fourier - Fourier solutions of some plate and beam bending problems in Python#
Version: 0.0.1a0
Useful links: Getting started | User Guide | Gallery | API Reference | Source Repository
Warning
This project is currently in an alpha stage. It’s important to note that the authors are aware of certain areas in the documentation that require improvement. As this is an early stage project, some features and functionalities might be incomplete or subject to change. We appreciate your understanding and welcome any feedback to enhance the project.
The sigmaepsilon.solid.fourier library offers semi-analytic solutions to some beam and plate bending problems, where the boundary conditions are a-priori satisfied by careful selection of the approximating functions. Although the calculations only cover a handful of boundary conditions, when they are applicable, they are significantly faster than let say a finite element solution. For this reason, it is very useful for a couple of things:
experimentation
verification
concept validation
education
publication
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.
Highlights#
Semi-analytic, Navier solutions of beam and plate problems.
Easy to use, high level interface to define various kinds of loads.
Support for arbitrary loads using Monte-Carlo based coefficient determination.
Industry-grade performance based on highly parallel, performant code.
Tight integration with popular Python libraries like NumPy, SciPy, xarray, etc.
A gallery of examples for plotting with Matplotlib for all types of problems.
A collection of downloadable Jupyter Notebooks ready for execution covering all available functionality.
Getting Started, User Guide and API Reference in the documentation.
The library is intensively tested on CircleCI and has a high coverage level.
Installation#
You can install the project from PyPI with pip:
$ pip install sigmaepsilon.solid.fourier
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.