Metadata-Version: 2.1
Name: ffpack
Version: 0.2.0
Summary: Fatigue and fracture package
Home-page: https://pypi.org/project/ffpack
Keywords: fatigue,fracture,counting
Author: Dongping Zhu
Maintainer: Dongping Zhu
Requires-Python: >=3.7,<4.0
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: 3.9
Classifier: Programming Language :: Python :: 3.10
Classifier: Programming Language :: Python :: 3.11
Classifier: Programming Language :: Python :: 3
Classifier: Topic :: Scientific/Engineering
Requires-Dist: numpy (>=1.21,<2.0)
Project-URL: Documentation, https://ffpack.readthedocs.io/en/latest/
Project-URL: Repository, https://github.com/dpzhuX/ffpack
Description-Content-Type: text/markdown

# FFPACK - Fatigue and Fracture PACKage

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[![DOI](https://zenodo.org/badge/575208693.svg)](https://zenodo.org/badge/latestdoi/575208693)

## Purpose
`FFPACK` ( Fatigue and Fracture PACKage ) is an open-source Python library for fatigue and fracture analysis. It supports load cycle counting with ASTM methods, load sequence generators, fatigue damage evaluations, etc. A lot of features are under active development. `FFPACK` is designed to help engineers analyze fatigue and fracture behavior in engineering practice.

## Installation

`FFPACK` can be installed via [PyPI](https://pypi.org/project/ffpack/):

```
pip install ffpack
```

## Status

`FFPACK` is currently under active development. 

## Contents

* Fatigue damage rule
    * Palmgren-miner damage rule
        * Naive Palmgren-miner damage rule
        * Classic Palmgren-miner damage rule

* Load cycle counting
    * ASTM
        * ASTM level crossing counting
        * ASTM peak counting
        * ASTM simple range counting
        * ASTM rainflow counting
    * Rychlik
        * Rychlik rainflow Counting

* Load sequence generator
    * Random walk
        * Uniform random walk
    * Autoregressive model
        * Normal autoregressive model

* Utility methods
    * Cycle counting aggregation
    * Fitter for SN curve
    * Sequence peak and valleys
    * Sequence degitization

## Document

You can find a complete documentation for setting up `FFPACK` at the [Read the Docs site](https://ffpack.readthedocs.io/en/latest/).

