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======= fatpack

Python package for fatigue analysis of data series. The package requires numpy.

Installation

Either download the repository to your computer and install, e.g. by pip

::

pip install .

or install directly from the python package index.

::

pip install fatpack

Usage

The package provides classes and functions for rainflow cycle counting, defining endurance curves, mean and compressive stress range correction and racetrack filtering. The code example below shows how fatigue damage can be calculated:

.. code:: python

import numpy as np
import fatpack


# Assume that `y` is the data series, we generate one here
y = np.random.normal(0., 30., size=10000)

# Extract the stress ranges by rainflow counting
S = fatpack.find_rainflow_ranges(y)

# Determine the fatigue damage, using a trilinear fatigue curve
# with detail category Sc, Miner's linear damage summation rule.
Sc = 90.0
curve = fatpack.TriLinearEnduranceCurve(Sc)
fatigue_damage = curve.find_miner_sum(S)

An example is included (example.py <https://github.com/Gunnstein/fatpack/blob/master/example.py>_) which extracts rainflow cycles, generates the rainflow matrix and rainflow stress spectrum, see the figure presented below. The example is a good place to start to get into the use of the package.

|example_img|

Additional examples are found in the examples folder <https://github.com/Gunnstein/fatpack/tree/master/examples>_.

Support

Please open an issue <https://github.com/Gunnstein/fatpack/issues/new>_ for support.

Contributing

Please contribute using Github Flow <https://guides.github.com/introduction/flow/>. Create a branch, add commits, and open a pull request <https://github.com/Gunnstein/fatpack/compare/>.

.. |logo_img| image:: https://github.com/Gunnstein/fatpack/blob/master/fatpack-logo.png :target: https://github.com/gunnstein/fatpack/

.. |example_img| image:: https://github.com/Gunnstein/fatpack/blob/master/example.png :target: https://github.com/gunnstein/fatpack/