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Efficient Python implementation demonstrating Discontinuity Layout Optimisation (DLO) for assessing geotechnical failure mechanisms

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DLOpy

Efficient Python implementation demonstrating Discontinuity Layout Optimisation (DLO) for assessing geotechnical failure mechanisms.

This repository is intended for handy open stack demonstration and/or research purposes to support the cross-discipline discovery of Linear Programming (LP) applications and numerical methods in general. For commercial practices please see LimitState:GEO.

Note herein also examples and ideas on implementing Numba (compiled generalized universal functions for NumPy arrays), SciPy (linear programming) and Sklearn (graph computing) for efficient numerical computation.

Getting Started & Usage

Clone the repository ensuring the dependencies in the requirements file are satisfied in the active Python environment, then start by running the files in the tests and examples folders.

Alternatively, to install in an active Python environment and run as demonstrated in the examples files, in the command line:

pip install git+https://github.com/dlincoln/dlopy

Prandtl Failure Mechanism

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Efficient Python implementation demonstrating Discontinuity Layout Optimisation (DLO) for assessing geotechnical failure mechanisms

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