The files correspond to the article in the Journal Composites Part C: Open Access: https://doi.org/10.1016/j.jcomc.2020.100072 (2021)
LAYLA is a deterministic method for optimising composite laminate lay-ups satisfying lay-up design guidelines.
Requirements:
-
A python IDE running python 3.7+
-
The following libraries should accessible:
- matplotlib
- pandas
- numpy
In order to use it:
-
clone or download the repository in your desired folder.
-
Set up your environment with the appropriate libraries.
-
Change the settings and run one of the files used to test LAYLA: run_LAYLA_V02.py, run_LAYLA_V02_SSpop.py, run_LAYLA_V02_loop.py, run_LAYLA_vs_BBK.py
Folder Structure
-
src and subfolders contain the files needed to run the code
-
populations contains the files storing the stacking sequence populations used for testing LAYLA
-
results-paper-LAYLA-V02 contains the results and analyses generated for the paper.
-
run_LAYLA_V02.py is used for to run LAYLA for optimising one composite laminate lay-up.
-
run_LAYLA_V02_SSpop.py is used for testing LAYLA capacity at retrieving populations of laminate lay-ups based on their lamination parameters and ply counts.
-
run_LAYLA_V02_loop.py is used for testing LAYLA capacity at retrieving laminate lay-ups based on their lamination parameters and increasing ply counts.
-
run_LAYLA_vs_BBK.py is used for comparing the optimiser LAYLA and the 'branch-and-bound'-based optimiser of Liu Xiaoyang by running both optimiser for a population of lay-up lamination parameters.
Version 1.0.0
License
This project is licensed under the MIT License. See the LICENSE for details.
Acknowledgments
- Terence Macquart, Paul Weaver and Alberto Pirrera, my PhD supervisors.
Author:
Noémie Fedon
For any questions or feedback don't hesitate to contact me at: noemiefedon@gmail.com or through github at https://github.com/noemiefedon/LAYLA