This repository contains the code for AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems. The code provides the following functions:
- An end to end microstructure optimization framework to generate multiple polycrystalline microstructures.
The basic requirement for using the files is a Python 3.8.19 environment.
Here is a brief description of the file and folder content:
- Simulator: folder where example data generated using proposed end2end framework.
- end2end_v2.py: code for the proposed end2end framework which can generated microstructures (represented by ODF vectors).
To generate the dataset, run end2end_v2.py file.
The code was developed by Yuwei Mao from the CUCIS group at the Electrical and Computer Engineering Department at Northwestern University.
- Mao, Yuwei, Mahmudul Hasan, Arindam Paul, Vishu Gupta, Kamal Choudhary, Francesca Tavazza, Wei-keng Liao, Alok Choudhary, Pinar Acar, and Ankit Agrawal. "An AI-driven microstructure optimization framework for elastic properties of titanium beyond cubic crystal systems." npj Computational Materials 9, no. 1 (2023): 111. PDF
The research code shared in this repository is shared without any support or guarantee on its quality. However, please do raise an issue if you find anything wrong and I will try my best to address it.
email: [email protected]
Copyright (C) 2023, Northwestern University.
See COPYRIGHT notice in top-level directory.
This work was supported primarily by National Science Foundation (NSF) CMMI awards 2053929/2053840. Partial support from NIST award 70NANB19H005 and DOE awards DE-SC0019358, DE-SC0021399 is also acknowledged.