GrainNN

A transformer-embedded seq2seq LSTM for grain microstructure evolution

Cite

If you are using the codes in this repository, please cite the following paper

@article{qin2023grainnn,
  title={GrainNN: A neighbor-aware long short-term memory network for predicting microstructure evolution during polycrystalline grain formation},
  author={Qin, Yigong and DeWitt, Stephen and Radhakrishnan, Balasubramaniam and Biros, George},
  journal={Computational Materials Science},
  volume={218},
  pages={111927},
  year={2023},
  publisher={Elsevier}
}

Build

pip install -r requirements.txt

Usage

training

cd GrainNN_2D
python3 grainNN.py train 

testing

cd GrainNN_2D
python3 grainNN.py test 

Example

Rectangular simulation

128grain.mp4

Metpool simulation

meltpool.mp4

Reference

[1] Xingjian, S. et al. Convolutional lstm network: A machine learning approach for precipitation nowcasting. In Advances in neural information processing systems, 802–810 (2015).
[2] Vaswani, A. et al. Attention is all you need. In Advances in neural information processing systems, 5998–6008 (2017).

Author

This software was primarily written by Yigong Qin who is advised by Prof. George Biros.