Under Construction
The data and code for the paper J. E. Lee, M. Zhu, Z. Xi, K. Wang, Y. O. Yuan, & L. Lu. Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration. Engineering Applications of Computational Fluid Mechanics, 18 (1), 2024.
The full dataset for Nested Fourier-DeepONet is available on OneDrive. Download and put all files into datasets
folder.
Steps to generate the full dataset for Nested Fourier-DeepONet:
- step 1: download raw data
- step 2: run file_config.sh to convert
.npy
file into.pt
files - step 3: create a new folder
datasets_nested_fno
under the main folder and put the files generated in step 2 into the folderdatasets_nested_fno
- step 4: run data_generation.py to covert
.pt
files into our.npz
files
to be uploaded
If you use this data or code for academic research, you are encouraged to cite the following paper:
@article{lee2024efficient},
author = {Jonathan E. Lee, Min Zhu, Ziqiao Xi, Kun Wang, Yanhua O. Yuan and Lu Lu},
title = {Efficient and generalizable nested Fourier-DeepONet for three-dimensional geological carbon sequestration},
journal = {Engineering Applications of Computational Fluid Mechanics},
volume = {18},
number = {1},
pages = {2435457},
year = {2024},
doi = {https://doi.org/10.1080/19942060.2024.2435457}
}
To get help on how to use the data or code, simply open an issue in the GitHub "Issues" section.