Prediction of pore-scale flow in heterogeneous porous media from periodic structures using deep learning
Data-driven deep learning models are emerging as a promising method for characterizing pore-scale flow through complex porous media while requiring minimal computational power. However, previous models often require extensive computation to simulate flow through synthetic porous media for use as tra...
| Main Authors: | , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
AIP Publishing LLC
2023-04-01
|
| Series: | AIP Advances |
| Online Access: | http://dx.doi.org/10.1063/5.0147472 |