A mixed pressure-velocity formulation to model flow in heterogeneous porous media with physics-informed neural networks
Author:
Funder
King Abdullah University of Science and Technology
Publisher
Elsevier BV
Subject
Water Science and Technology
Reference46 articles.
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3. Physics-Informed Neural Networks with monotonicity constraints for Richardson-Richards equation: estimation of constitutive relationships and soil water flux density from volumetric water content measurements;Bandai;Water Res.,2021
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1. A transfer learning physics-informed deep learning framework for modeling multiple solute dynamics in unsaturated soils;Computer Methods in Applied Mechanics and Engineering;2024-11
2. Modeling fluid flow in heterogeneous porous media with physics-informed neural networks: Weighting strategies for the mixed pressure head-velocity formulation;Advances in Water Resources;2024-11
3. Interface PINNs (I-PINNs): A physics-informed neural networks framework for interface problems;Computer Methods in Applied Mechanics and Engineering;2024-09
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