Improved physics-informed neural networks for the reinterpreted discrete fracture model

DOI10.1016/J.JCP.2024.113491MaRDI QIDQ6648401

Hui Guo, Yang Yang, Xia Yan, Zhanglei Shi, Chao Wang

Publication date: 4 December 2024

Published in: Journal of Computational Physics (Search for Journal in Brave)

zbMATH Keywords

fractured porous mediabound-preservinghybrid-dimensionimproved-physics-informed neural networksreinterpreted discrete fracture model

Mathematics Subject Classification ID

Basic methods in fluid mechanics (76Mxx) Numerical methods for partial differential equations, initial value and time-dependent initial-boundary value problems (65Mxx) Flows in porous media; filtration; seepage (76Sxx)

Cites Work

• Accurate multiscale finite element method for numerical simulation of two-phase flow in fractured media using discrete-fracture model
• On the use of enriched finite element method to model subsurface features in porous media flow problems
• The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems
• The hybrid-dimensional Darcy's law: a non-conforming reinterpreted discrete fracture model (RDFM) for single-phase flow in fractured media
• The hybrid dimensional representation of permeability tensor: a reinterpretation of the discrete fracture model and its extension on nonconforming meshes
• Algebraic dynamic multilevel method for embedded discrete fracture model (F-ADM)
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Bound-preserving discontinuous Galerkin methods with second-order implicit pressure explicit concentration time marching for compressible miscible displacements in porous media
• A physics-informed convolutional neural network for the simulation and prediction of two-phase Darcy flows in heterogeneous porous media
• Basic concepts in the theory of seepage of homogeneous liquids in fissured rocks [strata]
• Modelling fluid flow in fractured-porous rock masses by finite-element techniques
• Predicting entropy generation of a hybrid nanofluid in microchannel heat sink with porous fins integrated with high concentration photovoltaic module using artificial neural networks

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