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A conservative hybrid deep learning method for Maxwell-Ampère-Nernst-Planck equations - MaRDI portal

A conservative hybrid deep learning method for Maxwell-Ampère-Nernst-Planck equations (Q6126572)

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scientific article; zbMATH DE number 7829514

Language	Label	Description	Also known as
English	A conservative hybrid deep learning method for Maxwell-Ampère-Nernst-Planck equations	scientific article; zbMATH DE number 7829514

Statements

scholarly article

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A conservative hybrid deep learning method for Maxwell-Ampère-Nernst-Planck equations (English)

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Journal of Computational Physics

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publication date

9 April 2024

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full work available at URL

https://arxiv.org/abs/2312.05891

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zbMATH Keywords

Maxwell-Ampère-Nernst-Planck

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equations

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conservative numerical scheme

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deep learning

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physics-informed neural network

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MaRDI profile type

MaRDI publication profile

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Neural‐network‐based approximations for solving partial differential equations

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DGM: a deep learning algorithm for solving partial differential equations

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The Deep Ritz Method: a deep learning-based numerical algorithm for solving variational problems

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Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations

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Conservative physics-informed neural networks on discrete domains for conservation laws: applications to forward and inverse problems

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Weak adversarial networks for high-dimensional partial differential equations

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\textit{hp}-VPINNs: variational physics-informed neural networks with domain decomposition

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Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks

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A neural network multigrid solver for the Navier-Stokes equations

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CAN-PINN: a fast physics-informed neural network based on coupled-automatic-numerical differentiation method

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Hybrid FEM-NN models: combining artificial neural networks with the finite element method

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Discretizationnet: a machine-learning based solver for Navier-Stokes equations using finite volume discretization

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A free energy satisfying finite difference method for Poisson-Nernst-Planck equations

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A conservative discretization of the Poisson-Nernst-Planck equations on adaptive Cartesian grids

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Sympnets: intrinsic structure-preserving symplectic networks for identifying Hamiltonian systems

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The model reduction of the Vlasov–Poisson–Fokker–Planck system to the Poisson–Nernst–Planck system <i>via</i> the Deep Neural Network Approach

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Structure-preserving numerical method for Maxwell-Ampère Nernst-Planck model

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A Maxwell–Ampère Nernst–Planck Framework for Modeling Charge Dynamics

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Solving parametric PDE problems with artificial neural networks

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Finite element approximation of the Navier-Stokes equations

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M-matrix characterizations. I: nonsingular M-matrices

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New Poisson–Boltzmann type equations: one-dimensional solutions

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Identifiers

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Mathematics Subject Classification ID

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zbMATH DE Number

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10.1016/J.JCP.2024.112791

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Sitelinks

Mathematics(1 entry)

mardi Publication:6126572

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