Cover Image

Physics Informed Neural Networks for heat conduction with phase change

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Madir, Bahae-Eddine, Luddens, Francky, Lothodé, Corentin, Danaila, Ionut
Format:	Preprint
Published:	2024
Subjects:	Numerical Analysis
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

An implicit regularized enthalpy Lattice Boltzmann Method for the Stefan problem
by: Luddens, Francky, et al.
Published: (2025)

Influence of gauges in the numerical simulation of the time-dependent Ginzburg-Landau model
by: Tain, Cyril, et al.
Published: (2024)

Numerical simulation of transient heat conduction with moving heat source using Physics Informed Neural Networks
by: Kalyan, Anirudh, et al.
Published: (2025)

Physics-Informed Deep Learning for Industrial Processes: Time-Discrete VPINNs for heat conduction
by: Olivares, Manuela Bastidas, et al.
Published: (2026)

On the Stability and Convergence of Physics Informed Neural Networks
by: Gazoulis, Dimitrios, et al.
Published: (2023)

Coupling Physics Informed Neural Networks with External Solvers
by: Halder, Rahul, et al.
Published: (2025)

Preconditioning for Physics-Informed Neural Networks
by: Liu, Songming, et al.
Published: (2024)

Optimizing Variational Physics-Informed Neural Networks Using Least Squares
by: Uriarte, Carlos, et al.
Published: (2024)

A Physics-Informed Neural Network approach for compartmental epidemiological models
by: Millevoi, Caterina, et al.
Published: (2023)

Refined generalization analysis of the Deep Ritz Method and Physics-Informed Neural Networks
by: Xu, Xianliang, et al.
Published: (2024)

The Ill-Posed Foundations of Physics-Informed Neural Networks and Their Finite-Difference Variants
by: Langer, Andreas
Published: (2026)

Deep Ritz Physics-Informed Neural Network Method for Solving the Variational Inequality
by: Zhou, Qijia, et al.
Published: (2026)

Extended Interface Physics-Informed Neural Networks Method for Moving Interface Problems
by: Bi, Ran, et al.
Published: (2025)

Dual-Balancing for Physics-Informed Neural Networks
by: Zhou, Chenhong, et al.
Published: (2025)

Runge-Kutta Physics Informed Neural Networks: Formulation and Analysis
by: Akrivis, Georgios, et al.
Published: (2024)

PINNsur: Physics-Informed Neural Networks for PDEs on Curved Surfaces
by: Jain, Pranav, et al.
Published: (2026)

DMIS: Dynamic Mesh-based Importance Sampling for Training Physics-Informed Neural Networks
by: Yang, Zijiang, et al.
Published: (2022)

Mapping-based Hard-constrained Physics-Informed Neural Networks for unbounded wave problems
by: Zhang, Tao, et al.
Published: (2026)

Physics Informed Neural Networks for Learning the Horizon Size in Bond-Based Peridynamic Models
by: Difonzo, Fabio V., et al.
Published: (2025)

Solving Poisson Problems in Polygonal Domains with Singularity Enriched Physics Informed Neural Networks
by: Hu, Tianhao, et al.
Published: (2023)

E-PINNs: Epistemic Physics-Informed Neural Networks
by: Jacob, Bruno, et al.
Published: (2025)

Discontinuity Computing using Physics-Informed Neural Network
by: Liu, Li, et al.
Published: (2022)

A Unified Benchmark of Physics-Informed Neural Networks and Kolmogorov-Arnold Networks for Ordinary and Partial Differential Equations
by: Dzimah, Salvador K., et al.
Published: (2026)

PhysicsSolver: Transformer-Enhanced Physics-Informed Neural Networks for Forward and Forecasting Problems in Partial Differential Equations
by: Zhu, Zhenyi, et al.
Published: (2025)

Coupling of the Finite Element Method with Physics Informed Neural Networks for the Multi-Fluid Flow Problem
by: Nohra, Michel, et al.
Published: (2024)

Solution of Advection Equation with Discontinuous Initial and Boundary Conditions via Physics-Informed Neural Networks
by: Khosravi, Omid, et al.
Published: (2026)

Estimation of Hemodynamic Parameters via Physics Informed Neural Networks including Hematocrit Dependent Rheology
by: Sierpe, Moises, et al.
Published: (2025)

Numerical simulation of the dual-phase-lag heat conduction equation on a one-dimensional unbounded domain using artificial boundary condition
by: Bu, Weiping, et al.
Published: (2025)

Transformed Physics-Informed Neural Networks for The Convection-Diffusion Equation
by: Guan, Jiajing, et al.
Published: (2024)

Bayesian Physics Informed Neural Networks for Linear Inverse problems
by: Mohammad-Djafari, Ali
Published: (2025)

Number Theoretic Accelerated Learning of Physics-Informed Neural Networks
by: Matsubara, Takashi, et al.
Published: (2023)

Leveraging Lie Group Symmetries to Enhance Physics-Informed Neural Networks for the Fundamental Solution of Linear PDEs
by: Jiao, Xiaopei, et al.
Published: (2024)

Uniform estimates for transmission problems with high contrast in heat conduction and electromagnetism
by: Caloz, Gabriel, et al.
Published: (2009)

A Unified Weighted-Loss Physics-Informed Neural Network for Boundary Layer Problems in Singularly Perturbed PDEs
by: Hu, Wei-Fan, et al.
Published: (2026)

Singular Layer Physics-Informed Neural Network Method for Convection-Dominated Boundary Layer Problems in Two Dimensions
by: Gie, Gung-Min, et al.
Published: (2023)

Generalization Bounds for Physics-Informed Neural Networks for the Incompressible Navier-Stokes Equations
by: Andre-Sloan, Sebastien, et al.
Published: (2026)

Physics-Informed Neural Networks with Trust-Region Sequential Quadratic Programming
by: Cheng, Xiaoran, et al.
Published: (2024)

Inverse Physics-Informed Neural Networks for transport models in porous materials
by: Berardi, Marco, et al.
Published: (2024)

Heterogeneous optimized Schwarz Methods for heat conduction in composites with thermal contact resistance
by: Zhang, Huan, et al.
Published: (2025)

Variational and thermodynamically consistent finite element discretization for heat conducting viscous fluids
by: Gawlik, Evan S., et al.
Published: (2022)