Physics-informed geometry-aware neural operator

DOI10.1016/j.cma.2024.117540MaRDI QIDQ6669047

Hadi Meidani, Weiheng Zhong

Publication date: 22 January 2025

Published in: Computer Methods in Applied Mechanics and Engineering (Search for Journal in Brave)

zbMATH Keywords

physics-informed deep learningneural operatorgeometry generalization

Mathematics Subject Classification ID

Numerical analysis (65-XX) Computer science (68-XX)

Cites Work

• A comprehensive and fair comparison of two neural operators (with practical extensions) based on FAIR data
• Improved architectures and training algorithms for deep operator networks
• Physics-informed PointNet: a deep learning solver for steady-state incompressible flows and thermal fields on multiple sets of irregular geometries
• Physics-informed neural networks: a deep learning framework for solving forward and inverse problems involving nonlinear partial differential equations
• Physics informed WNO
• Geometrically-driven generation of mechanical designs through deep convolutional GANs
• Multi-scale time-stepping of partial differential equations with transformers
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