Physics-informed deep learning for digital materials

• Finite Operator Learning: Bridging neural operators and numerical methods for efficient parametric solution and optimization of PDEs

  2025 Finite Elements in Analysis and Design article Physics and Astronomy Model Reduction and Neural Networks

  10

  citations
• Digitalizing metallic materials from image segmentation to multiscale solutions via physics informed operator learning

  2025 npj Computational Materials article Materials Science Machine Learning in Materials Science Open access

  7

  citations
• A Finite Operator Learning Technique for Mapping the Elastic Properties of Microstructures to Their Mechanical Deformations

  2024 International Journal for Numerical Methods in Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access

  27

  citations
• On the order of derivation in the training of physics-informed neural networks: case studies for non-uniform beam structures

  2023 Acta Mechanica article Physics and Astronomy Model Reduction and Neural Networks

  25

  citations
• A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: Comparison with finite element method

  2022 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks Open access

  12

  citations
• A mixed formulation for physics-informed neural networks as a potential solver for engineering problems in heterogeneous domains: comparison with finite element method

  2022 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access

  216

  citations

6 results

• SO(3)-invariance of informed-graph-based deep neural network for anisotropic elastoplastic materials

  2020 Computer Methods in Applied Mechanics and Engineering article Engineering Elasticity and Material Modeling Open access

  129

  citations

1 result