Teaching solid mechanics to artificial intelligence—a fast solver for heterogeneous materials

• A finite element-based physics-informed operator learning framework for spatiotemporal partial differential equations on arbitrary domains

  2024 Engineering With Computers article Physics and Astronomy Model Reduction and Neural Networks Open access

  39

  citations
• Generative learning‐based model for the prediction of 2D stress distribution

  2023 PAMM article Physics and Astronomy Model Reduction and Neural Networks Open access

  5

  citations
• An artificial neural network for surrogate modeling of stress fields in viscoplastic polycrystalline materials

  2023 npj Computational Materials article Materials Science Machine Learning in Materials Science Open access

  97

  citations
• Graph Neural Network enhanced Finite Element modelling

  2023 PAMM article Physics and Astronomy Model Reduction and Neural Networks Open access

  36

  citations
• A Machine Learning Enabled Image‐data‐driven End‐to‐end Mechanical Field Predictor For Dual‐Phase Steel

  2023 PAMM article Materials Science Machine Learning in Materials Science Open access

  10

  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
• Machine-learning-based surrogate modeling of microstructure evolution using phase-field

  2022 Computational Materials Science article Materials Science Machine Learning in Materials Science

  62

  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
• Modeling and simulation of microstructure in metallic systems based on multi-physics approaches

  2022 npj Computational Materials article Materials Science Microstructure and mechanical properties Open access

  37

  citations

9 results

• Constitutive artificial neural networks: A fast and general approach to predictive data-driven constitutive modeling by deep learning

  2020 Journal of Computational Physics article Materials Science Machine Learning in Materials Science Open access cited by 3 patents

  341

  citations
• Application of artificial neural networks for the prediction of interface mechanics: a study on grain boundary constitutive behavior

  2020 Advanced Modeling and Simulation in Engineering Sciences article Materials Science Microstructure and mechanical properties Open access

  74

  citations

2 results