June 03, 2022 article Open access A data-driven approach to full-field nonlinear stress distribution and failure pattern prediction in composites using deep learning Computer Methods in Applied Mechanics and Engineering DOI: 10.1016/j.cma.2022.115126 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 2 stored of 137 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access A spatiotemporal deep learning framework for prediction of crack dynamics in heterogeneous solids: Efficient mapping of concrete microstructures to its fracture properties 2024 Engineering Fracture Mechanics article Engineering Numerical methods in engineering 18 citations Introducing a microstructure-embedded autoencoder approach for reconstructing high-resolution solution field data from a reduced parametric space 2024 Computational Mechanics article Physics and Astronomy Model Reduction and Neural Networks Open access 5 citations 2 results References 2 Search Sort Most cited Newest Oldest Patent citations Title Any typearticle review book-chapter conference-paper preprint dissertation book dataset other Any fieldAgricultural and Biological Sciences Arts and Humanities Biochemistry, Genetics and Molecular Biology Business, Management and Accounting Chemical Engineering Chemistry Computer Science Decision Sciences Dentistry Earth and Planetary Sciences Economics, Econometrics and Finance Energy Engineering Environmental Science Health Professions Immunology and Microbiology Materials Science Mathematics Medicine Neuroscience Nursing Pharmacology, Toxicology and Pharmaceutics Physics and Astronomy Psychology Social Sciences Veterinary Open access 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 An intelligent nonlinear meta element for elastoplastic continua: deep learning using a new Time-distributed Residual U-Net architecture 2020 Computer Methods in Applied Mechanics and Engineering article Physics and Astronomy Model Reduction and Neural Networks 71 citations 2 results