May 01, 2025 article Open access A physics-informed machine learning approach for predicting dynamic behavior of reacting flows with application to hydrogen jet flames Combustion and Flame DOI: 10.1016/j.combustflame.2025.114190 Full text (OA) OpenAlex Authors 0 Author list not loaded yet. Cited by 0 stored of 9 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 Using physics-informed enhanced super-resolution generative adversarial networks for subfilter modeling in turbulent reactive flows 2021 Proceedings of the Combustion Institute article Physics and Astronomy Model Reduction and Neural Networks Open access 150 citations BLASTNetv3: Multiphysics Simulation Dataset 2023 arXiv (Cornell University) preprint Physics and Astronomy Model Reduction and Neural Networks Open access 7 citations 2 results