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Adaptive physics-informed neural operator for coarse-grained non-equilibrium flows
This work proposes a new machine learning (ML)-based paradigm aiming to enhance the computational efficiency of non-equilibrium reacting flow simulations while ensuring compliance with the underlying physics. The framework combines dimensionality reduction and neural operators through a hierarchical...
| Autores principales: | , , |
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| Formato: | Online Artículo Texto |
| Lenguaje: | English |
| Publicado: |
Nature Publishing Group UK
2023
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| Materias: | |
| Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10509218/ https://www.ncbi.nlm.nih.gov/pubmed/37726349 http://dx.doi.org/10.1038/s41598-023-41039-y |