Physics informed neural networks for fluid flow analysis with repetitive parameter initialization
Abstract Physics-informed neural networks (PINNs) have been widely used to capture the behavior of physical systems governed by partial differential equations (PDEs), enabling the simulation of fluid dynamics across various scenarios. However, when applied to stiff fluid problems, the existing PINNs...
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| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Nature Portfolio
2025-05-01
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| Series: | Scientific Reports |
| Subjects: | |
| Online Access: | https://doi.org/10.1038/s41598-025-99354-5 |
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