A Direct-Forcing Immersed Boundary Method for Incompressible Flows Based on Physics-Informed Neural Network
The application of physics-informed neural networks (PINNs) to computational fluid dynamics simulations has recently attracted tremendous attention. In the simulations of PINNs, the collocation points are required to conform to the fluid–solid interface on which no-slip boundary condition is enforce...
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| Главные авторы: | , , |
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| Формат: | Artigo |
| Язык: | Inglês |
| Опубликовано: |
MDPI AG
2022-01-01
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| Серии: | Fluids |
| Предметы: | |
| Online-ссылка: | https://www.mdpi.com/2311-5521/7/2/56 |
| Метки: |
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