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physics.flu-dyn2025
Physics-informed neural networks for hidden boundary detection and flow field reconstruction
Yongzheng Zhu, Weizheng Chen, Jian Deng +1
Simultaneously detecting hidden solid boundaries and reconstructing flow fields from sparse observations poses a significant inverse challenge in fluid mechanics. This study presen…
physics.flu-dyn2024
Data-driven modeling of unsteady flow based on deep operator network
Heming Bai, Zhicheng Wang, Xuesen Chu +2
Time-dependent flow fields are typically generated by a computational fluid dynamics (CFD) method, which is an extremely time-consuming process. However, the latent relationship be…