3 papers
physics.flu-dyn2026
Deep learning accelerated solutions of incompressible Navier-Stokes equations on non-uniform Cartesian grids
Heming Bai, Dong Zhang, Shengze Cai +1
In incompressible flow simulations, non-uniform grids efficiently capture localized flow features; however, their spatially varying resolutions severely exacerbate computational co…
physics.flu-dyn2025
Hybrid deep learning and iterative methods for accelerated solutions of viscous incompressible flow
Heming Bai, Xin Bian
The pressure Poisson equation, central to the fractional step method in incompressible flow simulations, incurs high computational costs due to the iterative solution of large-scal…
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…