189 citations · 190 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2023★ 1 cited
Deep learning-based reduced order model for three-dimensional unsteady flow using mesh transformation and stitching
Xin Li, Zhiwen Deng, Rui Feng +4
Artificial intelligence-based three-dimensional(3D) fluid modeling has gained significant attention in recent years. However, the accuracy of such models is often limited by the pr…
physics.comp-ph2020
Hybrid deep neural network based prediction method for unsteady flows with moving boundaries
Renkun Han, Zhong Zhang, Yixing Wang +3
A novel hybrid deep neural network architecture is designed to capture the spatial-temporal features of unsteady flows around moving boundaries directly from high-dimensional unste…
physics.flu-dyn2019★ 189 cited
A new prediction method of unsteady wake flow by the hybrid deep neural network
Renkun Han, Yixing Wang, Yang Zhang +1
The fast and accurate prediction of unsteady flow becomes a serious challenge in fluid dynamics, due to the high-dimensional and nonlinear characteristics. A novel hybrid deep neur…