1 citations · 1 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2024
QLingNet: An efficient and flexible modeling framework for subsonic airfoils
Kuijun Zuo, Zhengyin Ye, Linyang Zhu +2
Artificial intelligence techniques are considered an effective means to accelerate flow field simulations. However, current deep learning methods struggle to achieve generalization…
physics.flu-dyn2023★ 1 cited
Fast simulation of airfoil flow field via deep neural network
Kuijun Zuo, Zhengyin Ye, Shuhui Bu +2
Computational Fluid Dynamics (CFD) has become an indispensable tool in the optimization design, and evaluation of aircraft aerodynamics. However, solving the Navier-Stokes (NS) equ…
physics.flu-dyn2022
Fast sparse flow field prediction around airfoils via multi-head perceptron based deep learning architecture
Kuijun Zuo, Shuhui Bu, Weiwei Zhang +3
In order to obtain the information about flow field, traditional computational fluid dynamics methods need to solve the Navier-Stokes equations on the mesh with boundary conditions…