QLingNet: An efficient and flexible modeling framework for subsonic airfoils
Kuijun Zuo(Hong Kong Polytechnic University), Weiwei Zhang, Xianxu Yuan(China Aerodynamics Research and Development Center), Linyang Zhu(China Aerodynamics Research and Development Center), Zhengyin Ye(Northwestern Polytechnical University)
Cited by 0
Related Papers
Fast aerodynamics prediction of laminar airfoils based on deep attention network
|Physics of Fluids|2023|98
Improved Point Selection Method for Hybrid-Unstructured Mesh Deformation Using Radial Basis Functions
|AIAA Journal|2014|88
Numerical investigation of structural geometric nonlinearity effect in high-aspect-ratio wing using CFD/CSD coupled approach
|Journal of Fluids and Structures|2014|56
Fast sparse flow field prediction around airfoils via multi-head perceptron based deep learning architecture
|Aerospace Science and Technology|2022|53
Fast simulation of airfoil flow field via deep neural network
|Aerospace Science and Technology|2024|38