1 citations · 2 across the 3 of their papers we have counts for
3 papers
physics.flu-dyn2021
High Reynolds number airfoil turbulence modeling method based on machine learning technique
Xuxiang Sun, Wenbo Cao, Yilang Liu +2
In this paper, a turbulence model based on deep neural network is developed for turbulent flow around airfoil at high Reynolds numbers. According to the data got from the Spalart-A…
physics.flu-dyn2021★ 1 cited
UCNN: A Convolutional Strategy on Unstructured Mesh
Mengfei Xu, Shufang Song, Xuxiang Sun +1
In machine learning for fluid mechanics, fully-connected neural network (FNN) only uses the local features for modelling, while the convolutional neural network (CNN) cannot be app…
physics.flu-dyn2020★ 1 cited
Machine learning for adjoint vector in aerodynamic shape optimization
Mengfei Xu, Shufang Song, Xuxiang Sun +2
Adjoint method is widely used in aerodynamic design because only once solution of flow field is required for adjoint method to obtain the gradients of all design variables. However…