80 citations · 85 across the 2 of their papers we have counts for
2 papers
physics.flu-dyn2020★ 80 cited
Explore missing flow dynamics by physics-informed deep learning: the parameterised governing systems
Hui Xu, Wei Zhang, Yong Wang
Gaining and understanding the flow dynamics have much importance in a wide range of disciplines, e.g. astrophysics, geophysics, biology, mechanical engineering and biomedical engin…
physics.flu-dyn2020★ 5 cited
Deep Reinforcement Learning in Fluid Mechanics: a promising method for both Active Flow Control and Shape Optimization
Jean Rabault, Feng Ren, Wei Zhang +2
In recent years, Artificial Neural Networks (ANNs) and Deep Learning have become increasingly popular across a wide range of scientific and technical fields, including Fluid Mechan…