5 citations · 5 across the 1 of their papers we have counts for
3 papers
physics.flu-dyn2020
Bluff body uses deep-reinforcement-learning trained active flow control to achieve hydrodynamic stealth
Feng Ren, Hui Tang
We propose a novel active-flow-control (AFC) strategy for bluff bodies to hide their hydrodynamic traces from predators. A group of windward-suction-leeward-blowing (WSLB) actuator…
physics.flu-dyn2020
Applying deep reinforcement learning to active flow control in turbulent conditions
Feng Ren, Jean Rabault, Hui Tang
Machine learning has recently become a promising technique in fluid mechanics, especially for active flow control (AFC) applications. A recent work [J. Fluid Mech. (2019), vol. 865…
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…