-
Article
Open AccessCorrection to: Deep reinforcement learning for turbulent drag reduction in channel flows
-
Article
Open AccessA dataset of direct observations of sea ice drift and waves in ice
Variability in sea ice conditions, combined with strong couplings to the atmosphere and the ocean, lead to a broad range of complex sea ice dynamics. More in-situ measurements are needed to better identify the ph...
-
Article
Open AccessDeep reinforcement learning for turbulent drag reduction in channel flows
We introduce a reinforcement learning (RL) environment to design and benchmark control strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The environment provides a framework for...
-
Article
Active flow control with rotating cylinders by an artificial neural network trained by deep reinforcement learning
In this paper, an artificial neural network (ANN) trained through a deep reinforcement learning (DRL) agent is used to perform flow control. The target is to look for the wake stabilization mechanism in an act...
-
Article
Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization
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 mechanics. While it will take time ...
