57 citations · 108 across the 17 of their papers we have counts for
4 papers · 1 filter
Drag-reduction strategies in wall-bounded turbulent flows using deep reinforcement learning
L. Guastoni, J. Rabault, H. Azizpour +1
In this work we compare different drag-reduction strategies that compute their actuation based on the fluctuations at a given wall-normal location in turbulent open channel flow. I…
Active flow control for three-dimensional cylinders through deep reinforcement learning
Pol Suárez, Francisco Alcántara-Ávila, Arnau Miró +4
This paper presents for the first time successful results of active flow control with multiple independently controlled zero-net-mass-flux synthetic jets. The jets are placed on a…
Effective control of two-dimensional Rayleigh--Bénard convection: invariant multi-agent reinforcement learning is all you need
Colin Vignon, Jean Rabault, Joel Vasanth +3
Rayleigh-Bénard convection (RBC) is a recurrent phenomenon in several industrial and geoscience flows and a well-studied system from a fundamental fluid-mechanics viewpoint. Howeve…
Deep reinforcement learning for turbulent drag reduction in channel flows
L. Guastoni, J. Rabault, P. Schlatter +2
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 environ…