57 citations · 62 across the 4 of their papers we have counts for
4 papers
Deep-reinforcement-learning-based separation control in a two-dimensional airfoil
Xavier Garcia, Arnau Miró, Pol Suárez +5
The aim of this study is to discover new active-flow-control (AFC) techniques for separation mitigation in a two-dimensional NACA 0012 airfoil at a Reynolds number of 3000. To find…
Active flow control for drag reduction through multi-agent reinforcement learning on a turbulent cylinder at
P. Suárez, F. Álcantara-Ávila, A. Miró +4
This study presents novel drag reduction active-flow-control (AFC) strategies} for a three-dimensional cylinder immersed in a flow at a Reynolds number based on freestream velocity…
Flow control of three-dimensional cylinders transitioning to turbulence via multi-agent reinforcement learning
P. Suárez, F. Alcántara-Ávila, J. Rabault +4
Designing active-flow-control (AFC) strategies for three-dimensional (3D) bluff bodies is a challenging task with critical industrial implications. In this study we explore the pot…
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…