activity
20152024
most citedArtificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control

572 citations · 2.1k across the 54 of their papers we have counts for

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Showing 2023 · physics.flu-dynShow all

7 papers · 2 filters

physics.flu-dyn2023

Observations of transient wave-induced mean drift profiles caused by virtual wave stresses in a two-layer system

Jan Erik H. Weber, Yiyi Whitchelo, Jon A. Pirolt +3

An experimental study of long interfacial gravity waves was conducted in a closed wave tank containing two layers of viscous immiscible fluids. The study focuses on the development…

physics.flu-dyn2023

Optimizing Flow Control with Deep Reinforcement Learning: Plasma Actuator Placement around a Square Cylinder

Mustafa Z Yousif, Kolesova Paraskovia, Yifang Yang +5

The present study proposes an active flow control (AFC) approach based on deep reinforcement learning (DRL) to optimize the performance of multiple plasma actuators on a square cyl…

physics.flu-dyn2023★ 12 cited

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…

physics.flu-dyn2023★ 2 cited

An affordable and customizable wave buoy for the study of wave-ice interactions: design concept and results from field deployments

Tsubasa Kodaira, Tomotaka Katsuno, Takehiko Nose +5

In the polar regions, the interaction between waves and ice has a crucial impact on the seasonal change in the sea ice extent. However, our comprehension of this phenomenon is rest…

physics.flu-dyn2023★ 157 cited

Recent advances in applying deep reinforcement learning for flow control: perspectives and future directions

Colin Vignon, Jean Rabault, Ricardo Vinuesa

Deep reinforcement learning (DRL) has been applied to a variety of problems during the past decade, and has provided effective control strategies in high-dimensional and non-linear…

physics.flu-dyn2023★ 57 cited

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…