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

collaborators
Showing 2022Show all

6 papers · 1 filter

physics.flu-dyn2022

A field investigation of the friction between cross-country skis and snow

Rasmus Nes Tjørstad, Jean Rabault, Olav Gundersen +1

Cross country skiing is an interplay between the active motion of the body of the skier and the physical interaction between the surface of the skis and the snow. Friction and glid…

physics.flu-dyn2022★ 2 cited

Deep reinforcement learning for flow control exploits different physics for increasing Reynolds-number regimes

Pau Varela, Pol Suárez, Francisco Alcántara-Ávila +6

Deep artificial neural networks (ANNs) used together with deep reinforcement learning (DRL) are receiving growing attention due to their capabilities to control complex problems. T…

physics.geo-ph2022★ 3 cited

A dataset of direct observations of sea ice drift and waves in ice

Jean Rabault, Malte Müller, Joey Voermans +25

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…

physics.flu-dyn2022★ 72 cited

DRLinFluids -- An open-source python platform of coupling Deep Reinforcement Learning and OpenFOAM

Qiulei Wang, Lei Yan, Gang Hu +5

We propose an open-source python platform for applications of Deep Reinforcement Learning (DRL) in fluid mechanics. DRL has been widely used in optimizing decision-making in nonlin…

physics.flu-dyn2022★ 60 cited

Comparative analysis of machine learning methods for active flow control

Fabio Pino, Lorenzo Schena, Jean Rabault +1

Machine learning frameworks such as Genetic Programming (GP) and Reinforcement Learning (RL) are gaining popularity in flow control. This work presents a comparative analysis of th…

physics.ins-det2022

OpenMetBuoy-V2021: an easy-to-build, affordable, customizable, open source instrument for oceanographic measurements of drift and waves in sea ice and the open ocean

Jean Rabault, Takehiko Nose, Gaute Hope +17

There is a wide consensus within the polar science, meteorology, and oceanography communities that more in-situ observations of the ocean, atmosphere, and sea ice, are required to…