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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 2018Show all

6 papers · 1 filter

physics.flu-dyn2018★ 35 cited

Wing fold angle determines the terminal descent velocity of double winged autorotating seeds, fruits and other diaspores

Richard A. Fauli, Jean Rabault, Andreas Carlson

Wind dispersal of seeds is one essential mechanisms for plants to proliferate and to invade new territories. In this paper we present a methodology that combines 3D-printing, a min…

physics.flu-dyn2018★ 70 cited

Experiments on wave propagation in grease ice: combined wave gauges and PIV measurements

Jean Rabault, Graig Sutherland, Atle Jensen +2

Water wave attenuation by grease ice is a key mechanism for the polar regions, as waves in ice influence many phenomena such as ice drift, ice breaking, and ice formation. However,…

physics.ao-ph2018★ 3 cited

An investigation into the interaction between waves and ice

Jean Rabault

This thesis is submitted in the partial fulfillment of the requirements for the degree of Doctor of Philosophy at the University of Oslo. It represents work that has been carried o…

physics.flu-dyn2018★ 2 cited

Deep Reinforcement Learning achieves flow control of the 2D Karman Vortex Street

Jean Rabault, Ulysse Reglade, Nicolas Cerardi +2

The Karman Vortex Street has been investigated for over a century and offers a reference case for investigation of flow stability and control of high dimensionality, non-linear sys…

physics.flu-dyn2018★ 572 cited

Artificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control

Jean Rabault, Miroslav Kuchta, Atle Jensen +2

We present the first application of an Artificial Neural Network trained through a Deep Reinforcement Learning agent to perform active flow control. It is shown that, in a 2D simul…

physics.ao-ph2018

A two layer model for wave dissipation in sea ice

Graig Sutherland, Jean Rabault, Kai H. Christensen +1

Sea ice is highly complex due to the inhomogeneity of the physical properties (e.g. temperature and salinity) as well as the permeability and mixture of water and a matrix of sea i…