J Rabault

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Coauteurs

Atle JensenDepartment of Mathematics, University of OsloAdresse e-mail validée de math.uio.no
Graig SutherlandEnvironment and Climate Change CanadaAdresse e-mail validée de canada.ca
Aleksey MarchenkoThe University Centre in SvalbardAdresse e-mail validée de unis.no
Alexander KuhnleBlue PrismAdresse e-mail validée de cantab.ac.uk
Kai Håkon ChristensenHead of Division for Ocean and Ice, Norwegian Meteorological InstituteAdresse e-mail validée de met.no
Ricardo VinuesaAssociate Professor, KTH Royal Institute of TechnologyAdresse e-mail validée de mech.kth.se
Ulysse REGLADECivil Engineer, Ecole des Mines de ParisAdresse e-mail validée de mines-paristech.fr
Jonathan ViqueratMines ParisTech - CEMEFAdresse e-mail validée de mines-paristech.fr
Elie HachemProfessor at MINES Paris PSL - ERC_Cog_2021Adresse e-mail validée de mines-paristech.fr
Joey VoermansUniversity of Melbourne, Ocean EngineeringAdresse e-mail validée de unimelb.edu.au
Miroslav KuchtaSimula Research LaboratoryAdresse e-mail validée de simula.no
Alexander BabaninThe University of MelbourneAdresse e-mail validée de unimelb.edu.au
takuji wasedaThe University of TokyoAdresse e-mail validée de k.u-tokyo.ac.jp
Müller MalteSenior Scientist, Norwegian Meteorological Institute; Professor II, University of OsloAdresse e-mail validée de met.no
Hui TangThe Hong Kong Polytechnic UniversityAdresse e-mail validée de polyu.edu.hk
Oyvind BreivikHead of Divison for Oceanography and Marine Meteorology, Norwegian Meteorological InstituteAdresse e-mail validée de met.no
Trygve LøkenAssociate professor at Nord UniversityAdresse e-mail validée de nord.no
Tsubasa KodairaOcean Technology, Policy, and Environment, GSFS, The University of TokyoAdresse e-mail validée de edu.k.u-tokyo.ac.jp
Oriol LehmkuhlLarge-scale Computational Fluid Dynamics Team Leader at Barcelona Supercomputer Center (BSC)Adresse e-mail validée de bsc.es
REN FENGNorthwestern Polytechnical UniversityAdresse e-mail validée de nwpu.edu.cn

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J Rabault

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Titre Trier par citations Trier par année Trier par titre	Citée par Citée par	Année
Artificial Neural Networks trained through Deep Reinforcement Learning discover control strategies for active flow control J Rabault, M Kuchta, A Jensen, U Reglade, N Cerardi Journal of Fluid Mechanics, 2019	293	2019
A review on Deep Reinforcement Learning for Fluid Mechanics P Garnier, J Viquerat, J Rabault, A Larcher, A Kuhnle, E Hachem Computers and Fluids, 2021	140	2021
Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning H Tang, J Rabault, A Kuhnle, Y Wang, T Wang Physics of Fluids, 2020	129	2020
Direct shape optimization through deep reinforcement learning J Viquerat, J Rabault, A Kuhnle, H Ghraieb, A Larcher, E Hachem Journal of Computational Physics 428, 110080, 2021	118	2021
Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach J Rabault, A Kuhnle Physics of Fluids 31 (9), 2019	111	2019
Performing particle image velocimetry using artificial neural networks: a proof-of-concept J Rabault, J Kolaas, A Jensen Measurement Science and Technology 28 (12), 125301, 2017	94	2017
Applying deep reinforcement learning to active flow control in weakly turbulent conditions F Ren, J Rabault, H Tang Physics of Fluids 33 (3), 2021	90	2021
Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization J Rabault, F Ren, W Zhang, H Tang, H Xu Journal of Hydrodynamics, 2020	79	2020
Observations of wave dispersion and attenuation in landfast ice G Sutherland, J Rabault Journal of Geophysical Research: Oceans, 2016	72	2016
Experiments on wave propagation in grease ice: combined wave gauges and particle image velocimetry measurements J Rabault, G Sutherland, A Jensen, KH Christensen, A Marchenko Journal of Fluid Mechanics 864, 876-898, 2019	58	2019
Exploiting locality and translational invariance to design effective deep reinforcement learning control of the 1-dimensional unstable falling liquid film V Belus, J Rabault, J Viquerat, Z Che, E Hachem, U Reglade AIP Advances 9 (12), 2019	52	2019
Active flow control with rotating cylinders by an artificial neural network trained by deep reinforcement learning H Xu, W Zhang, J Deng, J Rabault Journal of Hydrodynamics, 2020	50	2020
A two layer model for wave dissipation in sea ice G Sutherland, J Rabault, K Christensen, A Jensen Applied Ocean Research, 2019	48	2019
A study using PIV of the intake flow in a diesel engine cylinder J Rabault, JA Vernet, B Lindgren, PH Alfredsson International Journal of Heat and Fluid Flow, 2016	43	2016
Curving to fly: Synthetic adaptation unveils optimal flight performance of whirling fruits J Rabault, RA Fauli, A Carlson Physical Review Letters 122 (2), 024501, 2019	40	2019
Measurements of wave damping by a grease ice slick in Svalbard using off-the-shelf sensors and open source electronics J Rabault, G Sutherland, O Gundersen, A Jensen Journal of Glaciology, 2017	40	2017
An open source, versatile, affordable waves in ice instrument for scientific measurements in the Polar Regions J Rabault, G Sutherland, O Gundersen, A Jensen, A Marchenko, Ø Breivik Cold Regions Science and Technology 170, 102955, 2020	39*	2020
Flow control in wings and discovery of novel approaches via deep reinforcement learning R Vinuesa, O Lehmkuhl, A Lozano-Durán, J Rabault Fluids 7 (2), 62, 2022	34	2022
The attenuation of monochromatic surface waves due to the presence of an inextensible cover G Sutherland, T Halsne, J Rabault, A Jensen Wave motion, 2017	26	2017
Experimental evidence for a universal threshold characterizing wave-induced sea ice break-up JJ Voermans, J Rabault, K Filchuk, I Ryzhov, P Heil, A Marchenko, ... The Cryosphere 14 (11), 4265-4278, 2020	24	2020

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