Jean 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
Ricardo VinuesaAssociate Professor, KTH Royal Institute of TechnologyAdresse e-mail validée de mech.kth.se
Aleksey MarchenkoThe University Centre in SvalbardAdresse e-mail validée de unis.no
Alexander KuhnleZebra TechnologiesAdresse e-mail validée de cantab.ac.uk
Kai H. ChristensenSenior Scientist, Norwegian Meteorological InstituteAdresse e-mail validée de met.no
Oyvind BreivikHead of Divison for Oceanography and Marine Meteorology, Norwegian Meteorological InstituteAdresse e-mail validée de met.no
Oriol LehmkuhlLarge-scale Computational Fluid Dynamics Team Leader at Barcelona Supercomputer Center (BSC)Adresse e-mail validée de bsc.es
Joey VoermansUniversity of Melbourne, Ocean EngineeringAdresse e-mail validée de unimelb.edu.au
Ulysse REGLADECivil Engineer, Ecole des Mines de ParisAdresse e-mail validée de mines-paristech.fr
takuji wasedaThe University of TokyoAdresse e-mail validée de k.u-tokyo.ac.jp
Jonathan ViqueratMines ParisTech - CEMEFAdresse e-mail validée de mines-paristech.fr
Francisco Alcántara ÁvilaResearcher, UPVLCAdresse e-mail validée de alumni.upv.es
Miroslav KuchtaSimula Research LaboratoryAdresse e-mail validée de simula.no
Tsubasa KodairaOcean Technology, Policy, and Environment, GSFS, The University of TokyoAdresse e-mail validée de edu.k.u-tokyo.ac.jp
Elie HachemProfessor at MINES Paris PSL - ERC_Cog_2021Adresse e-mail validée de mines-paristech.fr
Alexander BabaninThe University of MelbourneAdresse e-mail validée de unimelb.edu.au
Bernat FontTU DelftAdresse e-mail validée de tudelft.nl
Nicolas CerardiPhD Student, CEA AIMAdresse e-mail validée de cea.fr
Müller MalteSenior Scientist, Norwegian Meteorological Institute; Professor II, University of OsloAdresse e-mail validée de met.no

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Jean Rabault

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Adresse e-mail validée de met.no


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	496	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	273	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	206	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	204	2021
Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach J Rabault, A Kuhnle Physics of Fluids 31 (9), 2019	186	2019
Applying deep reinforcement learning to active flow control in weakly turbulent conditions F Ren, J Rabault, H Tang Physics of Fluids 33 (3), 2021	159	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	149	2020
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	130	2017
Recent advances in applying deep reinforcement learning for flow control: perspectives and future directions C Vignon, J Rabault, R Vinuesa Physics of Fluids 35 (3), 2023	112	2023
Observations of wave dispersion and attenuation in landfast ice G Sutherland, J Rabault Journal of Geophysical Research: Oceans, 2016	84	2016
Deep reinforcement learning for turbulent drag reduction in channel flows L Guastoni, J Rabault, P Schlatter, H Azizpour, R Vinuesa The European Physical Journal E 46 (4), 27, 2023	76	2023
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	72	2020
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	71	2019
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	70	2019
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	68	2022
DRLinFluids: An open-source Python platform of coupling deep reinforcement learning and OpenFOAM Q Wang, L Yan, G Hu, C Li, Y Xiao, H Xiong, J Rabault, BR Noack Physics of Fluids 34 (8), 2022	64	2022
A two layer model for wave dissipation in sea ice G Sutherland, J Rabault, K Christensen, A Jensen Applied Ocean Research, 2019	63	2019
Comparative analysis of machine learning methods for active flow control F Pino, L Schena, J Rabault, MA Mendez Journal of Fluid Mechanics 958, A39, 2023	55	2023
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	55*	2020
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	53	2019

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