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A review on Deep Reinforcement Learning for Fluid Mechanics

Computers & Fluids (Comput. Fluids), 2019

12 August 2019

Papers citing "A review on Deep Reinforcement Learning for Fluid Mechanics"

39 / 39 papers shown

Title
Active Control of Turbulent Airfoil Flows Using Adjoint-based Deep Learning Xuemin Liu Tom Hickling J. MacArt AI4CE 84 1 0 08 Oct 2025
Optimizing Metachronal Paddling with Reinforcement Learning at Low Reynolds Number Alana A. Bailey Robert D. Guy 77 0 0 24 Jul 2025
Transfer learning-enhanced deep reinforcement learning for aerodynamic airfoil optimisation subject to structural constraintsThe Physics of Fluids (Phys. Fluids), 2025 David Ramos Lucas Lacasa E. Valero G. Rubio AI4CE 328 0 0 05 May 2025
Control of Rayleigh-Bénard Convection: Effectiveness of Reinforcement Learning in the Turbulent Regime Thorben Markmann Michiel Straat Sebastian Peitz Barbara Hammer AI4CE 318 0 0 16 Apr 2025
SALSA-RL: Stability Analysis in the Latent Space of Actions for Reinforcement Learning Xuyang Li Romit Maulik 386 0 0 21 Feb 2025
Multi-modal Policies with Physics-informed Representations in Complex Fluid Environments Haodong Feng Tailin Wu Yue Wang Dixia Fan AI4CE PINN 226 0 0 20 Oct 2024
Real-time optimal control of high-dimensional parametrized systems by deep learning-based reduced order modelsComputer Methods in Applied Mechanics and Engineering (CMAME), 2024 Matteo Tomasetto Andrea Manzoni Francesco Braghin AI4CE 225 6 0 09 Sep 2024
Enhancing Vehicle Aerodynamics with Deep Reinforcement Learning in Voxelised Models Jignesh Patel Yannis Spyridis Vasileios Argyriou 155 3 0 19 May 2024
Mixing Artificial and Natural Intelligence: From Statistical Mechanics to AI and Back to Turbulence Michael Chertkov AI4CE 306 4 0 26 Mar 2024
Beacon, a lightweight deep reinforcement learning benchmark library for flow control J. Viquerat P. Meliga Pablo Jeken E. Hachem AI4CE 206 1 0 27 Feb 2024
Model-based deep reinforcement learning for accelerated learning from flow simulations Andre Weiner Janis Geise AI4CE 249 6 0 26 Feb 2024
Reinforcement learning to maximise wind turbine energy generation Daniel Soler O. Marino D. Huergo Martín de Frutos Esteban Ferrer 103 0 0 17 Feb 2024
Better Neural PDE Solvers Through Data-Free Mesh MoversInternational Conference on Learning Representations (ICLR), 2023 Tailin Wu Yue Wang Zhi-Ming Ma AI4CE 225 8 0 09 Dec 2023
Differentiable DG with Neural Operator Source Term Correction Shinhoo Kang Emil M. Constantinescu AI4CE 354 0 0 29 Oct 2023
Physics-aware Machine Learning Revolutionizes Scientific Paradigm for Machine Learning and Process-based Hydrology Qingsong Xu Yilei Shi Jonathan Bamber Ye Tuo Ralf Ludwig Xiao Xiang Zhu AI4CE 817 19 0 08 Oct 2023
An unsupervised machine-learning-based shock sensor for high-order supersonic flow solvers A. Mateo-Gabín Kenza Tlales E. Valero E. Ferrer G. Rubio AI4CE 280 0 0 28 Jul 2023
Effective Latent Differential Equation Models via Attention and Multiple Shooting German Abrevaya Mahta Ramezanian-Panahi Jean-Christophe Gagnon-Audet Pablo Polosecki Irina Rish S. Dawson Guillermo Cecchi G. Dumas MedIm 272 4 0 11 Jul 2023
Parallel bootstrap-based on-policy deep reinforcement learning for continuous flow control applicationsFluids (Fluids), 2023 J. Viquerat E. Hachem 154 3 0 24 Apr 2023
Effective control of two-dimensional Rayleigh--Bénard convection: invariant multi-agent reinforcement learning is all you needThe Physics of Fluids (Phys. Fluids), 2023 Colin Vignon Jean Rabault Joel Vasanth Francisco Alcántara-Ávila M. Mortensen Ricardo Vinuesa AI4CE 229 54 0 05 Apr 2023
Learning a model is paramount for sample efficiency in reinforcement learning control of PDEs Stefan Werner Sebastian Peitz 271 10 0 14 Feb 2023
Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learningInternational Journal of Heat and Fluid Flow (IJHFF), 2023 Alec J. Linot Kevin Zeng M. Graham AI4CE 163 28 0 28 Jan 2023
Investigation of reinforcement learning for shape optimization of profile extrusion dies C. Fricke D. Wolff Marco Kemmerling S. Elgeti OffRL 51 6 0 23 Dec 2022
MeshDQN: A Deep Reinforcement Learning Framework for Improving Meshes in Computational Fluid Dynamics Cooper Lorsung A. Farimani AI4CE 135 3 0 02 Dec 2022
Learning swimming via deep reinforcement learning Jin Zhang Lei Zhou Bochao Cao 297 2 0 22 Sep 2022
Unsupervised Representation Learning in Deep Reinforcement Learning: A Review N. Botteghi M. Poel C. Brune SSL OffRL 333 22 0 27 Aug 2022
Variational multiscale reinforcement learning for discovering reduced order closure models of nonlinear spatiotemporal transport systemsScientific Reports (Sci Rep), 2022 Omer San Suraj Pawar Adil Rasheed AI4CE 119 7 0 07 Jul 2022
Data-Driven Evaluation of Training Action Space for Reinforcement Learning Rajat Ghosh Debojyoti Dutta 104 0 0 08 Apr 2022
A Thermodynamics-informed Active Learning Approach to Perception and Reasoning about FluidsComputational Mechanics (Comput. Mech.), 2022 B. Moya Alberto Badías D. González Francisco Chinesta Elías Cueto AI4CE 153 20 0 11 Mar 2022
Comparative analysis of machine learning methods for active flow controlJournal of Fluid Mechanics (JFM), 2022 F. Pino Lorenzo Schena Jean Rabault M. A. Mendez 272 50 0 23 Feb 2022
Multi-fidelity reinforcement learning framework for shape optimizationJournal of Computational Physics (JCP), 2022 Sahil Bhola Suraj Pawar Dali Wang R. Maulik AI4CE 125 30 0 22 Feb 2022
Machine Learning in Aerodynamic Shape OptimizationProgress in Aerospace Sciences (Prog. Aerosp. Sci.), 2022 Ji-chao Li Xiaosong Du J. Martins AI4CE 323 253 0 15 Feb 2022
Classifying Turbulent Environments via Machine Learning M. Buzzicotti F. Bonaccorso 154 0 0 03 Jan 2022
Multi-condition multi-objective optimization using deep reinforcement learningJournal of Computational Physics (JCP), 2021 Sejin Kim Innyoung Kim D. You AI4CE 152 32 0 10 Oct 2021
Physics-informed Dyna-Style Model-Based Deep Reinforcement Learning for Dynamic ControlProceedings of the Royal Society A (Proc. R. Soc. A), 2021 Xin-Yang Liu Jian-Xun Wang AI4CE 241 48 0 31 Jul 2021
Evaluating the progress of Deep Reinforcement Learning in the real world: aligning domain-agnostic and domain-specific research J. Luis E. Crawley B. Cameron OffRL 258 6 0 07 Jul 2021
Learning Principle of Least Action with Reinforcement Learning Zehao Jin J. Lin Siao-Fong Li 85 5 0 24 Nov 2020
Automating Turbulence Modeling by Multi-Agent Reinforcement Learning G. Novati Hugues Lascombes de Laroussilhe Petros Koumoutsakos AI4CE 211 15 0 18 May 2020
A physics-informed reinforcement learning approach for the interfacial area transport in two-phase flowSocial Science Research Network (SSRN), 2019 Z. Dang M. Ishii AI4CE 154 13 0 06 Aug 2019
Flow Navigation by Smart Microswimmers via Reinforcement LearningPhysical Review Letters (PRL), 2017 S. Colabrese K. Gustavsson A. Celani Luca Biferale 281 174 0 30 Jan 2017