This document contains a curated list of research articles concerned with the application of deep reinforcement learning (DRL) in fluid mechanics. Various categorizations of the articles are available:
- year
- topic
Naturally, in the topic-based sorting, articles may appear multiple times and the choice of topics is to some extend arbitrary. If you would like to expand or correct this list, feel free to open an issue.
Within each year, articles are sorted by family name of the first author.
2024
2023
- M. Chatzimanolakis et al.: Drag Reduction in Flows Past 2D and 3D Circular Cylinders Through Deep Reinforcement Learning [preprint]
- W. Chen et al.: Deep reinforcement learning-based active flow control of vortex-induced vibration of a square cylinder [article]
- A. Dixit and A. H. Elsheikh: Robust Optimal Well Control using an Adaptive Multigrid Reinforcement Learning Framework [article][preprint]
- T. P. Dussauge et al.: A reinforcement learning approach to airfoil shape optimization [article]
- L. Guastoni et al.: Deep reinforcement learning for turbulent drag reduction in channel flows [article][preprint][code]
- L. Guastoni et al.: Drag-reduction strategies in wall-bounded turbulent flows using deep reinforcement learning [preprint]
- F. Haodong et al.: How to control hydrodynamic force on fluidic pinball via deep reinforcement learning [article][preprint][code]
- H. Jiang and S. Cao: Reinforcement learning-based active flow control of oscillating cylinder for drag reduction [article]
- M. Kurz et al.: Deep reinforcement learning for turbulence modeling in large eddy simulations [article][preprint][code]
- T. Lee et al.: Turbulence control for drag reduction through deep reinforcement learning [article]
- A. J. Linot et al.: Turbulence control in plane Couette flow using low-dimensional neural ODE-based models and deep reinforcement learning [article][preprint]
- N. J. Nair and A. Goza: Bio-inspired variable-stiffness flaps for hybrid flow control, tuned via reinforcement learning [article][preprint]
- R. Paris et al.: Reinforcement-learning-based actuator selection method for active flow control [article]
- S. Peitz et al.: Distributed Control of Partial Differential Equations Using Convolutional Reinforcement Learning [preprint]
- F. Pino et al.: Comparative analysis of machine learning methods for active flow control [article][preprint]
- T. Sonoda et al.: Reinforcement learning of control strategies for reducing skin friction drag in a fully developed turbulent channel flow [article]
- P. Suarez et al.: Active flow control for three-dimensional cylinders through deep reinforcement learning [preprint]
- A. Vadrot et al.: Survey of machine-learning wall models for large-eddy simulation [article][preprint]
- C. Vignon et al.: Recent advances in applying deep reinforcement learning for flow control: Perspectives and future directions [article]
- C. Vignon et al.: Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need [article][preprint][code]
- J. Viquerat and E. Hachem: Parallel Bootstrap-Based On-Policy Deep Reinforcement Learning for Continuous Fluid Flow Control Applications [article][preprint]
- M. Shams and A. H. Elsheikh: PGym-preCICE: Reinforcement learning environments for active flow control [article][preprint][code]
- Q. Wang et al.: Dynamic Feature-based Deep Reinforcement Learning for Flow Control of Circular Cylinder with Sparse Surface Pressure Sensing [preprint]
- Z. Wang et al.: Deep reinforcement transfer learning of active control for bluff body flows at high Reynolds number [[article](Deep reinforcement transfer learning of active control for bluff body flows at high Reynolds number)]
- C. Xia et al.: Active Flow Control for Bluff Body Drag Reduction Using Reinforcement Learning with Partial Measurements [preprint]
- H. Xian-Jun et al.: Policy transfer of reinforcement learning-based flow control: From two- to three-dimensional environment [article]
- D. Xu et al.: Reinforcement-learning-based control of convectively unstable flows [article][preprint]
- L. Yan et al.: Stabilizing the square cylinder wake using deep reinforcement learning for different jet locations [article]
- X. Zhenlin et al.: Applying reinforcement learning to mitigate wake-induced lift fluctuation of a wall-confined circular cylinder in tandem configuration [article]
2022
- E. Amico et al.: Deep reinforcement learning for active control of a three-dimensional bluff body wake [article]
- H. J. Bae, P. Koumoutsakos: Scientific multi-agent reinforcement learning for wall-models of turbulent flows [article][code-1, code-2]
- H. Ghraieb et al.: Single-step deep reinforcement learning for two- and three-dimensional optimal shape design [article][code]
- J. Kim et al.: Deep reinforcement learning for large-eddy simulation modeling in wall-bounded turbulence [article][preprint][code]
- A. Kubo and M. Shimizu: Efficient reinforcement learning with partial observables for fluid flow control [article][preprint]
- M. Kurz et al.: Relexi - A scalable open source reinforcement learning framework for high-performance computing [article][code]
- M. Kurz et al.: Deep reinforcement learning for computational fluid dynamics on HPC systems [article][code]
- H. Liang et al.: A Model Coupling CFD and DRL: Investigation on Wave Dissipation by Actively Controlled Flat Plate [article]
- J. Li and M. Zhang: Reinforcement-learning-based control of confined cylinder wakes with stability analyses [article][preprint]
- C. Lorsung and A. B. Farimani: Mesh deep Q network: A deep reinforcement learning framework for improving meshes in computational fluid dynamics [article][preprint][code]
- Y. Mao et al.: Active flow control using deep reinforcement learning with time delays in Markov decision process and autoregressive policy [article]
- Y. F. Mei et al.: Active control for the flow around various geometries through deep reinforcement learning [article]
- J. R. Mianroodi et al.: Computational Discovery of Energy-Efficient Heat Treatment for Microstructure Design using Deep Reinforcement Learning [preprint]
- P. Varela et al.: Deep Reinforcement Learning for Flow Control Exploits Different Physics for Increasing Reynolds Number Regimes [article][preprint]
- R. Vinuesa et al.: Flow Control in Wings and Discovery of Novel Approaches via Deep Reinforcement Learning [article][preprint]
- J. Viquerat et al.: A review on deep reinforcement learning for fluid mechanics: An update [article][preprint]
- Q. Wang et al.: DRLinFluids: An open-source Python platform of coupling deep reinforcement learning and OpenFOAM [article][preprint][code]
- Y. Z. Wang et al.: Deep reinforcement learning based synthetic jet control on disturbed flow over airfoil [article]
- Y. Z. Wang et al.: Accelerating and improving deep reinforcement learning-based active flow control: Transfer training of policy network [article]
- J. Wei et al.: An Embedded Feature Selection Framework for Control [preprint][code]
- C. Zheng et al.: Data-efficient deep reinforcement learning with expert demonstration for active flow control [article][preprint]
- Y. Zhu et al.: Point-to-Point Navigation of a Fish-Like Swimmer in a Vortical Flow With Deep Reinforcement Learning [article]
2021
- P. Garnier et al.: A review on deep reinforcement learning for fluid mechanics [article][preprint]
- H. Ghraieb et al.: Single-step deep reinforcement learning for open-loop control of laminar and turbulent flows [article][preprint][code]
- E. Hachem et al.: Deep reinforcement learning for the control of conjugate heat transfer [article][preprint][code]
- M. Holm: Using Deep Reinforcement Learning for Active Flow Control [article][code]
- H. Korb et al.: Exploring the application of reinforcement learning to wind farm control [article]
- S. Li et al.: Active Simulation of Transient Wind Field in a Multiple-FanWind Tunnel via Deep Reinforcement Learning [article]
- R. Li et al.: Learning the aerodynamic design of supercritical airfoils through deep reinforcement learning [article][preprint]
- G. Novati et al.: Automating turbulence modelling by multi-agent reinforcement learning [article][preprint][code]
- R. Paris et al.: Robust flow control and optimal sensor placement using deep reinforcement learning [article][preprint]
- S. Qin et al.: Multi-Objective Optimization of Cascade Blade Profile Based on Reinforcement Learning [article]
- S. Pawar and R. Maulik: Distributed deep reinforcement learning for simulation control [article][preprint][code]
- S. Qin et al.: An application of data driven reward of deep reinforcement learning by dynamic mode decomposition in active flow control [preprint]
- F. Ren et al.: Applying deep reinforcement learning to active flow control in weakly turbulent conditions [article][preprint]
- J. Viquerat et al.: Direct shape optimization through deep reinforcement learning [article][preprint][code]
- D. Wada et al.: Unmanned Aerial Vehicle Pitch Control Using Deep Reinforcement Learning with Discrete Actions in Wind Tunnel Test [article]
- Y. Xie et al.: Sloshing suppression with active controlled baffles through deep reinforcement learning–expert demonstrations–behavior cloning process [article]
- L. Yan et al.: Learning how to avoid obstacles: A numerical investigation for maneuvering of self-propelled fish based on deep reinforcement learning [article]
- C. Zheng et al.: From active learning to deep reinforcement learning: Intelligent active flow control in suppressing vortex-induced vibration [article]
- Y. Zhu et al.: A numerical study of fish adaption behaviors in complex environments with a deep reinforcement learning and immersed boundary–lattice Boltzmann method [article]
2020
- G. Beintema et al.: Controlling Rayleigh–Bénard convection via reinforcement learning [article][preprint]
- D. Fan et al.: Reinforcement learning for bluff body active flow control in experiments and simulations [article][preprint][code]
- H. Tang et al.: Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning [article][preprint][code]
- S. Shimomura et al.: Closed-Loop Flow Separation Control Using the Deep Q Network over Airfoil [article]
- M. Tokarev et al.: A Deep Reinforcement Learning Control of Cylinder Flow Using Rotary Oscillations at Low Reynolds Number [article]
- J. Rabault et al.: Deep reinforcement learning in fluid mechanics: A promising method for both active flow control and shape optimization [article]
- H. Xu et al.: Active flow control with rotating cylinders by an artificial neural network trained by deep reinforcement learning [article]
- Y. Lang et al.: A numerical simulation method for bionic fish self-propelled swimming under control based on deep reinforcement learning [article]
2019
- V. Belus et al.: Exploiting locality and translational invariance to design effective deep reinforcement learning control of the 1-dimensional unstable falling liquid film [article][preprint][code]
- X. Y. Lee et al.: A Case Study of Deep Reinforcement Learning for Engineering Design: Application to Microfluidic Devices for Flow Sculpting [article][preprint]
- J. Rabault et al.: Artificial neural networks trained through deep reinforcement learning discover control strategies for active flow control [article][preprint][code]
- J. Rabault, A. Kuhnle: Accelerating deep reinforcement learning strategies of flow control through a multi-environment approach [article][preprint][code]
- X. Yan et al.: Aerodynamic shape optimization using a novel optimizer based on machine learning techniques [article]
2018
- O. J. Dessler et al.: Reinforcement Learning for Dynamic Microfluidic Control [article]
- P. Ma et al.: Fluid directed rigid body control using deep reinforcement learning [article][code]
- S. Verma et al.: Efficient collective swimming by harnessing vortices through deep reinforcement learning [article][preprint]
2017
2014
- M. Gazzola et al.: Reinforcement Learning and Wavelet Adapted Vortex Methods for Simulations of Self-propelled Swimmers [article]
Within each topic, articles are sorted by family name of the first author.
flow control in experiments
- E. Amico et al.: Deep reinforcement learning for active control of a three-dimensional bluff body wake [article]
- O. J. Dessler et al.: Reinforcement Learning for Dynamic Microfluidic Control [article]
- D. Fan et al.: Reinforcement learning for bluff body active flow control in experiments and simulations [article][preprint][code]
- S. Li et al.: Active Simulation of Transient Wind Field in a Multiple-FanWind Tunnel via Deep Reinforcement Learning [article]
- S. Shimomura et al.: Closed-Loop Flow Separation Control Using the Deep Q Network over Airfoil [article]
- D. Wada et al.: Unmanned Aerial Vehicle Pitch Control Using Deep Reinforcement Learning with Discrete Actions in Wind Tunnel Test [article]