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We conduct an active flow control (AFC) study on the mass flow rate of synthetic jets on the upper and lower surfaces of a square cylinder using a deep reinforcement learning (DRL) algorithm, with a focus on investigating the influence of…

Fluid Dynamics · Physics 2024-10-01 Wang Jia , Hang Xu

Active flow control of compressible transonic shock-boundary layer interactions over a two-dimensional RAE2822 airfoil at Re = 50,000 is investigated using deep reinforcement learning (DRL). The flow field exhibits highly unsteady dynamics,…

Fluid Dynamics · Physics 2025-11-12 Trishit Mondal , Ricardo Vinuesa , Ameya D. Jagtap

The real power of artificial intelligence appears in reinforcement learning, which is computationally and physically more sophisticated due to its dynamic nature. Rotation and injection are some of the proven ways in active flow control for…

Fluid Dynamics · Physics 2024-01-02 Kamyar Dobakhti , Jafar Ghazanfarian

This study showcases an experimental deployment of deep reinforcement learning (DRL) for active flow control (AFC) of vortex-induced vibrations (VIV) in a circular cylinder at a high Reynolds number (Re = 3000) using rotary actuation.…

Machine Learning · Computer Science 2025-09-30 Hussam Sababha , Bernat Font , Mohammed Daqaq

High-fidelity simulations are performed to study active flow control techniques for alleviating deep dynamic stall of a SD7003 airfoil in plunging motion. The flow Reynolds number is $Re=60{,}000$ and the freestream Mach number is $M=0.1$.…

This study investigates the effectiveness of Model Predictive Control (MPC) and Reinforcement Learning (RL) for active flow control over a NACA 4412 airfoil near static stall at Reynolds number 4*10^5. By systematically evaluating these…

Deep Reinforcement Learning (DRL) has recently been proposed as a methodology to discover complex Active Flow Control (AFC) strategies [Rabault, J., Kuchta, M., Jensen, A., Reglade, U., & Cerardi, N. (2019): "Artificial neural networks…

Computational Physics · Physics 2019-10-23 Jean Rabault , Alexander Kuhnle

This paper presents for the first time successful results of active flow control with multiple independently controlled zero-net-mass-flux synthetic jets. The jets are placed on a three-dimensional cylinder along its span with the aim of…

Deep Reinforcement Learning (DRL) has emerged as a promising approach for handling highly dynamic and nonlinear Active Flow Control (AFC) problems. However, the computational cost associated with training DRL models presents a significant…

Machine Learning · Computer Science 2024-09-27 Wang Jia , Hang Xu

This paper focuses on developing a deep reinforcement learning (DRL) control strategy to mitigate aerodynamic forces acting on a three dimensional (3D) square cylinder under high Reynolds number flow conditions. Four jets situated at the…

Fluid Dynamics · Physics 2024-01-24 Lei Yan , Gang Hu , Wenli Chen , Bernd R. Noack

This research examines the aerodynamic performance of wavy (corrugated) airfoils, focusing specifically on analyzing the impact of two angles of attack: the airfoil's angle of attack and the tail's angle of attack (beta). Simulations were…

Fluid Dynamics · Physics 2025-03-10 Mohammad Amin Esabat , Saeed Jaamei , Fatemeh Asadi , Ahmad Reza Kohansal , Hassan Abyn

This study proposes a self-learning algorithm for closed-loop cylinder wake control targeting lower drag and lower lift fluctuations with the additional challenge of sparse sensor information, taking deep reinforcement learning as the…

Machine Learning · Computer Science 2024-06-04 Qiulei Wang , Lei Yan , Gang Hu , Wenli Chen , Jean Rabault , Bernd R. Noack

Deep reinforcement learning (DRL) has been applied to a variety of problems during the past decade, and has provided effective control strategies in high-dimensional and non-linear situations that are challenging to traditional methods.…

Fluid Dynamics · Physics 2023-04-07 Colin Vignon , Jean Rabault , Ricardo Vinuesa

The control efficacy of classical periodic forcing and deep reinforcement learning (DRL) is assessed for a turbulent separation bubble (TSB) at $Re_\tau=180$ on the upstream region before separation occurs. The TSB can resemble a separation…

This study presents wall-resolved large-eddy simulations (WRLES) of a high-lift airfoil, based on high-order flux reconstruction (FR) commercial software Dimaxer, which runs on consumer level GPUs. A series of independence tests are…

Fluid Dynamics · Physics 2024-11-11 Keli Zhang , Shizhi Lin , Peiqing Liu , Shihao Liu , Kai Liu

The present research aims to enhance the efficiency of a DTU-10MW Horizontal Axis Wind Turbine (HAWT) via Active Flow Control (AFC) implementation and using Synthetic Jets (SJ). In the initial part of the study the flow around two airfoil…

Fluid Dynamics · Physics 2024-07-31 Marc Lahoz , Ahmad Nabhani , Mohammad Saemian , Josep M Bergada

This study presents the first experimental implementation of deep reinforcement learning (DRL) for the active real-time suppression of flow-induced vibrations in simultaneously vibrating tandem cylinders using rotary actuation, considering…

Fluid Dynamics · Physics 2026-05-21 Hussam Sababha , Mohammed Daqaq

Flow generated noise are caused shear flows and, hence, they can be used as feedback to control the flow. Existing flow control uses state variables like velocity, pressure, or vorticity, none use acoustic observables as the primary control…

Fluid Dynamics · Physics 2026-05-12 Siddharth Rout , Khai Phan , Chao-An Lin

We propose a novel active-flow-control (AFC) strategy for bluff bodies to hide their hydrodynamic traces from predators. A group of windward-suction-leeward-blowing (WSLB) actuators are adopted to control the wake of a circular cylinder…

Fluid Dynamics · Physics 2021-09-15 Feng Ren , Hui Tang

We combine three-dimensional (3D) large-eddy simulations (LES) and resolvent analysis to design active separation control techniques on a NACA 0012 airfoil. Spanwise-periodic flows over the airfoil at a chord-based Reynolds number of…

Fluid Dynamics · Physics 2019-05-01 Chi-An Yeh , Kunihiko Taira