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physics.flu-dyn2025

Strategies for energy-efficient flow control leveraging deep reinforcement learning

Wang Jia, Hang Xu

This study investigates active flow control in two-dimensional flows at a Reynolds number of 100 using Deep Reinforcement Learning (DRL). We utilize DRL to develop flow control str…

physics.flu-dyn2025

Vortex shedding suppression in elliptical cylinder via reinforcement learning

Wang Jia, Hang Xu

Flow control of bluff bodies plays a critical role in engineering applications. In this study, deep reinforcement learning (DRL) is employed to develop flow control strategies for…

physics.flu-dyn2024

Effect of Synthetic Jets Actuator Parameters on Deep Reinforcement Learning-Based Flow Control Performance in a Square Cylinder

Wang Jia, Hang Xu

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)…

physics.flu-dyn2024

Deep reinforcement learning-based active flow control of an elliptical cylinder: transitioning from an elliptical cylinder to a circular cylinder and a flat plate

Wang Jia, Hang Xu

We study the adaptability of deep reinforcement learning (DRL)-based active flow control (AFC) technology for bluff body flows with complex geometries. It is extended from a cylind…

physics.flu-dyn2024

Robust and Adaptive Deep Reinforcement Learning for Enhancing Flow Control around a Square Cylinder with Varying Reynolds Numbers

Wang Jia, Hang Xu

The present study applies a Deep Reinforcement Learning (DRL) algorithm to Active Flow Control (AFC) of a two-dimensional flow around a confined square cylinder. Specifically, the…