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 …

Closed-loop turbulence control is a critical enabler of aerodynamic drag reduction, lift
increase, mixing enhancement, and noise reduction. Current and future applications have …

Wind energy conversion system, aiming to convert mechanical energy of air flow into
electrical energy has been widely concerned in recent decades. According to the installation …

This paper focuses on the active flow control of a computational fluid dynamics simulation
over a range of Reynolds numbers using deep reinforcement learning (DRL). More …

Two vortex-induced vibration (VIV) events of the main girder of long-span bridges
successively happened on the Yingwuzhou suspension bridge and Humen suspension …

This article presents a review of the state of the art and present status of active aeroelastic
rotor control research for wind turbines. Using advanced control concepts to reduce loads on …

We mitigate vortex-induced vibrations of a square cylinder at a Reynolds number of 100
using deep reinforcement learning (DRL)-based active flow control (AFC). The proposed …

In recent years, artificial neural networks (ANNs) and deep learning have become
increasingly popular across a wide range of scientific and technical fields, including fluid …

Active control of laminar boundary layers with dielectric barrier discharge (DBD) plasma
actuators (PAs) has made considerable progress in the last 15 years. First pioneering …

The objective of this paper is to introduce the essential ingredients of linear systems and
control theory to the fluid mechanics community, to discuss the relevance of this theory to …