Super-resolution analysis via machine learning: a survey for fluid flows
This paper surveys machine-learning-based super-resolution reconstruction for vortical
flows. Super resolution aims to find the high-resolution flow fields from low-resolution data …
flows. Super resolution aims to find the high-resolution flow fields from low-resolution data …
A review on deep reinforcement learning for fluid mechanics: An update
In the past couple of years, the interest of the fluid mechanics community for deep
reinforcement learning techniques has increased at fast pace, leading to a growing …
reinforcement learning techniques has increased at fast pace, leading to a growing …
Deep reinforcement learning for turbulent drag reduction in channel flows
We introduce a reinforcement learning (RL) environment to design and benchmark control
strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The …
strategies aimed at reducing drag in turbulent fluid flows enclosed in a channel. The …
Reinforcement-learning-based control of confined cylinder wakes with stability analyses
This work studies the application of a reinforcement learning (RL)-based flow control
strategy to the flow past a cylinder confined between two walls to suppress vortex shedding …
strategy to the flow past a cylinder confined between two walls to suppress vortex shedding …
DRLinFluids: An open-source Python platform of coupling deep reinforcement learning and OpenFOAM
We propose an open-source Python platform for applications of deep reinforcement learning
(DRL) in fluid mechanics. DRL has been widely used in optimizing decision making in …
(DRL) in fluid mechanics. DRL has been widely used in optimizing decision making in …
Deep reinforcement learning-based active flow control of vortex-induced vibration of a square cylinder
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 …
using deep reinforcement learning (DRL)-based active flow control (AFC). The proposed …
From active learning to deep reinforcement learning: Intelligent active flow control in suppressing vortex-induced vibration
In the present work, an efficient active flow control strategy in eliminating vortex-induced
vibration of a cylinder at Re= 100 has been explored by two machine learning frameworks …
vibration of a cylinder at Re= 100 has been explored by two machine learning frameworks …
Flow control in wings and discovery of novel approaches via deep reinforcement learning
In this review, we summarize existing trends of flow control used to improve the aerodynamic
efficiency of wings. We first discuss active methods to control turbulence, starting with flat …
efficiency of wings. We first discuss active methods to control turbulence, starting with flat …
Deep reinforcement learning based synthetic jet control on disturbed flow over airfoil
This paper applies deep reinforcement learning (DRL) on the synthetic jet control of flows
over an NACA (National Advisory Committee for Aeronautics) 0012 airfoil under weak …
over an NACA (National Advisory Committee for Aeronautics) 0012 airfoil under weak …
Comparative analysis of machine learning methods for active flow control
Machine learning frameworks such as genetic programming and reinforcement learning
(RL) are gaining popularity in flow control. This work presents a comparative analysis of the …
(RL) are gaining popularity in flow control. This work presents a comparative analysis of the …