Recent advances in applying deep reinforcement learning for flow control: Perspectives and future directions
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 …
past decade and has provided effective control strategies in high-dimensional and non …
Review of active control of circular cylinder flow
Fluid flow around a circular cylinder is ubiquitous in nature and in various industrial
applications. The periodic von Kármán vortex shedding from the cylinder is one of the …
applications. The periodic von Kármán vortex shedding from the cylinder is one of the …
Robust active flow control over a range of Reynolds numbers using an artificial neural network trained through deep reinforcement learning
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 …
over a range of Reynolds numbers using deep reinforcement learning (DRL). More …
Applying deep reinforcement learning to active flow control in weakly turbulent conditions
Machine learning has recently become a promising technique in fluid mechanics, especially
for active flow control (AFC) applications. A recent work [Rabault et al., J. Fluid Mech. 865 …
for active flow control (AFC) applications. A recent work [Rabault et al., J. Fluid Mech. 865 …
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 …
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 …
[HTML][HTML] Recent progress of machine learning in flow modeling and active flow control
In terms of multiple temporal and spatial scales, massive data from experiments, flow field
measurements, and high-fidelity numerical simulations have greatly promoted the rapid …
measurements, and high-fidelity numerical simulations have greatly promoted the rapid …
Active flow control using machine learning: A brief review
Nowadays the rapidly developing artificial intelligence has become a key solution for
problems of diverse disciplines, especially those involving big data. Successes in these …
problems of diverse disciplines, especially those involving big data. Successes in these …
Effective control of two-dimensional Rayleigh–Bénard convection: Invariant multi-agent reinforcement learning is all you need
Rayleigh–Bénard convection (RBC) is a recurrent phenomenon in a number of industrial
and geoscience flows and a well-studied system from a fundamental fluid-mechanics …
and geoscience flows and a well-studied system from a fundamental fluid-mechanics …