most citedDeep reinforcement learning for flow control exploits different physics for increasing Reynolds-number regimes

2 citations · 2 across the 1 of their papers we have counts for

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2 papers

physics.flu-dyn2022★ 2 cited

Deep reinforcement learning for flow control exploits different physics for increasing Reynolds-number regimes

Pau Varela, Pol Suárez, Francisco Alcántara-Ávila +6

Deep artificial neural networks (ANNs) used together with deep reinforcement learning (DRL) are receiving growing attention due to their capabilities to control complex problems. T…

physics.flu-dyn2020

Deep learning of the spanwise-averaged Navier-Stokes equations

Bernat Font, Gabriel D. Weymouth, Vinh-Tan Nguyen +1

Simulations of turbulent fluid flow around long cylindrical structures are computationally expensive because of the vast range of length scales, requiring simplifications such as d…