most citedDeep reinforcement learning for the control of conjugate heat transfer with application to workpiece cooling

4 citations · 5 across the 2 of their papers we have counts for

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physics.flu-dyn2020★ 4 cited

Deep reinforcement learning for the control of conjugate heat transfer with application to workpiece cooling

Elie Hachem, Hassan Ghraieb, Jonathan Viquerat +2

This research gauges the ability of deep reinforcement learning (DRL) techniques to assist the control of conjugate heat transfer systems governed by the coupled Navier--Stokes and…

physics.flu-dyn2019★ 1 cited

Optimal transient growth in an incompressible flow past a backward-slanted step

Marco Martins Afonso, Philippe Meliga, Eric Serre

With the aim of providing a first step in the quest for a reduction of the aerodynamic drag on the rear-end of a car, we study the phenomena of separation and reattachment of an in…