4 citations · 7 across the 3 of their papers we have counts for
4 papers
Policy-based optimization: single-step policy gradient method seen as an evolution strategy
Jonathan Viquerat, Régis Duvigneau, Philippe Meliga +2
This research reports on the recent development of a black-box optimization method based on single-step deep reinforcement learning (DRL), and on its conceptual proximity to evolut…
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…
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…
Implementation of a discrete Immersed Boundary Method in OpenFOAM
E. Constant, C. Li, J. Favier +3
In this paper, the Immersed Boundary Method (IBM) proposed by Pinelli is implemented for finite volume approximations of incompressible Navier-Stokes equations solutions in the ope…