36 citations · 59 across the 9 of their papers we have counts for
6 papers
Robust deep learning for emulating turbulent viscosities
Aakash Patil, Jonathan Viquerat, George El Haber +1
From the simplest models to complex deep neural networks, modeling turbulence with machine learning techniques still offers multiple challenges. In this context, the present contri…
Folding instabilities in non-Newtonian viscous sheets: shear thinning and shear thickening effects
Anselmo Pereira, Nicolas Valade, Elie Hachem +1
In this work, we extend the analyses devoted to Newtonian viscous fluids previously reported by Ribe [Physical Review E 68, 036305 (2003)], by investigating shear thickening (dilat…
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…
Analysis and comparisons of various models in cold spray simulations : towards high fidelity simulations
Louis-Vincent Bouthier, Elie Hachem
Cold spray technology is a quickly growing manufacturing technology which impacts lots of industries. Despite many years of studies about the comprehension of the phenomena and the…
U-net architectures for fast prediction of incompressible laminar flows
Junfeng Chen, Jonathan Viquerat, Elie Hachem
Machine learning is a popular tool that is being applied to many domains, from computer vision to natural language processing. It is not long ago that its use was extended to physi…
Exploiting locality and physical invariants to design effective Deep Reinforcement Learning control of the unstable falling liquid film
Vincent Belus, Jean Rabault, Jonathan Viquerat +3
Instabilities arise in a number of flow configurations. One such manifestation is the development of interfacial waves in multiphase flows, such as those observed in the falling li…