108 citations · 395 across the 21 of their papers we have counts for
7 papers · 1 filter
Autoregressive Transformers for Data-Driven Spatio-Temporal Learning of Turbulent Flows
Aakash Patil, Jonathan Viquerat, Elie Hachem
A convolutional encoder-decoder-based transformer model is proposed for autoregressively training on spatio-temporal data of turbulent flows. The prediction of future fluid flow fi…
A review on deep reinforcement learning for fluid mechanics: an update
Jonathan Viquerat, Philippe Meliga, Elie Hachem
In the past couple of years, the interest of the fluid mechanics community for deep reinforcement learning (DRL) techniques has increased at fast pace, leading to a growing bibliog…
Graph neural networks for laminar flow prediction around random 2D shapes
Junfeng Chen, Elie Hachem, Jonathan Viquerat
In the recent years, the domain of fast flow field prediction has been vastly dominated by pixel-based convolutional neural networks. Yet, the recent advent of graph convolutional…
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…
A twin-decoder structure for incompressible laminar flow reconstruction with uncertainty estimation around 2D obstacles
Junfeng Chen, Jonathan Viquerat, Frederic Heymes +1
Over the past few years, deep learning methods have proved to be of great interest for the computational fluid dynamics community, especially when used as surrogate models, either…
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…
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…