106 citations · 202 across the 13 of their papers we have counts for
5 papers · 1 filter
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…
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…
Stabilized finite element method for incompressible solid dynamics using an updated Lagrangian formulation
R. Nemer, A. Larcher, T. Coupez +1
This paper proposes a novel way to solve transient linear, and non-linear solid dynamics for compressible, nearly incompressible, and incompressible material in the updated Lagrang…