196 citations · 211 across the 3 of their papers we have counts for
3 papers
Hydrogen reaction rate modeling based on convolutional neural network for large eddy simulation
Quentin Malé, Corentin J Lapeyre, Nicolas Noiray
This paper establishes a data-driven modeling framework for lean Hydrogen (H2)-air reaction rates for the Large Eddy Simulation (LES) of turbulent reactive flows. This is particula…
Reconstruction of Hydraulic Data by Machine Learning
Corentin J. Lapeyre, Nicolas Cazard, Pamphile T. Roy +2
Numerical simulation models associated with hydraulic engineering take a wide array of data into account to produce predictions: rainfall contribution to the drainage basin (charac…
Training convolutional neural networks to estimate turbulent sub-grid scale reaction rates
C. J. Lapeyre, A. Misdariis, N. Cazard +2
This work presents a new approach for premixed turbulent combustion modeling based on convolutional neural networks (CNN). We first propose a framework to reformulate the problem o…