196 citations · 207 across the 2 of their papers we have counts for
2 papers
cs.CE2019★ 11 cited
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…
physics.flu-dyn2018★ 196 cited
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…