49 citations · 54 across the 5 of their papers we have counts for
3 papers · 1 filter
Improved Surrogate Modeling using Machine Learning for Industrial Civil Aircraft Aerodynamics
Romain Dupuis, Jean-Christophe Jouhaud, Pierre Sagaut
Predicting and simulating aerodynamic fields for civil aircraft over wide flight envelopes represent a real challenge mainly due to significant numerical costs and complex flows. S…
Surrogate Modeling of Aerodynamic Simulations for Multiple Operating Conditions Using Machine Learning
Romain Dupuis, Jean-Christophe Jouhaud, Pierre Sagaut
This article presents an original methodology for the prediction of steady turbulent aerodynamic fields. Due to the important computational cost of high-fidelity aerodynamic simula…
Resampling Strategies to Improve Surrogate Model-based Uncertainty Quantification - Application to LES of LS89
Pamphile Tupui Roy, Luis Miguel Segui, Jean-Christophe Jouhaud +1
Uncertainty Quantification (UQ) is receiving more and more attention for engineering applications in particular from robust optimization. Indeed, running a computer experiment only…