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pro vyhledávání: '"Heymes, Fréderic"'
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 for flow reconstruction, turbulence modeling, or for the prediction of
Externí odkaz:
http://arxiv.org/abs/2104.03619
Publikováno v:
In Journal of Loss Prevention in the Process Industries April 2025 94
Autor:
Vacca, Pascale, Planas, Eulàlia, Mata, Christian, Muñoz, Juan Antonio, Heymes, Frederic, Pastor, Elsa
Publikováno v:
In Safety Science February 2022 146
Publikováno v:
In Optical Materials December 2021 122 Part B
Publikováno v:
In Process Safety and Environmental Protection September 2020 141:49-60
Publikováno v:
In Process Safety and Environmental Protection February 2018 114:251-270
Autor:
Lauret, Pierre, Heymes, Frederic, Forestier, Serge, Aprin, Laurent, Pey, Alexis, Perrin, Marcia
Publikováno v:
In Process Safety and Environmental Protection August 2017 110:71-76
Publikováno v:
In Environmental Modelling and Software November 2016 85:56-69
Publikováno v:
In Analysis of Flame Retardancy in Polymer Science 2022:333-379
Autor:
Lecysyn, Nicolas, Dandrieux, Aurélia, Heymes, Frédéric, Aprin, Laurent, Slangen, Pierre, Munier, Laurent, Le Gallic, Christian, Dusserre, Gilles
Publikováno v:
In Journal of Hazardous Materials 2009 172(2):587-594