Open AccessModeling subgrid-scale scalar dissipation rate in turbulent premixed flames using gene expression programming and deep artificial neural networks
Author(s) -
Christian Kasten,
Junsu Shin,
Richard D. Sandberg,
Michael Pfitzner,
Nilanjan Chakraborty,
Markus Klein
Publication year - 2022
Publication title -
physics of fluids
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.188
H-Index - 180
eISSN - 1089-7666
pISSN - 1070-6631
DOI - 10.1063/5.0095886
Subject(s) - gene expression programming , artificial neural network , turbulence , scalar (mathematics) , physics , benchmark (surveying) , population , artificial intelligence , dissipation , mathematics , machine learning , computer science , mechanics , geometry , demography , geodesy , sociology , geography , thermodynamics
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