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Published in:
Analysis of Flame Topology and Burning Rates Read chapter Read first chapter

2020 | OriginalPaper | Chapter

13. Application of an Evolutionary Algorithm to LES Modelling of Turbulent Premixed Flames

Authors : M. Schöpplein, J. Weatheritt, M. Talei, M. Klein, R. D. Sandberg

Published in: Data Analysis for Direct Numerical Simulations of Turbulent Combustion

Publisher: Springer International Publishing

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Abstract

Gene Expression Programming (GEP) has been used successfully for modelling the unclosed terms in the context of Reynolds Averaged Navier–Stokes (RANS) and Large Eddy Simulation (LES)-based turbulence modelling. In contrast to deep-learning-based methodologies, this approach has the advantage that the model can be documented in the form of a mathematical expression; it can be interpreted and easily implemented in existing solvers. Recently, application of GEP to a priori LES modelling has demonstrated the efficiency of the approach to find high fidelity LES closures. The present contribution explains the methodology, reviews recent work in the field and focuses on the robustness of the method and the scope for future efficiency improvements, by applying it to the modelling of the unclosed stress tensor in turbulent premixed statistically planar flames.

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previous chapter Analysis of Turbulent Reacting Jets via Principal Component Analysis
next chapter Machine Learning of Combustion LES Models from Reacting Direct Numerical Simulation
Footnotes
1
The indices are omitted for better readability.
 
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Metadata
Title
Application of an Evolutionary Algorithm to LES Modelling of Turbulent Premixed Flames
Authors
M. Schöpplein
J. Weatheritt
M. Talei
M. Klein
R. D. Sandberg
Copyright Year
2020
Book
Data Analysis for Direct Numerical Simulations of Turbulent Combustion

Print ISBN: 978-3-030-44717-5

Electronic ISBN: 978-3-030-44718-2

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-44718-2_13

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