Symbolic regression of algebraic stress-strain relation for RANS turbulence closure

Conference Paper (2020)
Author(s)

Martin Schmelzer (TU Delft - Aerodynamics)

Richard P. Dwight (TU Delft - Aerodynamics)

Paola Cinnella (151 Boulevard de l'Hospital)

Research Group
Aerodynamics
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Publication Year
2020
Language
English
Research Group
Aerodynamics
Pages (from-to)
1789-1795
ISBN (electronic)
9788494731167
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Abstract

In this work recent advancements are presented in utilising deterministic symbolic regression to infer algebraic models for turbulent stress-strain relation with sparsity-promoting regression techniques. The goal is to build a functional expression from a set of candidate functions in order to represent the target data most accurately. Targets are the coefficients of a polynomial tensor basis, which are identified from high-fidelity data using regularised least-square regression. The method successfully identified a correction term for the benchmark test case of flow over periodic hills in 2D at Reh = 10595.

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