Use of Symbolic Regression for construction of Reynolds-stress damping functions for Hybrid RANS/LES

2015 ◽  
Author(s):  
Jack Weatheritt ◽  
Richard D. Sandberg
Keyword(s):  
Reynolds Stress ◽  
Symbolic Regression ◽  
Damping Functions

scholarly journals Data-driven turbulence modelling using symbolic regression

2021 ◽  
Vol 2099 (1) ◽  
pp. 012020
Author(s):  
A Chakrabarty ◽  
S N Yakovenko
Keyword(s):  
Machine Learning ◽  
Turbulent Flows ◽  
Reynolds Stress ◽  
Learning Algorithm ◽  
Gene Expression Programming ◽  
Turbulent Channel Flow ◽  
Symbolic Regression ◽  
Test Case ◽  
Data Set ◽  
Anisotropy Tensor

Abstract The study is focused on the performance of machine-learning methods applied to improve the velocity field predictions in canonical turbulent flows by the Reynolds-averaged Navier–Stokes (RANS) equation models. A key issue here is to approximate the unknown term of the Reynolds stress (RS) tensor needed to close the RANS equations. A turbulent channel flow with the curved backward-facing step on the bottom has the high-fidelity LES data set. It is chosen as the test case to examine possibilities of GEP (gene expression programming) of formulating the enhanced RANS approximations. Such a symbolic regression technique allows us to get the new explicit expressions for the RS anisotropy tensor. Results obtained by the new model produced using GEP are compared with those from the LES data (serving as the target benchmark solution during the machine-learning algorithm training) and from the conventional RANS model with the linear gradient Boussinesq hypothesis for the Reynolds stress tensor.

Prediction of strongly curved turbulent duct flows with Reynolds stress model

AIAA Journal ◽  
1997 ◽  
Vol 35 ◽  
pp. 91-98
Author(s):  
Jiang Luo ◽  
Budugur Lakshminarayana
Keyword(s):  
Reynolds Stress ◽  
Reynolds Stress Model ◽  
Stress Model

Reynolds-stress-transport modeling for compressible aerodynamics applications

AIAA Journal ◽  
1999 ◽  
Vol 37 ◽  
pp. 785-797 ◽  
Author(s):  
P. Batten ◽  
T. J. Craft ◽  
M. A. Leschziner ◽  
H. Loyau
Keyword(s):  
Reynolds Stress ◽  
Transport Modeling

scholarly journals Application of Symbolic Regression for Constitutive Modeling of Plastic Deformation

2021 ◽  
pp. 100052
Author(s):  
Evgeniya Kabliman ◽  
Ana Helena Kolody ◽  
Johannes Kronsteiner ◽  
Michael Kommenda ◽  
Gabriel Kronberger
Keyword(s):  
Plastic Deformation ◽  
Constitutive Modeling ◽  
Symbolic Regression
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