Prediction of Separation Induced Transition on Thick Airfoil Using Nonlinear URANS Based Turbulence Model

TL;DR

This study evaluates nonlinear turbulence models for predicting laminar separation bubbles on a thick airfoil, demonstrating improved accuracy over linear models in capturing flow separation and transition phenomena.

Contribution

It introduces and assesses the effectiveness of nonlinear k- SST and transition models in accurately predicting flow separation and transition on a thick airfoil, outperforming traditional linear models.

Findings

Nonlinear models accurately predict laminar separation bubble location.

Nonlinear models provide better lift and drag predictions compared to linear models.

Linear models underpredict drag at low angles of attack.

Abstract

Most of the turbulence models in practice are based on the assumption of a linear relation between Reynolds stresses and mean flow strain rates which generally provides a good approximation in case of attached and fully turbulent flows. A two dimensional numerical study has been carried out over NACA 0021 with k-\omega SST model with non-linear correction at Re = 120,000 for various angles of attack which experiences the formation of a laminar separation bubble (LSB). A correct prediction of LSB requires an accurate resolution of anisotropy in Reynolds stresses. For comparison with other linear models, the simulations are also performed with k-kl-\omega, k-\omega SST and Spalart Allmaras. The performance of these models is assessed through aerodynamic lift, drag, pressure and friction coefficients. It is found that the non-linear k-\omega SST and k-kl-\omega transition model provide comparable quality of prediction in lift and drag coefficients (in spite of the fact that non-linear k-\omega SST involves solving less number of transport equation than the transition model) as observed in the experiments whereas k-\omega SST and SA models under predict the drag coefficient value at low angle of attack due to inability to capture the separation induced transition. It is also observed that the location of laminar separation bubble is captured accurately when nonlinear or transition model is used as opposed to the SA or linear SST models, which lack in the ability to predict the same.