Turbulence Modeling Effects on the CFD Predictions of Flow over a Detailed Full-Scale Sedan Vehicle

Chunhui Zhang,Mesbah Uddin,Charles Patrick Bounds,Lee Foster

doi:10.3390/fluids4030148

Abstract

In today’s road vehicle design processes, Computational Fluid Dynamics (CFD) has emerged as one of the major investigative tools for aerodynamics analyses. The age-old CFD methodology based on the Reynolds Averaged Navier–Stokes (RANS) approach is still considered as the most popular turbulence modeling approach in automotive industries due to its acceptable accuracy and affordable computational cost for predicting flows involving complex geometries. This popular use of RANS still persists in spite of the well-known fact that, for automotive flows, RANS turbulence models often fail to characterize the associated flow-field properly. It is even true that more often, the RANS approach fails to predict correct integral aerodynamic quantities like lift, drag, or moment coefficients, and as such, they are used to assess the relative magnitude and direction of a trend. Moreover, even for such purposes, notable disagreements generally exist between results predicted by different RANS models. Thanks to fast advances in computer technology, increasing popularity has been seen in the use of the hybrid Detached Eddy Simulation (DES), which blends the RANS approach with Large Eddy Simulation (LES). The DES methodology demonstrated a high potential of being more accurate and informative than the RANS approaches. Whilst evaluations of RANS and DES models on various applications are abundant in the literature, such evaluations on full-car models are relatively fewer. In this study, four RANS models that are widely used in engineering applications, i.e., the realizable k − ε two-layer, Abe–Kondoh–Nagano (AKN) k − ε low-Reynolds, SST k − ω , and V2F are evaluated on a full-scale passenger vehicle with two different front-end configurations. In addition, both cases are run with two DES models to assess the differences between the flow predictions obtained using RANS and DES.

Highlights

Since the last twenty years, Computational Fluid Dynamics (CFD) has played an important role in the early design stages of modern-day vehicles
The goal of the current study is to provide an evaluation of several Reynolds-Averaged Navier–Stokes (RANS) and Detached Eddy Simulation (DES)
In order to have a comprehensive understanding of the predictive differences between the six models, the proceeding discussions will cover analyses of force coefficients, velocity, pressure field, wake structures, and some other flow fields that are crucial to the flow features

Summary

Introduction

Since the last twenty years, Computational Fluid Dynamics (CFD) has played an important role in the early design stages of modern-day vehicles. In present day high-fidelity CFD analyses, simulations with 120 million cells are very common; even a RANS-based well-converged simulation of this size takes more 3000 core-hours for completion (see [4]), implying that a DES would have taken more than 50,000 core-hours for a single case. This makes the use DES analysis impractical for motorsports applications for sure and may be for the passenger vehicle industries as well. RANS approaches still remain a popular method in situations like the early design cycle of a new vehicle model where hundreds of design options need to be assessed

Objectives

Results

Conclusion