An Arbitrary Hybrid Turbulence Modeling Approach for Efficient and Accurate Automotive Aerodynamic Analysis and Design Optimization

The demand in solving complex turbulent fluid flows has been growing rapidly in the automotive industry for the last decade as engineers strive to design better vehicles to improve drag coefficients, noise levels and drivability. This paper presents the implementation of an arbitrary hybrid turbulence modeling (AHTM) approach in OpenFOAM for the efficient simulation of common automotive aerodynamics with unsteady turbulent separated flows such as the Kelvin–Helmholtz effect, which can also be used as an efficient part of aerodynamic design optimization (ADO) tools. This AHTM approach is based on the concept of Very Large Eddy Simulation (VLES), which can arbitrarily combine RANS, URANS, LES and DNS turbulence models in a single flow field depending on the local mesh refinement. As a result, the design engineer can take advantage of this unique and highly flexible approach to tailor his grid according to his design and resolution requirements in different areas of the flow field over the car body without sacrificing accuracy and efficiency at the same time. This paper presents the details of the implementation and careful validation of the AHTM method using the standard benchmark case of the Ahmed body, in comparison with some other existing models, such as RANS, URANS, DES and LES, which shows VLES to be the most accurate among the five examined. Furthermore, the results of this study demonstrate that the AHTM approach has the flexibility, efficiency and accuracy to be integrated with ADO tools for engineering design in the automotive industry. The approach can also be used for the detailed study of highly complex turbulent phenomena such as the Kelvin–Helmholtz instability commonly found in automotive aerodynamics. Currently, the AHTM implementation is being integrated with the DAFoam for gradient-based multi-point ADO using an efficient adjoint solver based on a Sparse Nonlinear optimizer (SNOPT).

Aerodynamic research of a racing car based on wind tunnel test and computational fluid dynamics

Wind tunnel test and computational fluid dynamics (CFD) simulation are two main methods for the study of automotive aerodynamics. CFD simulation software solves the results in calculation by using the basic theory of aerodynamic. Calculation will inevitably lead to bias, and the wind tunnel test can effectively simulate the real driving condition, which is the most effective aerodynamics research method. This paper researches the aerodynamic characteristics of the wing of a racing car. Aerodynamic model of a racing car is established. Wind tunnel test is carried out and compared with the simulation results of computational fluid dynamics. The deviation of the two methods is small, and the accuracy of computational fluid dynamics simulation is verified. By means of CFD software simulation, the coefficients of six aerodynamic forces are fitted and the aerodynamic equations are obtained. Finally, the aerodynamic forces and torques of the racing car travel in bend are calculated.

High-order detached-eddy simulation of external aerodynamics over an SAE notchback model

ABSTRACTThis research explores the modification and implementation of a Detached-Eddy Simulation (DES) in a high-order compressible solver and its application to automotive aerodynamics. This was conducted on a 20° SAE Reference Notchback Model with a Reynolds number of 2.23 × 105. This DES algorithm implemented within FLAMENCO, which is finite-volume research code operating over multi-block meshes, was used for all the simulations. The primary objectives were to capture unsteady flow features, separated coherent structures and also relax the meshing requirements to improve accessibility to turbulence-resolving methods for realistic configurations. This also aims to better understand the separated flow physics, especially around the base surfaces of the car. Simulations for three mesh refinement levels were compared to wind-tunnel measurements. Even on relatively coarse meshes (~7 m cells) for DES, time-averaged Cp was obtained with maximum errors of <8%.