Analysis of Turbulence Models Applied to CFD Drag Simulations of a Small Hatchback Vehicle

Buscariolo, Filipe Fabian; Magazoni, Felipe; Wolf, Marc; Maruyama, Flavio; Alves, Julio Cesar Lelis; Volpe, Leonardo José Della

doi:10.4271/2016-36-0201

Cited by 19 publications

(5 citation statements)

References 8 publications

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“…Literature revealed that the selection of turbulence model alone can result in significantly different predictions in many engineering applications. 19–22 As far as the road vehicle external aerodynamic studies are concerned, the turbulence modeling effects on RANS predictions are considerably explored with simplified vehicle models, most commonly, the Ahmed body and the DrivAer model, 23–25 as well as various types of passenger vehicles; 26,27 recent studies by Fu et al 28,29 are probably the only one related to stock racecar applications. However, since the racecar’s aerodynamic features can be very different under yaw and/or pitch and these racecars are intentionally made asymmetric, observations based on straightway attitudes may not be valid.…”

Section: Introductionmentioning

confidence: 99%

Turbulence modeling effects on the aerodynamic characterizations of a NASCAR Generation 6 racecar subject to yaw and pitch changes

Chen

Bounds

Selent

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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The characterization of a racecar’s aerodynamic behavior at various yaw and pitch configurations has always been an integral part of its on-track performance evaluation in terms of lap time predictions. Although computational fluid dynamics has emerged as the ubiquitous tool in motorsports industry, a clarity is still lacking about the prediction veracity dependence on the choice of turbulence models, which is central to the prediction variability and unreliability for the Reynolds Averaged Navier–Stokes simulations, which is by far the most widely used computational fluid dynamics methodology in this industry. Subsequently, this paper presents a comprehensive assessment of three commonly used eddy viscosity turbulence models, namely, the realizable [Formula: see text] (RKE), Abe–Kondoh–Nagano [Formula: see text], and shear stress transport [Formula: see text], in predicting the aerodynamic characteristics of a full-scale NASCAR Monster Energy Cup racecar under various yaw and pitch configurations, which was never been explored before. The simulations are conducted using the steady Reynolds Averaged Navier–Stokes approach with unstructured trimmer cells. The tested yaw and pitch configurations were chosen in consultation with the race teams such that they reflect true representations of the racecar orientations during cornering, braking, and accelerating scenarios. The study reiterated that the prediction discrepancies between the turbulence models are mainly due to the differences in the predictions of flow recirculation and separation, caused by the individual model’s effectiveness in capturing the evolution of adverse pressure gradient flows, and predicting the onset of separation and subsequent reattachment (if there be any). This paper showed that the prediction discrepancies are linked to the computation of the turbulent eddy viscosity in the separated flow region, and using flow-visualizations identified the areas on the car body which are critical to this analysis. In terms of racecar aerodynamic performance parameter predictions, it can be reasonably argued that, excluding the prediction of the %Front prediction, shear stress transport is the best choice between the three tested models for stock-car type racecar Reynolds Averaged Navier–Stokes computational fluid dynamics simulations as it is the only model that predicted directionally correct changes of all aerodynamic parameters as the racecar is either yawed from the 0° to 3° or pitched from a high splitter-ground clearance to a low one. Furthermore, the magnitude of the shear stress transport predicted delta force coefficients also agreed reasonably well with test results.

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Section: Introductionmentioning

confidence: 99%

Turbulence modeling effects on the aerodynamic characterizations of a NASCAR Generation 6 racecar subject to yaw and pitch changes

Chen

Bounds

Selent

et al. 2019

Proceedings of the Institution of Mechanical Engineers, Part D:

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“…According to BUSCARIOLO, et al (2016) [2], it is a closed circuit with temperature control to perform aerodynamic studies such as directional stability and thermal comfort in passenger cars, medium size "Pick Ups", sports cars and "SUVs (Sport Utility Vehicle). Its test section has a static floor with boundary layer suction system on the floor.…”

Section: Methodsmentioning

confidence: 99%

Drag Analysis of Autonomous Vehicles in Different Arrays using CFD simulations

Buscariolo¹,

Magazoni²,

Maruyama³

et al. 2018

Blucher Engineering Proceedings

Self Cite

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Autonomous vehicles, which are defined as capable of sensing environment and navigating without any human input, are the top trend of the automotive industry. The computers responsible for the control are able to set the vehicle to optimum operation point. With the advent of Computational Fluid Dynamics-CFD software, it is possible to study drag reduction proposals when the vehicles drive at the velocity, which contributes to increase fuel economy. In this context, based on a sedan vehicle virtual drag model, several simulations cases were developed considering different vehicle arrays and changing the distance between each one. The study aims to demonstrate, using virtual simulations, the potential drag coefficient reduction when vehicles are moving in a constant speed and which configuration leads to better performance increment. Taking the isolated vehicle, as the baseline value, all the vehicles in the different arrays were analysed. Results show that the vehicles staying behind the first vehicle in the arrays have better drag coefficient performance. Considering the presented results, it is possible to apply this methodology to others types of vehicles and optimize the driving of autonomous vehicles.

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“…The Reynolds-averaged Navier-Stokes (RANS) method based on time-averaged velocity is the basic method used in turbulent calculation. 44 In this article, the realizable k -e model in the RANS method was used in the formula for calculating the turbulent viscosity coefficient of which the influencing factors of rotation and curvature were introduced to prevent distortion in simulating a strong swirl or a curved wall in standard k -e model. 45 Meanwhile, compared to the RNG k À e model, the convergence of the realizable k À e model is improved and the calculation result is more accurate.…”

Section: Control Equationsmentioning

confidence: 99%

Analysis and multi-objective optimization design of wheel based on aerodynamic performance

Wang

Zhang

et al. 2019

Advances in Mechanical Engineering

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In the past studies, the influence of wheel structure design and optimization on the aerodynamic drag of car and heat transfer performance of brake disc was less studied. To study the influence mechanism, the finite element model for wheel aerodynamic analysis was established using computational fluid dynamic method and the correctness of the model was verified by the wind tunnel test data. The influence mechanism of the flow field on aerodynamic drag of car and wheel and heat transfer performance of brake disc was studied. The influence of wheel disc structure on aerodynamic drag coefficient of the car and average convective heat transfer coefficient of the brake discs was studied. The parametric model of the wheel under the computational fluid dynamic analysis was established using mesh morphing technology. A total of 100 and 10 sample points were extracted using the Hammersley Design and Optimal Latin Hypercube Design, respectively, to fit the radial basis function surrogate model and test the accuracy of the surrogate model. Based on the established surrogate model, taking the minimum of the wheel mass, the minimum of the aerodynamic drag coefficient of the car and the maximum of the average surface convective heat transfer coefficient of brake discs as objectives and design variables of wheel as constraints to ensure the wheel structural strength, the non-dominated sorting genetic algorithm was adopted to carry out multi-objective optimization design for the wheel. Pareto frontier was obtained and a compromise solution was selected as the optimization design result. After the optimization design, the wheel mass is reduced by 8.28%, the aerodynamic drag coefficient of the car is reduced by 3.17% and the average surface convective heat transfer coefficient of brake discs is increased by 9.31%.

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Analysis of Turbulence Models Applied to CFD Drag Simulations of a Small Hatchback Vehicle

Cited by 19 publications

References 8 publications

Turbulence modeling effects on the aerodynamic characterizations of a NASCAR Generation 6 racecar subject to yaw and pitch changes

Turbulence modeling effects on the aerodynamic characterizations of a NASCAR Generation 6 racecar subject to yaw and pitch changes

Drag Analysis of Autonomous Vehicles in Different Arrays using CFD simulations

Analysis and multi-objective optimization design of wheel based on aerodynamic performance

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