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Effects of collector shape on the performance of an automotive wind tunnel are experimentally investigated in a 1:15 model wind tunnel. A few types of collectors, each with different collector shape, were tested. For each collector shape, pressure pulsation level, total sound pressure level, pressure distribution, maximum wind tunnel speed and pressure loss were measured. From these measured data, the effects of collector on the pressure loss, static pressure gradient at the test section, and on the performance of low frequency buffeting were deduced. Based on these data, a preferred collector is suggested.

A computational study was conducted in order to characterize the heat transfers in a sedan vehicle underbody and the exhaust system. A steady-state analysis with consideration for both the radiation and conjugate heat transfers was undertaken using the High-Reynolds formulation of the k-epsilon turbulence model with standard wall function and the DO model for the radiation heat transfer. All three mechanisms of heat transfer, i.e., convection, conduction, and radiation, were included in the analysis. The convective heat transfer due to turbulent fluid motion was modeled with the assumption of constant turbulent Prandtl number; and heat conduction was solved directly for both fluid and solid.

The detailed design process of the diffuser for a Formula one racer is described. It begins with the study of overall aerodynamic performance and follows the basic function of the diffuser. And then forms the strategy for such a diffuser which should perform the maximum downforce. Then is the detailed analysis of diffuser by two different methods of development. The small-scaled wind tunnel data is presented, together with the CFD analysis, describing the major consideration in using these two developing methods and demonstrating the major influence for the diffuser design.

Effects of the wind tunnel blockage in a closed-wall wind tunnel were investigated using computational fluid dynamics (CFD). Flow over three generic vehicle models representing a passenger sedan, a sports utility vehicle (SUV), and a pickup truck was solved. The models were placed in a baseline virtual wind tunnel as well as four additional virtual wind tunnels, each with different size cross-sections, providing different levels of wind tunnel blockage. For each vehicle model, the CFD analysis produced an aerodynamic drag coefficient for the vehicle at the blockage free condition as well as the blockage effect increment for the baseline wind tunnel. A CFD based blockage correction method is proposed. Comparisons of this method to some existing blockage correction methods for closed-wall wind tunnel are also presented.

Effects of the pressure gradient in the wind tunnel test section on vehicle aerodynamic drag were investigated using computational fluid dynamics (CFD). The numerical study was used to obtain the aerodynamic drag of several vehicles in two virtual wind tunnels, one with a zero pressure gradient and another with a nonzero (but small) pressure gradient. A comparison of the vehicle aerodynamic drags in these two virtual wind tunnels, and investigation of the physical mechanisms causing these differences, have led to two correction formulas. These formulas can be used to correct for the pressure gradient effect on vehicle aerodynamic drag measurement in a wind tunnel that has a nonzero pressure gradient. In the first formula, the correction is given explicitly in terms of known variables. The correction is 80% accurate for passenger car, sports car, sports utility vehicle (SUV), and is 70% accurate for pickup truck.

Beamforming techniques are widely used today in aeroacoustic wind tunnels to identify wind noise sources generated by interaction between incoming flow and the test object. In this study, a planar spiral microphone array with 120 channels was set out-of-flow at 1:1 aeroacoustic wind tunnel of Shanghai Automotive Wind Tunnel Center (SAWTC) to test exterior wind noise sources of a production car. Simultaneously, 2 reference microphones were set in vehicle interior to record potential sound source signal near the left side view mirror triangle and the signal of driver’s ear position synchronously. In addition, a spherical array with 48 channels was set inside the vehicle to identify interior noise sources synchronously as well. With different correlation methods and an advanced algorithm CLEAN-SC, the ranking of contributions of vehicle exterior wind noise sources to interested interior noise locations was accomplished.

By means of particle image velocimetry(PIV) measurements, this paper uses vortex identification algorithms to find and analyze the coherent structures in the shear layer region of a 1:15 scaled 3/4 open jet automotive wind tunnel with a high Reynolds number(about 106), referring to SAWTC’s AAWT. The proper orthogonal decomposition(POD) is used to process the PIV experimental data to reconstruct the velocity fields. Based on the vortex identification functions, the locations of the center, the rotation direction and the radius of vortex can be computed. Furthermore, this paper uses the statistical method to study the regularities of distribution of these vortexes in a two-dimensional plane, and identify the vortex pairing process in the shear layer region. This paper also chooses different vortex identification algorithms to find the most accurate and suitable algorithms.

The computational fluid dynamics (CFD) based wind tunnel blockage correction method proposed in [1] was extended in the present study to production vehicles with detailed underhood and underbody components, fascia and grills. Three different types of vehicles (sedan, SUV, and pickup truck) were considered in the study. While the previous CFD based wind tunnel blockage correction method was for vehicle aerodynamic drag, the blockage effect on vehicle cooling airflow is also included in the present study, and a CFD based blockage correction method for vehicle cooling airflow is proposed. Comparisons were made between the blockage effects for the production vehicles and the blockage effects for the generic vehicles.

The effect of jet geometry on flow, heat transfer and defrosting characteristics was numerically investigated for elliptic and rectangular impinging jets on an automobile windshield. Initially, various turbulence models within the commercial computational fluid dynamics (CFD) package FLUENT were employed and validated for a single jet, and the results indicated that the impinging jet heat transfer was more accurately predicted by the SST k -ω turbulence model, which was then utilized for this study. The aspect ratios (AR) of elliptic and rectangular jets were respectively 0.5, 1.0, and 2.0, with jet-to-target spacing h/d=2, 4 and jet-to-jet spacing c/d=4, and all those situations were numerically analyzed with the same air mass flow and jet open area. It was observed that the heat transfer coefficient and defrosting performance of the inclined windshield were significantly affected by the shape of the jet, and the best results were obtained with the elliptic jet arrangements.

Based on a 1:15 scaled 3/4 open jet automotive wind tunnel, this paper studies the effect of vortex generator on the buffeting phenomenon. The mean velocity, static pressure gradient, turbulent intensity as well as frequencies of fluctuant velocities have been explored experimentally with and without vortex generator. It shows that the less protruding vortex generator could control the buffeting phenomenon and improve the flow quality. Furthermore, the unsteady coherent structures in the jet shear layer have been visualized and analyzed by Detached-eddy simulation (DES). The vortex-ring pairing process is identified in the shear layer along with obvious frequency characteristics and velocity fluctuations. The vortex generator can postpone and restrain this vortex-ring pairing process, then reducing the velocity fluctuations.

External rear view mirror is attached at the side of the vehicle which is to permit clear vision for the driver to the rear of the vehicle. When the vehicle is running, the flow field around external rear view mirror is highly three-dimensional, unsteady, separated and turbulent which is known to be a significant source of aerodynamic noise and a contributor to the total drag force on the vehicle. While among all the researches on the flow field around external rear view mirror, different installation environment were employed. The external rear view mirror is mounted on a production car in most researches which presents the real condition and it can also be mounted on the ground of a wind tunnel, a specially designed table, or a generic vehicle model based on the SAE model. While, the relationship between the flow field around external rear view mirror and the installation environment is not very clear.

In the field of vehicle aerodynamic simulation, Reynold Averaged Navier-Stokes (RANS) model is widely used due to its high efficiency. However, it has some limitations in capturing complex flow features and simulating large separated flows. In order to improve the computational accuracy within a suitable cost, the Field Inversion and Machine Learning (FIML) method, based on a data-driven approach, has received increasing attention in recent years. In this paper, the optimal coefficients of the Generalized k-ω (GEKO) model are firstly obtained by the discrete adjoint method of FIML, utilizing the results of wind tunnel experiments. Then, the mapping relationship between the flow field characteristics and the optimal coefficients is established by a neural network to augment the turbulence model.