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The primary advantage of an Adaptive Wall wind tunnel is that the test section walls and ceiling are contoured to closely approximate the ‘open road' flowfield around the test vehicle. This reproduction of the open road flowfield then results in aerodynamic forces and moments on the test vehicle that are consistent with actual open road forces and moments. Aerodynamic data measured in the adaptive wall test section do not require blockage corrections for adjusting the data to open road results. Extensive full scale experiments, published scale model studies, and Computational Fluid Dynamics (CFD) studies have verified the simulation capability of adaptive wall technology. For the CFD study described here, high-downforce, open-wheel race cars were studied. The numerical simulations with a race car in an Adaptive Wall Test Section (AWTS) wind tunnel are compared with simulations in ‘free air' condition and in a closed wall test section.

This paper summarizes the major activities of CFD study on rear window buffeting of production vehicles during the past two years at DaimlerChrysler. The focus of the paper is the attempt to find suitable solutions for buffeting suppression using a developed procedure of CFD simulation with commercial software plus FFT acoustic post-processing. The analysis procedure has been validated using three representative production vehicles and good correlation with wind tunnel tests has been attained which has gained the confidence in solving the buffeting problem. Several attempts have been proposed and tried to find solution for buffeting reduction. Some of them are promising, but feasibility and manufacturability still need discussion. In order to find suitable solution for buffeting reduction, more basic research is necessary, more ideas should be collected, and more joint efforts of CFD and testing are imperative.

This paper investigates the aerodynamic simulation accuracy of several types of wind tunnel test sections. Computational simulations were performed with a closed wheel race car in an 11.0 m2 adaptive wall, a 16.8 m2 open jet, and a 29.7 m2 slotted wall test section, corresponding to model blockage ratios of 20.9%, 13.7%, and 7.7%, respectively. These are compared to a simulation performed in a nearly interference-free condition having a blockage ratio of 0.05%, which for practical purposes of comparison, is considered a free air condition. The results demonstrate that the adaptive wall most closely simulates the free air condition without the need for interference corrections. In addition to this advantage, the significantly smaller size of the adaptive wall test section offers lower capital and operating costs.

Computational Fluid Dynamics (CFD) was applied to investigate blockage effects (or velocity correction) in a climatic wind tunnel (CWT) test environment. Different blockage effects in the CWT were modeled using four simplified vehicles that approximated a sedan, an SUV, a pickup truck, and a minivan. Blockage dependence on nozzle size and spacing between the nozzle exit plane (NEP) and the vehicle were also investigated. The study quantified the blockage effect using different correction methods based on vehicle frontal velocity profiles and upper surface pressure traces. The blockage-free solution was also simulated for each vehicle in an ‘open road’ or free air condition. The CFD study revealed that all the test cases resulted in blockage correction factors, defined by Vactual/Vsimulated greater than 1.0. This is a condition in which the uncorrected wind tunnel velocity was higher than the ‘open road’ condition.

Wind Tunnel 8 of the Driveability Test Facility (DTF), which achieved full operational status in 2001, is designed to provide full powertrain, aerodynamic, and aero-acoustic test capabilities for automotive product development. In order for it to be fully integrated into product testing, the Ford product engineering community needed to correlate the facility. The major objective of the correlation is quantitative aerodynamic correlation, which will be achieved when aerodynamic coefficients measured in Wind Tunnel 8 can be understood in the context of aerodynamic measurements obtained in other wind tunnels that Ford has used for product testing. The motivation for this study is the aerodynamic interference that is present in all wind tunnels. Aerodynamic interference is the deviation between the true result—which is difficult to determine—and the actual result obtained from the wind tunnel.

Experimental and computational simulation techniques were concurrently employed throughout the aerodynamic development of the NASCAR Dodge Intrepid R/T in order to achieve a greater understanding of the complex flow fields involved. With less than 500 days to design, understand, and build a competitive vehicle, the development team utilized a closed loop approach to testing. Scale wind tunnel models and Computational Fluid Dynamics (CFD) were used to identify program direction and to speed the development cycle versus the traditional process of full scale testing. This paper will detail the process and application of both the experimental and computational techniques used in the aerodynamic development of the Intrepid R/T race vehicle, primarily focusing on the earlier stages that led to its competition introduction at the start of the 2001 season.

Since being commissioned in 2001, the aero-acoustic wind tunnel at DTF, Wind Tunnel 8 (WT8) has been used to conduct a wide variety of tests. In 2003 alone, over 5250 hours of aerodynamic and aero-acoustic testing were run on over 2000 test articles, including commercial cars, trucks and racing vehicles. Additionally, more unique test articles such as solar cars, motorcycles, Olympic sleds, and others have also been recently tested. The demand for WT8 is driven by the fact that it is among the quietest wind tunnels in the world and one of a very small number of facilities that combines aerodynamic, aero-acoustic, and climatic capabilities in one facility. To enhance WT8's ability to meet the ever-increasing demands of the testing community, and the Motorsports community specifically, an effort was recently initiated to optimize and document the repeatability of aerodynamic force measurements in this tunnel.

Buffeting is a wind noise of high intensity and low frequency in a moving vehicle when a window or sunroof is open and this noise makes people in the passenger compartment very uncomfortable. In this paper, side window buffeting was simulated for a typical SUV using the commercial CFD software Fluent 6.0. Buffeting frequency and intensity were predicted in the simulations and compared with the corresponding experimental wind tunnel measurement. Furthermore, the effects of several parameters on buffeting frequency and intensity were also studied. These parameters include vehicle speed, yaw angle, sensor location and volume of the passenger compartment. Various configurations of side window opening were considered. The effects of mesh size and air compressibility on buffeting were also evaluated. The simulation results for some baseline configurations match the corresponding experimental data fairly well.

This paper provides an overview of the design and commissioning results for the DaimlerChrysler full-scale vehicle Aeroacoustic Wind Tunnel (AAWT) brought online in 2002. This wind tunnel represents the culmination of the plan for aeroacoustic facilities at the DaimlerChrysler Corporation Technical Center (DCTC) in Auburn Hills, Michigan. The competing requirements of excellent flow quality, low background noise, and constructed cost within budget were optimized using Computational Fluid Dynamics, extensive acoustic modeling, and a variety of scale-model experimental results, including dedicated experiments carried out in the 3/8-scale pilot wind tunnel located at DCTC. The paper describes the project history, user requirements, and design philosophy employed in realizing the facility. The AAWT meets all of DaimlerChrylser's performance targets, and was delivered on schedule. The commissioning results presented in this paper show its performance to be among the best in the world.

Recently, computational fluid dynamics (CFD) was applied to investigate blockage (or velocity) corrections using the nozzle method for a climatic wind tunnel (CWT) test environment (SAE 2003-01-0936). The study included two blockage corrections to the nozzle method reference velocity: vehicle frontal velocity and vehicle upper surface pressure trace. These methods resulted in well correlated predictions between the open road and CWT flow conditions. These CFD predicted blockage corrections are experimentally verified in a climatic wind tunnel in this study. A non-intrusive method applying particle image velocimetry is applied to acquire the velocity field in front of the test vehicle. The experimental data verifies the blockage correction predictions derived from the previous CFD work.

The importance of the automotive test facility has increased significantly due in large part to continuous pressure on manufactures to shorten product development cycles. Test facilities are no longer used only for regulatory testing, or development testing in which the effects of small design changes (A-to-B testing) are determined; automotive manufacturers are beginning to use these facilities for final design validation, which has traditionally required on road testing. A host of resources have gone into the design and construction of facilities with the capability to simulate nearly any environment of practical importance to the automotive industry. As a result, there are now a number of test facilities, and specifically wind tunnels, in which engineers can test most aspects of a vehicle's performance in real-world environments.

This paper presents an uncertainty analysis of aerodynamic force and moment coefficients for production vehicles in an automotive wind tunnel. The analysis uses a Monte Carlo numerical simulation technique. Emphasis is placed on defining the elemental random and systematic uncertainties from the tunnel’s instrumentation, understanding how they propagate through the data reduction equations and under what conditions specific elemental error sources are or are not important, and how the approach to data reduction influences the overall uncertainties in the coefficients. The results of the analysis are used to address the issue of averaging time in the context of maintaining a maximum allowable uncertainty level. Also, a maximum error requirement in the vehicle’s installation is suggested to allow the use of rapid but approximate vehicle alignment methods without incurring errors that exceed the data uncertainty. Observed reproducibility results are presented spanning a 16 month period.