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The Windshear Rolling Road Wind Tunnel in Concord, North Carolina, is a full-scale commercial wind tunnel conceived primarily as a facility to serve the various motorsports communities, although it has already expanded beyond that base into production car and truck testing. The wind tunnel is a 3/4-open-jet, closed-return design with a 16.7 m₂ nozzle, a wide-belt moving ground plane, and a top speed of 80 m/s (180 mph). This paper describes the project history and design philosophy of the wind tunnel, commissioning results, and an overview of the force measurement methods on the wide-belt rolling road. Some results of a recently completed correlation program are presented, along with performance validation results that include repeatability and reproducibility as well as an assessment of boundary corrections.

In recent years, there has been renewed attention focused on open jet correction methods, in particular on the two-measurement method of E. Mercker, K. Cooper, and co-workers. This method accounts for blockage and static pressure gradient effects in automotive wind tunnels and has been shown by both computations and experiments to appropriately adjust drag coefficients towards an on-road condition, thus allowing results from different wind tunnels to be compared on a more equitable basis. However, most wind tunnels have yet to adopt the method as standard practice due to difficulties in practical application. In particular, it is necessary to measure the aerodynamic forces on every vehicle configuration in two different static pressure gradients to capture that portion of the correction. Building on earlier proof-of-concept work, this paper demonstrates a practical method for implementing the two-measurement procedure and demonstrates how it can be used for production testing.

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.

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.

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.

This paper describes the new Honda R&D Americas Scale Model Wind Tunnel (SWT). To help address Honda's ongoing need to improve fuel economy, reduce the driving force of a vehicle, and decrease product development time, the wind tunnel was developed and implemented to achieve high accuracy aerodynamic predictions for product development and a significantly improved capability for vehicle aerodynamics research. The SWT can accommodate model scales up to 50%. The ¾-open jet test section has a top speed of 250 km/h, a 5-belt moving ground plane with a long center belt for proper wake simulation, a test section designed specifically for very low static pressure gradient, three separate dynamic pressure measurement systems for state-of-the-art blockage corrections, and an overhead traverse for specialized measurement activities. This paper describes the decision process that led to the SWT, key commissioning results, and performance validation results with models installed.

The Honda Automotive Laboratories of Ohio (HALO) includes a new aeroacoustic wind tunnel located near Marysville, Ohio that started operations in 2022. This facility provides world-class aerodynamic flow quality and acoustic testing capabilities for the development of both passenger and motorsports vehicles. This closed-return ¾ open jet wind tunnel features a two-position flexible nozzle system with cross sections of 25 m2 and 18 m2, providing wind speeds of up to 250 km/h and 310 km/h, respectively. There is a ±180 degree turntable with boundary layer control systems, and interchangeable single belt and 5-belt moving ground plane (MGP) modules. Extensive applications of acoustic treatment in the test section and throughout the wind tunnel circuit provide a hemi-anechoic test environment and low background noise levels. A temperature control system provides uniform and stable air temperature over an operating environment between 10 °C and 50 °C.

The Ford Motor Company Rolling Road Wind Tunnel (RRWT) is a state-of-the-art aerodynamic wind tunnel test facility in Allen Park, Michigan. The RRWT has operated since January 2022 and is designed for passenger and motorsport vehicle development. The test facility includes an office area, three secure customer vehicle preparation bays, a garage area, a vehicle frontal area measurement system, and a full-scale ¾ open jet wind tunnel. The wind tunnel features an interchangeable single belt and 5-belt Moving Ground Plane (MGP) system with an integrated 6-component balance, a two-position nozzle, boundary layer removal systems, and two independent flow traverse systems. Each flow traverse has a large horizontal box beam and vertical Z-strut that can position the flow traverse accurately within the test volume.

This paper presents the application of statistical process control (SPC) methods to Windshear, a 180-mph motorsports and automotive wind tunnel equipped with a wide-belt rolling road system. The SPC approach captures the complete variability of the facility and offers useful process performance metrics that are based on a sound statistical framework. Traditional control charts are explored, emphasizing the uniqueness of variability experienced in wind tunnels which includes significant, unexplained short-term and long-term variation compared to typical manufacturing processes. This unique variation is elegantly captured by the three-way control chart, which is applied to estimate the complete process reproducibility with different levels of repeatability of vehicle drag coefficient. The sensitivity of three-way control charts is explored including the evaluation of an alternate group assignment within the same dataset.