Abstract
As the automotive industry strives to increase the amount of digital engineering in the product development process, cut costs and improve time to market, the need for high quality validation data has become a pressing requirement. While there is a substantial body of experimental work published in the literature, it is rarely accompanied by access to the data and a sufficient description of the test conditions for a high quality validation study. This paper addresses this by reporting on a comprehensive series of measurements for a 25% scale model of the DrivAer automotive test case. The paper reports on the measurement of the forces and moments, pressures and off body PIV measurements for three rear end body configurations, and summarises and compares the results. A detailed description of the test conditions and wind tunnel set up are included along with access to the full data set.
Highlights
The use of virtual methods in the Automotive sector to design, develop and validate vehicles has increased rapidly over the past two decades. This has been important in vehicle aerodynamics where the use of Computational Fluid Dynamics (CFD) has almost completely replaced experimental approaches in the early design phases for manufacturers
At the time of writing the dataset had been downloaded over 1400 times, demonstrating the urgent need for such data, and a number of authors [2,3,4,5] have reported using it for validating CFD methodology
Fluids 2020, 5, 236 data, arising for example, from differences between experiments in the Particle Image velocimetry (PIV) processing approaches or model set up; but, the success of the data set illuminates the need for much more experimental validation data. In response to this demand, this paper reports on a new purpose built dataset [6] using three configurations of a 25% scale DrivAer model
Summary
The use of virtual methods in the Automotive sector to design, develop and validate vehicles has increased rapidly over the past two decades This has been important in vehicle aerodynamics where the use of Computational Fluid Dynamics (CFD) has almost completely replaced experimental approaches in the early design phases for manufacturers. The Wood et al [1] dataset was collated from data generated by three researchers, in three different studies, over a number of years rather than being purpose designed for publication as a dataset from the outset. This resulted in some limitations in the Fluids 2020, 5, 236; doi:10.3390/fluids5040236 www.mdpi.com/journal/fluids
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