Reducing a Sports Activity Vehicle's Aeroacoustic Noise using a Validated CAA Process

2012-01-1552

06/13/2012

Event
7th International Styrian Noise, Vibration & Harshness Congress: The European Automotive Noise Conference
Authors Abstract
Content
Developing a low interior noise level of vehicles is a big challenge - even a greater one if one thinks about aeroacoustics. Aeroacoustic noise and its origins are usually identified with the help of prototypes when exterior design changes or the replacement of exterior parts like side mirrors are very limited. However, computational aeroacoustic (CAA) methods in virtual project phases offer more design options for the vehicle's geometric shape. The early consideration of aeroacoustic relevant design changes helps to keep project costs low by avoiding tool changes.
This paper describes MAGNA STEYR's virtual aeroacoustic process starting from standardized model generation and simulation of wind noise, including the validation of computational results via comparison with measurement data gathered in an acoustic wind tunnel. The simulations are carried out using the commercial CAA code “PowerFLOW” (Exa) based on the Lattice-Boltzmann method. CAA post-processing results with the aim to detect hot spots and to derive effective measures are presented. As a typical application, a design modification example is highlighted: Pressure fluctuations on a vehicle's side window are influenced strongly by the design of the a-pillar. Improvement potential was identified by analyzing simulations results and a-pillar modifications were developed which led to a validated interior noise reduction of 1 dB(A).
Meta TagsDetails
DOI
https://doi.org/10.4271/2012-01-1552
Pages
10
Citation
Müller, G., Jany, J., and Neuhierl, B., "Reducing a Sports Activity Vehicle's Aeroacoustic Noise using a Validated CAA Process," SAE Technical Paper 2012-01-1552, 2012, https://doi.org/10.4271/2012-01-1552.
Additional Details
Publisher
Published
Jun 13, 2012
Product Code
2012-01-1552
Content Type
Technical Paper
Language
English