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A Computational Process to Effectively Design Seals for Improved Wind Noise Performance
ISSN: 2641-9645, e-ISSN: 2641-9645
Published June 05, 2019 by SAE International in United States
Citation: Oettle, N., Powell, R., Senthooran, S., and Moron, P., "A Computational Process to Effectively Design Seals for Improved Wind Noise Performance," SAE Int. J. Adv. & Curr. Prac. in Mobility 1(4):1690-1697, 2019, https://doi.org/10.4271/2019-01-1472.
The ability to assess noise transmitted through seals to cabin interiors early in the design process is very important for automotive manufacturers. When a seal design is inadequate, the noise transmitted can dominate the interior noise, making the wind noise performance of the vehicle unacceptable. This can cause launch delays, increasing costs and risking loss of sales. Designing seals using conventional experimental processes is challenging, since the location and strength of flow noise sources are not known when the seal design is planned. Making changes to the seal system after the tooling stage is expensive for manufacturers as tooling and redesign costs can be considerable. Deliberate overdesign by adding multiple layers of seals in a wide range of locations also can reduce profit by unnecessarily raising part and manufacturing costs. Consequently, there is a strong motivation to use reliable computational capabilities to predict interior noise transmitted through seals early in the design process to address these challenges, designing seals right first time.
The current study presents a computational process that can be used to predict interior noise transmitted through seals early in the design process. This computational approach uses a Lattice Boltzmann method (LBM) based computational fluid dynamics (CFD) solver to predict the transient flow field and exterior noise sources. A statistical energy analysis (SEA) solver was used to transmit noise from these sources into the cabin through glass panels and seals. Experiments were performed to quantify noise transmitted through glass panels, window seals and door seals, allowing validation of the computational predictions. Detailed flow analysis was performed to gain insight into the noise sources and the exterior loads on both the seals and glass panels. Accurate prediction of the seal noise and the insight provided by the flow analysis showed that this computational process can be used early in the vehicle development process to design efficient seals for improved wind noise performance.
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