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Investigation of Interior Noise from Generic Side- View Mirror Using Incompressible and Compressible Solvers of DES and LES
ISSN: 0148-7191, e-ISSN: 2688-3627
Published April 03, 2018 by SAE International in United States
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Exterior turbulent flow is an important source of automobile cabin interior noise. The turbulent flow impacts the windows of the cabins to excite the structural vibration that emits the interior noise. Meanwhile, the exterior noise generated from the turbulent flow can also cause the window vibration and generate the interior noise. Side-view mirrors mounted upstream of the windows are one of the predominant body parts inducing the turbulent flow. In this paper, we investigate the interior noise caused by a generic side-view mirror. The interior noise propagates in a cuboid cavity with a rectangular glass window. The exterior flow and the exterior noise are computed using advanced CFD methods: compressible large eddy simulation, compressible detached eddy simulation (DES), incompressible DES, and incompressible DES coupled with an acoustic wave model. The last method is used to simulate the hydrodynamic and acoustic pressure separately. The pressure fluctuations of the flow and noise are imposed on the window in the computation of the interior noise, but the reversal effect of the window vibration feeding back on the flow is neglected in the flow simulation. The localized flow characteristics are discussed. The energetic surface pressure appears in the regions where the shear layer from the mirror side edge impinges on the window. The contributions of the hydrodynamic and acoustic pressure to the interior noise are quantified. The acoustic component is found to be more efficient in the interior noise generation and to play the dominant role at high frequencies.
CitationYao, H., Davidson, L., and Chroneer, Z., "Investigation of Interior Noise from Generic Side- View Mirror Using Incompressible and Compressible Solvers of DES and LES," SAE Technical Paper 2018-01-0735, 2018, https://doi.org/10.4271/2018-01-0735.
Data Sets - Support Documents
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