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An Analysis on Automotive Side Window Buffeting Using Scale Adaptive Simulation

机译:尺度自适应模拟汽车侧窗外自动探测分析

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Automotive window buffeting is a source of vehicle occupant’s discomfort and annoyance. Original equipment manufacturers (OEM) are using both experimental and numerical methods to address this issue. With major advances in computational power and numerical modelling, it is now possible to model complex aero acoustic problems using numerical tools like CFD. Although the direct turbulence model LES is preferred to simulate aero-acoustic problems, it is computationally expensive for many industrial applications. Hybrid turbulence models can be used to model aero acoustic problems for industrial applications. In this paper, the numerical modelling of side window buffeting in a generic passenger car is presented. The numerical modelling is performed with the hybrid turbulence model Scale Adaptive Simulation (SAS) using a commercial CFD code. While the acoustic generation is modelled by solving compressible Navier-Stokes equation, integral method Ffowcs-Williams & Hawkings (FWH) is used to model acoustic propagation in the computational domain. Certain investigation on the influence of rear view mirror (RVM) & divide pillar on buffeting noises are analyzed using a few flow and spectral techniques. Differences in the noise levels between front and rear window buffeting are also investigated. A 3D-cavity test model is considered to validate the modelling methodology. Investigations have shown the installation of a divide pillar on window have significantly minimized noise levels and appendages like the glass mounted RVM have a minimizing effect on the buffeting intensity. Also the noise levels of rear window buffeting are found to be higher than front window buffeting. Modelling window buffeting using a SAS model have shown to be a reliable and computationally less expensive option. The investigations using spectral technique like Fast Fourier Transform (FFT) band analysis gave a better insight in to buffeting problem.
机译:汽车窗外自动驾驶是车辆占用者的不适和烦恼的源泉。原始设备制造商(OEM)正在使用两种实验和数值方法来解决这个问题。在计算能力和数值建模中具有主要进步,现在可以使用像CFD等数值工具模拟复杂的航空声学问题。虽然直接湍流模型LES是优选模拟航空声问题,但它对于许多工业应用来说是计算昂贵的。混合动力湍流模型可用于模拟工业应用的Aero声学问题。本文介绍了通用乘用车中侧窗自助式的数值建模。使用商业CFD码,利用混合湍流模型刻度进行自适应仿真(SAS)来执行数值建模。虽然通过解决可压缩Navier-Stokes方程来建模声学产生,但是整体方法FFOWCS-Williams&Hawkings(FWH)用于在计算域中的声学传播模拟声学传播。使用少数流动和光谱技术分析对后视镜(RVM)和划分柱对缓冲噪声影响的某些研究。还研究了前后窗口自动探测器之间的噪声水平的差异。考虑3D腔测试模型以验证建模方法。调查显示,窗户上的划分柱的安装具有显着最小化的噪声水平,如玻璃安装的RVM等附加物对缓冲强度的影响最小。还发现后窗缓冲的噪声水平高于前窗自窗。使用SAS模型的建模窗口自助式已显示是可靠且计算不太昂贵的选项。使用像快速傅里叶变换(FFT)频带分析等频谱技术的调查对缓冲问题进行了更好的见解。

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