Stochastic Noise Sources for Computational Aeroacoustics of a Vehicle Side Mirror

IF 0.5 Q4 TRANSPORTATION SCIENCE & TECHNOLOGY
Philipp Uhl, Alexander Schell, Roland Ewert, Jan Delfs
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Abstract

The broadband aeroacoustics of a side mirror is investigated with a stochastic noise source method and compared to scale-resolving simulations. The setup based on an already existing work includes two geometrical variants with a plain series side mirror and a modified mirror with a forward-facing step mounted on the inner side. The aeroacoustic near- and farfield is computed by a hydrodynamic–acoustic splitting approach by means of a perturbed convective wave equation. Aeroacoustic source terms are computed by the Fast Random Particle-Mesh method, a stochastic noise source method modeling velocity fluctuations in time domain based on time-averaged turbulence statistics. Three RANS models are used to provide input data for the Fast Random Particle-Mesh method with fundamental differences in local flow phenomena. Results of aeroacoustics simulations excited by the Fast Random Particle-Mesh method based on well-matching RANS data are in good agreement to the scale-resolving simulations in the integral acoustic Delta on the side window induced by the different side mirror geometries. For relative levels in between the variations, the robustness of the Fast Random Particle-Mesh method can be shown with secondary influences on the choice of the integral length scale. Absolute levels are only achieved with an adaptation of the length scale from literature. Two different RANS models with a missing separation bubble on the mirror or an overestimated wake flow show a good agreement with the plain series side mirror. However, they fail at computing the Delta to the step variant due to the missing amplification of the local turbulent kinetic energy interacting with the step and downstream mirror surfaces. Computational aeroacoustics simulations excited by the Fast Random Particle-Mesh method method based on RANS data only needs 14% of the computational effort compared to the conventional hybrid RANS-LES approach. This reveals its enormous potential for aeroacoustic broadband noise optimization purposes.
汽车侧视镜计算气动声学随机噪声源
采用随机噪声源方法对侧镜的宽带气动声学进行了研究,并与尺度分辨模拟进行了比较。该装置基于已经存在的作品,包括两个几何变体,一个是普通系列侧镜,另一个是内部安装有向前台阶的改进镜。利用扰动对流波动方程,采用水动力声分裂法计算了气动声近场和远场。气动声源项的计算采用快速随机粒子网格法,这是一种基于时间平均湍流统计量在时域上模拟速度波动的随机噪声源方法。采用三种RANS模型为快速随机粒子网格法提供输入数据,它们在局部流动现象上存在根本差异。基于匹配良好的RANS数据的快速随机粒子网格方法激发的气动声学模拟结果与不同侧镜几何形状引起的侧窗积分声学Delta的尺度分辨模拟结果吻合较好。对于变化之间的相对水平,快速随机粒子网格方法的鲁棒性可以显示出对积分长度尺度选择的次要影响。只有根据文献中的长度尺度进行调整,才能达到绝对水平。两种不同的RANS模型在镜面上缺失分离泡或尾流估计过高的情况下与普通系列侧镜的结果吻合较好。然而,由于缺少与阶梯和下游镜面相互作用的局部湍流动能的放大,他们无法计算阶梯变量的Delta。基于RANS数据的快速随机粒子网格法激发的计算气动声学模拟,与传统的混合RANS- les方法相比,只需14%的计算量。这揭示了其在航空声学宽带噪声优化方面的巨大潜力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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CiteScore
1.30
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