应用于通用侧视镜的第二代 URANS 模型（STRUCT$-ε$）及其对声音生成的影响
A second-generation URANS model (STRUCT$-ε$) applied to a Generic Side Mirror and its Impact on Sound Generation
AI总结：
本文研究第二代 URANS 模型 STRUCT$-ε$ 对通用侧视镜绕流中滞止、分离、涡脱落及噪声生成机制的预测能力，结果表明其优于其他混合方法并与大涡模拟和实验吻合良好，还可用于构建谱本征正交分解以识别主导流动结构。
摘要：
通用侧视镜可以近似为半圆柱体与四分之一球体的组合。侧视镜尾迹中的流动结构具有高度瞬态特性，湍流通过压力脉动对气动声学产生重要影响。因此，该几何构型是近年来多项数值研究中的测试案例之一，用于评估湍流模型的气动与气动声学预测能力。在此背景下，本研究展示了第二代 URANS 模型 STRUCT$-ε$ 如何能够正确预测预期的滞止、流动分离和涡脱落现象。此外，通过比较在多个静态压力传感器处测得的声压级频谱与 STRUCT$-ε$ 获得的数值结果，评估了该模型对噪声生成机制的预测精度。该湍流模型的响应表现优于其他混合方法，并与大涡模拟或实验结果具有良好的一致性。作为论文的结论部分，本文还介绍了 STRUCT$-ε$ 在构建谱本征正交分解方法中的适用性，该方法有助于识别能量最高的模态，从而恰当地捕捉主导流动结构。
英文摘要：
A generic side mirror can be approximated to the combination of a half cylinder topped with a quarter of sphere. The flow structure in the wake of the side mirror is highly transient and the turbulence plays an important role affecting aeroacoustics through pressure fluctuation. Thus, this geometry is one of the test cases object of several numerical studies in recent years to assess the aerodynamic and aeroacoustic capabilities of the turbulence models. In this context, this study presents how the second-generation URANS close STRUCT$-ε$ is able to properly predict the expected stagnation, flow separation and vortex shedding phenomena. Besides, the predictive accuracy for the noise generation mechanism is evaluated by comparing the spectra of the sound pressure level measured at several static pressure sensors with the numerical results obtained with the STRUCT$-ε$. The response of this turbulence model has overachieved other hybrid methods and is in good agreement with the results from Large-Eddy Simulations or the experiments. To conclude the paper, the applicability of STRUCT$-ε$ to construct a Spectral Proper Orthogonal Decomposition method that helps identifying the most energetic modes to appropriately capture the dominant flow structures is also introduced.
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