This paper uses Reynolds-averaged Navier–Stokes computational fluid dynamics to study trailing edge noise reduction with 3-D finlets. Reynolds-averaged Navier–Stokes computational fluid dynamics provides boundary layer parameters near a trailing edge for an empirical wall pressure spectrum model, and then an acoustic model predicts far-field noise based on pressure fluctuations obtained from the wall pressure spectrum model. First, this numerical approach is validated against experiments. Second, a comprehensive trend analysis is conducted to give insight into the design of 3-D finlets under different flow conditions. A data-driven turbulence spanwise length scale model is developed to tackle finlets with small spacing. Combined with acoustic results, detailed computational flow field results are analyzed to understand the physical mechanism of noise reduction. While the major part of the proposed mechanism is the same as prior work, several new observations are shown which better understand the physical mechanism of noise reduction with 3-D finlets. The goals of the current paper are to provide an efficient Reynolds-averaged Navier–Stokes-based approach to predict trailing edge noise of 3-D finlets, to give complete trend analysis results with various finlets under different flow conditions, and to advance an understanding of the underlying physics.

中文翻译：

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使用雷诺平均 Navier-Stokes 计算流体动力学对 3-D 小翼进行后缘降噪的数值研究

本文使用雷诺平均 Navier-Stokes 计算流体动力学来研究使用 3-D 鳍片的后缘降噪。雷诺平均 Navier-Stokes 计算流体动力学为经验壁压力谱模型提供后缘附近的边界层参数，然后声学模型根据从壁压力谱模型获得的压力波动预测远场噪声。首先，这种数值方法经过实验验证。其次，进行了全面的趋势分析，以深入了解不同流动条件下的 3-D 翅片设计。开发了一种数据驱动的湍流展向长度比例模型来处理小间距的翅片。结合声学结果，分析详细的计算流场结果以了解降噪的物理机制。虽然所提出机制的主要部分与之前的工作相同，但显示了一些新的观察结果，它们可以更好地理解使用 3-D 鳍片降噪的物理机制。当前论文的目标是提供一种有效的基于雷诺平均纳维-斯托克斯的方法来预测 3-D 鳍片的后缘噪声，在不同流动条件下给出各种鳍片的完整趋势分析结果，并促进理解基础物理学。