Semi-Empirical Modeling of Turbulent Anisotropy for Airfoil Self-Noise Predictions
Semi-Empirical Modeling of Turbulent Anisotropy for Airfoil Self-Noise Predictions
复制标题
用于机翼自噪声预测的湍流各向异性的半经验建模
DOI：
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发表时间：
2012
期刊：
影响因子：
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通讯作者：
E. Krämer
中科院分区：
文献类型：
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作者：
M. Kamruzzaman;T. Lutz;A. Herrig;E. Krämer
本文提出了一种从标准雷诺平均的Navier-Stokes数值模拟中提取各向异性湍流特性的方法。该理论包括各向异性速度谱模型和尺度函数，可用于推导湍流边界层后缘干扰噪声预报所需的其他湍流参数。这类噪声应该受到翼型或机翼尾缘附近的非均匀和各向异性流动特性的影响。为此，在斯图加特大学的层流风洞中，对两个翼型(NACA0012和NACA 3-418)在高雷诺数(Re=1.5×106和2.5×106)下的近尾区进行了两点湍流速度相关测量。为了模拟不同的各向同性和各向异性速度谱以及相关的长度尺度，对实验数据进行了详细的后处理和评估。对于该模型，应用了各向异性振幅标度方法和Kolmogorov局部各向同性假设。此外，将两个不同的半经验函数与合成的各向异性标度因子关联起来，以模拟数值预报的雷诺平均N-S资料中湍流各向异性的影响。所提出的谱模型可以准确地估计湍流的平均耗散率。对新模型进行了验证，并将其应用于湍流边界层后缘相互作用噪声预报方法(RNoise)，分析了各向异性对总预报噪声谱的影响。
In the present paper an approach to derive anisotropic turbulence properties from standard Reynolds-averaged Navier-Stokes simulations is proposed. The theory includes models for anisotropic velocity spectra and scaling functions that can be used to derive other turbulence parameters required for the turbulent boundary-layer trailing-edge interaction noise prediction. This type of noise is supposed to be affected by the inhomogeneous and anisotropic flow character near the trailing edge of an airfoil or wing. For this purpose, two-point turbulent velocity correlation measurements in the near wake of two airfoils (NACA 0012 and NACA 64 3 -418) at high Reynolds numbers (Re = 1.5 x 10 6 and 2.5 x 10 6 ) were conducted in the Laminar Wind Tunnel of the University of Stuttgart. A detailed postprocessing along with assessment of the experimental data has been performed for the modeling of different isotropic and anisotropic velocity spectra and related length scales. For this modeling, an anisotropy amplitude scaling method and Kolmogorov local-isotropy hypothesis have been applied. Furthermore, two different semi-empirical functions have been correlated to the resultant anisotropy scaling factors to model the effects of turbulence anisotropy in numerically predicted Reynolds-averaged Navier-Stokes data. The proposed spectrum modeling allows an accurate evaluation of the turbulence mean dissipation rate. The new models were validated and applied to a turbulent boundary-layer trailing-edge interaction noise prediction method (Rnoise) to analyze the impact of anisotropy on the total predicted noise spectra.