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Turbofan broadband noise predictions using a 3-D ZDES rotor blade approach

机译：使用3-D ZDES转子叶片方法的Turbofan宽带噪声预测

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Turbofan broadband noise prediction is a major concern for industry and probably the most challenging issue for Aeroacoustic community. The dominant source mechanism is attributed to the rotor turbulent wakes impacting on the outlet guide vanes. Unsteady computations of the full rotor-stator stage are generally out of reach so that interaction noise is commonly assessed using analytical models (related to Amiet's theory) and averaged turbulence characteristics issued from a steady RANS calculation and isotropic homogeneous turbulence assumption. However these models are questionable to accurately describe the turbulent rotor wakes characterized by a non-uniform spatial distribution stretched in the flow direction. Thus, a hybrid method based on a 3-D Zonal Detached Eddy Simulation of the flow around a single rotor blade is investigated to provide a full description of the turbulent wakes directly used in the Amiet-based code. The reliability of this approach is checked thanks to the comparisons of turbulent velocity and acoustic spectra respectively with hot-film probe and microphone measurements performed in Snecma engine test rig. A quite good agreement is shown between numerical and experimental turbulent velocity spectra and also the von Karman spectrum model, when mean turbulence characteristics are well adjusted. Moreover, sound pressure and power spectra in the outlet duct predicted by ZDES-Amiet coupling are reasonably close to the available measurements, and not so far from RANS-based ones.
机译：涡轮风扇宽带噪声预测是业界关注的重点，对于航空声学界来说可能是最具挑战性的问题。主导源机制归因于转子湍流尾流撞击出口导向叶片。整个转子-定子级的非定常计算通常是遥不可及的，因此通常使用解析模型（与Amiet理论有关）和由稳定的RANS计算和各向同性均质湍流假设得出的平均湍流特性来评估相互作用噪声。然而，这些模型对于准确描述以在流动方向上伸展的不均匀空间分布为特征的湍流转子尾流是有问题的。因此，研究了基于单个转子叶片周围流动的3-D区域分离涡流仿真的混合方法，以提供对直接用于基于Amiet的代码中的湍流尾流的完整描述。通过将湍流速度和声谱分别与在斯奈克玛发动机试验台中进行的热膜探头和传声器测量结果进行比较，检查了这种方法的可靠性。当平均湍流特性得到很好的调整时，数值和实验湍流速度谱以及冯·卡曼光谱模型之间显示出很好的一致性。此外，通过ZDES-Amiet耦合预测的出口管道中的声压和功率谱相当接近可用的测量值，与基于RANS的测量值相差不远。

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