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首页> 外文期刊>International Journal of Aeroacoustics >ANOPP landing-gear noise prediction with comparison to model-scale data
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ANOPP landing-gear noise prediction with comparison to model-scale data

机译:ANOPP起落架噪声预测与模型规模数据的比较

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The NASA Aircraft NOise Prediction Program (ANOPP) offers two empirically based methods to predict landing gear noise: the "Fink" method and the "Guo" method. The "Guo" method is the most recent and was developed almost exclusively using Boeing full-scale landing gear data. The "Fink" method was developed over 25 years ago, using both model and full-scale data. The details of the two methods are compared and contrasted. The Fink method is found to follow Strouhal scaling, and hence predictions are made with the scale model geometry as input. The Guo method was found not to scale for arbitrary sized landing gear and hence the method required full-scale geometry inputs and the resulting predictions required scaling in order to compare with the measured model results. Application of these methods to a model-scale landing gear is investigated by comparing predicted results from each method with measured acoustic data obtained for a high-fidelity, 6.3%-scale, Boeing 777 main landing gear. The measurements were obtained in the NASA Langley Quiet Flow Facility for a range of Mach numbers at a large number of observer angles. Noise spectra and contours as a function of polar and azimuthal angle characterize the directivity of landing gear noise. The measured spectra and contours are compared to predictions made using the Fink method and to scaled predictions from the Guo method. This is the first time an extensive set of landing gear noise directivity data are available to compare and assess predictive capabilities. Both methods predict comparable amplitudes and trends for the flyover locations, but deviate at sideline locations. Neither method fully captures the measured noise directivity.
机译:NASA飞机噪声预测程序(ANOPP)提供了两种基于经验的预测起落架噪声的方法:“ Fink”方法和“ Guo”方法。 “ Guo”方法是最新的方法,几乎​​是完全使用波音全尺寸起落架数据开发的。 “ Fink”方法是在25年前开发的,同时使用模型和全面数据。比较和对比了这两种方法的细节。发现Fink方法遵循Strouhal缩放,因此使用缩放模型几何体作为输入进行预测。郭的方法被发现不能缩放为任意大小的起落架,因此该方法需要全尺寸的几何输入,结果预测需要缩放以与测量的模型结果进行比较。通过将每种方法的预测结果与为高保真度,6.3%比例的波音777主起落架获得的测得的声学数据进行比较,研究了这些方法在模型级起落架上的应用。这些测量值是在NASA兰利静音流动装置中以大量观察者角度针对一系列马赫数获得的。噪声谱和轮廓是极角和方位角的函数,表征了起落架噪声的方向性。将测得的光谱和轮廓与使用Fink方法进行的预测以及通过Guo方法进行的按比例缩放的预测进行比较。这是首次广泛的起落架噪声方向性数据集可用于比较和评估预测能力。两种方法都预测了立交桥位置的可比幅度和趋势,但在边线位置偏离。两种方法都无法完全捕获所测得的噪声方向性。

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