Verfication of Noise Prediction Through Acoustic Analogy

Author(s):  
Ghader Ghorbaniasl ◽  
Charles Hirsch ◽  
Kris Van Den Abeele ◽  
Chris Lacor
AIAA Journal ◽  
2000 ◽  
Vol 38 ◽  
pp. 1095-1098 ◽  
Author(s):  
Jeonghan Lee ◽  
Kyungseok Cho ◽  
Soogab Lee

Author(s):  
Xihai Xu ◽  
Xiaodong Li

An anisotropic component of the jet noise source model for the Reynolds-averaged Navier–Stokes equation-based jet noise prediction method is proposed. The modelling is based on Goldstein's generalized acoustic analogy, and both the fine-scale and large-scale turbulent noise sources are considered. To model the anisotropic characteristics of jet noise source, the Reynolds stress tensor is used in place of the turbulent kinetic energy. The Launder–Reece–Rodi model (LRR), combined with Menter's ω -equation for the length scale, with modified coefficients developed by the present authors, is used to calculate the mean flow velocities and Reynolds stresses accurately. Comparison between predicted results and acoustic data has been carried out to verify the accuracy of the new anisotropic source model. This article is part of the theme issue ‘Frontiers of aeroacoustics research: theory, computation and experiment’.


2011 ◽  
Vol 52-54 ◽  
pp. 1388-1393
Author(s):  
Jun Tao ◽  
Gang Sun ◽  
Ying Hu ◽  
Miao Zhang

In this article, four observation points are selected in the flow field when predicting aerodynamic noise of a multi-element airfoil for both a coarser grid and a finer grid. Numerical simulation of N-S equations is employed to obtain near-field acoustic information, then far-field acoustic information is obtained through acoustic analogy theory combined with FW-H equation. Computation indicates: the codes calculate the flow field in good agreement with the experimental data; The finer the grid is, the more stable the calculated sound pressure level (SPL) is and the more regularly d(SPL)/d(St) varies.


AIAA Journal ◽  
2000 ◽  
Vol 38 (6) ◽  
pp. 1095-1098 ◽  
Author(s):  
Jeonghan Lee ◽  
Kyungseok Cho ◽  
Soogab Lee

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