SAMURAI - jet noise source analysis of a V2500 engine

2016 ◽  
Author(s):  
Henri A. Siller ◽  
Alessandro Bassetti ◽  
Stefan Funke
Keyword(s):  
Noise Source ◽  
Jet Noise ◽  
Source Analysis

scholarly journals Installed jet noise source analysis by microphone array processing

2019 ◽  
Author(s):  
Renaud Davy ◽  
Frédéric Mortain ◽  
Maxime Huet ◽  
Thomas Le Garrec
Keyword(s):  
Noise Source ◽  
Array Processing ◽  
Microphone Array ◽  
Jet Noise ◽  
Source Analysis

Jet noise source measurements using PIV

1999 ◽  
Author(s):  
John Seiner ◽  
Larry Ukeiley ◽  
Michael Ponton
Keyword(s):  
Noise Source ◽  
Jet Noise

Noise source analysis and control of two axial-flow cooling fans in series

2016 ◽  
Vol 64 (5) ◽  
pp. 677-687 ◽  
Author(s):  
Chen Wang ◽  
Weihao Zhang ◽  
Lixi Huang
Keyword(s):  
Noise Source ◽  
Axial Flow ◽  
Source Analysis ◽  
Cooling Fans ◽  
In Series ◽  
And Control

scholarly journals Jet-Surface Interaction Test: Phased Array Noise Source Localization Results

2012 ◽  
Author(s):  
Gary G. Podboy
Keyword(s):  
Source Localization ◽  
Phased Array ◽  
Noise Source ◽  
Jet Noise ◽  
Companion Paper ◽  
Far Field ◽  
Sound Waves ◽  
Axial Distribution ◽  
Noise Sources ◽  
Interaction Test

An experiment was conducted to investigate the effect that a planar surface located near a jet flow has on the noise radiated to the far-field. Two different configurations were tested: 1) a shielding configuration in which the surface was located between the jet and the far-field microphones, and 2) a reflecting configuration in which the surface was mounted on the opposite side of the jet, and thus the jet noise was free to reflect off the surface toward the microphones. Both conventional far-field microphone and phased array noise source localization measurements were obtained. This paper discusses phased array results, while a companion paper discusses far-field results. The phased array data show that the axial distribution of noise sources in a jet can vary greatly depending on the jet operating condition and suggests that it would first be necessary to know or be able to predict this distribution in order to be able to predict the amount of noise reduction to expect from a given shielding configuration. The data obtained on both subsonic and supersonic jets show that the noise sources associated with a given frequency of noise tend to move downstream, and therefore, would become more difficult to shield, as jet Mach number increases. The noise source localization data obtained on cold, shock-containing jets suggests that the constructive interference of sound waves that produces noise at a given frequency within a broadband shock noise hump comes primarily from a small number of shocks, rather than from all the shocks at the same time. The reflecting configuration data illustrates that the law of reflection must be satisfied in order for jet noise to reflect off of a surface to an observer, and depending on the relative locations of the jet, the surface, and the observer, only some of the jet noise sources may satisfy this requirement.

Evaluating the effectiveness of subarrays in beamforming computations of complex jet noise source environments

2018 ◽  
Vol 143 (3) ◽  
pp. 1723-1723
Author(s):  
David F. Van Komen ◽  
Tracianne B. Neilsen ◽  
Blaine M. Harker ◽  
Kent L. Gee ◽  
S. Hales Swift ◽  
...  
Keyword(s):  
Noise Source ◽  
Jet Noise

Resolvent analysis for jet noise source identification

2018 ◽  
Vol 144 (3) ◽  
pp. 1706-1706
Author(s):  
Ethan M. Pickering ◽  
Georgios Rigas ◽  
Oliver T. Schmidt ◽  
Tim Colonius
Keyword(s):  
Source Identification ◽  
Noise Source ◽  
Jet Noise ◽  
Noise Source Identification

scholarly journals Anisotropic source modelling for turbulent jet noise prediction

2019 ◽  
Vol 377 (2159) ◽  
pp. 20190075 ◽  
Author(s):  
Xihai Xu ◽  
Xiaodong Li
Keyword(s):  
Large Scale ◽  
Noise Source ◽  
Jet Noise ◽  
Source Model ◽  
Noise Prediction ◽  
Reynolds Stresses ◽  
Acoustic Analogy ◽  
Mean Flow ◽  
Navier Stokes Equation ◽  
Anisotropic Source

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’.

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