Physics and Prediction of Supersonic Jet Noise

1994 ◽  
Vol 47 (6S) ◽  
pp. S184-S187
Author(s):  
Christopher K. W. Tam

Both the large turbulence structures and the fine scale turbulence of the flows of supersonic jets are sources of turbulent mixing noise. At moderately high supersonic Mach numbers especially for hot jets, the dominant part of the noise is generated directly by the large turbulence structures. The large turbulence structures propagate downstream at supersonic velocities relative to the ambient sound speed. They generate strong Mach wave radiation analogous to a supersonically travelling wavy wall. A stochastic instability wave model theory of the large turbulence structures and noise of supersonic jets has recently been developed. The theory can predict both the spectrum and directivity of the dominant part of supersonic jet noise up to a multiplicative empirical constant. Calculated results agree well with measurements.

2012 ◽  
Vol 588-589 ◽  
pp. 860-863
Author(s):  
Xiao Bo Peng ◽  
Jia Ming Li ◽  
Chun Bo Hu

A systematic study has been undertaken to quantify the effects of jet Mach number and nozzle size on the noise radiated by supersonic jets. All the tests were carried out at an experimental bench of the supersonic jet. Results indicate that the field distribution of supersonic jet screech tones is characterized with very strong directivity. Under the textual experimental conditions, if the jet Mach number remain unchanged, the diameter of nozzle throat increases gradually from 5mm to 8mm or 10mm, and the amplitude values of both the turbulent mixing noise and broadband shockwave correlated noise increase by 2-5dB, and the amplitude value change of the whistler type noise is not obvious, and the occurrence frequency of the whistler type noise decreases by more than 2000Hz; if the jet Mach number increases to 3.0 from 2.0, the amplitude value of the whistler type noise increases by more than 2dB, and the occurrence frequency of the whistler type noise decreases obviously. The experimental measurements of supersonic jet noise provide the sound production mechanism research on the supersonic jet noise with data supports and references and provide the numerical modeling of the supersonic jet noise with validation criteria.


1998 ◽  
Vol 120 (3) ◽  
pp. 471-476 ◽  
Author(s):  
Milo D. Dahl ◽  
Philip J. Morris

In this paper, predictions are made of noise radiation from single, supersonic, axisymmetric jets. We examine the effects of changes in operating conditions and the effects of simulated enhanced mixing that would increase the spreading rate of the jet shear layer on radiated noise levels. The radiated noise in the downstream direction is dominated by mixing noise and, at higher speeds, it is well described by the instability wave noise radiation model. Further analysis with the model shows a relationship between changes in spreading rate due to enhanced mixing and changes in the far field radiated peak noise levels. The calculations predict that enhanced jet spreading results in a reduction of the radiated peak noise level.


Author(s):  
Toshinori Watanabe ◽  
Ryuichi Okada ◽  
Seiji Uzawa ◽  
Takehiro Himeno ◽  
Tsutomu Oishi

Experimental study was conducted concerning active control of supersonic jet noise with a microjet injection technique. The microjets were injected into a rectangular main jet with Mach number up to 1.49. The nozzle lip of the main jet was equipped with 44 injection holes of the microjets, whose angles against the main jet were changed as 60 and 90 degrees. From far-field sound pressure data, a significant reduction of the jet noise by several dB was found in the cases with 60 and 90 degrees of injection angles. The microjet was found to affect all components of supersonic jet noise, namely, turbulent mixing noise, shock-associated broadband noise and screech tone noise. In the results of FFT analysis, the effect of the microjet was observed in the sound pressure level of the shock-associated broadband noise, the pressure level and frequency of the screech tone noise, and average level of the turbulent mixing noise. Schlieren visualization was also made for the jet flow, and the microjet was seen to change the shock structure and shear layer behavior of the supersonic jet.


Author(s):  
Robert H. Schlinker ◽  
Ramons A. Reba ◽  
John C. Simonich ◽  
Tim Colonius ◽  
Kristjan Gudmundsson ◽  
...  

In this paper, we report on progress towards developing physics-based models of sound generation by large-scale turbulent structures in supersonic jet shear layers generally accepted to be the source of aft-angle noise. Aside from obtaining better engineering prediction schemes, the development and optimization of long term jet noise reduction strategies based on controlling instability wave generated large-scale turbulence structures in the shear layer can be more successful if based on predictive flow-noise models, rather than on build and test approaches alone. Such models, if successful, may also provide a path by which laboratory scale demonstrations can be more reliably translated to engine scale. Results show that the noise radiated by large-scale structures in turbulent jet shear layers may be modeled using a RANS based PSE method and projected to the far-field using a Kirchhoff surface approach. A key enabler in this procedure is the development of near-field microphone arrays capable of providing the pressure statistics needed to validate the instability wave models. Our framework provides, for the first time, a deterministic model that will allow understanding and predicting noise radiated by large-scale turbulence.


2017 ◽  
Vol 65 (2) ◽  
pp. 110-120 ◽  
Author(s):  
Zhe Chen ◽  
Jiu-Hui Wu ◽  
A-Dan Ren ◽  
Xin Chen ◽  
Zhen Huang

Author(s):  
Chris Nelson ◽  
Alan B. Cain ◽  
Robert P. Dougherty ◽  
Kenneth S. Brentner ◽  
Philip J. Morris

2022 ◽  
Author(s):  
Junhui Liu ◽  
Yu Yu Khine ◽  
Mohammad Saleem ◽  
Omar Lopez Rodriguez ◽  
Ephraim J. Gutmark

2021 ◽  
Author(s):  
Junhui Liu ◽  
Yu Yu Khine ◽  
Mohammad Saleem ◽  
Omar Lopez Rodriguez ◽  
Ephraim Gutmark

Author(s):  
Kailas Kailasanath ◽  
Andrew T. Corrigan ◽  
Junhui Liu ◽  
Ravi Ramamurti

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