scholarly journals A Hybrid Grid Compressible Flow Solver for Large-Scale Supersonic Jet Noise Simulations on Multi-GPU Clusters

Author(s):  
Andrew Corrigan ◽  
Kailas Kailasanath ◽  
Junhui Liu ◽  
Ravi Ramamurti ◽  
Douglas Schwer ◽  
...  
1998 ◽  
Author(s):  
S. Shih ◽  
D. Hixon ◽  
L. Povinelli ◽  
Reda Mankbadi

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

2021 ◽  
Vol 20 (1-2) ◽  
pp. 4-34
Author(s):  
Reda R Mankbadi ◽  
Saman Salehian

In this work we propose replacing the conventional flat-surface airframe that shields the engine by a wavy surface. The basic principle is to design a wavy pattern to reflect the incoming near-field flow and acoustic perturbations into waves of a particular dominant frequency. The reflected waves will then excite the corresponding frequency of the large-scale structure in the initial region of the jet’s shear layer. By designing the frequency of the reflected waves to be the harmonic of the fundamental frequency that corresponds to the radiated peak noise, the two frequency-modes interact nonlinearly. With the appropriate phase difference, the harmonic dampens the fundamental as it extracts energy from it to amplify. The outcome is a reduction in the peak noise. To evaluate this concept, we conducted Detached Eddy Simulations for a rectangular supersonic jet with and without the wavy shield and verified our numerical results with experimental data for a free jet, as well as, for a jet with an adjacent flat surface. Results show that the proposed wavy surface reduces the jet noise as compared to that of the corresponding flat surface by as much as 4 dB.


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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