Far-field noise radiation characteristics of an afterburning military jet aircraft

2020 ◽  
Vol 148 (4) ◽  
pp. 2702-2702
Author(s):  
Michael S. Bassett ◽  
Reese D. Rasband ◽  
Daniel J. Novakovich ◽  
Kent L. Gee ◽  
Steven C. Campbell ◽  
...  
1976 ◽  
Vol 21 (4) ◽  
pp. 2-16
Author(s):  
F. H. Schmitz ◽  
D. A. Boxwell

A new and highly successful method of collecting far‐field acoustic data radiated by helicopters in forward flight has been developed, utilizing a quiet aircraft flying in formation ahead of the subject helicopter. The lead aircraft, flown as an acoustic probe, was equipped with tape‐recording equipment and an external microphone. Spatial orientation of the helicopter with respect to the monitoring aircraft was achieved through visual flight reference. Far‐field acoustic data defining the impulsive noise radiation characteristics of the UH‐1H helicopter during high‐speed flight and partial ‐power descents have been gathered with this technique. Three distinct types of impulsive waveforms have been identified and correlated with helicopter steady operating conditions.


Author(s):  
Clifford A. Brown

Many configurations proposed for the next generation of aircraft rely on the wing or other aircraft surfaces to shield the engine noise from the observers on the ground. However, the ability to predict the shielding effect and any new noise sources that arise from the high-speed jet flow interacting with a hard surface is currently limited. Furthermore, quality experimental data from jets with surfaces nearby suitable for developing and validating noise prediction methods are usually tied to a particular vehicle concept and, therefore, very complicated. The Jet-Surface Interaction Tests are intended to supply a high quality set of data covering a wide range of surface geometries and positions and jet flows to researchers developing aircraft noise prediction tools. The initial goal is to measure the noise of a jet near a simple planar surface while varying the surface length and location in order to: (1) validate noise prediction schemes when the surface is acting only as a jet noise shield and when the jet-surface interaction is creating additional noise, and (2) determine regions of interest for future, more detailed, tests. To meet these objectives, a flat plate was mounted on a two-axis traverse in two distinct configurations: (1) as a shield between the jet and the observer and (2) as a reflecting surface on the opposite side of the jet from the observer. The surface length was varied between 2 and 20 jet diameters downstream of the nozzle exit. Similarly, the radial distance from the jet centerline to the surface face was varied between 1 and 16 jet diameters. Far-field and phased array noise data were acquired at each combination of surface length and radial location using two nozzles operating at jet exit conditions across several flow regimes: subsonic cold, subsonic hot, underexpanded, ideally expanded, and overexpanded supersonic. The far-field noise results, discussed here, show where the jet noise is partially shielded by the surface and where jet-surface interaction noise dominates the low frequency spectrum as a surface extends downstream and approaches the jet plume.


Author(s):  
Andrew L. Bodling ◽  
Anupam Sharma

A study was done to investigate how boundary layer tripping mechanisms can affect the ability of a permeable surface FW-H solver to predict the far field noise emanating from an airfoil trailing edge. The far field noise in a baseline airfoil as well as the baseline airfoil fitted with fin let fences was analyzed. Two numerical boundary layer tripping mechanisms were implemented. The results illustrated the importance of choosing a permeable integration surface that is outside any high frequency waves emanating from the trip region. The results also illustrated the importance of choosing a boundary layer tripping mechanism that minimizes any extraneous noise so that an integration surface can be taken close to the airfoil.


2021 ◽  
Vol 149 (3) ◽  
pp. 1772-1790
Author(s):  
Yaxi Peng ◽  
Apostolos Tsouvalas ◽  
Tasos Stampoultzoglou ◽  
Andrei Metrikine

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