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Tone and Broadband Noise Separation from Acoustic Data of a Scale-Model Counter-Rotating Open RotorRenewed interest in contra-rotating open rotor technology for aircraft propulsion application has prompted the development of advanced diagnostic tools for better design and improved acoustical performance. In particular, the determination of tonal and broadband components of open rotor acoustic spectra is essential for properly assessing the noise control parameters and also for validating the open rotor noise simulation codes. The technique of phase averaging has been employed to separate the tone and broadband components from a single rotor, but this method does not work for the two-shaft contra-rotating open rotor. A new signal processing technique was recently developed to process the contra-rotating open rotor acoustic data. The technique was first tested using acoustic data taken of a hobby aircraft open rotor propeller, and reported previously. The intent of the present work is to verify and validate the applicability of the new technique to a realistic one-fifth scale open rotor model which has 12 forward and 10 aft contra-rotating blades operating at realistic forward flight Mach numbers and tip speeds. The results and discussions of that study are presented in this paper.
Document ID
20150000891
Acquisition Source
Glenn Research Center
Document Type
Presentation
Authors
Sree, David
(Tuskegee Univ. AL, United States)
Stephens, David B.
(NASA Glenn Research Center Cleveland, OH United States)
Date Acquired
January 30, 2015
Publication Date
June 16, 2014
Subject Category
Aerodynamics
Acoustics
Report/Patent Number
AIAA Paper 2014-2744
GRC-E-DAA-TN15617
Meeting Information
Meeting: AIAA/CEAS Aeroacoustics Conference
Location: Atlanta, GA
Country: United States
Start Date: June 16, 2014
End Date: June 20, 2014
Sponsors: Council of European Aerospace Societies, American Inst. of Aeronautics and Astronautics
Funding Number(s)
WBS: WBS 473452.02.03.07.06.01.09
Distribution Limits
Public
Copyright
Public Use Permitted.
Keywords
Acoustic Data
Scale-Model
Noise Separation
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