In-flight Sound Measurements: A first Overview

Spehr, Carsten; Hennings, Holger; Buchholz, Heino; Bouhaj, Mohamed; Haxter, Stefan; Hebler, Anne

doi:10.2514/6.2012-2208

Cited by 18 publications

(11 citation statements)

References 9 publications

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“…Here, surface pressure measurement data from several flight test campaigns with DLR's A320 Advanced Technology Research Aircraft (ATRA) are used for this evaluation. Flight tests are in parts documented by Spehr et al 2 Forerunner work on this database by Haxter and Spehr 3-5 focused on the cross-spectral analysis in selected smaller regions of the fuselage, whereas the current contribution is dedicated to the spectral characteristics (like spectral peak and shape) of the point spectra at arbitrary fuselage positions. Corresponding cabin noise measurements results were reported by Hu et al, 6,7 to complete the picture.…”

Section: Nomenclaturementioning

confidence: 99%

Fuselage Excitation During Cruise Flight Conditions: Measurement and Prediction of Pressure Point Spectra

Klabes

Appel

Herr

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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In the last fifty years many semi-empirical models to predict surface pressure fluctuations beneath turbulent boundary layers (TBL) have been developed for a large variety of test conditions. Nowadays, the relevance of the TBL as a source of cabin interior noise is steadily increasing, due to quieter aircraft engines. The possibility of predicting surface pressure auto-spectra with the various publicly available semi-empirical models at several positions on the fuselage of DLR's Advanced Technology Research Aircraft (ATRA) is investigated. A large validation database was used, involving in-flight measurements at different flight levels (FL) and Mach numbers, applying two different sensor types. Predictions were performed based on semi-empirically estimated TBL parameters (partly included in the different models) and, additionally, based on TBL properties that were extracted from CFD simulations. This procedure served to identify different sources of error in the prediction. Overall, it is shown that today's models provide a large (> 10 dB) scatter among the predicted spectra. Even the most suitable approaches are not generally applicable to all relevant positions at the fuselage. Particularly in regions with strong pressure gradients and high turbulence kinetic energy measured auto-spectra cannot be reproduced with sufficient accuracy. This indicates the need for more universally applicable CFD-and CAA-based surface pressure prediction methods.

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Section: Nomenclaturementioning

confidence: 99%

Fuselage Excitation During Cruise Flight Conditions: Measurement and Prediction of Pressure Point Spectra

Klabes

Appel

Herr

et al. 2015

21st AIAA/CEAS Aeroacoustics Conference

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“…The main purpose of the flight test was to qualify and quantify the main sources of cabin noise as well as the transfer paths to the passengers under real flight condition. 22 The flight test setup and the outcomes of the flights from 2011 were published by Spehr et al [22][23][24] and Hu et al 25 In addition to the data described in the aforementioned publications, the flight test carrier ATRA was equipped with flush mounted microphones along the fuselage outer surface. The purpose of these surface microphones was to record the noise caused by the TBL excitation of the fuselage and by the engines.…”

Section: Methodsmentioning

confidence: 99%

RANS/CAA based Prediction of Jet Mixing Noise in Cruise Flight

Appel

Rossignol

Klabes

et al. 2014

20th AIAA/CEAS Aeroacoustics Conference

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“…Spatial coherence of turbulent boundary layer pressure fluctuations has been investigated on an Airbus model A320 aircraft at a Mach number of M¼0.78 and flight altitude of 10,668 m (FL 350) [22,23]. The coherence lengths of turbulent structures are extracted both parallel and perpendicular to the flow direction at three dummy windows located approximately 1 m in front of the wing.…”

Section: -D Evaluation Of Turbulent Boundary Layer Pressure Fluctuatmentioning

confidence: 99%