Research at DLR towards airframe noise prediction and reduction

Dobrzynski, W.; Ewert, Roland; Pott-Pollenske, Michael; Herr, Michaela; Delfs, Jan

doi:10.1016/j.ast.2007.10.014

Cited by 50 publications

(25 citation statements)

References 16 publications

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“…method 1 that has previously been successfully applied to several aeroacoustic problems such as wind tunnel measurements of airfoil self noise 2 , jet-noise 3 , aircraft landing gear noise 4 , aircraft fly-over tests 5 and field measurements of wind turbine noise 6 . The CB method enables the estimation of the direction of sound propagation from sources (typically, assumed to be of a monopole nature) towards a microphone array by means of an appropriate Green's function 1 .…”

mentioning

confidence: 99%

An experimental application of aeroacoustic time-reversal to the Aeolian tone

Mimani

Prime

Moreau

et al. 2016

The Journal of the Acoustical Society of America

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This paper presents an experimental application of the aeroacoustic Time-Reversal (TR) source localization technique for studying flow-induced noise problems and compares the TR results with those obtained using Conventional Beamforming (CB). Experiments were conducted in an Anechoic Wind Tunnel for the benchmark test-case of a full-span circular cylinder located in subsonic cross-flow wherein the far-field acoustic pressure was sampled using two Line Arrays (LAs) of microphones located above and below the cylinder. The source map obtained using the signals recorded at the two LAs without modeling the reflective surfaces of the contraction-outlet and cylinder during TR simulations revealed the lift-dipole nature of aeroacoustic source generated at the Aeolian tone; however, it indicates an error of th 3 20 of Aeolian tone wavelength in the predicted location. Modeling the reflective contraction-outlet and cylinder during TR was shown to improve the focal-resolution of the source and reduce side-lobe

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mentioning

confidence: 99%

An experimental application of aeroacoustic time-reversal to the Aeolian tone

Mimani

Prime

Moreau

et al. 2016

The Journal of the Acoustical Society of America

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“…On this basis, new combinations of modeled (existing) airframes and engines, for which input data are missing or which are not yet flying in such combination, can be established. A further refinement to detailed modeling of single sound sources, as done in [34], is still challenging, especially with the scope to cover a wide range of aircraft types with different dimensions [40]. However, this was beyond the scope of the study, where the objective was to develop a general aircraft noise emission model to reliably predict the total sound emission and the contributions from airframe and engine sources separately.…”

Section: Discussionmentioning

confidence: 99%

Aircraft Noise Emission Model Accounting for Aircraft Flight Parameters

Zellmann

Schäffer

Wunderli

et al. 2018

Journal of Aircraft

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Today's aircraft noise calculation programs either use simple sound source descriptions with few input parameters or highly sophisticated models with input parameters, which are difficult to obtain. To fill the gap between these two approaches, an aircraft noise emission model based on regression of measured noise with aircraft flight parameters is presented. To find a reasonable compromise between the degree of detail and number of required flight parameters, an extensive data exploration was conducted. The most relevant parameters were incorporated in two multiple linear regression models, one for airframe and one for engine noise sources. An iterative method allowed fitting both regression models to aircraft flyover measurements. In total, aircraft noise emission models for 19 aircraft types were established, which underlines the general applicability of the modeling approach to turbofan-powered aircraft. Example comparisons between measurements and model predictions for two aircraft types revealed that the model accurately reproduces directivity and spectra for different flight configurations. In addition, it is suitable for the assessment and optimization of noise abatement procedures.

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“…Typically, the vibration frequency band is from 0.1 Hz to 15 kHz. 33 It can be seen that this frequency band is almost the same as that of the impact-induced elastic wave, which means it is an important type of noise that has to be considered. In this research, the superposition of 50 Hz, 1 kHz, and 10 kHz vibrations are chosen to be the noise.…”

Section: Evaluation Under Environmental Noisementioning

confidence: 97%

An improved two-dimensional multiple signal classification approach for impact localization on a composite structure

Zhong

Yuan

2015

Structural Health Monitoring

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Efficient impact monitoring techniques are important to be researched to ensure the safety of in-service composite structures. Multiple signal classification-based method is a new promising method. This method uses small aperture sensor array arrangement instead of sparse sensor arrangement. It has the advantage of easy sensor array arrangement. By processing the whole sensor array outputs using the multiple signal classification algorithm, transfer function and material property of the structure are not needed. Although some researches have shown the potential of this new method, most of the current researches have been performed based on the far-field assumption on aluminum structures. In engineering applications, composite structures are the main structures which need impact monitoring. Deep research needs to be addressed. Aiming at these problems, an improved two-dimensional near-field multiple signal classification processing algorithm is presented for impact localization on composite structure in this article. The proposed method can simultaneously estimate the impact occurring direction and distance. A uniform carbon fiber composite plate and a real aircraft oil tank made of carbon composite structure with varied thickness are adopted to evaluate the presented method. To deal with the anisotropy performance of the complex composite, the two-dimensional multiple signal classification processing algorithm is also improved by taking into account the existing anisotropy performance.

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Research at DLR towards airframe noise prediction and reduction

Cited by 50 publications

References 16 publications

An experimental application of aeroacoustic time-reversal to the Aeolian tone

An experimental application of aeroacoustic time-reversal to the Aeolian tone

Aircraft Noise Emission Model Accounting for Aircraft Flight Parameters

An improved two-dimensional multiple signal classification approach for impact localization on a composite structure

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