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On Acoustic Multi-Port Characterisation Including Higher Order Modes
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Marcus Wallenberg Laboratory MWL.
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Marcus Wallenberg Laboratory MWL.
KTH, School of Engineering Sciences (SCI), Aeronautical and Vehicle Engineering, Aerodynamics.
2016 (English)In: Acta Acoustica united with Acustica, ISSN 1610-1928, E-ISSN 1861-9959, Vol. 192, no 5, 834-850 p.Article in journal (Refereed) Published
Abstract [en]

Methods to design test-procedures for acoustic multi-ports in ducts with a focus on pressure sampling positions for accurate modal decomposition are demonstrated. Acoustic fields up- and downstream of an in-duct acoustic element are excited by external sources and decomposed into transmitted and reflected aeroacoustic modal pres- sure amplitudes in order to first determine the acoustic scattering of the element. Secondly, the determination of the element source strength requires tests with no external sources, but with known terminations and scattering data. Unfavourable source and sensor positions lead to mode coupling and to ill-conditioned or even singular decomposition matrices, which results in high amplifications of uncertainties within the wave decomposition. An unoptimised but over-determined assembly is compared with a setup containing a minimum of sensors but with optimised positions. Lower uncertainty amplification, despite the usage of fewer sensors, is achieved for most frequencies, especially after the cut-on of t he higher order acoustic modes. A genetic algorithm (GA) is used to achieve this optimised setup by minimising the condition number of the decomposition matrix, which is a multi-dimensional optimisation problem with numerous local minima. To estimate the stability of the optimised configuration, a Monte-Carlo Method (MCM) is deployed to introduce normal distributed complex pressure un- certainties into the decomposition. In order to estimate the wave number, different approaches are compared - namely the classical non-dissipative wav e number estimate, an extended Kirchhoff method for viscous-thermal damping and an eigenvalue solution of the Linearised Navier Stokes Equations by Dokumaci. The presented de- composition method is not only applicable to measurement data but is equally useful to post-process results from numerical computation.

Place, publisher, year, edition, pages
2016. Vol. 192, no 5, 834-850 p.
Keyword [en]
multi-port, acoustic, acoustic duct modes, aeroacoustic, duct-acoustic, optimization, Monte Carlo, Genetic Algorithm, acoustic Measurements, orifice flow
National Category
Mechanical Engineering
Research subject
Aerospace Engineering
Identifiers
URN: urn:nbn:se:kth:diva-192482DOI: 10.3813/AAA.918998OAI: oai:DiVA.org:kth-192482DiVA: diva2:968884
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IDEAL VENT
Note

QC 20160916

Available from: 2016-09-13 Created: 2016-09-13 Last updated: 2016-09-16Bibliographically approved

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Sack, StefanMats, AbomEfraimsson, Gunilla
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Linné Flow Center, FLOWMarcus Wallenberg Laboratory MWLAerodynamics
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