Bayesian inference of the flow resistivity of a sound absorber and the room's influence on the Sabine absorption coefficientsa

A Bayesian analysis is applied to determine the flow resistivity of a porous sample and the influence of the test chamber based on measured Sabine absorption coefficient data. The Sabine absorption coefficient measured in a reverberation chamber according to ISO 354 is influenced by the test chamber...

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Bibliographic Details
Published in:The Journal of the Acoustical Society of America 2017-03, Vol.141 (3), p.1711-1714
Main Authors: Jeong, Cheol-Ho, Choi, Sang-Hyeon, Lee, Ikjin
Format: Article
Language:English
Online Access:Get full text
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Summary:A Bayesian analysis is applied to determine the flow resistivity of a porous sample and the influence of the test chamber based on measured Sabine absorption coefficient data. The Sabine absorption coefficient measured in a reverberation chamber according to ISO 354 is influenced by the test chamber significantly, whereas the flow resistivity is a rather reproducible material property, from which the absorptive characteristics can be calculated through reliable models. Using Sabine absorption coefficients measured in 13 European reverberation chambers, the maximum a posteriori and the uncertainty of the flow resistivity and the test chamber's influence are estimated. Inclusion of more than one chamber's absorption data helps the flow resistivity converge towards a reliable value with a standard deviation below 17%.
ISSN:0001-4966
1520-8524
DOI:10.1121/1.4977601