Noisy neighbours : towards a hybrid prediction and testing process for sound insulating partitions

Whittle, GCR, Elliott, A, Meggitt, JWR ORCID: https://orcid.org/0000-0002-6665-2939, Wong-McSweeney, DBC and Parsons, R 2021, Noisy neighbours : towards a hybrid prediction and testing process for sound insulating partitions , in: Acoustics 2021, 11th-12th October 2021, Glasgow, UK/Online.

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Abstract

There are numerous methods for characterising sound insulating and impact noise reducing components and systems, each with their own advantages and disadvantages. Two of the predominant modelling techniques for prediction of transmission loss through partitions are finite element analysis (FEA) and the transfer matrix method (TMM). FEA has the advantage that one can model the entire system, taking into account most of the degrees of freedom. However, this advantage makes the method more computationally expensive, especially in the high frequencies where the short wavelength dictates the length of computation, as identified in[1] . The TMM is useful for understanding how sound propagates through a medium and makes the addition of more layers to the model an easier task. There is an assumption of each layer as infinite, meaning that final results can be unreliable, as discussed in[2] . It is accepted that due to the distinct advantages and disadvantages inherent to each method, no one method is applicable for every system and across a broad frequency range. This paper is concerned with the creation of a method for characterising complex systems accurately with a view to creating a tool for optimisation of soundproofing technologies.

Item Type: Conference or Workshop Item (Paper)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Acoustics 2021
Publisher: Institute of Acoustics (IOA)
Series Name: Proceedings of the Institute of Acoustics
ISBN: 9781906913397 (online); 9781713841500 (print)
ISSN: 1478-6095
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Depositing User: USIR Admin
Date Deposited: 14 Mar 2022 11:37
Last Modified: 14 Mar 2022 11:37
URI: https://usir.salford.ac.uk/id/eprint/63378

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