Arjunan, Arun, Wang, Chang, English, Martin, Stanford, Mark and Lister, Paul (2015) A computationally-efficient numerical model to characterize the noise behavior of metal-framed walls. Metals, 5 (3). pp. 1414-1431. ISSN 2075-4701

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Abstract

Architects, designers, and engineers are making great efforts to design acoustically-efficient metal-framed walls, minimizing acoustic bridging. Therefore, efficient simulation models to predict the acoustic insulation complying with ISO 10140 are needed at a design stage. In order to achieve this, a numerical model consisting of two fluid-filled reverberation chambers, partitioned using a metal-framed wall, is to be simulated at one-third-octaves. This produces a large simulation model consisting of several millions of nodes and elements. Therefore, efficient meshing procedures are necessary to obtain better solution times and to effectively utilise computational resources. Such models should also demonstrate effective Fluid-Structure Interaction (FSI) along with acoustic-fluid coupling to simulate a realistic scenario. In this contribution, the development of a finite element frequency-dependent mesh model that can characterize the sound insulation of metal-framed walls is presented. Preliminary results on the application of the proposed model to study the geometric contribution of stud frames on the overall acoustic performance of metal-framed walls are also presented. It is considered that the presented numerical model can be used to effectively visualize the noise behaviour of advanced materials and multi-material structures.

Item Type:	Article
Keywords:	numerical analysis; metal framed walls; vibro-acoustics; sound insulation; sound transmission
Schools and Departments:	School of Engineering and Informatics > Engineering and Design
Subjects:	T Technology T Technology > TA Engineering (General). Civil engineering (General) T Technology > TA Engineering (General). Civil engineering (General) > TA0365 Acoustics in engineering. Acoustical engineering
Depositing User:	Chang Wang
Date Deposited:	09 Nov 2015 09:22
Last Modified:	03 Jul 2019 02:06
URI:	http://sro.sussex.ac.uk/id/eprint/57771

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