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    A Computationally-Efficient Numerical Model to Characterize the Noise Behavior of Metal-Framed Walls

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    Authors
    Arjunan, Arun
    Wang, Chang
    English, Martin
    Stanford, Mark
    Lister, Paul
    Issue Date
    2015-08-07
    
    Metadata
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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.
    Citation
    A Computationally-Efficient Numerical Model to Characterize the Noise Behavior of Metal-Framed Walls 2015, 5 (3):1414 Metals
    Publisher
    MDPI AG, Basel, Switzerland
    Journal
    Metals
    URI
    http://hdl.handle.net/2436/620729
    DOI
    10.3390/met5031414
    Additional Links
    http://www.mdpi.com/2075-4701/5/3/1414/
    Type
    Journal article
    Language
    en
    Description
    © 2015 The Authors. Published by MDPI. This is an open access article available under a Creative Commons licence. The published version can be accessed at the following link on the publisher’s website: https://doi.org/10.3390/met5031414
    ISSN
    2075-4701
    ae974a485f413a2113503eed53cd6c53
    10.3390/met5031414
    Scopus Count
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    Faculty of Science and Engineering

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