Modelling sound absorption of tunable double layer woven fabrics

The woven fabric is known to have micro structures inherently so that it can be employed as sound absorber with the same absorption mechanism as the micro-perforated panel (MPP) when it is backed up by an air cavity. In the context of multi-layer system, having high flow resistance at all layers do...

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Main Authors: Prasetiyo, Iwan, Muqowi, Eki, Putra, Azma, Novenbrianty, Melissa, Desendra, Gradi, Adhika, Damar Rastri
Format: Article
Language:English
Published: Elsevier Ltd. 2020
Online Access:http://eprints.utem.edu.my/id/eprint/24565/2/WOVEN-FABRICS-2020.PDF
http://eprints.utem.edu.my/id/eprint/24565/
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spelling my.utem.eprints.245652023-06-12T12:28:05Z http://eprints.utem.edu.my/id/eprint/24565/ Modelling sound absorption of tunable double layer woven fabrics Prasetiyo, Iwan Muqowi, Eki Putra, Azma Novenbrianty, Melissa Desendra, Gradi Adhika, Damar Rastri The woven fabric is known to have micro structures inherently so that it can be employed as sound absorber with the same absorption mechanism as the micro-perforated panel (MPP) when it is backed up by an air cavity. In the context of multi-layer system, having high flow resistance at all layers do not guarantee high sound absorption coefficients are achieved apart from narrow absorption bandwidth issue in the MPP. These have been extensively discussed in fibrous porous materials, but it is lacking for the woven fabrics, particularly on the analysis of the relationship of flow resistance for each layer to the sound absorption bandwidth. In this paper, a double-layer system of woven fabric is considered. Two cases are studied: a system with identical flow resistance and one with non-identical flow resistance. The Johnson-Champoux-Allard (JCA) formulation and the transfer matrix method are used to develop the prediction model. It is revealed that for a system with identical flow resistances, high flow resistance produces low amplitude of absorption coefficient, but with relatively wide frequency bandwidth. Lower flow resistance can improve the absorption amplitude, but with a dip in between two absorption peaks which degrades the half absorption bandwidth. This can be solved by having the combination of non-identical resistance between the layers. The selection of flow resistances together with the ratio of the air cavity depths can be used in tuning the performance of the double-layer woven fabric absorber. The experimental data show good agreement with the predictions. Elsevier Ltd. 2020-01 Article PeerReviewed text en http://eprints.utem.edu.my/id/eprint/24565/2/WOVEN-FABRICS-2020.PDF Prasetiyo, Iwan and Muqowi, Eki and Putra, Azma and Novenbrianty, Melissa and Desendra, Gradi and Adhika, Damar Rastri (2020) Modelling sound absorption of tunable double layer woven fabrics. Applied Acoustics, 157. pp. 1-11. ISSN 0003-682X https://reader.elsevier.com/reader/sd/pii/S0003682X19302695?token=1A87E4F4708BC559CBA13D9275E78A49424F9028285F95401940DA018937146B63A4123A83A2D2498BF493F45E267583 10.1016/j.apacoust.2019.107008
institution Universiti Teknikal Malaysia Melaka
building UTEM Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Teknikal Malaysia Melaka
content_source UTEM Institutional Repository
url_provider http://eprints.utem.edu.my/
language English
description The woven fabric is known to have micro structures inherently so that it can be employed as sound absorber with the same absorption mechanism as the micro-perforated panel (MPP) when it is backed up by an air cavity. In the context of multi-layer system, having high flow resistance at all layers do not guarantee high sound absorption coefficients are achieved apart from narrow absorption bandwidth issue in the MPP. These have been extensively discussed in fibrous porous materials, but it is lacking for the woven fabrics, particularly on the analysis of the relationship of flow resistance for each layer to the sound absorption bandwidth. In this paper, a double-layer system of woven fabric is considered. Two cases are studied: a system with identical flow resistance and one with non-identical flow resistance. The Johnson-Champoux-Allard (JCA) formulation and the transfer matrix method are used to develop the prediction model. It is revealed that for a system with identical flow resistances, high flow resistance produces low amplitude of absorption coefficient, but with relatively wide frequency bandwidth. Lower flow resistance can improve the absorption amplitude, but with a dip in between two absorption peaks which degrades the half absorption bandwidth. This can be solved by having the combination of non-identical resistance between the layers. The selection of flow resistances together with the ratio of the air cavity depths can be used in tuning the performance of the double-layer woven fabric absorber. The experimental data show good agreement with the predictions.
format Article
author Prasetiyo, Iwan
Muqowi, Eki
Putra, Azma
Novenbrianty, Melissa
Desendra, Gradi
Adhika, Damar Rastri
spellingShingle Prasetiyo, Iwan
Muqowi, Eki
Putra, Azma
Novenbrianty, Melissa
Desendra, Gradi
Adhika, Damar Rastri
Modelling sound absorption of tunable double layer woven fabrics
author_facet Prasetiyo, Iwan
Muqowi, Eki
Putra, Azma
Novenbrianty, Melissa
Desendra, Gradi
Adhika, Damar Rastri
author_sort Prasetiyo, Iwan
title Modelling sound absorption of tunable double layer woven fabrics
title_short Modelling sound absorption of tunable double layer woven fabrics
title_full Modelling sound absorption of tunable double layer woven fabrics
title_fullStr Modelling sound absorption of tunable double layer woven fabrics
title_full_unstemmed Modelling sound absorption of tunable double layer woven fabrics
title_sort modelling sound absorption of tunable double layer woven fabrics
publisher Elsevier Ltd.
publishDate 2020
url http://eprints.utem.edu.my/id/eprint/24565/2/WOVEN-FABRICS-2020.PDF
http://eprints.utem.edu.my/id/eprint/24565/
https://reader.elsevier.com/reader/sd/pii/S0003682X19302695?token=1A87E4F4708BC559CBA13D9275E78A49424F9028285F95401940DA018937146B63A4123A83A2D2498BF493F45E267583
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score 13.18916