An empirical model to predict sound absorption ability of woven fabrics. (15th December 2020)

• Record Type: Journal Article
• Authors: Cai, Zenong; Li, Xianhui; Gai, Xiaoling; Zhang, Bin; Xing, Tuo
• Is Part Of: Applied acoustics. Volume 170(2020)
• Publication Date: 2020-12-15
• Subjects: Sound-absorbing textile -- Woven fabrics -- Noise absorption; 00-01 -- 99-00; Acoustical engineering -- Periodicals; Periodicals; 620.2
• DOI: 10.1016/j.apacoust.2020.107483
• Languages: English
• ISSNs: 0003-682X

Abstract

Abstract: Well-designed thin lightweight fabrics can effectively replace bulky porous materials traditionally used in sound absorption. In this paper, a method based on Johnson-Champoux-Allard (JCA) model and multiple regression is proposed to predict the sound absorption effect of woven fabrics. Detailed 3D geometric models are built for a set of woven samples. Multiple regression method is conducted to obtain the empirical formulae of the parameters required by the JCA model, such as geometric tortuosity, flow resistivity, and porosity. Experimental results from the impedance tube test agree well with the numerical predictions.