Compared with other sound-absorbing materials, spacer fabric with a “sandwich” structure has many advantages, such as light weight, an environmentally friendly production process, recyclability, versatility, low production cost and high efficiency, and strong designability of the organizational structure. However, as a porous sound-absorbing material, the effective sound-absorbing frequency band of the spacer fabric is concentrated at high frequencies, so the sound-absorbing performance needs to be improved. This paper establishes a Johnson–Champoux–Allard theoretical model by using a genetic algorithm to characterize the sound absorption performance of the three-dimensional (3D) warp-knitted spacer fabric. The theoretical model is validated through finite element analysis and experimental methods. Based on this model, two composite materials are designed to improve the sound absorption performance: (1) multi-layer spacer fabric composite material and (2) multi-layer spacer fabric-aluminum foil composite material. Numerical simulation and experimental results show that the sound absorption performance is significantly improved by widening the effective frequency band and increasing the sound absorption coefficient. The contribution of this paper is twofold. Firstly, the theoretical acoustic model of 3D warp-knitted spacer fabric is established. Secondly, the superior sound absorption performance is achieved by proposing multi-layer and multi-material composite material. The spacer fabric-based composite material has broad application prospects in the field of noise reduction and sound insulation. The paper provides a theoretical basis and more strategies for the acoustic and multifunctional design of spacer fabric in the future.
LuLZhuangHZhangY.Research on the change of heart rate variability under strong noise stimulation. J Investig Med2019;
67: A1–A6.
2.
LeeHMHuaYTWangZM, et al.
A review of the application of active noise control technologies on windows: challenges and limitations. Appl Acoust2021;
174: 107753.
3.
LiXHHeZYJiangAB.Research on a new type of sound absorber. Eng Construct Des2002;
2: 47–48.
4.
RenSWLiuYYSunW, et al.
Broadband low-frequency sound absorbing metastructures composed of impedance matching coiled-up cavity and porous materials. Appl Acoust2022;
200: 109061.
5.
JiangSCaiYDZhouX, et al.
Preparation and performance study of multilayer composite sound absorbing structure. J Text Res2012;
33: 20–25.
6.
ZhangWTXinFX.Coiled-up structure with porous material lining for enhanced sound absorption. Int J Mech Sci2023;
256: 108480.
7.
RyooHJeonW.Broadband sound absorption using multiple hybrid resonances of acoustic metasurfaces. Int J Mech Sci2022;
229: 107508.
8.
QuRHGuoJWFangY, et al.
Broadband acoustic meta-porous layer for reflected wave manipulation and absorption. Int J Mech Sci2022;
227: 107426.
9.
YakirKS.Noise absorption by a combination of woven and nonwoven fabrics. J Text Inst1991;
82: 500–503.
10.
KangYLeeELeeK, et al.
Acoustic properties of sound-absorbing polyester fabrics woven with thick staple and thin draw textured yarn for use in interior decoration. J Text Inst2019;
110: 202–210.
11.
ChenJHLiHQWangN, et al.
Fabrication of flexible sound absorption composite by constructing membrane with damping function on fabric. Appl Acoust2022;
191: 108666.
HassanzadehSZarrebiniMHasaniH.An investigation into acoustic properties of lightly needled Estabragh nonwovens using the Taguchi method. J Eng Fibers Fabrics2014;
9: 155892501400900303.
14.
AbedkarimiRHasaniHSoltaniP, et al.
Experimental and computational analysis of acoustic characteristics of warp-knitted spacer fabrics. J Text Inst2020;
111: 491–498.
15.
MiuXHGeMQ.Discussion on vibration characteristics of warp-knitted spacer fabric for lining. Text J2008;
29: 57–60.
16.
WuMJZhiCMengJG, et al.
3D spacer fabric structure for the prevention and care of pressure ulcers. IEEE Access2020;
8: 213512–213521.
17.
YuSDongMCJiangGM, et al.
Compressive characteristics of warp-knitted spacer fabrics with multi-layers. Compos Struct2021;
256: 113016.
18.
DehghanNPayvandyPTalebiS.Numerical simulation and image analysis of thermal behavior of spacer fabric. J Therm Anal Calorimet2023;
148: 1–12.
19.
LiuSMaXTMaYT, et al.
Review on the design and application of concrete canvas reinforced with spacer fabric. J Eng Fibers Fabrics2023;
18: 15589250231152591.
20.
JanarthananMGopalakrishnanMPrakashC, et al.
Aloe vera gel finished 3D spacer knitted sports textiles. Ind J Fibre Text Res2023;
48: 85–90.
21.
NguyenTHNgoBVNguyenTN, et al.
Flexible pressure sensors and machine learning algorithms for human walking phase monitoring. Micromachines2023;
14: 1411.
22.
Kolcavová SirkováBLenfeldováIHavlíčekK, et al.
Warp knitted spacer microfiber biomass carrier for wastewater treatment. J Ind Text2023;
53: 15280837231154533.
23.
ZhangKZhengLXuF.Compressive strength of copper yarn/Kevlar yarn 3D woven spacer hybrid composites and its application for multifunctional composite antennas. J Mater Sci2023;
58: 7303–7318.
24.
YeXHFangueiroRHuH, et al.
Application of warp-knitted spacer fabrics in car seats. J Text Inst2007;
98: 337–344.
25.
DiasTMonaragalaRNeedhamP, et al.
Analysis of sound absorption of tuck spacer fabrics to reduce automotive noise. Meas Sci Technol2007;
18: 2657.
26.
LiuYPHuH.Sound absorption behavior of knitted spacer fabrics. Text Res J2010;
80: 1949–1957.
27.
ArumugamVMishraRMilitkyJ, et al.
Thermo-acoustic behaviour of 3D knitted spacer fabrics. Fibers Polym2015;
16: 2467–2476.
28.
ChenSChenHXGaoXP, et al.
Sound absorption properties of polyurethane-based warp-knitted spacer fabric composites. Ind J Fibre Text Res J2017;
42: 299–306.
29.
Davoudabadi FarahaniMJamshidi AvanakiMJeddiAA.Sound absorption of warp knitted spacer fabrics based on knit structure and nanofiber enhancement. J Ind Text2022;
51: 1539–1557.
30.
QiLZZhiCMengJG, et al.
Highly efficient acoustic absorber designed by backing cavity-like and filled-microperforated plate-like structure. Mater Des2023;
225: 111484.
31.
BiotMA.Theory of propagation of elastic waves in a fluid‐saturated porous solid. II. Higher frequency range. J Acoust Soc Am1956;
28: 179–191.
32.
ChampouxYAllardJF.Dynamic tortuosity and bulk modulus in air‐saturated porous media. J Appl Phys1991;
70: 1975–1979.
33.
DelanyMEBazleyEN.Acoustical properties of fibrous absorbent materials. Appl Acoust1970;
3: 105–116.
34.
ChampouxYStinsonMR.On acoustical models for sound propagation in rigid frame porous materials and the influence of shape factors. J Acoust Soc Am1992;
92: 1120–1131.
35.
Alba FernándezJRey TormosRMDRamis SorianoJ, et al.
An inverse method to obtain porosity, fibre diameter and density of fibrous sound absorbing materials. Arch Acoust2011;
36: 561–574.
36.
AtallaYPannetonR.Inverse acoustical characterization of open cell porous media using impedance tube measurements. Can Acoust2005;
33: 11–24.
37.
SellenNGallandM-AHilbrunnerO. Identification of the characteristic parameters of porous media using active control. In: proceedings of the 8th AIAA/CEAS aeroacoustics conference & exhibit, Breckenridge, Colorado, 17–29 June 2002, paper no. AIAA 2002-2504, pp.1–10. VA: AIAA.
38.
DoutresOSalissouYAtallaN, et al.
Evaluation of the acoustic and non-acoustic properties of sound absorbing materials using a three-microphone impedance tube. Appl Acoust2010;
71: 506–509.
39.
MarezePHLenziA. Characterization and optimization of rigid-frame porous material. In: 18th international congress on sound and vibration, Brazil, 2011, pp.10–14. Auburn:IIAV.
40.
ISO 10534-2:1998. Acoustics-determination of sound absorption coefficient and impedance in impedance tubes: part 2:transfer-function method.
41.
LinPXuXMWuXL, et al.
Establishment and experimental verification of the sound absorption model of jute fiber felts. Noise Vibr Contr2021;
41: 232–236 + 266.
42.
CaiMZhangJYDongKP.Fitting of computational model of porous materials and simulation application. Acoust Found2021;
45: 12–16.
43.
RosenbergRS.Simulation of genetic populations with biochemical properties, Thesis, University of Michigan, 1967.
44.
BagleyJD.The behavior of adaptive systems which employ genetic and correlation algorithms, Thesis, University of Michigan, 1967.
45.
WongCCLinYHLeeSA, et al.
GA-based fuzzy system design in FPGA for an omni-directional mobile robot. J Intell Robot Syst2005;
44: 327–347.
46.
LiZJSuCYLiGL, et al.
Fuzzy approximation-based adaptive backstepping control of an exoskeleton for human upper limbs. IEEE Trans Fuzzy Syst2014;
23: 555–566.
47.
NaJZhangHDLianJX, et al.
Genetic algorithm-based online-partitioning BranchyNet for accelerating edge inference. Sensors2023;
23: 1500.
48.
RasyidHSoekamtoNHFirdausiahS.Modelling the anticancer activity of 4-alkoxy cinnamic analogues using 3D-descriptors and genetic algorithm-multiple linear regression (GA-MLR) method. J King Saud Univ Sci2023;
35: 102514.
49.
ChalmersG.Introducing ligand GA, a genetic algorithm molecular tool for automated protein inhibitor design. Sci Rep2022;
12: 20877.
