Sound Absorption Spectra Research Articles

Experimental study of granular particle stacks’ circumferential edge-constraint effect and the level- and time-dependent acoustical behavior

Granular materials, such as activated carbon, have shown advantages in absorbing low-frequency sounds, but they also exhibit significant nonlinearities. In this article, three unique types of granular particle stacks’ acoustical behavior are described and experimentally analyzed. First, when measuring the sound absorption spectra of particle stacks with varying depths and sample holder sizes, it was found that the frictional interaction with the tube circumferential wall can significantly affect the measurements, and a 1-D plane-wave acoustical model is only valid when the sample is thin. Secondly, when granular samples were tested with increasing excitation levels, the results indicated a decreased modulus and an increased damping. By further varying excitation’s level and bandwidth, a fluid-displacement-related metric was identified to describe this behavior. Thirdly, when measuring particle stacks over a longer period, the stack’s resonance peak gradually shifts to a higher frequency as the sample consolidates. This frequency shift was proportional to log(Time).

Numerical Simulation and Analysis of the Acoustic Properties of Bimodal and Modulated Macroporous Structures

In recent decades, cellular metallic materials have increasingly been used for control of reverberation and cutback. These materials offer a unique combination of expanded pores, high specific surfaces, improved structural performance, low weight, corrosion resistance at high temperatures, and a fixed/rigid pore network (i.e., at the boundaries, porosity does not change). This study examines the ability of sphere-packing models combined with numerical modelling and simulations to predict the acoustic properties of bimodal and modulated bottleneck-shaped macroporous structures that can realistically be achieved through liquid melts infiltration casting technique. The simulations show that porosity, openings, pore sizes and permeability of the material have significant effects on acoustics, and the predictions are consistent with experimental data substantiated in the literature. The modelling suggests that the creation of bimodal structures increases the capacity of the interstitial pores and pore contacts. The result is improved sound absorption properties and spectra, characterised by a pore volume fraction of 0.73 and a mean pore size to mean pore opening ratio of 4.8 for the 50% volume bimodal structure created at a 10 µm capillary radius. The importance of how pore structure-related parameters and existing fluid flow regimes can modulate the sound absorption performance of macroporous structures was revealed by numerical simulations of the sound absorption spectra for dual-porosity and dilated macroporous structures working from high-resolution tomography datasets. Sound absorption properties were optimised for structures having pore volume fractions between 0.68 and 0.76, maintaining the mean pore size to mean pore opening ratios between 4.0 and 6.0. Using this approach, enhanced and self-supporting macroporous structures may be designed and fabricated for efficient sound absorption in specific applications.

Research of the numerical simulation and machine learning backpropagation networks analysis of the sound absorption properties of cellular soundproofing materials

Cellular soundproofing materials have been critical for lowering incidence pressure waves, which have led to their wide application in studios, auditoria, automotive and aerospace applications, among others. This work, therefore, premiers the utilisation of machine learning backpropagation algorithm of artificial neural networks (ANN) to develop and train a series of datasets of sound absorption properties (noise reduction coefficient, sound absorption average, and area under the sound absorption spectrum) obtained via numerical modelling and simulations. ANN models were established to analyze these sound absorption properties in relation to several non–acoustical parameters associated with cellular materials, including their thickness. Modelling and simulation revealed the relative importance of non–acoustic parameters on sound absorption spectra for these structures. ANN models predicted output signals that almost overlapped with their respective “real” signals with correlation coefficients over 95 %. Model confidence was proposed to analytically predict sound absorption phenomena accurately for cellular materials characterized by permeability ranging between 0.5–3.0 × 10−09 m2 or viscous characteristic lengths ranging between 80 and 300 μm. Analytical models based on optimised synaptic weights, biases, non–acoustic parameters, and material thickness could assist manufacturers design soundproofing materials for noise reduction and reverberation control.

Design of acoustic absorbing metasurfaces using a data-driven approach

The design of acoustic metasurfaces with desirable properties is challenging due to their artificial nature and the large space of physical and geometrical parameters. Until recently, design strategies were primarily based on numerical simulations based on finite-element or finite-difference time-domain methods, which are limited in terms of computational speed or complexity. Here, we present an efficient two-stage data-driven approach for analyzing and designing membrane-type metasurface absorbers with desirable characteristics. In the first stage, a forward model consisting of a neural network is trained to map an input, comprising the membrane parameters, to the observed sound absorption spectrum. In the second stage, the learned forward model is inverted to infer the input parameters that produce the desired absorption response. The metasurface membrane parameters, which serve as input to the neural network, are estimated by minimizing a loss function between the desired absorption profile and the output of the learned forward model. Two devices are then fabricated using the estimated membrane parameters. The measured acoustic absorption responses of the fabricated devices show a very close agreement with the desired responses.

Programmable time-serial resonances for broadband spectrum matching

Spatially parallel and cascading acoustic liners are commonly used to treat duct noise. Their performance depends on the spectral match with source characteristics. Such liners rely on subtle geometrical and mechanical designs which are not difficult to adapt to different noise sources in a passive device. Here, we propose a temporal analogy, which is a shunted electromechanical diaphragm (SEMD) having different resonant frequencies in different time segments, namely, a time-serial resonator. Its sound absorption spectrum can be easily adapted by a program and yet the device functions passively. The acoustic impedance of the SEMD is determined by the shunt circuit, hence its resonant frequency and absorption peak. A multiple set of branch circuits are used to shunt the diaphragm. A MOSFET, which is a voltage-controlled ultrafast electronic switch, is introduced to cascade and switch each circuit branch. By activating circuit branches in a pre-defined time sequence, we obtain a series of resonance and the absorption which are effective for specific frequency bands at different time segments. When viewed over a long period, the averaged effective sound absorption spectrum is broadened and can be easily shaped by the working duty cycle of each circuit branch. Note that the switching voltage changes the circuit states without supplying power to the SEMD. Both numerical results and experimental demonstrations are presented. This study would open the new era of temporal design of acoustic liners.

Study of the acoustic performance of composites made from recycled cellulose acetate and polymer waste

The main objective of this study is to evaluate the acoustic behaviour of composites made by mixing cellulose acetate, from recycled cigarette butts, with polymers such as polyethylene and polypropylene, from recycled plastic containers and surgical masks, respectively. For this purpose, the spectra of the measured sound absorption coefficients and the calculated NRC and SAA indices of samples with thicknesses of 1.5, 3, 4.5, 6 and 7.5 cm are analysed. The results of both experiments reveal that the studied composites present a sound absorption capacity comparable to that of fibre glass and rock wool, being even more efficient for thicknesses greater than 4.5 cm. Moreover, the acoustical properties of the composites are predicted using the Miki model over the frequency range from 100 to 6400 Hz, showing very accurate predictions of the sound absorption spectrum at normal incidence.

Prediction of sound absorption performance of fibers coming from cigarette butts using a phenomenological model

This work deals with experimental and theoretical research about cellulose acetate fibers coming from cigarette butts. This waste, considered one of the most hazardous, numerous, and polluting waste all over the world, represents a high environmental risk. The possibility of using these fibers in sound-absorbing panels is evaluated. The acoustical properties are measured according to ISO 10534-2, and predicted using a phenomenological model over the frequency range from 100 Hz to 6400 Hz. This work includes the study of important non-acoustical properties for a better understanding of the porous structure. The Johnson-Champoux-Allard model provides good accuracy. The experimental results of the sound absorption spectrums show mean errors ranging from 1.1% to 9.0%. Moreover, it is possible to obtain non-acoustic properties of cellulose acetate fibers, which are difficult to obtain experimentally, using the Johnson-Champoux-Allard model and an inverse technique. The input parameters of this model are successfully obtained with low errors concerning the measurements (0.6–5.2% for porosity or 2.6–10.5% for flow resistivity). The results of the sound absorption spectrum at normal incidence of the cellulose acetate show very accurate predictions. The experimental results show values of sound-absorption coefficients close to 1.0 and sound absorption average ranging from 0.42 to 0.8. Therefore, these waste fibers are an alternative to the traditional porous absorbers, mainly composed of synthetic fibers or foams and petroleum-based resins.

Machine learning-assisted low-frequency and broadband sound absorber with coherently coupled weak resonances

An artificial broadband sound absorber composed of multiple components is of significant interest in the physics and engineering communities. The existence of coherently coupled weak resonances (CCWRs) makes it difficult to achieve optimal broadband sound absorption, especially in the presence of complex and aperiodic components. Here, we present and experimentally implement a machine learning-assisted subwavelength sound absorber with CCWRs using an improved Gauss–Bayesian model, which exhibits flexible, high-efficient, and broadband properties at low frequencies (<500 Hz). The proposed aperiodic structure comprises three parallel split-ring units, which enable a quasi-symmetric resonant mode to be generated and effectively dissipate energy because of the huge phase difference between each component at the coupled resonant frequency. With high algorithmic efficiency (no more than 80 iterations), the improved Gauss–Bayesian model inversely determines the optimal CCWRs, realizing a reconfigurable high sound absorption spectrum (α > 0.9) from 229 to 457 Hz. The optimal configuration of sound spectrum characteristics and the unit cell structure can be confirmed flexibly. Good agreement between numerical and experimental results verifies the effectiveness of the proposed method. To further exhibit broadband and multiparameter optimization, a nine-unit sound absorber (27 parameters) is numerically simulated and shown to achieve high acoustic absorption and a relatively broad bandwidth (44.8%). Our work lifts the restrictions on analytic models of complex and aperiodic components with coherent coupling effects, paving the way for combining machine learning with the optimal design of metamaterials.

The impact of microcellular structures on the sound absorption spectra for automotive exhaust performance mufflers

The role of microcellular structures on the sound absorption spectra of packed structures for automotive exhaust performance mufflers are presented herein, via numerical modelling and simulation. Numerical simulations involving the application of Attenborough’s empirical model are demonstrated to be a better predictor for the sound absorption properties for packed beds of near-spherical structures, with reasonable scatter, when compared to experimental data substantiated in contemporary literature. By varying the packing arrangement for packed samples and stacking with differential microcellular structures, improvements in the absorption properties were achieved – thereby highlighting the dependence of propagated pressure waves on the structural configuration, positioning and thickness of soundproofing materials. This approach could assist in the implementation of microcellular structures in reducing unwanted engine noise, reduction in packing weight and improved active product lifetime of miniaturized soundproofing package in automotive exhaust performance mufflers.

Numerical modelling and optimisation of reverberation cutback for packed spheres

Against multiple sources of experimentally measured data, Attenborough’s acoustic porous media has proven to be a better predictor of the reverberation cutback for packed beds of near-spherical structures compared to several other equivalent fluid models. Numerical predictions using Attenborough’s model were therefore used to illuminate the importance of key pore-structure related parameters of packed structures on their normal incidence sound absorption spectra. A parametric study was instigated to account for the influence of void fraction and particle size on predicted broadband sound absorption properties targeting permeability values in the range of 0.3 to 2.0×10−09m2. This approach could assist material manufacturers and acoustic engineers in the design of highly efficient and timely packed structures for applications-specific to sound absorption.

Characterizing and modelling the sound absorption of the cellulose acetate fibers coming from cigarette butts.

This work deals an experimental and theoretical research about the porous structure and the acoustic performance of cellulose acetate coming from the used cigarette filters. The porous structure was studied through the measurement and the prediction (using an inverse methodology) of some non-acoustic properties (bulk density, fiber size, porosity or flow resistivity and tortuosity). The sound absorption performance was evaluated by comparing experimental measurements using an impedance tube according to ISO 10534-2 with the best-fit approach obtained using some empirical models (Delany and Bazley, Garai-Pompoli, Komatsu and Miki). The accuracy of empirical models to obtain the flow resistivity was relatively high showing differences lower than 8% in the case of the Miki model or lower than 12% in the case of Delany & Bazley model. Regarding the absorption spectra, the errors found were lower than 9% for all the empirical models used in this work. These results showed that using relatively simple models such as empirical models were able to predict accurately the acoustic behaviour of the cellulose acetate. Finally, the sound absorption spectra obtained for cellulose acetate were compared with those obtained for fibrous materials currently used in building sector, suggesting that this fibrous waste could act as a possible substitute to traditional ones, due to the similar relatively high NRC values obtained for both type of fibrous absorber (NRC = 0.65).

The recycling of surgical face masks as sound porous absorbers: Preliminary evaluation

This paper presents the results of an experimental study on the acoustic efficiency of plastic surgical face masks. Since the very high number of disposable masks being used globally on a daily basis to face the Covid19 pandemic is posing new environmental risks, mainly connected to improper disposal, any possible improvements in the management of this waste stream is very important. In this work their potential use as sound porous absorber is discussed. Surgical face masks are mainly made of polypropylene fibers which show good acoustical properties. Their porous structure was studied through the measurement of some non-acoustic properties: bulk density, fiber diameter, porosity, flow resistivity and tortuosity. Moreover, the sound absorption performance of samples, made of scrapped face masks, with different thicknesses was evaluated using an impedance tube according to ISO 10534-2. The results obtained from the sound absorption spectra and two single indexes, Noise Reduction Coefficient and Sound Absorption Average showed a high sound absorption value over a frequency range of interest. Finally, the sound absorption spectra obtained for surgical face masks were compared with those obtained for fibrous materials currently used in building sector, suggesting that this fibrous waste could act as a possible substitute to traditional ones.

Sound Absorption Properties of Materials Based on Recycled Plastic Granule Mixtures

Abstract This article reports on impedance tube measurements of the sound absorption coefficient α (-) of selected recycled foam plastics, i.e., ethylene-vinyl acetate (EVA), polyvinyl chloride (PVC), polystyrene (PS), and polypropylene (PP), in different mixtures with a binding adhesive. The effect of the thickness of the sample on the sound absorption spectrum as well as the variability in absorption across the different samples of the same composition and thickness are discussed. For the EVA/ PP and PS/PP mixtures, the spectrum is characterized by two peaks that shift as the thickness is changing. These mixtures were also found to be the most absorbent across the whole audible frequency range.

Improvement of acoustic model and structural optimization design of porous asphalt concrete based on meso-structure research

In order to further reveal the influence of voids on sound absorption performance of porous asphalt pavement, more factors were considered to improve an acoustic model (Zwikiker-Kosten) and structural optimization design of porous asphalt concrete (PAC) based on meso-structure was conducted in this paper. Based on the Otsu algorithm, a square image segmentation algorithm was proposed through comparative analysis to obtain the meso-structure characteristic parameters of voids in porous asphalt concrete. Combined with the effect of airflow velocity on the flow resistance and the measured sound absorption spectrum, the relationship between void length and pavement thickness was quantified, and the Zwikiker-Kosten model of rigid skeleton porous material was improved and verified for the prediction of sound absorption performance of PAC. Besides, the influence of void parameters on the sound absorption performance of PAC was analyzed, the structural optimization design was carried out for the road dominated by small vehicles, and proposing pavement design parameters at last. The results show that the two-dimensional air voids obtained by square region segmentation algorithm have high accuracy, which can be used for the recognition and segmentation of voids in CT images; According to the comparative and correlation analysis, the improved Zwikiker-Kosten model can accurately predict the sound absorption performance of PAC; The peak sound absorption coefficient (SAC) of PAC is mainly affected by air voids, while its corresponding frequency is mainly affected by the length of voids. Moreover, the road dominated by small vehicles was recommended to adopt the following design parameters: void equivalent diameter, air void and pavement thickness should be limited to about 3 mm, 18% and 30 mm, respectively.

Prediction of the sound absorption behavior of nonwoven fabrics: Computational study and experimental validation

Prediction of acoustic characteristics of porous media from the microstructure is the first step in designing novel materials with enhanced acoustic properties. This paper aims to provide insights into the microstructure of nonwoven fabrics and demonstrate how it collectively dictates their acoustical macro-behavior. To this end, fibers of different fineness were spun on an industrial-scale compact melt spinning line. Fibers were then fed into a laboratory needle punching line to produce nonwoven fabrics. Microstructural properties of fabrics were obtained using morphological analysis of their 3D realistic images obtained using X-ray micro-computed tomography (µCT). The sound absorption coefficient (SAC) of samples was measured using a two-microphone impedance tube. Moreover, to investigate the effect of fabric microstructure on sound absorption behavior, virtual fibrous structures with different thicknesses, porosities, fiber diameters, and through-plane fiber orientations were simulated. Fluid resistivity was calculated by simulation of airflow through the microstructure of generated virtual structures and solving the Stokes equations. Finally, the sound absorption spectrum of nonwoven fabrics was predicted using the empirical model of Delany-Bazley-Miki, and the results were compared with experimental data. Very good agreement was observed between the results of the proposed model and the experimental data. The results indicated that for samples with the same porosity of 91% and fiber diameter of 16 µm, an increase in fabric thickness up to 2 cm leads to an increase in SAC, while further increase in thickness does not improve SAC at high-frequency bands. Moreover, with increasing fabric thickness, the SAC peak shifts from the high-frequency range to the low-frequency range. It was found that for samples with a thickness of 3 cm, decreasing fiber diameter from 32 µm to 16 µm enhances SAC at low- and medium-frequency ranges, while a further decrease in fiber diameter adversely affects the SAC. It was also found that there is an optimal porosity for a nonwoven fabric in view of maximizing its sound absorption performance. The results indicated that SAC decreases with decreasing the angle between the dominant fiber orientation and sound incidence direction. It was concluded that 3D uniform isotropic samples exhibit the highest SAC.

Optimization on metasurface-enabled sound absorbing panels

An optimization scheme based on the genetic algorithm is proposed to achieve a desired sound absorption spectrum using coupling of multiple resonators at a minimum thickness. The proposed optimization strategy considers the area of supercell, the number of unit cells in a supercell and the shape of each unit cell. Besides the optimization based on the mechanism of coupled resonances, topology optimization with thermoviscous losses being taken into account is further proposed to explore the absorption performance of metasurface-enabled sound absorbing panels. A simplified set of equations and a relatively simple interpolation for the distribution of design variables make the topology optimization an viable option.

Soundproofing flexible polyurethane foams: Effect of chemical structure of chain extenders on micro-phase separation and acoustic damping

In this study, a new high-performance acoustic damping flexible polyurethane foam (FPUF) was successfully designed and fabricated using synthesized linear saturated aliphatic polyester resin as polyol, methylene diphenyl diisocyanate, and ethylene glycol, monoethanolamine, and ethylenediamine as chain extenders and other reagents by one-shot bulk polymerization (isocyanate index = 100 and water content = 2.5%). The effect of the chemical structure of different chain extenders on micro-phase separation and acoustic damping properties of FPUFs were investigated using comprehensive characterization techniques such as atomic force microscopy (AFM), Fourier transform infrared spectroscopy (FT-IR), compressive strength, optical microscope, and‏ ‏impedance tube. It was indicated that the micro-phase separation degree of the FPUF matrix increased with increasing amine content in the chain extender structure due to the more bidentate hydrogen bondings formation between urea-urea groups. Also, by increasing micro-phase separation, average cell sizes decreased and compressive strength, open-cell contents%, cell walls roughness, and cell size distribution of FPUFs increased. According to the sound absorption spectra, it was found that sound absorption efficiency of FPUF containing DEA was higher than FPUF manufactured by EG by 13.23% in the range of 1500–4000 Hz due to the increase of the amine content of chain extenders. These results indicate that the acoustic properties of FPUFs can be explained with the synergistic actions of micro-phase separation including the viscoelastic behavior of hard-soft segments and increasing of airflow pathway leading to dissipating of the kinetic energy of sound waves. Finally, the results revealed that soundproofing FPUFs with an optimum condition for micro-phase separation and drainage flow can be a promising candidate for using as sound insulating materials in transportation industries such as airplanes, trains, etc.

Numerical modelling of the sound absorption spectra for bottleneck dominated porous metallic structures

Numerical simulations are used to test the ability of several common equivalent fluid models to predict the sound absorption behaviour in porous metals with “bottleneck” type structures. Of these models, Wilson’s relaxation model was found to be an excellent and overall best fit for multiple sources of experimental acoustic absorption data. Simulations, incorporating Wilson’s model, were used to highlight the relative importance of key geometrical features of bottleneck structures on the normal incidence sound absorption spectrum. Simulations revealed significant improvements in absorption behaviour would be achieved, over a “benchmark” structure from the literature, by maximising the porosity (0.8) and targeting a permeability in the range of 4.0 × 10−10 m2. Such a modelling approach should provide a valuable tool in the optimisation of sound absorption performance and structural integrity, to meet application-specific requirements, for a genre of porous materials that offer a unique combination of acoustic absorption and load bearing capability.

Enhancing the sound absorption performance of porous metals using tomography images

Commercially available porous metals are known to provide useful sound absorption, but it may be possible to modify their structures to improve their acoustical properties. Images from high-resolution X-ray computer tomography have been used to make pore-level characterization of Inconel, Recemat and Porvair foams. Based on these characterisations, flow simulations have been used to deduce parameters that determine the acoustical properties according to the Johnson-Champoux-Allard (JCA) and Delany-Bazley-Miki (DBM) models. While the DBM model enables a good agreement with measured normal incidence absorption coefficients for glass fiber materials, the JCA model enables a better agreement with data for metallic foams. The predicted sound absorption spectra were observed to depend mainly on the permeability of the porous medium being better for structures with the smallest openings and extremely poor for those with larger connectivity. It is shown that dilating the skeletal frame i.e. increasing the width of the ‘struts’ in a metallic foam should lead to more efficient sound absorption. It is the hope that this approach would lend itself well to use in the design of enhanced soundproofing porous metals.

Microstructures for lowering the quarter wavelength resonance frequency of a hard-backed rigid-porous layer

The frequency of the quarter wavelength resonance in the sound absorption spectra due to a thin hard-backed rigid-porous layer can be influenced by the design of its microstructure as well as its thickness. Microstructures considered include parallel arrays of identical cylindrical, slit-like or rectangular pores with deep sub-wavelength cross sections inclined to the surface normal, cylindrical annular pores, slits with log-normal width distributions, slits with cross sections that vary in a sinusoidal manner and slits with two distinct widths (dual porosity). Formulae that predict the bulk acoustical properties due to these microstructures are presented and used to explore the extent to which specific microstructures could be used separately or in combination to improve low-frequency absorption. Predicted normal incidence absorption coefficient spectra are compared using microstructural dimensions that would be feasible for 3D printing. The most effective microstructures are predicted to be slits with sinusoidally-varying widths, or with two distinct widths, inclined to the surface normal at 70°. The quarter wavelength layer resonances predicted in absorption coefficient spectra using these microstructures are comparable with those predicted for layers of the same thickness and bulk porosity having cylindrical pores with dead-end branches.