Porous Sound-absorbing Material Research Articles

Improvement of Sound-Absorbing Wool Material by Laminating Permeable Nonwoven Fabric Sheet and Nonpermeable Membrane

Thin sound-absorbing materials are particularly desired in space-constrained applications, such as in the automotive industry. In this study, we theoretically analyzed the structure of relatively thin glass wool or polyester wool laminated with a nonpermeable polyethylene membrane and a permeable nonwoven fabric sheet. We also measured and compared the sound-absorption coefficients of these samples between experimental and theoretical values. The sound-absorption coefficient was derived using the transfer matrix method. The Rayleigh model was applied to describe the acoustic behavior of glass wool and nonwoven sheet, while the Miki model was used for polyester wool. Mathematical formulas were employed to model an air layer without damping and a vibrating membrane. These acoustic components were integrated into a transfer matrix framework to calculate the sound-absorption coefficient. The sound-absorption coefficients of glass wool and polyester wool were progressively enhanced by sequentially adding suitable nonwoven fabric and PE membranes. A sample approximately 10 mm thick, featuring permeable and nonpermeable membranes as outer layers of porous sound-absorbing material, achieved a sound-absorption coefficient equivalent to that of a sample occupying 20 mm thickness (10 mm of porous sound-absorbing material with a 10 mm back air layer).

Analysis of noise characteristics of metal processing equipment

The management and prevention of industrial injuries among workers are crucial in the work environment. Industrial injuries occur in various forms and have diverse causes, and noise-induced hearing loss accounts for a significant proportion of workplace injuries. Therefore, this study aimed to measure the factory noise during engine-component (metal) processing for automobiles, where substantial noise-induced hearing loss is prevalent. The measurement results revealed that the 24-h equivalent continuous noise level (Leq) was approximately 83.8 dB(A), and the noise at two points was higher than the noise exposure standard of 89 dB(A). These points were identified as locations where 2,200- to 3,500-ton casting machines were positioned on both sides to melt iron to produce components. The noise generated from each machine is assumed to have combined at these points, resulting in elevated noise levels. The results were plotted on a noise rating (NR) curve. The NR values ranged from 81 to 83, surpassing the standard NR range of 60 to 70 that is commonly used in typical workplaces. The frequency band that determined the NR was 2 kHz. Therefore, measures such as the use of porous sound-absorbing materials should be considered to attenuate the frequency range based on the noise characteristics.

Preparation and Characterization of Waste Cotton Fabric Reinforced Polylactic Acid Green Composites with Multifunctional Properties in a Low-Carbon Process

The development and design of eco-friendly materials prove crucial for promoting the recycling of waste cotton textiles and reducing environmental pollution. In this study, waste cotton fabric (WCF) and polylactic acid (PLA) serve to produce cotton fabric-reinforced PLA composite material (CF/P). The CF/P is then integrated with traditional porous sound-absorbing materials to create a novel composite plate. This research highlights the potential of WCF reinforced plates for sound absorption and thermal insulation applications in the construction field of construction and reports the effects of variables such as hot pressing temperature, WCF mass fraction, and WCF layer alignment angle on the material properties. The optimum tensile strength, water absorption, and thermal conductivity of the prepared CF/P are 64.2 ± 1.8MPa, 1.98% ± 0.04%, and 0.03W/(m·K), respectively. By combining with porous sound-absorbing materials and modifying the layering structure of composite plates, its acoustic performance can be adjusted. The highest Sound Absorption Average (SAA) of plates with a multilayer composite structure is 0.67. Direct shaping through hot pressing diminishes the use of adhesives, thereby reducing costs and health hazards. This approach offers a practical and efficient solution for the recycling and repurposing of natural fibers.

Material Design and Performance Study of a Porous Sound-Absorbing Sound Barrier

A new type of porous sound-absorbing sound barrier was developed with quartz sand and self-developed polysiloxane resin. The forming process of the material was studied. The test specimens of the porous sound-absorbing sound barrier were prepared with different mesh numbers of quartz sand and different proportions of resin, and the void properties, compressive strength, durability, and acoustic performance were investigated. Based on the mix design results, it is suggested that 20-mesh quartz sand and a 10:1 mass ratio of quartz sand are used to prepare the porous sound-absorbing sound barrier. The durability study showed that the porous sound-absorbing sound-barrier material had good salt and alkali resistance, poor acid resistance, good water stability, and freeze–thaw stability. The laboratory acoustic test and practical engineering application results showed that the porous sound-absorbing sound barrier had excellent acoustic performance and good noise-reduction effects.

Research on the design and noise reduction performance of periodic noise barriers based on nested structure

The rapid development of highway transportation has led to a gradual deterioration of the sound environment along highways. The theory of periodic structures provides a new approach for the design of traffic noise barriers. However, the lack of practical numerical models and on-site experimental validation has hindered the widespread application of periodic structure sound barriers. This study investigates the noise reduction performance of nested structure periodic sound barriers. Results from semi-anechoic chamber tests demonstrate excellent wave attenuation at the air gap of the barrier, achieving a peak noise reduction of 16 dB without the addition of any sound-absorbing materials or treatment measures, particularly at local peaks in the highway noise spectrum. To enhance the noise reduction performance of nested structure periodic sound barriers, three optimization measures were explored: filling sound-absorbing materials inside the scattering elements, adding micro-perforated panels, and their combined effects. The results indicate that both porous sound-absorbing materials and micro-perforated panels can improve noise reduction effectiveness, especially outside the air gap. In the optimization design of nested structure periodic sound barriers, adding porous sound-absorbing materials inside the micro-perforated panels effectively enhances noise reduction within the air gap. Considering the abundance of abandoned w-beam guardrails in highway projects, which also meet the requirements of scattering elements, this study proposes the use of abandoned w-beam guardrails as scattering elements. This approach aligns with principles of cost-effectiveness and environmental sustainability, and it provides design guidance to promote the application of nested structure periodic sound barriers in traffic noise control.

Study on the properties of anorthite-based porous sound-absorbing materials prepared by steel slag and fly ash

The efficient utilization of solid wastes, such as fly ash and steel slag, has attracted significant attention across the globe. In this paper, these two kinds of waste materials are used to prepare porous sound-absorbing materials, so as to achieve efficient resource utilization and environmental protection, and promote green manufacturing and circular economy. In this study, steel slag and high-alumina fly ash were used as the primary raw materials to prepare green bodies via organic foam impregnation. Subsequently, a high-temperature sintering process was implemented to get the porous sound absorption material product from the green bodies. The effects of several factors, including the ratio of steel slag and fly ash, sintering temperature, and pore structure, on the sound absorption and mechanical properties of the product were investigated. Based on the anorthite region in the CaO–Al2O3–SiO2 ternary phase diagram region, the composition ratio of the material was designed. The composition and microstructure of the material were characterized by X-ray diffraction and scanning electron microscopy. From the results, with the increase of the ratio of fly ash and steel slag, the composition of low melting point substances in the system decreases, and the amount of liquid phase decreases, which weakens the pore blocking phenomenon inside the material, resulting in the increase of pore size and noise reduction coefficient of the material. Besides, higher sintering temperature tends to correlate to greater density and higher compressive and flexural strengths but lower porosity, and the sound absorption coefficient demonstrated a peak with respect to sintering temperature. Furthermore, when the reduction of polyurethane sponge body pore size was taken into account, the product's sound absorption coefficient also showed a peak. The optimal parameters for our porous materials are as follows: fly ash:steel slag = 48 : 25, polyurethane sponge pore size = 40 ppi, sintering temperature = 1160 °C at 1-h duration (bulk density = 573.98 kg/m3), compressive strength = 1 MPa, porosity = 79.35 %, and noise reduction coefficient = 0.47.

Enhanced broadband sound absorption of multi-layer composite material based on three-dimensional warp-knitted spacer fabric

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.

Sound-Absorbing, Thermal-Insulating Material Based on Poly(methylsiloxane) Xerogel and Cellulose Nanofibers

The automotive industry needs to improve energy efficiency rapidly to achieve carbon neutrality while creating a safe, secure, and comfortable driving environment for customers. Porous sound-absorbing materials and porous thermal insulators are typically used to satisfy these requirements despite limitations in mass and space. While these porous materials are similar, the microstructures they offer for high performance differ in the size and connectivity of their fluid phases, which enhances the difficulty of achieving excellent sound absorption and thermal insulation in the same material. In this study, a hydrophobic cellulose nanofiber–poly(methylsiloxane) xerogel composite was developed using computational microstructure modeling. This porous material has high porosity and excellent thermal insulation and sound absorption properties.

Preparation and Properties of Gradient Sound-Absorbing Composites with Waste Feathers

To make full use of waste feather resources, waste feather fiber/polybutanediol succinate gradient sound-absorbing composites were prepared by a hot-pressing process with waste feather fiber as a reinforcing material and polybutanediol succinate as a matrix material. It can be applied to construction and other fields. The influence of gradient waste feather fiber mass fraction, gradient material density, and gradient material thickness on the sound-absorbing performance was studied, and the sound-absorbing mechanism of the material was analyzed. To determine the average sound-absorbing coefficient, maximum absorbing coefficient, and noise reduction coefficient as the evaluation index, the gradient sound-absorbing composites with waste feathers were compared with market common porous sound-absorbing materials with polyester fiber and wool fiber. The maximum sound-absorbing coefficient of the gradient sound-absorbing composites with waste feathers was 0.860; the average sound-absorbing coefficient was 0.408; the noise reduction coefficient was 0.393; and the noise reduction grade was IV. The sound-absorbing band was wide, and gradient sound-absorbing composites with waste feathers can be applied over a wide range.

Stochastic modeling of porous sound absorbing materials using homogenization method and machine learning

This research introduces a novel approach to investigate porous sound absorbing materials using stochastic modeling techniques. The study employs the homogenization method and machine learning to predict the acoustic properties of porous materials. The homogenization method simplifies the analysis of microstructural properties in porous materials, while machine learning is a data analysis technique that utilizes algorithms to learn from data and make predictions. By integrating these methods, this study quantitatively assesses the impact of microscopic structural randomness on sound absorption properties. The study assumes that microstructural parameters are random variables and calculates the sound absorption coefficient through homogenization method. This dataset serves as input for machine learning. A Gaussian process regression model is developed using the dataset to evaluate the distribution of the sound absorption coefficient via the Gauss-Hermite quadrature method. The study implements Bayesian optimization, utilizing the variance of the resulting probability distribution as the acquisition function, to adaptively update the dataset. By iteratively performing these processes, the probability distribution of the sound absorption coefficient can be predicted efficiently and with high accuracy.

Predicting the effect of microstructural variations in porous sound absorbers on their sound absorption performance using the perturbation method

Noise reduction is one of the most important issues in various industries. Quantifying the variation in acoustic properties is an essential task to improve the quality of products. Porous sound-absorbing materials are commonly applied to reduce noise. Variations in the microstructure of porous materials have a significant impact on variations of sound absorption coefficient. Experimental methods have been used to predict manufacturing variability of sound-absorbing porous materials. However, they take a lot of time and cost. In this study, a perturbation method is applied to predict variations of sound absorption coefficient of sound-absorbing porous materials combined with the homogenization method based on an asymptotic expansion. Properties of microstructure of a sound-absorbing porous material, such as fiber diameter and cell size, are assumed to follow normal distribution and identify the expectation and variance from the observation of microscopic images obtained by scanning electron microscope. Calculated variability of sound absorption coefficient is compared with measured variability and they agree well in the frequency range of interest.

Experimental studies on the effect of ceiling materials on the sound environment of underpass concourse using the station simulator

Sound environments in railway stations are often noisy because of sound-reflective materials and many noise sources. Especially in underpass concourses, structure-borne sounds are radiated from the ceiling due to vibrations when trains pass by. This results in a high noise level, which often interferes with listening to the announcements. In this study, to examine interior materials that effectively reduce such noise in railway stations, the following measurements and laboratory experiments were carried out: 1) Field measurements of vibrations of the ceiling and environmental sound in stations in Tokyo. 2) Reproduction of vibrations and sounds in the station simulator (full-scale mock-up of a station building), under the four different types of ceilings. 3) Auditory tests to evaluate the noisiness of train passing sounds and environmental sounds, using reproduced sounds in the station simulator as test sounds. As a result, the ceiling with damping material was effective for structure-borne sound, while the ceiling with porous sound-absorbing material was effective for air-borne sound. This result suggests that it is important to consider the placement of ceiling materials according to the noise situations.

Acoustic performance of a multi-layer vehicle interior trim sound-absorbing material

This paper investigated the acoustic properties of a multi-layer vehicle interior trim acoustic material. In this study, a thin fiber layer was inserted between the vehicle carpet and the porous sound-absorbing material layer, and backed by the vehicle floor. The theoretical prediction method was based on the Johnson-Champoux-Allard (JCA) model, and the sound absorption coefficient of the multi-layer vehicle interior trim acoustic material was calculated by using the transfer matrix method (TMM). An impedance tube was used to measure the normal incidence sound absorption coefficient of the vehicle interior trim with different combinations of acoustical materials. The comparison of the theoretical and the experimental results showed that the sound absorption coefficient curves predicted using the JCA model are consistent with the measurement data across the mid and high-frequency range (500-6400 Hz). In addition, a car cabin Statistical Energy Analysis (SEA) model was developed and used to predict the effect of the acoustic properties of the multi-layer vehicle interior trim acoustic material. The results presented in this paper, are useful for enhancing vehicle interior acoustic design and refining vehicle cabin sound quality in future vehicles.

A mechanically adjustable acoustic metamaterial for low- frequency sound absorption with load-bearing and fire resistance

ABSTRACTBroadband sound absorption is limited to discrete noise with abrupt peaks in the spectrum. Here, we proposed a mechanically adjustable acoustical metamaterials (AAMM) for low-frequency sound absorption with deep-subwavelength (0.025λ), which integrates Helmholtz resonators and Fabry–Perot (FP) tubes by precise modular design. The calculation results based on the theoretical model demonstrate that the broad low frequency (from 100 Hz to 500 Hz) tunability of the composite adjustable sound absorbing materials. The adjustable design scheme is further verified by numerical simulation. Then a multi-impedance adjustment method is proposed to improve the local optimal defect and make it have quasi-perfect sound absorption effect in the range of 120 Hz–348 Hz. The sound absorbing material sample can withstand 2.7 tons of dynamic load and 1300° high temperature, presenting superior compression and fire resistance compared to conventional porous sound absorbing materials and membrane acoustic metamaterials. This research on assembled machine-adjustable sound absorption material enriches the conventional acoustic metamaterial design scheme, further improves the space utilization rate, and provides an effective solution for dealing with low-frequency complex variable noise.

Design and demonstration of composite mufflers based on dissipative and reactive units

We have proposed and validated a design of a composite muffler. By a combination of dissipative and reactive units with different operating mechanisms, the advantages of both structures are utilized to achieve high transmission loss (TL) from low to high frequency in the ventilation duct system. A dissipative muffler composed of porous sound absorbing materials (PSAM) is chosen for noise attenuation above 1000 Hz, and a reactive muffler composed of Helmholtz resonators is used to reduce the noise below 1000 Hz. The combination of the two can achieve a TL above 20 dB in the broadband range of 244–1600 Hz and up to 30 dB in the vast majority of the frequency band, demonstrating excellent noise reduction effect. The proposed composite muffler has great advantages in broadband noise reduction for ventilation systems.

A novel semi-analytical meshless method for the thickness optimization of porous material distributed on sound barriers

This paper presents a novel semi-analytical meshless method to optimize the thickness of porous material distributed on sound barriers, by employing the Burton–Miller-type singular boundary method in conjunction with the method of moving asymptotes. Firstly, the Delany–Bazley–Miki model is utilized to characterize the acoustic property of sound barrier with a porous sound-absorbing material. Then, the sensitivity formula with respect to the thickness of the porous layer is derived based on the analytical computation and the adjoint variable formula, in which the design variable is a thickness parameter distributed between [0,1]. Finally, the optimal thickness distribution is achieved by solving the optimization model using the method of moving asymptotes. Compared to traditional algorithms, the proposed new method is simple, accurate, easy-to-program, and free of mesh and integration. Numerical experiments demonstrate the feasibility and effectiveness of the proposed algorithm.

Acoustic optimization design of porous materials on sandwich panel under flow-induced vibration

In this study, porous sound-absorbing materials used as a lining in double-panel structure applications (such as high-speed train body structures) to limit flow-induced vibration interior noise were studied, and acoustic optimization design was performed. First, in the wavenumber domain, the cross-spectrum Corcos model was used to characterize the dynamic hydrodynamic pressure of turbulence. Biot’s theory is used to model the porous materials. The transmission loss (TL) of the sandwich panel were also determined based on the model superposition method. Three types of sandwich panel structures were considered: air–air (A–A), bonded-bonded (B–B), and bonded-air (B–A). The TL of the three structure types under hydrodynamic pressure was used to evaluate the suppression of flow-induced vibration interior noise in porous materials. The effects of flow velocity, thickness and density of the porous material, and three types of polyimide foam on the TL characteristics of the sandwich panel were investigated. The results show that the flow velocity has a significant influence on the TL of the sandwich panel. The TL of the sandwich panel decreases by 3–4 dB when the flow velocity increases by 100 km/h The B–A configuration has satisfactory sound insulation performance at most frequencies. With an increase in material thickness, the TL of the sandwich panel structure first increases and then decreases, and the material density mainly affects the TL of the structure at intermediate and high frequencies. Based on the objectives of maximizing the average transmission loss (TLavg) and minimizing the structural weight, the acoustic optimization design of the B–A structure was performed, and the balance between the two objective functions was achieved by a nondominated sorting genetic algorithm (NSGA-Ⅱ). The TLavg s of the sandwich panel structure increased by 5.2 dB when the total mass of the structure was decreased by 0.2 kg.

Estimating the airflow resistivity of porous materials in an impedance tube using an electroacoustic technique

Airflow resistivity is an essential parameter for characterizing air-saturated porous sound-absorbing materials theoretically and selecting sound-absorbing materials in practice. Although standardized methods can determine this non-acoustic parameter in the laboratory, many indirect alternative methods have been proposed to measure it. One of them is the technique presented in the 1980s by Ingard and Dear using a standing wave tube, a loudspeaker, and two microphones. This paper suggests an electroacoustic procedure based on a modification of the Ingard and Dear setup. Equations are derived through the transfer matrix method. After a simple calibration, the airflow resistivity of a material sample is indirectly estimated from the total electric impedance measured at the loudspeaker input connection terminals. Thus, implementing the proposed method is straightforward and inexpensive, since microphones and complex instrumentation are unnecessary. The method is tested by comparing measured values of the airflow resistivity of different material samples with those obtained through the Ingar and Dear approach and the ISO standardized method. Reasonably good agreement is observed, confirming the validity of the electroacoustic method.

Stochastic multiscale simulation of porous sound absorbing material based on adaptive bayesian quadrature

This presentation proposes a method to analyze porous sound absorbing materials by multiscale simulation with the adaptive Bayesian quadrature method. The homogenization method calculates equivalent physical acoustic properties from the microstructure of a porous material. This method is powerful in designing new porous materials because it can predict acoustic properties from arbitrary microstructures. On the other hand, it is difficult to consider the randomness of actual materials because of the assumption of periodic microstructures. We propose a method for quantifying uncertainty in acoustic properties by incorporating a Bayesian perspective into Gaussian process regression. Assuming the microscopic structure of porous material as random variables, the response obtained by the homogenization method is approximated by Gaussian process regression. Bayesian quadrature is used to calculate the statistical moments of the integral of the characteristic functions.An additional integration point that minimizes the variance of the integral is adaptively selected, and further responses are obtained using the homogenization method. Repeating this process shows that the integral of characteristic functions can be calculated accurately and efficiently, and their uncertainties can be quantitatively evaluated.

Numerical modeling and field test of sonic crystal acoustic barriers.

The rapid development of highway traffic has gradually deteriorated the acoustic environment along the line. Sonic crystal theory provides new ideas for traffic acoustic barrier. However, the lack of practical numerical models and field test verifications has restricted the promotion and application of sonic crystal acoustic barriers (SCABs). In this study, a field test was conducted to study the noise reduction performance of SCAB. The SCAB exhibits excellent wave attenuation in the band gap, when compared with concrete acoustic barriers (CABs) along highways, the noise reduction performance in the band gap is improved by 0.5-2.1dB(A), especially at the local peak in the highway noise spectrum. However, from the perspective of total insertion loss, CAB performs better than SCAB in all distances in the protected area. Next, the 3D FEM model is established based on the highway site and validated by the measured results. Compared with the commonly used 2D model, the 3D FEM model is more practical for considering the top diffraction and ground reflection, which influence the noise reduction performance a lot and need to be considered. To improve the noise reduction performance of SCAB, three types of optimization measures are explored. The gradient combination of scatterers can effectively improve the noise reduction effect in the low-frequency band gap, especially the high- to low-gradient layout. Besides, not only the porous sound-absorbing material but also the microperforated plates can improve the noise reduction effect, especially outside the band gap. The larger perforation rates and smaller apertures of microperforated plate are preferred in SCAB. This work provides field test support and promotes the application of SCABs in traffic noise control.