Porous materials are widely used for noise control treatments. Sound-absorb cotton is commonly used in the transportation industry such as automobiles and airplanes because of its excellent sound ...absorption performance. In this paper, two typical acoustical models were used to evaluate the sound absorption coefficient of sound-absorb cotton. By comparing the measurement results with those of acoustical models, suitable model for sound-absorb cotton can be found. Physical parameters are measured and calculated by experimentally and inverse methods. Porosity and density are directly measured, while airflow resistivity is measured by changing boundary conditions between sample and container. Tortuosity and characteristic length are identified by using material acoustic parameters identification software, when samples considered as limp and rigid skeleton-type respectively. When all parameters of the samples are obtained, then the sound absorption coefficient of the sample can be simulated by material acoustic simulation software. This paper, also investigated the effect on sound absorption coefficient by airflow resistivity due to different boundary conditions. The conclusion of the theoretical model applicable to sound-absorb cotton can be drawn from the results obtained, also proved the best method of airflow resistivity measure.
The use of natural fibers in the buildings and construction industries as a sustainable and biodegradable product with the aim of noise pollution control has attracted the attention of many ...researchers. This work aims to study the acoustic behavior of porous absorbers made of natural Kenaf fibers. To this end, samples of sound absorber were fabricated with thicknesses of 10–40 mm at two different bulk densities of 150 and 200 kg/m3, and their sound absorption coefficient (SAC) was determined by standing wave sound impedance tube at different air gap cavities. A hybrid numerical-mathematical model was also proposed to investigate the acoustic behavior of the samples. To this end, a code was developed to simulate the 3D virtual structure of samples, and flow resistivity was calculated by numerically solving the flow of air in the structures. Tortuosity and two characteristic lengths were obtained using an inverse method programmed in MATLAB®. These parameters were then imported into the Johnson-Champoux-Allard (JCA) model to predict SACs at different frequencies. Afterward, considering the cost and sound absorption average (SAA), samples were optimized using factorial design. Consequently, the acoustic behavior of the optimized acoustic panels was investigated in the reverberation room in terms of reverberation time and random absorption coefficient. Moreover, in order to provide aesthetically and artistically pleasing appearance, the samples were covered with spacer fabrics, and their sound absorption behavior was also studied.
The results revealed the promising sound absorption performance of Kenaf fibers. It was found that the SAC at low, mid, and high frequencies increases significantly with increasing the bulk density. The average of SACs for frequencies above 1250 Hz for samples of 40 mm thickness was found to be 0.95, while these values for samples of 30 and 20 mm thickness were respectively 0.85 and 0.7. The introduction of the air gap was found to improve the SAC at low-frequency bands and shift the peak of absorption toward low frequencies. Very good consistency was observed between the predicted and experimental data. The results of the statistical analysis suggested a thickness of 33 mm and a bulk density of 150 kg/m3 for the optimized panels. The results showed that the mean of SAC increased from 0.68 to 0.72 after covering the optimized panels with spacer fabrics.
•Normal and random acoustic absorption coefficient of the Kenaf fibers were studied.•The effects of sample thickness and airgap behind the samples were investigated.•A mathematical method for prediction of sound absorption coefficient was proposed.•JCA model have a good agreement with the experimental data.•The statistical analysis suggested for optimized acoustic panels.
•Effect of aggregate gradation on sound absorption ability of porous concrete was examined.•Effect of thickness on sound absorption ability of porous concrete was explored.•Influence of cement to ...aggregate ratio on sound absorption ability of porous concrete was analyzed.•Correlation between porosity and sound absorption ability was investigated.
Porous concrete (PC) is considered as an environmentally friendly pavement material due to its internal porosity. It has good functions such as: mitigate stormwater runoff, removal water pollutants, noise reduction, and mitigate urban heat island benefits. Many parameters have an effect on the sound reduction of PC, especially the porosity was often considered as the main factor affecting the sound absorption ability of PC. Therefore, thirty-six groups of porous concrete were selected to obtain different porosities of PC samples in this study. These groups include twelve kinds of aggregate gradation and three kinds of cement to aggregate (C/A) ratios. The selected concrete materials are mixed and cast on different thicknesses to study the influence of different mixtures on the sound absorption ability of PC using impedance tubes method with varied sound frequency (200 ~ 2000 Hz). In addition, the correlation between the sound absorption ability and the porosity of mixtures was investigated. The results show that the porosity, aggregate gradation, C/A ratio and pavement thickness have significant effects on the sound absorption performance for the examined PC mixtures.
The increase in coffee consumption has led to increased production of coffee waste. Methods to recycle coffee waste are constantly being researched. Coffee powder is a porous material that can ...effectively be used to absorb sound. In this study, sound-absorbing panels were developed using coffee waste combined with resin. A sound absorption characterization of the new material was performed. Then, the noise reduction potential using coffee-waste sound absorbers was investigated in cafés. A café has several noise sources, such as coffee machines, music, and the voices of people. The noise reduction effect was evaluated using the ODEON simulation software together with the improvement in both the clarity and reverberation time in a case study café. In the investigated room, the acoustic definition (D50) increased up to 0.8, while the reverberation time (RT) reduced to 0.6 s. The results of this study demonstrate that the noise generated in the café was reduced by recycling the coffee waste produced as a by-product in the same building. Finally, this study presents a new construction material manufactured through coffee waste that is in turn applied to cafés where the coffee waste itself is produced.
•The coffee waste was made of sound absorbing material and applied to the cafe.•The reverberation time was reduced to 0.7 s with CWSA.•The sound pressure level was reduced by 7 dB.•D50 of up to 0.8 was shown above 500 Hz.
The sound absorption performance of micro-perforated plate (MPP) is mainly restricted by four parameters: cavity depth, aperture, plate thickness and perforation rate. The concept of change rate of ...sound absorption coefficient is introduced, which is taken as the measuring standard to judge the influence of changing these parameters on the sound absorption performance of MPP. Generally, the parameter sensitivity of MPP sound absorber from large to small is as follows: cavity depth, aperture, perforation rate, plate thickness. According to the characteristic that the resonant frequency of MPP will shift when the cavity depth changes, combined with the acoustoelectric analogy principle, two kinds of single-layer honeycomb micro-perforated plate (HMPP) structures with different cavity depth are designed by using particle swarm optimization algorithm. Simulation and experimental results show that the structures can use their own different depth of honeycomb cores to achieve the purpose of broadband sound absorption. The feasibility of using particle swarm optimization algorithm to design broadband sound absorber is verified. In addition, through the contrastive analysis of the two structures, compared to the four regions HMPP, the experimental results of the seven regions HMPP are closer to the theoretical and simulation results, which is consistent with the characteristics of particle swarm optimization (PSO): the more optimization parameters are, the better the performance is.
Escalation in noise pollution due to urbanization and industrial development needs to be control by effective way. Different synthetic material shows excellent acoustic performance though synthetic ...material needs to be dealt with its high cost and environment harmful effect. This review highlights properties of natural fibers and waste (recyclable) material composite as acoustic material and significant parameters which affect acoustic performance. The natural material is an efficient alternative to this synthetic material due to their low cost and less environment effect. Waste material present in environment like rubber tire crumb, wooden scrap can be used in acoustic application. Also this paper emphasis on current research on different natural fiber materials are like jute, kenaf fibers, kapok fibers, arenga pinnata, coconut coir, sugarcane fiber, corn husk and their acoustic performance. It can be observed that latent qualities of these natural materials can be effectively used for acoustic application.
•The sound absorption mechanism.•Different sound absorbing materials with their sound absorption characteristics (compared with synthetic materials).•Different material properties along with experimental parameters which affects the acoustic performance.•Testing standards.
Porous concrete with expanded clay inherent porosity makes it an interesting and effective acoustic material, applied in numerous scenarios such as highways, airports and architectural structures, ...due to its capacity to mitigate noise pollution, by absorbing and damping sound waves. It is usually accepted that macroscopic properties such as open porosity, tortuosity or airflow resistivity of such materials play a fundamental role in the definition of the internal absorption process. This study explores the application of tailored artificial neural networks (ANNs) for predicting first the macroscopic properties (open porosity, tortuosity and airflow resistivity) and then the sound absorption coefficient (α) of these porous concrete mixtures, using only two input parameters (size class of the expanded clay and density of the test specimens). The results demonstrate the efficacy of the proposed ANN approach in accurately predicting macroscopic properties and the sound absorption coefficient of these mixtures, making it possible to obtain such important parameters in an effective and much simpler way.
•ANNs efficiently predict macroscopic parameters of porous concrete with just two input parameters specimens.•ANN model agrees with Horoshenkov-Swift, proving accurate in predicting properties and sound absorption coefficient.•This research provides an effective and simpler alternative, using ANNs, for porous concrete acoustic characterization.•The ANN model excels in predicting sound absorption for new data, optimizing concrete formulations reliably.
•Detailed air-void parameters were obtained by VG Studio.•Significant air-void parameters were found by correlation analysis.•Prediction models for the sound acoustic absorption coefficient were ...established.
In the study of the noise reduction performance of porous asphalt pavements, it is usually necessary to establish an acoustic model to develop the experiment and the theoretical analysis. However, although the traditional acoustic model is rational, there are some limitations in its accuracy and further research should be carried out. Through CT scanning, image processing and three-dimensional model building, the mesostructure characteristics of porous asphalt concrete (PAC) specimens were identified, the air-void parameters of PAC specimens were obtained, and a prediction model of the sound absorption coefficient and air-void parameters was established. In view of the difficulty involved in obtaining air-void parameters in engineering, a macroscopic prediction model of the sound absorption coefficient and air voids was established. The study showed that PAC specimens contained a large number of voids, most of which were smaller than 1 mm in equivalent diameter and were mostly distributed within 0.4–0.5 mm. Through correlation analysis, several parameters that highly correlated with the sound absorption coefficient were found out: measured air voids, reconstructed air voids, total air-void volume, average air-void volume, total air-void surface area and average air-void surface area. A prediction model for the sound absorption coefficient was established based on measured air voids, total air-void volume, average air-void volume, total air-void surface area, and average air-void surface area. In addition, a prediction model of the sound absorption coefficient and measured air voids was proposed for practical engineering purposes. The above two models can predict the sound absorption coefficient of PAC accurately, which may provide a reference in the study and application of PAC in noise reduction and impact energy absorption.
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•A system error analysis of sound absorption coefficient measurement is conducted.•Three error-causing factors slit, verticality and surface finish are proposed.•A simulation ...experiment by impedance tube method is established in ANSYS.•The effects of error-causing factors on sound absorption coefficient are studied.•The achieved conclusions have reference value for reducing the system errors.
Measuring the sound absorption coefficient by the impedance tube method is an important step in the research and development of the underwater sound-absorbing materials and structures. Generally, the experimental results are more persuasive than the theoretical results are. However, the system errors caused during the preparation and installation process of the sample to be tested are often ignored, which will affect the reliability of the experimental results. In order to reduce the system errors, three factors that may cause the system errors, including the slit length and width, the inclination angle and the surface finish, are proposed in this paper. First, a finite element (FE) simulation experiment environment of the underwater sound absorption coefficient measurement by the impedance tube method is established and the correctness of the FE algorithm is verified. Then the effects of the related parameters on the sound absorption coefficient of rubber are studied. When the sound absorption coefficient is within a certain acceptable error range, the restrictions of the related parameters are given. The achieved conclusions have reference value for reducing the system errors and improving the reliability of the experimental results.
Porous ZrC ceramics with uniform pore distribution were successfully prepared using evaporating solvent and hot-pressing sintering. A sintering model of porous ZrC ceramics was established under ...applied sintering pressure to illustrate the formation mechanism of controllable pore. As the sintering pressure increases, the porosity of porous ZrC ceramics decreases from 73.5% to 55.4%, and the corresponding compressive strengths increase from 5.67 MPa to 31.25 MPa and the thermal conductivities decrease at different temperature. Sound absorption measurement shows that as the median pore sizes of porous ZrC ceramics decrease from 12.48 μm to 4.83 μm, their optimum sound absorption frequency shifts from 2.7 kHz to 4.5 kHz, which is attributed to the fact that porous ceramics with different pore sizes have different responses to specific frequency bands.
