Johnson Champoux Allard Model Research Articles

Synthesis of Highly Porous Graphene Oxide-PEI Foams for Enhanced Sound Absorption in High-Frequency Regime.

High-frequency noise exceeding 1 kHz has emerged as a pressing public health issue in industrial and occupational settings. In response to this challenge, the present study explores the development of a graphene oxide-polyethyleneimine (GO-PEI) foam (GPF) featuring a hierarchically porous structure. The synthesis and optimization of GPF were carried out using a range of analytical techniques, including Raman spectroscopy, scanning electron microscopy (SEM), Braunauer-Emmett-Teller (BET) analysis, X-ray diffraction (XRD), and Fourier-transform infrared spectroscopy (FT-IR). To evaluate its acoustic properties, GPF was subjected to sound absorption tests over the 1000-6400 Hz frequency range, where it was benchmarked against conventional melamine foam. The findings demonstrated that GPF with a GO-to-PEI composition ratio of 1:3 exhibited enhanced sound absorption performance, with improvements ranging from 15.0% to 118%, and achieved a peak absorption coefficient of 0.97. Additionally, we applied the Johnson-Champoux-Allard (JCA) model to further characterize the foam's acoustic behavior, capturing key parameters such as porosity, flow resistivity, and viscous/thermal losses. The JCA model exhibited a superior fit to the experimental data compared to traditional models, providing a more accurate prediction of the foam's complex microstructure and sound absorption properties. These findings underscore GPF's promise as an efficient solution for mitigating high-frequency noise in industrial and environmental applications.

Acoustic and thermal performance of wood strands-rock wool-cement composite boards as eco-friendly construction materials

With a growing emphasis on eco-friendly building materials, wood strands-rock wool-cement boards (WRCB) offer a promising solution due to their composition of renewable wood fibers and cementitious binder. This study delves into the intricate balance between sound absorption, thermal insulation, and cost-effectiveness of WRCB, all of which are crucial factors shaping indoor comfort, energy efficiency, and the economic viability of constructions. WRCB incorporating wood strands, Portland cement, rock wool, and calcium chloride were manufactured at various thicknesses (20–60 mm) and densities (400, 500, and 600 kg/m³). The WRCB exhibited sound absorption average (SAA) and effective thermal conductivity (Keff) values ranging from 0.28 to 0.56 and 0.285–0.381 W/(mK), respectively. These results underscore the remarkable SAA and Keff of the panels, showcasing their potential as sustainable construction materials. Notably, WRCB with thicknesses ranging from 30 mm to 50 mm and densities of 400–500 kg/m³ exhibited nearly ideal absorption levels between 1000 and 2000 Hz, indicating their practical suitability for speech-related scenarios in architectural environments. The utilization of the Response Surface Methodology allowed the optimal conditions for maximizing SAA while simultaneously minimizing Keff and cost to be identified through the optimization process. A density of 452.8 kg/m³ and a thickness of 37.8 mm were determined as the optimal parameters. Under these conditions, the resultant SAA reached 0.554, with a corresponding cost of 1724 IRR and Keff of 0.317 W/(mK). The results also demonstrated the significant impact of thickness and density on the acoustic and thermal performance of the WRCB. The acoustic performance of WRCB was further analyzed through predictive modeling using the Johnson-Champoux-Allard (JCA) and Delany-Bazley (DB) models. The results revealed that the JCA model exhibited superior predictive accuracy compared to the DB model.

Wood chip sound absorbers: Measurements and models

Normal incidence absorption coefficient spectra of samples made from glued wood chips have been measured for various mesh sizes, bulk densities, thicknesses, and air gaps. Increasing thickness introduces additional layer resonance peaks and shifts the initial peak towards lower frequencies. The wood chip samples composed of the smallest mesh sizes were found to offer the highest sound absorption, comparable with that of the same thickness of materials made from synthetic fibers. Measured absorption spectra are compared with predictions of four models for the acoustical properties of rigid porous media. These include a model for slanted parallel identical uniform slits (SS), the Johnson-Champoux-Allard (JCA) and Johnson-Champoux-Allard-Lafarge (JCAL) models for arbitrary pore structures, and model for a non-uniform pore size distribution (NUPSD). Porosity and flow resistivity values have been determined non-acoustically. However, the tortuosity and characteristic lengths required for the JCA model have been obtained by fitting the measured absorption spectra. The thermal permeability required for the JCAL model has been deduced indirectly from the fitted tortuosity through a relationship with standard deviation of the pore size distribution due to the NUPSD model. JCAL and JCA models give the best agreement overall, but predictions of the SS and NUPSD models that use only the fitted tortuosity in addition to measured porosity and flow resistivity are found to give comparable agreement with data for many samples. SS and NUPSD predictions are improved by increasing the tortuosity values compared with those obtained by fitting the JCA model. The study should encourage the creation of sustainable sound-absorbing materials from wood chip wastes.

Adapting a phenomenological model for predicting acoustical behaviour of Camellia sinensis/Ananas comosus/E-glass fibre-blended epoxy hybrid composites

Developing a hybrid phenomenological model for predicting the sound absorption coefficient of a pineapple leaf fibre/waste tea leaf fibre/glass fibre/epoxy-based natural fibre-reinforced hybrid composites is the predominant topic of this article. Phenomenological models excel at extrapolating characteristic impedance and wave number whereas empirical models require fewer inputs but overlook wave propagation in pores. Existing models apply only to single-fibre-reinforced composites, necessitating the creation of a hybrid model for hybrid composites. The developed hybrid Zwikker–Kosten and Johnson–Champoux–Allard model shows good agreement with experimental data across the frequency range, with standard deviations of 0.001–0.029 and percent deviations of 1.11%–11.43%. The overall noise reduction coefficient between the model and experiments is 0.31 vs. 0.30, with a 3.33% deviation. Furthermore, the application of alkali treatment increased the surface roughness which in turn, enhanced the sound absorption capabilities of these composites. The increased fibre roughness also amplified friction between fibres and sound waves, resulting in higher sound absorption coefficients. In addition, X-ray diffraction, thermal stability (thermogravimetric analysis and differential scanning calorimetry), and scanning electron microscopy examinations were performed on the designated composition (5% by weight of pineapple leaf fibre and 25% by weight of waste tea leaf fibre) of the pineapple leaf fibre/waste tea leaf fibre/glass fibre/epoxy-based natural fibre-reinforced hybrid composite.

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.

Determination of the characteristic impedance and the complex wave number by five different approaches

This study presents several methods to determine the characteristic impedance and the complex wave number of porous materials. These methods include the two-cavity method by Utsuno et al., the two-thickness method by Dunn and Davern, the four-microphone transfer-matrix method by Song and Bolton, the empirical method by Miki and theoretical calculation by the inverse method of Johnson-Champoux-Allard (JCA) model. Glass wool and polyester materials are used to compare different approaches. The results indicate a clear correlation among all methods. The theoretical calculation based on the inverse method of the JCA model can predict well without direct measurement of the non-acoustical parameters. However, there are disadvantages to several methods including sharp peaks in some frequency ranges for the two-cavity method, data fluctuation at low frequency for the four-microphone method, and inaccuracy in predicting the characteristic impedance of thick materials at middle and high frequencies for the two-thickness method. The results imply that the inverse method of the JCA model is a reliable method to predict the characteristic impedance and the complex wave number with comparable accuracy to traditional experimental methods.

Sound absorption performance of natural areca plant husk fibers: Experimental and theoretical study

Fibers extracted from plant wastes can be used for sound absorption (SA) applications in vehicles due to its lightweight and porosity. The SA capability of raw areca fibers bundle (RAFB) as a function of the density and thickness of the test specimen is analyzed. Experimental results obtained using the impedance tube approach reveal that an increase in the specimen bulk density and thickness improves the SA capability of RAFB. Similarly, hollow air volume behind the sample enhances the SA in the lower frequency range. Theoretical results predicted using the Johnson–Champoux–Allard model match well with the experimental predictions. The ability of the RAFB to absorb sound is demonstrated to be equivalent to other commercially available natural and artificial fibers by comparing the results available in the literature.

Imaging based pore network modeling of acoustical materials

The acoustical behavior of porous materials is dictated by their underlying pore network geometry. Given the complexity of accurately characterizing the various pore network features, current acoustical models instead rely on indirectly incorporating these features by accounting for them within acoustical transport properties, such as tortuosity, viscous and thermal characteristic lengths, and flow resistivity. In turn, these transport properties are currently identified using inverse characterization techniques or using multiphysics modeling techniques. Here, we propose the use of advanced image processing methods to characterize the pore network of acoustical materials and allow the direct calculation of their transport and acoustical properties. To establish the feasibility of this idea, we create 3D printable CAD models of porous materials with controlled pore geometries and use a Matlab-based watershed segmentation technique to calculate their effective pore and throat size distributions. These distributions are then used to calculate their transport properties and predict their sound absorption coefficients using the Johnson–Champoux–Allard model. For comparison, we calculate the transport properties using the hybrid multiphysics modeling technique and the inverse characterization method. The predictions from the three different methods are then compared with experimental measurements obtained by printing and testing the models using an impedance tube.

Optimization and modeling of the sound absorption behavior of polyurethane composite foams reinforced with kenaf fiber

In this study, hybrid composites made of polyurethane (PU) matrix and natural kenaf fiber filler were designed and fabricated. The Response Surface Methodology (RSM) optimization approach coupled with a Central Composite Design (CCD) was used to design the experiments and optimize the parameters affecting the acoustic performance of the samples in the low and mid-frequency ranges. The acoustic performance of the samples was investigated using the impedance tube method. Additionally, the acoustic performance was predicted using a developed Quadratic model as well as the Delany-Bazley (DB) and Johnson-Champoux-Allard (JCA) models. The results showed that the acoustic absorption of neat PU foam is remarkably improved at all frequencies with the addition of kenaf fibers as the filler. It was found that the acoustic performance of the composite samples is optimal when the added amount of kenaf fibers to the polymer matrix and fiber length are 1.2 wt% and 8 mm, respectively. The sound absorption average (SAA) of the optimized composite and neat PU foam was calculated as 0.65 and 0.48, respectively i.e., an increase of 35.4 %. The Quadratic model showed very high accuracy for the prediction of the SAA of the optimized sample. The JCA model provided higher accuracy for the prediction of the frequency-dependent sound absorption coefficient of the composites as compared with the DB model.

Experimental and Numerical Investigation of Sound Absorption Characteristics of Rebonded Polyurethane Foam

Polyurethane foam (PUF) is an exceptionally adaptable product that has a variety of applications—it can be found almost everywhere. Due to such high utilization, the amount of polyurethane foam waste generated each year is growing over time. Rebonding polyurethane foam waste is a suitable way to progress towards a circular economy. In this paper, the prospect of using rebonded polyurethane foam (RPUF) in noise control applications is examined. An experimental study was carried out on RPUFs with various thicknesses and densities. The sound absorption coefficients at normal incidence and air resistivity were measured. The five-parameter Johnson-Champoux-Allard (JCA) model was adopted for the simulation of the porous layer. The remaining unknown parameters of the JCA model were estimated by inverse acoustic characterization based on fitting the transfer matrix method (TMM) model of an unbounded porous layer with rigid backing to the experimentally obtained sound absorption coefficients. Furthermore, sound absorption coefficients were calculated for a wide range of sample thicknesses, as well as for different air gap thicknesses between the wall and the porous layer. For some of the considered RPUFs, a sound absorption coefficient above 0.8 was achieved over a wide frequency range.

A Model for Sound Propagation Through Corrugated Porous Structures With Mean Flow

Abstract For applications of porous materials where mean pressure drop is a concern, packaging the material into a corrugated structure is better compared to other geometries such as block or wedge shapes. The goal of this study is to integrate noise reduction functionality within that material, which requires an understanding of sound propagation through corrugated porous structures, including flow effects. The corrugated porous structure involves porous partitions separating inlet and outlet fluid channels. The porous materials considered are periodic octet-truss and body-centered cubic unit cells, and sound propagation across these porous partitions is modeled using the Johnson–Champoux–Allard model. The predicted transmission loss (TL) is benchmarked using designed additively manufactured corrugated structures measured using a flow duct. The laminar flow regime is maintained across the porous structure to reduce flow-noise effects. It is shown that the TL for a given corrugated structure increases with a decrease in porosity, and the impact of flow becomes significant as the porosity decreases. The influence of flow on TL also depends on the unit cell configuration. Furthermore, the model provides insights into pressure and acoustic particle velocity distributions within the corrugated structure and reveals regions of the porous material that effectively participate in noise reduction.

Ultralight Single‐Walled Carbon Nanotube Aerogels for Low‐Frequency Sound Absorption

In the article number 2200357 Tomonaga Ueno, and co-workers report an ultralight single-walled carbon nanotube (SWCNT) aerogel for low-frequency sound absorption, with a hierarchical porous structure and a high-modulus framework. The Biot–Johnson–Champoux–Allard model indicates the significant effect of the high elastic modulus of the SWCNT aerogel on the low-frequency sound absorption.

Effects of urea–formaldehyde and polyvinyl acetate adhesive on sound absorption coefficient and sound transmission loss of palmyra palm fruit fiber composites

Composite materials made from palmyra palm fruit fiber (PPFF) were formed using urea–formaldehyde (UF) and polyvinyl acetate (PVAc). We prepared two sets of five different cylindrical samples with varying PPFF contents. The PPFF composites’ normal-incident sound absorption coefficient (SAC) and transmission loss (TL) were measured by using the impedance tube method. The sample with higher PPFF content shows a lower SAC spectrum. It is the opposite for the TL, where a sample with high PPFF content demonstrates a higher TL spectrum. We conducted the least-square fitting method on the experimental SAC and TL spectra utilizing the Johnson-Champoux-Allard (JCA) equivalent fluid model. Non-acoustic parameters were acquired from the fitting. The optimized porosity (ϕ), viscous characteristic length (Λ), and thermal characteristic length (Λ′) are inversely proportional to the PPFF content. The airflow resistivity (σ) and tortuosity (α∞), on the other hand, demonstrate a direct correlation with the PPFF content. Even though the UF samples have an average density of 14.7 % higher than the PVAc samples, their σ,Λ′, and α∞ are just 7.7 %, 4.5 %, and 0.39 % higher than PVAc samples. On the other hand, PVAc samples show higher average Λ and ϕ of 1.4 % and 0.73 %, respectively. The optimized porosity values obtained from the JCA model (ϕJCA) are coherent with ones from the direct estimation method assuming adhesive-coated fiber (ϕfa). It can be concluded that the adhesive’s quantity and density contribute to the composites’ porosity value, ultimately affecting material acoustic properties. Researchers can control and predict how the SAC and TL of fibrous sound absorbers would behave by varying the quantity and density of an adhesive.

Ultralight Single‐Walled Carbon Nanotube Aerogels for Low‐Frequency Sound Absorption

Absorbing low‐frequency sound below 1000 Hz with an ultralight material is a critical challenge. Nanofibrous sound‐absorbing materials have many interfaces for air‐borne sound loss. In addition, nanofibers with a high elastic modulus can increase the loss of sound propagating in the solid, enabling good, low‐frequency sound absorption. Herein, a composite aerogel based on single‐walled carbon nanotubes (SWCNTs) and carboxymethyl cellulose (CMC) as an ultralight material that effectively absorbs low‐frequency sound is reported. This ultralight aerogel has a hierarchical porous structure composed of high‐modulus SWCNT–CMC composite nanofibers. A sample with an areal density of 20 mg cm−2 (bulk density: 5 mg cm−3, thickness: 39 mm) achieves a sound‐absorption coefficient of 0.44 at 500 Hz. The sound‐absorption behavior is sufficiently described by the Biot–Johnson–Champoux–Allard model, indicating the significant effect of the high elastic modulus of the nanofibers on the sound‐absorption performance. The article presents a new design principle for ultralight materials with low‐frequency sound absorption that takes into consideration both the porous structure and the elastic modulus of the material framework.

Measuring and modeling the effect of density and pile height on sound absorption of double base Persian rug

The purpose of this study is to investigate the role of density and pile height on sound absorption coefficient in Double Base Persian (DBP) rug and possibility of prediction the acoustic behavior of DBP rug using the mathematical model. For this aim, in the first step, three double base rug samples were produced at different base densities (2, 4, and 6 warp yarn/cm) and the sound absorption coefficient of samples was measured with Impedance tube in two thicknesses (15 & 13 mm) to study the pile height effect. Moreover, the sound absorption of the double base zone was also measured by shaving off the pile from the double base rug samples. Three rug samples at different base densities were produced with very thin warp and weft yarns to avoid the base effect in this sample. Besides, the macroscopic empirical model (Johnson–Champoux–Allard (JCA)) was implemented on obtained data. The results showed that the sound absorption of the double base rug samples increases with increasing the pile height and base density. The role of the base zone in the sound absorption of the rug is bolder than the pile zone. What leads to improve the rug sound absorption by increasing density is increasing the sound absorption of base zone and the pile density changes do not play a major role in increasing the rug sound absorption. In addition, by assuming DBP rugs as a two-layer porous (pile + base zone) absorber, JCA model shows a good consistency with experimental data.

Gaussian-Based Machine Learning Algorithm for the Design and Characterization of a Porous Meta-Material for Acoustic Applications

The scope of this work is to consolidate research dealing with the vibroacoustics of periodic media. This investigation aims at developing and validating tools for the design and characterization of global vibroacoustic treatments based on foam cores with embedded periodic patterns, which allow passive control of acoustic paths in layered concepts. Firstly, a numerical test campaign is carried out by considering some perfectly rigid inclusions in a 3D-modeled porous structure; this causes the excitation of additional acoustic modes due to the periodic nature of the meta-core itself. Then, through the use of the Delany–Bazley–Miki equivalent fluid model, some design guidelines are provided in order to predict several possible sets of characteristic parameters (that is unit cell dimension and foam airflow resistivity) that, constrained by the imposition of the total thickness of the acoustic package, may satisfy the target functions (namely, the frequency at which the first Transmission Loss (TL) peak appears, together with its amplitude). Furthermore, when the Johnson–Champoux–Allard model is considered, a characterization task is performed, since the meta-material description is used in order to determine its response in terms of resonance frequency and the TL increase at such a frequency. Results are obtained through the implementation of machine learning algorithms, which may constitute a good basis in order to perform preliminary design considerations that could be interesting for further generalizations.

Experimental and modeling investigation of the acoustic behavior of sustainable kenaf/yucca composites

The increased awareness of environmental issues has motivated researchers and manufacturers towards the use of natural acoustic absorbers, which are environmentally friendly, sustainable, and relatively cheap. One approach in this direction is to explore the use of waste fibers for potential applications in sound absorption. This study investigates the acoustic behavior of kenaf and yucca waste fiber composites. To this end, yucca and kenaf waste fibers were collected. The separation and extraction of fibers from non-fibrous tissues and woody parts were carried out using the water retting technique. Afterward, yucca and kenaf fibers were blended with a mass ratio of 70:30, 50:50, and 30:70. Polyvinyl alcohol (PVA) was used as the binder to fabricate the composite samples. The acoustic performance of the composites was evaluated using the impedance tube technique. The frequency-dependent absorption behavior of the samples was also investigated using the Delany-Bazley (D-B), Garai-Pompoli (G-P), and Johnson-Champoux-Allard (JCA) models. An in-house developed Matlab code was used for the simulation of the 3D structure of the specimens, and flow resistivity was calculated by simulation of the airflow through the structure. Additionally, tortuosity, viscous, and thermal characteristic lengths were calculated by an inverse technique. It was found that samples of 100% kenaf fibers have the highest flow resistivity values. Flow resistivity decreased with decreasing the kenaf content in the composite samples. It was found that samples of 100% kenaf fibers exhibit promising performance at the low- and mid-frequency bands. A decrease in the amount of kenaf content led to the shift of absorption peak towards the high-frequency region. It was also found that the JCA model closely follows the trend of experimental data for the frequency range of 80–6300 Hz.

Acoustic Characterization of Some Steel Industry Waste Materials

From a circular economy perspective, the acoustic characterization of steelwork by-products is a topic worth investigating, especially because little or no literature can be found on this subject. The possibility to reuse and add value to a large amount of this kind of waste material can lead to significant economic and environmental benefits. Once properly analyzed and optimized, these by-products can become a valuable alternative to conventional materials for noise control applications. The main acoustic properties of these materials can be investigated by means of a four-microphone impedance tube. Through an inverse technique, it is then possible to derive some non-acoustic properties of interest, useful to physically characterize the structure of the materials. The inverse method adopted in this paper is founded on the Johnson–Champoux–Allard model and uses a standard minimization procedure based on the difference between the sound absorption coefficients obtained experimentally and predicted by the Johnson–Champoux–Allard model. The results obtained are consistent with other literature data for similar materials. The knowledge of the physical parameters retrieved applying this technique (porosity, airflow resistivity, tortuosity, viscous and thermal characteristic length) is fundamental for the acoustic optimization of the porous materials in the case of future applications.

Investigation on the Acoustic Performance of Multiple Helmholtz Resonator Configurations

Helmholtz resonator is considered and widely accepted as a basic acoustic model in engineering applications and research. In this paper, the normal incidence sound absorption characteristics of series and parallel configurations of Helmholtz resonators is studied analytically, numerically and experimentally. The proposed analytical model for series configuration of HRs comprises of Johnson–Champoux–Allard model and transfer matrix method while parallel configuration of HRs is described using parallel transfer matrix method. The results from proposed analytical models fit well with the finite element method (FEM) results obtained from COMSOL multiphysics. Incorporation of parallel configuration and proper tuning of geometric parameters helps to overcome the trade-off between broad band sound absorption and minimum space utilization. Also, the experimental observations of one of the parallel configuration substantiates the FEM results. Moreover, the FEM models are more accountable for the variation in neck position and also provide better visualization of acoustic absorption with frequency.

Elucidating the Sound Absorption Characteristics of Foxtail Millet (Setariaitalica) Husk.

The current study deals with the analysis of sound absorption characteristics of foxtail millet husk powder. Noise is one the most persistent pollutants which has to be dealt seriously. Foxtail millet is a small seeded cereal cultivated across the world and its husk is less explored for its utilization in polymer composites. The husk is the outer protective covering of the seed, rich in silica and lingo-cellulose content making it suitable for sound insulation. The acoustic characterization is done for treated foxtail millet husk powder and polypropylene composite panels. The physical parameters like fiber mass content, density, and thickness of the composite panel were varied and their influence over sound absorption was mapped. The influence of porosity, airflow resistance, and tortuosity was also studied. The experimental result shows that 30-mm thick foxtail millet husk powder composite panel with 40% fiber mass content, 320 kg/m3 density showed promising sound absorption for sound frequency range above 1000 Hz. We achieved noise reduction coefficient (NRC) value of 0.54. In view to improve the performance of the panel in low-frequency range, we studied the efficiency of incorporating air gap and rigid backing material to the designed panel. We used foxtail millet husk powder panel of density 850 kg/m3 as rigid backing material with varying air gap thickness. Thus the composite of 320 kg/m3 density, 30-mm thick when provided with 35-mm air gap and backing material improved the composite’s performance in sound frequency range 250 Hz to 1000 Hz. The overall sound absorption performance was improved and the NRC value and average sound absorption coefficient (SAC) were increased to 0.7 and 0.63 respectively comparable with the commercial acoustic panels made out of the synthetic fibers. We have calculated the sound absorption coefficient values using Delany and Bezlay model (D&B model) and Johnson–Champoux–Allard model (JCA model) and compared them with the measured sound absorption values.