Effect of casing on sound absorption characteristics of fine spherical granular material

Dual-Scale Spiral Material for Balancing High Load Bearing and Sound Absorption

Porous materials with sound absorption and load-bearing capabilities are in demand in engineering fields like aviation and rail transportation. However, achieving both properties simultaneously is challenging due to the trade-off between interconnected pores for sound absorption and mechanical strength. Inspired by quilling art, a novel design using spiral material formed by rolling planar materials into helical structures is proposed. Experimental results show high structural strength through self-locking mechanisms, while double porosities from interlayer spiral slits and aligned submillimeter pores provide excellent sound absorption. These spiral sheets surpass foam aluminum in specific strength (up to 5.1 MPa) and approach aerogels in sound absorption (average coefficient of 0.93 within 0-6400 Hz). With its adaptability to various planar materials, this spiral design allows for hybrid combinations of different materials for multi-functionality, paving the way for designing advanced, lightweight porous materials for broad applications.

Learning acoustic responses from experiments: A multiscale-informed transfer learning approach

A methodology to learn acoustical responses based on limited experimental datasets is presented. From a methodological standpoint, the approach involves a multiscale-informed encoder used to cast the learning task in a finite-dimensional setting. A neural network model mapping parameters of interest to the latent variables is then constructed and calibrated using transfer learning and knowledge gained from the multiscale surrogate. The relevance of the approach is assessed by considering the prediction of the sound absorption coefficient for randomly-packed rigid spherical beads of equal diameter. A two-microphone method is used in this context to measure the absorption coefficient on a set of configurations with various monodisperse particle diameters and sample thicknesses, and a hybrid numerical approach relying on the Johnson-Champoux-Allard-Pride-Lafarge model is deployed as the multiscale-based predictor. It is shown that the strategy allows for the relationship between the micro-/structural parameters and the experimental acoustic response to be well approximated, even if a small physical dataset (comprised of ten samples) is used for training. The methodology, therefore, enables the identification and validation of acoustical models under constraints related to data limitation and parametric dependence. It also paves the way for an efficient exploration of the parameter space for acoustical materials design.

Experimental study on sound absorption of hollow glass beads with inner closed cavities under low-frequency vertical vibration

Normal incidence sound absorption coefficients α of hollow glass beads were measured under a sinusoidal vertical vibration of 10 Hz. It was found that α depends on the vibrational displacement amplitude. As the displacement amplitude increased, the frequency width of the peak extended toward low frequencies. In addition, different evolutions of α were observed for the time periods during which the displacement of the sinusoidal vibration was positive or negative. It seems that the variation in packing state, which is caused by the inertial forces due to vibration, causes the different evolutions of α.

Effect of acoustically-induced elastic softening on sound absorption coefficient of hollow glass beads with inner closed cavities

This study investigated the effects of sound wave magnitude on the sound absorption characteristics of granular materials. The normal incidence sound absorption coefficients of the hollow glass bead packings were measured with different incident sound pressure levels. The measurement results exhibited spectral peaks of sound absorption coefficients at several frequencies, implying that the first peak was caused by the resonance of the hollow glass beads as a layer. Although the first peak in the sound absorption coefficients did not vary when an incident sound pressure was low, the first peak shifted to a lower frequency when the sound pressure exceeded a certain magnitude. These results indicate that the hollow glass beads are softened at high incident sound pressures. Furthermore, by modelling the velocity-dependent elasticity of the hollow glass beads, the velocity and elasticity in the hollow glass beads were simulated in the direction of the sound propagation. The simulation results indicate that the velocity and elasticity profiles depend on the sound wave magnitude. Finally, the velocities of the hollow glass beads under acoustic excitation were measured by inserting an accelerometer into the beads. The measurement results demonstrated that the velocity profile depends on the sound wave magnitude, which parallels the simulation results.

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.