Acoustical properties of double porosity granular materials

Granular materials have been conventionally used for acoustic treatment due to their sound absorptive and sound insulating properties. An emerging field is the study of the acoustical properties of multiscale porous materials. An example of these is a granular material in which the particles are porous. In this paper, analytical and hybrid analytical-numerical models describing the acoustical properties of these materials are introduced. Image processing techniques have been employed to estimate characteristic dimensions of the materials. The model predictions are compared with measurements on expanded perlite and activated carbon showing satisfactory agreement. It is concluded that a double porosity granular material exhibits greater low-frequency sound absorption at reduced weight compared to a solid-grain granular material with similar mesoscopic characteristics

Sound absorption and reflection from a resonant metasurface : homogenization model with experimental validation

Efficient manipulation of sound waves by some resonant acoustic metasurface designs has recently been reported in the literature. This paper presents a general theoretical framework for the description of sound wave interaction with the resonant metasurface that is independent of the nature of resonators and the excitation. The equations governing the behaviour of the metasurface are upscaled from the rigorous description of its unit cell using the two scale asymptotic homogenisation. The procedure relies on the existence of the boundary layer confined in the vicinity of the resonators operating in the deep subwavelength regime. The model is capable of describing sound interaction with the array of resonators positioned above or upon the substrate, so that the out of plane direction becomes an additional degree of freedom in the design. It is shown that at the leading order, the behaviour of the resonant surface is described in terms of the effective admittance, whose unconventional properties makes it possible to achieve the total sound absorption at multiple frequencies, broadband absorption, the phase reversal of the reflected wave at resonance and the control of the enclosure modes. The theory is validated by experiments performed in the impedance tube and in the anechoic environment using a surface array of spherical Helmholtz resonators with the extended inner neck. Experimental results confirm the effectiveness and robustness of the resonant surface for control of sound waves

Volumetric diffusers : pseudorandom cylinder arrays on a periodic lattice

Most conventional diffusers take the form of a surface based treatment, and as a result can only operate in hemispherical space. Placing a diffuser in the volume of a room might provide greater efficiency by allowing scattering into the whole space. A periodic cylinder array (or sonic crystal) produces periodicity lobes and uneven scattering. Introducing defects into an array, by removing or varying the size of some of the cylinders, can enhance their diffusing abilities. This paper applies number theoretic concepts to create cylinder arrays that have more even scattering. Predictions using a Boundary Element Method are compared to measurements to verify the model, and suitable metrics are adopted to evaluate performance. Arrangements with good aperiodic autocorrelation properties tend to produce the best results. At low frequency power is controlled by object size and at high frequency diffusion is dominated by lattice spacing and structural similarity. Consequently the operational bandwidth is rather small. By using sparse arrays and varying cylinder sizes, a wider bandwidth can be achieved

Low frequency sound absorption in a porous material with periodically distributed dead-end pores

A theoretical and numerical study of the sound propagation in air-saturated porous media with straight pores bearing lateral cavities (dead-ends) is proposed. The straight pores can be considered as the main (Biot) pores. The lateral cavities are located at ”nodes” periodically spaced along each ”main pore” axis. The effect of periodicity in the distribution of the lateral cavities is studied and the low frequency limit valid for the closely spaced dead-ends is considered separately. It is shown that the absorption coefficient and transmission loss are influenced by the viscothermal losses in the main pores as well as their perforation rate. The presence of long or short dead-ends significantly alters the acoustical properties of the material. These depend strongly on the geometry (diameter and length) of the dead-ends, on their number per node and on the periodicity along the propagation axis. These effects are primarily due to low sound velocity in the main pores and on thermal losses occurring in the lateral cavities. The model predictions are compared with experimental results and examples of material design featuring periodically distributed dead-end pores are proposed

Influence of Forchheimer’s nonlinearity and transient effects on pulse propagation in air saturated rigid granular materials

It has been shown in the earlier work of Umnova et al. [Noise Control Eng. 50, 204–210 (2002)] that interaction of a relatively long, high amplitude acoustic pulse with a rigid porous material can be accurately described accounting for the Forchheimer nonlinearity. In the present study, the goal is to determine whether the accuracy of the modeling can be improved in the case of a lower amplitude and a shorter pulse. A model that accounts for the Forchheimer’s nonlinearity and the transient effects is developed. It is assumed that all the contributions to the viscous force are additive in the time domain. The governing equations are solved numerically using finite difference time domain scheme. The results are compared with the data for two granular materials. The latter are obtained in an impedance tube and in a shock tube experiments, where acoustic pulses with various amplitudes and durations are generated

Effects of porous covering on sound attenuation by periodic arrays of cylinders

The acoustic transmission loss of a finite periodic array of long rigid cylinders, without and with porous absorbent covering, is studied both theoretically and in the laboratory. A multiple scattering model is extended to allow for the covering and its acoustical properties are described by a single parameter semi-empirical model. Data from laboratory measurements and numerical results are found to be in reasonable agreement. These data and predictions show that porous covering reduces the variation of transmission loss with frequency due to the stop/pass band structure observed with an array of rigid cylinders with similar overall radius and improves the overall attenuation in the higher frequency range. The predicted sensitivities to covering thickness and effective flow resistivity are explored. It is predicted that a random covered array also gives better attenuation than a random array of rigid cylinders with the same overall radius and volume fraction

Machine learning and DSP algorithms for screening of possible osteoporosis using electronic stethoscopes

Osteoporosis is a prevalent but asymptomatic condition that affects a large population of the elderly, resulting in a high risk of fracture. Several methods have been developed and are available in general hospitals to indirectly assess the bone quality in terms of mineral material level and porosity. In this paper we describe a new method that uses a medical reflex hammer to exert testing stimuli, an electronic stethoscope to acquire impulse responses from tibia, and intelligent signal processing based on artificial neural network machine learning to determine the likelihood of osteoporosis. The proposed method makes decisions from the key components found in the time-frequency domain of impulse responses. Using two common pieces of clinical apparatus, this method might be suitable for the large population screening tests for the early diagnosis of osteoporosis, thus avoiding secondary complications. Following some discussions of the mechanism and procedure, this paper details the techniques of impulse response acquisition using a stethoscope and the subsequent signal processing and statistical machine learning algorithms for decision making. Pilot testing results achieved over 80% in detection sensitivity

Low frequency sound propagation in activated carbon

Activated carbon can adsorb and desorb gas molecules onto and off its surface. Research has examined whether this sorption affects low frequency sound waves, with pressures typical of audible sound, interacting with granular activated carbon. Impedance tube measurements were undertaken examining the resonant frequencies of Helmholtz resonators with different backing materials. It was found that the addition of activated carbon increased the compliance of the backing volume. The effect was observed up to the highest frequency measured (500 Hz), but was most significant at lower frequencies (at higher frequencies another phenomenon can explain the behavior). An apparatus was constructed to measure the effective porosity of the activated carbon as well as the number of moles adsorbed at sound pressures between 104 and 118 dB and low frequencies between 20 and 55 Hz. Whilst the results were consistent with adsorption affecting sound propagation, other phenomena cannot be ruled out. Measurements of sorption isotherms showed that additional energy losses can be caused by water vapor condensing onto and then evaporating from the surface of the material. However, the excess absorption measured for low frequency sound waves is primarily caused by decreases in surface reactance rather than changes in surface resistance

Detection of osteoporosis from percussion responses using an electronic stethoscope and machine learning

Osteoporosis is an asymptomatic bone condition that affects a large proportion of the elderly population around the world, resulting in increased bone fragility and increased risk of fracture. Previous studies had shown that the vibroacoustic response of bone can indicate the quality of the bone condition. Therefore, the aim of the authors' project is to develop a new method to exploit this phenomenon to improve detection of osteoporosis in individuals. In this paper a method is described that uses a reflex hammer to exert testing stimuli on a patient's tibia and an electronic stethoscope to acquire the impulse responses. The signals are processed as mel frequency cepstrum coefficients and passed through an artificial neural network to determine the likelihood of osteoporosis from the tibia's impulse responses. Following some discussions of the mechanism and procedure, this paper details the signal acquisition using the stethoscope and the subsequent signal processing and the statistical machine learning algorithm. Pilot testing with 12 patients achieved over 80% sensitivity with a false positive rate below 30% and accuracies in the region of 70%. An extended dataset of 110 patients achieved an error rate of 30% with some room for improvement in the algorithm. By using common clinical apparatus and strategic machine learning, this method might be suitable as a large population screening test for the early diagnosis of osteoporosis, thus avoiding secondary complications