Granular chains are a benchmark system for strongly nonlinear wave propagation, where impulse transmission is typically controlled through mass, material, or lattice design. Here, we introduce contact topology as a new and experimentally accessible control parameter. By locally tuning contact geometry, we directly modify the nonlinear force–displacement law and realise exponent-driven contact defects without altering particle mass or material.Combining controlled experiments with discrete element simulations, we show that local variations in the interaction exponent induce amplitude-dependent scattering, delay, pulse splitting, and energy redistribution. When multiple defects are introduced, their interactions are non-additive: upstream defects condition the waveform before it reaches downstream ones, enabling tunable attenuation, programmable delay, and passive directional transmission asymmetry.These results establish exponent engineering via contact topology as a practical design approach for granular metamaterials, opening new pathways for compact impact mitigation, waveform conditioning, and nonlinear mechanical signal control.

This study explores the application of ensemble learning, decision tree, random forest, and XGBoost, to predict the damping response of irregular granular materials using a data-driven approach. Training and testing data were measured using an acrylic beam excited with a low-amplitude sinusoidal sweep waveform (root mean square <1 N). Six granular materials, featuring both spherical and irregular particle shapes and varying mechanical properties, were selected as infill for the beam cavity. The main aim was to map between six input features: force, filling ratio, granular materials properties, and two targeted outputs: reduction of the beam's first resonance peak and root mean square acceleration. Feature importance analysis was conducted for each model developed to assess the dependence of the target values on the input features. It is concluded that ensemble models can offer accurate estimates (R2 ≥ 90%) with the XGBoost model incorporating all input features in the estimation. An attempt to estimate the damped response of hard-soft granular mixtures using empirically determined mixture-equivalent properties gave good estimates that differ from simple mass/volume-fraction averaging, with performance varying by filling ratio and excitation amplitude.

Given the similarity of unconsolidated Granular Materials (GMs) to fibrous materials in airborne attenuation, it is important to study their sound absorption properties and their particle-based distinct relationships. Quantifying absorption using equivalent fluid models is challenging due to the need to estimate several geometric parameters of the porous media. This work presents experimental and modelling insights into the Sound Absorption Coefficient (SAC) spectrum of irregularly shaped granules in unconsolidated granular materials with particle sizes ranging from 100 mu m to 15 mm. Experimentally, impedance tube measurements were taken for the granular material beds with a thickness of 50 mm, and their airflow resistivities were determined using a new sieve arrangement. Absorption models were developed based on the measured flow resistivity and other non-acoustical parameters of GMs, obtained through established empirical and numerical relationships, using three reported porous media models. It was found that the granule size-dependent relationship models the SAC spectrum into three dominant phases (Regions) based on the mean particle diameter (D-e) of the GMs: Region 1 (D-e > 2 mm), Region 2 ( D-e< 2 mm), and Region 3 (D-e <= 100 m). Modelling of these regions showed that the Johnson-Champoux-Allard (JCA)-based model provides a good estimate for the high-frequency absorption peak (>1 kHz) found in Region 1 GMs. Empirical models, such as the Delaney and Bazley and Miki-based sound absorption models, provide better estimates for the frequency-independent plateau absorption in Region 2. For Region 3, a new coupled fluid-solid characteristic impedance model is developed to explain the frame resonance-enhanced attenuation in powders with D-e < 100 m.

This research addresses two significant environmental impacts of urbanization and mechanization: noise pollution and ventilation. Noise pollution is increasingly recognized as a pervasive physical and mental health concern, linked to a growing array of medical conditions. Meanwhile, ventilation problems in many homes lead to excessive dampness, contributing to respiratory health issues. Current construction technology does not provide affordable solutions to these challenges, and the industry continues to rely on homogeneous materials. Cost-effective lightweight construction methods often fail to adequately reduce noise transmission between dwellings, while mechanical ventilation systems are costly, and passive trickle vents typically provide insufficient airflow. This study explores using metastructures and metasurfaces to improve sound insulation, with a focus on scalable, practical implementation. Consisting of metamaterial systems, they incorporate elements designed to reflect, absorb, and guide acoustic waves. The paper presents applications of locally resonant metamaterials, phononic crystals, subwavelength coiled acoustic resonators, and passive noise-cancellation waveguides utilizing Fano-resonance. Our findings demonstrate the effectiveness of these systems, with both experimental and simulation results showing a strong correlation. Diffuse-field testing indicates significant sound attenuation within the targeted frequency bands. We assess the advantages of each approach and identify the most effective methods.

Granular Materials (GM) employed within particle dampers attenuate vibration energy due to interparticle and particle-wall interactions. Estimating their kinetic energy losses is usually performed using the Discrete Element (DE) method assuming that particles of uniform size (monodisperse) are excited at anti-resonance conditions. However, the GM found in nature and industrial by-products exhibit size distributions within specific ranges. Estimating their energy losses is important in the presence of structural resonance conditions to obtain the associated damping. This study numerically investigates both monodisperse and mixtures of GM integrated within vibrating structures using a coupled Finite Element-Discrete Element approach. The model developed simulates the oscillation of a small-scale suspended panel system integrated with a 6 mm thick granular layer with a cubic packing arrangement. Various monodisperse and mixed spherical particles ranging from 1 to 6 mm occupy the packing space. Damping characteristics of various spherical particle arrangements were quantified by the panel system's damping loss factor, determined through the logarithmic decrement method. The results showed that mixtures of larger particles of 2-4 mm diameter develop higher damping compared to smaller monodisperse particles and mixtures of smaller sizes (with diameters of 3 mm or less) for the same mass. It is concluded that the damping of these particle sets (with diameters of 3 mm or less) can be assessed using a new geometric parameter developed in this study that characterizes the particles' bed. Additionally, the segregation effect in the 2-4 mm mixture with large porosity results in higher tangential velocities that increase interparticle losses.

The Sound Absorption Coefficient (SAC) of unconsolidated Granular Material (GM) is usually characterized by utilizing empirical models based on airflow resistivity correlations or more comprehensive models like Johnson–Champoux–Allard (JCA). These models rely on porous media geometrical parameters, which are obtained through inverse characterization methods using SAC experimental results. This presents challenges when GM’s SAC estimates are required in the absence of experimental results. Therefore, this paper reports a sound absorption model for GMs based on three porous media absorption models. Each model corresponds to GMs with a mean particle diameter (De) range, related to a specific SAC frequency profile that transitions through three stages, influenced by particle size changes, up to 2 kHz. Model parameters were determined based on granular frame geometrical properties as a function of airflow resistivity and porosity of packed polydisperse Discrete-Element spherical particles. SAC estimates for various GMs were validated against impedance tube measurements. JCA-based absorption model was found suitable for larger-particle GMs (De > 2 mm), exhibiting absorption peaks at frequencies above 1 kHz (Stage 1). Meanwhile, empirical-based absorption model characterized the frequency-independent SAC plateau observed in GMs with De < 2 mm (Stage 2). A newly developed coupled fluid-solid powders absorption model characterized SAC for 100-micron-sized particles (Stage 3).

The sound transmission loss (STL) of wall partitions, especially in the coincidence region, is investigated. A Mindlin plate with periodically attached masses in a periodic “supercell” pattern is analyzed theoretically and experimentally for sound attenuation. Modeling the masses as points, analytical expressions for predicting the dispersion relation and frequency bandgaps of the plate are developed. The results show that varying the distances between the masses or the masses themselves can lead to the emergence of additional lower-frequency bandgaps and slightly decrease the bandwidth of the primary complete bandgap. Additionally, a triangular periodic pattern of point masses can provide a larger complete bandgap than the conventional rectangular pattern. The results are validated by numerical analyses using the wave and finite element method. Experimental testing is conducted on large-scale plates (2.4 m × 1 m) with periodically attached masses under diffuse field conditions, demonstrating the benefits of utilizing multiple scattering to increase the STL in the coincidence region of the bare plate. The proposed approach is seen to significantly increase the STL of wall partitions in the coincidence region and provides insights into the fundamental principles of sound and vibration attenuation in complex structures based on multiple scattering.

Granular Materials (GM) employed within the mechanism of particle dampers attenuate the vibration energy due to their interparticle and particle-wall interactions. Estimating their damping effect using the analytical equivalent single mass approach overlooked the particles' individual losses that are built into the total damping. Alternatively, the numerical techniques (e.g., Discrete Element) are time-inefficient and computationally demanding. Therefore, this study explores the implementation of Machine learning (ML) algorithms to estimate the damping effect of GM. The ML model in this study will rely on a Data-Driven Modeling approach (DDM) incorporating the ensemble tress nonlinear regressor method. The models' training and testing data were obtained from an experimental setup of an acrylic beam internally integrated with Stainless Steel (SS) and glass spheres undergoing low excitation amplitude (RMS <1N). The main aim was to map between seven input features (e.g. filling ratio) and one targeted output: the beam's damped frequency response. Three ensemble trees' algorithms were used to create the DDM; Decision Tree, Random Forest, and XGBoost. The hyperparameter combination based on the Gridsearch CV function increases the prediction accuracy of each model. The developed ML models provided high accuracy (86-93%) in predicting the damping effect of the granular materials spheres.

In the context of a wider research project investigating the use of Granular Material (GM) within floor and wall structures to increase their sound insulation, this study presents the sound absorption coefficient (SAC) measurements of different thicknesses for a range of GM. A primary aim has been to extend the understanding of the behaviour of GM layers in absorbing the propagated incident sound wave. Equally important has been an assessment of what GM could be sourced from waste and be acceptable for use in buildings from the point of view of fire insulation, handleability, economy, etc. Samples of GM were placed in an 88mm diameter vertical impedance tube and SACs measured up to 2kHz. The results show the effect GM's different structure (size and shape), bulk volume, and mechanical characteristics have on the range and value of the SAC. These determine the extent to which GM could be a replacement for traditional sound absorption materials.

Modern structures incorporating lightweight, low-stiffness floors face challenges for low-frequency impact noise transmission. Using spring isolators or resilient layers (e.g., floating floors) to improve isolation in light weight floor can introduce variability over time and increase structural complexity, making the system more sensitive to construction errors. An alternative approach is reviewed in this work, using internal floor cavities that contain Granular Materials (GM). Previous studies describe GM particle dampers in different applications where large movements between particles result in significant energy losses. However, a review of the experimental methods used in those studies is needed to be able to quantify the energy losses in relation to the type and degree of impact excitation. Modelling approaches are reviewed comparing their computational demand and which properties of GM are included, motion regimes and container properties. These studies span both destructive and non-destructive testing methods and give some pointers to both the geometrical and mechanical properties of granules which influence dissipation. This review goes beyond structural damping to include airborne sound absorption provided by a granular bed. This additional attenuation can be significant over a wide frequency range. A small number of practical studies of GM integrated with light weight floors show improvement in impact sound insulation. However, the lack of more detailed knowledge of GM damping mechanisms and a better understanding of GM bed interactions with containers prevents optimization of their use for insulating floors against sound transmission. This review proposes a general framework for future GM research to guide the selection of appropriate GM and addresses what is needed for optimizing lightweight floor impact sound insulation.

Recognizing the need for effective control of vibration and sound propagation in various industries, this study investigates the potential of designing heterogeneous granular networks for vibroacoustic transmission mitigation. It introduces new models of granular systems: decorated, stepped, and tapered 2-level branching structures. The research assesses changes in particle size (5–10 mm radii) and material properties (density and Young's Modulus) to create finely-tuned composites that significantly modulate pulse waves. The discrete element method predicts wave propagation in these granular metamaterials, comparing monodispersed chains, conventional chain networks, and the proposed heterogeneous structures. Their pulse diffusion capacity is evaluated, showing how collective responses can be adjusted by altering physical parameters like particle size and composition. Preliminary findings underscore the utility of these configurations in advancing the development of elastic and acoustic metamaterials, demonstrating a peak amplitude reduction more than five times greater than an equivalent monomer system. With versatility across a wide frequency range, these metamaterials could pioneer a new direction in impact mitigation.

This paper reviews the creation of a design course for mechanical engineering students at the University of Auckland. The primary objective of the course is to introduce students to the field of acoustics, teaching basic theoretical and experimental acoustics principles, together with product design and fabrication methods, in an engaging and educational manner. During the course, students were assigned the task of developing a noise reduction duct jacket that reduced sound propagation whilst allowing free airflow, all within specified dimensions. Students were required to create designs that attenuated a predefined sound spectrum, with both narrow-band and wide-band components. Over six weeks students developed their designs using mathematical modelling and fabricated their prototypes. The performance of their suppressors was assessed through sound pressure level and impedance tube transmission loss measurements. Students then modified their designs to maximise performance before final submission. Four-person teams produced a diverse range of implementations. The most successful designs achieved impressive performance with peak transmission loss up to 70dB, 2kHz bandwidths of 10 + dB transmission loss and a delta dBA reduction of 21.5 dB. Student feedback indicates a high level of satisfaction with the course, highlighting its effectiveness in imparting key knowledge and skills in acoustics engineering.

The building industry continues to rely on homogeneous materials for acoustic insulation despite the progress of research into acoustic metamaterials. With the inevitable densification of housing, the severity of noise pollution within residential living environments is escalating. While the insulation of high-frequency audible sound through building elements is often relatively good between 1 and 5 kHz, the overall acoustic transmission loss performance is often significantly limited by two specific frequency regions. The mass air mass resonance band, and the coincidence band. We present the results of an investigation into the use of metastructures and metasurfaces to improve transmission loss in these frequency regions with a focus on scalable implementation. These metastructures are metamaterial systems constructed from impedance change elements, surface variations and vibroacoustic resonant elements. The performance of selected systems from this research are presented. Experimental and modeling results are in good qualitative agreement and promising diffuse-field testing results indicate significant attenuation within the targeted band regions. The merits of each technique are analysed, and results indicate which methods are most effective at either mitigating or shifting the regions of poor transmission loss outside of the most important part of the audible frequency region.

A successful learning experience requires children to be able to hear what the teacher is saying. To that end, children need a high signal-to-noise ratio (SNR) or speech audibility to hear the teacher under background noise, but SNR in the classrooms may not always be favourable depending on the activities taking place during a school day. We propose a classroom acoustic measurement system to monitor the time-varying SNR under interactive teaching scenarios. Emulating a child listening to the speech made by a teacher, the system utilises two consumer-grade wireless microphones, one attached to the teacher and the other located where the children would be seated. The signal received by the teacher's microphone is used as a voice activity detector to indicate the presence of the teacher's voice or noise-only audio instances. Subsequently, the children's microphone observes these instances to monitor the average classroom noise and estimate the resulting SNR. A pilot study was conducted at a primary school in Auckland, New Zealand where the SNR measurements were recorded and matched against behavioural coding of the classroom activities. Results show a reasonable agreement of the SNR to the activities performed under real-life classroom teaching scenarios.

Reduction in sound transmission through walls and ceilings, particularly at lower frequencies, is important both because of ongoing growth in noise pollution and the challenges faced in providing good sound insulation with existing construction methods. Mechanical metamaterials can help address these challenges by enabling the creation of an artificial medium that produces significantly greater attenuation than existing passive lightweight material constructions. In part one of this work we designed, modelled and tested simple local resonance structures (LRS) to investigate their potential for future acoustic insulation systems. In part two we extend this work to multilayer and multi-resonance systems. Three LRS families have been studied: multilayer with single resonance, multilayer with multiple resonances and intermediate layer with single resonance. Comparisons are presented based on lumped parameter modelling and transmission loss (TL) measurements under plane wave acoustic excitation. The LRS designs achieved peak transmission losses up to 40 dB greater than non-resonant structures of equivalent surface density within a specified frequency range, and exhibited gains having bandwidths up to 300 Hz. The depth and width of the attenuation bands were found to be controlled by different design parameters, so systems with appropriately tuned interlayer couplings and resonator stiffness exhibited large increases in magnitude and bandwidth of the attenuation. Furthermore, the distribution of stiffness, damping and mass in the resonators powerfully affected the shape of the TL spectrum, and could be used to keep TL at or above mass law levels throughout. LRS systems have the potential to provide significantly higher transmission loss at low frequencies than conventional wall systems of similar size and weight. This is a step towards a locally resonant architecture that can be incorporated into a practical insulation system. (C) 2021 Elsevier Ltd. All rights reserved.

This paper investigates the learning effect of a developed coursework for an engineering acoustics course offered to fourth year and postgraduate engineering students at the University of Auckland, New Zealand. The coursework incorporated practical active-learning activities and was developed to help students gain understanding of complex concepts related to the room-acoustics measurement and analysis and also introduce students to some of the practical tasks that are typical of a practising acoustical engineer in New Zealand. The learning effect of the coursework was measured by comparing students' performance in two quizzes that were run before and after students worked on the coursework. Students' performance on the final examination was also analyzed. An analysis of the common mistakes made by students in the assignment report was also conducted. Overall, the analysis suggests that the coursework generally improved the students' understanding of the material that it covered.

This paper reports the learning effect achieved by a newly developed coursework for an engineering acoustics course offered to fourth year and postgraduate engineering students at the University of Auckland, New Zealand. The course teaches fundamental knowledge that acoustical engineers need and which underpins a variety of sub-disciplines in acoustics including: fundamental physics of wave propagation, building and room acoustics, electro-acoustics, audio signal processing, and the psychology of hearing. The coursework incorporated practical active learning activities and was developed in order to help students gain understanding of complex concepts related to the room acoustics measurement and analysis. The coursework also has the goal of providing students with an introduction to some of the practical tasks which are typical of a practising acoustical engineering in New Zealand. The learning effect was measured by comparing students' performance in a quiz that was run before students commenced working on the coursework and that in the final examination and by investigating common mistakes students made in the report which was the required deliverable of the coursework. Overall, the new coursework successfully improved students' understanding of the material which it covered.

This paper presents the results of a study evaluating the human perception of the noise produced by small quadcopter UAVs. The study utilised recordings of the noise produced by several different quadcopter UAVs in hover and in constant-speed flight at a fixed altitude. These recordings were made using an eigenmic system. The recordings were reproduced using a 3D sound reproduction system located in the large anechoic chamber at the University of Auckland. Human subjects were asked to rate the annoyance of the recordings. The responses of the test subjects are presented and these are compared with objective metrics to assess suitable metrics for quantifying the impact of noise from these vehicles on humans.

This paper presents the results of a study evaluating the human perception of the noise produced by four different small quadcopter unmanned aerial vehicles (UAVs). This study utilised measurements and recordings of the noise produced by the quadcopter UAVs in hover and in constant-speed flight at a fixed altitude. Measurements made using a ½″ microphone were used to calculate a range of different noise metrics for each noise event. Noise recordings were also made using a spherical microphone array (an Eigenmike system). The recordings were reproduced using a 3D sound reproduction system installed in a large anechoic chamber located at The University of Auckland. Thirty-seven participants were subjected to the recordings and asked to rate their levels of annoyance in response to the noise, and asked to perform a simple cognitive task in order to assess the level of distraction caused by the noise. This study discusses the noise levels measured during the test and how the various noise metrics relate to the annoyance ratings. It was found that annoyance strongly correlates with the sound pressure level and loudness metrics, and that there is a very strong correlation between the annoyance caused by a UAV in hover and in flyby at the same height. While some significant differences between the distraction caused by the UAV noise for different cases were observed in the cognitive distraction test, the results were inconclusive. This was likely due to a ceiling effect observed in the participants’ test scores.