The partial discharge (PD) event in high voltage insulation releases energy, exerts mechanical pressure, and generates elastic waves. Detecting and locating these PD events through short-duration acoustic pulses is well-established, particularly in gas-insulated systems and oil-insulated transformers. However, its full potential remains untapped in solid insulation systems, where the propagation capability of acoustic pulse and the acoustic reflections pose fundamental challenges to the Acoustic Emission (AE) detection technique. This study investigates the influence of reflections and multiple paths on the propagating acoustic pulse in polymeric insulating materials using a finite element method (FEM) in COMSOL. It was observed that the reflections from the boundary influence the propagating pulse's shape, peak magnitude, and arrival time. An analytical MATLAB model further quantifies the impact of multiple propagation paths on the shape, magnitude, and arrival time of the pulse travelling in a cylinder. Additionally, a Perfect Matched Layer (PML) was implemented in the COMSOL model to eliminate reflections from the boundary, and it revealed that the acoustic pulse magnitude decreases with distance following the inverse square law. In essence, the models aid in measuring how reflections contribute to the observed signals, facilitating the precise identification of the source of the PD event in the tested system.

Acoustic energy mapping provides the functionality to obtain characteristics of acoustic sources, such as: presence, localization, type and trajectory of sound sources. Several beamforming-based techniques can be used for this purpose, however, they rely on the difference of arrival times of the signal at each capture node (or microphone), so it is of major importance to have synchronized multi-channel recordings. A Wireless Acoustic Sensor Network (WASN) can be very practical to install when used for mapping the acoustic energy of a given acoustic environment. However, they are known for having low synchronization between the recordings from each node. The objective of this paper is to characterize the impact of current popular synchronization methodologies as part of the WASN to capture reliable data to be used for acoustic energy mapping. The two evaluated synchronization protocols are: Network Time Protocol (NTP) y Precision Time Protocol (PTP). Additionally, three different audio capture methodologies were proposed for the WASN to capture the acoustic signal: two of them, recording the data locally and one sending the data through a local wireless network. As a real-life evaluation scenario, a WASN was built using nodes conformed by a Raspberry Pi 4B+ with a single MEMS microphone. Experimental results demonstrate that the most reliable methodology is using the PTP synchronization protocol and audio recording locally.

In the past two decades, acoustic metamaterials have garnered much attention owing to their unique functional characteristics, which is difficult to be found in naturally available materials. The acoustic metamaterials have demonstrated to exhibit excellent acoustical characteristics that paved a new pathway for researchers to develop effective solutions for a wide variety of multifunctional applications such as low-frequency sound attenuation, sound wave manipulation, energy harvesting, acoustic focusing, acoustic cloaking, biomedical acoustics, and topological acoustics. This review provides an update on the acoustic metamaterials' recent progress for simultaneous sound attenuation and air ventilation performances. Several variants of acoustic metamaterials, such as locally resonant structures, space-coiling, holey and labyrinthine metamaterials, and Fano resonant materials, are discussed briefly. Finally, the current challenges and future outlook in this emerging field is discussed as well.

In forensic acoustics, a possible area of analysis is represented by unwanted sound that 1 is perceived as a source of intrusion or disturbance within a certain auditory context. This context 2 is defined as the "auditory scene" and refers to the set of sounds present in a specific environment. 3 The presence of unwanted sounds in the auditory scene can cause a wide range of negative effects, 4 including disturbance, discomfort, moral or immoral harm, and other types of negative impact on the 5 health and well-being of individuals exposed to noise. In 2022, the technical specification UNI/TS 6 11844:2022 dedicated to the measurement and analysis of intrusive noise was published. The standard 7 introduces the concept of intrusive noise and defines its calculation methods based on environmental 8 measurements. The purposes of this technical specification is to provide an objective support to 9 methods already in used in acoustic disputes, where the assessment of the annoyance of a noise is 10 often a subjective evaluation of the technician. This work delves into the application to some real 11 cases, identifying the potentiality and the limits of the standardized method.

The increasing focus on the development of positioning techniques reflects the growing interest in applications and services based on indoor positioning. Many applications necessitate precise indoor positioning or tracking of individuals and assets, leading to rapid growth in products based on these technologies in certain market sectors. Ultrasonic systems have already proven effective in achieving the desired positioning accuracy and refresh rates. The typical signal used in ultrasonic positioning systems for estimating the range between the target and reference points, specifically the linear chirp, can undergo shape aberration due to the effects of acoustic diffraction when the aperture exceeds a certain limit. The extent of the aberration is influenced by the shape and size of the transducer, as well as the angle at which the transducer is observed by the receiver. This aberration also impacts the shape of the cross-correlation, causing it to lose its characteristic easily detectable single global peak. In such instances, cross-correlation techniques yield results with a significantly higher error than anticipated. In this study, an alternative technique to global peak detection is proposed, leveraging the inherent symmetry observed in the shape of the aberrated cross-correlation. The numerical simulations, performed using the academic acoustic simulation software Field II, conducted using a typical ultrasonic chirp and ultrasonic emitter, compare the classical and the proposed range techniques in a standard office room. The results demonstrate that the proposed technique enables accurate range estimation even in the presence of severe cross-correlation shape aberrations. This allows the use of emitting transducers with a much larger aperture than that allowed by the classical cross-correlation technique. Consequently, it becomes possible to have greater acoustic power available, leading to improved Signal-to-Noise Ratio (SNR).

This study aims at an acoustic design of the classical concert hall and evaluation of the acoustic performance. In terms of three acoustic parameters (i.e., reverberation time (RT), clarity (C80), and lateral fraction (LF)), this study performed acoustic simulation modeling and site measurement with the K Art Hall located in South Korea as a case study. First, in order to meet the acoustic performance of the K Art Hall (target RT: 1.4~1.7 seconds, target C80: -2dB or more +2dB or less, and target LF: 10~35%), the finish materials and shape of the room as an interior acoustic design were determined. Second, the average values of the RT, C80, and LF using the acoustic simulation modeling were estimated at 1.4 second, 1.2~1.6 dB, and 29%, respectively. Third, the average values of the RT, C80, and LF through site measuring were measured at 1.5~1.64 second, 0.07~1.31dB, and 22.22~31.37%, respectively. Thus, the results of both the acoustic simulation modeling and site measuring were analyzed so as to satisfy the target acoustic performance. The results of this study will help the decision-makers (i.e., owner, construction managers, etc.) to plan the classical concert hall in terms of the RT, C80, and LF.

Underwater communication for Underwater Wireless Sensor Networks (UWSNs) faces challenges due to the unique underwater environment. This review explores these challenges (attenuation, multipath propagation, limited bandwidth) across acoustic, optical, and radio frequency (RF) communication channels. It highlights how innovative antenna designs are crucial to mitigate these limitations and enable efficient data transmission. The review analyzes monopole, dipole, and helical antennas, discussing their trade-offs in radiation pattern, efficiency, and mitigating multipath effects. Advancements in materials, metamaterials, and reconfigurable antennas offer promising solutions for improved signal propagation, reduced attenuation, and better environmental adaptability. Research gaps include material exploration for low-conductivity antennas and optimizing antenna designs. Rigorous performance evaluation remains essential. Overall, advancements in underwater antenna technology are key to unlocking the full potential of UWSNs and enabling breakthroughs in marine applications.

Infant cry is evolutionarily, psychologically, and clinically significant. During the last 60 years, several researchers and clinicians assessed the possibility of investigating the acoustical properties of cry for medical purposes. However, there is a lack of standardization in conducting and reporting cry-based studies. In this work, methodologies and procedures employed in infant cry analysis are reviewed, and best practices for reporting studies are provided. First, available literature on vocal and audio acoustic analysis have been examined to identify critical aspects of participant information, data collection, methods, and data analysis. Then, 180 peer-reviewed research articles have been assessed to certify the presence of identified critical information. Results show a general lack of critical description. Researchers in the field of infant cry need to agree on a standard set of criteria to report experimental studies, to better demonstrate the validity of the methods and obtained results.

The high level of noise in helicopter cabins considerably compromises the comfort and safety of the pilot and passengers. To verify the feasibility and effectiveness of microperforated panel composite sound absorption structures for noise suppression in helicopter cabins, simulation and experimental studies were conducted on a model of a light helicopter cabin. First, three microperforated composite sound absorption structures for the helicopter cabin wall panel were designed. Then, a finite element model of the main gear/body acoustic vibration coupling was established to obtain the target frequencies of the microperforated composite sound absorption structures; the acoustic effect was verified by simulation. Finally, a model helicopter cabin equipped with the three microperforated composite sound absorption structures was built, and a cabin noise test was performed. The test results showed that the combined microperforated panel acoustic structure and microperforated panel–porous material composite structure realized an overall cabin sound pressure level attenuation of 8–10 dB, on average, in the wide frequency range of 500–2000 Hz, with an amplitude of more than 20 dB. The microperforated panel–acoustic supermaterial composite structure achieved low-frequency sound absorption in the frequency range of 300–450 Hz. The sound absorption effect reached 50%, and it also exhibited good noise reduction effects in the middle- and high-frequency bands.

Veterinary science has benefitted from technological advancements in the past and will hopefully continue to do so, especially in the field of equine gait analysis. There is a need for rapid and easy to use technology that is accurate and portable, but at the same time is also readily interpretable. This manuscript presents two new approaches to equine gait analysis, both of which are commer-cial devices. The use of Acoustic MyoGraphy (AMG) has been proven in the field of muscle func-tion and performance as well as ligament health, but it can also provide details concerning gait when placed on the wall of the hoof of a horse. The TendibootTM system is a limb focused unit that can be easily attached, activated and used in a Veterinary clinic setting, rapidly providing gait details for equine diagnostic purposes. In conclusion this manuscript provides an insight into gait parameters from recent research trials that are novel and challenge current thinking.

A labyrinth metamaterial wall with glass coverage is measured in a reverberating chamber and after its installation in a restaurant. Glass is used to meet two aims, namely acoustic absorption and visual design demands. The wall consists of five multiple labyrinth elements of 1.83 m$^2$ each. Glass was taken to make the wall act as a room lightning device where a translucent cover material is needed. Absorption measurements show about four times improved absorption compared to typical glass. Due to the metamaterial behavior, absorption is high in the low-frequency range below 300 Hz where damping is problematic with traditional materials. Especially in this range, the glass metamaterial wall is an excellent compromise between room acoustic and visual design demands, as loud low-frequencies make visitors speak louder and experience less intimacy with additionally reduced speech intelligibility. For mid-frequencies, absorption is shown less effective and improvements are discussed.

Dysprosody is a commonly described feature of speech deterioration due to Parkinson’s disease. Descriptions of the tonal movements underlying dysprosody have been attempted but has not afforded automation. The current study assessed a fully automated acoustic analysis pipeline in terms of its ability to predict human raters’ perception of dysprosody in patients with Parkinson’s disease. Read speech samples of 68 speakers with PD (45 male and 23 female) aged 65.0±9.8 years were assessed by four human clinical experts in terms of dysprosody severity. The recordings were also submitted to a speech processing pipeline in which portions with speech were identified and provided with a parametrization of intonation. Five models were trained and tuned based on 75% of utterances and their perceptual evaluations in a 10-fold cross-validation procedure and evaluated in terms of their ability to predict the perceptual assessments of recordings not included in the training. The performances of models were compared to human raters’ agreement with the majority vote on a speech sample. The results showed that human raters’ assessments of dysprosody can be approximated by the automated procedure. Variability in pitch does not adequately describe the level of dysprosody due to Parkinson’s disease.

Voice spoofing attempts to break into a specific automatic speaker verification (ASV) system by forging the user’s voice, and can be used through methods, such as text-to-speech (TTS), voice conversion (VC), and replay attacks. Recently, deep learning-based voice spoofing countermeasures have been developed. however, the problem with replay is that it is difficult to construct a large number of datasets because it requires a physical recording process. To overcome these problems, this study proposes a pre-training framework based on multi-order acoustic simulation for replay voice spoofing detection. Multi-order acoustic simulation utilizes existing clean signal and room impulse response (RIR) datasets to generate audios, which simulate the various acoustic configurations of the original and replayed audios. The acoustic configuration refers to factors, such as the microphone type, reverberation, time delay, and noise that may occur between a speaker and microphone during the recording process. We assume that a deep learning model trained on an audio that simulates the various acoustic configurations of the original and replayed audios can classify the acoustic configurations of the original and replay audios well. To validate this, we performed pre-training to classify the audio generated by the multi-order acoustic simulation into 3 classes: clean signal, audio simulating the acoustic configuration of the original audio, and audio simulating the acoustic configuration of the replay audio. We also set the weights of the pre-training model to the initial weights of the replay voice spoofing detection model using the existing replay voice spoofing dataset and then performed fine-tuning. To validate the effectiveness of the proposed method, we evaluated the performance of the conventional method without pre-training and proposed method using an objective metric, i.e., the accuracy. As a result, the conventional method achieved 92.94% accuracy and proposed method achieved 98.16% accuracy.

Information is given on the application of the acoustic emission method for studying the kinetics of destruction of protective and decorative coatings of cement concrete. A different nature of the destruction of coatings has been established. When evaluating the nature of the destruction, it was found that for coatings based on polymer-lime and PF-115 paints, after curing, an adhesive type of destruction is characteristic, while for PVAC coatings it is cohesive. Thermal aging mainly changes the nature of destruction of PVAC coatings from cohesive to adhesive. With a decrease in the porosity of the substrate, higher values of the energy released when the coatings are detached from the substrates are observed. It was revealed that during aging as a result of alternating freezing-thawing, the greatest destructive effect is observed in the contact zone of the coating with the substrate. With an increase in the cycles of alternating freezing-thawing, the amount of energy released at the last stage of loading decreases

The cornea is the optical window to the brain. Its optical and structural properties are responsible for optical transparency and vision. The shape, elasticity, rigidity or stiffness are given by its biomechanical properties, whose stability results in ocular integrity and intraocular pressure dynamics. Here, we report in vivo observation of structural changes and biomechanical alterations of the human cornea induced by acoustic wave pressure within the frequency range of 50-350 Hz and 90 dB of sound pressure level. Central corneal thickness (CCT) and eccentricity (e2) were measured using Scheimpflug imaging and biomechanical properties [corneal hysteresis (CH) and intraocular pressure (IOP] were assessed with air-puff tonometry in 6 young healthy subjects. At the specific 150 Hz acoustic frequency, the variation in CCT and e2 were of 0.058 and 7.33 µm, respectively. Biomechanical alterations were also observed in both IOP (decrease of 3.60 mmHg) and CH that showed an increase of 0.40 mmHg.

Tinnitus is a heterogeneous auditory disorder without a pharmacological cure but with several palliative treatments. One of the most applied treatments for tinnitus relief combines counselling with sound therapy. The efficiency of this sound therapy depends on the type of sound stimulus and the exposition time. The fundamentals of a customized sound therapy that stimulates the auditory system with a continuous or sequential sound which compensates for the subject hearing loss are described here. A sample of 137 tinnitus subjects are treated with this sound therapy, named Enriched Acoustic Environment. 90% of these patients achieved a clinically relevant and statistically significant tinnitus-related distress relief quantified as a mean drop of their Tinnitus Handicap Inventory score of 24.3 points. These subjects exposed with sequential stimuli (31%) achieved greater distress relief (5.1 points more in their Tinnitus Handicap Inventory score) than those stimulated with continuous sound (69%). Therefore, this sound constitutes an optimized stimulus for tinnitus treatment.

We propose a new statistical analysis of the Acoustic Emissions (AE) produced in a series of triaxial deformation experiments leading to fractures and failure of two different rocks, namely, Darley Dale Sandstone (DDS) and AG Granite (AG). By means of q-statistical formalism, we are able to characterize the pre-failure processes in both types of rocks. In particular, we study AE inter-event time and AE inter-event distance distributions. Both of them can be reproduced with q-exponential curves, showing universal features which are observed here for the first time and could be important in order to understand more in detail rock fractures dynamics.

The distributed acoustic sensing (DAS) has great potential for monitoring natural-resource reservoirs and borehole conditions. However, the large volume of data and complicated wavefield add challenges to processing and interpretation. In this study, we demonstrate that seismic interferometry based on deconvolution is a convenient tool for analyzing this complicated wavefield. We extract coherent wave from the observation of a borehole DAS system at the Brady geothermal field in Nevada. Then, we analyze the coherent reverberating waves, which are used for monitoring temporal changes of the system. These reverberations are tirelessly observed in the vertical borehole DAS data due to cable or casing ringing. The deconvolution method allows us to examine the wavefield at different boundary conditions. We interpret the deconvolved wavefields using a simple 1D string model. The velocity of this wave varies with depth, observation time, temperature, and pressure. We find the velocity is sensitive to disturbances in the borehole related to increasing operation intensity. The velocity decreases with rising temperature, which potentially suggests that the DAS cable or the casing are subjected to high temperature. This reverberation can be decomposed into distinct vibration modes in the spectrum. We find that the wave is dispersive, and the the fundamental mode propagate with a large velocity. The method can be useful for monitoring borehole conditions or reservoir property changes. For the later, we need better coupling than through only friction in the vertical borehole to obtain coherent energy from the formation.

The subject of the research is to Development of laser ablation method for Fabrication of surface acoustic wave sensors on quartz wafer, the target of the GQW – is to design Acoustic wave sensor by using laser ablation method. By using the surface acoustic wave theory to sense by the signal and using this physical phenomenon, We will design the sensor which transduce an input electrical signal into a mechanical wave which unlike an electrical signal, can be easily influenced by physical phenomena. The device then transducers this wave back into an electrical signal on the secondary terminal of the sensor. Changes in amplitude, phase, frequency, or time-delay between the input and output electrical signals can be used to measure the presence of the desired Our work in this part, especially the practical part like temperature, vibration ,etc. we design a combs on the waver of quartz to make like an electrode primary electrode & secondary electrode by putting coats of cuppers & vanadium on the waver and then using the fiber optic laser regime to design this combs to can able transfer the signal by ablation the most important here to use the regime of fiber optic laser then we using this sensor in any electronic circuit How we will select the suitable kind of laser to design, this is the most important part, and what it will be the diameter of that combs of secondary and primary , how much the value of the wave length to select the micro distant combs to avoid any inductance and interference for transferred signal , also take the benefit of using MEMS theory in our project.

A novel characterization method for discrete saw filters vibrational sensitivity is presented. The proposed approach allows the characterization of filters under vibrations and the extraction of a behavioural model. Filters are assumed to be transducers so that external induced vibrational energy is partially transformed in a undesired simultaneous amplitude and phase modulation of the input RF signal. When the filter is mechanically excited with vibrations, it introduces spurious amplitude and phase modulation to the input signal that can potentially affect the link quality.

An area has been designated for demonstrating the utility of marine hydrokinetic turbines in Minas Passage, Bay of Fundy. Marine renewable energy may be useful for the transition from carbon-based energy sources but there is concern for the safety of fish that might encounter turbines. Acoustic receivers that detect signals from acoustically tagged fish that pass through the tidal demonstration area and detection efficiency of tag signals might be used to estimate the likelihood of fish encountering marine hydrokinetic turbines. The method requires that tagged fish passing through the development area will be reliably detected by a receiver array. The present research tests the reliability with which passing tags are detected by suspending tags beneath GPS-tracked drifters. Drifters carrying high residency Innovasea tags that transmitted every 2 seconds were usually detected by the receiver array even in fast currents during spring tides but pulse position modulation tags were inadequate. Sometimes very few high residency tag signals were detected when fast tidal currents swept a drifter through the receiver array, so increasing the transmission interval degrades performance at the tidal energy development area. High residency tags suspended close to the sea surface were slightly less likely to be detected if they passed by during calm conditions. Previously measured detection efficiencies were found to slightly overestimate the chances of a high residency tag carried by a drifter being detected as it passed by a receiver. This works elucidates the effectiveness with which acoustically tagged fish are detected in fast, highly turbulent tidal currents and informs the application of detection efficiency measurements to calculate the probability that fish encounter a marine hydrokinetic turbine.

Seafloor geodetic station positioning generally uses internal precision to judge the quality of the positioning result, which has many limitations. This paper proposes to use a seafloor geodetic station structure, which can obtain the external coincident accuracy of the acoustic beacon positioning, to evaluate the quality of the observation configuration. The results of the sea trial show that a circular line with a radius of 2 times the depth of the water has an internal precision and an external coincident accuracy of approximately 0.02m; this circular line path also happens to be the best trajectory.

The purpose of this work is to study the mechanism of running-in during the friction and to determine the informative parameters characterizing the degree of its completion. During the friction, contact interaction of rough surfaces causes various wave phenomena covering a wide range of frequencies, the subsequent frequency analysis can provide information about the sizes of wave sources and thereby clarify the mechanism of interaction between surface roughness. The using of the wavelet transform for processing of the signals of audible acoustic emission made it possible to determine the beginning and the end of the change in the frequency ranges of the interaction of roughness. The code developed by the authors was used to analyze the acoustic emission signals by using wavelet energy and entropy criteria. The mother wavelet was chosen by carefully evaluating the effectiveness of 54 preliminary candidates for the mother wavelet from 7 wavelet families, ac-cording to three criteria: 1) maximum wavelet energy; 2) Shannon entropy minimum; 3) maximum energy-to-Shannon entropy ratio.

We proposed a novel concept of flight time matrix (FTM). In this work, the proposed FTM was verified first numerically. The numerical simulation revealed perfect results which showed that FTM can be used to assist the nondestructive evaluation of ballistic armor plates using acousto-ultrasonics. Two donated commercial ballistic armor plates were sought for a case study where artificial defects were prepared. The results of FTM were reasonably well. The artificial defects were clearly identifiable in one directional location array and FTM contour graphs. More comprehensive superimpositions of flight time vs location and FTM contour plots can be advanced to a better visualization of the defect presence. The resolution of FTM method is in the range of submillimeter or less. This study demonstrated that AU (acousto-ultrasonics) technique is a field applicable and yet reliable tool for inspection of the hidden defects in body armors. A broader merit of the proposed FTM algorithm is that it may promote the development of specific tools/device for nondestructive evaluations field.

Non-destructive testing is an emerging need in manufacturing processes and in service of ballis-tic armor plates. It has been shown that acoustic emission and ultrasonics are among the most applicable techniques. However, these techniques often require relative sophisticated processing and strong tech background for the evaluators. The purpose of the present work is to develop a flight time based algorithm and to demonstrate this algorithm using commercial multilayered armor plates. We proposed a novel concept of flight time matrix (FTM). In this work, the proposed FTM was verified first numerically. The numerical simulation revealed perfect results which showed that FTM can be used to assist the nondestructive evaluation of ballistic armor plates using acous-to-ultrasonics. Two donated commercial ballistic armor plates were sought for a case study where artificial defects were prepared. The results of FTM were reasonably well. The artificial defects were clearly identifiable in one directional location array and FTM contour graphs. More com-prehensive superimpositions of flight time vs location and FTM contour plots can be advanced to a better visualization of the defect presence. The resolution of FTM method is in the range of submillimeter or less. This study demonstrated that AU (acousto-ultrasonics) technique is a field applicable and yet reliable tool for inspection of the hidden defects in body armors. A broader merit of the proposed FTM algorithm is that it may promote the development of specific tools/device for nondestructive evaluations field.

Acoustic metasurface are artificial structures which could manipulate the wavefront in sub-wavelength dimensions and the previous proposed acoustic metasurface were mostly realized with single materials. An acoustic metasurface with composite structure is proposed for underwater acoustic stealth considering both wavefront manipulation and sound absorption. The unit cells of the metasurface are composed by metallic supporting lattice, interconnecting polymer materials and mass balancing columns. With the gradual modulations of equivalent physical properties along the horizontal direction of metasurface, the incident acoustic wave is reflected to other directions. Meanwhile, the polymer material inside the unit cells would dissipate the acoustic wave energy due to inherent damping properties. With the simultaneous modulations of reflected wave direction and scattering acoustic amplitude, significant improvement of underwater stealth effect is achieved. Compared with single-phase metasurface, the Far-Field Sound Pressure Level (FFSPL) of the multiphase metasurface decreased by 4.82 dB within the frequency range of 3kHz~30kHz. Under a hydrostatic pressure of 5MPa, the linearized mean stress for multiphase metasurface is only 1/3 of that of single-phase metasurface due to much thicker struts and much more uniform stress distribution. The proposed composite structure possesses potential applications due to acceptable thickness (80mm) and low equivalent density (1100 kg/m3).

The plate embedded with acoustic black hole (ABH) indentations is potential for structural vibration and noise control. This work focuses on the mid- and low-frequency performance of plates embedded with the array of ABH for energy focalization and vibration & noise suppression. Plates embedded with two-dimensional ABHs are modelled with detailed Finite Element (FE) models, and the power flow method is introduced to analyze the energy propagation characteristics arising from ABH effect. Then the distribution of average vibration power density along ABH radius is studied. Next, the energy dissipation effects of the plate model embedded with ABH array with two types of damping layers are investigated. Finally, the sound pressure levels of the ABH structure are calculated and discussed. This work is helpful to understand the characteristics of plates embedded with ABH array in reducing vibration and noise radiation. Results show the tremendous potential of ABH array for vibration and noise control.

Postpartum depression (PPD), a condition that affects up to the 15% of mothers in high-income countries, reduces attention toward the needs of the child and it is among the first causes of infanticide. PPD is usually identified using self-report measures and therefore the diagnosis may not always be valid. Previous studies highlighted the presence of significant differences in the acoustical properties of the vocalizations of children of depressed and healthy mothers. In this study, cry episodes of infants of depressed and non-depressed mothers are analyzed to investigate the possibility that a machine learning model can identify PPD in mothers from the acoustical properties of infants' vocalizations. Acoustic features (F0, F1-4, Intensity) are first extracted from recordings of crying infants, then novel cloud-based artificial intelligence models are employed to identify maternal depression versus non depression from estimated features. Trained model shows that commonly adopted acoustical features can be successfully used to individuate Post-Partum Depressed mothers with very high accuracy (89.5%).

This paper presents a study of different types of parametric signals with application to underwater acoustic communications. In all the signals, the carrier frequency is 200 kHz, which corresponds to the resonance frequency of the transducer under study and different modulations are presented and compared. In this sense, we study modulations with parametric sine sweeps (4 to 40 kHz) that represent binary codes (zeros and ones), getting closer to the application in acoustic communications. The different properties of the transmitting signals in terms of bit rate, directivity, efficiency and power needed are discussed as well.

Surface acoustic wave (SAW) is effective for the manipulation of fluids and particles in microscale. The current approach of integrating interdigitated transducers (IDTs) for SAW generation into microfluidic channels involves complex and laborious microfabrication steps. These steps often require the full access to clean room facilities and hours to align the transducers to the precise location. This work presents an affordable and innovative method for fabricating SAW-based microfluidic devices without the need of clean room facilities and alignment. The IDTs and microfluidic channels are fabricated in the same process and thus precisely self-aligned in accordance with the device design. With the use of the developed fabrication approach, a few types of different SAW-based microfluidic devices have been fabricated and demonstrated for particle separation and active droplet generation.

The present study investigated how two types of face masks affected seven acoustic parameters, commonly used in forensic speaker recognition, in several languages. Reading samples from an excerpt of “The Little Prince” were recorded by volunteers of both genders speaking in Lithuanian, Croatian, Romanian, Turkish, Ukrainian, Portuguese, Georgian, Hungarian, Spanish, Russian, Polish, and German, without a protection mask, wearing a surgical mask, and wearing an FFP2 mask. In addition, recordings from mobile and landline communications in some of the mentioned languages were also obtained. A total of 860 volunteers were recorded. The dataset is part of the Forensic Multilingual Voices Database (FMVD), developed under the “Competency, Education, Research, Testing, Accreditation, and Innovation in Forensic Science” (CERTAIN-FORS) project, funded by the European Union (EU) and coordinated by the European Network of Forensic Science Institutes (ENFSI). The results showed that face masks have an impact on the studied acoustic parameters and that the effects vary with mask type, sex, language, and recording channel.

The review considers physics and some applications of a new approach that promises to be a breakthrough in efficiency and instrumentation of various methods for nondestructive testing (NDT) of composites. The approach is based on frequency-selective properties of defects which fall into resonance (Local Defect Resonance (LDR)) at certain frequencies. An activation of LDR enables to route the input acoustic energy directly to the defect that dramatically increases its vibration amplitude and thus facilitates defect-selective imaging, rises efficiencies of various derivative acoustic NDT methods (nonlinear, acousto-thermal) and enables to develop some new methodologies, like Resonant Air-Coupled Emission (RACE), machine and remote imaging.

Recent publications on acoustic MEMS transducers present a new three-dimensional folded diaphragm that utilizes buried in-plane vibrating structures to increase the active area from a small chip volume. Characterization of the mechanical properties plays a key role in the development of new MEMS transducers, whereby established measurement methods are usually tailored to structures close to the sample surface. In order to access the lateral vibrations, extensive and destructive sample preparation is required. This work presents a new passive measurement technique that combines acoustic transmission measurements and Lumped-element modelling. For diaphragms of different lengths, compliances between 0.08 ∙ 10-15 and 1.04 ∙ 10-15 m³/Pa are determined without using destructive or complex preparations. In particular, for lengths above 1000 µm, the results differ from numerical simulations only by 4% or less.

The study examines the noise, vibration, and harshness (NVH) management of electric vehicle (EV) powertrains, considering the challenges of the automotive industry's transition to electric drivetrains. The growing popularity of EVs brings new NVH challenges, as the lack of internal combustion engine (ICE) noise makes drivetrain noise more prominent. Key to managing NVH in EV powertrains is understanding the noise from electric motors, inverters, and gear systems. Noise from electric motors, mainly resulting from electromagnetic forces, and high-frequency noise generated by inverters significantly impact overall NVH performance. The article details sources of mechanical noise and vibration, including gear defects in gear systems and shaft imbalances. Methods presented in the publication include simulation and modeling techniques that help identify and solve NVH difficulties. Tools like multi-body dynamics (MBD), finite element method (FEM), and multi-domain simulation are crucial for understanding the dynamic behavior of complex systems. With the support of simulations, engineers can predict noise and vibration challenges and develop effective solutions during the design phase. The study emphasizes the importance of a system-level approach in NVH management, where the entire drivetrain is modeled and analyzed together, not just individual components.

Accurate and prompt determination of fire types is essential for effective firefighting and reducing damages. However, traditional methods such as smoke detection, visual analysis, and wireless signals pose unavailability in identifying fire types. This paper introduces FireSonic, an acoustic sensing system that leverages commercial speakers and microphones to actively probe the fire using acoustic signals, effectively identifying indoor fire types. By incorporating beamforming technology, FireSonic first enhances signal clarity and reliability, thus mitigating signal attenuation and distortion. To establish a reliable correlation between fire types and sound propagation, FireSonic quantifies the Heat Release Rate (HRR) of flames by analyzing the relationship between fire heated areas and sound wave propagation delays. Furthermore, the system extracts spatiotemporal features related to fire from channel measurements. Experimental results demonstrate that FireSonic attains an average fire type classification accuracy of 95.5% and a detection latency of less than 400 ms, satisfying the requirements for real-time monitoring. This system significantly enhances the formulation of targeted firefighting strategies, boosting fire response effectiveness and public safety.

To address the requirements of sonar imaging, such as high receiving sensitivity, wide bandwidth, wide receiving angle, an AlN PMUT with an optimized ratio of 0.6 for the piezoelectric layer diameter to backside cavity diameter is proposed in this paper. A sample AlN PMUT is designed and fabricated with SOI substrate-based bulk MEMS process. The characterization test result of the sample demonstrates a -6 dB bandwidth of approximately 500 kHz and a measured receiving sensitivity per unit area of at 1.37 V/μPa/mm2, which significantly surpasses the performance of previously reported PMUTs. The -6 dB horizontal angles of the AlN PMUT at 300 kHz and 500 kHz are measured 68.30° and 54.24°, respectively. To achieve an accurate prediction of its characteristics when being packaged and assembled in a receive array, numerical simulations with the consideration of film stress are conducted. The numerical result shows a maximum deviation of ±7% in the underwater receiving sensitivity across the frequency range of 200 kHz to 1000 kHz and a deviation of about 0.33% in the peak of underwater receiving sensitivity comparing to the experimental data. By such good agreement, the simulation method reveals its capability of providing theoretical foundation for enhancing the uniformity of the AlN PMUTs in future studies.

Nowadays, microfluidics has become an anarchist interdisciplinary topic with considerable attention in a wide range of biotechnology applications. In this research work, numerical investigation of microfluidic micro-mixer is carried out using hybrid actuation approach with different micropillar shapes and gaps. For this purpose, COMSOL Multiphysics is used with three different physics such as thermoviscous acoustic to solve acoustic governing equations, laminar physics is used to solve fluid flow governing equations and diluted transport species is used to solve mixing governing equations. The simulations were carried out with flow velocity of 200 µm/s at both inlets with an oscillation frequency of 15kHz. The outcomes were in the form of acoustic characteristics such as acoustic pressure, acoustic velocity, acoustic streaming and mixing index. The results revealed that the inclusion of micropillars enhanced the mixing performance and strength of acoustic field resulting in improvement of mixing performance compared to the case without micropillars. In addition, it was also investigated that blade shape micropillars with 0.150 mm gaps deliver best results compared to the other cases with maximum and minimum values of the mixing index 0.95 and 0.72 respectively. The obtained results can be extremely helpful for design and modifications of hybrid microfluidics micro-mixer.

This paper presents an acoustic emission (AE) detection method for refined oil storage tanks, enabling online detection of corrosion points and microleakage in the tank floor. The method utilizes an explosion-proof acoustic emission instrument to detect the floor of a refined oil storage tank. By calculating the time difference between the defective acoustic signal and the speed of acoustic wave transmission, a mathematical model is constructed to analyze the detected signals. A technical scheme for acoustic emission detection in storage tanks is designed, and the instru-ment is used to carry out acoustic emission testing on the product oil storage tank floor. Based on these test results, location analysis of acoustic emission sources is conducted on the bottom plate of the tank, evaluating its corrosion condition accurately. The consistency between the evaluation and subsequent open tank tests confirms that using acoustic emission technology effectively captures corrosion signals from product oil storage tank bottoms. Consequently, it significantly improves inspection efficiency by avoiding unnecessary tank-opening operations. Combining this method with open tank inspection operations such as the leakage magnetic method, one can fully grasp the status of the refined oil storage tanks.

Acoustic focusing of particle flow in microfluidics has been shown to be an efficient tool for particle separation for various chemical and biomedical applications. The mechanism behind the method is the selective effect of the acoustic radiation force on distinct particles. In this way, they can be selectively focused and separated. The technique can also be applied under stationary conditions, i.e., in the absence of fluid flows. In this study, the manipulation of self-propelled particles, such as Janus particles, in an acoustofluidic setup is investigated. In experiments with self-propelled Janus particles and passive beads, we explore the interplay between self-propulsion and the acoustic radiation force. Our results demonstrate unusual and potentially useful effects such as selective trapping, escape and assisted escape in binary mixtures of active and passive particles. We also analyze various aspects related to the behavior of Janus particles in acoustic traps in the presence and absence of flows.

In this paper, we aim to address the challenge of airflow interference during fault detection in high-speed train bogies by introducing a flow field and investigating the characteristics of the sound field distribution of critical components under its influence. This approach overcomes the limitation observed in previous studies that ignored the impact of the flow field. Furthermore, we evaluate and compare various layouts for inter-track acoustic sensor arrays. The proposed sensing methods hold significant practical engineering value, and the collected data serves as a valuable reference for acquiring acoustic signals from key bogie components in future research.

When a suspension passes through a high-frequency standing sound wave, the particles it contains are manipulated by acoustic forces. In a one-dimensional sound field, these forces lead to a planar arrangement of the particles and the formation of agglomerates. It is known that the combination of these forces and depth filtration can be utilized to significantly increase the filter efficiency of coarse-pored media. So far, this concept has only been used in microfluidics. In this paper, we present the results of a scaled-up filtration channel to test the viability of the industrial application of acoustically assisted filtration systems for the removal of microparticles. The influences of acoustic power input, flow rate, and the porosity of the filter media are investigated. In addition to verifying the scalability, a significant decrease in the large particle fraction in the outflow of the channel was observed when a high-power sound field is applied. Furthermore, the formed agglomerates tend to rise to the fluid surface. The floating particles mostly consist of a large particle fraction.

The paper deals with applying Artificial Intelligence techniques to examine CHIRP-recorded data in sand and sandstone sea-bottom sites. The provided analysis of the state of the art portrays that actual time series or spectrum backscattered data from a point on the sea bottom were rarely used as the features for machine learning models. The results of the examination indicate that types of sea bottom can be quantitatively characterized by applying logistic regression models to either the backscatter time series of a frequency-modulated signal or the spectrum of that backscatter. The examination accuracy reached 90% for the time series and 94% for the spectra. The application of spectral data as features for more advanced machine learning algorithms, and the advantages of its combination with other types of data have great potential for future research and the enhancement of remote marine soil classification.

The issue of monitoring and early warning of rock instability has received increasing critical attention in the study of rock engineering. To investigate the damage evolution process of granite under triaxial compression tests, acoustic emission (AE) tests were performed simultaneously. This study firstly introduced two novel parameters, i.e., the coefficient of variation (CoV) of the information entropy and correlation dimension of the amplitude data from the AE tests, to identify the precursor of the failure of granite. Then the relationship between the changes in these parameters and the stress-time curve was compared and analyzed. The results of this study show that: (1) There is a strong correlation between the CoV of the information entropy and the failure process of granite. The granite failed when the CoV curve raised to a plateau. (2) The fluctuation of the correlation dimension indicates the different stages of the loading process, i.e., the initial compaction stage, the linear elastic stage, the yield stage, and the failure stage. Each stage contains a descending and a rising process in the correlation dimension curve, which indicates that this parameter could be used to identify the precursor of the failure as well. (3) The combined analysis of the two can improve the accuracy of rock instability prediction. This study provides new insights into the prediction of rock instability, which has theoretical implications for the stability of subsurface engineering rock masses.

Noise induces oxidative stress in the cochlea followed by sensory cell death and hearing loss. The proof of principle that injections of antioxidant vitamins and Mg²⁺ prevent noise-induced hearing loss (NIHL) has been established. However, effectiveness of oral administration remains controversial and otoprotection mechanisms unclear. Using auditory evoked potentials, quantitative PCR and immunocytochemistry, we explored effects of oral administration of vitamins A, C, E and Mg²⁺ (ACEMg) on auditory function and sensory cell survival following NIHL in rats. Oral ACEMg reduced auditory thresholds shifts after NIHL. Improved auditory function correlated with increased survival of sensory outer hair cells. In parallel, oral ACEMg modulated the expression timeline of antioxidant enzymes in the cochlea after NIHL. There was increased expression of Glutathione peroxidase-1 and Catalase at 1 and 10 days, respectively. Also, pro-apoptotic Caspase-3 and Bax levels were diminished in ACEMg-treated rats, at 10 and 30 days, respectively, following noise overstimulation, whereas, at day 10 after noise exposure, the levels of anti-apoptotic Bcl-2, were significantly increased. Therefore, oral ACEMg improves auditory function by limiting sensory hair cell death in the auditory receptor following NIHL. Regulation of the expression of antioxidant enzymes and apoptosis-related proteins in cochlear structures is involved in such otoprotective mechanism.

In this paper we present experimental results concerning Acoustic Emission (AE) recorded during cyclic compression tests on two different kinds of brittle building materials, namely concrete and basalt. The AE inter-event times were investigated through a non-extensive statistical mechanics analysis which shows that their decumulative probability distributions follow q-exponential laws. The entropic index q and the relaxation parameter q  1=Tq, obtained by fitting the experimental data, exhibit systematic changes during the various stages of the failure process, namely (q; Tq) linearly align. The Tq = 0 point corresponds to the macroscopic breakdown of the material. The slope, including its sign, of the linear alignment appears to depend on the chemical and mechanical properties of the sample. These results provide an insight on the warning signs of the incipient failure of building materials and could therefore be used in monitoring the health of existing structures such as buildings and bridges.

The use of salt rock for underground radioactive waste disposal facilities requires a comprehensive analysis of creep-damage process in salt rock. A computer-controlled creep setup is employed to carry out a creep test of salt rock lasted as long as 359 days under a constant uniaxial stress. The AE space-time evolution and energy releasing characteristics during creep test are studied in the meantime. A new creep-damage model is proposed on the basis of fractional derivative by combining the AE statistical regularity. It indicates that the AE data in non-decay creep process of salt rock can be divided into three stages. Furthermore, the parameters of new creep-damage model are determined by Quasi-Newton method. The fitting analysis suggests that the creep-damage model based on fractional derivative in this paper provides a precise description of full creep regions in salt rock.

Reliable and precise damage localization in mechanical structures is of high importance in the context of structural health monitoring (SHM). The acoustic emission (AE) method has already shown its excellent suitability for damage localization. However, low signal-to-noise ratios (SNRs) are often prevalent in SHM, thus an increase in localization accuracy and robustness is still in demand. The present study faces this task through the integration of various model knowledge for AE source localization. The basis of the presented algorithm is the consideration of the dispersive behavior of elastic waves in thin-walled structures. The continuous wavelet transform (CWT) is used to obtain time-frequency representations of the signals, where frequency-dependent values for time-of-arrival (TOA) are extracted. Furthermore, the algorithm incorporates the knowledge that all sensors receive signals with the same time and location of origin, as well as the slightly different sensitivity of the theoretically equal sensors. The final localization results are achieved by a two-parameter grid search optimization. The algorithm is experimentally tested on a large aluminum plate with four piezoelectric wafer active sensors (PWASs) arranged in an array of 100 mm × 100 mm. The mean localization error of pencil lead breaks at ten different positions within the sensor array is used as an accuracy measure. It is shown that as more of the described model knowledge is incorporated into the localization, the accuracy increases. With the final algorithm, the mean localization error is more than halved compared to AE localization based on classical TOA estimation. Although the experiment described is conducted under laboratory conditions, the remarkable increase in accuracy suggests that AE source localization may be successful even at low SNR as typical for operational conditions.

In the field of music education, the incorporation of technology originally designed for professionals presents both significant opportunities and challenges. These technologies, although advanced and powerful, are often not adapted to meet the specific needs of the educational envi-ronment. Therefore, this study details the design and implementation process of a system con-sisting of a hardware device called "Play Box" an associated software, "Imaginary Play Box". The Design Sciences Research Methodology (DSRM) specifically adapted to software development was used to structure the project. The three phases shown in this study ranged from the conception of an initial prototype to the realisation of a working software. During the design phase, a questionnaire was developed to evaluate various aspects of the soft-ware, such as the visual interface, the programming of components and the sound interactivity provided by the Play Box. The technique of panels of experts in music pedagogy and program-ming in MAX-MSP was used to obtain critical feedback. This expert evaluation was crucial to it-erate and polish the software, culminating in a beta version optimised for the creation of electro-acoustic music for music education.

The acoustic environment in learning spaces significantly influences learning effectiveness and occupant well-being. Recent studies have shown that a series of architectural factors within physical learning environments can impact students' educational experiences. This research delves into the relationship between architectural characteristics and the perceived acoustic environment among 467 primary students in 19 learning spaces across 9 schools in Chile. The survey comprises a student questionnaire, a checklist evaluating space characteristics, and acoustic measurements of indoor noise levels during occupied conditions. Examined topics include Indoor Environmental Quality (IEQ) comfort perception, noise annoyance, hearing ability, and acoustic preference. Architectural characteristics considered encompass flexible and acoustic space design parameters. The results indicated that noise discomfort was a common issue, especially in traditional learning spaces without acoustic treatment. The type of learning space (traditional or flexible settings) has a greater impact on acoustic perception particularly concerning noise discomfort and acoustic preference. However, poorly acoustic spaces lacking absorbing materials or exhibiting lower spatial density (m2 per student) contribute to increased indoor noise levels affecting noise annoyance caused by children's talking inside. The study emphasizes the importance of considering both architectural design and acoustic conditioning for optimizing the acoustic experience in educational spaces.

This paper presents the results of experiments on the study of a hydraulic fracture interaction with a preliminary created fracture that simulates a natural fracture. A distinctive feature of the conducted experiments is the ability to use an ultrasonic sounding to measure the fracture propagation and opening simultaneously with the fluid pore pressure measurements at the several points of the porous saturated sample. It allows to obtain the pressure distributions at various experiment stages and to establish a relation between the pore pressure distribution and the hydraulic fracture propagation and its interaction with macroscopic natural fracture. The possibilities of active ultrasonic monitoring have been expanded due to preliminary calibration experiments, which make it possible to estimate the fracture opening value by attenuation of ultrasonic pulses. The experiments show that the fracture propagation is limited by the natural fracture. This is caused by the hydraulic fracturing fluid leaks into the natural fracture, so both hydraulic fracture and natural fracture compose united hydraulic system.

Aircraft heat exchangers play a crucial role in maintaining thermal balance and ensuring that essential components operate efficiently and safely. In this context, it is highly relevant to gain knowledge about the deterioration and the predominant damage mechanisms of these components. In this study, two different non-destructive methods are employed to analyze the damage initiation of a heat exchanger part during fatigue test. On the one hand, Acoustic Emission technique is employed using membrane-free microphones capable of capturing a broad bandwidth. The acoustic events were classified by a machine learning algorithm to determine their source and damage mechanisms. On the other side, Digital Image Correlation (DIC) allowed the measurement of the strain evolution along the test and more precisely, redistributions were considered as damage indicators. As a result, it was identified that AE served as early damage indicator as the cumulative number of events was in good agreement with the severity of the damage. With respect to classification two clear clusters ascribed to different type of events were identified. In the case of DIC, strain redistributions gave clear indications of damage or deterioration but at a later stage compared to AE

Multiple entities use unmanned underwater drones for various functions, but how can they navigate underwater at such depths without a pilot? It is essential to understand how different unmanned underwater drones, such as remotely operated and autonomous underwater vehicles, function with underwater sensing technology. As each unmanned underwater drone has its function, the combination or chief use of the sensors is equally essential to recognize. Different underwater drone designs can be more cost-effective when a human is not on board as it can lead to a smaller, streamlined design in which oxygen and pressure control need not be a factor. Without considering oxygen limitations, these underwater drones can remain submerged for extended periods. These underwater vehicles operate autonomously or in conditions that may leave the individuals controlling the trajectory relying upon these sensors. It is also necessary to review how these sensors work, how they are implemented, and how they can help the public. This review was performed to address these research questions and provide an overview of sensors employed by unmanned underwater vehicles.

This paper investigates the ion-acoustic wave structures in fluid ions for the Benjamin-Bona-Mahony-Peregrine-Burgers (BBMPB) equation. The various types of wave structures, are extracted including the three-wave hypothesis, breather wave, lump periodic, mixed-type wave, periodic cross-kink, cross-kink rational wave, M-shaped rational wave, M-shaped rational wave solution with one kink wave and M-shaped rational wave with two kink wave solutions. The Hirota bilinear transformation is a powerful tool that allows us to accurately solutions and predict the behavior of these wave structures. Through our analysis, we gain a better understanding of the complex dynamics of ion-acoustic waves and their potential applications in various fields. Moreover, our findings contribute to the ongoing research in plasma physics that utilize ion-acoustic wave phenomena. To show the physical behavior of the solutions, some 3D plots have been performed and their respective contour level, choosing different values of the parameters.

Acoustic emission (AE) is caused by the sudden release of energy by a material as a result of material degradation related to deformation, crack, or fault within a solid. The same situation also occurs in leaks caused by turbulence in the fluid around the leak. In this study, analytical modeling for AE due to leakage through a circular pinhole in a gas storage cylinder was performed. The displacement fields responsible for AE, excited by the concentrated force (CF) associated with the turbulent flow though the pinhole, were derived by solving the Navier-Lamé equation. The CF as an excitation source was formulated in terms of a fluctuating Reynolds stress (FRS) and spatial Green’s function. In particular, a series of experiments were conducted under different operating conditions to explore the characteristics of the AE signals due to leak in a gas cylinder. Finally, the simulation and experimental results were compared to verify the accuracy of the simulation results.

Wet granulation is a frequent process in the pharmaceutical industry. As a starting point for numerous dosage forms, the quality of the granulation not only affects subsequent production steps but also impacts the quality of the final product. It is thus crucial and economical to monitor this operation thoroughly. Here, we report on identifying different phases of a granulation process using a machine learning approach. The phases reflect the water content which in turn influences the processability and quality of the granule mass. We used two kinds of microphones and an acceleration sensor to capture acoustic emissions and vibrations. We trained convolutional neural networks (CNNs) to classify the different phases using transformed sound recordings as the input. We achieved a classification accuracy of up to 90 % using vibrational data and an accuracy of up to 97 % using the audible microphone data. Our results indicate the suitability of using audible sound and machine learning to monitor pharmaceutical processes. Moreover, since recording acoustic emissions is contactless, it readily complies with legal regulations and present Good Manufacturing Practices.

As rotary machines have become more complicated, balancing processes have been classified as a vital step in condition monitoring to ensure machines operate both reliably and safely. This is especially important for flexible machines which normally work at rotations speeds above critical limits. Imbalance is a common problem in flexible rotating machinery that can lead to extreme vibration and noise levels. This is one of the major reasons for studying various balancing methods applied to the vibration response of rotating machines. Recently, the relation between acoustic and vibration response during a rotary machine balancing process based on the Four-Run method has been presented for constant speed machines. This method cannot be applied to machines in start-up or shut-off. Hence, by considering the acoustic and vibration responses of a machine between its critical speeds, this research presents a new innovative speed-variant balancing method based on the original Four-Run method, named as "Peak to Peak for Critical Speeds (PPCS)". The proposed method consists of two major types of application: the first is in the Run-up of the machine and the second is in Shut-down. Experimental laboratory results show that the PPCS method can be implemented for speed-variant and flexible rotary machines during run-up or shut-down transient processes based on acoustic and vibration measurements. As a phase-less and a contactless method, the PPCS can be employed as an innovative and readily available method for condition monitoring in the future.

To date electric pianos and samplers tend to concentrate on authenticity in terms of temporal and spectral aspects of sound. They barely recreate the original sound radiation characteristics, contribute to the perception of width and depth, vividness and voice separation, especially for instrumentalists, who are located in the near field. This paper describes an operational procedure to measure, store, and synthesize the complete sound of a harpsichord, including its spatial sound radiation characteristics. First, actuators excite the instrument at the intersection point of each string with the bridge with an exponential sine-sweep. Then, the radiated sound field is recorded in the near and the far field with microphone arrays. The pressure distribution in the near field is propagated back to the soundboard of the instrument, using Minimum Energy Method. The vibration of each single string is captured with lightweight contact microphones. The soundboard is then replaced by an array of 128 loudspeakers. The loudspeaker signal is a convolution of the back-propagated sweep recording with the string recording to perform a wave field synthesis. Above the spatial Nyquist frequency, the Radiation Method is applied to perform a sound field synthesis which is valid for the listening region of the instrumentalist. The result is an electric harpsichord, that approximates the sound of a real harpsichord precisely in time, frequency, and space domain. Applications for such a radiation keyboard are music performance, instrument and synthesizer building and interactive psychoacoustic research.

The acoustic emission (AE) technique was applied to monitor the pitting corrosion of carbon steel in NaHCO₃ + NaCl solutions. The open circuit potential (OCP) measurement and the corrosion morphology in-situ capturing using optical microscope were conducted during AE monitoring. The corrosion micromorphology was characterized with scanning electron microscope (SEM). The propagation behavior and AE features of natural pitting on carbon steel were investigated. After the performing of signal processing including pre-treatment, shape preserving interpolation and denoising for raw AE waveforms, three types of AE signals can be classified in the correlation diagrams of new waveform parameters. Finally, a 2D pattern recognition method was established to calculate the similarity of different continuous AE graphics, which is quite effective to distinguish the localized corrosion from uniform corrosion.

Acoustic emission (AE) has proven to be a very useful technique for determining damage in ceramic matrix composites (CMCs). CMCs rely on various cracking mechanisms which enable non-linear stress-strain behavior with ultimate failure of the composite due to fiber failure. Since these damage mechanisms are all micro-fracture mechanisms, they emit stress waves ideal for AE monitoring. These are typically plate waves since for most specimens or applications one dimension is significantly smaller than the wavelength of the sound waves emitted. By utilizing the information of the sound waveforms captured on multiple channels from individual events, the location and identity of the sources can often be elucidated. The keys to the technique are the use of wide-band frequency sensors, digitization of the waveforms (modal AE), strategic placement of sensors to sort the data and acquire important contents of the waveforms pertinent for identification, and familiarity with the material as to the damage mechanisms occurring at prescribed points of the stress history. The AE information informs the damage progression in a unique way which adds to the understanding of the process of failure for these composites. The AE methodology was applied to composites tested in fatigue at different frequencies where identification of when and where AE occurred coupled with waveform analysis leads to source identification and failure progression.

Pipe-type cable systems, including high-pressure fluid-filled (HPFF) and high-pressure gas-filled (HPGF) cables, are widely used for underground high-voltage transmission. These systems consist of insulated conductor cables within steel pipes, filled with pressurized fluids or gases for insulation and cooling. Despite their reliability, faults can occur due to insulation degradation, thermal expansion, and environmental factors. As many circuits exceed their 40-year design life, efficient fault localization becomes crucial. Fault location involves pre-location and pinpointing. Therefore, a novel fully pinpointing approach for pipe-type cable systems is proposed, utilizing accelerometers mounted on the steel pipe to capture fault-induced acoustic signals and employing a time difference of arrival (TDOA) method to accurately pinpoint the location of the fault. Experimental investigations utilized a scaled-down HPFF pipe-type cable system model, featuring a carbon steel pipe, high-frequency accelerometers, and both mechanical and capacitive discharge methods for generating acoustic pulses. Tests evaluated propagation velocity, attenuation, and pinpointing accuracy with the pipe in various embedment conditions. Results demonstrated accurate fault pinpointing within centimeters, even in fully embedded pipes, with acoustic pulse velocities close to theoretical values. These findings highlight the potential of the novel acoustic pinpointing technique presented in this study to improve fault localization in underground systems, enhance grid reliability, and reduce outage. Further research is recommended to validate this technique on full-scale systems.

The sound power LW of wind turbines (WTs) over the past decades has developed in relation to their electric power P as LW ∝ logP. The spectral distribution of the sound did not change significantly over time. This applies to the average performance of wind turbines, with differences between individual WT types. Because of the expected growth of onshore wind energy, a greater number of people will be living close to wind farms. This sustains the need for sound reduction. Sound reduction measures, such as serrations, reduced tip speed and low noise modes, may counteract the development of higher sound power from ever bigger WTs. To investigate this, the sound production of WT types over the last decades is analysed in relation to their size and electric power and the application of sound reduction measures. The analysis includes the broad band A-weighted and low frequency sound power levels as well as more detailed spectral distributions. Results show that the sound power level of wind turbines above 3 MW on average increases less with size than smaller turbines did. This is due to a lower blade tip speed and the use of sound reducing serrations. The spectral content of wind turbine sound, including the lower frequencies, has not changed significantly.

In 2023, we proposed the modified Delay and Doppler Profiler (mDDP) as an inter-carrier interference (ICI) countermeasure for underwater acoustic OFDM mobile communications in a multipath environment. However, the performance improvement in computer simulation and pool experiments was not significant. In a subsequent study, the accuracy of the Channel Transfer Function (CTF), which is the input for the mDDP channel parameter estimation, was considered insufficient. Then a 2-step mDDP was devised. This paper presents simulations of underwater OFDM communications using 1- to 3-step mDDPs. The simulation conditions are a two-wave multipath environment where the receiving transducer moves at a speed of 0.3 m/sec and is subjected to a Doppler shift in the opposite direction. As NumCOL, the number of taps in the multi-tap equalizer which removes ICI, was increased, Bit Error Rate (BER) of 0.016 at NumCOL = 1 was significantly reduced by a factor of approximately 40 to BER of 0.00041 at NumCOL = 41 for the 2-step mDDP.

Acoustic Radiation Forced Impulse (ARFI) is an ultrasound integrated method, measuring stiff-ness by point shear wave elastography. To evaluate the diagnostic performance of ARFI of the liver and of the spleen, combined with spleen dimension and platelet count, in predicting clinical events in cirrhosis, a prospective and cross-sectional study was conducted between February 2017 and February 2021. The following ratio scores with ARFI measurements were performed: ALSDP (ARFI Liver-Spleen Diameter-to-Platelets ratio score), ASSDP (ARFI Spleen-Spleen Diam-eter-to-Platelets ratio score), ASSAP (ARFI Spleen-Spleen Area-to-Platelets ratio score), ALSAP (ARFI Liver-Spleen Area-to-Platelets ratio score). In 100 enrolled subjects, spleen ARFI, ASSDP, ASSAP, were significantly associated with high-risk oesophageal varices (HRVs) in the prospec-tive short- and long-term follow-up and in the cross-sectional study (p 0.7). ARFI-ratio scores can predict, in cirrhotic patients, the risk of developing HVRs in short and long-term period.

The quartz tuning fork used as an acoustic sensor in Quartz-Enhanced Photo-Acoustic Spectroscopy gas detection systems is usually read-out by means of a transimpedance preamplifier, based on a low-noise operational amplifier closed in a feedback loop. The gain-bandwidth product of the operational amplifier used in the circuit is a key parameter which must be properly chosen to guarantee that the circuit works as expected. Here we demonstrate that, if the value of this parameter is not sufficiently large, the response of the preamplifier exhibits a peak at a frequency which does not coincide with the series resonant frequency of the quartz tuning fork. If this peak frequency is selected for modulating the laser bias current and is also used as reference frequency of the lock-in amplifier, a penalty results in terms of signal to noise ratio at the output of the QEPAS sensor. This worsens the performance of the gas sensing system in terms of ultimate detection limits. We show that this happens when the front-end preamplifier of the quartz tuning fork is based on some amplifier models that are typically used for such application, both when the integration time of the lock-in amplifier filter is long, to boost noise rejection, and when it is short, in order to comply with a relevant measurement rate.

The article is devoted to the study of ultrasonic agglomeration of PM2.5 in uniform and non-uniform ultrasonic fields. The possibility of increasing the efficiency of ultrasonic agglomeration by initiating acoustic streams in a resonant non-uniform ultrasonic field is shown. A non-uniform ultrasonic field with zones of high and low sound pressure levels formed using a bending-oscillating disk transmitter made it possible to initiate acoustic vortex-type streaming that promote the movement of particles into the nodal areas of a standing wave and between them. The efficiency of ultrasonic treatment was determined indirectly by the degree of inertial trapping of agglomerates. It has been established that the impact of an non-uniform ultrasonic field in comparison with the impact of a uniform ultrasonic field makes it possible to increase the efficiency of inertial capture of agglomerates PM2.5 from 89% to 95%, PM1.5 from 85% to 92%, PM0.5 from 76% to 85%. The results obtained made it possible to propose a design for an agglomeration chamber, which allows for a multiple increase in the productivity of ultrasonic processing of a gas-dispersed flow.

This paper presents a novel sensor for the detection and characterization of regions of air turbulence that would be of use to improve UAV stability in bad weather. It consists of a combined Schlieren imager and a Radar Acoustic Sounding System (RASS) to produce dual modality “images” of air movement within the measurement volume. The ultrasound modulated Schlieren imager consists of a strobed point light source, parabolic mirror, light-block and camera which are controlled by two laptops. It provides a fine scale projection of the acoustic pulse modulated air turbulence through the measurement volume. The narrow beam 40 kHz/ 17 GHz RASS produces spectra based on Bragg enhanced Doppler radar reflections from the acoustic pulse as it travels. Tests using artificially generated air vortices showed some disruption of the Schlieren image and of the RASS spectrogram. This should allow the higher resolution Schlieren images to identify the turbulence mechanisms that are disrupting the RASS spectra.

Quantitative evaluation of the musical timbre and its variations is important for the analysis of audio recordings and computer-aided music composition. Using the FFT acoustic descriptors and their representation in an abstract timbral space, variations of a sample of monophonic sounds of chordophones (violin, cello) and aerophones (trumpet, transverse flute, and clarinet) sounds are analyzed. It is concluded that the FFT acoustic descriptors allow us to distinguish the timbral variations of the musical dynamics, including crescendo and vibrato. Furthermore, using the Random Forest algorithm, it is shown that the FFT-Acoustic provides a statistically significant classification to distinguish musical instruments, family of instruments, and dynamics. We observed a better behavior for the FFT-Acoustic descriptors when classifying pitch compared to some timbral features of Librosa.

Hyperacusis, i.e., an increased sensitivity to sounds, is described in several neurodevelopmental disorders (NDDs), including Fragile X Syndrome (FXS). The mechanisms underlying hyperacusis in FXS are still largely unknown and effective therapies are lacking. Big conductance calci-um-activated potassium (BKCa) channels have been proposed as a therapeutic target to treat several behavioral disturbances in FXS preclinical models, but their role in mediating their au-ditory alterations has not been specifically addressed. Furthermore, studies on the acoustic phe-notypes of FXS animal models have mostly focused on central rather than peripheral auditory pathways. Here we provided an extensive characterization of the peripheral auditory phenotype of the Fmr1-knockout (KO) mouse model of FXS at adulthood. We also assessed whether the acute administration of Chlorzoxazone, a BKCa agonist, could rescue the auditory abnormalities of mutant mice. Fmr1-KO mice both at 3 and 6 months showed a hyperacusis-like startle pheno-type with paradoxically reduced auditory brainstem responses associated with a loss of ribbon synapses in the inner hair cells (IHCs). BKCa expression was markedly reduced in the IHCs of KO mice, but only at 6 months, when Chlorzoxazone rescued mutant auditory dysfunction. Our findings highlight the age-dependent and progressive contribution of peripheral mechanisms and BKCa channels to hyperacusis in FXS, suggesting a novel therapeutic target to treat auditory dysfunction in NDDs.

This article presents a low-cost and flexible solution for acoustic startle response (ASR) tests that can be used in any laboratory with CED Power1401 or a similar Spike2-based interface. ASR is a reflexive response to an unexpected, loud acoustic stimulus, and prepulse inhibition (PPI) is a phenomenon in which the startle response is reduced when preceded by a weak prestimulus of the same modality. Measuring PPI is important because changes in PPI have been observed in patients with various psychiatric and neurological disorders. Commercial ASR testing systems are expensive, and their closed source code affects their transparency and result reproducibility. The proposed setup is easy to install and use, and simultaneous recording of ASR and brain activity (electrocorticogram or intracerebral local field potential) is possible. The Spike2 script is customizable and supports a wide range of PPI protocols. The article presents data obtained in female rats, both wild-type (WT) and dopamine transporter knockout (DAT-KO), showing the same tendency as the data obtained in males, with ASR on single pulse higher than ASR on prepulse+pulse, and PPI reduced in DAT-KO rats compared to WT.

Next Generation IoT systems will allow sustainable performance in long-term monitoring systems. This sustainability concept is applicable to soundscape description, as it allows monitoring in urban environments. In this work, the implementation of psycho-acoustic annoyance models in a 5G-enabled IoT system is proposed applying two Edge Computing approaches. A modified Zwicker’s model is adopted in this research, introducing a term that takes into account the tonal component of the captured sound. These implementations have been validated in a measurement campaign where several IoT devices have been deployed to evaluate different sound environments of a University Campus. Then, the analysis of the sound quality metrics is done in different location showing that if tonality is present in a noisy environment, it results in greater subjective annoyance. Moreover, the Just Noticeable Difference of these results are derived for the Zwicker’s psycho-acoustic annoyance to establish a limitation for this metric.

Understanding the effect of staking sequences and identifying the damage occurring within a structure using a structural health monitoring system are the keys to an efficient design of composite-based parts. In this research, a combination of digital image correlation (DIC) and acoustic emission (AE) is used to locate and classify the type of damage depending on the stacking sequence of the laminate during flexural loading. A comparison of the strain field results for unidirectional, cross-ply, and quasi-isotropic laminates was made in a first attempt to discuss their global behavior and to correlate the different damage patterns with the possible failure mechanisms. The damage was then addressed using a comprehensive interpretation of the acoustic emission signatures using the K-means classification of the acoustic events. The development of each damage mechanism was correlated to the applied load and expressed as a function of the loading rate to highlight the effect of the stacking sequence. Finally, the results of DIC and AE were combined to improve the reliability of the damage investigation without limiting the failure mechanism to matrix cracking, interfacial failure, and fiber breakage, as expected by the unsupervised event clustering.

The article presents the results of tests related to failure analysis and finding ways to diagnose used semiconductor elements, among other, in power electronics converter systems on vessels and offshore facilities (drilling and production rigs, wind turbines). Diagnostic relationships were found between the temperature change in the above systems and the signals generated in form of elastic waves of acoustic emission.

The presence of bubbles near the sea surface under certain conditions leads to abnormal sound scattering and a significant change in the acoustic properties of the upper layer of the sea. The article presents some results of sound scattering studies under various sea conditions, up to stormy conditions, when extensive bubble clouds arise. By the method of unsteady acoustic spectroscopy, data on the size distribution of bubbles at various depths have been obtained, which can be described by a power function with exponential decay at small bubble sizes of the order of 10 microns. Estimates of the gas content in bubble clouds and their influence on the acoustic characteristics of the upper layer of the sea have been carried out. It is shown that at sufficiently high concentrations, sharp increases in absorption and dispersion of the sound velocity are observed. Modeling of sound propagation in the presence of a quasi-homogeneous bubble layer shows that it leads both to a change in the laws of the average decay of the sound field along the sound propagation path and to a change in the shallow spatial structure of the field.

This work focuses on analyzing acoustic emission (AE) signals as a means to predict failure in structures. Two main approaches are considered: (i) long-range correlation analysis using both the Hurst (H) and the Detrended Fluctuation Analysis (DFA) exponents, and (ii) natural time domain (NT) analysis. These methodologies are applied to the data collected from two application examples: a glass fiber reinforced polymeric plate and a spaghetti bridge model, where both structures were subjected to increasing loads until collapse. A traditional (AE) signal analysis is also performed to reference the study of the other methods. Results indicate that the proposed methods yield a reliable indication of failure in the studied structures.

Music has the ability to evoke a wide variety of emotions in human listeners. Research has shown that treatment for depression and mental health disorders is significantly more effective when it is complemented by music therapy. However, because each human experiences music-induced emotions differently, there is no systematic way to accurately predict how people will respond to different types of music at an individual level. In this experiment, a model is created to predict humans’ emotional responses to music from both their electroencephalographic data (EEG) and the acoustic features of the music. By using recursive feature elimination (RFE) to extract the most relevant and performing features from the EEG and music, a regression model is fit and accurately correlates the patient’s actual music-induced emotional responses and model’s predicted responses. By reaching a mean correlation of r = 0.788, this model is significantly more accurate than previous works attempting to predict music-induced emotions (e.g. a 370% increase in accuracy as compared to Daly et al. (2015)). The results of this regression fit suggest that accurately predicting how people respond to music from brain activity is possible. Furthermore, by testing this model on specific features extracted from any musical clip, music that is most likely to evoke a happier and pleasant emotional state in an individual can be determined. This may allow music therapy practitioners, as well as music-listeners more broadly, to select music that will improve mood and mental health.

Concerning fan systems with an air pipe connecting air intake and a closed outlet, aerodynamic noise cannot be directly transmitted from the fan inlet and outlet to the outside. At this moment, the volute vibrational radiation noise induced casing surface vibration is the major noise component. The main factors affecting the fan vibrational noise are analyzed through theoretical derivation, then a vibrational noise optimization control method for the volute casing is proposed that considered the influence of vibro-acoustic coupling, taking the panel thickness of the volute (front-panel thickness [FT], side-panel thickness [ST], and back-panel thickness [BT]) as design variables, and the acoustical power of the volute surface and the total mass of the volute as the optimal target function. The optimization method is mainly divided into three main parts: the first was based on the simulation of unsteady flow of the fan to obtain the vibrational noise source; the second, using the design of experimental (DOE) method and the proposed numerical simulation of fluid-structure-acoustic coupling method to obtain the designing space, then the radical-based function (RBF) method is used to construct the approximate surrogate model instead of the simulation model previously mentioned, which was used to provide the basic mathematical model for the optimization of the next part; the third part, implementing the low vibrational noise optimization for the fan volute, applied the single-target (taking volute radiated acoustical power as the target function) and the multi-target (taking the volute radiated acoustical power and volute total mass as the target function) methods. In addition, the fan aerodynamic performance, volute casing surface fluctuations, and vibration response were validated by experiments, showing good agreement. It is of utmost importance that the dynamic pressure measurements and vibrational tests on the volute casing verify the accuracy of the numerical calculation. The optimization results showed that the vibrational noise optimization method proposed in this study can effectively reduce the vibration noise of the fan, obtaining a maximum value of noise reduction of 7.3 dB. The optimization identified in this paper provides a significant reference for the design of a low-vibrational-noise volute.

This paper presents a novel approach for indoor acoustic source localization using microphone arrays and based on a Convolutional Neural Network (CNN). The proposed solution is, to the best of our knowledge, the first published work in which the CNN is designed to directly estimate the three dimensional position of an acoustic source, using the raw audio signal as the input information avoiding the use of hand crafted audio features. Given the limited amount of available localization data, we propose in this paper a training strategy based on two steps. We first train our network using semi-synthetic data, generated from close talk speech recordings, and where we simulate the time delays and distortion suffered in the signal that propagates from the source to the array of microphones. We then fine tune this network using a small amount of real data. Our experimental results show that this strategy is able to produce networks that significantly improve existing localization methods based on SRP-PHAT strategies. In addition, our experiments show that our CNN method exhibits better resistance against varying gender of the speaker and different window sizes compared with the other methods.

Acoustic emissions (AE) are produced by elastic waves generated by damage in solid materials. AE sensors have been widely used in several fields as a promising tool to analyze damage mechanisms such as cracking, dislocation movement, etc. However, accurately determining the location of damage in solids in a non-destructive manner is still challenging. In this paper, we propose a crack wave arrival time determination algorithm that can identify crack waves with low SNR(signal-to-noise ratios) generated in rocks. The basic idea comes from that the variances of the crack wave and noise have different characteristics depending on the size of the moving window. The results can be used to accurately determine the crack source location. The source location is determined by observing where the variance in the crack wave velocities of the true and imaginary crack location reach a minimum. By performing a pencil lead break test using rock samples, it was confirmed that the proposed method could successfully find wave arrival time and crack localization. The results using the proposed algorithm to detect crack wave source localization suggest use for evaluating and real-time monitoring of damage in tunnels or other underground facilities.

Pipelines extend thousands of kilometers to transport and distribute oil and gas. Given the challenges often faced with corrosion, fatigue, and other issues on steel pipes, the demand for glass fiber reinforced plastics (GFRP) pipes is increasing in the oil and gas gathering and transmission systems. However, the medium transported through these pipelines contains multiple acid gases such as CO2 and H2S, as well as ions including Cl-、Ca2+、Mg2+、SO42-、CO32- and HCO3-. These substances can cause a series of problems, such as aging, debonding, delamination, and fracture. In this study, a series of aging damage experiments were conducted on V-shaped GFRP pipes with depths of 2mm and 5mm. The aging and failure of GFRP were studied under the combined effects of external force and acidic solution using acoustic emission (AE) techniques. It was found that the acidic aging solution promoted matrix damage, fiber/matrix desorption, and delamination damage in GFRP pipes over a short period. However, the overall aging effect was relatively weak. Based on the experimental data, the SSA-LSSVM algorithm was proposed and applied to the damage pattern recognition of GFRP. An average recognition rate of up to 90% was achieved, indicating that this method is highly suitable for analyzing AE signals related to GFRP damage.

Measuring sound pressure is a complex and tedious task in industrial environments. Classical methods can be costly, inaccurate, and potentially dangerous for workers. Integrating robotics and computer vision into acoustic measurement processes offers an innovative solution to these problems. This paper uses a Doosan Robotic Vision System to investigate an innovative automatic acoustic sound pressure measurement solution. The Doosan robot, equipped with a scanning camera and microphone, captures acoustic data and produces a map of the machine’s acoustic radiation using computer vision algorithms. The measurement technique is accurate, efficient, and safe for workers. It can also be used for continuous monitoring of the industrial acoustic environment. The developed measurement method offers a promising way to automate acoustic measurement, which can be performed faster and with better accuracy to help industries improve their product sound quality and reduce noise levels. The method was compared to analytical predictions. A 3D acoustic mapping was conducted to visualize the spatial distribution of sound sources within the environment. The experimental results show a good correlation with the theory.

Various wood fibres, including pine and flax, are used in wood–plastic composites (WPCs). This paper studies the effect of the lignin content on the morphological and thermal degradation and damage due to the ultraviolet (UV) aging of polypropylene/flax (PP-flax) and polypropylene/pine (PP-pine) fibres composites. Flax and pine fibres exhibited distinct densities of 1.51 and 1.47 g/cm³, respectively, potentially influenced by growth factors and varying compositions of light substances, such as hemicellulose, lignin, and impurities. The thermal decomposition mass loss increased proportionally with the percentage of lignin in the fibre. From 238°C to 390°C, the pine fibre exhibited a 72% mass loss compared to flax fibre, which showed a 54% mass loss, owing to the higher lignin content in pine fibres. Based on differential scanning calorimetry (DSC), the fibre composition affected the material melting temperature. Moreover, DSC curves revealed a higher degree of crystallinity in the case of the PP-flax biocomposite (12%) compared to pure polypropylene (9%) and PP-pine (6%). This result can be attributed to the high content of crystalline components in flax fibres, such as cellulose. Acoustic emissions analysis confirmed that the high lignin content delays degradation and mitigates the appearance of microcracks on the surface of the PP-pine biocomposite. Overall, the study provides valuable data for understanding the UV degradation phenomenon in biocomposites and highlights the influence of fibre composition on material performance.

This article introduces a new physically based Lyapunov function difinition, which can be used as acoustic energy for finite amplitude pressure oscillations in reacting systems especially in combustion chambers. Reacting flow is seen as an open, non-equilibrium (parameters are distributed unevenly locally) thermodynamic system. This Lyapunov function is defined as the maximum mechanical work, which could be extracted by a heat engine from studied system, if this system would be disconnected from inlet and outlet and from any other surrounding environment, and the engine could transfer to the surrounding environment only mechanical work.

Practically important properties of real liquids, including seawater, are their nonlinear properties, which include a nonlinear acoustic parameter, as well as cavitation strength – a rupture of the continuity of a liquid at high intensities in an acoustic wave. The manifestation of nonlinear effects is greatly facilitated by the presence of various nuclei in the liquid – gas bubbles, foreign particles, and other inclusions of various origins. For practical applications, it is important to study the properties of real liquids with inclusions in them. Due to the difficulties of measuring cavitation strength by acoustic methods, other methods are being sought. It is proposed to use an optoacoustic method associated with the use of laser radiation that causes optical breakdown - optical cavitation, that accompanied by a strong sound generation effect. The connection between optical breakdown thresholds and acoustic cavitation thresholds has been established, which can later be used to identify cavitation thresholds at high static pressures (at great depths in the sea), where the use of acoustic emitters is extremely difficult. The paper studies the bubble size distribution function in seawater, combined with studies of the acoustic nonlinearity parameter and cavitation strength at various depths. The interrelation of these characteristics for seawater is shown.

Spray technology is widely used in various industries, including medicine, food production, mechanical engineering, and nanopowder manufacturing. Achieving high dispersion and a narrow particle size distribution is crucial for many applications. Ultrasonic spraying is commonly used to achieve this. On other hand, hydraulic nozzles provide high atomization performance. Combining these two technologies promises to offer significant benefits, but the complex processes that occur simultaneously in such a device require careful study. This work proposes a fundamental design for an acoustic-hydraulic nozzle and investigates the physical processes when a liquid is sprayed using this nozzle, both theoretically and experimentally. The study identifies the critical modes of spraying and confirms that the simultaneous use of ultrasound and hydraulic pressure can produce a fine spray (droplet size less than 50 μm) with high productivity (5-10 ml/s). This approach has significant potential for modern industries and technologies.

The unreliable prediction of the low frequency components from inverted acoustic impedance causes uncertainty in quantitative seismic interpretation. To address this issue, we first calculate various seismic and geological attributes that contain low frequency information, such as relative geological age, interval velocity, and integrated instantaneous amplitude. Then, we develop a method to predict the low frequency content of seismic data using these attributes, their high frequency components, and recurrent neural networks. Next, we test how to predict the low frequency components using stacking velocity obtained from velocity analysis. Using all the attributes and seismic data, we propose a supervised deep learning method to predict the low frequency components of the inverted acoustic impedance. The results obtained in both synthetic and real data cases show that the proposed method can improve the prediction accuracy of the low frequency components of the inverted acoustic impedance, with the best improvement in a real data example of 57.7% compared with the impedance predicted using well log interpolation.

In this paper, the feasibility of automated and accurate in vivo measurements of vascular parameters continuously and non-invasively using ultrasound sensor is presented. Vascular parameters such as pulse wave velocity (PWV), blood pressure (BP), arterial compliance (AC) and stiffness index (SI) are affluent indicators of cardiovascular disorders and needs to be monitored non-invasively and continuously during surgeries and follow-up procedures. Cuff based or invasive catheter techniques are considered as gold standard to measure BP and are fed manually to compute AC and SI which employ imaging algorithms. In this context, a Continuous and Non-Invasive Vascular Stiffness and Arterial Compliance Screener (CaNVAS) is developed to measure said parameters continuously and non-invasively using ultrasound sensor. Acoustic waves of 5 MHz (2.2 – 10 MHz) are driven through target arterial walls, reflected echoes captured, pre-processed and frequency shift is used to calculate PWV. It is observed that PWV measured using CaNVAS varies exponentially with BP values obtained from sphygmomanometer (BPMR-120) and this relationship is used to compute instantaneous values of BP. The proposed device is validated by performing measurements on 250 subjects in pre and post exercise conditions and found to have 95% accuracy and an average of 12.5% coefficient of variation.

This study aimed to establish and verify the validity of an acoustic simulation method during sustained phonation of the Japanese vowels /i/ and /u/. The study participants were six healthy adults. First, vocal tract models were constructed based on computed tomography (CT) data, such as the range from the frontal sinus to the glottis, during sustained phonation of /i/ and /u/. Next, cylindrical shapes virtually extended by 12 cm were added to the vocal tract models to imitate the trachea between the tracheal bifurcation and lower part of the glottis. The Kirchhoff–Helmholtz integral equation was formulated as the wave equation for sound propagation, and the boundary element method was used for discretization. As a result, the relative discrimination thresholds of the vowel formant frequencies for /i/ and /u/ against actual voice were 1.1%–10.2% and 0.4%–9.3% for the first formant and 3.9%–7.5% and 5.0%–12.5% for second formant, respectively. In the vocal tract model with nasal coupling, a pole–zero pair was observed at around 500 Hz, and for both /i/ and /u/, a pole–zero pair was observed at around 1000 Hz regardless of the presence or absence of nasal coupling. These findings demonstrated that /i/ and /u/ could be simulated with high validity in a vocal tract model constructed from CT data obtained during sustained phonation using the boundary element method.

We discuss two methods to detect the presence and location of a person in a small-scale room and compare the performances. The first method is Direct Intersection, which determines a coordinate point based on the intersection of spheroids defined by observed distances of high-intensity reverberations. The second method, Sonogram analysis, overlays all channel’s room impulse responses to generate an intensity map for the observed environment. We demonstrate that the former method has lower computation complexity and higher accuracy for small numbers of channels, while the latter performs more robustly.

The contactless coalescence of a droplet is of paramount importance for physical and industrial applications. This paper describes a coalescence method in mid-air via acoustic levitation using an ultrasonic phased array system. Acoustic levitation using ultrasonic phased arrays provides promising lab-on-a-drop applications, such as transportation, coalescence, mixing, separation, evaporation, and extraction in a continuous operation. The mechanism of droplet coalescence in mid-air may be better understood by experimentally and numerically exploring the droplet dynamics immediately before the coalescence. In this study, water droplets were experimentally levitated, transported, and coalesced by controlling acoustic fields. We observed that the edge of droplets deformed and attracted each other immediately before the coalescence. Through image processing, the radii of curvature of the droplets were quantified and the pressure difference between the inside and outside the droplet was simulated to obtain the pressure and velocity information on the droplet surface. The results revealed that the sound pressure acting on the droplet clearly decreased before the impact of the droplets. This pressure on the droplets was quantitatively analyzed from the experimental data. Our experimental and numerical results provide deeper physical insights into contactless droplet manipulation for futuristic lab-on-a-drop applications.

The use of high strength to weight ratio laminated composites is emerging in marine industry and applications as a very efficient solution for improving productivity. Nevertheless, delamination between the layers is a limiting factor for the wider application of laminated composites, as it reduces the stiffness and strengths of the structure. Interleaving nanofibrous mats between layers of composite laminates has been proved to be an effective method for improving composites delamination resistance. This paper aims to characterize the effect of interleaved nanofiber on mode I interlaminar properties and failure mechanisms when subjected to static and fatigue loadings. For this purpose, virgin and nanomodified woven laminates were subjected to Double Cantilever Beam (DCB) specimens. Static and fatigue tests were performed and the tests were monitored by acoustic emission technique. The mechanical results showed a 130% increase of delamination toughness for nanomodified specimens in the static loadings and more crack growth resistance in the fatigue loading. The AE results revealed that different type of failure mechanisms was the cause of these improvements for the modified specimens compared with the virgin ones.

Recently Kawashima has reported that, when wetted with alkanes, several forms of graphite and single-layer graphene exhibit superconductor-like properties above room temperature under ambient pressure [AIP Adv. 2013, 3, 052132; arXiv:1612.05294; arXiv:1801.09376]. Under the assumption that these seemingly unlikely properties arise from the presence of paired electrons brought about by the alkane-wetting, we explored their implications to arrive at a probable mechanism for strong electron-pairing driven by Fermi surface nesting and acoustic phonon. This mechanism explains why alkane-wetting is essential for the graphene systems to become “superconductor-like” above room temperature and why the “T_c” of alkane-wetted pitch-based graphite fibers increases almost linearly from ~363 to ~504 K with increasing the molecular weight of alkane from heptane to hexadecane. It also provides a number of experimentally-verifiable predictions, the confirmation of which will provide a strong support for the superconductivity driven by Fermi surface nesting and acoustic phonon.

Underwater wireless sensor networks (UWSN) have recently been proposed as a way to monitor and explore the water depths' environments. Efficiently delivering the data is still a challenging problem in these networks because of the weaknesses in the acoustic transmission. To tackle such a problem, we propose a novel algorithm provides controlling mechanisms for critical long-term data forwarding underwater sensor networks, called Hop by Hop Power-Efficient Routing Protocol (Hⁿ-PERP). The proposed Hⁿ-PERP is a centralized full-control model that enhances the network's throughput and energy efficiency by a set of solutions depend on power monitoring in UWSN nodes. In particular, the model provides a guaranteed mechanism for scheduling and processing data transmission based on number of nodes, hops between the nodes, energy level and congestion within each node to minimize energy levels or power consumption by avoiding disconnected probability for any node, which in turn maximizing the network lifetime. Simulation results show that our proposed model is consistent with energy level and congestion, and is more accurate for enabling routing and data transmission. Therefore, the data packet delivery ratio and overall throughput also achieves robust scenarios of very sparse or/and weak networks, to keep on Performance stability in UWSN via adjusting hop-by-hop delay and energy consumption during packages delivery.

One of the major concerns in structural health management (SHM) is the early detection of a growing crack. Using this, future damage due to crack propagation can be mitigated or eliminated by implementing proper repair and maintenance. Acoustic Emission (AE) is a non-destructive testing (NDT) method with potential applications for locating and monitoring fatigue cracks. The research presented in this paper focuses on SHM using AE. A novel AE signal analysis approach was proposed in order to detect crack initiation and assess small crack lengths. Experimental investigation indicated that initiation of a crack could be identified through the statistical analysis of the resulting features of the AE signals. A probabilistic AE-based model for small fatigue crack sizing was developed and the uncertainties of the model were estimated. In addition, a probabilistic model validation approach was implemented to confirm accurate estimation of the results. The outcome of this research can be used to evaluate the integrity of structures under fatigue loading. The proposed approach can also be applied as an approach to manage health and assess prognosis of structures.

There are few results about the internal damping ratio of normal and high strength concretes. Hence, this paper presents the expansion of the investigation about internal damping ratio under undamaged and damaged conditions, for usual concretes (NSC) and high strength concretes (HSC). In this way, the study cover a strength range of 42 to 83 MPa. Cyclic load was employed by a servo-controlled hydraulic testing machine and for each cyclic step the dynamic elastic modulus (Ed) and internal damping ratio (ξ) were determinate by acoustic tests. Normal strength concretes (fc = 42MPa) presented undamaged internal damping ratio ξ = 0.5% and achieved the maximum value of ξ = 2.5 for a damage index equal to 0.8. High strength concretes mixtures (fc = 83MPa) presented an undamaged internal damping of ξ=0.29% and maximum internal damping equal to ξ=0.93% (under damage index of 0.32). Porosity and the transition zones were the responsible to the initial internal damping values and how the material behavior under each cyclic load. The progressive damage generates the increase of coulomb damping. There are few studies allowing the quantification and comprehension of internal damping ratio under damage cyclic loading and this approach will lead to improve the understanding of NSC and HSC under dynamical excitation subject to damage evolution, mainly in impact situations.

An analysis of the processes of plastic deformation and acoustic relaxation in a high-entropy alloy Al0.5CoCrCuFeNi was carried out. The following have been established: dominant dislocation defects; types of barriers that prevent the movement of dislocations; mechanisms of thermally activated movement of various elements of dislocation lines through barriers at room and low temperatures. Based on modern dislocation theory, quantitative estimates have been obtained for the most important characteristics of dislocations and their interaction with barriers.

A fern, Polypodium aureum, possesses a specialized spore-releasing mechanism like a catapult induced by quick expansion of vaporized bubbles. This study introduces lipid-coated perfluorocarbon droplets to enable repeatable vaporization-condensation cycles, inspired by the repeatable vaporization of Polypodium aureum. Lipid-perfluorocarbon droplets have been considered not to exhibit repeatable oscillations due to bubble collapse by low surface tension of lipid layers. However, a single lipid-dodecafluoropentane droplet with a diameter of 9.17 µm shows expansion-contraction oscillations over 4,000 cycles by changing lipid composition and applying low power of 1.7 MHz ultrasound to induce partial vaporization of droplets. The optimal combinations of shell composition, droplet fabrication, and acoustic conditions can minimize damage on shell structure and quick recovery of damaged shell layers. The highly-expanding oscillatory microbubbles provide a new direction for fuel-free micro or nanobots as well as biomedical applications of contrast agents and drug delivery.

The intensification of conflicts associated with the use of water in the transition region of the Cerrado and Amazon biomes caused by population and economic growth, combined with the interest in generating energy from hydroelectric plants, raise the need to quantify the surface water availability of rivers contributing with different drainage areas. The present study estimated and compared loco measurements of liquid flow (QL) and depth of rivers in the Teles Pires river basin by reference methods (MLN-7 hydrometric windlass and metal rod/winch) and by Acoustic Current Profiler by Doppler Effect (ADCP RiverRay), in addition, evaluated the total measurement time underestimation uncertainty by ADCP. Field measurements were carried out at monthly intervals between March 2020 and October 2021, seeking to represent the water seasonality and depth and QL variations in the cross-sections of the Caiabi 1 and 2, Celeste, Preto and Renato rivers. The evaluated rivers had a net flow between 3.48 and 60.78 m3 s-1 by the windlass and between 2.66 and 54.30 m3 s-1 by the ADCP, while the depths obtained were from 0.17 to 6.34 m by the rod/winch and from 0.65 to 6.20 m by the ADCP. The methods resulted in similar measurements of net flow and depth in each of the cross-sections, and the statistical performance of the linear regression model was satisfactory with a Willmott concordance index of 0.9977 and 0.9819 for estimates of QL and of the depth of the cross-sections, respectively. The ADCP accurately measured net discharge and depth in shallow (up to 6.5 m) cross-sections of Teles Pires River in relative to the reference method. Determining the total measurement time and pairs of transects to obtain accurate QL by ADCP depends on the hydraulic characteristics of the watercourses.

In order to study the acoustic emission characteristics of sandstone under the action of the high temperature-water cooling cycle, the RMT-150B electro-hydraulic servo rock test system and the DS-5 acoustic emission detection and analysis system were used to conduct a single analysis of the sandstone after the high temperature-water cooling cycle. Experimental study on acoustic emission characteristics under axial compression, analyzing the deformation, strength and acoustic emission characteristics of sandstone under different temperatures and cycles. The results of the study show that the high temperature-water cooling action causes changes in the physical properties of the sandstone. The expansion rate of the rock sample decreases first and then increases when the temperature rises, and the strength first increases and then decreases. The number of cycles has little effect on the physical properties of the rock sample; sandstone acoustic emission ringing count increases with the increase of temperature and cycle times, acoustic emission activities become more frequent with the loading process; with the increase of cycle times and temperature, acoustic emission ringing counts and accumulative acoustic emission energy appear earlier The rock sample enters the elastic deformation stage ahead of schedule, the yielding period increases, and the rock sample presents a trend of transition from brittle failure to ductile failure; the ringing count and cumulative energy increase with the increase in temperature and cycle times, and the high-energy ringing count and cumulative energy increase. The simultaneous sharp increase of the rock sample is the harbinger of the failure and instability of the rock sample.

Fiber distributed optical fiber acoustic sensor (DAS) is generally used in distributed long-distance acoustic/vibration measurement. We found that DAS with excellent performance of low self-noise and anti-fading in combination with the plastic structure in daily life as an acoustic transducer can achieve high-sensitivity acoustic measurement at a single point rather than designing a state-of-the-art acoustic transducer or using special enhanced scattering fiber. The simple acoustic transducer we proposed for DAS can reach the sensitivity level of -106.5dB re. 1rad/μPa at a sensing range of 5.1 km, which can meet many demands on the industrial site.

Shock waves, as used in medicine, can induce cell permeabilization, genetically transforming filamentous fungi; however, little is known on the interaction of shock waves with the cell wall. Because of this, the selection of parameters has been empirical. We studied the influence of shock waves on the germination of Aspergillus niger, to understand their effect on the modulation of four genes related to the growth of conidia. Parameters were varied in the range reported in protocols for genetic transformation. Vials containing conidia in suspension were exposed to either 50, 100 or 200 single-pulse or tandem shock waves, with different peak pressures (approximately 42, 66 and 83 MPa). In the tandem mode, three delays were tested. To equalize the total energy, the number of tandem “events” was halved compared to the number of single-pulse shock waves. Our results demonstrate that shock waves do not generate severe cellular effects on the viability and germination of A. niger conidia. Nevertheless, increase in the aggressiveness of the treatment induced a modification in the four genes tested. Scanning electron microscopy revealed significant changes to the cell wall of the conidia. Under optimized conditions, shock waves could be used for several biotechnological applications, surpassing conventional techniques.