Carbon Fiber Reinforced Polymers (CFRP) are extensively utilized in high-performance engineering, yet localized structural discontinuities can severely compromise their integrity. This paper aims to achieve high-sensitivity characterization of such anomalies using a proposed acoustic shearography technique based on continuous acoustic excitation. A comprehensive finite element model (FEM) was developed to clarify the mechanical-energy coupling between the acoustic fields and localized surface strain field modulations. By exploiting ultrasonic energy coupling, the localized features of discontinuities were identified through full-field, non-contact optical measurement of localized phase distortions. Key parameters, including shearing amount, excitation frequency, driving voltage, and geometric characteristics of blind flat-bottom holes (BFBH), were systematically investigated. The results demonstrate a high correlation between FEM simulations and experimental observations quantitatively elucidating how defect diameter and hole depth modulate surface strain distributions. The proposed hybrid acoustic optical approach achieves near-instantaneous full field imaging within a millisecond timeframe typically under 200 ms. Additionally, the methodology leverages localized acoustic resonance to significantly boost the signal-to-noise ratio (SNR) resulting in highly quantified phase map contrast.

High brittleness and rapid post-peak capacity loss are often observed in cemented gangue backfill (CGB) under uniaxial compression. The risk of sudden instability in deep mining panels is therefore increased. Chopped basalt fibers (0-0.60 wt%) were incorporated to improve early-age load capacity and ductility, and curing ages of 3–60 d were investigated. Uniaxial compression tests were performed. Crack evolution was interpreted mainly through Acoustic emission (AE) characteristics and surface failure observations, with digital image correlation DIC serving as an auxiliary qualitative tool. Scanning electron microscopy and discrete element simulations were used to clarify multiscale toughening mechanisms. An optimal dosage was identified at 0.3 wt%. At 28 d, uniaxial compressive strength (UCS) and peak strain were increased by 67.2% and 37.0%, reaching 5.71 MPa and 3.7%. A rapid strength-gain window occurred from 3 d to 7 d. For the 0.3 wt% mixture, UCS rose from 0.74 MPa to 3.23 MPa (436.49%), supporting mining initiation at approximately 7 d after backfilling. At 7 d, tensile cracks dominated the reference mixture (82.6%). After fiber addition, crack deflection and branching were promoted and shear sliding was activated. At 0.3 wt%, the shear-associated crack proportion increased markedly, while crack deflection and branching were promoted. Failure mode evolved from concentrated longitudinal splitting toward a more distributed oblique mixed-mode crack network, and post-peak softening was mitigated. A dense C-S-H-rich hydration layer was formed in situ on fiber surfaces, creating a fiber-hydration product-matrix interface. Strength and damage tolerance were jointly improved through bridging-based load transfer, stress redistribution, and crack-tip blunting. The results clarify the early-age strengthening and quasi-brittle toughening mechanism of basalt-fiber-reinforced cemented gangue backfill and provide a basis for mixture optimization and early-age support design.

Abstract For axially symmetric accretion maintained in hydrostatic equilibrium along the vertical direction, we investigate how the characteristic features of the embedded acoustic geometry depend on the background Kerr metric, and how such dependence is governed by two different expressions for the geometrical configurations of the matter flow. We first obtain the location of the sonic points and stationary shock between the sonic points. We then perturb the flow to obtain the corresponding metric elements of the acoustic space-time. We compute the value of the acoustic surface gravity as a function of the spin angular momentum of the rotating black hole for the different flow thicknesses considered in the present work.

The aeroacoustic impact of ground proximity on an eVTOL propeller in hover and edgewise flight is examined using a multi-fidelity framework. Delayed-Detached Eddy Simulations (DDES) in OpenFOAM, coupled with PSU-WOPWOP, for high-fidelity acoustic predictions, and CDI-CHARM, a free-vortex panel-method code, as a lower fidelity approach. Extensive validation of the numerical simulations against experiments was performed. Performance metrics and flow-field analyses were examined prior to conducting the acoustic analysis. In-ground-effect (IGE) conditions, here defined as rotor operation within a few radii of a rigid ground plane, modify wake dynamics and alter tonal and overall sound levels, producing around ∼ 5 dB SPL increases beneath the rotor. CHARM reproduces the main tonal trends observed in DDES cannot predict broadband content. We also evaluate approaches for treating ground reflections, including the Method of Images (MOI), and introduce a permeable “upside-down T” acoustic surface that captures reflected waves without requiring MOI. These findings clarify rotor–ground acoustics and offer practical guidance for permeable acoustic surface selection in high-fidelity simulations.

Sound pressure recordings at different positions at the head such as ear canal, nasal cavity, or on the skin are effective tools to verify, fit, or follow up the output of bone conduction devices (BCDs) intra- and post-operatively. Here, we investigated the possibility of using a surface microphone (SM) as a non-invasive alternative to laser Doppler vibrometry (LDV) measuring cochlear promontory (CP) vibrations in human heads. A percutaneous BCD (Ponto system) was implanted at the standard position in five human (four males/one female) cadaver heads (ten ears). CP vibration was measured using LDV in response to the BCD stimulation. Simultaneously, the sound pressure level (SPL) emitted by the skin was measured by the SM attached to the forehead of the specimens. A linear regression model estimated the vibration amplitudes based on the measured SPL. A frequency-independent linear regression between recorded SM SPL and CP velocity showed a significant correlation (slope = 1.012; r2 = 0.535, p < 0.001). An enforced fixed slope (constant = 166.7 dB) of one resulted in a mean absolute error of MAE = 7.7 ± 2.7 dB across frequencies. Although the initial linear model with a fixed slope of one showed frequency-dependent deviations, applying a frequency-specific correction significantly improved the prediction accuracy (r2 = 0.557, MAE = 6.5 ± 1.5 dB). Microphone-based recording of acoustic surface emissions offers a non-invasive alternative to LDV to assess BCD output.

ABSTRACT Bubbles are versatile tools in applications spanning biomedicine, industry, and engineering. Their unique physical properties, such as surface tension and elasticity, as well as their strong resonance behavior, enable innovative uses in medical imaging, microfluidics, soft actuators, and microrobotics. Through acoustic actuation, bubbles exhibit high‐efficiency acoustic‐to‐mechanical transduction, selective oscillation, and non‐contact liquid manipulation. However, for the existing bubble‐based systems, the programmability, stability, scalability, and multifunctionality remain the primary challenges. Here, we present acoustic bubble surfaces using bioinspired liquid‐repellent microstructures, which enable programmable on‐demand trapping, pumping, mixing, and high degrees of flow control. Using two‐photon lithography‐based 3D printing, we fabricate springtail‐inspired bubble actuators in different sizes, ranging from 200 µm to 1 mm in diameter. We demonstrate the multifunctionality feature of our proposed approach, utilizing a rectangular arrangement of bubble surfaces that enables the trapping, pumping, and mixing functionalities of the acoustic actuators in an all‐in‐one device. For programmability, we show actuator arrays arranged in the shape of distinct letters. Furthermore, to accommodate the multidimensionality of our approach, a 3D structure is shown on the five faces of a cube. As a real‐world application, we also tested springtail‐inspired bubble actuators’ actuation and stability in whole blood from an animal.

Accurate acoustic simulations of enclosed spaces require precise boundary conditions, typically expressed through surface impedances for wave-based methods. Conventional measurement techniques rely on simplifying assumptions about the sound field and mounting conditions, limiting their validity for real-world scenarios. To overcome these limitations, this study introduces a Bayesian framework for the in situ estimation of frequency-dependent surface impedances from sparse interior sound pressure measurements. The approach employs simulation-based inference, which leverages the expressiveness of neural network architectures to directly map simulated data to posterior distributions of model parameters, bypassing conventional sampling-based Bayesian approaches and offering advantages for high-dimensional inference problems. Impedance behavior is modeled using a damped oscillator model extended with a fractional calculus term. The framework is verified on a finite element model of a cuboid room with a volume of 1.95 m3 and further tested with impedance tube measurements used as reference, achieving robust and accurate estimation of all six individual impedances from 63 to 500 Hz. Application to a numerical car cabin model further demonstrates reliable uncertainty quantification and high predictive accuracy for complex-shaped geometries. Posterior predictive checks and coverage diagnostics confirm well-calibrated inference, highlighting the method's potential for generalizable and physically consistent characterization of acoustic boundary conditions in real-world interior environments.

Abstract This study aimed to investigate the role of force stimulation in promoting peripheral nerve regeneration and to elucidate the underlying mechanisms by which it enhances nerve repair. We developed two distinct force stimulation devices for in vivo and in vitro experiments. The in vivo device applied tensile stress to the sciatic nerve of mice, whereas the in vitro device used acoustic surface wave (SAW) actuators to apply fluid shear stress to dorsal root ganglion (DRG) neurons. We evaluated the effects of these mechanical forces on axonal regeneration, mitochondrial biogenesis, and adenosine triphosphate (ATP) production. In vivo experiments demonstrated that controlled mechanical stretching significantly improved axonal regeneration and functional recovery compared to autologous nerve grafting. Mechanical stretching facilitated myelin reformation and angiogenesis, providing a favorable environment for axonal growth. In vitro studies revealed that fluid shear stress increased mitochondrial density and ATP production in DRG neurons by promoting mitochondrial biogenesis through the activation of peroxisome proliferator‐activated receptor γ coactivator 1α (PGC‐1α). In conclusion, tensile stress and fluid shear stress positively impact peripheral nerve repair and regeneration. Our findings suggest that mechanical forces can enhance the body's natural nerve repair mechanisms by restoring cellular energy and promoting axonal regeneration. These results have significant implications for the development of novel therapeutic strategies for peripheral nerve injuries and diseases.

As electric vertical take-off and landing (eVTOL) concepts and urban air mobility gain prominence, the mitigation of propeller noise has become essential. This study presents a comprehensive assessment of acoustic prediction methodologies, focusing on the application of both Formulation-1A and the more recent Formulation-1C of the Ffowcs Williams-Hawkings (FWH) equation. The work demonstrates the use of steady-state Reynolds-averaged Navier-Stokes (RANS) simulations with a single rotating frame (SRF) approach for efficient acoustic analysis, enabling the transformation of steady flow solutions into time-varying acoustic surface data. The methodology is implemented as a new class within the open-source libAcoustics library for OpenFOAM, leveraging its parallelization capabilities. Validation with experimental data and comparison against numerical results were performed for a range of propeller configurations. Comparative analysis with direct noise computation (DNC) highlights the improved accuracy of Formulation-1C, especially in scenarios with ambient flow, and demonstrates the limitations of Formulation-1A in such conditions. The results confirm the robustness of the proposed framework for propeller noise prediction across a range of operating regimes.

Active acoustic sensing with a smartphone’s built-in speaker -microphone pair enables around-device interaction, but recognizing hand poses above the display remains difficult with conventional top-speaker and bottom-microphone placement. We leverage screen-integrated speakers (Acoustic Surface) that vibrate the display, extending sensing coverage above the screen and integrating near-surface hand-pose recognition with touch. On commodity smartphones that integrate this technology, we compare a screen-bottom configuration with a typical top-bottom layout. Across datasets of single-hand and double-hand poses, our models recognize 12 single-hand classes at 94.5%, 10 double-hand classes at 90.6%, and 20 combined classes at 90.4%, surpassing the conventional layout. We also conducted a formative within-set elicitation study where participants assessed poses and proposed pose -command mappings. We synthesize results and feedback into four design guidelines for near-surface hand-pose input. The findings expand input above the display without external hardware and offer guidance for around-device interaction on commodity devices.

Long-Term Evaluation of Acoustic Decay, Drainage, and Surface Resistance in Engineered Asphalt Pavements through Integrated Field and Laboratory Analysis

Abstract This study investigates the Helmholtz resonator, focusing on its inherent limitations of narrow sound absorption bandwidth and suboptimal performance in confined spaces. To mitigate these issues, we propose a conical tube Helmholtz resonator. First, an acoustic impedance model is established based on the unique sound absorption characteristics of the conical tube Helmholtz resonator. Subsequently, a neural network model is developed for the inverse optimization of structural parameters to achieve a target sound absorption coefficient. The model is trained using a dataset generated from both forward prediction and inverse optimization networks within a deep learning framework. The predictive accuracy of the neural network is validated through finite element simulations. Based on weak primitive coupling principles, a superstructure sound absorber is designed. It comprises four conical tube Helmholtz resonators arranged in a 2 × 2 configuration on the surface of the acoustic superstructure. Finally, a high-performance sound absorber is engineered using the trained neural network model. This absorber achieves a sound absorption coefficient exceeding 0.9 in the 175–225 Hz frequency range, with a compact structural thickness of only 50 mm.

Skyrmions—topologically protected nanoscale spin textures with vortex-like configurations—hold transformative potential for ultra-dense data storage, spintronics and quantum computing. However, their practical utility is challenged by dynamic instability, complex interaction, and the lack of deterministic control. Here, we introduce a skyrmion molecule lattice, a novel architecture where pairs of skyrmions with opposite polarizability are symmetry-locked into stable molecule configurations. These molecules emerge as propagating eigenstates of the system, enabling robust transport. Using a boundary engineering technique, we achieve deterministic control over skyrmion creation, deformation, annihilation, and polarizability inversion. This is experimentally demonstrated in a graphene-inspired acoustic surface wave metamaterial by harnessing topological acoustic spin structures. Our work, leveraging symmetry principles, establishes a universal framework for stabilizing, transporting and manipulating the skyrmion quasiparticles.

The in situ measurement of acoustic surfaces presents a significant challenge in room acoustics, as it is often impractical to conduct laboratory measurements of already installed materials. In a former study, the in situ analysis of porous samples that react locally when supported by a solid wall demonstrated a good degree of accuracy. Nevertheless, when a porous layer is supported by a large air cavity (depth &gt;100 mm), a situation commonly seen in suspended ceiling designs, the air cavity exhibits a non-locally reacting behavior; thus, the local reaction cannot be reliably assumed. This study introduces a method to characterize such a non-locally responding system through in situ PU probe measurements, utilizing an inverse technique to fit the parameters of the impedance model of a porous layer that is backed by an infinite air layer, based on the measured reflection coefficient. The precision of the approach was confirmed through 2D numerical simulations, indicating that the method produced reliable results for air cavities of 200 mm or deeper. The method was then experimentally validated on systems comprising several porous layers supported by air cavities of varying depths. Good agreement was obtained between the parameters measured experimentally using the proposed technique and the references, even in cases where the air cavity was less than 200 mm deep. Additionally, the proposed method demonstrated more precise characterization results compared to those achieved by fitting the parameters of an impedance model based on a standard multilayer model.

Abstract Graphene oxide (GO) has great potential in enhancing the strength and durability of cement-based materials due to its superior nano properties. While existing studies focus on ambient-condition enhancements, the thermal stability of GO enhanced systems remains unexplored. This investigation systematically evaluates the thermal performance and failure mechanisms of GO-modified cement composite under elevated temperatures. The results show that after high-temperature degradation, the tensile strength of cement-based materials optimized with GO can be increased by 6.5–46.8%. The nucleation and pore-infilling effects of GO nanosheets can be better demonstrated under the condition of high-temperature degradation. The acoustic emission and surface characterization results suggest that the addition of GO can transform a large-scale violent disruption into multiple small-scale disruptions and significantly reinforce the integrity of the hardened cement matrix. Microscopic tests have shown that GO nanosheets optimize the matrix of cement-based materials and suppress the propagation of microcracks during their fracture process. The fractal dimension value of the optimized GO sample is smaller than that of the unoptimized sample. The enhanced thermal stability and fracture integrity of GO-modified cement materials highlight their potential for improving fire resistance in high-temperature engineering applications.

Topological textures of spin vectors are fundamentally interesting and possess generic features for various vector waves. However, experimental realizations of spin skyrmions are mostly restricted to magnetic materials and optical waves, which remains a significant challenge for airborne sound waves with intrinsic curl-free features. In this work, we propose a concentric cylindrical metastructure to construct spin skyrmion textures with subwavelength scale excited by an acoustic spin source. By acoustic spin-orbital coupling, we achieve multi-order confined Bessel spoof acoustic surface waves with orbital angular momentum on the metastructure surface, experimentally observe the acoustic spin skyrmion configurations with subwavelength scale, and verify the topologically protection for introducing the defects. The achievement of acoustic spin skyrmions not only expands the family of topological textures in sound but also provides an avenue to manipulating small particles by controlling structural acoustic fields.

CFRP is extensively utilized in the manufacturing of aerospace equipment owing to its distinctive properties, and hole-making processing continues to be the predominant processing method for this material. However, due to the anisotropy of CFRP, in its processing process, processing damage appears easily, such as stratification, fiber tearing, burrs, etc. These damages will seriously affect the performance of CFRP components in the service process. This work employs acoustic emission (AE) and infrared thermography (IT) techniques to analyze the characteristics of AE signals and temperature signals generated during the CFRP drilling process. Fast Fourier transform (FFT) and short-time Fourier transform (STFT) are used to process the collected AE signals. And in combination with the actual damage morphology, the material removal behavior during the drilling process and the AE signal characteristics corresponding to processing defects are studied. The results show that the time-frequency graph and root mean square (RMS) curve of the AE signal can accurately distinguish the different stages of the drilling process. Through the analysis of the frequency domain characteristics of the AE signal, the specific frequency range of the damage mode of the CFRP composite material during drilling is determined. This paper aims to demonstrate the feasibility of real-time monitoring of the drilling process. By analyzing the relationship between the RMS values of acoustic emission signals and hole surface topography under different drilling parameters, it provides a new approach for the research on online monitoring of CFRP drilling damage and improvement of CFRP machining quality.

The propagation characteristics of acoustic surface waves and the applications of power ultrasound based on AlN/GaN piezoelectric thin films.

Complete CASSE acceleration data measured upon landing of Philae on comet 67P at Agilkia

Abstract The requirements for the stability of power system operation are becoming increasingly stringent. As a key equipment in the power system, monitoring the operation of switchgear has become increasingly important. In the work monitoring, traditional monitoring techniques can only monitor a single element separately. Therefore, this study proposes an integrated monitoring technology for passive wireless temperature partial discharge in switchgear based on ultra-high frequency technology. This study takes ultra-high frequency to monitor partial discharge in switchgear and introduces surface acoustic waves for temperature monitoring. Ultra-high frequency sensors and acoustic surface sensors are used to collect temperature electrical signals and partial discharge signals. Then, a passive wireless temperature partial discharge integrated monitoring model for switchgear is constructed. The results showed that the proposed method achieved monitoring accuracy of 94.32%, 93.14%, and 92.5% for three types of partial discharge signals. When conducting temperature monitoring, the temperature obtained by the proposed method is not significantly different from the actual monitored temperature value, indicating good stability during temperature monitoring. The above results indicate that the proposed ultra-high frequency combined with surface acoustic waves can achieve high accuracy in passive wireless temperature partial discharge integrated monitoring of switchgear.