Search Results (101)

This study evaluates adaptive spatial matrix filtering (AMF) combined with MUSIC for underwater acoustic direction-of-arrival estimation under strong out-of-sector interference and extends the method to coherent sources by incorporating forward spatial smoothing (FSS) into the AMF design. Simulations compared AMF-MUSIC with conventional MUSIC and continuous matrix filter (CMF)-MUSIC. For a 20-sensor array with targets at −2° and 1°, an interferer at 50°, an SNR of −5 dB, and an INR of 20 dB, both AMF-MUSIC and CMF-MUSIC resolved the targets under a common −25 dB stopband bound, but AMF-MUSIC produced a smoother out-of-sector background. Tightening the CMF bound to −40 dB reduced background peaks but degraded target resolution. In coherent-source simulations using a 25-sensor array, AMF-FSS-MUSIC resolved the targets for all tested subarray lengths when the angular separation was at least 4.5°, achieving resolution probabilities of at least 95%. A 900–1100 Hz broadband simulation maintained an approximately −15 dB stopband response and a passband-response error below −12 dB. For the SWellEx-96 narrowband data, AMF-MUSIC reduced the DOA-estimation RMSE from 11.16° to 5.18° and increased the mean spatial-spectrum SIR from −0.41 dB to 13.18 dB, while the broadband results qualitatively demonstrated interference suppression. These results indicate a favorable configuration-dependent suppression–fidelity tradeoff, while robustness to other coherent-source conditions and broader measured-data validation require further investigation. Full article

To address the broadband noise distribution, complex excitation sources, and insufficient low-frequency attenuation of conventional porous acoustic packages in commercial vehicle cabs, this study proposes a PU–six-cavity Helmholtz metamaterial composite acoustic package for broadband noise reduction. The proposed structure consists of a 30 mm PU porous layer for mid-to-high-frequency dissipation and a 30 mm six-cavity Helmholtz metamaterial layer for low-frequency absorption, forming a 60 mm composite acoustic package. A full-vehicle acoustic model of a commercial vehicle cab was established in VA One to identify the A-weighted sound pressure level (SPL) spectrum at the driver position. The results show that the PU porous acoustic package improves the mid- and high-frequency noise response, whereas pronounced peaks remain in the low- and low-to-mid-frequency ranges. To enhance these bands, the six sub-cavities of the Helmholtz metamaterial were tuned to 200, 250, 315, 400, 500, and 630 Hz through spatial partitioning and cavity grouping. COMSOL (version 6.1) simulations and particle velocity distributions confirmed the multi-peak absorption mechanism and the selective excitation of the corresponding sub-cavities. The composite structure was further validated through impedance-tube measurements, full-vehicle acoustic simulations, and in-vehicle tests. The VA One simulation shows that the total A-weighted SPL at the driver position decreases from 68.25 dB for the PU porous package to 66.01 dB after introducing the six-cavity Helmholtz metamaterial, corresponding to an additional reduction of 2.24 dB. A preliminary in-vehicle test under a stationary idling condition shows that the total A-weighted SPL near the driver’s ear decreases from 55.83 dB(A) to 54.56 dB(A). These results demonstrate that the proposed PU–six-cavity Helmholtz metamaterial composite acoustic package combines broadband porous dissipation with low-frequency resonant absorption, providing a feasible solution for broadband noise control in commercial vehicle cabs. Full article

Wake-induced magnetic fields provide a potential non-acoustic signature for underwater-vehicle sensing, but their weak amplitudes can be masked by ocean-wave magnetic backgrounds. This study evaluates their engineering observability under representative wind–wave conditions. The wake-induced field at fixed observation points was calculated from CFD-derived wake velocities of an engineering-scale fully appended SUBOFF model using discrete Biot–Savart summation. The ocean-wave background was computed using a JONSWAP spectrum and linear wave theory, and a peak-to-background-rms SNR was used as the observability indicator. Results show that speed and diving depth strongly control the target signal. At the baseline point, increasing speed from 10 to 40 kn raised $B_{wake,max}$ from 0.0406 to 1.65 nT and SNR from −1.01 to 31.2 dB under W2. Increasing diving depth from $2D$ to $4D$ reduced $B_{wake,max}$ from 0.129 to 0.0204 nT and SNR from 9.03 to −6.99 dB. Wind speed dominated the wave background: at $U_{10}=10$ m/s, $B_{wave,rms}$ reached 0.542 nT and the Case 2 SNR decreased to −12.5 dB. Sensor placement affected both signal and background; deeper underwater sensors improved observability, whereas aerial observations suffered from weak wake-signal amplitudes. Wake-field observability is therefore jointly governed by wake source strength, ocean-wave magnetic background, and observation geometry. Full article

The rapid global expansion of data center infrastructure has prompted substantial clean technology research on energy, water, and carbon impacts, while the acoustic health dimension of these facilities remains virtually unstudied. Existing occupational and environmental noise assessments rely on A-weighted (dBA) metrics, which apply more than 26 decibels (dB) of attenuation at 63 hertz (Hz) and exceed 50 dB at infrasound frequencies, sharply discounting their sensitivity to infrasound and low-frequency noise (ILFN) generated by data center cooling fans, heating, ventilation, and air conditioning (HVAC) systems, backup generators, and power transformers. This narrative review synthesizes evidence from established ILFN health research alongside the emerging data center acoustics literature, identifying a consequential gap: no published study has measured the ILFN spectrum of an operational data center, nor examined health outcomes in workers or surrounding communities with respect to sub-audible acoustic exposure. Evidence from wind turbine, industrial, and laboratory contexts documents non-auditory ILFN pathways, including sleep disturbance, cardiovascular stress responses, cognitive impairment, and audiovestibular symptoms—effects that operate below the auditory threshold and are substantially undercounted by standard dBA monitoring. A prioritized research agenda is proposed, beginning with G-weighted and flat-response ILFN characterization of operational data centers across at least 1–200 Hz—a prerequisite for evidence-based acoustic design standards and health-protective infrastructure development consistent with clean technology principles. Full article

Acoustic emission (AE) measurements are commonly used in studies of cementitious composites subjected to various types of loading. Recording macrocracks that result in a decrease in stress is not relatively difficult. This paper focuses on the possibility of identifying micro-events and microcracks during the compression of concrete with dispersed reinforcement. Most AE studies on cement composites correspond to a reduction in stress exceeding the elastic range defined by Hooke’s law, typically associated with the formation of the first crack and detected in the medium- and high-frequency ranges. However, identifying micro-events which do not reduce stress beyond the elastic range is difficult. This study demonstrates that such micro-events can be detected using low-frequency sound and infrasound. In many papers, medium- and high-frequency acoustic signals are effective for recording macrocracks or reinforcement damage. In this work, a 3D acoustic spectrum was used to analyze recorded data in the infrasound range in a concrete compressive test. This approach proved to be the most effective method for determining the critical point f_cr (the end of the elastic range) regarding low-intensity micro-events and microcracks. This type of micro-damage has no significant influence on the linear stress–strain correlation at f_cr. The results indicate that identifying micro-events and low-intensity microcracks using medium- and high-frequency acoustic signals is not possible and that infrasound should be considered for the detection. Significant differences in stress and displacement corresponding to f_cr and f_max were confirmed in concrete compressive tests. The results indicate that accurately determining f_cr is required for correctly assessing the durability of cementitious composites. Full article

Unauthorized unmanned aerial vehicle (UAV) intrusions in sensitive areas such as airports have made accurate UAV detection and localization a pressing need. Acoustic sensing is passive and weather-independent, but conventional microphone arrays require many elements and a large aperture. This paper proposes an acoustic vector sensor (AVS)-based method, termed Covariance Enhancement and Confidence-guided Tracking for 3D Acoustic Localization (CECT-3DAL). A single AVS measures the sound pressure and three-axis particle velocity at one point. Adaptive diagonal loading improves the robustness of the covariance matrix at a low signal-to-noise ratio (SNR). An exponential spectral enhancement strategy sharpens the spatial spectrum peaks for direction estimation, and an eigenvalue-ratio-based confidence drives confidence-weighted smoothing of the angle sequences. Meanwhile, a dual-sensor geometric model provides a closed-form three-dimensional solution. In simulations, the azimuth and elevation root-mean-square errors (RMSEs) were below 1.5° for SNR above 4 dB. In an anechoic chamber, confidence-weighted smoothing reduced the azimuth and elevation standard deviations from 4.34° and 2.63° to 1.46° and 0.86°. In field experiments, the hovering azimuth stayed within a 90% span of 2–3.5°, with an average horizontal RMSE of 0.209 m against a GPS reference, and trajectories under various flight modes remained continuous and smooth. The proposed method offers a compact, passive, and low-cost solution for counter-UAV acoustic surveillance. Full article

Audio–visual speech enhancement aims to recover clean speech by jointly using noisy acoustic signals and synchronized visual cues. Although diffusion-based methods achieve promising restoration performance, their multi-step sampling causes high inference latency and computational cost, limiting real-time deployment. To address this issue, this paper proposes FAV-DenoiseNet, a two-stage framework based on discriminative prior denoising and conditional residual flow matching. The first stage uses a pre-trained discriminative denoising network to suppress dominant noise and provide a structurally stable speech prior. The second stage reformulates enhancement as residual compensation between the first-stage output and the clean speech spectrum instead of directly predicting the entire clean spectrum. A conditional flow-matching network estimates the residual from zero-residual initialization through single-step inference, reducing generative sampling cost. Multi-scale cross-modal attention provides adaptive visual guidance for audio refinement at different resolutions. A residual-controlled fusion strategy preserves the stable structure recovered by the first stage while compensating for residual noise, high-frequency details, and weak speech components. The experimental results show that FAV-DenoiseNet achieves PESQ, ESTOI, and SI-SDR scores of 2.805, 0.775, and 12.480 dB on VoxCeleb2 and 3.157, 0.876, and 13.281 dB on GRID, respectively, with an RTF of 0.086. These results demonstrate that the proposed framework effectively balances enhancement quality, detail restoration, and real-time inference efficiency. Full article

Low-frequency sound insulation remains a major challenge for conventional passive materials, as improved attenuation is usually achieved at the expense of increased thickness and mass. In this work, a smooth fixed third-order ring-curve fractal-maze acoustic metamaterial is proposed for compact low-frequency sound insulation, and a physics-guided long short-term memory–physics prediction surrogate network (LSTM–PPS-Net) tandem framework is developed for its full-spectrum inverse design. Different from conventional Hilbert-type, right-angled, or sharply folded labyrinthine structures, the proposed topology uses recursively arranged curved channels to extend the effective acoustic propagation path and enhance phase accumulation within a limited space. Based on this mechanism, four physically meaningful parameters, namely slit width d, characteristic radius R₃, wall thickness t_w, and inter-column spacing l_E, are selected to construct a low-dimensional design space. A COMSOL–MATLAB automated finite-element method (FEM) workflow is established to generate 1000 valid transmission-loss (TL) spectra over 100–1700 Hz with a 5 Hz interval. For forward prediction, PPS-Net is developed by integrating geometry encoding, frequency-conditioned spectral decoding, and peak-weighted learning. The proposed PPS-Net achieves the best prediction accuracy among the tested models, with a mean absolute error (MAE) of 0.75 dB, a root mean square error (RMSE) of 1.88 dB, and a coefficient of determination (R²) of 0.96, outperforming multi-layer perceptron (MLP), convolutional neural network (CNN) and Transformer models under the same dataset and training protocol. For inverse design, the LSTM encoder extracts frequency-ordered spectral features from the target TL curve, while the frozen PPS-Net decoder provides differentiable acoustic-response feedback, thereby addressing the non-unique mapping from acoustic response to structural parameters. Furthermore, a compactness-oriented optimization strategy is introduced to balance spectral consistency, peak alignment, bandwidth preservation, and occupied-area reduction. In two representative cases, the optimized designs reduce the occupied area by approximately 21% in both representative cases, while maintaining the target attenuation characteristics after FEM verification. These results demonstrate that the proposed framework provides an efficient and physically interpretable route for the full-spectrum inverse design and compact optimization of low-frequency acoustic metamaterials. Full article

This study investigates the coupling between flow dynamics, acoustic response, and convective heat transfer in a rectangular impinging jet striking on a heated slotted plate at two closely spaced Reynolds numbers (Re = 3550 and Re = 3750). Velocity fields were obtained using Particle Image Velocimetry (PIV), and coherent structures were analyzed using Proper Orthogonal Decomposition (POD) while acoustic measurements were used to characterize the tonal behavior. Infrared thermography was employed to determine local and mean Stanton numbers. The mean Stanton number increased by 6.6% when the Reynolds number increased from Re = 3550 to Re = 3750, while the sound pressure level decreased from 78 dB to 71 dB. At Re = 3550, the acoustic spectrum exhibited multi-tone behavior associated with distributed modal energy. In contrast, at Re = 3750, a single dominant frequency governed the flow dynamics. The energy of the first POD mode nearly doubled when passing from Re = 3550 to Re = 3750. The cross-correlation coefficients between the first POD mode and the acoustic field increase from 0.76 to 0.93 when changing from Re = 3550 to Re = 3750. These findings show that the dominant vortex mode which contains nearly 20% of the fluctuating energy (for Re = 3750), significant influences the energy transfer from the dynamic field to the acoustic field resulting in a strong noise reduction. Simultaneously, convective heat transfer increases, highlighting the key role of coherent flow organization on both acoustic and thermal behavior of the system. Full article

To address the demand for underwater acoustic detection with hydrostatic pressure resistance, this paper proposes a fiber-optic Fabry–Perot (F-P) underwater acoustic sensor based on micro-electromechanical system (MEMS) technology. According to the F-P interference principle, the diaphragm deforms under acoustic pressure, inducing variations in the F-P cavity length which modulate the interference spectrum and enable the measurement of underwater acoustic signals. A sensing diaphragm with a composite structure consisting of a central boss and a micro-hole array is designed, which improves the optical signal quality while reducing the influence of the pressure difference between the inner and outer surfaces of the diaphragm on sensor operation. MEMS fabrication, computer numerical control (CNC) machining, and laser fusion splicing technologies are employed to achieve batch fabrication of the sensing units and adhesive-free integration of the sensor. Experimental results show that the proposed sensor exhibits a flat frequency response within ±1.5 dB over the range of 1 kHz to 10 kHz, with an average signal-to-noise ratio (SNR) of 86.35 dB. The sensitivity reaches −181.79 dB re 1 rad/μPa at 10 kHz, with a maximum nonlinearity of 0.48% F.S., a repeatability error of 0.15% F.S. and a dynamic range of 100.83 dB. The proposed sensor features miniaturization, high consistency, hydrostatic pressure self-balancing capability, and immunity to electromagnetic interference, providing a solid foundation for hydrostatic-pressure-resistant underwater acoustic measurements in deep-sea environments. Full article

The International Civil Aviation Organization (ICAO) sets strict limits for aircraft ramp noise, a key source of which is Auxiliary Power Unit (APU) inlet noise. This paper presents a systematic and computationally efficient design methodology for APU inlet mufflers. The high-frequency noise necessitates validating a single-degree-of-freedom liner impedance model up to 10,000 Hz. The core innovation overcomes prohibitive full-passage simulation costs (days) by optimally selecting attenuation center frequencies from the source spectrum and implementing an axially segmented design. This approach enables efficient, targeted optimization (minutes per case) and leverages acoustic mode scattering at segment interfaces to enhance overall attenuation. The design is verified via high-fidelity, full-flow-path simulation. Experimental validation under various operating conditions shows good agreement with predictions, achieving approximately 9 dB reduction in overall A-weighted Sound Power Level (OASPL) with consistent performance. The results demonstrate the feasibility and effectiveness of the proposed rapid, precise, and efficient design framework. Full article

A novel broadband ultrasonic transducer design based on a non-uniform-thickness double-layer piezoelectric structure and a variable-thickness matching layer is proposed to overcome the limitations of conventional thickness-mode piezoelectric ultrasonic transducers, such as weak even-order harmonic responses and restricted bandwidth. The implementation of a non-uniform-thickness double-layer piezoelectric structure enables the simultaneous excitation and reception of ultrasonic signals containing both fundamental and second-harmonic frequencies. Furthermore, through the integration of variable-thickness matching layers with a backing material of non-uniform acoustic impedance, the dual resonant frequency responses are effectively merged into a broad bandwidth. The broadband transducer prototype is manufactured and characterized through electrical input impedance, time-domain pulse-echo signals, and corresponding frequency spectrum. Experimental results indicate a center frequency of 411.5 kHz, with dual resonant peaks observed near 298.6 kHz and 585.6 kHz, achieving a −6 dB relative bandwidth of 116%. The findings demonstrate that the self-developed broadband transducer is capable of effectively generating and receiving broadband signals containing both fundamental and second-harmonic components, thereby offering a new design strategy for broadband piezoelectric transducers. Full article

As ocean resources are further developed and utilized, bionic covert underwater acoustic communication (CUAC) is increasingly important for military and underwater telemetry applications. The primary purpose of this study was to design a highly secure and undetectable text information (TI) encryption mechanism to realize CUAC using real bottlenose dolphin vocalizations (BDVs). For this purpose, a chaotic encryption scheme, spread spectrum (SS) technology, and a modified chaotic Hénon map (MCHM) were integrated into a TI encryption and hiding (EH) mechanism. Four BDVs and four test TIs were employed to demonstrate the performance of the proposed MCHM-based TI EH mechanism (MCHMTIEHM). The simulation results show that the MCHMTIEHM yields more accurate de-hiding and decryption results. When the correct encryption and decryption parameters were used, the test TI was completely recovered and could be recognized by humans. When the MCHM encryption and decryption parameters ${SP}_x \mathrm{a}\mathrm{n}\mathrm{d} n_I$ were not identical, tests involving TI01, TI02, TI03, and TI04 demonstrated correct de-hiding and error decryption performance; in particular, the test TI had superior correct de-hiding and error decryption results, was unrecoverable, and could not be recognized by the human eye. The modified amplitude correlation coefficient (ACC) and modified unified average amplitude change intensity (UACI) metrics were used to evaluate the hiding performance of MCHM-based encryption of TI using BDVs. The simulation results show that the average modified ACC and average UACI were 0.99995924 and $3.84\times {10}^{-6}$, respectively. Performance was evaluated in terms of the average number of changing SS bit rates (NCSSBRs), the average number of changing bit rates (NCBRs), and the average number of changing character rates (NCCRs) for correct de-hiding and correct/erroneous TI decryption. The average NCSSBRs, NCBRs, and NCCRs were all 0% in correct de-hiding and decryption scenarios, while they were 49.29%, 47.65%, and 98.10%, respectively. with correct de-hiding and error-decryption scenarios. In summary, the proposed MCHMTIEHM yields superior encryption and hiding performance. Full article

Left ventricular (LV) apical obliteration represents a convergent imaging phenotype arising from diverse cardiac conditions, including thrombotic, hypertrophic, infiltrative, congenital, and neoplastic diseases. These conditions, despite sharing overlapping morphological features, require profoundly different management strategies. In this context, an accurate characterization of the LV apex is a cornerstone point, and can be performed through various techniques. Advances in multimodality imaging have substantially improved diagnostic precision, allowing clinicians to differentiate true obliteration from mimicking conditions such as hypertrabeculation, apical hypertrophy, or subendocardial fibrosis. This review provides a comprehensive overview of the anatomical variability of the LV apex and its implications for imaging interpretation. We appraise the role of echocardiography, including contrast-enhanced and speckle-tracking studies—alongside cardiac magnetic resonance (CMR), computed tomography (CT), and selective nuclear imaging in the evaluation of apical pathology. For each principal cause of apical obliteration—LV thrombus, apical hypertrophic cardiomyopathy, left ventricular non-compaction, endomyocardial fibrosis, cardiac amyloidosis, and intracardiac tumors—we outline key diagnostic clues, imaging red flags, and distinguishing tissue characteristics. Special emphasis is given to the incremental value of CMR for tissue characterization, thrombus detection, and fibrosis mapping, as well as to the interpretative challenges posed by apical foreshortening, near-field artefacts, and suboptimal acoustic windows. A practical, stepwise imaging framework is proposed to guide clinicians through the differential diagnosis of apical obliteration using an integrated multimodality approach. Future directions include the incorporation of 4D flow, advanced mapping techniques, and artificial intelligence-powered analysis to refine apical phenotyping and identify early disease signatures. Recognizing the full spectrum of apical pathology and its imaging manifestations is essential to prevent misdiagnosis, enable timely therapeutic decisions, and improve risk stratification. Full article

The floor acoustic package is a crucial component of a vehicle’s overall acoustic insulation system, and its performance directly influences the interior sound field distribution and acoustic comfort. Conventional investigations of acoustic package performance primarily rely on experimental testing and computer-aided engineering (CAE) simulations. However, these methods often suffer from limited accuracy control, high computational cost, and low efficiency. In contrast, data-driven modeling approaches have recently demonstrated strong potential in addressing these challenges. In this paper, a Squeeze-and-Excitation Residual Network (SE-ResNet) is proposed to predict and analyze the sound insulation performance of vehicle floor systems based on the original structural and material parameters of acoustic package components. By replacing the conventional CAE process with a data-driven framework, the proposed method enhances prediction accuracy and computational efficiency. With the lowest recorded RMSE of 0.4048 dB across the 200–8000 Hz spectrum, the SE-ResNet model ranks first in overall performance. It substantially outperforms the SE-CNN (0.9207 dB) and also shows a clear advantage over both the SE-LSTM (0.4591 dB) and the ResNet (0.4593 dB). Validation using the acoustic package data of a new vehicle model further confirms the robustness of the proposed approach, yielding an overall RMSE = 0.4089 dB and CORR = 0.9996 on the test dataset. These results collectively demonstrate that the SE-ResNet-based method presents a promising and robust solution for forecasting the sound insulation performance of vehicle floor systems. Moreover, the proposed framework offers methodological and technical support for the data-driven prediction and analysis of other vehicle noise and vibration problems. Full article