Search Results (88)

Conventional acoustic positioning systems are typically confined to regions where direct-path measurements are available. However, in long-range underwater environments, acoustic rays undergo multiple reflections at the sea surface and seafloor, complicating the modeling of sound speed and introducing uncertainty due to seafloor bathymetric errors. To address these challenges, a high-precision positioning technology suitable for long-range deep-sea scenarios is proposed. This technology constructs an effective sound speed model based on ray-tracing principles to accommodate multipath propagation. To mitigate model errors caused by inaccurate seafloor bathymetry, a sound speed compensation mechanism is introduced to enhance the precision of reflected-path measurements. The experimental results demonstrate that, with an array baseline of 8 km, the proposed method reduces the maximum ranging error over a 50 km horizontal distance from 137.9 m to 15.5 m. The root-mean-square positioning error is decreased from 157.9 m to 31.0 m, representing an improvement in positioning precision of 80.4%. These results confirm the feasibility of high-precision long-range acoustic positioning. Full article

Erosion wear is a major cause of surface degradation in metallic materials exposed to harsh marine environments. In this study, the erosion wear resistance of the 18Ni300 maraging steel repaired by underwater direct metal deposition (UDMD) is investigated. Results show that UDMD is successfully applied to repair the 18Ni300 samples in underwater environment. Full groove filling and sound metallurgical bonding without cracks are achieved, demonstrating its potential for underwater structural repair. Microstructural analyses reveal good forming quality with fine cellular structures and dense lath martensite in the deposited layer, attributed to rapid solidification under water cooling. Compared to in-air DMD, the UDMD sample exhibits higher surface microhardness due to increased dislocation density and microstructural refinement. Erosion wear behavior is evaluated at 30° and 90° impingement angles, showing that wear mechanisms shift from micro-cutting and plowing at 30° to indentation, crack propagation, and spallation at 90°. The UDMD samples demonstrate superior erosion wear resistance with lower mass loss, particularly at 30°, benefiting from surface work hardening and microstructural advantages. Progressive surface hardening occurs during erosion due to severe plastic deformation, reducing wear rates over time. The combination of refined microstructure, high dislocation density, and enhanced work hardening capability makes UDMD-repaired steel highly resistant to erosive degradation. These findings confirm that UDMD is a promising technique for repairing marine steel structures, offering enhanced durability and long-term performance in harsh offshore environments. Full article

Considering that the information contained in the interference structure of the “target-receiver” path in active sonar is crucial for remote sensing of the target position or the environmental information, this paper studies the method for coherent extraction and enhancement of the interference structure of the scattered sound field using a monostatic horizontal line array (HLA) in deep water. The HLA element–frequency domain sound intensity interference pattern of the monostatic scattered sound field is numerically simulated, and the “cutting” effect on the pattern is explained by combining the scattered sound pressure expression. Then, the mechanism of the sound propagation effect of the “source-target” path on the interference structure of the “target-receiver” path is clarified. In deep water, the phase relationship of the HLA scattered sound pressure is derived based on the ray theory, and its similarity with the phase relationship of the array passive received signals affected by the source spectrum is researched. The method for the coherent enhancement of the interference structure between the target and the reference array element for the deep-water active sonar is proposed, which uses the phase information of the single-element (SE) signal to generate the array cross-correlation data and then performs striation-based beamforming on it (i.e., the striation–correlation-based beamforming with single element, SCBF-SE). The results of numerical simulation and sea trial data analysis show the effectiveness of this method for interference structure enhancement. The performance differences between SCBF-SE and the incoherent accumulation of the striation energy (IASE) method in interference structure enhancement are compared. The results indicate that SCBF-SE has better performance under the conditions of the same received signal-to-noise ratio and the number of array elements. Full article

This paper proposes an approach to identify interacting objects (IOs) and determine their interaction losses (ILs) using point cloud data from wide-band double-directional channel sounding data. The scattering points (SPs) were identified using the maximum likelihood-based approach applied to the high-resolution path parameters estimated from the channel sounding data, and then IOs were identified via visual inspection of SPs within a 3D point cloud. The proposed approach utilizes all path parameters to calculate the approximate likelihood function for all candidate SPs to determine the SP, regardless of the propagation mechanism. The proposed technique was demonstrated at a suburban residential site with a frequency of 11 GHz. The results show that IOs that are not usually considered in the ray-tracing simulation were identified. Full article

Ultrasonic wave attenuation in biological tissues arises from complex interactions between mechanical, structural, and fluidic properties, making it essential to identify dominant mechanisms for accurate simulation and device design. This work introduces a novel integration of experimentally measured tissue parameters into time-explicit nonlinear acoustic wave simulations, in which the equations are directly solved in the time domain using an explicit solver. This approach captures the full transient waveform without relying on frequency-domain simplifications, offering a more realistic representation of ultrasound propagation in heterogeneous media. The study estimates both sound diffusivity and viscous damping parameters (dynamic and bulk viscosity) for a broad range of ex vivo tissues (skin, adipose tissue, skeletal muscle, trabecular/cortical bone, liver, myocardium, kidney, tendon, ligament, cartilage, and gray/white brain matter). Four regression models (power law, linear, exponential, logarithmic) were applied to characterize their frequency dependence between 0.5 and 5 MHz. Results show that attenuation is more strongly driven by bulk viscosity than dynamic viscosity, particularly in fluid-rich tissues such as liver and myocardium, where compressional damping dominates. The power-law model consistently provided the best fit for all attenuation metrics, revealing a scale-invariant frequency relationship. Tissues such as cartilage and brain showed weaker viscous responses, suggesting the need for alternative modeling approaches. These findings not only advance fundamental understanding of attenuation mechanisms but also provide validated parameters and modeling strategies to improve predictive accuracy in therapeutic ultrasound planning and the design of non-invasive, tissue-specific acoustic devices. Full article

Cone Penetration Tests with pore pressure measurements (CPTu) are widely used in geotechnical site investigations due to their high-resolution profiling capabilities. However, traditional interpretation methods—such as the Soil Behavior Type Index ($I_c$)—often fail to capture the internal heterogeneity typical of mining tailings deposits. This study presents a machine learning-based approach to enhance stratigraphic interpretation from CPTu data. Four unsupervised clustering algorithms—k-means, DBSCAN, MeanShift, and Affinity Propagation—were evaluated using a dataset of 12 CPTu soundings collected over a 19-year period from an iron tailings dam in Brazil. Clustering performance was assessed through visual inspection, stratigraphic consistency, and comparison with $I_c$-based profiles. k-means and MeanShift produced the most consistent stratigraphic segmentation, clearly delineating depositional layers, consolidated zones, and transitions linked to dam raising. In contrast, DBSCAN and Affinity Propagation either over-fragmented or failed to identify meaningful structures. The results demonstrate that clustering methods can reveal behavioral trends not detected by $I_c$ alone, offering a complementary perspective for understanding depositional and mechanical evolution in tailings. Integrating clustering outputs with conventional geotechnical indices improves the interpretability of CPTu profiles, supporting more informed geomechanical modeling, dam monitoring, and design. The approach provides a replicable methodology for data-rich environments with high spatial and temporal variability. Full article

Near-field acoustic holography (NAH) provides an effective way to achieve wide-band, high-resolution visualization measurement of the sound insulation performance of building components. However, based on Green’s function, the microphone array’s inherent amplitude and phase mismatch errors will exponentially amplify the sound field inversion process, significantly reducing the measurement accuracy. To systematically evaluate this problem, this study combines numerical simulation with actual measurements in a soundproof room that complies with the ISO 10140 standard, quantitatively analyzes the influence of array system errors on NAH reconstructed sound insulation and acoustic images, and proposes an error correction strategy based on channel transfer function normalization. The research results show that when the array amplitude and phase mismatch mean values are controlled within 5% and 5°, respectively, the deviation of the weighted sound insulation measured by NAH can be controlled within 1 dB, and the error in the key frequency band of building sound insulation (200–1.6k Hz) does not exceed 1.5 dB; when the mismatch mean value increases to 10% and 10°, the deviation of the weighted sound insulation can reach 2 dB, and the error in the high-frequency band (≥1.6k Hz) significantly increases to more than 2.0 dB. The sound image shows noticeable spatial distortion in the frequency band above 250 Hz. After applying the proposed correction method, the NAH measurement results of the domestic microphone array are highly consistent with the weighted sound insulation measured by the standard method, and the measurement difference in the key frequency band is less than 1.0 dB, which significantly improves the reliability and applicability of low-cost equipment in engineering applications. In addition, the study reveals the inherent mechanism of differential amplification of system errors in the propagating wave and evanescent wave channels. It provides quantitative thresholds and operational guidance for instrument selection, array calibration, and error compensation of NAH technology in building sound insulation detection. Full article

This study establishes a multiphysics coupling model of acoustics, mechanics, and electrostatics through COMSOL, systematically explores the sound field distribution and stress–strain characteristics of tailing particles in sand silos under different frequencies of ultrasonic radiation, and proposes an optimization scheme for the sound field. The simulation results show that under 28 kHz ultrasonic radiation, the amplitude of sound pressure in the sand silo (173 Pa) is much lower than that at 40 kHz (1220 Pa), which can avoid damaging the original settlement mode of the tail mortar. At the same time, the periodic fluctuation amplitude of its longitudinal sound pressure is significantly greater than 25 kHz, which can promote settlement by enhancing particle tensile and compressive stress, achieving the best comprehensive effect. The staggered placement scheme of the transducer eliminates upward disturbance in the flow field by changing the longitudinal opposing sound field to oblique propagation, reduces energy dissipation, and increases the highest sound pressure level in the compartment to 130 dB. The sound pressure distribution density is significantly improved, further enhancing the settling effect. This study clarifies the correlation mechanism between ultrasound parameters and tailings’ settling efficiency, providing a theoretical basis for parameter optimization of ultrasound-assisted tailing treatment technology. Its results have important application value in the optimization of tailings settling in metal mine tailing filling. Full article

The formation of hot tearing during direct chill casting of aluminum alloys, specifically AA6111, is a significant challenge in the production of ingots for industrial applications. This study investigates the role of hydrostatic pressure and tensile stress in the formation of hot tearing during direct chill casting of rectangular ingots. Combining experimental results and finite element modeling with ABAQUS/CAE 2022, the mechanical behavior of the semi-solid AA6111 alloy was analyzed under different cooling conditions. “Hot” (low water flow) and “Cold” (high water flow) conditions were the two types of cooling conditions that produced cracked and sound ingots, respectively. The outcomes indicate that high tensile stress and localized negative hydrostatic pressure in the hot condition are the main factors promoting the initiation and propagation of cracks in the mushy zone, whereas the improvement of the cooling conditions reduces these defects. Full article

The real-time acquisition of an accurate underwater sound velocity profile (SSP) is crucial for tracking the propagation trajectory of underwater acoustic signals, making it play a key role in ocean communication positioning. SSPs can be directly measured by instruments or inverted leveraging sound field data. Although measurement techniques provide a good accuracy, they are constrained by limited spatial coverage and require a substantial time investment. The inversion method based on the real-time measurement of acoustic field data improves operational efficiency but loses the accuracy of SSP estimation and suffers from limited spatial applicability due to its stringent requirements for ocean observation infrastructures. To achieve accurate long-term ocean SSP estimation independent of real-time underwater data measurements, we propose a semi-transformer neural network (STNet) specifically designed for simulating sound velocity distribution patterns from the perspective of time series prediction. The proposed network architecture incorporates an optimized self-attention mechanism to effectively capture long-range temporal dependencies within historical sound velocity time-series data, facilitating an accurate estimation of current SSPs or prediction of future SSPs. Through the architectural optimization of the transformer framework and integration of a time encoding mechanism, STNet could effectively improve computational efficiency. For long-term forecasting (using the Pacific Ocean as a case study), STNet achieved an annual average RMSE of 0.5811 m/s, outperforming the best baseline model, H-LSTM, by 26%. In short-term forecasting for the South China Sea, STNet further reduced the RMSE to 0.1385 m/s, demonstrating a 51% improvement over H-LSTM. Comparative experimental results revealed that STNet outperformed state-of-the-art models in predictive accuracy and maintained good computational efficiency, demonstrating its potential for enabling accurate long-term full-depth ocean SSP forecasting. Full article

Medical phantoms are essential to imaging calibration, clinician training, and the validation of therapeutic procedures. However, most ultrasound phantoms prioritize acoustic realism while neglecting the viscoelastic and anisotropic properties of fibrous soft tissues. This gap limits their effectiveness in modeling realistic biomechanical behavior, especially in wave-based diagnostics and therapeutic ultrasound. Current materials like gelatine and agarose fall short in reproducing the complex interplay between the solid and fluid components found in biological tissues. To address this, we developed a soft, anisotropic composite whose dynamic mechanical properties resemble fibrous biological tissues such as skin and skeletal muscle. This material enables wave propagation and vibration studies in controllably anisotropic media, which are rare and highly valuable. We demonstrate the tunability of damping and stiffness aligned with fiber orientation, providing a versatile platform for modeling soft-tissue dynamics and validating biomechanical simulations. The phantoms achieved Young’s moduli of 7.16–11.04 MPa for skin and 0.494–1.743 MPa for muscles, shear wave speeds of 1.51–5.93 m/s, longitudinal wave speeds of 1086–1127 m/s, and sound absorption coefficients of 0.13–0.76 dB/cm/MHz, with storage, loss, and complex moduli reaching 1.035–6.652 kPa, 0.1831–0.8546 kPa, and 2.138–10.82 kPa. These values reveal anisotropic response patterns analogous to native tissues. This novel natural fibrous composite system affords sustainable, low-cost ultrasound phantoms that support both mechanical fidelity and acoustic realism. Our approach offers a route to next-gen tissue-mimicking phantoms for elastography, wave propagation studies, and dynamic calibration across diverse clinical and research applications. Full article

As a fundamental technology in environmental perception, sound source localization (SSL) plays a critical role in public safety, marine exploration, and smart home systems. However, traditional methods such as beamforming and time-delay estimation rely on manually designed physical models and idealized assumptions, which struggle to meet practical demands in dynamic and complex scenarios. Recent advancements in deep learning have revolutionized SSL by leveraging its end-to-end feature adaptability, cross-scenario generalization capabilities, and data-driven modeling, significantly enhancing localization robustness and accuracy in challenging environments. This review systematically examines the progress of deep learning-based SSL across three critical domains: marine environments, indoor reverberant spaces, and unmanned aerial vehicle (UAV) monitoring. In marine scenarios, complex-valued convolutional networks combined with adversarial transfer learning mitigate environmental mismatch and multipath interference through phase information fusion and domain adaptation strategies. For indoor high-reverberation conditions, attention mechanisms and multimodal fusion architectures achieve precise localization under low signal-to-noise ratios by adaptively weighting critical acoustic features. In UAV surveillance, lightweight models integrated with spatiotemporal Transformers address dynamic modeling of non-stationary noise spectra and edge computing efficiency constraints. Despite these advancements, current approaches face three core challenges: the insufficient integration of physical principles, prohibitive data annotation costs, and the trade-off between real-time performance and accuracy. Future research should prioritize physics-informed modeling to embed acoustic propagation mechanisms, unsupervised domain adaptation to reduce reliance on labeled data, and sensor-algorithm co-design to optimize hardware-software synergy. These directions aim to propel SSL toward intelligent systems characterized by high precision, strong robustness, and low power consumption. This work provides both theoretical foundations and technical references for algorithm selection and practical implementation in complex real-world scenarios. Full article

The nonlocal macro–meso-scale damage (NMMD) model, implemented in the framework of the finite element method, has been demonstrated to be a promising numerical approach in simulating crack initiation and propagation with reliable efficacy and high accuracy. In this study, the NMMD model was further enhanced by employing an identical degradation mechanism for both the tensile and shear components of shear stiffness, thereby overcoming the limitation of equal degradation in shear and tensile stiffness inherent in the original model. Additionally, a more refined and physically sound seepage evolution function was introduced to characterize the variation in permeability in porous media with geometric damage, leading to the development of an improved NMMD model suitable for simulating coupled seepage–stress problems. The reliability of the enhanced NMMD model was verified by the semi-analytical solutions of the classical KGD problem. Finally, based on the modified NMMD model, the effects of preset fracture spacing and natural voids on hydraulic fracture propagation were investigated. Full article

Motion of dislocations is a common mechanism of plasticity in many materials. Acoustic emissions and stress bursts turned out to be integral parts of this mechanism. An adequate description of these processes is an important goal of the Materials Theory, which aims to describe the mechanical properties of materials and their reliability in service. In this article, a novel approach to dislocation plasticity capable of describing emission events and stress bursts is introduced, and computational experiments intended to model the processes of compressive creep and shock compression in samples of various makeup and sizes are discussed. It turns out that the emission events self-organize into dislocation avalanches, which propagate at a speed determined by the conditions of loading. In the compressive creep experiments, the avalanches arrange into slow-moving slip bands, while in the shock compression experiments the avalanches move faster than sound. Full article

Fluororubber sealing products are widely used in nuclear power equipment, and the degree of degradation of their mechanical properties directly affects the sealing performance, which in turn affects the overall safety of nuclear power units. In order to quantitatively evaluate the degradation of the mechanical properties of fluororubber, the theory of ultrasonic propagation in fluororubber was studied. A second-order generalized Maxwell viscoelastic model was constructed in a small strain scenario of high-frequency harmonic vibration to describe the correlation between the mechanical properties and acoustic parameters. A nondestructive evaluation method for mechanical performance degradation using ultrasonic waves based on the nonlinear fitting of the model parameters was proposed. A control experiment was designed using O-rings that had been in service and those that had not yet been used in nuclear power, and mechanical tensile tests and electron microscopy microscopic analyses were conducted. The results showed that the overall elastic modulus of the used sealing ring (2.97 ± 0.15 GPa) was significantly higher than that of the unused sealing ring (2.75 ± 0.22 GPa), consistent with the results of the mechanical tensile tests. However, the sound attenuation coefficient of the unused sealing ring was significantly higher than that of the used sealing ring. Therefore, the ultrasonic evaluation of the mechanical performance degradation of fluororubber based on the viscoelastic model is a nondestructive testing method with engineering application potential. Full article