Search Results (206)

Hybrid structural materials (HSMs), such as nanoparticle-treated fabrics, have been shown to enhance acoustic and ballistic performance in multifunctional protective structures. They offer a promising means for low-frequency (<~1000 Hz) noise mitigation, which remains a critical challenge in aerospace and defense applications. The measurement and modeling of their sound transmission loss (TL) behavior using a coupled acoustic–poroelastic approach is explored in this study. A colloid-based soaking and drying process is used to impregnate nanoparticles into the fabric. Previous studies using SEM imaging have established that at low (<~20 wt.%) treatment levels, the nanoparticles agglomerate in the interstitial spaces between yarn crossover points, whereas at higher levels, they begin to coat the yarn bundle tops. TL was measured experimentally using normal-incidence impedance tube tests. Further, parameters such as static flow resistivity, porosity, flexural modulus, and density required to model the neat and treat samples as fluid-filled porous solids using the Biot–Allard model were obtained from experiments for a limited set of neat and treated cases. Static flow resistivity was measured using an air permeability tester as per ISO 9237, and a modified version of the Peirce’s cantilever beam test was used to obtain the flexural modulus for neat and treated samples. Porosity was estimated using digital image analytics. The poroelastic fabric model was implemented in finite element simulations, and the predicted TL was compared with experiments including those for uncalibrated treated cases. The model shows close alignment with measured TL at low frequencies (<~600 Hz) for all cases but deviates closer towards the theoretical mass law at higher frequencies, where flanking effects and the influence of the hierarchy of pores are expected to be dominant in experiments. Further studies are underway to incorporate such higher-order effects to improve predictions at higher frequencies. The development of this model provides a means to capture the influence of nanoparticle addition on the acoustic performance of Kevlar, enabling fast and efficient virtual design iterations. The approach helps optimize HSMs for noise mitigation in multifunctional applications for the aerospace, defense, and infrastructural sectors. Full article

A powder layer was treated as a one-dimensional beam undergoing longitudinal vibration, and the loss factor was derived from the damping ratio based on Rayleigh damping, thereby introducing frequency dependence into the complex modulus. The transfer matrix of the powder layer was subsequently formulated based on the complex modulus, and the validity and effectiveness of the proposed model were evaluated by comparing the calculated and measured values of transmission loss and sound-absorption coefficient. A loss correction was introduced to account for energy dissipation associated with viscous boundary-layer effects and other dissipative mechanisms. A parametric study of the loss correction was conducted, and the correction was quantitatively incorporated through curve fitting based on the root mean square error (RMSE). Comparison of theoretical and experimental transmission loss values revealed that the increasing trend in transmission loss at high frequencies was captured by the proposed model. In the comparison between the experimental and theoretical sound absorption coefficients, this evaluation approach places greater emphasis on the average degree of agreement across the full measurement frequency range rather than at specific frequency points. Consequently, the loss correction yielding the minimum error across the entire frequency range was selected, which occasionally resulted in differences in peak values near the first-order peak frequency. Full article

Accurate daily three-dimensional (3D) ocean sound speed prediction is essential for underwater acoustic applications. Existing data-driven studies often focus on global field errors, leaving localized thermocline-related errors insufficiently addressed. Using ten years of daily GLORYS12 reanalysis data from an equatorial Pacific region, we developed a 3D ConvLSTM predictor for background spatiotemporal evolution. We then proposed the Full-Depth Dynamic Gradient-Guided Residual Correction Network (FDGRC-Net), which derives a continuous mask from the previous-day regional temperature gradient profile to guide residual learning and output gating. On the 2009 test set, FDGRC-Net reduced the overall RMSE from $0.4209$ to $0.3916$ m/s and the MAE from $0.2302$ to $0.2180 \mathrm{m}/\mathrm{s}$. It also demonstrated improved prediction performance in the northern South China Sea cross-region evaluation and achieved annual RMSE reductions of $5.12$–$7.90\%$ in frozen 2010–2015 tests. Against 521 collocated Argo profiles, it slightly but consistently improved the observational agreement. In a controlled Bellhop diagnostic, the transmission loss MAE decreased from $2.825$ to $2.489 \mathrm{dB}$ and the mean arrival time error from $4.099$ to $3.653 \mathrm{ms}$. These results demonstrate that FDGRC-Net provides an effective and physically interpretable approach to thermocline-aware daily 3D sound speed prediction. Full article

A novel hierarchical honeycomb structure is proposed as the core layer of sandwich panels, replacing the hexagonal vertices with other shapes. Its vibration and sound insulation performance are further discussed. Structural acoustic finite element analysis methods were used to simulate the natural frequency, sound transmission loss (STL), and sound pressure distribution within the acoustic domain of the sandwich panels. Within the given simulation parameter range, the sound insulation efficiency of the new hierarchical honeycomb sandwich panel was significantly improved, and the triangular vertex configuration exhibited the best noise reduction ability. By varying the vertex size and the dimensions of the units, the sandwich panels’ vibration reduction and noise insulation capabilities can be further optimized. The average sound transmission loss (STLo) for hierarchical parameter (the ratio of the vertex edge length to the wall length) $\lambda$ = 0.4 increases by 17.2% compared to $\lambda$ = 0.2, greatly improving sound reduction efficiency. When the size of the honeycomb unit is small, the sandwich panel exhibits enhanced acoustic transmission loss within the resonance frequency range. The hierarchical honeycombs after vertex triangle rotation show an STLo level of around 43.08–44.24 dB. The influence of vertex triangle rotation on the STLo of hierarchical honeycomb is closely related to the hierarchical parameters, with STLo increasing by 14.8% for λ = 0.2 and 4% for λ = 0.3, while the opposite phenomenon occurs when$\lambda$ is 0.4. The research results provide valuable insights into improving the vibration reduction and sound insulation performance of honeycomb sandwich panels within the target frequency range by introducing hierarchical features. However, related engineering applications need to rely on subsequent experimental verification. Full article

The construction sector’s substantial contribution to global energy consumption and CO₂ emissions motivates the development of bio-based alternatives to fossil-derived rigid polyurethane (PUR) foam cores in structural sandwich panels. This study presents a comprehensive comparison of plywood sandwich panels manufactured with a rigid PUR foam containing a fast pyrolysis bio-oil (FPBO)-derived sugar polyol diluted with triethyl phosphate and panels of identical topology produced with a commercial reference PUR foam. In the bio-based formulation, a fraction of the sorbitol-based polyether polyol was replaced with the FPBO-derived sugar polyol. Both systems were characterized at the foam and panel levels for cellular microstructure, skeletal and envelope density, thermogravimetric stability, flammability, color, thermal conductivity and heat capacity, internal bond strength, compressive properties, and normal-incidence sound absorption and transmission loss. The newly developed foam exhibited similar skeletal density and porosity to the reference, comparable thermogravimetric stability with a slightly higher char residue, and lower thermal conductivity across the tested temperature range. Mechanical properties, including compressive strength, compressive modulus, and internal bond strength, showed minor reduction but remained within a comparable range. A distinct color change was observed, attributable to the presence of chromophoric constituents of the FPBO fraction. Overall, the results indicate that partial substitution of the fossil polyol with an FPBO-derived sugar polyol is technically feasible, yielding materials with comparable thermal, mechanical, or acoustic performance. No consistent performance advantage of either system was observed across the evaluated properties. The results support the potential of pyrolysis-derived bio-polyols for use in sustainable structural insulation products. Full article

Insulated concrete sandwich panels (ICSPs) are widely utilized in modern building structures due to their excellent combination of energy efficiency and structural load-bearing capacity. However, compared to their mechanical and thermal properties, the sound insulation characteristics of ICSPs remain insufficiently studied, presenting a scientific deficit. In practical engineering, insufficient consideration of these acoustic properties—particularly the “acoustic bridging” induced by connectors—often leads to unpredictable noise transmission, making it difficult for building envelopes to meet stringent modern acoustic codes. To further investigate their acoustic characteristics, this paper extends existing theories on infinite periodic ICSPs to study the airborne sound insulation performance of finite-sized ICSPs. First, analytical models for ICSPs under simply supported on all edges (SS) and clamped on all edges (CC) boundary conditions are derived, wherein the connectors are equivalently modeled as elastic media and discrete elastic springs, respectively. Subsequently, the accuracy and applicability of the analytical models are verified through finite element (FE) models and an airborne sound insulation experiment. Finally, based on the analytical models, a parametric study is conducted to explore the effects of the stiffness of connectors, boundary conditions, and the thickness of the core layer on the sound insulation performance of the ICSPs. The results indicate that connector stiffness has a non-monotonic influence on the sound insulation performance of ICSPs. As the connector stiffness increases, the R_w first decreases and then increases, and the sound insulation performance gradually stabilizes when the connector stiffness becomes sufficiently high. Boundary conditions have a significant effect on the acoustic response. For the reference ICSPs, changing the boundary condition from SS to CC increases the R_w from 49 dB to 62 dB, corresponding to an increment of 13 dB and an approximately 95.0% reduction in the equivalent sound transmission coefficient. When the total panel thickness is kept constant, reducing the core layer thickness from 80 mm to 40 mm increases the R_w from 49 dB to 55 dB under SS boundary conditions and from 62 dB to 66 dB under CC boundary conditions, corresponding to increments of 6 dB and 4 dB, respectively. These improvements are equivalent to reductions of approximately 74.9% and 60.2% in the sound transmission coefficient, though this must be weighed against the inevitable reduction in thermal insulation capacity. Although the sound insulation performance of ICSPs is inferior to that of solid concrete panels (SCPs) of equivalent thickness, with reasonable parameter optimization, their sound insulation indices can significantly exceed the latest requirements of current building codes. By fully accounting for boundary effects in practical engineering, this study provides an analytical basis for the acoustic performance prediction and engineering-oriented optimization of finite-sized ICSPs. 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

Three packaging methods were applied to fresh red apricots: P1 (plastic basket), P2 (breathable foam box), and P3 (perforated corrugated carton). To evaluate the effects of different packaging methods on apricot quality during simulated transportation and subsequent cold storage, fruit quality parameters were measured at 0 h, after 48 h of simulated vibration, and on days 3, 6, and 9 of cold storage. The results showed that, compared with P2 and P3, P1 more effectively maintained fruit surface color and firmness, delayed declines in soluble solids content (SSC), titratable acidity (TA), ascorbic acid content, and moisture content, and reduced water loss and overall weight loss. P1 also suppressed the increase in respiration rate, enhanced peroxidase (POD) and catalase (CAT) activities, suppressed increases in polyphenol oxidase (PPO) activity and hydrogen peroxide (H₂O₂) accumulation, and reduced lipid peroxidation. Additionally, P1 alleviated damage to the cell wall, maintained the structural integrity of the pulp cell walls, and improved the percentage of sound fruit. Transmission electron microscopy (TEM) confirmed that P1 delayed the degradation of the pulp cell wall and maintained the structural integrity of fruit cells. In conclusion, P1 (plastic basket) was the optimal packaging method for maintaining postharvest quality of fresh apricots during simulated transportation and cold storage. Full article

High-precision identification of acoustic convergence zones (CZs) and acoustic shadow zones (SZs) is a core prerequisite for deep-sea sonar performance prediction and long-range underwater target detection. However, in data-scarce marine environments, traditional acoustic identification methods suffer from high environmental sensitivity and significant computational costs, while pure data-driven deep learning methods face dilemmas such as a lack of physical consistency and poor generalization on small samples. To address these issues, a three-level cascaded recognition framework based on physics-prior-augmented deep learning is proposed in this paper, enabling accurate segmentation of CZs and intelligent classification of sound field types under data-scarce scenarios. In this framework, physical acoustic principles are incorporated exclusively as priors through a training dataset generated by a Gaussian beam acoustic propagation code (Bellhop) and through hand-crafted geometric features derived post hoc from the initial segmentation outputs. Taking a typical deep-sea area in the Northwest Pacific Ocean as the research object, a hybrid dataset comprising 5000 simulated transmission loss images and 500 simulated images from a geographically distinct sea area is constructed. The sound field is categorized into four types: strong convergence, usable convergence, weak convergence, and shadow zone. In the first stage, the ResNet-34 backbone is improved by integrating deformable convolution and a global statistical feature module, which, combined with a joint loss function, achieves high-precision pixel-level segmentation of CZs and SZs, with the regional gray contrast reaching 86.9%. In the second stage, a customized dual-channel VGG16 architecture is designed to fuse the extracted geometric priors and visual features, achieving a sound field classification accuracy of 89.91%. In the third stage, a hybrid data augmentation technique combining Mixup and convolutional autoencoder is adopted alongside a transfer learning strategy to mitigate the data scarcity under cross-domain conditions, boosting the small-sample classification accuracy to 84.45%. The experimental results demonstrate that the models in each stage of the proposed framework significantly outperform traditional methods and baseline networks. This study provides a novel methodology and technical support for intelligent sound field identification in data-scarce marine environments. Finally, the core contributions and current limitations are summarized, and future research directions, such as constructing a dynamic hydrological parameter feedback mechanism and identifying three-dimensional complex sound fields, are prospected. Full article

This study presents a comprehensive experimental investigation of lightweight cementitious composites incorporating pumice and expanded perlite as sustainable substitutes for conventional aggregate systems. Four replacement ratios (25%, 50%, 75%, and 100%) were evaluated to determine their effects on density, compressive strength, flexural strength, modulus of elasticity, and acoustic insulation properties, including the noise reduction coefficient (NRC) and frequency-dependent sound transmission loss (STL). The results showed that increasing the lightweight aggregate content generally reduced the strength-related mechanical properties while improving acoustic performance, particularly in the mid- and high-frequency ranges. Among all mixtures, the expanded perlite-based PRC-1.0 specimen exhibited the best overall acoustic performance, achieving the highest NRC value and the widest STL range. These findings demonstrate a clear trade-off between mechanical strength and acoustic efficiency, indicating that expanded perlite-based lightweight cementitious composites are promising materials for building applications requiring enhanced sound insulation performance. Full article

This paper presents a method for determining the reduction in noise transmission provided by small samples of acoustic metamaterials, based on comparative sound intensity measurements. The proposed approach offers an alternative to conventional laboratory methods that require large specimens and controlled acoustic conditions, which limit the rapid testing of prototypes. As part of this study, a mobile and modular measurement setup was developed in the form of a cubic enclosure with replaceable panels, enabling experiments to be conducted under near-real conditions. The measurement methodology is based on determining the difference in sound intensity level, $\Delta L_I$, between a reference configuration and a configuration with an installed metamaterial lining, which allows for the direct evaluation of the increase in sound insulation of the tested partition. To verify the method, a locally resonant metamaterial structure was designed and numerically tuned to a frequency of approximately 460 Hz. Physical samples were then fabricated using 3D printing technology and experimentally tested for two variants of base partitions with different sound insulation performance. The obtained results showed a clear noise transmission reduction in the vicinity of the tuning frequency, reaching approximately 17 dB for the partition with a lower baseline sound insulation and approximately 10 dB for the more insulating partition. A dependence of the metamaterial effectiveness on the properties of the base partition was also observed. The results confirm that the proposed method enables a reliable assessment of the influence of metamaterial structures on the noise transmission reduction of partitions using small samples and a simplified measurement setup. Full article

Quantifying the detection efficiency of buoy-based sonar and optimizing deployment strategies in complex marine environments remain significant challenges. This study proposes a transceiver depth optimization method based on the Bellhop ray model to enhance underwater remote sensing data quality. For the first time, we validated the applicability of acoustic reciprocity in deep-sea environments exceeding 5000 m, characterized by non-uniform sound speed profiles, horizontal inhomogeneity, and steep seamount terrain, with a maximum relative error of <1.2%. This extends the applicable boundaries of the acoustic reciprocity theorem from idealized simple waveguides to complex, realistic deep-sea environments. Building on this validation, we developed a novel, equivalent, superposition modeling framework for bidirectional transmission loss (TL), which converts the computationally intractable TL from target to receiver into the calculable TL from receiver to target, thus significantly reducing computational complexity. Systematic simulations uncovered a depth-layered dependency mechanism: shallow sources (23.14~69.42 m) and deep sources (≥347.10 m) show robustness to large depth differences exceeding 500 m, whereas mid-layer sources (161.98~231.40 m) exhibit a distinct critical threshold effect. Static simulations identify a performance degradation cliff with an onset at an approximate depth difference of 185 m, leading to a 50% reduction in detection range and fragmented near-field detection coverage. To accommodate environmental temporal variability (e.g., internal waves), a conservative safety margin was incorporated, establishing a robust engineering threshold of 150 m. Accordingly, we define 160~350 m as the optimal detection depth window and propose a layered deployment protocol that fills a critical industry gap in quantitative deployment design for deep-sea acoustic detection. Specifically, transceiver depth differences should be strictly constrained to <150 m for mid-layer operations, while more-flexible depth configurations are permissible for shallow and deep sources. These findings furnish quantitative engineering criteria for the design of reliable underwater remote sensing networks, while balancing long-range detection stability and near-field coverage integrity. Full article

Ray-based models have been extensively applied in underwater acoustic propagation modeling because of their favorable physical interpretability and engineering practicality. Nevertheless, in complex ocean environments, conventional acoustic propagation models still face several limitations, including low computational efficiency, empirically determined grid settings, and inadequate local refinement capability, which restrict their application in high-accuracy and high-efficiency simulations. To address these limitations, an adaptive receiver-grid construction method for the BELLHOP model is proposed in this study. The method adaptively adjusts receiver-grid spacings by using seafloor bathymetric features and sound-speed-profile gradient characteristics as the primary driving factors. Specifically, local grid refinement is introduced in the receiver-grid region of critical acoustic propagation areas, whereas relatively coarse grids are employed in non-critical regions, thereby improving acoustic-field resolution while reducing the overall computational cost. Simulation results show that the proposed method effectively improves the transmission-loss computation efficiency and spatial resolution of the BELLHOP model in complex ocean environments, thus providing a practical approach for rapid and high-precision underwater acoustic propagation modeling. Full article

This study focuses on how mesoscale eddies at the Kuroshio boundary in the East China Sea modulate underwater acoustic propagation. Using high-resolution reanalysis data from the Hybrid Coordinate Ocean Model (HYCOM) and validated acoustic ray-tracing simulations, the OW + SLA method is employed for eddy identification and classification. Statistical analysis of 120 eddy events from 2015 to 2020 clarifies their seasonal variation characteristics. Warm eddies shift the convergence zone 15–30 km away from the sound source and broaden it by 20–40%, while cold eddies shift it 10–25 km toward the source and narrow it by 15–35%. A linear relationship exists between eddy amplitude and acoustic transmission loss (TL = 72.4 + 0.42 h, R² = 0.61), where TL is the transmission loss in decibels (dB) and h is the eddy amplitude in meters (m), and there are depth-dependent transmission loss modulation effects. These results provide practical guidance not only for sonar system design and acoustic communication optimization but also for error correction in underwater acoustic navigation systems operating in eddy-prone environments. Full article

This study investigates the sound insulation performance of an anechoic chamber, exploring the influence patterns of different multilayer material combinations on wall sound insulation characteristics. Based on sound transmission theory, a predictive model for multilayer material wall sound insulation was established. The finite element method was employed to simulate the sound propagation characteristics of walls and glass doors with various material combinations. After validating the simulation results through a double-room method experiment, the material combination scheme for the anechoic chamber walls and glass doors was optimized. Based on this, a 1000 mm × 1000 mm × 2300 mm soundproof room prototype was designed and constructed. Its sound insulation performance under reverberant conditions was tested using the insertion loss method and compared with simulation data. Simultaneously, a hybrid calculation method combining low-frequency finite element analysis with high-frequency statistical energy analysis enabled precise and efficient prediction of the overall sound insulation performance of the soundproof room. Research revealed that single-pane glass with thicknesses between 5 and 20 mm conformed to the mass law, with sound insulation increasing by an average of 0.8 dB per additional millimeter. The 10 mm single-pane glass emerged as the optimal choice for the soundproof room’s glass door due to its ideal thickness and excellent low-to-mid-frequency sound insulation. The optimized wall structure featured compact thickness, outstanding low-frequency sound insulation, and balanced mid-to-high-frequency performance. Simulation and experimental results for the core frequency range of 63–1000 Hz showed high consistency, which validates the reliability of the theoretical model and simulation methodology within this frequency band. The deviation of simulation results from experimental data in the frequency range above 1000 Hz is mainly caused by acoustic leakage due to experimental sealing defects, and the high-frequency simulation results are only used for trend analysis rather than conclusion support. This study identifies the optimal multi-layer material combination for soundproof rooms, providing practical material strategies for acoustic design. It also reveals the sound insulation mechanisms of multi-layer composite structures. The findings offer significant reference for optimizing soundproofing materials and structures in architectural acoustics and transportation noise control. Full article