Acoustic metamaterials are artificially engineered materials composed of subwavelength structural units, whose effective acoustic properties are primarily determined by structural design rather than intrinsic material composition. By introducing local resonances, these materials can exhibit unconventional acoustic behavior, enabling enhanced sound insulation beyond the limitations of conventional structures. In this study, a thin plate (thin sheet) refers to a structural element whose thickness is much smaller than its in-plane dimensions and can be accurately described using classical thin-plate vibration theory. When resonant mass blocks are attached to a thin plate, a thin-plate acoustic metamaterial is formed through the coupling between plate bending vibrations and local resonances. Thin-plate acoustic metamaterials exhibit excellent sound insulation performance in the low- and mid-frequency ranges. Multilayer configurations and the combination with porous materials can effectively broaden the insulation bandwidth and improve overall performance. However, the large number of structural parameters in multilayer composite thin-plate acoustic metamaterials significantly increases design complexity, making conventional trial-and-error approaches inefficient. To address this challenge, a neural-network-based inverse design framework is proposed for multilayer composite thin-plate acoustic metamaterials. An analytical model of thin-plate metamaterials with multiple attached cylindrical masses is established using the point matching and modal superposition methods and validated by finite element simulations. A multilayer composite unit cell is then constructed, and a dataset of 30,000 samples is generated through numerical simulations. Based on this dataset, a forward prediction network achieves a test error of 1.06%, while the inverse design network converges to an error of 2.27%. The inverse-designed structure is finally validated through impedance tube experiments. The objective of this study is to establish a systematic theoretical and neural-network-assisted inverse design framework for multilayer thin-plate acoustic metamaterials. The main novelties include the development of an accurate analytical model for thin-plate metamaterials with multiple attached masses, the construction of a large-scale simulation dataset, and the proposal of a neural-network-assisted inverse design strategy to address non-uniqueness in inverse design. The proposed approach provides an efficient and practical solution for low-frequency sound insulation design.

Nickel–Aluminum–Bronze (NAB) has gained significant attention in marine applications due to its excellent corrosion resistance and has shown growing potential for laser powder bed fusion (L-PBF) additive manufacturing. However, research on the fabrication of NAB alloys using L-PBF remains relatively limited. In this study, fully dense NAB samples were successfully fabricated through L-PBF process parameter optimization. The microstructural evolution and mechanical properties of both as-built and annealed L-PBF samples were systematically investigated and compared with those of traditionally cast NAB. The results reveal that the as-built L-PBF specimens primarily consist of columnar β′ grains, with the α phase distributed along the grain boundaries and a small amount of κ phase precipitated within the β′ matrix, distinctly different from the cast microstructure characterized by a columnar α-phase matrix with precipitated β′ and κ phases. After annealing at 675 °C for 6 h, the β′ phase in both methods decomposed into α + κ phases, and the original columnar structure in the L-PBF specimens transformed into a dendritic morphology. Compared to the cast samples, the L-PBF-produced NAB alloy exhibited significantly enhanced yield strength, tensile strength, and microhardness, attributable to rapid solidification during the L-PBF process. Following annealing, the yield strength and elongation increased by 12.8% and 184.4%, respectively, compared to the as-built condition, resulting from the decomposition of the martensitic phase into α + κ phases and further grain refinement.

This study proposes a composite acoustic porous duct metamaterial muffler composed of a perforated tortuous channel and an externally wrapped porous layer, integrating both structural resonance and material damping effects. Theoretical models for the perforated plate, tortuous channel, and porous material were established, and analytical formulas for the total acoustic impedance and transmission loss of the composite structure were derived. Finite element simulations verified the accuracy of the models. A systematic parametric study was then performed on the effects of porous material type, thickness, and width on acoustic performance, showing that polyester fiber achieves the best results at a thickness of 30 mm and a width of 5 mm. Further analysis of periodic distribution modes revealed that axial periodic arrangement significantly enhances the peak noise attenuation, radial periodic arrangement broadens the effective bandwidth, and multi-frequency parallel configurations further expand the operating range. Considering practical duct conditions, a single-layer multi-cell array was constructed, and its modal excitation mechanism was clarified. By employing the Particle Swarm Optimization (PSO) algorithm for multi-parameter optimization, the average transmission loss was improved from 26.493 dB to 29.686 dB, corresponding to an increase of approximately 12.05%. Finally, physical samples were fabricated via 3D printing, and four-sensor impedance tube experiments confirmed good agreement among theoretical, numerical, and experimental results. The composite structure exhibited an average experimental transmission loss of 24.599 dB, outperforming the configuration without porous material. Overall, this work highlights substantial scientific and practical advances in sound energy dissipation mechanisms, structural optimization design, and engineering applicability, providing an effective approach for broadband and high-efficiency duct noise reduction.

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.

Cantilever roadheaders are widely used in medium-soft rock tunneling. However, conventional pick cutters suffer from high rock-breaking load, excessive energy consumption, and severe abrasion, which restrict the performance of roadheader vehicle-end intelligent control systems. Existing ultrasonic rock-breaking studies mainly focus on drilling and polycrystalline diamond compact (PDC) cutters, while calibrated EDEM simulation and experimental studies of synchronous ultrasonic-vibration-assisted pick cutter cutting remain limited. This study investigates the rock-breaking behavior of synchronous ultrasonic vibration coupled with pick cutter cutting using 21 MPa artificial rock-like specimens. A calibrated EDEM simulation model was developed based on the Hertz–Mindlin with Bonding contact model and validated by uniaxial compression and Brazilian splitting tests. Meta-particle technology was applied to analyze fragmentation characteristics. The effects of ultrasonic frequency, cutting angle, and cone angle on rock-breaking load, debris production, and specific energy consumption were investigated through simulations and experiments. An ultrasonic-assisted cutting test system equipped with force sensors was established for validation. Results show that 30 kHz ultrasonic vibration effectively reduces rock-breaking load under the investigated operating conditions. A relatively favorable parameter combination obtained from the numerical simulations consists of an ultrasonic frequency of 30 kHz, a cutting angle of 40°, and a cone angle of 60°. Compared with conventional cutting, the optimized scheme reduces average cutting load by 74.69%, increases debris yield by 54.71%, and decreases mass-specific mechanical cutting energy consumption by 83.63%. This study provides quantitative data support for roadheader vehicle-end intelligent control systems.