Search Results (1,762)

Practical testing of a novel underwater circulating towing experimental system has revealed that vibrations induce unstable vehicle operation, necessitating the implementation of vibration mitigation strategies. This paper first establishes a dynamic model of the system using mechanical system dynamics theory and analyzes its vibrational characteristics. The analysis shows that the third-order natural frequency closely aligns with the rotational frequency of the traction motor, thereby risking resonance and performance instability. To address this, shock absorbers are incorporated, and the spring stiffness of the tensioning device is adjusted. Using the vehicle’s vibration acceleration root mean square as the objective function, an annealed particle swarm optimization algorithm is employed to optimize parameters including the equivalent stiffness and damping coefficients of the shock absorbers, as well as those of the spring tensioning device, thus refining the vibration mitigation strategy. The results demonstrate a 6% increase in the initial third-order natural frequency, effectively avoiding resonance. Additionally, the average vibration displacement and acceleration are reduced by 45.8% and 20%, respectively, significantly enhancing operational stability. This research provides substantial theoretical support for improving system stability. Full article

To reveal the real deformation behavior and control mechanism of surrounding rock in hard rock drifts under deep high-stress conditions, a systematic study was conducted involving engineering geological investigation, in situ monitoring of surrounding rock microstrain, and numerical simulation, taking the −1465 m deep main drift of Shaling Gold Mine as the engineering background. Joint and fissure characteristics of the surrounding rock were acquired via the traverse method, and dominant joint sets were identified to evaluate rock mass integrity, providing a geological basis for deformation analysis. On this premise, vibrating wire microstrain sensors were employed to continuously monitor the time-dependent deformation of surrounding rock at different depths in the drift roof and two sidewalls. The strain evolution law of deep hard rock surrounding rock under the combined action of excavation disturbance and high ground stress was systematically analyzed. The results demonstrate that the surrounding rock is dominated by compressive strain in the early stage after excavation, which gradually transforms into tensile strain over time, exhibiting distinct time-dependent deformation characteristics. The deformation magnitude of the surrounding rock decreases significantly with increasing distance from the drift exposure surface, and the overall deformation amplitude of the roof is greater than that of the two sidewalls. Integrating the monitoring results with the surrounding rock structural characteristics, a combined support scheme of “resin rock bolt + wire mesh + shotcrete” was proposed, and its control effect was verified using RS2 numerical simulation. The simulation results indicate that this support system can effectively constrain the near-surface surrounding rock deformation, reduce the degree of stress concentration, and significantly improve drift stability. The research findings provide engineering references for understanding the surrounding rock deformation and optimizing support parameters of deep hard rock drifts in metal mines. Full article

This study investigated the dynamic behavior of AA7075 plates joined by Friction Stir Welding (FSW), focusing on the influence of key process parameters, rotation, and traverse speeds, on the resulting dynamic characteristics. Experimental Modal Analysis (EMA) was performed under free boundary conditions to determine resonance frequencies, mode shapes, and damping ratios, revealing that an increase in traverse speed consistently led to a decrease in natural frequencies across most modes, thereby indicating reduced joint stiffness attributed to insufficient heat input. Furthermore, localized weld defects caused significant damping variations, particularly in low-order modes. To complement the experimental findings and enable simultaneous, multi-output prediction of these coupled dynamic parameters, a Co-Active Neuro-Fuzzy Inference System (CANFIS) model was developed. The CANFIS architecture utilized spindle speed and feed rate as inputs to predict natural frequency and damping ratio for multiple vibration modes as tightly coupled outputs. The trained model demonstrated strong agreement and high predictive accuracy against the EMA experimental data, with convergence analysis confirming its stable learning and excellent generalization capability. The successful integration of EMA and CANFIS establishes a robust hybrid framework for both physical interpretation and intelligent, coupled prediction of the dynamic behavior of FSW-welded AA7075 plates. Full article

Vibration-assisted technology has been employed to satisfy various requirements for different polymeric products due to its excellent performance, but because of the large inertia of the vibration excitation system, these attempts are strictly limited to several fixed vibration amplitudes and frequencies in small extruders or injectors. The purpose of this study is to carry out a numerical investigation via smoothed particle hydrodynamics (SPH) and to perform a comparative analysis of physical parameters among different cases from various perspectives on the fluid channel in twin-screw extruders (TSEs). The results demonstrate that certain combinations of larger vibration amplitudes and frequencies can significantly enhance the velocity, pressure, and particle distribution characteristics within the flow channel. However, no monotonic (i.e., strictly increasing or decreasing) trends are observed with respect to either amplitude or frequency alone. These findings are in excellent agreement with previously reported experimental studies and confirm that the meshless smoothed particle hydrodynamics (SPH) method is a robust and effective computational tool for investigating how various vibrational parameters influence flow behavior in twin-screw extruders (TSEs). Moreover, the results underscore that optimal amplitude and frequency selections must be tailored to the specific rheological and thermal properties of the polymer being processed. This work establishes a solid theoretical and numerical foundation for integrating superimposed vibration-assisted technology into the design optimization of TSE systems. Full article

Vibration is a critical issue in aerospace structures, where lightweight design, high flexibility, and complex operational environments often lead to pronounced nonlinear dynamic responses. Excessive vibrations induced by harmonic excitations, aerodynamic loads, or onboard equipment can significantly degrade structural integrity, control accuracy, and service life. Consequently, advanced passive vibration suppression techniques with strong robustness and broadband effectiveness are of great importance in aerospace engineering applications. The bifurcation boundary and vibration suppression performance of Piezoelectric–Monostable Nonlinear Energy Sink (PMNES) are crucial for evaluating its effectiveness on the main structure. To simplify the analysis of flexible aerospace structures, a reduced-order model is derived by modal truncation in the low-frequency range, which is then treated as a two-degree-of-freedom main structure. To focus on the underlying nonlinear dynamic mechanisms, an equivalent two-degree-of-freedom lumped-parameter system is adopted as a generic representation of the dominant low-frequency dynamics of flexible aerospace structures. In this work, the electromechanical coupling control equations of the system of a two-degree-of-freedom main structure coupled with PNES are derived through the application of Newton’s second law and Kirchhoff’s voltage law. The methods of complexification-averaging (CX-A) and Runge–Kutta (RK) are employed to assess the vibration suppression performance and stability characteristics of the system under harmonic excitation. The approximate solution is validated through numerical solutions. The approximate solutions of the system are employed to derive the Saddle Node (SN) bifurcation and codimension-two cusp bifurcation points, while the enhanced algorithm is employed to ascertain the most unfavorable amplitude at each external excitation circular frequency and to determine whether the mark represents a Hopf Bifurcation (HB) point. The generalized transmissibility is utilized to assess the efficacy of vibration suppression. The various vibration suppression efficiency regions are created by superimposing the vibration suppression efficiency maps and bifurcation maps. The influence of PNES parameters on the vibration suppression region is investigated. The results indicate that this method can effectively evaluate the bifurcation boundary and vibration suppression performance of PMNES. Full article

With the rapid development of Head-Up Display (HUD) technology for vehicles, optical freeform mirrors, as its core optical components, are crucial for achieving system compactness and high imaging quality. However, their complex surface shapes and large-aperture characteristics pose significant challenges to ultra-precision manufacturing. This study presents a systematic optimization framework for the ultra-precision machining of HUD optical freeform mold cores, integrating surface design, tool path planning, vibration analysis, and process parameter optimization. Firstly, based on the XY polynomial freeform surface model, an off-axis three-mirror HUD system was designed, and the surface parameters and machining dimensions of the mold core were determined. For the Single-Point Diamond Turning (SPDT) Slow Tool Servo (STS) process, a hybrid trajectory planning method combining equidistant projection and cubic spline interpolation was proposed to ensure the smoothness and accuracy of the tool path. Through theoretical analysis and experimental verification, the selection criteria for tool parameters such as tool nose radius and effective cutting angle were clarified, and the mechanistic impact of Z-axis vibration on surface roughness and waviness was quantitatively revealed. Finally, through ultra-precision turning experiments and on-machine measurement, a high-precision freeform surface mold core was successfully fabricated. This validates the effectiveness and feasibility of the proposed process solution and provides technical support for the high-quality manufacturing of HUD optical elements. Full article

The dynamic characteristics of bridges are not only influenced by structural damage but also by ambient environmental variations. If environmental factors are not incorporated into the detection algorithm, they may lead to false positives or false negatives. In recent years, vibration-based damage detection methods have gained significant attention in structural health monitoring (SHM), particularly for assessing structural integrity under varying temperature conditions. This study introduces a deep-learning framework for identifying damage in composite bridges by utilizing both time-domain and frequency-domain vibration signals while explicitly accounting for temperature effects. Two deep learning models—Convolutional Neural Network (CNN) and Artificial Neural Network (ANN)—were implemented and compared. The effectiveness of the proposed damage identification approach was evaluated using an experimental dataset obtained from a composite bridge structure. Furthermore, statistical evaluation metrics—including accuracy, precision, recall, F1 score, and the ROC curve—were used to compare the damage detection performance of the two deep learning models. The results reveal that the CNN model consistently outperforms the ANN in terms of classification accuracy. Moreover, frequency-domain analysis was shown to be more effective than time-domain analysis for damage classification, and integrating temperature data with vibration signals improved the performance of all model architectures. Full article

To address the failure risks associated with long-term service of subsea Christmas tree-wellhead systems under the complex marine environment of the South China Sea, a multi-factor coupled mechanical analysis method is proposed to evaluate the system’s mechanical characteristics and ensure the safety of deepwater oil and gas production. A dynamic model of lateral vibration under seismic loading is established, considering the combined effects of earthquakes, ocean currents, and seabed soil resistance. Based on the actual operating parameters of a well in the Lingshui area of the South China Sea, a three-dimensional finite element model of the subsea Christmas tree-wellhead assembly was developed in ABAQUS 2023. The combined effects of ocean currents, seismic loading, and corrosion over long-term service were simulated to compute and analyze the distributions of stress, bending moment, and associated failure risk. The results indicate that, under a once-in-a-century current combined with seismic waves of intensity V–VI, the system risk remains controllable. However, when the seismic intensity exceeds level VII, the maximum stress and bending moment reach 324.9 MPa and 6.02 MN·m, respectively, surpassing the allowable limits for an X56-grade surface conductor. Considering corrosion effects over a 25-year service life, the extreme stress values increase by 1–5% while the bending moment increases slightly; corrosion significantly amplifies the system’s failure risk. An analysis of the mudline burial height of the subsea wellhead during long-term service shows that, within a range of 1–7 m, variations in system loading are minimal. Based on the mechanical characteristics analysis, it is recommended that the design of subsea Christmas trees and wellheads incorporate regional seismic history, specify X56-grade surface conductors to mitigate corrosion effects, and install leakage-monitoring devices at critical locations to ensure the long-term service safety of the subsea Christmas tree-wellhead system. Full article

In conventional band sawing, the long-span compression of the flexible saw blade often results in large fluctuations in cutting force, low cutting efficiency, and poor force predictability. To address these issues, this study investigates the dynamic cutting force modeling and experimental validation of ultrasonic vibration-assisted band sawing using 304 stainless steel as the workpiece material. Based on an analysis of the band sawing mechanism, an ultrasonic vibration-assisted approach is proposed to modify the contact conditions between the saw blade and the workpiece. A dynamic model of the saw blade is established using the string vibration equation, and a multi-tooth dynamic cutting force prediction model is further developed by incorporating variable cutting depth characteristics under ultrasonic vibration. Comparative experiments are conducted between conventional sawing and ultrasonic vibration-assisted sawing to validate the proposed model. At feed rates of 0.1–0.4 mm/s and preload values of 0.1–0.5 mm, the proposed model predicts dynamic cutting forces with good agreement to experimental results, achieving an average relative error of 5.44%. Under typical cutting conditions for difficult-to-machine materials, ultrasonic vibration-assisted sawing reduces the average cutting force and feed force by approximately 15% and 18%, respectively, while decreasing surface roughness along the feed direction by about 21%, thereby improving sawing efficiency and surface quality. Full article

This study investigates the dynamic behaviors of re-entrant unit-cell-shaped steel frames through numerical and experimental modal analyses. Inspired by re-entrant honeycomb structures, individual frame units were modeled to explore how natural frequencies vary with beam cross-sectional dimensions and frame angles. Twenty distinct frame models—incorporating four cross-sectional sizes (4 × 4 mm, 8 × 8 mm, 12 × 12 mm, and 16 × 16 mm) and five main frame angles (120°, 150°, 180°, 210°, and 240°)—were developed using 3D modeling and finite element analysis (FEA) tools, and the first eight natural frequencies and corresponding mode shapes were extracted for each model. The results reveal that lower modes exhibit global bending and torsional behaviors, whereas higher modes demonstrate increasingly localized deformations. It is found that the natural frequencies decrease in the straight frame configuration and increase in the hexagonal configurations, highlighting the critical influence of the frame geometry. Increasing the cross-sectional size consistently enhances the dynamic stiffness, particularly in hexagonal frames. A quadratic polynomial surface regression analysis was performed to model the relationship of the natural frequency with the cross-sectional dimension and frame angle, achieving high predictive accuracy (R² > 0.98). The experimental validation results were in good agreement with the numerical results, with discrepancies generally remaining below 7%. The developed regression model provides an efficient design tool for predicting vibrational behaviors and optimizing frame configurations without extensive simulations; furthermore, experimental modal analyses validated the numerical results, confirming the effectiveness of the model. Overall, this study provides a comprehensive understanding of the dynamic characteristics of re-entrant frame structures and proposes practical design strategies for improving vibrational performance, which is particularly relevant in applications such as machine foundations, vibration isolation systems, and aerospace structures. Full article

In this study, we report a reproducible in situ photochemical method for the simultaneous synthesis of metallic and hybrid metal/metal oxide nanoparticles (NPs) within a UV–curable polymer matrix. A series of epoxy diacrylate-based formulations (BEA) was prepared, consisting of Epoxy diacrylate, Di(Ethylene glycol)ethyl ether acrylate (DEGEEA), and Phenylbis (2,4,6-trimethylbenzoyl) phosphine oxide (BAPO), which served as a Type I photoinitiator. These formulations were designed to enable the simultaneous photopolymerization and photoreduction of metal precursors at various Ag⁺/Co²⁺ ratios, resulting in nanocomposites containing in situ-formed Ag NPs, cobalt oxide NPs, and hybrid Ag–Co₃O₄ nanostructures. The photochemical, magnetic, and dielectric properties of the resulting nanocomposites were evaluated in comparison with those of the pure polymer using UV–Vis and Fourier Transform Infrared Spectroscopy (FT-IR), Photo-Differential Scanning Calorimetry (Photo-DSC), Thermogravimetric Analysis (TGA), Scanning Electron Microscopy (SEM), X-Ray Diffraction (XRD), Impedance Analysis, and Vibrating Sample Magnetometry (VSM). Photo-DSC studies revealed that the highest conversion values were obtained for the BEA-Ag₁Co₁, BEA-Co, and BEA-Ag₁Co₂ samples, demonstrating that the presence of Co₃O₄ NPs enhances polymerization efficiency because of cobalt species participating in redox-assisted radical generation under UV irradiation, increasing the number of initiating radicals and leading to faster curing and higher final conversion. On the other hand, the Ag NPs, due to the SPR band formation at around 400 nm, compete with photoinitiator absorbance and result in a gradual decrease in conversion values. Crystal structures of the NPs were confirmed by XRD analyses. The dielectric and magnetic characteristics of the nanocomposites suggest potential applicability in energy-storage systems, electromagnetic interference mitigation, radar-absorbing materials, and related multifunctional electronic applications. Full article

This study investigates the vibrations at the Castello Svevo-Normanno in Aci Castello (Catania), focusing on its historical and cultural significance. The research aims to analyze vibration levels and frequency distribution to achieve two objectives: protecting historical artifacts and structures through preventive vibration analysis and exploring the use of kinetic energy for powering autonomous systems. The study specifically focuses on the indoor context to understand its unique vibrational characteristics. Measurements were recorded along the X, Y, and Z axes, with detailed analysis of the Z axis using Fast Fourier Transform (FFT) and Power Spectral Density (PSD). The results revealed consistent vibration patterns across all axes, with the Z axis significantly influenced by environmental factors such as wind and sea movement. These findings provide valuable insights for designing optimized energy harvesting systems, electromechanical converters, and monitoring devices suitable for operation in this specific historical context. Full article

To address the impact of environmental and equipment factors on signal identification in highway tunnel drainage pipeline blockage monitoring, this study aims to elucidate the influence patterns of pipeline flow rate, optical fiber deployment scheme, and fiber performance on blockage-induced acoustic signals. A full-scale concrete pipeline experimental platform was established. Data were acquired using a HIFI-DAS V2 sensing system. The time–frequency domain characteristics of acoustic signals under different flow rates (50 m³/h and 100 m³/h), fiber deployment schemes (inside the pipe, outside the pipe, and outside a soundproofing layer), and fiber materials (six typical types) were analyzed and compared. The degree of influence of each factor on signal amplitude and dominant frequency components was quantified. The experimental results indicate that: Compared to a flow rate of 50 m³/h, the amplitude characteristic value at the blockage channel exhibited a marked increase at 100 m³/h, accompanied by an increase in the number and amplitude of dominant frequency components. While the dominant frequency components of the acoustic signals were less stable across the three deployment schemes, the overall amplitude at the blockage channel was consistently higher than that at non-blockage channels. When the fiber was deployed farther from the fluid core (outside the soundproofing layer), the dominant frequencies essentially disappeared, with energy distributed in a broadband form. The peak amplitude and array energy of the sensitive vibration sensing fiber were 2 times and 3.6 times those of the worst-performing type, respectively. Furthermore, its physical properties are better suited to the tunnel environment, effectively enhancing signal acquisition stability and the signal-to-noise ratio. Comprehensive analysis demonstrates that deploying sensitive fibers inside the pipe is more conducive to the accurate identification of blockage events. Moreover, uniform dominant frequency components and threshold criteria are not recommended along the entire length of the drainage pipe. This research provides theoretical and experimental support for parameter optimization of DAS systems to achieve high-precision pipeline blockage monitoring in complex tunnel environments. Full article

Five Cornus mas L. genotypes were analysed based on their attractive colour and high productivity. The ‘Bordo’ cultivar stood out, demonstrating the highest berry weight (3.07 g) and yield per plant (8.24 kg). Close behind was the MH-7-17 selection, with an average yield of 7.37 kg per plant. Both the ‘Bordo’ cultivar and the MH-7-17 selection exhibited excellent agronomic potential, making them ideal candidates for large-scale cultivation. UV-Vis absorption spectroscopy was used to quantify the fruits’ levels of sugars, polyphenols, flavonoids, tannins, anthocyanins and carotenoids (lycopene and β-carotene) and to evaluate their antioxidant capacity. The ‘Bordo’ cultivar had the highest carotenoid content (0.88 mg lycopene and 2.47 mg β-carotene per 100 g), while the TG-J-9-17 and TG-J-20-17 selections had the highest total content of sugars, polyphenols, flavonoids, tannins and anthocyanins and the highest antioxidant capacity. According to the correlations analysis, bigger fruit (which correlated to higher yield) had higher carotenoid content, although lower-level tannin (TTC), flavonoid (TFC), anthocyanin (TAC), and sugar (TSC). Also, total phenolic content (TPC) was positively correlated to TTC, TFC, and radical scavenging activity (RSA), while TFC was positively correlated to TTC, TAC, RSA, but also to TSC. Other positive correlations were those found between TTC and RSA and between lycopene and β-carotene. FTIR spectroscopy was used to identify the characteristic vibrations of the biochemical constituents. Processing the FTIR data using chemometric techniques (principal component analysis and hierarchical clustering analysis) revealed consistent clustering patterns between samples with similar characteristics. Full article

This paper presents the design and fabrication of a triboelectric nanogenerator based on a Quadruple Parallel-cavity Helmholtz Resonator (4C–HR TENG) for the efficient harvesting of noise energy in marine engine room environments. The device utilizes sound waves to drive periodic contact and separation between polytetrafluoroethylene (PTFE) particles in the resonant cavity and the vibrating diaphragm as well as the upper electrode plate, thereby converting sound energy into mechanical energy and finally into electrical energy. The device consists of an acoustic waveguide with a length of 350 mm and both width and height of 60 mm, along with a Helmholtz Resonator with a diameter of 60 mm and a height of 40 mm. Experimental results indicate that under resonance conditions with a sound pressure level of 109.8 dB and a frequency of 110 Hz, the device demonstrates excellent output performance, achieving a peak output voltage of 250 V and a current of 4.85 μA. We analyzed and investigated the influence mechanism of key parameters (filling ratio, sound pressure level, the height between the electrode plates, and particle size) on the output performance. Through COMSOL Multiphysics simulation analysis, the sound pressure enhancement effect and the characteristic of concentrated diaphragm center displacement at the first-order resonance frequency were revealed, verifying the advantage of the four-cavity structure in terms of energy distribution uniformity. In practical applications, the minimum responsive sound pressure level corresponding to the operating frequency range of the 4C–HR TENG was determined. The output power reaches a maximum of 0.27 mW at a load resistance of 50 MΩ. At a sound pressure level of 115.1 dB, the device can charge a 1 μF capacitor to 4.73 V in just 32 s and simultaneously illuminate 180 LEDs in real-time, demonstrating its potential for environmental noise energy harvesting and micro-energy supply applications. This study provides new insights and experimental evidence for the efficient recovery of noise energy. Full article