Search Results (1,006)

In response to common issues with traditional automotive switches, such as poor contact of terminals, low durability, and weak vibration resistance, this paper proposes and designs a novel high-performance automotive toggle switch. Through structural design and parameter optimization, a new solution is provided to enhance the structural strength and service life of automotive electronic components. After completing three-dimensional modeling based on SolidWorks 2025, a full set of simulation analyses was carried out using ANSYS Workbench 2024 R2. After structural optimization, the maximum stress of the core valve stem decreased from 17.19 MPa to 14.877 MPa, a reduction of 13.5%; meanwhile, the fatigue life increased to 2.51 times that before optimization, indicating that for polycarbonate materials, a slight reduction in stress can significantly slow the rate of component damage accumulation. The switch’s first-order natural frequency is 1171.7 Hz, and a random vibration analysis of the switch was conducted according to the industry standard ISO 16750-3:2023. Under excitations covering the entire 2000 Hz frequency range, the switch structure did not show deformation or fatigue risks caused by resonance, indirectly confirming that vibration energy density is often more concentrated at low frequencies. This study not only completes the innovative design and performance verification of the novel toggle switch but also demonstrates that the comprehensive research methods employed provide a systematic analytical approach for developing high-performance, highly reliable automotive electronic components under stringent industry standards. Full article

High-g accelerometers are in high demand across sectors such as aerospace, defense, and industrial inspection. This paper presents a MEMS accelerometer based on graphene piezoresistors, designed for precise acceleration measurement under sudden impacts, intense vibrations, and extreme conditions, such as engine fault diagnosis and weapon impact testing. A step-by-step structural optimization and simulation analysis were conducted using finite-element simulation. Taking the peak strain at the beam root, the first-order natural frequency, and the maximum equivalent stress as optimization objectives, progressive parametric optimization was sequentially performed on four progressive architectures: a simple beam, a beam mass, a beam mass with stress concentration grooves, and a beam mass with stress concentration grooves and symmetric masses. The results indicate that the introduction of a central mass enhances the peak strain by more than 15 times compared to the simple beam. The addition of stress concentration grooves further increases the strain by approximately 30%. Finally, the incorporation of symmetric masses yields a further 9% strain enhancement while reducing cross-axis sensitivity by 5.6%, effectively suppressing off-axis interference. The final structure achieves maximized strain while maintaining a first-order natural frequency above 200 kHz, with the maximum equivalent stress staying within the allowable limit. This optimal comprehensive performance provides essential technical support for high-performance graphene-based accelerometers. In addition to the mechanical structural optimization, the graphene piezoresistors were treated as surface sensing regions at the beam-root locations, and the area-averaged longitudinal strain was extracted as the input of a piezoresistive transduction model. The simulated strain was converted to resistance variation and bridge output voltage using a graphene gauge-factor-based readout model incorporating contact-resistance effects, thereby providing a sensor-level electromechanical performance estimation for the proposed high-g accelerometer. Full article

Intelligent fault diagnosis of rotating machinery is essential for ensuring the safety and reliability of industrial systems. While hypergraph neural networks (HGNNs) have recently shown promise for modeling high-order dependencies beyond pairwise graph methods, most existing variants operate in Euclidean space, which is not explicitly aligned with hierarchical fault-response structure (root cause to fault mode to observed response). To address this limitation, we propose Hyperbolic Hypergraph Neural Network (H²GNN), a framework that integrates hyperbolic geometry with hypergraph neural networks for fault diagnosis. Specifically, H²GNN constructs fault-response-aware hyperedges over diagnostic views of vibration signals and performs message passing in the Poincaré ball model, a Riemannian manifold of constant negative curvature commonly used for hierarchical representation learning. We introduce Poincaré hyperedge aggregation via an iterative Fréchet-mean solver, a learnable curvature parameter for adaptive manifold fitting, and a tangent-space classification head. Experiments are conducted on two public benchmarks, namely the Case Western Reserve University (CWRU) bearing dataset and the Machinery Failure Prevention Technology (MFPT) bearing dataset, and report mean accuracies of 99.87% and 99.75%, respectively, outperforming six competing methods, including CNN, GCN, HGNN, dynamic-HGNN, contrastive-HGNN, and spatial-temporal HGNN. Ablation studies indicate that hyperbolic geometry and the adaptive curvature mechanism both contribute to the observed performance gain. Full article

Permanent magnet synchronous motors (PMSMs) are widely employed in electric vehicles owing to their high efficiency, high power density, and wide speed regulation capability. However, electromagnetic vibration is aggravated by the non-sinusoidal air gap magnetic field distribution and cogging torque. To suppress vibration, this paper proposes an optimized asymmetric rotor design. Through sensitivity analysis of rotor parameters on motor performance, a high-precision Metamodel of Optimal Prognosis (MOP) is developed for the surrogate-based motor model. Subsequently, rotor parameters are comprehensively optimized using a genetic algorithm. The results demonstrate that, compared with the reference motor under identical operating conditions, the optimized motor maintains equivalent output torque while achieving significant reductions in vibration-related performance indicators: torque ripple is reduced by 17.9%, and cogging torque is reduced by 82.8%, the amplitude of the 48th-order electromagnetic force decreases from 2.60 N to 1.28 N (representing a 50.7% reduction), and the peak vibration response decreases from 109.7 dB to 107.2 dB. This study provides an effective design approach for electromagnetic vibration suppression in PMSMs. Full article

In this study, a high-order Galerkin–Numerov approach is presented to solve the transient vibration problem of anisotropic Kirchhoff plates supported by a uniform Vlasov foundation. A discretization of the governing fourth-order plate equation is derived based on a mixed boundary value problem and a hybrid Hermite–sine Galerkin formulation, which maintains the C1-continuity properties of classical plate theory. The resulting reduced-order modal system is integrated in time with the Numerov scheme, which is fourth-order accurate, and has a small numerical dispersion and good phase-preserving properties for oscillatory dynamics. The proposed methodology is evaluated using stability and convergence tests and parametric investigations. The fourth-order temporal convergence and rapid spectral-like spatial convergence of the numerical results are validated, and the long-time accuracy and robustness of the formulation is confirmed by the negligible phase error and bounded energy drift. The results from the parametric study indicate that the thickness of the plates and the stiffness of the Winkler foundation are the two most important mechanisms for vibration suppression, while the orthotropic coupling and the Vlasov shear interaction have substantial effects on the modal redistribution and transient deformation properties. The proposed method is compared with the conventional lower-order integration schemes, and it is observed that the method gives better phase fidelity and computational efficiency, and it is possible to predict the vibration amplitude and vibration timing accurately. In addition to the numerical benefits, the framework also provided physical insights on the coupled effect of anisotropy, foundation interaction and boundary restraint. The suggested model is directly applicable for composite floor systems, aerospace panels, foundation supported slabs, biomechanical plate analogs, etc., and smart vibration control platforms. This work thus lays the groundwork for future studies of nonlinear behavior, adaptive foundations and digital twin simulation of structural systems and presents a strong and scalable computational tool for the study of plate–foundation dynamics. Full article

In this study, we reveal the emergence of a tri-regime gradient in stiffness across substrate-supported poly(3-alkylthiophene) (P3AT) thin films, comprising an adsorbed region, a bulk-like region, and a free surface region. The stiffness distribution is found to be largely independent of the degree of polymerization but is significantly modulated by side chain length and temperature. Specifically, longer side chains (bead count = 4) expand the adsorbed and free surface regions, while elevating temperature above the glass transition leads to an order-of-magnitude reduction in stiffness. Phonon mode analysis demonstrates a clear inverse correlation between vibrational frequency and both the degree of polymerization and temperature, with side chain length exerting minimal influence. A high phonon mode similarity index between the main and side chains indicates coupled vibrational dynamics. Interfacial energy decomposition confirms that van der Waals interactions, particularly through distinct π–π stacking, dominate the substrate adhesion. These findings provide fundamental insights into the nanoscale thermomechanical properties of P3AT thin films on silica substrates, offering valuable guidance for the interface engineering of P3AT-on-silica systems in organic electronics. Full article

Studies of third-order shear-deformation theory (TSDT) and an advanced shear coefficient for thick-walled functionally graded material (FGM) spherical shells subjected to thermal vibrations triggered by sinusoidal temperature are presented. The nonlinear TSDT and linear and nonlinear shear coefficient can be converted into fully homogeneous equation algorithms under the sinusoidal form of free vibrations to obtain the fundamental natural frequency by using Newton’s numerical method. Then, the generalized differential quadrature (GDQ) method can be used to prepare dynamic discrete equations of motion triggered by sinusoidal temperature field in thick FGM spherical shells for materials SUS304 and Si₃N₄. The Young’s modulus expressed as a power-law function of thick FGM spherical shells is considered and subjected to applied thermal load. The response results of thermal stress and center displacement are compared for the cases of linear and nonlinear advanced shear coefficient, and simply and fully homogeneous equation algorithms, respectively. The practical insights for temperature effect considered in the calculation of stress and displacement are very clear and practical for FGM structures with geometries of spherical shells. The power-law function property of FGMs can be used under high temperature for four-sided simply supported constraints. Full article

Dye removal from aqueous solutions remains a major global environmental challenge. Among the various remediation techniques, adsorption using natural materials has gained significant attention. In this study, the adsorption of methylene blue (MB) by a natural volcanic rock (VR) adsorbent—collected from the Cerro Blanco volcano in Divisaderos, Sonora, Mexico—was investigated, and the process efficiency was evaluated at different temperatures. The comprehensive characterization revealed a rough and irregular porous surface via SEM, while the EDS elemental data and the CIPW normative calculations identified the material as a silica-saturated tholeiitic basalt, primarily composed of bytownite (${An}_{71})$ and pyroxenes. This petrological classification was cross-validated by XRD and FTIR spectra, which exhibited vibrational modes characteristic of mafic silicate. The surface analysis via the BET method indicated a specific surface area of 12 m²·g⁻¹, while a BJH analysis indicated a mesoporous structure (average pore diameter of 3.75 nm), and a Type IV isotherm with H3-type hysteresis, suggesting narrow, slit-shaped pores. Batch adsorption experiments demonstrated an exceptional removal efficiency of 99.99% for 50 mg·L⁻¹ MB within only 30 min. The equilibrium data and the adsorption kinetics followed the Langmuir isotherm and a pseudo-second-order model, respectively. Cytotoxicity assays confirmed the VR is biosafe. The combination of high removal efficiency, low cost, and environmental safety positions this material as high-potential adsorbent for sustainable water remediation processes. Full article

As the foundational sensing element for AI-driven structural health monitoring systems, piezoelectric ceramic (PZT) is widely adopted in civil engineering to capture high-fidelity physical responses. Distinct from existing studies focusing on the actuation mode or static/quasi-static sensing conditions, this study specifically investigates the dynamic strain transfer behavior of surface-bonded PZT sensors in sensing mode by establishing a three-layer analytical model incorporating the adhesive shear lag effect, validated by finite element simulations. Accordingly, a dual-regime dynamic calibration strategy is proposed: employing a single sensitivity value for low-frequency global structural vibrations and frequency-dependent correction for high-frequency elastic wave applications. Parametric analyses on PZT thickness, adhesive thickness, and shear modulus quantitatively demonstrate that reducing PZT/adhesive thicknesses and increasing adhesive shear modulus extend the compensation-negligible frequency range (defined by a 10% strain ratio deviation threshold) and elevate the first-order longitudinal natural frequency; practical sensor fabrication guidelines are further derived from these findings. Additionally, the system’s first-order longitudinal natural frequency stabilizes when the host-to-PZT area ratio (A_s/A_p) exceeds a critical threshold. These findings provide a theoretical basis for the optimal design, dynamic calibration, and engineering application of bonded PZT sensors. Full article

The vibration characteristics of clamped–clamped Alumina–Steel axially functionally graded (AFG) fluid-conveying Timoshenko pipes are investigated using a physics-based generalized integral transform technique (GITT) benchmark and a multi-layer perceptron (MLP) surrogate trained on GITT data. Parametric GITT sweeps over the power-law gradation index k, dimensionless flow velocity u, and aspect ratio $L/D$ quantify how axial material gradation controls the first two natural frequencies (${\omega }_1$, ${\omega }_2$) and the maximum vibration deflection ($y_M$): increasing k reduces ${\omega }_1$ and ${\omega }_2$; on u-sweeps at $L/D=50$, larger k also increases $y_M$ and lowers the critical flow velocity, whereas on $L/D$-sweeps at $u=3.0$, $y_M$ decreases with k. A feedforward MLP surrogate fitted to $N_{\mathrm{s}}=336$ GITT samples via an interior block-wise train–test split and three independent networks with output-specific preprocessing achieves $R^2>0.99$ on held-out data, with maximum relative errors below 9%, and reproduces representative GITT parametric curves in overlay validation. After one-time offline training, MLP inference is orders of magnitude faster than online GITT runs, enabling large-scale global sensitivity analysis based on Sobol indices, SHAP values, and partial dependence plots; these identify u as the dominant influence on the modal responses, while SHAP ranks k first for ${\omega }_2$. The physics-based GITT and MLP surrogate workflow combines high-fidelity material–structure benchmarking with efficient metamodeling for design optimization, reliability assessment, and sensitivity-driven screening of Alumina–Steel AFG fluid-conveying pipes. Full article

This work examines how well a Negative Derivative Feedback (NDF) controller suppresses vibration in a nonlinear electromechanical oscillator that is subjected to mixed excitations. Coupled nonlinear ordinary differential equations are used to model the system and show how mechanical and electrical components interact. The method of multiple scales (MMS) is used to develop analytical approximate solutions up to the second order, specifically for the primary resonance scenario. This study’s main contribution is a thorough bifurcation analysis and proof of the NDF controller’s high efficacy, which effectively lowers the first and second mode resonance amplitudes by roughly $99.8\%$ and $98\%$., respectively, with impressive reported effectiveness values of roughly 590 and 51.5. Additionally, the quantitative error analysis between the numerical simulation and the analytical approximation solution demonstrates a high degree of agreement, with a maximum error of less than ${10}^{-5}\%$ for the second mode and just $0.01\%$ for the first mode. Furthermore, we present the impact of parameters on FRCs. Frequency response curves (FRCs) are used in a thorough comparison analysis to assess the behavior of the system both before and after the controller is activated. A strong degree of connection between the analytical conclusions and numerical simulations carried out using the “fourth-order Runge–Kutta method” rigorously validates the accuracy of the perturbation analysis. Additionally, a performance benchmark between different control techniques, such as the NDF controller, Positive Position Feedback (PPF), and Linear Negative Position Feedback (LNPF), is shown in the paper. When compared to alternative approaches, the NDF controller shows the greatest reduction in oscillation amplitudes and higher robustness, as shown by transient response analysis (time history) at various time intervals. The outcomes validate the NDF approach’s dependability and efficiency in stabilizing intricate nonlinear electromechanical systems. The chaotic response and system periodicity were demonstrated through bifurcation diagrams and Poincaré maps. Full article

A Negative Derivative Feedback (NDF) controller is designed for vibrations suppression of an atomic force microscope (AFM) model. The controlled system is modeled as a two-degree-of-freedom (2-DOF) closed-loop dynamic system. The average method was used to derive approximate analytical solutions. All possible resonance conditions were identified, with particular attention given to the simultaneous resonance case $\mathsf{\Omega }={\omega }_1, {\mathsf{\Omega }}_1={2\mathsf{\omega }}_1, {\mathsf{\omega }}_2={\mathsf{\omega }}_1$, identified as the most critical. For validation and proper insights, the system was also solved numerically using the fourth-order Rung–Kutta method. The time response of the AFM system in contact mode was analyzed before and after applying the NDF controller under the worst-case resonance conditions. A comprehensive parametric study was conducted to evaluate the controller’s robustness and effectiveness. The results demonstrate a high degree of agreement between the numerical simulations and the analytical approximations, confirming the reliability of the approach. Full article

The acceleration and deceleration of high-speed gas flow within a pipeline, induced by the action of flow-restriction devices, frequently result in the emergence of unsteady flow phenomena. Consequently, the generated excitation forces provoke intense vibrations in the pipeline, thereby substantially elevating the operational risks of the pipeline system. To mitigate such risks, the pipeline is typically subjected to fixed constraints to reduce vibration. A pipeline designed to simulate unsteady airflow was developed for the purpose of validating the vibration attenuation effect. Within this context, the effects of binding and friction constraints were compared through fluid–structure interaction simulation, and their respective mechanisms of action were analyzed individually. The results demonstrate that the constraints, in conjunction with the original pipeline, will result in a higher first-order natural frequency, which constitutes one of the primary methods for mitigating resonance effects. Both friction constraints and binding constraints significantly elevate the first-order natural frequency of the pipeline system, with binding constraints demonstrating higher efficiency. This phenomenon is attributable to the arch-like bending deformation observed in such experimental pipelines during first-order resonance, as binding constraints effectively maximize the restriction on pipeline strain. Through a comparative analysis of the time-domain and frequency-domain results of outlet pipe 1 before and after constraint application, it was observed that the axial RMS value of the constrained pipe decreased by 21.8%, while the radial value diminished by 33%. This finding further substantiates that imposing binding constraints at the location of maximum strain can elevate the pipe’s natural frequency by reducing both strain and the effective length of the “beam”, thereby significantly alleviating pipe vibrations induced by unsteady flow. Full article

The influence of debonding in concrete-filled steel tube (CFST) columns on the dynamic characteristics of super high-rise buildings is a common concern that remains insufficiently understood. The abnormal vibration incident of the SEG Plaza on 18 May 2021, also known as the 5·18 incident, serves as a typical case highlighting this issue. After two decades of service, the first-order bending frequency of the building decreased by approximately 6.1%, and extensive CFST column debonding was observed, with the maximum debonding rate reaching up to 97% on certain middle floors. To investigate the influence of CFST column debonding on structural dynamic characteristics, this study first derives a theoretical relationship between debonding parameters, namely angle and distance, and the equivalent bending stiffness of CFST columns. This analytical formulation is then implemented and validated through finite element simulations at multiple scales, including planar frame analysis in ABAQUS, a thin-interlayer simulation method in ANSYS, and full-building modeling in ETABS. Results show that for a planar frame, when a CFST column debonds at 270°, the structural natural frequency decreases by 0.984%; when the debonding angle is 180° with a 2 mm gap, the first-order frequency decreases by 0.141%. Numerical simulation of the SEG Plaza structural model predicts a reduction in the first-order frequency of 0.987% under the observed debonding conditions, confirming that debonding impairs force transmission, reduces structural stiffness, and alters natural frequencies. This study provides a mechanistic basis for evaluating stiffness degradation in long-service super high-rise buildings. Full article

Accurate spot-centroid localization is fundamental for determining optical metrics such as modulation transfer function (MTF) and effective focal length (EFL). Conventional methods struggle under non-ideal conditions—asymmetric spots, high noise, and vibration—and mid-wave infrared (MWIR) vibration has received little attention. To address these gaps, we propose multi-scale Gaussian fitting with subpixel edge reconstruction (MSGF-SER), combining image pyramid fitting, Zernike-moment edge extraction, and adaptive eccentricity-weighted fusion. Validated on simulated spots with varying SNRs and experimental sequences (visible off-axis aberration, long-wave infrared (LWIR) high-noise, MWIR micro-vibration), MSGF-SER achieved a noise-free RMSE of 0.03 pixel and 0.84 pixel at 5 dB SNR. On real MWIR vibration sequences, the Y-direction standard deviation (STD) dropped to 0.098 pixel, and the trajectory displacement variance was more than an order of magnitude lower than that of conventional methods. MTF deviations remained within 0.01, and the deviation of the measured mean EFL from the nominal focal length was better than 0.05 mm, and the STD was below 0.02 mm. These results demonstrate that MSGF-SER substantially improves centroid localization accuracy, repeatability, and smoothness under challenging conditions, providing reliable support for high-precision optical system parameter measurement. Full article