Search Results (1,830)

The vertical landing of quadrotor unmanned aerial vehicles (UAVs) involves highly transient impact dynamics that generate significant vibrations on the UAV body, particularly under uncertain touchdown conditions such as uneven terrain, asymmetric ground contact, and high-impact landing. In this study, a robust semi-active vibration control framework is proposed for a quadrotor UAV equipped with a four-point soft landing gear system. The UAV is modeled as a three-degree-of-freedom rigid body including heave, pitch, and roll motions, while each landing gear leg is represented by an equivalent spring-damper mechanism with adaptively controllable damping characteristics. To evaluate the effectiveness of the proposed framework, PID (Proportional–Integral–Derivative), GA-PID (Genetic Algorithm-Based Proportional–Integral–Derivative), Fuzzy–PID (Fuzzy Logic-Based Proportional–Integral–Derivative), and ANFIS-PID (Adaptive Neuro-Fuzzy Inference System-Based Proportional–Integral–Derivative) controllers are comparatively investigated under five different landing scenarios. The nonlinear touchdown dynamics are implemented in the MATLAB/Simulink environment using a state-space-based simulation model. The results demonstrate that intelligent adaptive control methods significantly improve landing stability and vibration attenuation compared to the conventional PID controller. Among all methods, the ANFIS-PID controller achieved the best overall performance. Under the most severe landing condition, the peak vertical displacement was reduced from 0.114 m to 0.025 m, while the maximum pitch and roll angles decreased from approximately 11° to nearly 2°. Additionally, the settling time was reduced from nearly 10 s to below 3 s. Full article

Although foamed lightweight soil is widely used for its light weight and high strength, its insufficient dynamic performance under cyclic loading and the poorly understood reinforcement mechanism have become key bottlenecks restricting its optimized application. To investigate the dynamic characteristics and influencing factors of geogrid-reinforced foamed lightweight soil (GRFLS), laboratory dynamic triaxial tests were conducted using a DJSZ-100D dynamic–static triaxial testing system. The effects of the number of geogrid layers and wet density on the dynamic mechanical properties were examined, with analysis focused on failure patterns, backbone curves, dynamic strength, dynamic shear modulus, and damping ratio. The results indicate that the inclusion of geogrids effectively restrained the propagation of longitudinal cracks in the foamed lightweight soil. The hyperbolic backbone curves were well characterized by the Hardin–Drnevich model. An increase in wet density significantly enhanced the dynamic strength, and an optimal number of two reinforcement layers was identified based on the reinforced strength–stress ratio. The dynamic elastic modulus and damping ratio of GRFLS increased with growing dynamic strain. Compared with the unreinforced condition, the initial dynamic elastic modulus of the specimens with two geogrid layers increased by an average of 15.6%, and the maximum damping ratio increased by an average of 12.9%. While both geogrid reinforcement and higher wet density effectively increased the dynamic elastic modulus, only an increase in wet density notably improved the damping ratio. Finally, predictive models for the enhanced dynamic elastic modulus and damping ratio, which incorporate wet density and the number of reinforcement layers, were established. These models indirectly reflect the dynamic deviator stress–strain relationship of GRFLS. This study provides a theoretical basis for engineering construction. Full article

To reveal the nonlinear instability mechanism by which the three-degree-of-freedom rotor system of a magnetic-liquid double suspension bearing transforms from stable suspension to periodic vibration, a nonlinear dynamic model considering electromagnetic suspension force, hydrostatic supporting force, rotor unbalance force, and liquid film resistance is established. The equilibrium point of the system is linearized, and the Hopf bifurcation boundary is determined using the Routh–Hurwitz criterion. Numerical simulations are then carried out to investigate the effects of the initial current i₀, supply flow rate q₀, and different initial disturbances on the displacement time histories, phase trajectories, and spatial phase trajectories of the rotor. The results show that, under the given system parameters, the Hopf bifurcation boundary is 0.61 A for the initial current and 9.62 × 10⁻⁵ m³/s for the supply flow rate. Current variation mainly affects electromagnetic stiffness and nonlinear electromagnetic force, whereas flow rate variation primarily changes the hydrostatic load capacity and oil film damping characteristics. Under different initial disturbances, the system may exhibit amplitude attenuation, recovery to stable suspension, or finite amplitude periodic vibration. Experimental results show good agreement with numerical simulations in terms of frequency spectra, displacement time histories, and phase trajectories, thereby verifying the effectiveness of the proposed three-degree-of-freedom dynamic model and Hopf bifurcation analysis method. The results can provide theoretical guidance for parameter matching, stability evaluation, and self-excited vibration suppression of magnetic-liquid double suspension bearings. Full article

Autonomous navigation of a vehicle in an environment where there are obstacles is difficult due to low onboard sensing technology, high measuring noise, and external interference, which collectively result in poor tracking performance of the vehicle’s trajectory and compromise safety. In this paper, a UAV-assisted Distributed Sliding Mode Control (DSMC) is proposed to robustly and safely implement path tracking for autonomous ground vehicles (AGVs). The proposed system utilizes an aero-sensor layer for enhanced perception, such as obstacle sensing, reference path preview, and look-ahead trajectory information, and it shares this information with the vehicle via wireless communication. The fundamental scheme, called DSMC, is based on a conventional Sliding Mode Control (SMC) technique and uses UAV preview-based feedback. This allows anticipation of control actions to enhance tracking performance and achieve more timely, smoother obstacle avoidance than baseline SMC. The proposed method is designed to overcome the limitations of traditional SMC strategies, such as chattering and poor responsiveness. The proposed method features continuous nonlinear approximation and damping mechanisms to reduce chattering and improve response characteristics, thereby enhancing stability and reducing oscillations. Strict safety enforcement through constraint is always achieved by keeping the vehicle and obstacles separated by a minimum distance only; that is, a minimum distance is always guaranteed: a Constraint Barrier Function (CBF)-based constraint is used. By combining UAV-assisted perception with DSMC and CBF the system can guarantee its formal safety in the presence of disturbances and sensing uncertainties while maintaining accurate trajectory tracking. Based on our simulation results, the proposed UAV-assisted DSMC method is shown to be significantly superior to conventional SMC and Model Predictive Controller (MPC) in terms of tracking accuracy, control smoothness, and adherence to the safety margin. Our simulation results demonstrate that the proposed method significantly outperforms conventional SMC and MPC control. Specifically, it achieves a 22.9% reduction in RMSE (0.135 m vs. 0.175 m) and 63% lower mean control effort, and it strictly maintains the minimum safety distance under both static and dynamic obstacles. The algorithm runs in real-time with an average execution time of 1.85 ms (>200 Hz), making it highly suitable for embedded deployment. These results highlight the effectiveness of combining UAV-assisted preview, adaptive robust control, and formal safety constraints for reliable autonomous navigation in complex environments. Full article

Copper (Cu) thin films and meshes on polyethylene terephthalate (PET) substrates are promising flexible transparent conductive electrodes (TCEs), yet their practical use is limited by insufficient interfacial adhesion and poor oxidative stability on inert polymer substrates. This work addresses these issues via a synergistic strategy of interfacial layer engineering and maskless laser lithography-based aperiodic mesh patterning, systematically comparing ceramic (Al₂O₃) and metallic (NiCr) interfacial layers for PET-supported Cu films and fabricating Linear/Sinusoidal aperiodic Cu meshes with tailored performance. Magnetron sputtering shows that Ar plasma-activated NiCr interfacial layers form a gradient-alloyed interface with Cu via interdiffusion, achieving 5B-level adhesion, mitigating bending-induced stress concentration, and enhancing damp-heat resistance (85 °C/85% RH) by suppressing oxidation—outperforming brittle Al₂O₃ layers. Patterning the optimized Cu/NiCr/PET structure into micrometer-scale meshes yields a Linear design with superior optoelectronic performance (~10.8 Ω/sq sheet resistance, >87% transmittance at 550 nm) and a Sinusoidal design with enhanced bending robustness via stress delocalization. Microstructural and elemental analyses clarify the NiCr layer’s interfacial toughening and anti-oxidation mechanisms. Practical validation in flexible transparent heaters demonstrates rapid thermal response and >20 h continuous operational stability. This study provides a scalable design strategy for high-performance PET-supported Cu meshes, offering insights for interface and structural optimization of flexible metallic TCEs for next-generation optoelectronics. Full article

In this study, the development of a novel machine mount utilizing an advanced polymer composite and porous materials is presented. Initially, a preliminary evaluation of the proposed materials was conducted, focusing on their static mechanical properties and their dynamic properties, and assessed through loading–unloading cycles and Dynamic Mechanical Thermal Analysis (DMTA). All tests were performed at the coupon scale, with specimens manufactured via Fused Filament Fabrication (FFF). Subsequently, a conceptual design incorporating the proposed materials was developed, and functional prototypes were fabricated using multi-material additive manufacturing techniques. The structural integrity of the prototypes was evaluated by analyzing their oscillatory response and damping behavior under laboratory-scale conditions, with transmissibility metrics extracted to quantify performance. The results indicate that all three prototypes exhibit adequate damping for machine mounting applications, ranging between 5% and 20%, with the porous variant demonstrating the highest damping performance (20.9%). In terms of load-bearing capacity, the porous configuration withstood loads up to 10 kN, while the standard TPU variant sustained up to 20 kN. The carbon-fiber-reinforced configuration exhibited the highest mechanical performance, tolerating loads up to 50 kN without significant structural failure. Full article

With the increased application of porous asphalt, the recycling and reutilization of aged materials have become a critical issue for sustainable pavement engineering. This study investigates the evolution of the performance characteristics of porous asphalt mixtures under high-temperature heating conditions, with the aim of providing a theoretical basis for hot in-place recycling (HIR) technology in the rehabilitation of porous asphalt pavements. The heating states of asphalt, mortar and mixtures in HIR were simulated using controlled oven heating. Their microscopic, mechanical and thermal properties were evaluated under different aging conditions and with the incorporation of different rejuvenators. The results show that asphalt aging intensifies with the increasing heating temperature and time. The incorporation of bio-based rejuvenators significantly alleviates aging effects and demonstrates superior performance compared to conventional rejuvenators. Furthermore, aggregates and rejuvenators enhance the thermal conductivity of materials, while aging reduces the thermal conductivity coefficient and increases the risk of temperature gradient diseases. The rheological properties of asphalt are closely related to the degree of aging. While aging mitigation improves low-temperature cracking resistance and acoustic damping performance, it may compromise high-temperature deformation resistance. In conclusion, to achieve an optimal balance between performance recovery and aging control, it is recommended that the HIR of porous asphalt pavements be conducted at a heating temperature of 180 °C for 5 min, with the addition of 3% bio-based rejuvenator. Full article

In this paper, we address shaft oscillations and grid-connected oscillation frequency coupling in doubly fed induction generators (DFIGs) under DC-link dynamics. A comprehensive DFIG shaft system model incorporating DC-link dynamics is established, and frequency coupling is analyzed. From our findings, we reached the following conclusions: (a) DC-link voltage fluctuations alter electromagnetic torque through rotor-side converter (RSC) and grid-side converter (GSC) coupling, affecting shaft dynamics; (b) DC-link dynamics compromise grid connection stability by influencing both GSC and RSC output voltages. To mitigate these effects, a DC-link dynamics suppression module is proposed. Simulations confirm that in maximum power point tracking (MPPT) mode, the module enhances electrical positive damping and improves shaft stability. In constant power mode, its stabilizing effect is comparatively limited. The suppression module effectively mitigates grid-connected frequency coupling during DC-link voltage fluctuations. Full article

Two-stage grid-forming (GFM) photovoltaic inverters leverage the dynamic characteristics of the DC-bus capacitor to emulate the inertia of synchronous generators. However, under conditions of drastic solar irradiance fluctuations or sudden increases in grid load, fixed virtual inertia parameters struggle to simultaneously ensure both effective grid frequency support and stable DC-bus voltage, often leading to DC voltage dips or even system disconnection. To address this issue, this paper proposes an adaptive virtual inertia control strategy that takes into account the dynamic resources on the DC side. First, based on the dynamics of the DC-bus voltage, the synchronous equations for the inverter are derived, and a quantitative mapping relationship between the control parameters and the virtual inertia, as well as the damping coefficient, is established. Second, an inertia control law that adaptively adjusts according to the photovoltaic output power is designed. When solar irradiance is abundant, the virtual inertia is increased to provide sufficient frequency support, and vice versa. At the same time, a damping coordination mechanism with power-difference feedforward is introduced, which enhances the system’s dynamic response under complex operating conditions. Verification using the PLECS RT-Box hardware-in-the-loop (HIL) experimental platform demonstrates that, compared to the conventional fixed-parameter control, the proposed strategy effectively suppresses DC-bus voltage dips during sudden changes in solar irradiance, thereby avoiding undervoltage protection trips. Under load-transient conditions, the strategy dynamically adjusts the inertia response based on the photovoltaic output status, achieving a balance between transient system stability and grid friendliness. Full article

A high quality factor, denoted as the Q-factor, is crucial for micromachined disk resonator gyroscopes, commonly referred to as DRGs, to suppress thermomechanical noise and improve bias stability. However, the coupled energy dissipation mechanisms under low-pressure conditions impose significant limitations on further Q-factor enhancement. This paper establishes a rigorous multiphysics damping analysis framework for DRGs and quantitatively investigates the contributions of air damping, thermoelastic damping, and anchor loss. A free-molecular squeeze-film damping model is derived based on kinetic gas theory and molecular energy transfer mechanisms, avoiding the continuous fluid assumption of the classical Reynolds equation, which fails in low-pressure regimes. Due to the highly symmetric ring structure and central anchor design, finite element method simulations reveal an extremely high anchor-loss-limited quality factor, Q_anchor, of approximately 1.85 × 10¹², indicating negligible anchor-induced dissipation. Under an operating pressure of 0.1 Pa, air damping is validated as the absolute dominant energy dissipation mechanism with a gas quality factor, Q_air, of approximately 1.105 × 10⁵, which is significantly lower than the thermoelastic damping quality factor, Q_TED, evaluated at 8.98 × 10⁵. To break the classical trade-off between squeeze-film damping suppression and capacitive drive efficiency, a decoupled gap optimization strategy is proposed. By maintaining the drive electrode gap, gap_e, at 7.2 µm while increasing only the parasitic ring-to-suspended-mass gap, gap_m, to 12 µm, the squeeze-film-damping-limited Q-factor is improved by approximately 25% to 1.381 × 10⁵ without degrading electromechanical coupling efficiency. In addition, the optimal anchor radius is determined to be approximately 160 µm. The proposed framework provides practical design guidance for high-Q DRGs and other MEMS resonant inertial sensors. Full article

As the core sensor of inertial measurement units, the reliability of Micro-Electro-Mechanical Systems (MEMS) gyroscopes is critical for long-term navigation and motion control applications. To bridge the mechanism-data gap in MEMS multi-mechanism degradation modeling, this paper proposes a physics-informed dual-indicator reliability assessment framework based on Wiener processes. Two degradation indicators under consideration are frequency-related degradation caused by stiffness degradation and Q-factor degradation caused by damping degradation, for which corresponding physics-embedded stochastic degradation models are formulated. The two indicators are normalized and fused through a generalized weighted limit state function, where failure is defined as gyroscope-level performance failure. Closed-form reliability expressions are derived for linear limit states, while Monte Carlo simulation is used for nonlinear cases. Reduced-order multiphysics simulation cases, including a double-ended fixed beam and a cantilevered MEMS mass block, are used to demonstrate the mechanism-to-indicator-to-reliability modeling procedure. The results show that the proposed dual-indicator framework provides more balanced reliability assessment than single-indicator analysis under the simulation setting. The proposed method offers an alternative mechanism-informed approach for reliability analysis and lifetime prediction of other MEMS devices. Full article

Micro quadrotor unmanned aerial vehicles (UAVs) are highly sensitive to external disturbances and model uncertainties because of their small mass, low moment of inertia, and limited onboard computational resources. To improve the disturbance rejection and trajectory tracking performance of micro quadrotor UAVs, this paper proposes an event-triggered extended state observer (ET-ESO)-based prescribed-time funnel control (PTFC) method. First, a control-oriented dynamic model of the micro quadrotor is established, in which wind disturbances, unmodeled aerodynamic effects, damping uncertainties, and parameter perturbations are represented as lumped disturbances in the translational and rotational subsystems. Then, two event-triggered ESOs are designed to estimate the lumped disturbances of the velocity and angular velocity channels. Compared with conventional continuously sampled ESO schemes, the proposed event-triggered mechanism reduces the frequency of sensor-to-controller information transmission while preserving disturbance estimation capability. Furthermore, a prescribed-time funnel control law is developed to constrain the position and attitude tracking errors within predefined performance boundaries and ensure convergence to the desired accuracy region within a user-specified time. Lyapunov-based stability analysis is provided to prove the boundedness of all closed-loop signals and the validity of the prescribed funnel constraints. Finally, MATLAB/Simulink simulations based on the Parrot Mambo mini-drone parameters are conducted to verify the effectiveness of the proposed method. The results demonstrate that the proposed controller achieves robust trajectory tracking, effective disturbance compensation, improved transient performance, and reduced control update frequency. Full article

This study investigates broadband vibration and mechanical shock mitigation for an aluminum (AlSi10Mg) battery pack casing by integrating mechanical metamaterial wall modifications and add-on damping structures. A 12.432 kWh underbody-type casing is designed. Two wall architectures, i.e., the star-triangular honeycomb (STH) and a novel hybrid auxetic (NHA), are implemented on three walls (top, front, and rear) of the battery pack casing. A mechanical damping (DSMS) and three biomimetic damping concepts (BWBIS, BPPIS and BBIGPS) are further compared. All designs are evaluated through simulation using random vibration analysis based on ISO 12405-2 standard, followed by shaker-based shock and random vibration experiments. Simulations show that both modified casings suppress the casing vibration by approximately ${10}^2$–${10}^6$ relative to the solid casing, and their dominant peaks shift to above 150 Hz. The NHA casing provides higher overall vibration mitigation than the STH casing (98.07% longitudinal, 95.09% vertical, and 93.60% transverse versus 97.64%, 94.00%, and 91.51%). Thus, the NHA casing is selected for fabrication. In addition, BPPIS and BBIGPS outperform BWBIS and DSMS, and thus, BPPIS is selected for fabrication due to its simpler geometry and lower mass. Experimentally, the solid-BPPIS configuration achieves the most robust random vibration attenuation across all measurement points, with average root mean square (RMS) reductions of 26.82% (vertical), 87.34% (longitudinal), and 83.60% (transverse). Shock tests reveal strong direction dependence; adding damping structures improves longitudinal and transverse shock mitigation, while vertical shock mitigation remains limited. The results provide design-level guidance on selecting wall architectures and damping layouts for practical vibration and shock protection of electric vehicle (EV) battery pack casings. Full article

Rockfall from slope unstable rock masses is a typical geological hazard induced by brittle failure, with abrupt occurrence, limited macroscopic deformation before failure, and a short warning lead time. Conventional static analysis methods are useful for design-stage stability checks, but they cannot continuously capture structural-plane damage or update the stability state in real time. Dynamic evaluation based on structural dynamics links measurable parameters such as natural frequency, damping ratio, mode shape, vibration trajectory, wave velocity, and energy dissipation to the degradation of structural planes. This review synthesizes the dynamic behavior mechanism, parameter system, theoretical models, sensing technologies, and engineering applications for slope unstable rock masses. Different from previous reviews that mainly summarize rockfall monitoring or conventional slope stability analysis, this paper organizes the literature by failure mode, monitoring scale, model assumptions, field validation, uncertainty sources, and engineering applicability. The single-degree-of-freedom models for sliding-, toppling-, and falling-type rock masses, multi-block chain-collapse models, and data-physics dual-driven surrogate models are compared critically. Contact monitoring based on MEMS sensors, non-contact LDV monitoring, acoustic emission, microseismic monitoring, coda wave interferometry, and cloud-edge early-warning architectures are further reviewed. Key challenges include field-scale validation under heterogeneous and anisotropic geological conditions, environmental compensation, robust threshold calibration, and probabilistic linkage between dynamic indicators and failure probability. The review provides guidance for selecting dynamic evaluation models, designing field monitoring systems, and developing full-life-cycle digital-twin platforms for rockfall risk mitigation. Full article

The study is driven by its importance in modern material processing and precision engineering, where understanding and controlling interfacial stability is crucial in maintaining reliable performance across various operating conditions. The interplay between the tangential magnetic field and temporal periodicity generates additional mechanisms of mode coupling and amplifies instability. These observations address critical shortcomings in nonlinear stability theory and suggest practical uses in flow regulation and the control of conductive fluids. The fluids are assumed as Eyring–Powell non-Newtonian and flow with uniform velocities through porous media. The analysis is conducted using a non-perturbative method that relies mainly on He’s frequency formulation. To facilitate the mathematical treatment, viscous potential theory is adopted. The governing linear partial differential equations describing the flow are then solved under nonlinear boundary conditions, resulting in a nonlinear characteristic equation that represents the displacement of the interface. A non-dimensional procedure is then applied to extract the key dimensionless physical parameters influencing the system behavior. A set of graphical results is provided to demonstrate how the system’s stability behavior is influenced by changes in the key dimensionless physical parameters. The validation of the innovative process is achieved using Mathematica Software. The study considers both uniform and periodically varying magnetic fields, and the associated stability conditions are evaluated for each case, where the impacts of various non-dimensional attributes are assessed. As density ratio increases, it stabilizes periodic magnetic fields while destabilizing uniform ones. A stronger MF enhances magnetic damping, reducing instability regions and promoting stable periodic interfacial motion. Enhanced conductivity improves Magnetohydrodynamic interactions, resulting in greater energy dissipation and stability. Full article