Search Results (254)

This paper presents a novel temperature compensation approach for dual-axis Micro–Electro–Mechanical System (MEMS) accelerometers, integrating Adaptive Mode Decomposition (AMD) with Grey Wolf Optimization (GWO) and Hybrid Convolutional–Recurrent Temporal Network (HCR-TN). The proposed method aims to address temperature-induced bias drift, which significantly affects accelerometer performance. Experiments were conducted across a temperature range from −40 °C to +60 °C to evaluate the effectiveness of the compensation algorithm. The results show considerable improvements in bias stability, with the compensation method successfully reducing temperature-induced drift across both axes. Additionally, the algorithm was tested under realistic conditions, including noise and mechanical disturbances, demonstrating its robustness in practical applications. These findings highlight the potential of the proposed method for enhancing the reliability and accuracy of MEMS accelerometers in real-world sensing environments. Full article

Additive manufacturing technologies are no longer limited to rapid prototyping but are increasingly used for low-volume production of functional end-use components. Among advanced AM techniques, HP Multi-Jet Fusion (MJF) stands out for its high precision and efficiency. Polyamides, thanks to their balanced mechanical and thermal properties, are commonly used as building materials in this technology. However, these materials are notoriously difficult to bond with conventional adhesives. This study investigates the shear strength of bonded joints made from two frequently used MJF materials—PA12 and glass-bead-filled PA12—using four different industrial adhesives. Experimental procedures were conducted according to ASTM standards. Specimens for single-lap-shear tests were fabricated on an HP MJF 4200 series printer, bonded using a custom jig, and tested on a Zwick-Roell Z250 electro-mechanical testing machine. Surface roughness of the adherends was measured with a 3D optical microscope to assess its influence on bonding performance. The polyurethane-based adhesive (3M Scotch-Weld DP620NS) demonstrated superior performance with maximum shear strengths of 5.0 ± 0.35 MPa for PA12 and 4.4 ± 0.03 MPa for PA12GB, representing 30% and 17% higher strength, respectively, compared to epoxy-based alternatives. The hybrid cyanoacrylate–epoxy adhesive (Loctite HY4090) was the only system showing improved performance with glass-bead-reinforced substrate (16.5% increase from PA12 to PA12GB). Statistical analysis confirmed significant differences between adhesive types (F_3,24 = 31.37, p < 0.001), with adhesive selection accounting for 65.7% of total performance variance. In addition to the experimental work, a finite element-based numerical simulation was performed to analyze the distribution of shear and peel stresses across the adhesive layer using Siemens Simcenter 3D 2406 software with the NX Nastran solver. The numerical results were compared with analytical predictions from the Volkersen and Goland–Reissner models. Full article

The electro-hydraulic hybrid system has emerged as a critical technology in new energy vehicles, owing to the remarkable power density and efficient energy regeneration capabilities of hydraulic technology, coupled with the high energy density of electric power. This system effectively enhances vehicle range and battery life. We developed an energy management strategy (EMS) for the electro-hydraulic hybrid system (EHHS) to ensure smooth energy conversion, while ensuring the full utilization of electrical and hydraulic energy within a reasonable and efficient range. To enhance the system’s overall performance, it is imperative to address pivotal technologies, including power coupling and energy management. In this research, the structure of an electro-hydraulic hybrid vehicle (EHHV) is classified, compared and discussed. The application of existing EHHVs is studied. Subsequently, an analysis and summary are conducted on the current status and development trends of EMSs and collaborative operation control strategies (COCSs), and a novel mechanical-electro-hydraulic power-coupled system (MEHPCS) is put forward that successfully converts mechanical, electrical, and hydraulic energy in performance. Simultaneously, other applications of the system are forecasted. Finally, some suggestions for the electro-hydraulic hybrid systems’ future development are made. This study can promote the development of sustainable transportation technologies. The system integrates mechanical engineering, control theory, and environmental science, enabling interdisciplinary methodological innovation. In addition, relevant studies provide data support for policy makers by quantifying energy consumption indicators. Full article

To address the pronounced asymmetry and strong nonlinearity exhibited by the tractor electro-hydraulic hitch system during lifting and lowering operations, this study proposes a distributed parameter identification method based on a dual-mode grey-box modelling approach. Following a mode decomposition strategy, the lifting and lowering processes are regarded as two independent subsystems. Benchmark transfer function models are established for each subsystem through theoretical derivation. Considering the nonlinear characteristics and unmodeled dynamics that cannot be accurately captured by the benchmark model, a long short-term memory (LSTM) neural network compensator is introduced to enhance the model performance. Ultimately, a series-compensated dual-channel grey-box model is established, which effectively integrates mechanistic interpretability with high modelling accuracy. Then, to cope with the high-dimensional and heterogeneous parameter space of the constructed grey-box structure, a distributed parameter identification framework is proposed. This framework employs a staged optimization process that combines the whale optimization algorithm (WOA) with the gradient descent (GD) method to efficiently identify the hybrid parameter set. The identified models are validated through bench experiments. The results show that the proposed grey-box models achieve root mean square errors (RMSEs) of 0.33 mm and 0.48 mm, and mean absolute errors (MAEs) of 0.24 mm and 0.40 mm for the lifting and lowering processes, respectively. Compared with a single transfer function model, the RMSE is reduced by 57.6% and 87.3%, and the MAE is reduced by 59.2% and 87.9%, respectively. The proposed method substantially improves the modelling accuracy of the electro-hydraulic hitch system, providing a reliable foundation for system characterization and the design of high-performance control strategies for tractor electro-hydraulic hitch systems. Full article

To address the problems of local optima and insufficient convergence accuracy in parameter identification of primary frequency regulation (PFR) for steam turbines, this paper proposed a hybrid identification method that integrated an Improved Bayesian Optimization (IBO) algorithm and an Improved Whale Optimization Algorithm (IWOA). By initializing the Bayesian parameter population using Tent chaotic mapping and the reverse learning strategy, employing a radial basis kernel function hyperparameter training mechanism based on the Adam optimizer and optimizing the Expected Improvement (EI) function using the Limited-memory Broyden–Fletcher– Goldfarb–Shanno with Bounds (L-BFGS-B) method, IBO was proposed to obtain the optimal candidate set with the smallest objective function value. By introducing a nonlinear convergence factor and the adaptive Levy flight perturbation strategy, IWOA was proposed to obtain locally optimized optimal solutions. By using the reverse-guided optimization mechanism and employing a fitness-oriented selection strategy, the optimal solution was chosen to complete the closed-loop process of reverse learning feedback. Nine standard test functions and the Proportional Integral Derivative (PID) parameter identification of the electro-hydraulic servo system in a 330 MW steam turbine were presented as examples. Compared with Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), Bayesian Optimization (BO) and Particle Swarm Optimization-Grey Wolf Optimizer (PSO-GWO), the Improved Bayesian Optimization-Whale Optimization Algorithm (IBO-WOA) proposed in this paper has been validated to effectively avoid the problem of getting stuck in local optima during complex optimization and has high parameter recognition accuracy. Meanwhile, an Out-Of-Distribution (OOD) Test based on noise injection had demonstrated that IBO-WOA had good robustness. The time constant identification of the steam turbine were carried out using IBO-WOA under two experimental conditions, and the identification results were input into the PFR model. The simulated power curve can track the experimental measured curve well, proving that the parameter identification results obtained by IBO-WOA have high accuracy and can be used for the modeling and response characteristic analysis of the steam turbine PFR. Full article

Understanding vehicle acceleration behavior during intersection departures is critical for advancing traffic safety, sustainable mobility, and intelligent transport systems. This study presents a high-resolution kinematic analysis of 714 vehicle departures from signalized intersections, encompassing straight crossings, left turns, and right turns, and involving a diverse sample of internal combustion engine (ICE), hybrid electric (HEV), and battery electric vehicles (BEV). Using synchronized Micro Electro-Mechanical Systems (MEMS) accelerometers and Real-Time Kinematic (RTK)-GPS systems, the study captures longitudinal acceleration and velocity profiles over fixed distances. Results indicate that BEVs exhibit significantly higher acceleration and final speeds than ICE and HEV vehicles, particularly during straight crossings and longer left-turn maneuvers. Several mathematical models—including polynomial, arctangent, and Akçelik functions—were calibrated to describe acceleration and velocity dynamics. Findings contribute by modeling jerk and delay propagation, supporting better calibration of AV acceleration profiles and the optimization of intersection control strategies. Moreover, the study provides validated acceleration benchmarks that enhance the accuracy of forensic engineering and road accident reconstruction, particularly in scenarios involving intersection dynamics, and demonstrates that BEVs accelerate more rapidly than ICE and HEV vehicles, especially in straight crossings, with direct implications for traffic simulation, ADAS calibration, and urban crash analysis. Full article

This study presents the mechanical design and analysis of a quantum electro-optical transducer engineered to operate at millikelvin temperatures within a dilution refrigerator. The transducer enables bidirectional microwave-optical frequency conversion through a hybrid architecture that integrates a superconducting radiofrequency (SRF) cavity with an electro-optic optical cavity. Among several design options investigated, the configuration offering the best thermal and mechanical performance was selected, yielding a robust solution with reduced sensitivity to fabrication tolerances, improved heat dissipation, as well as alignment precision. The design ensures uniform temperature distribution, enabling higher laser pump powers and, thus, increased conversion efficiency, while maintaining mechanical stresses safely below the material yield strength. Electromagnetic simulations further validate the design, demonstrating enhanced coupling between the optical and microwave modes, as well as a broader tuning range achieved with smaller tuner displacements. Full article

This paper presents a comprehensive comparative analysis of high-voltage, high-frequency pulse generation techniques for Pockels cell drivers. These drivers are critical in electro-optic systems for laser modulation, where nanosecond-scale voltage pulses with amplitudes of several kilovolts are required. The study reviews key design challenges, with particular emphasis on thermal management strategies, including air, liquid, solid-state, and phase-change cooling methods. Different high-voltage, high-frequency pulse generation architectures including vacuum tubes, voltage multipliers, Marx generators, Blumlein structures, pulse-forming networks, Tesla transformers, switching-mode power supplies, solid-state switches, and high-voltage operational amplifiers are systematically evaluated with respect to cost, complexity, stability, and their suitability for driving capacitive loads. The analysis highlights hybrid approaches that integrate solid-state switching with modular multipliers or pulse-forming circuits as offering the best balance of efficiency, compactness, and reliability. The findings provide practical guidelines for developing next-generation high-performance Pockels cell drivers optimized for advanced optical and laser applications. Full article

As water pollution from dyes, pharmaceuticals, heavy metals, and other emerging contaminants continues to rise at an alarming rate, ensuring access to clean and safe water has become a pressing global challenge. Conventional water treatment methods, though widely used, often fall short in effectively addressing these complex pollutants. In response, researchers have turned to Advanced Functional Membranes (AFMs) as promising alternatives, owing to their customizable structures and enhanced performance. Among the most explored AFMs are those based on metal–organic frameworks (MOFs), carbon nanotubes (CNTs), and electro–catalytic systems, each offering unique advantages such as high permeability, selective pollutant removal, and compatibility with advanced oxidation processes (AOPs). Notably, hybrid systems combining AFMs with electrochemical or photocatalytic technologies have demonstrated remarkable efficiency in laboratory settings. However, translating these successes to real-world applications remains a challenge due to issues related to cost, scalability, and long-term stability. This review explores the recent progress in AFM development, particularly MOF-based, CNT-based, and electro-Fenton (EF)-based membranes, highlighting their material aspects, pollutant filtration mechanisms, benefits, and limitations. It also offers insights into how these next-generation materials can contribute to more sustainable, practical, and economically viable water purification solutions in the near future. Full article

In recent years, one of the major problems facing humanity has been the contamination of the environment by various organic pollutants, with some of them exhibiting environmental persistence or pseudo-persistence. For this reason, it is necessary today, more than ever, to find new and effective methods for degrading these persistent pollutants. Transition metal selenides (TMSes) have emerged as a versatile and promising class of catalysts for the degradation of organic pollutants through various advanced oxidation processes (AOPs). The widespread use of these materials lies in the desirable characteristics they offer, such as unique electronic structures, narrow band gaps, high electrical conductivity, and multi-valent redox behavior. This review comprehensively examines recent progress in the design, synthesis, and application of these TMSes—including both single- and composite systems, such as TMSes/g-C₃N₄, TMSes/TiO₂, and heterojunctions. The catalytic performance of these systems is being highlighted, regarding the degradation of organic pollutants such as dyes, pharmaceuticals, antibiotics, personal care products, etc. Further analysis of the mechanistic insights, structure–activity relationships, and operational parameter effects are critically discussed. Emerging trends, such as hybrid AOPs combining photocatalysis with PMS or electro-activation, and the challenges of stability, scalability, and real wastewater applicability are explored in depth. Finally, future directions emphasize the integration of multifunctional activation methods for the degradation of organic pollutants. This review aims to provide a comprehensive analysis and pave the way for the utilization of TMSe catalysts in sustainable and efficient wastewater remediation technologies. Full article

Among various failure causes, lightning overvoltage represents the most significant threat to overhead distribution lines, which serve as critical components in power systems. This study uses the hybrid partial element equivalent circuit (PEEC) multi-conductor transmission line (MTL) method to perform overvoltage simulations and investigate lightning risk distribution along distribution lines developed from a real 10 kV distribution networks in Guizhou, China. The results of the rocket-triggered lightning observation verify the accuracy of the hybrid method for direct lightning simulation. Combining the Monte Carlo method with the electro-geometric model (EGM), the impact of differential protection configurations on annual lightning flashover rates is analyzed. The results demonstrate that lightning strikes on phase wires generate high-magnitude overvoltages but with limited spatial influence, resulting in fewer pole flashovers. Conversely, strikes on poles produce lower overvoltage peaks but affect wider areas, leading to significantly more flashovers. Using annual flashover rates as the risk evaluation metric, the line topologies into high-risk, medium-risk, and other low-risk areas are classified. Targeting an annual flashover rate below 0.4 as the design objective, the configuration schemes of the arresters are progressively optimized. This risk-based approach provides an effective reference framework for differential protection design of distribution line safeguards. Full article

A series of experiments were carried out to evaluate different anti-/de-icing approaches for a Pitot probe. Using the Iowa State University Icing Research Tunnel (ISU-IRT), this study compared the performance of a traditional electrically heated system with that of a hybrid concept combining reduced-power electrical heating and a superhydrophobic surface (SHS) coating. The effectiveness and energy efficiency of both methods were assessed. High-speed imaging was employed to capture the transient ice accretion and removal phenomena on the probe model under a representative glaze icing condition, while infrared thermography provided surface temperature distributions to characterize the unsteady heat transfer behavior during the protection process. Results indicated that, due to the placement of the internal resistive heating elements, ice deposits on the total pressure tube were easier to shed than those on the supporting structure. Relative to the conventional approach of maintaining a fully heated probe, the hybrid technique achieved comparable anti-/de-icing performance with substantially reduced power requirements—showing up to ~50% savings during anti-icing operation and approximately 30% lower energy use with 24% faster removal during de-icing. These findings suggest that the hybrid strategy is a promising alternative for improving Pitot probe icing protection. Full article

Electromagnetic micro-electro-mechanical system (MEMS) micromirrors are widely used in optical scanning systems but often encounter mechanical crosstalk due to the use of shared drive coils. This phenomenon leads to parasitic motion along the slow axis during fast-axis operation, resulting in undesirable elliptical scanning patterns that degrade image quality. To tackle this issue, a hybrid actuation scheme is proposed in which a piezoelectric actuator drives the fast axis through an S-shaped spring structure, achieving a resonance frequency of 792 Hz, while the slow axis is independently driven by an electromagnetic actuator operating in quasi-static mode. Finite element simulations and experimental measurements validate that the proposed decoupled design significantly suppresses mechanical crosstalk. When the fast axis is driven to a 40° optical scan angle, the hybrid system reduces the parasitic slow-axis deflection (typically around 1.43°) to a negligible level, thereby producing a clean single-line scan. The piezoelectric fast axis exhibits a quality factor of Q = 110, while the electromagnetic slow axis achieves a linear 20° deflection at 20 Hz. This hybrid design facilitates a distortion-free field of view measuring 40° × 20° with uniform line spacing, presenting a straightforward and effective solution for high-precision scanning applications such as LiDAR (Light Detection and Ranging) and structured light projection. Full article

In order to solve a certain type of Electro-Hydrostatic Actuators (EHA) hydraulic cylinder small cavity buffer end impact problem, based on AMESim to establish a hydraulic cylinder small cavity buffer machine–hydraulic joint simulation model. First, four important structural parameters, namely, the fitting clearance G of the buffer sleeve and buffer hole, the fixed orifice D, the wedge face angle $\theta$, and the wedge face length L₁ were selected to analyze their influence on the pressure of the buffer chamber and the end speed of the piston. Second, enhanced Social Behavior Optimization (SBO) was used to optimize the back-propagation neural network (BP) model to construct a prediction model for the buffer time T of the small chamber of the hydraulic cylinder, the end-piston speed V_e, the rate of change of the end-piston speed V_r, and the return speed of the hydraulic oil V_h. The SBO–BP model performed well in several key performance evaluation metrics, showing better prediction accuracy and generalization performance. Finally, the multi-objective Non-dominated Sorting Genetic Algorithm II (NSGA-II) was used to optimize the hydraulic cylinder small-cavity buffer structure using the multi-objective NSGA-II with the objectives of the shortest buffer time, the minimum end-piston speed, the minimum change rate of the end-piston speed, and the minimum hydraulic oil reflux speed. The optimized design reduced the piston end speed from 0.060 m/s to 0.032 m/s, corresponding to a 46.7% improvement. The findings demonstrate that the proposed hybrid optimization approach effectively alleviates the end-impact problem of EHA small-cavity buffers and provides a novel methodology for achieving high-performance and reliable actuator designs. Full article

Micro-accelerometers are in high demand across many due to their compact size, low energy consumption, and excellent precision. Since gravity causes a large movement when the device is positioned vertically, measuring low gravitational acceleration is challenging. This study examines the intrinsic relationship between applied voltage levels and displacement in micro-accelerometers. The study introduces a novel design that integrates hybrid flexures, comprising both linear and angular configurations, with an out-of-plane overlap varying (OPOV) electrostatic actuation mechanism. This design aims to measure the micro-accelerometer’s movement and low frequency response. The proposed device with silicon material is designed and simulated using the IntelliSuite^® software, considering its small dimensions and 25 µm thickness. The norm value of 28.0916 μN from gravity’s reaction forces on the body, a resonant frequency of 179.668 Hz at the first desired mode, and a maximum stress of 24.7 MPa were obtained through the electro-mechanical analysis. A comparison of the proposed design was conducted with other configurations, measuring a frequency of 179.668 Hz at a minimum downward displacement of 7.69916 µm under the influence of gravity without electrostatic mechanisms. Following this, an electrostatic actuation mechanism was introduced to minimize displacement by applying different voltage levels, including 1 V, 1.5 V, and 3 V. At 3 V, a significant improvement in displacement reduction was observed compared to the other applied voltages. Additionally, dynamic and sensitivity analyses were carried out to validate the performance of the proposed design further. Full article