Search Results (6,518)

The development of alternative transportation methods has become paramount in the context of sustainable urban population connectivity. The promise of hyperloop as a high-speed, low-emission travel means motivates both academic and industrial interests. The present work centers on the design of hyperloop levitation systems. A component-level optimization is outlined for the appropriate selection of levitation module geometric parameters, followed by an integration into a capsule and bogie system. Two heteropolar levitation module types are numerically studied in realistic operating conditions: a hybrid electromagnet configuration with permanent magnets and a fully active one. To give means for comparison, both configurations are designed with the aid of a general multi-objective optimization approach. For the hybrid case, a position controller is synthesized with a zero-power policy and a specific frequency response function. The active configuration features comparable behavior. Two main power consumption streams are considered: gap control and magnetic drag. While the former depends on the position control effort, the latter depends on the losses of ferromagnetic elements. The two systems are compared in smooth and irregular track conditions over the studied speed range of 400–700 km/h. This study demonstrates that the hybrid heteropolar case achieves a minimum of 97.6% in specific power consumption reduction at the maximum speed of 700 km/h under smooth track conditions. Under irregular track conditions, a benefit in average specific consumption reduction is noted up to 662 km/h for the hybrid case. The maximum reduction in specific consumption is 57.2% at the minimum speed of 400 km/h. Full article

This study examines the upper-ocean response to Typhoon Khanun, which traversed the northern South China Sea in October 2017, by integrating multi-satellite observations with numerical simulations from the Regional Ocean Modeling System (ROMS). For the ROMS simulations, an Arakawa C-grid was adopted with a 4-km horizontal resolution and 40 vertical terrain-following $\sigma$-layers, covering the domain of 105° E to 119° E and 15° N to 23° N. Typhoons significantly influence ocean dynamics, altering sea surface temperature (SST), sea surface salinity (SSS), and ocean currents, thereby modulating air–sea exchange processes and marine ecosystem dynamics. High-resolution satellite datasets, including GHRSSST for SST, SMAP for SSS, GPM IMERG for precipitation, and GLORYS12 for sea surface height, were combined with ROMS simulations configured at a 4-km horizontal resolution with 40 vertical layers to analyze ocean changes from 11 to 18 October 2017. The results show that Typhoon Khanun induced substantial SST cooling, with ROMS simulations indicating a maximum decrease of 1.94 °C and satellite data confirming up to 1.5 °C, primarily on the right side of the storm track due to wind-driven upwelling and vertical mixing. SSS exhibited a complex response: nearshore regions, such as the Beibu Gulf, experienced freshening of up to 0.1 psu driven by intense rainfall, while the right side of the storm track showed a salinity increase of 0.6 psu due to upwelling of saltier deep water. Ocean currents intensified significantly, reaching speeds of 0.5–1 m/s near coastal areas, with pronounced vertical mixing in the upper 70 m driven by Ekman pumping and wave-current interactions. By effectively capturing typhoon-induced oceanic responses, the integration of satellite data and the ROMS model enhances understanding of typhoon–ocean interaction mechanisms, providing a scientific basis for risk assessment and disaster management in typhoon-prone regions. Future research should focus on refining model parameterizations and advancing data assimilation techniques to improve predictions of typhoon–ocean interactions, providing valuable insights for disaster preparedness and environmental management in typhoon-prone regions. Full article

A directly coupled waveguide uni-traveling carrier photodetector (UTC-PD) with high responsivity and broad bandwidth is demonstrated. The device’s epitaxial structure was carefully optimized via optical simulations to enhance quantum efficiency. Furthermore, the fabrication process was refined to introduce a vertically defined mushroom-shaped mesa structure, which effectively maintains high responsivity while facilitating further improvement in bandwidth performance. As a result, the fabricated device, without the use of an anti-reflection coating, simultaneously achieves a responsivity of 0.49 A/W and a 3 dB bandwidth of 90 GHz. Full article

The Honeycomb Distribution Network is a new distribution network architecture that utilizes the Smart Power-Exchange Station (SPES) to enable power interconnection and mutual assistance among multiple microgrids/distribution units, thereby supporting high-proportion integration of distributed renewable energy and promoting a sustainable energy transition. To promote the continuous and reliable operation of the Honeycomb Distribution Network, this paper proposes a Hierarchical Switching Control Strategy to address the issues of DC bus voltage (U_dc) fluctuation in the SPES of the Honeycomb Distribution Network, as well as the state of charge (SOC) and charging/discharging power limitation of the energy storage module (ESM). The strategy consists of the system decision-making layer and the converter control layer. The system decision-making layer selects the main converter through the importance degree of each distribution unit and determines the control strategy of each converter through the operation state of the ESM’s SOC. The converter control layer restricts the ESM’s input/output active power—this ensures the ESM’s SOC and input/output active power stay within the power boundary. Additionally, it combines the Flexible Virtual Inertia Adaptive (FVIA) control method to suppress U_dc fluctuations and improve the response speed of the ESM converter’s input/output active power. A simulation model built in MATLAB/Simulink is used to verify the proposed control strategy, and the results demonstrate that the strategy can not only effectively reduce U_dc deviation and make the ESM’s input/output power reach the stable value faster, but also effectively avoid the ESM entering the unstable operation area. Full article

In the three-motor hybrid architecture, the auxiliary drive uses electrically excited synchronous motor (EESM), which has the advantages of high torque density, wide speed range and strong anti-demagnetization ability. However, the strong electromagnetic coupling between the field winding and the armature winding leads to the difficulty of current control, and the traditional PID has limitations in dynamic response and immunity. In order to solve this problem, a linear active disturbance rejection control (LADRC) method for the rotor of EESM is proposed in this paper, linear extended state observer (LESO) is used to estimate and compensate the system internal and external disturbances (such as winding coupling and parameter perturbation) in real time. The method only uses the input and output of the system and does not depend on any mechanical parameters, so that the torque response is improved by 50%, and the steady-state fluctuation is reduced by 10.2%. In addition, an adaptive dynamic programming (ADP) parameter optimization strategy is proposed to solve the bandwidth parameter tuning problem of LADRC algorithm in complex operating conditions, and the related mathematical analysis of optimality properties is given. Finally, the proposed method is compared with the traditional PI controller in several operating conditions of EESM, and the effectiveness of the proposed method is validated by the corresponding results. Full article

A comprehensive understanding of aerodynamic instabilities, such as flutter, non-synchronous vibration (NSV), rotating stall, and forced response, is crucial for the safe and efficient operation of turbomachinery, particularly fans and compressors. These instabilities impose significant limitations on the operating envelope, necessitating precise monitoring and accurate quantification of vibration amplitudes during experimental investigations. This study addresses the challenge of measuring these amplitudes by comparing multiple measurement systems applied to the open-test case of the ultra-high bypass ratio (UHBR) fan ECL5. During part-speed operation, the fan exhibited a complex aeromechanical phenomenon, where an initial NSV of the second blade eigenmode near peak pressure transitioned to a dominant first-mode vibration. This mode shift was accompanied by substantial variations in blade vibration patterns, as evidenced by strain gauge data and unsteady wall pressure measurements. These operating conditions provided an optimal test environment for evaluating measurement systems. A comprehensive and redundant experimental setup was employed, comprising telemetry-based strain gauges, capacitive tip timing sensors, and a high-speed camera, to capture detailed aeroelastic behaviour. This paper presents a comparative analysis of these measurement systems, emphasizing their ability to capture high-resolution, accurate data in aeroelastic experiments. The results highlight the critical role of rigorous calibration procedures and the complementary use of multiple measurement technologies in advancing the understanding of turbomachinery instabilities. The insights derived from this investigation shed light on a complex evolution of instability mechanisms and offer valuable recommendations for future experimental studies. The open-test case has been made accessible to the research community, and the presented data can be used directly to validate coupled aeroelastic simulations under challenging operating conditions, including non-linear blade deflections. Full article

To address the challenge of predicting lubrication states and reliability caused by the uncertainty of gear materials and structural parameters, a lubrication reliability analysis method considering the randomness of gear parameters is proposed. Firstly, a nonlinear dynamic model of a gear pair is established to derive the dynamic meshing force. The geometric and kinematic analyses are then performed to determine time-varying equivalent curvature radius and entrainment velocity. The minimum film thickness during meshing is further calculated. Considering gear parameters as random variables, a gear lubrication reliability model is formulated. Monte Carlo Simulation method is employed to accurately analyze the dynamic response, dynamic meshing force, equivalent curvature radius, entrainment velocity, probability distribution of minimum film thickness, and gear lubrication failure probability. Additionally, a specialized wear test device is designed to investigate the evolution of tooth surface roughness with wear and to forecast trends in gear lubrication failure probability as wear progresses. The results indicate that the uncertainty in gear parameters have minimal impact on the equivalent curvature radius and entrainment velocity, but significantly affect the dynamic meshing force. The gear speed and root mean square roughness are critical factors affecting lubrication reliability, and the early wear of the teeth enhances the lubrication reliability. The present work provides valuable insights for the design, maintenance, and optimization of high-performance gear systems in practical engineering applications. Full article

Wind turbine blades feature complex geometries and operate under harsh conditions, including high curvature gradients, nonlinear deformations, elevated humidity, and particulate contamination. This study presents the design and kinematic analysis of a novel climbing robot based on a 10R folding metamorphic mechanism. The robot employs a hybrid wheel-leg drive and adaptively reconfigures between rectangular and hexagonal topologies to ensure precise adhesion and efficient locomotion along blade leading edges and windward surfaces. A high-order kinematic model, derived from a modified Grubler–Kutzbach criterion augmented by rotor theory, captures the mechanism’s intricate motion characteristics. We analyze the degrees of freedom (DOF) and motion branch transitions for three representative singular configurations, elucidating their evolution and constraint conditions. A scaled-down prototype, integrating servo actuators, vacuum adhesion, and multi-modal sensing on an MDOF control platform, was fabricated and tested. Experimental results demonstrate a configuration switching time of 6.3 s, a single joint response time of 0.4 s, and a maximum crawling speed of 125 mm/s, thereby validating stable adhesion and surface tracking performance. This work provides both theoretical insights and practical validation for the intelligent maintenance of wind turbine blades. Full article

An improved Mass–Spring Model (iMSM) is developed by adding central springs to the conventional Mass–Spring Models (MSMs) of tubular structures. This improvement is necessary to model fibers that have enough stiffness so that they do not collapse under transverse loading. Such is the case with many pulp fibers used in papermaking. Four different types of pulp fibers (Aspen CTMP, Aspen BCTMP, Birch BCTMP, and Spruce BKP) were simulated in the study. A geometric model and iMSM of a single fiber were developed, in which the topological structure of iMSM is explained in detail. The mass of mass points and the elastic coefficient of different springs in iMSM were calculated using axial tensile and torsional responses. A dynamic simulation of transverse bending of the fiber over a rigid cylinder and subjected to a transverse pressure was used to determine the effective elastic modulus for four different single fibers and compared to experimental values with an average relative error of 8.49%. The dynamic simulations were completed in 1.04–2.64 min for the four different paper fibers representing sufficient speeds to meet the needs of most real application scenarios. The acceptable accuracy and the fast simulation speed with the developed iMSM fiber model demonstrate the feasibility of the methodology in analyzing paper structures as well as similar fiber-based materials. Full article

The permanent magnetic synchronous motor (PMSM) is of significant use for the centrifugal hydrogen compressor (CHC) in the hydrogen fuel cell system. In order to satisfy the demand for improving the CHC’s performance, including higher accuracy, higher response speed, and wider speed range, this paper proposes a novel adaptive super-twisting sliding mode observer (ASTSMO)-based position sensorless control strategy for the highspeed PMSM. Firstly, the super-twisting algorithm (STA) is introduced to the sliding mode observer (SMO) to reduce chattering and improve the accuracy of position estimation. Secondly, to increase the convergence speed, the ASTSMO is extended with a linear correction term, where an extra proportionality coefficient is used to adjust the stator current error under dynamic operation. Finally, a novel adaptive law is designed to solve the PMSM’s problems of wide speed change, wide current variation, and inevitable parameters fluctuation, which are caused by the CHC’s complex working environment like frequent load changes and significant temperature variations. In the experimental verification, the position accuracy and dynamic performance of the PMSM are both improved. It is also proved that the proposed strategy can guarantee the stable operation and fast response of the CHC, so as to maintain the reliability and the hydrogen utilization of the hydrogen fuel cell system. Full article

To address the challenges of layered fertilization in orchards and the lack of dedicated equipment, this study proposes a layered fertilization technique based on the three-dimensional distribution characteristics of jujube root systems and develops an orchard layered fertilizer applicator. First, the agronomic advantages of layered fertilization were systematically elucidated by analyzing the spatial distribution patterns of jujube roots, as well as the mechanisms of fertilizer nutrient transport and uptake. Second, parametric design was conducted for key components (e.g., trenching–fertilizing unit), with emphasis on the structural design of the fertilizer-dividing box and the augerless spiral conveying mechanism. A three-factor, three-level experiment based on response surface methodology was implemented, where the coefficient of variation (CV) of fertilization uniformity and row consistency were selected as evaluation indices to optimize key parameters (forward speed, augerless spiral speed, and fertilizer gate opening). The optimal operational combination was determined as follows: forward speed of 2.62 km/h, augerless spiral speed of 29.87 r/min, and fertilizer gate opening of 3.49 cm. Field tests demonstrated that the CVs of fertilization uniformity and row consistency reached 7.77% and 8.46%, respectively, meeting the agronomic requirements for orchard fertilization. This study provides a reference for the development of orchard fertilization technologies and machinery. Full article

In this paper, we design a self-powered photoelectrochemical (PEC)-type photodetector based on a hybridization of two-dimensional (2D) few-layer antimony (Sb) nanosheets (NSs) and reduced graphene oxide (rGO). The few-layer Sb NSs obtained by liquid-phase exfoliation can be anchored on the surface of rGO through hydrothermal treatment. Specifically, during photoexcitation, the electron–hole pairs photogenerated on the surface of Sb NSs can be well stimulated and transferred by rGO, reducing the photogenerated carriers recombine on Sb NSs. The excellent electrochemical performance is confirmed by PEC tests. The photobehavior performance of the Sb NSs-rGO composite is significantly improved; its photocurrent density reaches 48.830 nA/cm² at zero potential, approximately twice that of pure Sb NSs. The hybrid exhibits a faster photoresponse speed, with the response time and recovery time being 0.140 s and 0.163 s, respectively. This enhancement arises from the conductive role of rGO as a conductive channel, and as a result, the efficient separation of photoinduced electron–hole pairs is facilitated. This study is a further exploration of hybrid engineering of 2D materials in photochemical photodetectors and demonstrates significant progress in this field. Full article

The increasing elderly population presents major challenges to traditional healthcare due to the need for continuous care, a shortage of skilled professionals, and increasing medical costs. To address this, smart elderly care homes where multiple residents live with the support of caregivers and IoT-based assistive technologies have emerged as a promising solution. For their effective operation, a reliable high speed network like 5G is essential, along with intelligent resource allocation to ensure efficient service delivery. This study proposes a deep reinforcement learning (DRL)-based resource management framework for smart elderly homes, formulated as a Markov decision process. The framework dynamically allocates computing and network resources in response to real-time application demands and system constraints. We implement and compare two DRL algorithms, emphasizing their strengths in optimizing edge utilization and throughput. System performance is evaluated across balanced, high-demand, and resource-constrained scenarios. The results demonstrate that the proposed DRL approach effectively learns adaptive resource management policies, making it a promising solution for next-generation intelligent elderly care environments. Full article

This study presents a general 3 × 5 × 5 factorial experimental design to maximize the Power Coefficient (Cp) of an H-Darrieus hydrokinetic turbine equipped with external accessories. Five accessory configurations (standard, cycloidal, flat plate, curve, and blocking plate), three solidity levels, and five Tip-Speed Ratio (TSR) levels were evaluated as main factors under the hypothesis that these factors significantly influence Cp. The data analyzed were obtained from numerical simulations, and their processing was conducted using Analysis of Variance (ANOVA), linear regression models, and response surfaces in the software programs Minitab 21 and RStudio V4.4.2. ANOVA makes it possible to determine the statistical significance of the effect of each factor and their interactions on the obtained Cp, identifying the accessories, TSR, and solidity that have the greatest impact on turbine performance. The results indicate that the optimal configuration to maximize Cp includes the flat-plate accessory, a solidity of 1.0, and a TSR of 3.2. From the linear regression models, mathematical relationships describing the system’s behavior were established, while the response surface analysis identified optimal operating conditions. These findings provide an effective tool for optimizing H-Darrieus turbine designs, highlighting the positive impact of accessories on performance improvement. Full article

Hands-free computer interaction is a key topic in assistive technology, with camera-based and voice-based systems being the most common methods. Recent camera-based solutions leverage facial expressions or head movements to simulate mouse clicks or key presses, while voice-based systems enable control via speech commands, wake-word detection, and vocal gestures. However, existing systems often suffer from limitations in responsiveness and accuracy, especially under real-world conditions. In this paper, we present 3-Modal Human-Computer Interaction (3M-HCI), a novel interaction system that dynamically integrates facial, vocal, and eye-based inputs through a new signal processing pipeline and a cross-modal coordination mechanism. This approach not only enhances recognition accuracy but also reduces interaction latency. Experimental results demonstrate that 3M-HCI outperforms several recent hands-free interaction solutions in both speed and precision, highlighting its potential as a robust assistive interface. Full article