Search Results (1,958)

With the widespread deployment of high-voltage and ultra-high-voltage transmission lines, composite insulators play a vital role in modern power systems. However, prolonged service leads to material aging, and the current lack of standardized, quantitative methods for evaluating silicone rubber degradation poses significant challenges for condition-based maintenance. To address this measurement gap, we propose a novel aging assessment framework that integrates Fourier Transform Infrared (FTIR) spectroscopy with a measurement-oriented ensemble learning model. FTIR is utilized to extract absorbance peak areas from multiple aging-sensitive functional groups, forming the basis for quantitative evaluation. This work establishes a measurement-driven framework for aging assessment, supported by information-theoretic feature selection to enhance spectral relevance. The dataset is augmented to 4847 samples using linear interpolation to improve generalization. The proposed model employs k-nearest neighbor (KNN), Support Vector Machine (SVM), Random Forest (RF), and Gradient-Boosting Decision Tree (GBDT) within a two-tier ensemble architecture featuring dynamic weight allocation and a class-balanced weighted cross-entropy loss. The model achieves 96.17% accuracy and demonstrates strong robustness under noise and anomaly disturbances. SHAP analysis confirms the resistance to overfitting. This work provides a scalable and reliable method for assessing silicone rubber aging, contributing to the development of intelligent, data-driven diagnostic tools for electrical insulation systems. Full article

This study presents a comprehensive review of the viability of hydrogen as an energy carrier for offshore wind energy compared to existing electricity carrier systems. To enable a state-of-the-art system comparison, a review of wind-to-hydrogen energy conversion and transmission systems is conducted alongside wind-to-electricity systems. The review reveals that the wind-to-hydrogen energy conversion and transmission system becomes more cost-effective than the wind-to-electricity conversion and transmission system for offshore wind farms located far from the shore. Electrical transmission systems face increasing technical and economic challenges relative to the hydrogen transmission system when the systems move farther offshore. This study also explores the feasibility of using seawater for hydrogen production to conserve freshwater resources. It was found that while this approach conserves freshwater and can reduce transportation costs, it increases overall system costs due to challenges such as membrane fouling in desalination units. Findings indicated that for this approach to be sustainable, proper management of these challenges and responsible handling of saline waste are essential. For hydrogen energy transmission, this paper further explores the potential of repurposing existing oil and gas pipeline infrastructure instead of constructing new pipelines. Findings indicated that, with proper retrofitting, the existing natural gas pipelines could provide a cost-effective and environmentally sustainable solution for hydrogen transport in the near future. Full article

Synchronized oscillatory fluctuations in intracellular calcium concentration across extended neuronal networks represent a functional indicator of connectivity and signal coordination. In this study, a model of human immature neurons (differentiated from LUHMES precursors) has been used to establish a robust protocol for generating reproducible intracellular Ca²⁺ oscillations in both two-dimensional monolayers and three-dimensional spheroids. Oscillatory activity was induced by defined ionic conditions in combination with potassium channel blockade. It was characterized by stable frequencies of approximately 0.2 Hz and high synchronization indices across millimeter-scale cultures. These properties were consistently reproduced in independent experiments and across laboratories. Single-cell imaging confirmed that oscillations were coordinated throughout large cell populations. Pharmacological interventions demonstrated that neither excitatory nor inhibitory chemical synaptic transmission influenced oscillatory dynamics. Gap junction blockers completely disrupted synchronization, while leaving individual cell activity unaffected. Functional dye-transfer assays provided additional evidence for electrical coupling. This was further supported by connexin-43 expression profiles and immunostaining. Collectively, these findings indicate that synchronized Ca²⁺ oscillations in LUHMES cultures are mediated by gap junctional communication rather than by conventional synaptic mechanisms. This system offers a practical platform for studying fundamental principles of network coordination and for evaluating pharmacological or toxicological modulators of intercellular coupling. Moreover, it may provide a relevant human-based model to explore aspects of neuronal maturation and to assess compounds with potential neurodevelopmental toxicity. Full article

The rapid development of Intelligent Connected Vehicles (ICVs) and the Internet of Vehicles (IoV) has paved the way for new real-time monitoring and control systems. However, most existing telemetry solutions remain limited by high costs, reliance on cellular networks, lack of modularity, and insufficient field validation in competitive scenarios. To address this gap, this study presents the design, implementation, and real-world validation of a low-cost telemetry platform for electric race vehicles. The system integrates an ESP32-based data acquisition unit, LoRaWAN long-range communication, and real-time visualization via Node-RED on a Raspberry Pi gateway. The platform supports multiple sensors (voltage, current, temperature, Global Positioning System (GPS), speed) and uses a FreeRTOS multi-core architecture for efficient task distribution and consistent data sampling. Field testing was conducted during Colombia’s 2024 National Electric Drive Vehicle Competition (CNVTE), under actual race conditions. The telemetry system achieved sensor accuracy exceeding 95%, stable LoRa transmission with low latency, and consistent performance throughout the competition. Notably, teams using the system reported up to 12% improvements in energy efficiency compared to baseline trials, confirming the system’s technical feasibility and operational impact under real race conditions. This work contributes to the advancement of IoV research by providing a modular, replicable, and cost-effective telemetry architecture, field-validated for use in high-performance electric vehicles. The architecture generalizes to urban e-mobility fleets for energy-aware routing, predictive maintenance, and safety monitoring. Full article

Aiming to address the insulation and power supply challenges faced by electrical measurement in ultra-high voltage (UHV) environments, this study proposes and implements a nitrogen-vacancy (NV) center magnetic sensing system based on Power over Fiber (PoF) technology. The system adopts a high-voltage and low-voltage separation design, realizing the isolated transmission of electrical energy and the reliable recovery of measurement signals through an optical fiber link. The sensing unit on the high-voltage side is composed of NV center sensors, microwave excitation modules, and signal processing modules. Its power supply is provided by an independently developed high-power laser power converter (LPC) assembly via 830 nm optical fiber laser transmission. Under an optical input of 10 W, this assembly can achieve an electrical output of 4.88 W with a conversion efficiency of 48.9%. The experimental results show that the system can operate stably in a simulated UHV environment; by optimizing modulation parameters, the optimal magnetic measurement sensitivity reaches 6.1 nT/Hz^1/2. This research provides a safe and reliable solution for the power supply and precise sensing of high-potential side equipment in UHV scenarios, and demonstrates the application potential of PoF technology in advanced sensing for power systems. Full article

Ultra-high-voltage direct current (UHVDC) wall bushings are critical components in DC transmission systems, ensuring insulation integrity and operational reliability. In recent years, surface discharge incidents induced by charge accumulation at the gas–solid interface have become increasingly prominent. A comprehensive understanding of the electric field distribution and charge accumulation behavior of wall bushings under UHVDC is therefore essential for improving their safety and stability. In this work, an electrostatic field model of a ±800 kV UHVDC wall bushing core was developed using COMSOL Multiphysics 6.3. Based on this, a geometrically scaled model of the bushing core was further established to investigate charge distribution characteristics along the gas–solid interface under varying voltage amplitudes, application durations, and practical operating conditions. The results reveal that the maximum surface charge density occurs near the geometric corner of the core, with charge accumulation increasing as the applied voltage amplitude rises. Over time, the accumulation exhibits a saturation trend, approaching a steady state after approximately 480 min. Moreover, under actual operating conditions, the charge accumulation at the gas–solid interface increases by approximately 40%. These findings provide valuable insights for the design optimization of UHVDC wall bushings, thereby contributing to improved insulation performance and enhanced long-term operational reliability of DC transmission systems. Full article

This paper introduces innovative approaches to the design of railway point machines, with particular emphasis on the implementation of multi-component AlNiCoFe alloys, classified as semi-hard magnetic materials. A comprehensive review of existing mechanisms for mechanical force transmission—from the electric motor to the throwing bar—was conducted. The inherent limitations of conventional dry friction clutches, commonly used in current point machine designs, are critically analyzed. Furthermore, the feasibility of employing multi-component AlNiCoFe alloys as functional materials in hysteresis magnetic clutches is examined, with a view toward enhancing the reliability and performance of railway point actuation systems. A review of diagnostic methods for railway point machines was conducted to evaluate the potential application of a novel magnetic torque limiter as a means to eliminate maintenance activities typically required for systems utilizing dry friction clutches. Experimental research was performed on AlNiCoFe alloys employed as the hysteresis layer in the proposed torque limiter. Microstructural and compositional analyses were carried out using scanning electron microscopy (SEM), Energy Dispersive Spectroscopy (EDS), and X-ray Diffraction (XRD) to determine the crystallographic structure, chemical composition, and selected physical properties of the tested materials. The hysteresis loops of the tested materials were measured using a Vibrating Sample Magnetometer (VSM) over a wide temperature range. A prototype magnetic clutch, functioning as a torque limiter in a railway point machine, was developed and presented. The operational characteristics—specifically the throwing force as a function of time—were recorded for a railway point machine equipped with an electromechanical module incorporating the new magnetic torque limiter. The advantages of the proposed solution in terms of force transmission and overall system performance in railway point machine design were analyzed and discussed. Full article

Integrated Energy Transmission Systems (IETSs) are essential to bridge the geographical gap between where energy is produced and where it is needed, transporting power from resource-rich regions to distant load centers. The fundamental challenge is to resolve the inherent asymmetry between an intermittent power supply and distant load demand. Conventional approaches, focusing only on capacity, fail to address this issue while achieving an effective economic and reliable balance. To address the concerns above, a bilevel optimization framework is proposed to optimize the capacity configuration of IETSs, including wind power, photovoltaic (PV), thermal power, and pumped storage. The optimal capacity of wind and PV is determined by the upper-level model to minimize electricity price, whereas the lower-level model optimizes the system’s operational dispatch for given configuration to minimize operational expenses. A detailed IETS model is also developed to accurately capture the operational characteristics of diverse power sources. Furthermore, the proposed model integrates carbon emission costs and High-Voltage Direct Current (HVDC) utilization constraints, thereby allowing for a comprehensive assessment of their economic efficiency and reliability for capacity configuration. Case studies are conducted to verify the proposed method. The results show that the capacities of wind and PV are optimized, and the electricity costs of IETSs are minimized while satisfying reliability constraints. Full article

Modern power distribution systems are increasingly stressed as they operate closer to their voltage stability limits, driven by growing electricity demand, complex load behaviors, and the evolving structure of power networks. Radial distribution systems, in particular, are highly susceptible to voltage instability under critical loading conditions, where even minor load increases can trigger voltage collapse. Such events threaten the continuity and quality of power supply and can cause damage to infrastructure and sensitive equipment. While large-scale cascading failures are typically associated with transmission systems, localized cascading effects such as sequential voltage drops, feeder outages, and protective device operations can still occur in distribution networks, especially under high loading. Therefore, reliable and timely voltage stability assessment is essential to maintain system reliability and prevent disruptions. This study presents a comprehensive comparative analysis of four voltage stability indices designed for radial distribution networks. The performance of these indices is evaluated on the IEEE 33-bus and 69-bus test systems under various critical loading conditions and multiple static load models, including Constant Power Load (CPL), Constant Current Load (CIL), Constant Impedance Load (CZL), Composite Load (COML), and Exponential Load (EXL). The analysis investigates each index’s effectiveness in identifying voltage collapse points, estimating critical load levels, and calculating load margins, while also evaluating their robustness across diverse operating scenarios. The findings offer practical insights and serve as a valuable benchmark for selecting suitable voltage stability indicators to support monitoring and planning in modern distribution networks. Full article

The thermal coal supply chain serves as core infrastructure for ensuring the safe and stable supply of electricity in China. Effective risk management and control of this supply chain are therefore critical to national energy security and socio-economic development. However, the thermal coal supply chain involves multiple complex risk dimensions, including cross-regional multi-entity coordination, a complex network structure, and a dynamic policy environment. Traditional risk analysis methods often fall short in depicting the concurrent events and dynamic propagation characteristics inherent to such a system. This necessitates systematically investigating the thermal coal supply chain within the Coal–Electricity Joint Venture (CEJV) operational framework, which primarily involves equity-based consolidation and long-term contractual coordination between coal producers and power generators, to comprehensively analyze its critical risk factors and transmission mechanisms. Initially, based on the integration of coal-fired power joint operation policy evolution and industry characteristics, 28 risk factors were identified across three dimensions: internal enterprise, external environment, and overall structure. These encompassed production fluctuation risks, thermal coal transport process risks, and insufficient supply chain flexibility. A dynamic behavior model for the thermal coal supply chain was constructed by analyzing the causal relationships among these risk factors, based on the operational processes of each link. Utilizing Petri net simulation technology enables a quantitative analysis of supply chain risks, facilitating the identification of bottleneck links and potential risk points. Through model simulation, 18 key risk factors were determined, providing a theoretical basis for optimizing supply chain resilience within CEJV enterprises. The limitations of traditional methods in dynamic process modeling and industrial applicability were addressed through a Petri net-based methodology, thereby establishing a novel analytical paradigm for risk management in complex energy supply chains. Full article

The rural community of L’Anse au Loup in southern Labrador depends on a long-distance transmission link to Hydro-Québec for its electricity supply, with diesel generation as backup during outages. This dependence raises electricity costs, exposes the community to supply disruptions, and limits control over local energy security. This study evaluates the feasibility of a solar–wind hybrid energy system to reduce imported electricity and improve supply reliability. A detailed site assessment identified a 50-hectare area north of the community as suitable for system installation, offering adequate space and minimal land-use conflict. Using Hybrid Optimization of Multiple Energy Resources (HOMER Pro 3.18.3) software, the analysis modeled local load data, renewable resource profiles, and financial parameters to determine the optimal grid-connected configuration. The optimized design installs 19.25 MW of photovoltaic (PV) and 4.62 MW of wind capacity, supported by inverters and maximum power point tracking (MPPT) to ensure stable operation. Simulations show that the hybrid system supplies about 70% of annual demand, cuts greenhouse gas emissions by more than 95% compared with conventional generation, and lowers long-term energy costs. The results confirm that the proposed configuration can strengthen local energy security and provide a replicable framework for other remote and coastal communities in Newfoundland and Labrador pursuing decarbonization. Full article

Vibration-based predictive maintenance is an essential element of reliability engineering for modern automotive powertrains including internal combustion engines, hybrids, and battery-electric platforms. This review synthesizes advances in sensing, signal processing, and artificial intelligence that convert raw vibration into diagnostics and prognostics. It characterizes vibration signatures unique to engines, transmissions, e-axles, and power electronics, emphasizing order analysis, demodulation, and time–frequency methods that extract weak, non-stationary fault content under real driving conditions. It surveys data acquisition, piezoelectric and MEMS accelerometry, edge-resident preprocessing, and fleet telemetry, and details feature engineering pipelines with classical machine learning and deep architectures for fault detection and remaining useful life prediction. In contrast to earlier reviews focused mainly on stationary industrial systems, this review unifies vibration analysis across combustion, hybrid, and electric vehicles and connects physics-based preprocessing to scalable edge and cloud implementations. Case studies show that this integrated perspective enables practical deployment, where physics-guided preprocessing with lightweight models supports robust on-vehicle inference, while cloud-based learning provides cross-fleet generalization and model governance. Open challenges include disentangling overlapping sources in compact e-axles, coping with domain and concept drift from duty cycles, software updates, and aging, addressing data scarcity through augmentation, transfer, and few-shot learning, integrating digital twins and multimodal fusion of vibration, current, thermal, and acoustic data, and deploying scalable cloud and edge AI with transparent governance. By emphasizing inverter-aware analysis, drift management, and benchmark standardization, this review uniquely positions vibration-based predictive maintenance as a foundation for next-generation vehicle reliability. Full article

With the rapid expansion of electric vehicles, the risk of battery fires has become a critical safety concern. Conventional suppression methods, such as submerging battery packs in large water tanks, are inefficient due to long response times and potential secondary hazards. This study introduces a polymer-based fire suppression tube system that automatically activates under specific conditions. The system utilizes energy from a C4 explosion to rupture the tube, rapidly releasing the extinguishing agents stored inside. Explicit dynamics simulations in ANSYS Workbench 2024 R2 were conducted by varying tube thickness from 0.5 mm to 2.0 mm to evaluate the structural response of adjacent components. Three indices were examined: total deformation, deformation of the adjacent plate, and deformation of the tube itself. The results showed that thinner tubes (0.5 mm) allowed for greater propagation of blast energy, increasing the risk of damage, whereas thicker tubes (≥1.5 mm) effectively confined the explosive energy and reduced shock transmission. These findings confirm that tube thickness is a key parameter governing blast-induced deformation, with 1.5 mm identified as the threshold for minimizing structural damage. This study provides practical design guidelines for polymer-based automatic suppression systems, contributing to safer fire protection solutions for electric vehicles and related industrial applications. Full article

The ocean offers abundant wind and wave energy resources. This paper proposes an integrated concept that co-locates a semi-submersible floating wind platform with wave energy converters (WECs) to exploit the geographical consistency of these resources. By sharing the platform foundation and power transmission infrastructure, this integrated system enhances the utilization efficiency of marine space and renewable energy. Inspired by the principles of the Tuned Mass Damper (TMD) and leveraging mature hydraulic technologies from wave energy conversion and offshore drilling heave compensation systems, this study introduces a novel scheme. This scheme integrates a heave plate with a hydraulic Power Take-Off (PTO) system, functionally acting as a wave energy converter, to the floating platform. The primary objective is to mitigate the platform’s motion response while simultaneously generating electricity. The research investigates the motion performance improvement of this integrated platform under South China Sea conditions. The results demonstrate that the proposed WEC–PTO system not only improves the platform’s wave resistance and adaptability to deep-sea environments but also increases the overall efficiency of marine energy equipment deployment. Full article

The central purpose of this study is to develop and validate an advanced numerical model capable of simulating the vibrational behavior of the operator’s seat in a tractor-type agricultural vehicle designed for operation in protected horticultural environments, such as vegetable greenhouses. The three-dimensional (3D) model of the seat was created using SolidWorks 2023, while its dynamic response was investigated through Finite Element Analysis (FEA) in Altair SimSolid, enabling a detailed evaluation of the natural vibration modes within the 0–80 Hz frequency range. Within this interval, eight significant natural frequencies were identified and correlated with the real structural behavior of the seat assembly. For experimental validation, direct time-domain measurements were performed at a constant speed of 5 km/h on an uneven, grass-covered dirt track within the research infrastructure of INMA Bucharest, using the TE-0 self-propelled electric tractor prototype. At the operator’s seat level, vibration data were collected considering the average anthropometric characteristics of a homogeneous group of subjects representative of typical tractor operators. The sample of participating operators, consisting exclusively of males aged between 27 and 50 years, was selected to ensure representative anthropometric characteristics and ergonomic consistency for typical agricultural tractor operators. Triaxial accelerometer sensors (NexGen Ergonomics, Pointe-Claire, Canada, and Biometrics Ltd., Gwent, UK) were strategically positioned on the seat cushion and backrest to record accelerations along the X, Y, and Z spatial axes. The recorded acceleration data were processed and converted into the frequency domain using Fast Fourier Transform (FFT), allowing the assessment of vibration transmissibility and resonance amplification between the floor and seat. The combined numerical–experimental approach provided high-fidelity validation of the seat’s dynamic model, confirming the structural modes most responsible for vibration transmission in the 4–8 Hz range—a critical sensitivity band for human comfort and health as established in previous studies on whole-body vibration exposure. Beyond validating the model, this integrated methodology offers a predictive framework for assessing different seat suspension configurations under controlled conditions, reducing experimental costs and enabling optimization of ergonomic design before physical prototyping. The correlation between FEA-based modal results and field measurements allows a deeper understanding of vibration propagation mechanisms within the operator–seat system, supporting efforts to mitigate whole-body vibration exposure and improve long-term operator safety in horticultural mechanization. Full article