Search Results (193)

Fire protection remains one of the key challenges in the field of architectural heritage conservation, particularly for heritage buildings dominated by timber structures, which face greater difficulties in fire prevention and risk assessment. To systematically evaluate the fire safety performance of high-rise timber heritage buildings, this study takes the Shengjin Pagoda, a typical brick–timber pavilion-style ancient tower in Jiangxi Province, China, as the research object. A three-dimensional performance-based fire assessment framework was developed using Fire Dynamics Simulator (FDS) and PyroSim. Based on field survey data and historical documentation, the geometric characteristics, material properties, and vertical circulation system of the pagoda were reconstructed. Three representative fire scenarios, including bottom-floor ignition, simultaneous multi-level ignition, and wind-driven top-floor ignition, were established to investigate smoke propagation, thermal insulation degradation, and the thermal response of critical timber components under different fire conditions. The results show that brick walls provide effective thermal insulation during the early stages of fire, with efficiency exceeding 90%, but this decreases to approximately 55% in upper regions due to chimney-effect-driven smoke accumulation. Under wind-driven top-floor ignition, exposed dougong components can reach temperatures of 782 °C, resulting in a progressive “top-down and outside-in” failure mechanism. The study reveals the dominant smoke-driven heat transfer pathways and the failure sequence of critical load-bearing elements. Based on these findings, a performance-based fire protection strategy incorporating vertical virtual smoke control zoning and fire-resistance enhancement of key structural components is proposed to support the sustainable conservation of historic high-rise timber structures. Full article

Insulation failure in aviation generator windings is one of the most common faults. Modern aircraft winding materials often employ polyimide enameled wire, making research on its reliability and health monitoring particularly important. Based on the relationship between temperature and aging rate described by the Arrhenius law, this study designed accelerated thermal aging experiments, testing twisted-pair, coil, and winding samples made of copper-core polyimide enameled wire. The variation in multiple parameters was visualized using B-spline fitting, ultimately identifying parallel equivalent capacitance as the most suitable parameter for monitoring generator winding insulation. It was also indicated that aging of the winding insulation coating has almost no effect on the performance of the electrical system. Finally, experimental data were processed using Bayesian nonlinear regression, where prior data were updated with new data to obtain posterior aging curves. When the IC ($C_p$) value reaches 1.2009 and 1.4089 times its initial value, the sample is considered to have reached 50% and 100% of its lifespan, respectively. This provides a reference approach and quantitative indicators for predicting the lifespan of polyimide enameled wire windings. Full article

Oil-filled current transformers are crucial in high-voltage substations, directly affecting grid safety and reliability. Traditional defect diagnosis methods often show low accuracy and limited monitoring coverage, failing to meet operation and maintenance requirements. This paper proposes an AI-empowered digital twin-based defect diagnosis method that addresses typical issues like oil leakage, insulation damage, and moisture ingress by extracting relevant characteristic parameters to create an evaluation index system. A digital twin model integrates winding, core, and thermal flow characteristics, enabling real-time acquisition of operation parameters and precise mapping between physical and virtual transformers. A dual-model AI framework using Extreme Gradient Boosting (XGBoost) and Support Vector Machine (SVM) is introduced for intelligent defect identification and early defect prediction through multi-source data fusion. Finally, a corresponding diagnostic system is developed and verified using actual operation data from a 220 kV substation in Liaoning Province. The results show that the proposed method enables the online monitoring of multiple operating parameters, and the dual-model framework exhibits higher diagnostic accuracy and faster computation speed compared with Convolutional Neural Networks (CNN) and Recurrent Neural Networks (RNN), providing effective support for intelligent condition-based maintenance of current transformers. Full article

Inter-turn short-circuit faults (ITSC) in the stator winding of large synchronous machines are among the most critical failures in power systems and may lead to severe insulation damage and unplanned outages. At the same time, such faults, due to their nature in critical industrial scenarios, make it difficult to collect sufficiently rich labeled datasets for data-driven and deep-learning-based diagnostic methods. Training diagnostic models purely on simulated signals often results in a severe domain shift between the digital twin and the physical machine due to nonlinearities, mechanical noise, and measurement imperfections, causing a significant degradation of performance when the model is deployed in practice. This paper proposes a hybrid diagnostic framework that combines a nonlinear physics-based digital twin of a synchronous machine, formulated using an extended Park’s transformation model with a dedicated fault loop, with a Domain-Adversarial Neural Network (DANN) driven by a minimal physics-guided feature vector composed of the 100 Hz and 200 Hz harmonic amplitudes of the excitation current. Simulated data from the digital twin are used as a labeled source domain, whereas test-bench measurements of the excitation current form an unlabeled target domain, enabling unsupervised sim-to-real transfer of the stator fault resistance. The proposed architecture achieves accurate regression of the stator fault-loop resistance on a laboratory machine without any labeled measurements of real faults. Experimental results demonstrate Mean Absolute Error (MAE) below 3% across the investigated fault severity range, significantly outperforming baseline approaches that lack domain adaptation. The industrial significance of this approach lies in its potential to facilitate a transition from reactive to predictive maintenance. By enabling early-stage detection, the framework allows power plant operators to avoid catastrophic failures and significantly reduce exceptionally high costs associated with unplanned outages and cascading grid disturbances. Full article

Wide-bandgap power devices, particularly silicon carbide (SiC) MOSFETs, have seen widespread adoption in electric vehicle (EV) motor drive systems due to their superior switching characteristics, including high switching speeds and high switching frequencies. However, these advantages exacerbate motor terminal overvoltage, with peaks reaching twice the inverter output voltage, causing insulation breakdown in windings and bearing electro-corrosion, which shorten motor lifespan. Traditional overvoltage prediction methods, such as distributed parameter models or detailed ladder network approaches, require extensive system parameters and involve high computational loads, while simplified models lack generality. To address these issues, this paper proposes a simplified prediction method based on a lumped ladder network model combined with frequency scanning. The approach uses impedance analysis to identify anti-resonance frequencies, enabling direct estimation of overvoltage amplitudes without prior knowledge of cable or motor specifics. Experimental validation on a SiC-based drive system demonstrates prediction errors below 10% and a reduction in computational time compared to conventional methods. Full article

Epoxy-glass-mica composite materials are widely used as electrical insulating materials in high-voltage rotating machinery due to their layered structure and excellent dielectric properties. Taking the F-class epoxy glass with a small amount of rubber powder mica tape commonly used as the main insulation of wind turbine stator coils as the research object, 7-day, 14-day, 21-day, and 28-day low-temperature treatment tests were conducted at −50 °C. The surface morphology and chemical structure changes of the materials were characterized by SEM and FTIR, and the influence laws of low-temperature treatment on the electrical properties of the mica tape insulation materials were systematically studied. The experimental results show that the low-temperature environment will induce microcracks and interface delamination and other structural damages, but no obvious change in the chemical structure of the mica tape was observed. With the extension of the low-temperature treatment time, the electrical properties of the mica tape show a deteriorating trend, and after 28 days of low-temperature treatment, the breakdown field strength of the F-class mica tape decreased by approximately 18.5%, and the volume conductivity overall increased by about two orders of magnitude. This indicates that the microcrack defects induced by low-temperature will lead to an enhanced electrical-thermal coupling effect in the insulation structure, thereby accelerating the degradation process of the insulation material. This reveals the degradation mechanism of wind turbine stator main insulation from “structural damage” to “performance degradation” and then to “insulation aging” under low-temperature conditions, providing a theoretical basis for the design and reliability assessment of insulation systems in wind turbine generators in cold regions. Full article

Waste from the wind power and textile industries poses major environmental challenges. While the textile industry is a significant global contributor to waste, producing around 92 million tons of waste annually, and greenhouse gas emissions, wind power, although one of the cleanest energy sources during operation, still generates waste and associated CO₂ emissions, particularly associated with the end-of-life decommissioning of turbine blades. This waste can be reused, combined with bio-based binders, to reduce the construction sector’s long-term environmental impact. The present work identifies research trends and gaps in the use of these waste materials, either individually or combined, for the development of thermal and acoustic insulation solutions for the construction sector, by means of a combined bibliometric and content analysis of Scopus and Web of Science documents from 2014 to 2025. The study focuses on bibliometric indicators and reports on physical properties (thermal conductivity, density, mechanical strength, and acoustic performance) of the resulting composites, including those produced with bio-binders. Additionally, a qualitative review of life cycle assessment studies indicates that bio-based and waste-derived insulation materials can significantly reduce environmental impacts compared with conventional mineral or petrochemical insulators. Results reveal growing scientific interest in this subject, highlighting an annual publication growth of 5.09%. They emphasize the performance of natural textile fibers in thermal and acoustic insulation, the mechanical capacity of synthetic fibers, and the semi-structural potential of fiberglass composites. Meanwhile, bio-binders improve the upcycling of textile waste; however, they reveal a significant research gap in the integration of wind turbine blade waste into insulation composites. No indexed studies were found that simultaneously combine textile waste, blade-derived fibers, and bio-based binders in a single insulation system, despite projected cumulative blade waste of 43 million tons by 2050. These findings advocate hybrid innovations and standardized assessments to drive circular economy and low-carbon building solutions. Full article

This study presents a characterization method for High-Frequency Current Transformers (HFCTs) intended for partial discharge (PD) measurement in on-line acquisition systems designed for AI-based processing and clustering. The primary objective is to analyze how key design parameters, ferrite core material, and number of turns, influence HFCT frequency response, attenuation, and sensitivity, thereby providing a basis for optimized sensor design when data analysis is to be performed by means of AI-based algorithms. The investigation focuses on the influence of different ferrite core materials and varying secondary turn numbers on the frequency spectrum and the response to IEC 60270-compliant calibrator impulses Both concentrated and well-distributed HFCT secondary winding configurations are analyzed to evaluate their impact on signal behavior and sensitivity. The experimental results are compared with a simplified theoretical model to validate performance trends and identify key design factors. The HFCT response to IEC 60270-compliant calibrator impulses is examined to assess its suitability for PD measurement systems and monitoring. The results highlight the critical role of core selection and the number of turns in shaping HFCT bandwidth, attenuation, and impulse response, which are essential for accurate and reliable PD detection in continuous monitoring systems to perform the diagnostic of the electrical insulation condition. This diagnostic approach is based on the detection of partial discharge (PD) activity over time, with the objective of identifying evolving phenomena by monitoring the amplitude and characteristics of the signals associated with different defects. Therefore, accurate separation of signals originating from different defects and from noise is essential. These results provide a foundation for designing HFCT sensors suitable for integration into advanced diagnostic frameworks, AI-aided for Condition-Based Maintenance (CBM). Full article

This study presents an integrated engineering methodology aligned with the planning phase of the ISO 50001:2018 (Energy Management Systems—Requirements with Guidance for Use. International Organization for Standardization (ISO): Geneva, Switzerland, 2018) energy management standard for the design, sizing, and assessment of a solar thermal system applied to domestic hot water production in a medium-scale hotel building. The proposed framework focuses on the energy review stage of ISO 50001, incorporating site-specific climatic assessment, spatial layout optimization, structural feasibility analysis, and energy performance evaluation to support informed technology selection and system viability. Thermal performance is assessed using real operational data from the case study, complemented by a data-driven multivariable regression-based energy performance indicator (EnPI) that relates electricity consumption to cooling degree days and room occupancy. This regression model, developed in accordance with ISO 50001 recommendations, enables transparent monitoring of energy performance under real operating conditions without relying on black-box predictive techniques. Material selection criteria for absorber plates, heat-transfer components, transparent covers, and insulation layers are discussed to support both initial efficiency and performance stability under site-specific climatic conditions. In addition, an indicative and qualitative analysis of material-dependent performance evolution is introduced to support comparative decision-making, without implying quantitative lifetime prediction. Structural feasibility of the collector support system is examined through finite-element simulations under combined gravitational and wind loads, providing illustrative verification of stress distribution under representative operating conditions. The installed system delivers an annual thermal energy contribution of 8468 kWh, resulting in an estimated reduction of 7.79 t of CO₂ emissions per year. Economic indicators suggest a short payback period and a favorable internal rate of return, which should be interpreted as order-of-magnitude estimates within the planning scope of the methodology. Overall, the proposed methodology provides a replicable and multidisciplinary planning-phase framework aligned with ISO 50001 for the design and assessment of solar thermal systems in medium-scale buildings under real operating conditions. Full article

This study evaluates the performance of a flat-plate solar collector thermal system located in Bucharest, Romania, by combining experimental measurements (December 2024–April 2025) with numerical modeling. The system, coupled to a 4000 L tank and using a 30% glycol–water mixture, was monitored for irradiance, wind speed, temperature, flow rate, and humidity. Monthly irradiance averaged 448–584 W/m², and wind speed 2.3–4.3 m/s. Instantaneous efficiency ranged from 25.09% to 73.25% (mean 52.96%), with CUF (capacity utilization factor) ranging between 6.55% and 9.38%. Total heat losses were 4.80–7.79 kW and dominated by top losses (3.60–5.59 kW). The model reproduced the manufacturer’s efficiency curve within 5% for data obtained in the spring, with winter deviations of up to 37% due to weather variability and aged insulation. The results provide reference values for the CUF and loss coefficients of flat-plate collectors in temperate continental climates and can support retrofit and sizing decisions. Full article

High-voltage direct current gas-insulated equipment (HVDC GIE) is becoming a key component in DC transmission systems due to its compactness and reliability, particularly for cost-effective offshore wind power integration. However, its reliability is compromised by surface charge accumulation at the gas–solid interface—a problem intensified by metallic contaminants and the adoption of eco-friendly gas mixtures. Addressing this challenge requires not only material and design innovations but also the development of standardized testing protocols to validate insulation performance. This review systematically examines the critical, interconnected areas essential for advancing HVDC GIE, focusing on the dynamics of charged metallic particles and their role in charge accumulation, interface charge behavior under alternative gas environments, and experimental methodologies with evolving test standards. By synthesizing insights across these domains, this work aims to provide both theoretical insights and practical guidance for optimizing HVDC GIE insulation design formulating scientifically grounded operation and maintenance strategies. Full article

To address the issues of insulation layer damage and conductor exposure in offshore floating photovoltaic systems occurring in shallow marine regions characterized by significant tidal ranges under multi-field coupling effects, an overhead cable laying scheme based on the hybrid pile–floater structure is proposed, while its mechanical response is investigated in this paper. The motion response model of the floating platform, considering wind load, wave load, current load, and mooring load, as well as the equivalent density and mathematical model of the overhead cable are established. The mechanical response characteristics of the overhead cable are analyzed through finite element analysis software. The results indicate that the overhead cable’s mechanical response is influenced by the span length and coupled wind–ice loads. Specifically, the tension exhibits a nonlinear increasing trend, while the deflection shows differential variations driven by the antagonistic interaction between wind and ice loads. The influence of ice loads on the configuration of overhead cables is significantly weaker than that of wind loads. This study provides crucial theoretical support for enhancing the lifespan of the overhead cable. Full article

Ventilated façade systems are being increasingly used in energy-efficient building envelopes due to their configurational flexibility and potential to reduce thermal bridging. This study focuses on the experimental evaluation of anchoring components used in such systems, specifically examining the effect of various thermal insulation pads and internal inserts on the system’s mechanical, thermal, and fire performance. A series of laboratory tests was carried out to assess the static behavior of aluminum brackets under both tensile (suction wind load) and compressive (pressure wind load) forces. The results demonstrate that the use of thermal pads and inserts does not lead to any significant degradation of the mechanical capacity of the anchoring brackets, confirming their structural reliability. Additional thermal testing revealed that the use of insulating materials significantly reduces heat transfer through the brackets. Fire resistance tests were conducted to compare the performance of different types of insulation pads under elevated temperatures. The findings indicate that the choice of pad material substantially influences both fire integrity and thermal performance. This study confirms the potential of incorporating optimized insulating pads and inserts into façade brackets to enhance the thermal and fire performance of ventilated façades without compromising their structural behavior. Full article

This study introduces a review on high-speed electrical motors (HSEMs) used for fuel cell (FC) compressor systems, to feed air into the FC stack. This technology is designed for electric vehicle (EV) applications. First, an evaluation of electrical machines as the main energy consumers of EVs is conducted to situate the current study in terms of the mechanical characteristics. Next, the main electrical motor configurations found in the scientific literature, and suitable for applications in FC compressor systems, are presented. Three case studies are depicted to identify the main challenges of this application in terms of the mechanical robustness and efficiency. Finally, a perspective on improving the energetic performance of HSEMs is presented, in terms of the materials used, the shape of the geometry, the winding type and insulation, the cooling, and the optimization techniques used to maximize the performance of HSEMs. Full article

The global transition from internal combustion engines (ICEs) to hybrid (HEVs) and electric vehicles (EVs) is fundamentally reshaping lubricant design requirements, driven by evolving thermal demands, electrical constraints, and material compatibility challenges. Conventional ICE lubricants are primarily formulated to withstand high operating temperatures, mechanical stresses, and combustion-derived contaminants through established additive chemistries such as zinc dialkyldithiophosphate (ZDDP), with thermal stability and wear protection as dominant considerations. In contrast, HEV lubricants must accommodate frequent start–stop operation, pronounced thermal cycling, and fuel dilution while maintaining performance across coupled mechanical and electrical subsystems. EV lubricants represent a paradigm shift, where requirements extend beyond tribological protection to include electrical insulation and conductivity control, thermal management of electric motors and battery systems, and compatibility with copper windings, polymers, elastomers, and advanced coatings, alongside mitigation of noise, vibration, and harshness (NVH). This review critically examines lubricant behavior, formulation strategies, and performance requirements across ICE, HEV, and EV powertrains, with specific emphasis on heat transfer, electrical performance, and lubricant–material interactions, covering mineral, synthetic, and bio-based fluids. Additionally, regulatory drivers, sustainability considerations, and emerging innovations such as nano-additives, multifunctional and smart lubricants, and AI-assisted formulation are discussed. By integrating recent research into industrial practice, this work highlights the increasingly interdisciplinary role of tribology in enabling efficient, durable, and sustainable mobility for next-generation automotive systems. Full article