Search Results (833)

Low-voltage networks are designed as solidly grounded neutral networks (TN, TT) or isolated neutral networks (IT). The latter type is used when continuity of supply and effective protection against electric shock are required despite a single ground fault. A characteristic feature of the IT network is the application of insulation monitoring systems, currently officially named Insulation Monitoring Device (IMD). The aim of this device is to signal the first ground fault, and the network can still be powered. This article shows a comprehensive overview of IMD solutions, from historical to contemporary. IMD structures and characteristic features, as well as critical evaluation, are presented, highlighting their advantages and disadvantages. The desired directions for the development of IMDs are indicated to ensure their proper functioning in modern power networks. Full article

The use of 3D-printed concrete (3DPC) for home building has been of interest to several newly formed 3D printing companies over the past few years. This interest is largely due to its time and material efficiency, as well as its flexibility in architectural design. Although the structural capabilities of 3DPC are still being researched, the enclosure aspects of printed buildings are not equally studied. Current applications of 3DPC for home building are more suitable for mild climates where there is limited risk from harsh weather and drastic temperature differences throughout the seasons. There is a void in understanding how 3DPC walls in cold climates will perform with respect to heat transfer through the wall, which can affect the energy consumption of the building. Therefore, this literature review will explore select numerical and experimental research studies that have been completed on the building science aspects of 3DPC walls and identify gaps for future research. While the main aspect of interest in building science for this study is related to the thermal conductivity property of 3DPC, other aspects are also addressed to a lesser degree. The review then focuses on the thermal performance of the printed concrete, the print configuration and the cavity infill, various waterproofing methods, and hygrothermal properties relating to humidity levels, freeze–thaw cycles, corrosion and mold risk. The research methodology for this review consisted of using keywords to search for relevant 3DPC documents with some reference to building science aspects, categorizing the literature contents based on relevance, recency and quantifiable data, providing a summary of the studies performed and their conclusions, and suggesting any remaining knowledge gaps that merit future studies. Based on the literature review, it is very unlikely that only adjusting the concrete mixture, changing the print configuration or infilling the cavities of 3DPC walls with insulation will satisfy thermal performance requirements across climate zones. The literature review identifies a few future research and study directions. To meet energy standards such as the International Energy Conservation Code (IECC) and avoid thermal bridging, studies need to explore how a continuous layer of insulation can be incorporated into the wall assembly, whether it is interior or exterior, and how it would affect energy consumption. The humidity distribution and risk of condensation across assemblies should also be further researched to determine if they impact the placement of continuous insulation, as well as the risk of corrosion for any structural metal elements in the assembly. Regarding ongoing 3DPC construction, this study shows that while there exists a good understanding of the material and print characteristics, there is a need to use sensors and monitoring systems within current 3DPC builds to gather data on the enclosure performance through different seasons for future improvement. Full article

Climate change is accelerating the frequency of extreme thermal environments, threatening animal welfare, global herd productivity, and agricultural economics. Heat stress—occurring when the ambient temperature-humidity index (THI) surpasses species-specific thermoneutral thresholds—initiates physiological heat-loss cascades (panting, sweating, and peripheral vasodilation), neuroendocrine disruptions (depressed thyroid hormones, elevated glucocorticoids, and insulin dysregulation), mitochondrial oxidative stress, and gut-barrier breakdown. These systemic disruptions drive substantial performance declines: voluntary dry matter intake drops by 15–25%, average daily gain by 15–30%, milk yield by 10–25%, conception rates by 30–50%, and poultry egg output and shell integrity by 15–25%. Species-specific vulnerability is governed by intrinsic anatomical and metabolic differences, including the substantial fermentation heat increment in ruminants, the lack of functional sweat glands and heavy feather insulation in poultry, and the low cutaneous evaporative capacity of swine. Furthermore, thermal stress induces oxidative damage via free radical accumulation and alters blood composition, triggering severe immunosuppression that heightens susceptibility to mastitis, respiratory complexes, and metabolic endotoxemia. Mitigation requires an integrated solutions matrix combining environmental cooling (tunnel ventilation, pad cooling, and shade), targeted nutrition (antioxidants, organic trace minerals, osmolytes, and rumen-protected fats), genomic selection (SLICK locus and thermotolerant crossbreeding), and real-time Precision Livestock Farming (PLF) monitoring. Addressing these challenges is paramount to ensuring sustainable livestock production, animal welfare, and global food security under impending climate scenarios. Full article

Partial discharge (PD) generates transient acoustic-vibration signals that can be used for the passive monitoring of cable insulation. Unlike previous studies that separately addressed DFB-FL sensitivity, polymer-property effects, or acoustic attenuation in a particular cable, this study establishes an application-oriented cross-scale assessment that links material-level propagation loss with cable-scale detection by a distributed feedback fiber laser (DFB-FL)/fiber Bragg grating (FBG) system. This study compared the Young’s moduli of polypropylene (PP), cross-linked polyethylene (XLPE), and methyl silicone rubber (MQ), and measured their frequency-dependent attenuation coefficients along with those of insulating oil in the range of 50 to 300 kHz. Subsequently, a 250 mm-long, 220 kV XLPE cable specimen containing a needle-induced artificial cavity was tested at sensing distances of 0–7 cm and at four circumferential positions. For the three tested materials, the extrapolated initial response amplitude decreased as the Young’s modulus increased. The measured polymer attenuation coefficients were approximately 0.052–0.192 Np/cm, compared with approximately 0.018–0.033 Np/cm for insulating oil. Under the stated laboratory criteria, the lowest time-correlated apparent-charge event detected by the DFB-FL system was 16 pC. The DFB-FL peak-to-peak response decreased from 5.04 Vpp at 0 cm to 1.00 Vpp at 7 cm, crossing below the background threshold between 6 and 7 cm, which experimentally verifies the intrinsic connection among material attenuation, internal cable propagation paths, and sensor-placement constraints. Full article

Traditional fault diagnosis methods for gas-insulated switchgear (GIS) equipment primarily rely on offline detection and periodic maintenance, which suffer from limitations such as poor real-time performance and localization difficulties, thereby compromising the safe and stable operation of ultra-high-voltage power grids. To enhance the accurate identification and localization capabilities of defects within GIS equipment, this study first establishes a multi-physics coupled simulation model integrating temperature field, flow field, and concentration field to analyze gas diffusion characteristics under varying conditions of fault source locations, decomposition product types, and initial concentrations. Subsequently, a GIS busbar gas chamber experimental platform is constructed to validate the simulation model. Finally, a response time matrix, a peak concentration matrix, and a fault coverage index are developed, and a weighted comprehensive evaluation method is employed to optimize sensor placement schemes. The findings reveal that fault source location significantly influences concentration response speed and spatial distribution patterns; SO₂, HF, H₂S, and SOF₂ exhibit distinct diffusion characteristics due to their differing physical properties; and initial concentration primarily affects the non-uniformity during the early diffusion stage. The simulation results demonstrate good agreement with experimental data, with a maximum root-mean-square error of 3.936 × 10⁻⁴. Monitoring point M4 achieves the highest comprehensive score, making it the preferred location for single-sensor deployment. These results provide a theoretical foundation and technical guidance for GIS online monitoring and fault diagnosis. Full article

Gas-insulated switchgear (GIS) is an important component of power transmission systems. Accurate partial discharge (PD) pattern recognition is a key requirement for identifying internal insulation defects within the equipment. However, ultra-high-frequency (UHF) PD pulse sequences produced by different insulation defects usually contain complex nonlinear temporal structures and multi-scale periodic variations. These coupled characteristics are difficult to describe adequately via a single feature-mapping strategy. Thus, this paper proposes a temporal-frequency dual-branch stochastic configuration network (TF-SCN), which consists of two heterogeneous hidden-layer branches, for GIS PD pattern recognition. Specifically, in the temporal branch, the model uses a non-periodic, nonlinear activation function similar to that used in a conventional SCN to capture the nonlinear temporal characteristics. The frequency-sensitive branch introduces paired sine–cosine harmonic nodes with shared random projection parameters to capture frequency-sensitive features. The hidden outputs of the two branches are concatenated into a joint temporal-harmonic feature space, and the output weights are solved under the residual inequality constraints for GIS PD classification. To verify the superiority of the proposed model, comparative experiments are conducted on a dataset containing four PD patterns collected from the GIS PD experimental platform. Several baseline models, including 1DCNN, BPNN, SVM, KELM, RVFL, and SCN, are selected for performance comparison. The results show that, compared to 1DCNN, BPNN, SVM, KELM, RVFL, and SCN, TF-SCN effectively extracts distinguishable features in both the time and frequency domains, thereby achieving the best overall performance. Furthermore, its recognition performance remains consistently superior even on noisy data with signal-to-noise ratios ranging from 50 dB to 20 dB. By integrating highly sensitive UHF sensors with the proposed TF-SCN, this study presents a robust, AI-enhanced intelligent sensing and fault diagnosis system for continuous condition monitoring of power equipment. Full article

In the present circumstances, it is exceedingly hard for people to monitor their blood sugar levels on a regular basis. Checking the blood glucose levels of diabetic individuals is often an essential part of managing diabetes. Now, this means repeatedly pricking your finger and bleeding. Non-invasive (NI) detection methods are anticipated to have several benefits, including the elimination of discomfort, avoidance of sharp items and biohazardous chemicals, the possibility of more frequent testing, and, therefore, better regulation of glucose levels. Infrared technology has become one of the most important technologies for the development of the NI self-monitoring of blood glucose (NI-SMBG). One good thing about this approach is that it does not need any chemicals and can employ fiber optic parts. So, only insulators come into direct contact with the skin. Also, the spectrometer may be made without any moving parts, which makes it strong. For this method to be effective, the spectral signature of glucose must be uniquely identifiable from all other chemical constituents in the human body, and this glucose-specific data must be obtained with a sufficiently high signal-to-noise ratio to facilitate reliable differentiation between glucose-dependent signals and those generated by other matrix components. In this paper, we have addressed the issue of infrared signature analysis for blood glucose, which has been done in the infrared region of the electromagnetic spectrum. Firstly, the analysis is carried out for the glucose molecule only. Later, looking at the presence of numerous other analyses in whole blood, tissues, skin, etc., for in vivo measurement of blood glucose, a set of wavelengths is identified on which in vivo measurements can be done with minimal interference from other body fluid analyses. Absorption of spectroscopic information collected on these wavelengths, along with a suitable calibration model, can be a step ahead for in vivo NI glucose measurement. The main innovative features of the present study are non-invasive glucose sensing, Patient-friendly and continuous monitoring opportunity, Progress towards wearable and real-time diagnostics, Clinical and Social Relevance and Contribution to Research. The paper investigates a non-invasive infrared-based methodology for glucose estimation, focusing on the spectral response characteristics of glucose in biological tissue. While the complexity of tissue spectroscopy involves potential interference from other biomolecules, the present work emphasizes the feasibility of glucose detection without invasive blood extraction, rather than conducting a dedicated interference-analysis study. Full article

Partial discharge (PD) detection is a crucial means for the early warning of incipient insulation defects in arresters. However, under strong electromagnetic interference and background noise, PD signals are prone to distortion, making it difficult to accurately determine the pulse onset front and thus severely degrading the accuracy of time-delay estimation. To address the difficulty of time-delay estimation under low signal-to-noise ratio (SNR) and multi-channel aliasing conditions, this paper proposes a method for arrester PD detection and high-precision time-delay estimation based on joint denoising and improved cross-correlation. First, a joint denoising strategy that integrates singular value decomposition (SVD), variational mode decomposition adaptively optimized by the sparrow search algorithm (SSA-VMD), and the Teager energy operator (TEO) is constructed. This strategy suppresses white noise and periodic narrowband interference while effectively extracting the oscillatory onset characteristics of PD pulses. Second, an enhanced time-delay estimation method based on HB-weighted generalized quadratic cross-correlation is introduced. By employing the dual mechanisms of HB frequency-domain weighting and amplitude weighting to sharpen the correlation peak, the estimation robustness under low SNR is improved. Simulation results show that the proposed method attains an accuracy of 99.9911%, significantly outperforming conventional cross-correlation, PHAT-SCOT, and NLMS methods. Finally, experiments are conducted on a needle-plate discharge platform. In multiple comparative experiments with different spatial distance differences (ranging from <30 cm to >50 cm), the maximum relative error is kept within 0.6%, verifying the reliability and accuracy of the proposed algorithm under controlled laboratory conditions. This method can provide a new approach for online monitoring and accurate fault location of arresters in power systems. Full article

Introduction/Objectives: Implicated in the regionalization of the anterior central nervous system (CNS) and the progression of pallial astrogliogenesis, the transcription factor gene EMX2 has been reported to be specifically silenced in several tumors, both non-neural and neural. Based on that, its overexpression has been proposed as a tool for the treatment of a subset of these malignancies, including glioblastoma. Here we tested this proposal. Methods/Results: We found that Emx2 overexpression in human glioblastoma cells transplanted into the striatum of immunotolerant mice significantly prolonged animals’ survival, outperforming their treatment by temozolomide. However, this approach did not eradicate the tumor, because of in vivo silencing of the therapeutic Emx2 transgene. Notably, silencing of this transgene (or of a reporter designed to monitor its competence to be expressed) also occurred during long-term in vitro culture of GBM cells and was exacerbated by coculture with murine pallial glia under hypoxic conditions. Remarkably, partial insulation of the transgene and the use of a specific combination of epigenetic drugs substantially counteracted the progressive activatability decline undergone by the Emx2-transgene expression reporter, suggesting a promising strategy for overcoming a major limitation of Emx2-based therapy for GBM. Conclusions: An Emx2-encoding transgene, protected by insulation and appropriate epigenetic drugs, can provide a substantial benefit in experimental therapy for glioblastoma. Full article

The first divider in the feedback path of a frequency synthesizer runs at the full oscillator frequency and so constrains the speed and the power of the loop. Current-mode logic reaches high speed but draws a constant bias current independent of switching activity, whereas an all-digital, fully static-CMOS divider draws only dynamic and leakage current at the cost of far greater timing sensitivity to process, voltage, and temperature (PVT) variation. This paper presents a wide-range all-digital multi-modulus divider in 22 nm fully depleted silicon-on-insulator (FDSOI) technology, together with the methodology that makes the digital approach robust. The chain exhibits three distinct PVT failure modes, setup at the slow corners, hold at the fast-cold corner, and collapse of the internal clock duty cycle at the skewed corners; each is identified analytically and closed by a scheme combining back-gate body bias, a per-stage programmable delay trim, and a systematic integral-nonlinearity trim. Characterization is by post-layout simulation over a 45-point corner matrix, with the applied back-gate rail voltages and trim codes reported for every point. The divider covers $N=$ 8 to 127, reaches $39.5$ GHz at the typical corner, and holds a worst-case $33.0$ GHz across the corner box against a 33 GHz target that the uncompensated chain misses at the slow and skewed low-supply corners (SS, SF, and FS at $0.72$ V). A paired Monte Carlo campaign of 100 samples with process and mismatch variation, run at the binding corner, raises the yield at the target from 39% uncompensated to 72% with a single global back-gate setting and 99% with a per-die setting. At the target the divider consumes $5.3$ mW at $N=127$ ($6.2$ GHz/mW) with $35.2$ fs of additive jitter in a $0.005$ ${\mathrm{mm}}^2$ core. The bias and trim settings are chosen by an external search and applied as fixed per-corner values; the monitors, controller, and bias generator that an autonomous implementation would require are specified but not designed, so the work demonstrates externally calibrated corner closure rather than a self-contained compensation system. Full article

Food cold chains rely on refrigeration, cold storage, refrigerated transport, packaging and monitoring systems that consume electricity and fuel while preserving food safety, quality and shelf life. Although many studies propose energy-saving technologies or optimization models for individual cold-chain operations, less is known about how energy-efficiency actions are distributed across refrigeration, logistics and digital monitoring domains, which actors must collaborate to implement them, and which benefits and barriers shape adoption. This paper presents a systematic literature review supported by bibliometric and structured content analysis. Searches in Scopus and Web of Science identified 3930 records before deduplication. After removing out-of-year records and duplicates, 2368 unique records were screened; 896 reports were sought for full-text assessment; 751 reports were retrieved and assessed; 466 studies were included in the final review corpus; and 408 were coded as an applied/action corpus. The synthesis identifies ten energy-efficiency action families, seven cold-chain stage classes, multi-actor configurations, evidence types, collaboration-intensity levels, energy benefits, non-energy benefits and implementation barriers. Transport, routing and distribution is the largest action family (134 records), followed by cold storage and refrigeration technology (66), digital monitoring and information sharing (58), life-cycle assessment, energy assessment and decision support (36), energy systems and renewable cooling (34), packaging and thermal insulation (33), and inventory, and planning and coordination (27). The findings show that food cold-chain energy efficiency is not only a technical refrigeration problem but also a collaborative implementation challenge: many actions require information sharing, coordinated operating decisions, joint investment, data governance or cost/benefit-sharing mechanisms. The review contributes an action-oriented framework that links energy-saving actions to stages, actors, collaboration requirements, benefits and barriers, and it identifies future research priorities on comparable energy metrics, measured savings, renewable cooling, digital twins, demand-side flexibility and governance of collaborative energy-efficiency investments. Full article

Rolling bearings in modern wind turbines operate under demanding tribological conditions that include high contact stresses, mixed lubrication, transient loads, electrical discharge, corrosion, and hydrogen-assisted damage. These factors contribute to premature failures such as micropitting, scuffing, white etching cracks (WECs), and electrical fluting, which remain major reliability challenges in both onshore and offshore turbines. Surface-engineering technologies have emerged as effective tools to mitigate these failure modes. Carbon-based coatings improve sliding performance and reduce wear under boundary-lubricated conditions; black oxide conversion layers enhance the corrosion resistance, lubricant retention, and early-life running-in behavior; and insulating ceramic coatings protect generator bearings from electrical discharge damage. Additional solutions, including polymer overlays, composite films, and hybrid ceramic architectures, offer further improvements in friction, surface fatigue resistance, and environmental robustness. This manuscript reviews the current state of coated bearing technologies relevant to wind turbine applications, synthesizing findings from tribological research, industrial practice, and emerging material developments. While only a limited number of coating suppliers provide documented evidence of coating use in wind turbine drivetrain bearings, the collective progress in surface engineering demonstrates clear potential for improving reliability and extending service life across the installed turbine base. The analysis highlights the mechanisms by which coatings enhance performance, the conditions under which they are most effective, and the gaps that remain in field validation and large-scale deployment. Coated bearings represent a promising pathway toward higher turbine availability, reduced maintenance costs, and improved drivetrain durability. Continued advances in carbon-based films, multilayer architectures, and insulating coatings, combined with better integration of lubrication strategies and condition-monitoring technologies, will play an increasingly important role in enabling the next generation of high-power wind energy systems. Full article

Owing to their exceptional thermal insulation and protective capabilities, thermal barrier coatings (TBCs) are widely applied to critical hot-section components of aero-engines. However, under increasingly harsh service environments, internal defects such as delamination tend to form within the coatings, posing a severe threat to engine operational safety and service life. To effectively evaluate delamination defects in TBCs, this study employs the immersion ultrasonic pulse-echo technique to inspect specimens subjected to various thermal cycling treatments. Four specimens, subjected respectively to 21, 32, 43, and 54 thermal cycles at 1200 °C, were tested. Ultrasonic response data were systematically acquired via normal incidence scanning from both the superalloy substrate side and the ceramic top coat side. Combining Fast Fourier Transform (FFT), Continuous Wavelet Transform (CWT) based on the generalized Morse wavelet, Wavelet Packet Energy Entropy (WPEE), and peak-to-peak amplitude variations of the second echo, multi-dimensional features were extracted from ultrasonic signals across the frequency domain, joint time-frequency domain, and energy distribution profiles. Through comparative analysis, ultrasonic waveform and time-frequency characteristics representing defect evolution were obtained. A significant monotonically decreasing trend of WPEE with the aggravation of interfacial delamination was established, characterizing the acoustic energy confinement process induced by interfacial damage. Furthermore, a multilayer finite element (FE) model reasonably reproduced dynamic acoustic wave propagation; numerical results are in agreement with experimental data, validating the feasibility of the proposed detection method. The detection and evaluation framework established in this study provides a reference for safety monitoring and lifespan prediction of aero-engine TBCs. Full article

Battery packs for new energy vehicles have evolved from simple load-bearing and protective assemblies into multifunctional safety structures integrating structural support, crash protection, thermal-runaway mitigation, flame retardancy, electrical insulation, electromagnetic interference shielding, waterproof sealing, and long-term reliability. Fiber-reinforced polymer composites are promising for upper covers, underbody shields, trays, cross beams, side frames, and local protective structures because of their low density, corrosion resistance, design flexibility, and functional-integration potential. However, composite-part performance is strongly governed by forming. Resin flow, impregnation, curing or cooling shrinkage, fiber orientation, filler dispersion, and interfacial bonding may induce voids, dry spots, resin-rich regions, delamination, warpage, and fiber waviness, thereby affecting load bearing, sealing, thermal protection, and durability. This review focuses on composite-forming technologies for new energy-vehicle battery packs. It summarizes component-level service requirements and material systems and compares representative forming routes, including sheet molding compound (SMC), prepreg compression molding/wet compression molding (PCM/WCM), resin transfer molding/high-pressure resin transfer molding (RTM/HP-RTM), vacuum-assisted resin transfer molding (VARTM), long-fiber thermoplastic direct processing (LFT-D), glass-mat thermoplastic (GMT), thermoplastic sheet forming, pultrusion, and multi-material joining. These routes are evaluated from six dimensions: material form, forming cycle, typical defects, representative mechanical performance, applicable components, and engineering maturity. The review further discusses defect mechanisms, performance effects, detection and control methods, and the roles of in-line monitoring, non-destructive testing, process simulation, machine learning, and digital twins in closed-loop quality manufacturing. Finally, engineering challenges are examined in multi-material joining, thermal-safety integration, low-carbon recycling, and standard certification. Composite-material battery-pack structures should therefore be developed as coordinated design and closed-loop manufacturing systems linking materials, processes, defects, performance, and validation. Full article

Methanol is a critical molecular marker for the early aging of oil-paper insulation, and its rapid detection is highly valuable for insulation condition assessment and the fault warning of power transformers. Widely used chromatographic methods require sophisticated pretreatment workflow and are not suitable for in situ monitoring. Non-destructive spectroscopic methods remain challenging due to the intrinsically small cross section of trace molecules in complex liquid environments. The rapid, direct detection of trace methanol in an oil mixture has yet to be demonstrated. In this study, a high-performance Raman-enhancing substrate was developed through hierarchical microstructure regulation, combining microscale light-trapping structures and nanoscale field-confinement sites to sense the weak Raman response of methanol in transformer oil. Direct detection of ppm-level methanol in the oil matrix was achieved, without additional adsorption enrichment or other complicated pretreatment procedures. The characteristic Raman band of methanol in transformer oil was identified, and a quantitative sensing method was established. Furthermore, the intrinsic temperature-dependent Raman response of methanol was investigated to evaluate the stability of its characteristic fingerprint bands over a broad temperature range. This work demonstrates a rapid, sensitive, and pretreatment-free spectroscopic strategy for trace methanol detection in complex oil matrices, and also sheds light on the high-sensitivity detection of small molecular markers in complex liquid environments. Full article