Search Results (1,077)

Rapid and accurate prediction of the maximum remaining life of lithium-ion batteries is a critical technical challenge for enhancing battery management system reliability and enabling the efficient secondary utilization of retired batteries. Traditional approaches that rely on full charge–discharge cycles or complex electrochemical models often suffer from long detection time and limited adaptability, making them unsuitable for fast testing scenarios. To address these limitations, this study proposes a novel capacity prediction method that integrates charging segment feature extraction with a back-propagation neural network (BPNN) co-optimized using the genetic algorithm (GA) and dung beetle optimizer (DBO). Leveraging the public CALCE datasets, key degradation-related features were extracted from partial charging segments to serve as inputs to the prediction framework. The hybrid GA_DBO algorithm is employed to jointly optimize the BPNN’s weights, learning rate, and activation thresholds. A comparative analysis is conducted across various charging durations (900 s, 1800 s, and 2700 s) to evaluate performance under different input lengths. Results reveal that the model using 1800 s charging segment features achieves the best overall accuracy, with a test set mean squared error (MSE) of 0.0001 Ah², mean absolute error (MAE) of 0.0092 Ah, root mean square error (RMSE) of 0.0122 Ah, and a coefficient of determination (R²) of 99.66%, demonstrating strong robustness and predictive capability. This research overcomes the traditional reliance on full cycles, demonstrating the effectiveness of short charging segments combined with intelligent optimization algorithms. The proposed method offers a high-precision, low-cost solution for online battery health monitoring and rapid sorting of retired batteries, highlighting its significant engineering application potential. Full article

Electrical cable insulation, mainly composed of polymeric materials, progressively deteriorates under thermal, electrical, mechanical, and environmental stress factors. This degradation reduces dielectric strength, thermal stability, and mechanical integrity, thereby increasing susceptibility to failure modes such as partial discharges, arcing, and surface tracking—recognized precursors of fire ignition. This review consolidates current knowledge on the degradation pathways of cable insulation and their direct link to fire hazards. Emphasis is placed on mechanisms including thermal-oxidative aging, electrical treeing, surface tracking, and thermal conductivity decline, as well as the complex interactions introduced by flame-retardant additives. A bibliometric analysis of 217 publications reveals strong clustering around material degradation phenomena, while underlining underexplored areas such as ignition mechanisms, diagnostic monitoring, and system-level fire modeling. Comparative experimental findings further demonstrate how insulation aging modifies ignition thresholds, heat release rates, and smoke toxicity. By integrating perspectives from materials science, electrical engineering, and fire dynamics, this review establishes the nexus between aging mechanisms and fire hazards. Full article

The use of reclaimed water is crucial to prevent pollution from wastewater discharges and mitigate the water deficit faced by irrigation districts or other non-potable water users. Therefore, the zero-discharge strategy represents a significant challenge for coastal cities affected by marine pollution from effluents. In regions such as the Mediterranean arc, agricultural areas located near these cities are increasingly exposed to reduced water allocations or rising irrigation demands due to the impacts of climate change. To address this dual challenge, a circular system is proposed through the implementation of hybrid treatment technologies that enable zero wastewater discharge into the sea. This approach would contribute up to 30 hm³ of reclaimed water annually for irrigation, covering approximately 27,000 hectares of cropland in the province of Alicante. The proposed system integrates advanced techniques, such as reverse osmosis, to ensure irrigation water quality, while also considering partial blending strategies to optimize resource use. Additionally, constructed wetlands are incorporated to regulate and treat the reject streams produced by these processes, minimizing their environmental impact. This combined strategy enhances water reuse efficiency, strengthens agricultural resilience, and provides a sustainable model for managing water resources in coastal Mediterranean regions. Full article

Basin insulator is a critical component of gas-insulated transmission line (GIL) systems. Air gap defects and surface crack defects may form in basin insulators due to casting, installation, or transport processes. This phenomenon poses a significant threat to long-term safety and stability and may even lead to partial discharges. This study establishes a simulation model of a GIL system-incorporating insulator to systematically analyze the influence patterns of various defects on the insulation characteristics of the basin insulator. Meanwhile, an equation predicting the relationship between defect size and maximum electric field strength is derived. The research revealed the following: For short air gap defects near the conductor, increasing length reduces their impact on the surrounding electric field, with the radius having minimal effect; for long air gap defects near the conductor, increasing length amplifies their influence. Smooth air gap defects distant from the conductor show negligible variation in maximum electric field strength with increasing length, while unsmooth air gap defects exhibit more pronounced effects at shorter lengths. Under identical conditions, unsmooth air gap defects demonstrate greater influence on the electric field than smooth ones. For elliptical surface defects, variations in radius show the strongest distortion. The degree of influence from surface crack defects correlates directly with their proximity to the conductor. These findings provide critical diagnostic criteria for assessing the insulation performance of basin insulator under damaged conditions. Full article

Silver (Ag) is widely released into aquatic environments through industrial and municipal discharges, with concentrations often reaching toxic levels for aquatic organisms. Its further extensive use in antimicrobials, especially during the COVID-19 pandemic, has increased environmental inputs. As Ag⁺ is the most toxic form of Ag, understanding its ecological risks remains critical for environmental regulation and ecosystem protection. Thus, we investigated multigenerational and transgenerational toxicity of Ag⁺ as AgNO₃ on the ecologically important species midge Chironomus riparius using two complementary long-term life-cycle experiments. Experiment 1 simulated exposures with pulsed high environmentally relevant concentrations and recovery phases (nominal 3 µg/L), while Experiment 2 assessed continuous low environmentally relevant concentrations (nominal 0.01, 0.1, 1 and 3 µg/L) across four exposed generations of C. riparius followed by three recovery generations. Endpoints included survival, development, reproduction, growth as well as the population growth rate (PGR). Continuous Ag⁺ exposure produced cumulative increases in mortality and declines in emergence, reduced fertility and eggs per rope, delayed development (especially in females), and progressive reductions in PGR. Notably, adverse effects emerged or intensified over generations and were detectable at very low concentrations: some reproductive and survival endpoints showed significant impairment at the European Union’s environmental quality standard (EU-EQS) level (0.01 µg/L) by the fourth generation, while transgenerational effects persisted at ≥0.1 µg/L. Partial recovery occurred after removal of contamination at the lowest concentrations but not after higher exposures. The present study not only indicates that chronic, low-level Ag⁺ contamination can produce persistent, population-level adverse impacts on C. riparius, but also underscores the necessity for long-term ecological assessments to establish more protective standards and maintain ecosystem stability. Full article

Partial Discharge (PD) measurement is one of the effective methods for assessing the internal insulation condition of power transformers in factories and substations. The pulse current signals generated by PD within transformer windings are significantly influenced by the winding structure during their propagation from the discharge source to the external measurement system. This influence may lead to misinterpretation of the insulation status, particularly in the analysis of PD measurement results. Such effects are closely related to the signal transmission path and distance and exhibit a strong correlation with the winding transfer function, manifesting as attenuation, distortion, or delay of the measured signals compared to the original PD waveforms. Therefore, it is essential to investigate the impact of the discharge path on the propagation characteristics of transformer windings and its effect on PD waveforms. This paper establishes a simplified distributed parameter model of a 180-turn single-winding multi-conductor transmission line using the finite element method and mathematical modeling, deriving the transfer functions between the winding head or winding end and various internal discharge positions. By injecting different types of PD waveforms collected in the laboratory at various discharge locations within the winding, the alterations of PD signals propagated to the winding head and winding end are simulated, and clustering analysis is performed on the propagated PD signals of different types. Full article

The paper presents experimental results for a modified pulsed plasma thruster (PPT) with solid propellant, using a coaxial anode–cathode design. Graphite from pencil leads served as propellant, and a tungsten trigger electrode was tested to reduce carbonization effects. Experiments were performed in a vacuum chamber at 0.001 Pa, employing diagnostics such as discharge current/voltage recording, power measurement, ballistic pendulum, time-of-flight (TOF) method, and a Faraday cup. Current and voltage waveforms matched an oscillatory RLC circuit with variable plasma channel resistance. Key discharge parameters were measured, including current pulse duration/amplitude and plasma channel formation/decay dynamics. Impulse bit values, obtained with a ballistic pendulum, reached up to 8.5 μN·s. Increasing trigger capacitor capacitance reduced thrust due to unstable “pre-plasma” formation and partial pre-discharge energy loss. Using TOF and Faraday cup diagnostics, plasma front velocity, ion current amplitude, current density, and ion concentration were determined. Tungsten electrodes produced lower charged particle concentrations than graphite but offered better adhesion resistance, minimal carbonization, and stable long-term performance. The findings support optimizing trigger electrode materials and PPT operating modes to extend lifetime and stabilize thrust output. Full article

This study presents an innovative bimodal approach for laboratory partial discharge (PD) analysis using a YOLOv8-based convolutional neural network (CNN). The main contribution consists, first, in the transformation of a conventional DDX-type electrical detector into a smart and autonomous data source. By training the CNN, a system capable of automatically reading and interpreting the data from the detector display—discharge magnitude and applied voltage—is developed, achieving an average training accuracy of 0.91 and converting a passive instrument into a digitalized and structured data source. Second, and simultaneously, an optical visualization system captures direct images of the PDs with a high-resolution camera, allowing for their morphological characterization and spatial distribution. For electrical voltages of 10, 13, and 16 kV, PDs were detected with a confidence level of up to 0.92. The fusion of quantitative information intelligently extracted from the electrical detector with qualitative characterization from optical analysis offers a more complete and robust automated diagnosis of the origin and severity of PDs. Full article

The results from previous environmental studies on the physicochemical properties of bottom sediments from the Odra River estuary (SW Baltic Sea) and their contamination by pharmaceutically active compounds (PhACs) were compiled and analyzed by the use of various statistical methods (Principal Component Analysis, ANOVA/Kruskal–Wallis, Spearman correlation analysis, Partial Least Squares Discriminant Analysis, and Cluster Analysis). These studies included data on 130 PhACs determined in sediment samples collected from 70 sites across the Odra River estuary as well as the site distance to wastewater treatment plant discharge, PhACs’ physicochemical properties (Kd, Kow, pKa, solubility, metabolism), and sales data. Additionally, total organic carbon, total nitrogen, total phosphorus, acid volatile sulfides, clay mineral content, and trace elements such as As, Ba, Cd, Co, Cr, Cu, Fe, Hg, Mn, Mo, Ni, Pb, Sn, and Zn were analyzed. Clay mineral content and TP were identified as the key physicochemical factors influencing the spatial distribution of PhACs in bottom sediments, exerting a greater impact than the distance of sampling sites from WWTP discharge points. The distribution of PhACs in the estuary was also influenced by the Kd and solubility of the compounds. More soluble pharmaceuticals with low adsorption affinity to sediments were detected more frequently and transported to distant locations, whereas less soluble compounds with high adsorption affinity settled down in bottom sediments near contamination sources. Neither the proportion of a drug excreted unchanged, nor its prescription frequency and sales volume, influenced the spatial distribution of PhACs. In general, Kd may be a useful parameter in the planning of environmental monitoring and tracing migration of PhACs in aquatic environments. Full article

Partial discharge (PD) signals are used to evaluate the insulation condition of stators in electrical machines. Their measurements are often heavily corrupted by ambient noise, making denoising essential for effective detection and analysis of PD signals. Wavelet thresholding techniques are widely applied to denoise PD signals. However, existing hard and soft thresholding functions introduce oscillation or deviation into PD signals after wavelet reconstruction, particularly under high-noise conditions. This paper proposes an improved thresholding function for the wavelet threshold denoising method that effectively overcomes the oscillation issue associated with the hard thresholding function and the constant deviation of the soft thresholding function. Additionally, wavelet basis selection based on the correlation coefficient and an adaptive threshold value is integrated with the improved thresholding function to implement the wavelet threshold denoising method. The proposed technique is applied to both simulated and real-world measured PD signals to evaluate its performance across different signal-to-noise ratio (SNR) levels. Compared with traditional soft and hard thresholding functions, simulation results confirm the superiority of the improved thresholding function, especially under high-noise conditions. At an input Gaussian noise level of −10 dB, the proposed method yielded an SNR that was 1.20 dB and 2.66 dB higher than those of the hard and soft thresholding functions, respectively. Full article

This study evaluates the use of seawater and continental water in tailings thickening and copper flotation at laboratory scale, focusing on water reuse in mining operations in arid regions. The tailings had a mean particle size of 10 µm, with 75% < 50 µm, and a specific weight of 2.64 g/cm³. Seawater contained significantly higher ion concentrations Na⁺ 10,741 ppm, Mg²⁺ 1245 ppm, and Ca²⁺ 556 ppm compared with continental water (187, 32, and 127 ppm, respectively), which negatively affected polymer performance. Sedimentation tests showed that the anionic polymer (A3) increased settling rates by 33 times with continental water at 40 g/t, while with seawater the increase was 31 times at 60 g/t. In column thickener tests, discharge solids reached 65% with continental water and 62% with seawater, representing an annual reduction of ~17,000 m³ of recovered water when seawater is used. Consistency tests indicated that achieving slump <20% required 75% solids with continental water and 77.5% with seawater. With dewatering polymers, doses of 200 g/t achieved ~70% solids and slump values near 50%, surpassing column thickener performance. Primary flotation results showed that recirculated and filtered seawater improved copper recovery by 3–5% compared with fresh seawater, due to partial removal of interfering ions. In contrast, recirculated and filtered continental water reduced recovery by 2–4%, likely because of residual polymer effects on mineral surfaces. These findings highlight the importance of polymer selection and dosage optimization to ensure efficient water recovery and sustainable flotation performance under varying water chemistries. Full article

Background and Objectives: Partial nephrectomy is the standard treatment for small renal tumors, balancing cancer control with renal function preservation. Robot-assisted partial nephrectomy (RAPN) has improved surgical precision and reduced morbidity. Near-infrared fluorescence (NIRF) imaging with indocyanine green (ICG) improves intraoperative visualization of renal vasculature and tissue perfusion, potentially enabling selective arterial clamping to reduce ischemic injury. This study updates contemporary evidence on NIRF/ICG-guided RAPN, focusing on intraoperative, perioperative, and renal function outcomes. Materials and Methods: We systematically queried PubMed, Scopus, and Web of Science databases up to June 2025 for controlled prospective and retrospective studies comparing NIRF/ICG-guided RAPN (selective clamping or zero-ischemia) versus conventional RAPN with main artery clamping in adults with renal masses. Data were synthesized narratively, and random-effects meta-analyses were performed on warm ischemia time (WIT), operative time, estimated blood loss, transfusion rate, length of hospital stay, complication rate, positive surgical margins, and variation in renal function. Results: Eleven studies (10 full-text and one abstract), including two randomized controlled trials, encompassing a patient population of 893 patients (403 NIRF/ICG-guided RAPN and 490 conventional RAPN), were included. Ischemia strategies varied between no clamping, selective or super-selective clamping for NIRF/ICG, and main artery clamping for controls. ICG doses ranging from 3 to 7.5 mg or 0.5–7 mL. Most evidence was classified as level 2b or 3b, indicating a moderate to serious risk of bias. Meta-analysis showed that compared to conventional RAPN, NIRF/ICG-guided RAPN was associated with a shorter WIT (MD: −1.30 min, 95% CI: −2.51 to −0.09; p = 0.039), with no differences in other outcomes. Renal function favored NIRF/ICG at discharge and short-term follow-up, although the difference was not statistically significant. Conclusions: NIRF/ICG reduces WIT during RAPN without increasing perioperative risks. The technique shows promise for better preserving functional outcomes. However, further well-designed, large-scale trials with longer follow-up are needed to confirm these benefits and define clinical indications. Full article

The monitoring of partial discharge activity is part of very basic methods used to determine the status of insulation systems in high-voltage electric power devices. These methods use direct galvanic coupled measurement, measurement by inductive offline methods, or other non-electric methods. The inductive method requires sensitive inductive sensors, which detect the partial discharge pulses occurring in high-voltage circuits. The sensitivity of such sensors strongly depends on the design, construction, and materials of the sensor core. Therefore, knowledge of the magnetic material parameters of a sensor is crucial for obtaining optimal values in terms of the sensor’s final sensitivity. In this experiment, experimental sensor cores were constructed using different magnetic materials and different sensor construction processes. For the laboratory experiments, two types of magnetic material were selected: a magnetic material based on Fe-Ni (Permalloy) and a magnetic material based on MO.Fe₂O₃. As a reference level for sensitivity, the minimum acceptable sensitivity was defined as the equivalent measuring sensitivity obtained using the direct galvanic measurement method. The optimal construction type and magnetic material for the sensor core of inductive sensors were determined. Full article

The Yangtze River Basin is vital to China’s water security and flood management yet lacks a basin-wide quantitative assessment of long-term hydroclimatic changes. This study uses the high-resolution CMFD 2.0 dataset and the VIC model to evaluate spatiotemporal trends in precipitation and natural streamflow from 1951 to 2020. The results show a significant increase in annual precipitation in the upper basin (1.10 mm yr⁻¹, p < 0.05), particularly during the wet season, with spatially concentrated increases along the eastern Tibetan Plateau. The VIC model performed reliably across major stations, with NSE > 0.9 and PBIAS within ±10% during calibration. Natural streamflow trends are spatially heterogeneous: upper mainstream stations (e.g., Shigu, Panzhihua, Zhutuo) exhibit significant increases (6.25–14.58 m³/s per year), while lower stations remain stable or decline. Seasonally, wet-season streamflow increased in the upper basin, whereas dry-season streamflow decreased in the middle and lower reaches. At Yichang, natural simulations reveal growing seasonal extremes, with rising wet-season and declining dry-season flows (−19.06 m³/s yr⁻¹). Human interventions have partially offset these extremes. Since 1990, observed peak discharge at Yichang during the wet season has decreased by 10.04% compared to natural streamflow, while the dry-season minimum discharge has increased by 27.63%. This shows that large reservoirs help reduce flood peaks and increase low flows. These findings highlight the intensifying impacts of climate variability and human regulation on hydrological processes and provide a scientific basis for adaptive water resource management in large river basins. Full article

As a key equipment in the power system, the insulation state of oil-immersed transformer is directly related to the safe and stable operation of the power grid. To explore the feasibility of optical detection methods for detecting transformer insulation defects and further analyze the trend of partial discharge optical signal characteristics under typical oil-paper insulation defects in transformers, this paper proposes a method for detecting insulation defects in transformers based on photon detection technology. This method can not only reflect the periodicity and phase characteristics of photon signals, but also exhibits higher sensitivity compared to the traditional PRPD method. Firstly, the study builds an experimental platform for optoelectronic combined transformer partial discharge based on photon detection technology and carries out partial discharge simulation experiments on four typical insulation defect models through the step-up method to collect their pulse current signals and photon signals. Then, a phase-resolved photon counting (PRPC) method is proposed to analyze the signals during the development of partial discharges. Finally, the optical signal characteristics of the four defect models are extracted for comparative analysis. The results show that the optical signals of partial discharges can effectively respond to the generation and development process of partial discharges inside the transformer, and different types of insulation defects and development stages can be clearly distinguished according to the phase distribution characteristics and characteristic parameters of the optical signals. This study verifies the effectiveness of photon detection technology and provides a new effective tool for the detection of transformer oil-paper insulation defects. Full article