Search Results (8,654)

Water-bearing faults pose critical hazards in tunnel excavation due to sudden water inrush, making reliable advance detection essential. This study presents a systematic forward modeling framework that integrates COMSOL Multiphysics and MATLAB to simulate three-dimensional direct current (DC) responses ahead of the tunnel face. A three-dimensional finite-element model was developed to investigate the influence of electrical anisotropy on apparent resistivity under controlled geological conditions. Electrical anisotropy of both surrounding rock and water-bearing faults is incorporated to evaluate its influence on apparent resistivity. Numerical experiments investigate the effects of surrounding-rock and fault anisotropy and reveal the mechanism behind hourglass-shaped low-resistivity anomalies. The results also reveal systematic biases when anisotropy is neglected, including forward-shifted anomaly positions, overestimated lateral extents, and more diffuse anomaly boundaries. When anisotropy is considered in both the surrounding rock and the fault, the simulated anomaly closely matches the preset fault location, demonstrating improved localization accuracy. The modeling results clarify the effects of key parameters on apparent resistivity responses and improve the interpretation of low-resistivity anomalies. They also provide a theoretical basis for enhancing the reliability of DC resistivity-based tunnel advance detection. Full article

With the continuous increase in coal mining depth in China, concealed geological structures—such as collapsed columns and faults—pose a severe threat to mine safety by triggering water inrush accidents. Mine DC resistivity methods exhibit high sensitivity to water-bearing characteristics but suffer from limited resolution, while mine seismic exploration offers superior resolution but weak sensitivity to water-rich bodies. Single-method inversion is inevitably plagued by solution non-uniqueness. This study aims to enhance the detection accuracy of concealed structures by implementing a joint seismic–electric inversion that exploits the complementary strengths of both methods. For the DC resistivity component, a forward model was established using the finite element method with unstructured meshes, and inversion was performed via Occam regularization. For seismic exploration, forward modeling employed curved-ray tracing, and inversion was conducted via the LSQR algorithm. Cross-gradient constraints were incorporated into the joint inversion to establish a structurally coupled framework. The novelty of this study lies in the integration of unstructured mesh discretization, curved-ray seismic tomography, and cross-gradient-constrained joint inversion for mine water detection. Numerical simulation results demonstrate that joint inversion effectively constrains the spatial extent of anomalies, accurately characterizes the morphology of multiple anomalous bodies and water-conducting fault channels, and substantially reduces solution non-uniqueness compared to single-method inversions. This research provides a reliable methodology for the refined detection of concealed hazard-inducing structures, offering considerable practical value for safeguarding coal mine safety. Full article

This study presents an empirical fleet-level assessment of 110 autonomous-range trolleybuses using anonymized records collected over 12 months. The dataset comprises 40,150 vehicle-day operating records, 40,150 energy records, 3960 pack-month SOH records, and 584 maintenance, failure, and downtime events. Outcomes are reported in absolute units: RUB/km for LCC, kg CO₂-eq/km for ELC, events per 100,000 km, and downtime hours per 10,000 km. Autonomous operation accounted for 24.5% of mileage. Average net energy consumption was 1.520 kWh/km, whereas mode-distributed gross energy was 1.521 kWh/km in contact-supply mode and 1.752 kWh/km in autonomous mode. The daily-energy model achieved a full-sample fit of R² = 0.860 and MAPE = 8.119%. Validation of vehicle-grouped data using the generated dataset showed R² = 0.842 and MAPE = 8.74%. Mean SOH decreased from 89.98% to 85.94%, accompanied by higher internal resistance. In the central 6.5-year scenario, diagnostic-gated strategy B2 reduced estimated LCC from 29.52 to 26.16 RUB/km. The event-weighted control effect by RPN decreased from 125.4 to 80.4 (35.9%). Baseline ELC decreased only from 0.6646 to 0.6594 kg CO₂-eq/km because operational electricity dominated the total. The contribution is an observation-linked framework that integrates vehicle-day operation, pack-month diagnostics, and event-level maintenance data to compare cost, emissions, and risk under explicit battery-eligibility and service-coverage constraints. The novelty is therefore the empirical, observation-level coupling and joint calibration of existing energy, battery-condition, life-cycle, and reliability methods within one auditable fleet workflow, rather than the introduction of a new standalone degradation or reliability model. Full article

The presence of near-surface cavities poses a significant geohazard due to potential ground subsidence and structural collapse. To mitigate threats to urban stability, this study presents an integrated geophysical framework to locate and characterize abandoned mining galleries and exploitation voids near Linares (Jaén, Spain). The approach combines four complementary techniques: electrical resistivity tomography (ERT), ground-penetrating radar (GPR), frequency-domain electromagnetics (FDEM), and microgravity. The resulting multi-physics responses were cross-referenced with visible surface subsidence features and archival mine plans. Air-filled galleries and shafts generated highly pronounced high-resistivity anomalies. Shallow voids detected at depths of 2–5 m were undocumented in 19th-century mining maps, suggesting older historical origins, whereas deeper ERT profiles and structural disturbance trends (up to 30 m) correlated well with historical records. Within this framework, FDEM provided high-resolution lateral mapping, GPR excelled at resolving ultra-shallow structural boundaries, and ERT characterized deep gallery networks. Crucially, microgravity mitigated inversion non-uniqueness by directly confirming physical mass deficits over the anomalies. This integrated workflow overcomes individual resolution limits, offering a practical tool for land-use planning and early geohazard risk assessment in collapse-susceptible areas. Full article

Flexible thermoelectric textiles have emerged as promising materials for wearable energy harvesting and electrothermal applications because they combine mechanical flexibility with the ability to convert low-grade heat into electrical energy. In this study, reduced graphene oxide/zinc oxide/copper oxide (rGO/ZnO/CuO) hybrid nanocomposites were synthesized and deposited onto Cotton–Nylon–Spandex (80:15:05) stretch fabrics using a silicone elastomer-assisted coating process to develop flexible conductive textiles. The influence of nanocomposite loading (2–8 g/100 mL elastomer) on the structural, electrical, thermal, and thermoelectric properties of the coated fabrics was systematically investigated. SEM, EDX, XRD, and Raman analyses confirmed the successful formation and uniform distribution of the rGO/ZnO/CuO hybrid coating on the textile substrate. Increasing the nanocomposite loading progressively reduced the electrical resistance from approximately 42 to 18 MΩ, indicating the formation of an interconnected conductive network, while the Seebeck coefficient increased from 0.049 to 0.056 mV K⁻¹ (49–56 μV K⁻¹). The measured effective thermal conductivity of the coated textile decreased from approximately 12 to 2.68 W m⁻¹ K⁻¹, reflecting changes in the thermal transport behavior of the composite coating. The coated fabrics also exhibited stable electrical performance under repeated bending, stretching (up to 80% strain), and washing, together with improved thermal stability and uniform Joule-heating behavior. These results demonstrate that the rGO/ZnO/CuO hybrid coating provides an effective strategy for developing flexible, mechanically durable, and multifunctional conductive textiles with potential applications in wearable thermoelectric energy harvesting and smart heating systems. Full article

Air duct contamination in HVAC systems degrades indoor air quality and reduces energy efficiency by increasing aerodynamic resistance, pressure drop, and electricity consumption. This study systematically analyzes contamination causes and their effects on indoor health, system performance, and energy use. It examines physical, biological, and chemical pollutants and their accumulation mechanisms. Emphasis is placed on inspection and diagnostic methods to guide effective monitoring strategies. Ten methods were evaluated using five criteria: reliability, applicability, speed, cost efficiency, and diagnostic value. Optical camera inspection with image processing and pressure drop measurement ranked highest, highlighting the importance of continuous monitoring for preventive maintenance and energy optimization. Full article

Busbars are key components in electric vehicle (EV) battery packs, providing electrical connections between individual cells to form modules and between modules to form the full battery pack while operating under demanding environmental conditions. In this context, busbar-to-busbar and busbar-to-cell terminal interconnections are critical to overall system performance, making their design and reliability of paramount importance. Any failure occurring in these interconnections, including thermal fatigue, vibration-induced cracking, corrosion, and interfacial degradation, can compromise joint integrity and result in a progressive increase in electrical resistance. In this review paper, to support the selection and development of suitable joining solutions for busbar interconnections, a detailed analysis of joining technologies is presented, including mechanical fastening, welding, and joining by forming techniques. Their performance is compared in terms of electrical resistance, mechanical strength, fatigue behavior, and suitability for busbar interconnections. This work outlines current limitations in the understanding and characterization of mechanical, electrical, and fatigue behavior and identifies key research gaps, particularly the lack of fatigue data under coupled electro-thermo-mechanical loading that is representative of real EV operation. The review thus provides a comprehensive foundation for the design and optimization of reliable interconnections, supporting improved durability, safety, and sustainability in next-generation EV battery systems. Full article

Antimony (Sb) thin films are critical precursors for next-generation chalcogenide-based optoelectronics. However, the synergistic effects of sputtering power and pressure on their growth dynamics are not yet fully understood. The objective of this study is to establish the conditions for controlling the growth process of Sb films. To this end, we systematically investigated the interplay between RF-Sputtering parameters and film functionality. Samples were deposited as ~800 nm-thick films using RF-Sputtering, varying the power (50–70 W) and working pressure (10–25 mTorr), followed by comprehensive structural (XRD), morphological (SEM), chemical (XPS), and electrical characterization. A critical power threshold of 60 W was identified for the amorphous-to-crystalline transition, at which the films adopt a rhombohedral phase. Increasing the power to 70 W triggered a significant texture redistribution toward the (104) plane and an increase in grain size from 40 nm to 110 nm. Consequently, electrical resistivity dropped by several orders of magnitude, reaching a minimum of ~10⁻⁴ Ω cm due to enhanced grain connectivity and reduced boundary scattering and the transition from semiconductor-type conductivity to metallic-type conductivity. XPS analysis confirmed that these variations are driven by microstructural evolution rather than chemical changes, as the films maintain a stable metallic character beneath a nanometric surface oxide. These findings establish a direct correlation between plasma conditions and material properties. This strategic framework supports the optimization of Sb-based precursor layers in high-efficiency thin-film technologies. Full article

The increasing penetration of renewable energy sources has increased the need for advanced control strategies capable of maintaining stability under low-inertia, converter-dominated operating conditions. In grid-connected wind energy conversion systems (WECSs), constant power loads (CPLs) exhibit negative incremental impedance characteristics that can amplify DC-link oscillations and complicate the coordination between the electrical and mechanical subsystems. The main contribution of this work is a Soft Actor–Critic (SAC) reinforcement learning algorithm that tunes the outer proportional-integral gains of the machine-side DC-voltage-squared control loop together with the active damping gain, allowing online adaptation of the controller according to the operating condition and disturbance level, thereby improving energy system sustainability. The proposed control framework includes a two-mass shaft model, virtual inertia control, and DC-link load uncertainty in the form of both resistive loads and CPLs. The system is modeled and evaluated using MATLAB/Simulink, and its performance is compared with that of a conventional fixed-gain controller under AC load disturbances and wind speed variations. It has been found that for a 25% load disturbance, the maximum DC-link voltage deviation is reduced by 1.2% under resistive loading and 6.5% under CPL operation. For a 1 m/s reduction in wind speed, the corresponding reductions are 0.8% and 0.9%, respectively. The proposed controller also provides smoother output power and improved damping of the rotor speed and system frequency responses. Full article

Bacteria play a vital role in enhancing host resistance to salt–alkali stress. However, the composition and structure of bacterial communities associated with halophytes under natural high salt–alkali conditions remain poorly understood. Here, a transect comprising six sampling points (0, 9, 18, 27, 36, and 45 m) was established across a natural population of Salicornia europaea L. in Guhya Salt Lake salt–alkali soils. At each sampling site, bulk soil, rhizosphere soil, root, and leaf samples were collected for 16S rRNA gene amplicon sequencing. The pH and soil electrical conductivity (EC) significantly increased along the sampling sites establishing a distinct salt–alkali gradient. This gradient provides an ideal model for studying the ecological adaptation mechanisms of halophytes and their related microorganisms. The results showed that alpha diversity (Shannon index) of bacterial communities significantly decreased across sampling sites in bulk soil, rhizosphere soil and root, but not in leaf. Beta diversity varied significantly across sampling points in all sample types examined. Linear Discriminant Analysis Effect Size (LEfSe) identified specific microbial biomarkers (such as Halomonas spp.) for each sampling point and sample type, many of which are known salt–alkali-tolerant lineages. Random forest and correlation analysis indicated that soil chemical properties had a clear impact on these identified biomarkers. Overall, salt–alkali gradient was associated with habitat-specific microbial communities across plant compartments and certain bacterial taxa were found to be enriched in specific niches. These taxa include known salt–alkali-tolerant lineages, and may putatively contribute to host adaptation to extreme environments, which provides deeper insights into plant–microbe interactions in natural ecosystems and offers potential microbial resources for improving crop salt–alkali tolerance. Full article

Ground-penetrating radar (GPR) and electrical resistivity tomography (ERT) are physically complementary non-destructive evaluation methods for reinforced concrete, yet their integrated diagnostic use has been limited by the absence of controlled, ground-truth-validated calibration of the joint-signature space. This paper presents a laboratory calibration programme in which a single C30/37 reinforced concrete beam (3000 mm × 300 mm × 200 mm, three T12 bars at 35 mm cover, CEM I 42.5N, w/c = 0.50) was sequentially conditioned through four controlled deterioration states—intact reference (Model A), water-filled saw-cut crack (Model B), full saturation by seven-day top-surface ponding (Model C), and chloride-induced active corrosion (Model D). Seven RES2DINV inverted ERT sections at three electrode spacings (a = 7, 15, and 30 mm) and three 800 MHz GPR profiles were acquired across the four known ground-truth conditions. The intact-reference resistivity ρ₀ = 558 Ω·m (full-section median of the mlab dataset at a = 7 mm) and GPR-calibrated velocity v = 0.095 ± 0.008 m/ns (from hyperbola fitting at 35 mm rebar cover) establish the absolute baselines. The four conditions produce systematically distinct joint signatures: Model A exhibits uniform high resistivity with clean rebar hyperbolae and no anomalous reflections; Model B produces a localised ERT low-ρ anomaly (ρ_min = 1.46 Ω·m) co-located with a negative-polarity (R = −0.68) GPR crack-mouth reflection confirming water-fill; Model C produces pervasive low-ρ with a smooth depth gradient and 50–65% GPR amplitude attenuation (−6.0 to −9.1 dB); Model D produces the same bulk GPR signatures as Model C but with a critically different ERT spatial texture—a heterogeneous near-surface layer above a sharp boundary at z ≈ 40 mm with depth-preferential low-ρ concentrated at rebar level. This depth-preferential signature, quantified here by a reproducible Depth-Preferential Index (DPI), is the primary ERT-only diagnostic criterion distinguishing active corrosion from pervasive saturation. For the Model C versus Model D distinction, the GPR response is non-discriminating; this high-risk distinction is resolved exclusively by the ERT depth-preferential criterion. The calibration demonstrates that GPR and ERT are physically non-redundant in the strict sense: neither method alone can unambiguously discriminate all four states, but their combination yields correct classification within the controlled laboratory conditions and subject to the stated qualification conditions. The corrosion state was confirmed at the regime level (chloride above the depassivation threshold, under accelerated polarisation) but was not quantified electrochemically, so the depth-preferential signature is interpreted as an indirect spatial proxy for active corrosion rather than a measurement of corrosion rate. Seven failure modes are quantitatively characterised and embedded in the framework as a priori qualification conditions. The calibrated reference values (ρ₀, A₀, Stage 2 thresholds, depth-preferential criterion) are specific to the laboratory mix and curing history and require local Stage 1 recalibration for field application. Full article

Permanent magnet synchronous motors (PMSMs) used in hybrid shunting locomotive traction systems operate under complex conditions, and their electrical parameters may vary with temperature rise, load disturbance and magnetic saturation. To improve online parameter tracking under such conditions, this paper investigates a forgetting-factor recursive least squares (FFRLS)-based identification method for stator resistance, stator inductance and permanent magnet flux linkage. The main contribution lies in the traction-oriented formulation of the identification model, DSP28335-based real-time implementation, and simulation/experimental validation of three-parameter online tracking. Simulation results show that the proposed method can track the three key parameters under selected perturbation conditions. The experimental results provide algorithm-level evidence for the real-time implementation and three-parameter tracking capability of the proposed method on a scaled-down PMSM platform, thereby establishing a basis for subsequent full-scale validation and studies on traction-control robustness and energy-efficiency optimization. Full article

Cylindrical LiFePO₄ batteries are increasingly used in 3C consumer electronics, including computers, communication devices, and consumer electronic products, owing to their favorable safety characteristics, structural robustness, and stable electrochemical performance. Nevertheless, these batteries may inevitably experience mechanical deformation during manufacturing, transportation, assembly, accidental dropping, collision, or vibration, which can compromise their structural integrity and trigger coupled electrochemical degradation. In this study, the structural-damage-induced failure behavior of cylindrical LiFePO₄ batteries for 3C consumer electronics was systematically investigated at 25 °C under different states of charge. By integrating mechanical response, in situ open-circuit voltage, surface temperature, and electrochemical impedance spectroscopy, the evolution of electro-mechanical failure during external loading was quantitatively characterized. The results reveal a pronounced State-of-Charge (SOC) dependent failure mechanism: the initial yield load increases with increasing state of charge, indicating improved resistance to mechanical deformation, whereas electrical failure occurs earlier at higher states of charge, accompanied by abrupt voltage collapse, abnormal voltage rebound, and unstable voltage oscillations. This phenomenon demonstrates a clear decoupling between mechanical strength and electrochemical stability under structural damage, suggesting that a higher state of charge enhances the apparent load-bearing capability while simultaneously aggravating internal electrical instability. These findings indicate that mechanical deformation thresholds alone are insufficient for evaluating the safety of LiFePO₄ batteries used in 3C consumer electronics, and that state of charge, voltage evolution, thermal response, and impedance variation should be jointly considered. This work provides mechanistic insight and experimental guidance for safety assessment, structural protection, and damage-tolerant design of LiFePO₄ batteries in portable electronic devices and other 3C consumer electronics applications. Full article

Electrical slip rings are key components for power and signal transmission in rotating equipment, and degradation of sliding electrical contact is a major factor limiting their reliability. To analyze the sliding electrical contact behavior of slip rings, an elastoplastic contact framework incorporating thermal–mechanical–electrical coupling is developed. The semi-analytical method combined with discrete convolution-fast Fourier transform is employed to efficiently solve the coupled contact problem, while J₂ flow theory and radial return algorithm are adopted to determine plastic deformation. Based on the proposed model, the elastoplastic sliding electrical contact behaviors of smooth and sinusoidal surfaces are systematically investigated. The results show that plastic deformation increases the contact area, thereby reducing the electrical contact resistance, current density at the contact edge, and maximum temperature rise, although it may induce the residual stress. Reducing the asperity height of sinusoidal surfaces while maintaining multiple discrete micro contact spots can effectively lower the electrical contact resistance and interfacial temperature rise. The proposed model provides a useful theoretical tool for evaluating the thermal–mechanical–electrical performance of sliding electrical contact in slip rings. Full article

Silicon carbide (SiC), a third-generation wide-bandgap semiconductor, demonstrates prominent application advantages for extreme-environment sensing scenarios including deep-space exploration, nuclear reactor monitoring, and fusion device diagnosis, which benefit from its excellent radiation resistance, high-temperature stability, and chemical inertness. This review systematically investigates the action mechanisms of different radiation environments on the electrical and mechanical properties of SiC-based sensors, with emphasis on the regulatory effects of radiation-induced defects on key sensing parameters, including piezoresistive properties, charge-collection efficiency, leakage current, and sensitivity. In addition, this paper discusses the response behavior and research progress of SiC sensors applied in mixed radiation fields. Existing research confirms that although high-fluence radiation can induce lattice defects and further result in the degradation of SiC sensor sensing performance, SiC still retains remarkable advantages in intrinsic radiation resistance. The sensing reliability of SiC in extreme environments can be further improved via device-structure optimization and material-modification strategies. This review is expected to provide a theoretical reference for the development and design of SiC sensors applied in advanced nuclear energy, aerospace, and nuclear medicine fields. Full article