网络首发
An improved success likelihood index method for human reliability assessment
Ming Jie;Chen Xu;Zhou Rong;He Caijun;Li Menghu;Zhou Jianlan;Yu Jing;This study addresses practical challenges in existing Human Reliability Assessment (HRA) methods within hydraulic engineering construction， including incomplete parameter acquisition， inadequate integration of expert consensus， and increasing difficulty in achieving consensus as expert groups expand. We propose an improved Success Likelihood Index Method (SN–SLIM) that integrates Structural Equation Modeling (SEM) and complex network analysis. First， the Human Factors Analysis and Classification System (HFACS) was employed to analyze the behavioral causes of construction safety accidents， leading to the design of a four-dimensional questionnaire to collect empirical data from hydraulic engineering practitioners. A total of 430 questionnaires were distributed， with 336 valid responses retained after data cleaning. The Cronbach’s α coefficient and KMO value for the questionnaire reached 0.971 and 0.928， respectively， confirming the high reliability and validity of the research data. Second， based on the HFACS framework， twelve local SEM models were constructed using AMOS software according to the one-way causal relationships between adjacent levels. The maximum likelihood estimation method was applied to calculate path coefficients between latent variables， resulting in 52 sets of values that reflect the interaction intensity of human factors. Human factors at all levels of HFACS were treated as network nodes， with hierarchical correlations represented as directed connections and path coefficients as weights for directed edges， thus forming a one-way weighted accident cause network. The weights of Probability Success Factors (PSFs) were determined using a node importance calculation model that integrates in-weight intensity and node efficiency. Third， we conducted a case study on tower crane operations in hydraulic engineering， identifying twelve typical human error categories through accident case analysis and expert brainstorming. The PSF weights were incorporated into the SLIM model to compute the Success Likelihood Index (SLI) and Human Error Probability (HEP) for each category. Finally， Fault Tree Analysis (FTA) combined with Monte Carlo simulation was used to validate the proposed method. The Pearson correlation coefficient between HEP values calculated via SN–SLIM and simulated values is 0.992 6， confirming the method's high accuracy and robustness. A comparative analysis with ten existing improved SLIM methods (e.g.， CN–SLIM， BN–SLIM， LG–SLIM) demonstrates that SN–SLIM can incorporate opinions from over 30 experts without necessitating a consensus model， thus broadening expert coverage. Moreover， the method facilitates statistical integration of group opinions through large-sample SEM analysis， effectively minimizing subjective deviations caused by individual expert weight settings and offering enhanced scalability and adaptability for HRA in large-scale complex systems. This study provides a quantitative foundation for the hierarchical control of human factor risks and the optimization of on-site safety management measures in hydraulic engineering tower crane operations， enriching the technical system of HRA within the construction engineering domain.
Research on scheduling optimization of multi-UAV power line inspection in mountainous areas considering energy replenishment
YANG Mi;ZHANG Junhua;HU Zhengshuo;LI Jiguang;This paper formulates a multi-UAV collaborative scheduling optimization problem for large-scale power line inspection under multi-site battery swapping and resupply constraints. The inspection region is served by a shareable battery swapping station network， and the problem is modeled as a multi-site， multi-flight combinatorial optimization model. The objective function minimizes total flight path length subject to four categories of hard constraints: (1) single-flight energy consumption must not exceed battery capacity; (2) each inspection tower must be visited exactly once across all UAVs and flights; (3) take-off and landing point attribution must satisfy site-assignment logic; and (4) cross-site battery swapping and resupply coordination must conform to spatial accessibility rules. To address the resulting highly nonlinear， strongly constrained discrete optimization problem， an improved dream optimization algorithm (IDOA) is proposed with three targeted enhancements. First， a load balancing-Latin Hypercube Sampling (LHS) hybrid initialization strategy is designed. The load balancing component distributes inspection tasks evenly across UAVs to avoid skewed initial solutions， while LHS ensures uniform coverage of the solution space， jointly improving initial population quality and reducing premature convergence risk. Second， a collaborative evolution mechanism based on a three-layer management architecture is constructed. The three layers correspond to global exploration， regional exploitation， and individual refinement， with each layer governed by dedicated operators， achieving logical decoupling of search behaviors. This hierarchical structure improves search efficiency across heterogeneous solution spaces and prevents mutual interference between exploration and exploitation phases. Third， a periodic single-task local search operator is embedded into the algorithm's iterative process. By periodically applying task-level perturbations to elite solutions， the operator strengthens fine-grained mining in the discrete solution space and enables targeted improvement of near-optimal candidate solutions that are difficult to escape through global operators alone. Computational experiments are conducted on power line inspection instances of small， medium， and large scales. IDOA is benchmarked against five state-of-the-art metaheuristic algorithms under identical experimental settings. Results demonstrate that IDOA achieves consistently superior convergence stability across all tested scales， reflected in both faster convergence speed and lower final objective values. In terms of key performance indicators including total path length， task completion time， and number of battery swaps， IDOA outperforms all comparison algorithms in every experimental scenario. Notably， the performance advantage of IDOA over the best-performing baseline becomes progressively more pronounced as problem scale increases， confirming the algorithm's strong scalability. Statistical analysis of repeated runs further verifies that IDOA maintains low solution variance， demonstrating robust behavior under stochastic search conditions. These results collectively confirm that IDOA possesses comprehensive advantages in solution quality， algorithmic robustness， and scalability for multi- UAV collaborative power line inspection scheduling.
SF6 leakage characteristics and exhaust port layout in GIL tunnels under axial and jet ventilation
Zhong Ke;Chen Wangyu;Li He;Wang Liang;Yang Qinghai;Wang Ling;Kang Yanming;This study employs Computational Fluid Dynamics (CFD) numerical simulation methods using FLUENT software to investigate the transport and elimination characteristics of Sulfur Hexafluoride (SF6) during accidental leakage in a Gas-Insulated Transmission Line (GIL) cable tunnel. The research compares two ventilation modes—axial fans and jet fans—and explores the effects of exhaust port parameters on SF6 capture performance. A typical tunnel section， measuring 1 600 m in length， 13.5 m in inner width， and 8 m in total height， was modeled， containing 18 GIL pipelines with a diameter of 512 mm. The simulations utilized the RNG k–ε turbulence model coupled with the species transport equation. To simulate a severe single-compartment incident， the leakage source was positioned 50 m from the tunnel entrance above the central GIL pipeline， with an SF6 mass flow rate of 5.76 kg/s maintained for 300 s. Under equivalent conditions of a 5 m/s average wind speed across the cross-section， the performance of axial and jet fan ventilation modes was compared， along with a detailed analysis of exhaust port parameter configurations. The results indicate that the stratified flow field produced by jet fans， characterized by high velocity in the upper region and low velocity near the bottom， effectively suppresses the upward diffusion of SF6 toward the breathing zone. Compared to axial ventilation， jet fans reduced the peak SF6 volume fraction in the breathing zone from approximately 21 000 μL/L to around 8 500 μL/L， representing a reduction of about 60%. Additionally， the longitudinal spread distance L1000 decreased by approximately 17% relative to the axial fan mode. Given their organizational flexibility and the benefits of segmented relay ventilation， jet fans are deemed more suitable for meeting emergency ventilation requirements in ultra-long GIL cable tunnels. The layout parameters of the exhaust ports play distinct roles in SF6 elimination performance: the total extraction area and negative pressure are crucial for determining the overall capture amount， while the degree of spatial concentration influences the effectiveness of spread control. A decentralized layout fails to inhibit SF6 migration; under operating conditions B1， B2， and B3， the maximum spread distance exceeded 900 m during the leakage period. In contrast， a centralized layout effectively blocks SF6 migration， limiting the maximum spread distance to approximately 350 m under conditions B4， B5， and B6—about 61% shorter than that observed with the decentralized layout. Furthermore， maintaining a constant total exhaust area and negative pressure， reducing the port spacing from 125 m to 50 m can further limit the spread distance by approximately 50%.
Optimization strategies of pollution control and carbon-reduction for electric vehicles based the 5G and lightweight technologies
Jia Shuwei;To enhance pollution control and carbon reduction in electric vehicles， this study integrates the framework effect with social norms， information disclosure， and default options (referred to as the SID–FE theory). By incorporating 5G and lightweight technologies， we propose a travel inhibition algorithm for electric vehicles based on the SID–FE theory. Additionally， we establish a model for pollution control and carbon reduction in electric vehicles that incorporates nudge strategies and intelligent technology. Through simulation comparisons， we evaluated the environmental and economic performance of the efficiency enhancement model. The findings reveal several significant outcomes: (1) Both the 5G–lightweight mode and the SID–5G–lightweight mode demonstrate substantial potential for pollution control and carbon reduction， with the SID–5G–lightweight mode yielding more effective results. (2) In terms of carbon reduction， compared to the baseline scenario， the 5G–lightweight mode reduces the CO2 pollution cost of electric vehicles by approximately 66.47%， while the SID–5G–lightweight mode achieves a reduction of about 72.84%. The corresponding governance potentials are estimated at approximately 2.997 69 × 108 CNY and 3.285 00 × 108 CNY， respectively. (3) Regarding pollution control， under the 5G–lightweight mode， the pollution costs associated with PM2.5， NOx， and SO2 for electric vehicles are approximately 4.652 55 × 108 CNY， 1.592 12 × 108 CNY， and 1.843 17 × 107 CNY， respectively. Compared to the baseline scenario， the impact of the 5G–lightweight mode is approximately 35.37%. (4) In comparison to the baseline scenario， the SID–5G–lightweight mode reduces the pollution costs of PM2.5， NOx， and SO2 for electric vehicles by approximately 6.267 70 × 108 CNY， 2.144 83 × 108 CNY， and 2.483 02 × 107 CNY， resulting in an overall effectiveness of around 47.65%. This research offers a new perspective from the psychological attribute viewpoint to optimize strategies for pollution control and carbon reduction in electric vehicles.
Spatiotemporal patterns and drivers of landscape ecological risk in the Weihe River Basin based on XGBoost–SHAP
Meng Xiaolan;Xu Fujun;Zhai Meng;Zhang Mantong;Hong Hui;Zhang Xing;This study investigates the spatiotemporal patterns and nonlinear driving mechanisms of landscape ecological risk in the Weihe River Basin from 2000 to 2020. Landscape ecological risk indices were calculated for each grid cell using land use data， and spatial autocorrelation analysis was employed to characterize spatial clustering. The Extreme Gradient Boosting Integrated with Shapley Additive Explanations (XGBoost–SHAP) framework was applied to quantify the nonlinear contributions and threshold effects of various driving factors. The landscape ecological risk values ranged from 0.01 to 0.68 across all evaluation grids. Medium-risk areas constituted the largest proportion， averaging 32.47%， with a gradually increasing trend， while high-risk areas decreased from 8.52% to 8.16% by 2020. Spatially， high-risk zones progressively retreated toward the northern Loess hilly-gully region， coinciding with areas where the Grain for Green Program was implemented. In contrast， low-risk zones in the central Guanzhong Plain exhibited fragmentation and outward displacement. Global Moran’s I values remained above 0.40 (p < 0.001) throughout the study period， indicating significant spatial autocorrelation. H–H clusters were predominantly located in the northern and southern basin， while L–L clusters were concentrated in the central plain. SHAP analysis revealed that distance to residential areas， mean annual temperature， and slope were the three most influential factors， collectively contributing nearly 60% of the total SHAP values. Nonlinear threshold effects were identified for multiple factors. Specifically， NDVI exhibited strong negative effects under low coverage conditions that diminished at higher coverage levels. Precipitation and temperature displayed inverted U-shaped patterns， with effects shifting from positive to negative across different value ranges. Slope showed a U-shaped pattern， while elevation exhibited a positive nonlinear relationship with ecological risk. GDP and population density demonstrated negative nonlinear relationships， suppressing risk only beyond certain developmental thresholds. Distance to river also showed an inverted U-shaped pattern， with risk suppression observed in both nearby and distant zones. These findings indicate that the contributions of driving factors vary dynamically across different value ranges， providing a quantitative basis for spatially targeted risk management in ecologically fragile arid and semi-arid regions.
Source analysis of inorganic elements in atmospheric dustfall in the main urban area of Xi'an city based on ED-XRF and PMF
Yang Jianjun;Zhang Yong;Liu Suixin;Zhang Zhimin;Liu Chao;Zhang Jiaqi;Ma Jiaqi;Lian Zifan;Geng Chenfei;Gu Chunyang;Li Shenglong;The inorganic element determination technology for atmospheric dustfall in the main urban area of Xi'an city was independently constructed based on energy dispersive X-ray fluorescence spectroscopy for a period of one year. At the same time， the source of inorganic elements in atmospheric dustfall was analyzed using positive matrix factorization method. The research results show that the abundance distribution range of 20 inorganic elements is relatively wide， with Fe element having the highest abundance and Se element having the lowest level. The abundance levels of each inorganic element vary greatly; The factors determined by source apportionment are mobile sources， construction dustfall， metal processing and smelting， industrial production and manufacturing， biomass combustion sources， road and soil dustfall， and coal-fired sources. The contribution rates of each factor are 10.90%， 23.63%， 13.11%， 10.45%， 12.64%， 25.34%， and 3.92%， respectively， with the highest being road and soil dustfall and the lowest being coal-fired sources; The overall balance of the proportion of motor vehicle sources is fundamentally related to the high degree of "dispersion" and "mobility" of motor vehicle emission sources; The differential changes in construction dustfall are related to the number of construction projects started by construction enterprises and the distribution of construction projects; The proportion of biomass burning at all locations from July to October 2023 (except for the first location after June) is relatively high， which is related to factors such as agricultural open burning， outdoor barbecue， and relatively good atmospheric diffusion conditions; The proportion of road and soil dustfall in March-May 2023 and November-December 2023 is relatively high， mainly due to the high frequency of sandstorms and the accumulation of a large amount of dustfall on the surface during the deciduous season; The coal-fired sources from June to October 2023 have a certain proportion and are relatively significant in most locations， which is related to external contributions.
Experimental study on methane explosion propagation under localized premixed gas cloud conditions
LI Ranran;LIU Qiqi;LIU Zhenyi;To investigate explosion safety issues associated with localized combustible gas clouds propagating in confined and elongated spaces， a pipeline explosion experimental system capable of generating localized premixed gas clouds was developed. The effects of methane concentration and the volume of localized premixed gas clouds on methane explosion propagation characteristics were systematically studied. High-speed imaging and pressure sensors were employed to measure and analyze key parameters， including flame morphology evolution， flame propagation dynamics， explosion overpressure， and the overpressure rise rate. The results indicate that the volume of the premixed gas cloud has a significant influence on explosion propagation characteristics. As the premixed cloud volume increased from one pipe section to two sections， the flame luminosity was markedly enhanced and the flame propagation velocity increased significantly. The maximum average flame propagation velocity reached 205.88 m/s for the two-section condition， which is substantially higher than the 154.18 m/s observed for the one-section condition. Methane concentration also plays a critical role in both flame propagation dynamics and explosion pressure characteristics. The flame propagation velocity， peak overpressure， and maximum overpressure rise rate all reached their maximum values at the stoichiometric concentration of 9.5%. When the mixture deviated from the stoichiometric condition， the combustion intensity weakened， leading to reductions in both flame propagation velocity and explosion overpressure. For the same deviation from the stoichiometric concentration， the peak overpressure and its rise rate under fuel-rich conditions were significantly higher than those under fuel-lean conditions. In addition， the axial evolution of explosion overpressure in the pipeline exhibited a characteristic pattern: slight initial oscillatory growth， rapid increase， sharp decay， and a slight rebound near the pipe end. The maximum overpressure occurred at 3.75 m， where the superposition of reflected shock waves and their coupling with the combustion wave were most pronounced. These findings provide useful insights for hazard assessment of localized gas cloud explosions and the design of explosion protection strategies in confined spaces.
Quantitative HAZOP risk assessment based on steady-State fluid-structural coupling simulation: a case study of a shell-and-tube heat exchanger
MA Hanpeng;YU Jialiang;YANG Tiejun;HE Yanyan;Traditional hazard and operability (HAZOP) analysis relies heavily on expert judgment and lacks quantitative evidence when evaluating structural risks in shell-and-tube heat exchangers， often resulting in ambiguous and experience-dependent consequence descriptions. To address this limitation， this study proposes a systematic methodology that integrates steady-state fluid–thermal–structural sequential coupling simulations into the HAZOP framework to enable quantitative， mechanics-based risk assessment of structural integrity. A detailed three-dimensional numerical model of a fixed tube-sheet heat exchanger is constructed using the ANSYS Workbench platform， incorporating realistic geometric features and temperature-dependent material properties of 304 stainless steel. Steady-state computational fluid dynamics (CFD) simulations are first conducted to solve the Reynolds-averaged Navier–Stokes equations with the shear stress transport (SST) k–ω turbulence model， thereby obtaining the flow field and conjugate heat transfer temperature distributions under both nominal and deviation conditions. The resulting temperature and pressure fields are subsequently transferred as thermal and mechanical loads to a finite element structural model， where thermoelastic equilibrium equations are solved to determine equivalent stress distributions and total deformation. A dedicated risk assessment matrix is established by integrating the computed safety factor—defined as the ratio of material yield strength to maximum equivalent stress—with a region-specific sensitivity classification that distinguishes primary， secondary， and peak stress zones in accordance with pressure vessel design codes. Eight deviation scenarios are designed based on HAZOP guidewords， encompassing variations in cold and hot fluid mass flow rates (0.7–2.8 kg/s) and inlet temperatures (0–100 ℃). Simulation results demonstrate that temperature-induced deviations exert the most pronounced influence on structural integrity. Notably， the cold fluid inlet at 0 ℃ yields a maximum equivalent stress of 274 MPa and a safety factor of 0.8， corresponding to an extremely high risk level， while a hot fluid inlet at 100 ℃ results in 242 MPa and a safety factor of 0.91. In contrast， flow rate deviations induce comparatively moderate stress variations (102–177 MPa) and lower risk rankings. The proposed methodology not only aligns closely with empirical engineering judgment but also transforms qualitative HAZOP consequence descriptions into explicit， data-driven risk classifications， thereby providing robust， quantitative support for risk-based inspection planning and proactive safety management of shell-and-tube heat exchangers.
Research Progress and Prospects in the Comprehensive Utilization of Phosphogypsum Solid Waste
Li Shiqi;Hu Jianhua;Yu Zhi;Li Jianing;Ma Wenjin;Zhou Ying;Gao Benming;Zhao Xiangbo;This review systematically examines the physicochemical characteristics， utilization pathways， engineering applicability， and environmental constraints of phosphogypsum (PG). Relevant studies were classified into eight categories: mine backfilling， construction materials， road engineering， cementitious materials， chemical conversion， agricultural use， rare-earth-element recovery， and environmental functional materials. These pathways were compared in terms of bulk-consumption potential， technological maturity， pretreatment requirements， product-market capacity， process complexity， cost constraints， and environmental risks. The interactions of PG with cementitious phases， soil minerals， and stabilizing agents were also analyzed to clarify the mechanisms governing hydration， setting， strength development， pollutant immobilization， and long-term release.The review shows that PG is composed mainly of CaSO₄·2H₂O but commonly contains free acids， soluble phosphorus， fluorides， organic matter， heavy metals， and naturally occurring radionuclides. These impurities may retard hydration， disturb setting， reduce early strength and durability， increase process instability， and raise long-term leaching and radiological risks. Construction materials represent the most mature route for large-scale utilization， but product quality， pretreatment cost， and market demand limit further expansion. Road engineering and mine backfilling provide high unit consumption and strong regional disposal potential; however， their application depends on mechanical durability， seepage control， and long-term pollutant-release behavior under service conditions. Cementitious utilization is technically feasible， particularly when PG is used as a setting regulator or sulfate-bearing component， but the overall consumption is restricted by low addition levels and impurity-related interference with hydration. Chemical conversion and rare-earth-element recovery can increase product value， yet their high reagent and energy demands， complex separation processes， and limited throughput make them more suitable as supplementary routes. Agricultural and ecological applications are strongly controlled by soil type， impurity concentration， application rate， and long-term monitoring requirements.Based on the comparative analysis， a prospective integrated route is proposed: source-specific characterization and classification， low-cost physical pretreatment， targeted purification or stabilization， application-oriented route matching， closed-loop wastewater treatment， and by-product recovery. Construction materials are suggested as the principal pathway， while road engineering and mine backfilling serve as high-consumption regional options， and chemical conversion and rare-earth-element recovery act as small-volume， high-value supplements. Life-cycle assessment together with long-term leaching and radiological-risk evaluation should be used to define application boundaries and access criteria.
Research on integrated safety risk assessment and decision-making methods for centralized photovoltaic projects in Northwest China
Yan Liang;Liu Ping;Zhang Yu;He Zongfeng;Wang Jianping;This paper proposes an integrated safety risk assessment and decision-making method for centralized photovoltaic projects in Northwest China from the perspective of risk evolution. The proposed method incorporates three core components. First， a dual-dimensional quantitative model consisting of “static risk” and “transmitted risk” is constructed based on Bayesian networks and information entropy theory. The static risk captures the inherent potential harm of each risk node given its parent nodes’ states， while the transmitted risk quantifies the amplifying effect of risk propagation along the network using Shannon entropy. Second， a data-driven threshold determination method is developed to identify the failure criterion for each risk node. This method employs second-order difference analysis on candidate threshold percentiles obtained from Monte-Carlo simulation results， and the optimal threshold is identified at the percentile where the system behavior exhibits a critical transition. Third， a multi-strategy decision-making framework is established by integrating sensitivity analysis and value engineering theory， enabling both the identification of critical risk triggers and the selection of optimal intervention strategy portfolios that balance risk control effectiveness and cost efficiency. The proposed framework is validated through an empirical study on a centralized photovoltaic project in Northwest China. A total of 38 risk factors are identified across the design， construction， and operation phases. The Monte-Carlo simulation with 5，000 iterations yields a baseline comprehensive safety risk level of 32.527， with the 5%， 50%， and 95% percentiles being approximately 16.000， 32.457， and 49.455， respectively， indicating a symmetric risk distribution. Sensitivity analysis identifies five key risk triggers that contribute most significantly to the overall system risk: lack of experience in regional risk perception， reduction of maintenance investment， improper contractor selection， incomplete emergency plans， and failure of safety supervision mechanisms. Among four categories of intervention strategies (organizational， managerial， technical， and economic)， the optimal combination of “organizational + managerial + technical” strategies achieves the highest value index of 2.698， outperforming other combinations including the four-strategy full combination (value index 1.925). The results demonstrate that the proposed framework can effectively identify critical risk triggers and select optimal intervention portfolios， providing both theoretical foundations and methodological support for systematic and precise safety risk management in centralized photovoltaic projects in Northwest China.