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Table of Content

    28 February 2026, Volume 36 Issue 2
    Safety Science Theories and Methods
    Identification model of miners' risk perception ability under influence of alertness level
    TIAN Shuicheng, LI Hongyan, SHI Yanbin, TIAN Fangyuan, WANG Yajuan, DUAN Mengfei
    2026, 36(2):  1-8.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0465
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    In order to explore the influence of miners' alertness on risk perception ability, miners' alertness tests and risk perception experiments were designed and implemented. During the experiments, fNIRS, behavioral data, and peripheral physiological signals were collected. Methods such as the normality test and one-way analysis of variance (ANOVA) were applied to investigate the differences in risk perception ability among miners with different alertness levels. Thirteen significantly different indicators were selected as feature variables. Thirteen significant differential indicators were selected as feature indicators, and Sine-SSA-BP was introduced to construct a classification and recognition model for miners' risk perception ability. The results show that miners' alertness significantly affects their risk perception ability. With increasing alertness, the correct rate of risk perception improves notably. As the alertness level rises, significant differences appear in the activation index β values of the dorsolateral prefrontal cortex and frontopolar areas. The mean skin conductance (SC_mean) in electrodermal activity (EDA) increases significantly, while the mean inter-beat interval (Mean_IBI), standard deviation of normal to normal R-R intervals(SDNN), and root mean square of successive differences (RMSSD) in heart rate variability (HRV) decrease significantly, and mean heart rate (Mean_HR) increases. The constructed miners' risk perception ability classification and identification model based on the Sine-SSA-BP achieves an accuracy of 92.30%, demonstrating excellent overall performance and robustness.

    Influence mechanism of authentic leadership style on safety behavior of flight cadets
    WANG Yanqing, FENG Weiran, JIANG Gan
    2026, 36(2):  9-17.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1137
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    In order to improve the development of safety behavior of flight cadets and enhance the level of flight training, conduct an indepth exploration of the relationship and intrinsic mechanism between authentic leadership style and safety behavior of flight cadets, a theoretical model of the safety behavior of flight cadets based on the authentic leadership style theory was constructed. The questionnaire was developed by drawing on established scales and consulting experts to align it with the current training conditions of aviation schools. AMOS26.0 software was used to test the mediating effect of authentic follow and the moderating effect of basic psychological needs satisfaction, and verify the effect on all constructs, the applicability of the theoretical model of flight cadets safety behavior in different stages of learning to fly, flight level, instructor job groups and work environment. The results show that there is a positive correlation between the authentic leadership style of flight instructors and the safety behavior of flight cadets, and the authentic follow of flight cadets plays a mediating role between the two. The authentic leadership style has a positive impact on authentic follower, and the basic psychological needs satisfaction plays a moderating role in this process. Different groups between the four dimensions of stages of learning to fly, flight level, instructor job groups and work environment have no moderating effect on the model, further verifying the structural stability of the model.

    Method of coupling identifying unsafe behaviors of underground personnel based on dual-model algorithm
    TAN Bo, SUI Longkun, KE Wei, LIU Yan, ZHU Quanjie, HE Ning
    2026, 36(2):  18-26.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1372
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    In order to prevent safety accidents caused by unsafe behaviors of underground personnel and to ensure their safety, by utilizing advanced machine vision and computer technologies, the traditional YOLOv5s algorithm and OpenPose algorithm target detection models were improved, and a dual-model coupled algorithm for identifying unsafe behaviors of underground personnel was proposed. Through statistical analysis of the most common unsafe behaviors in current underground coal mines, the unsafe behaviors of miners were classified, including item-related, action-related, and area-related unsafe behaviors. According to the characteristics of miners' unsafe behaviors, the improved YOLOv5s algorithm and the OpenPose algorithm were coupled for recognition, and training and verification were conducted on public datasets and self-built datasets. The results show that compared with the current mainstream methods, the dual-model coupled recognition method has a significant improvement in recognition accuracy on self-built datasets and public datasets, with an increase of 5% to 10%, and can quickly and effectively identify unsafe behaviors of underground personnel.

    Association analysis between driving-scenario-induced negative emotions and cognitive load in drivers
    WANG Weiwei, WEN Zhiqiang, YANG Xiaoyan, PENG Qizhao, ZHANG Zihao, SHI Congge
    2026, 36(2):  27-36.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0459
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    In order to reduce traffic safety incidents, the mechanism by which negative emotions affect drivers' CL was investigated, and the influence of driving scenarios on emotional intensity and multi-channel CL levels was analyzed. A simulated driving experiment was designed, integrating emotion-inducing materials with a driving simulator, and young drivers were recruited to complete driving tasks. The interaction characteristics between negative emotions and CL were systematically examined through the Self-Assessment Manikin (SAM) scale, the VACP multidimensional assessment model, and retrospective interviews. The results indicate that negative emotions significantly increase CL. Specifically, anger and fear tend to trigger transient fluctuations in load, whereas anxiety is associated with the highest average load level. Furthermore, stressors embedded in driving scenarios induce negative emotions of varying intensities: aggressive cut-ins and sudden lane changes commonly elicited high levels of anger. Traffic accidents and pedestrians running red lights predominantly evoke intense fear, and unfamiliar routes primarily trigger heightened anxiety. Finally, emotional intensity is significantly positively correlated with CL level, highly arousing emotions lead to a substantial increase in the demand for visual, cognitive, and motor resources.

    Theoretical basis, constituent elements and construction methods of behavioral risk profiling
    WANG Leyao, LI Xin, WU Qi, TONG Ruipeng
    2026, 36(2):  37-43.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0902
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    In order to address the managerial complexities arising from the multi-causal and dynamic nature of unsafe behaviors in high-risk industries such as mining and construction, and to overcome the "one-size-fits-all" limitations of traditional behavior-based safety management in the era of informatization and intelligence, this paper introduces the concept of behavioral risk profiling based on the developmental trajectory of behavioral safety and risk profiling theory. By employing literature review methodology and integrating interdisciplinary perspectives, this study systematically examines the constituent elements and construction methods of behavioral risk profiling. The findings reveal that behavioral risk profiling effectively addresses the growing limitations of traditional behavior-based safety management, providing a powerful analytical and managerial tool for the new era. Through a four-layer labeling system comprising work scenarios, behavioral manifestations, risk factors, and risk assessment, it systematically reveals the mapping relationships of unsafe behaviors from phenomena to their underlying essence. On this basis, a construction methodology is developed following the logic of hierarchical data collection, risk-based group assessment, and personalized intervention.

    Prediction of pilot human errors during the carrier landing phase under complex task environments based on an improved CREAM method
    LIU Weicheng, SUN Youchao, JIN Heng, CHEN Zichang
    2026, 36(2):  44-51.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0102
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    To improve the safety of aircraft landing phase, this study investigates the prediction of pilot human error during the carrier landing phase complex task environments based on CREAM. Based on the pilot operational workflows during the carrier landing phase, this work recalibrates the original Common Performance Condition (CPC) factors in CREAM, and proposes an improved approach for predicting the probability of human error in pilots based on the improved CREAM method, describing the situational environment in which the pilot is located during the carrier landing phase. It introduces an Environmental Impact Index and Effect Impact Index to characterize the influence of various task environments on pilots' cognitive functions. A simulated carrier landing assessment experiment is designed and conducted based on the actual situational environment during the carrier landing phase. By analyzing characteristic indicators such as electroencephalogram(EEG), eye-tracking, electrocardiogram(ECG), and electromyography(EMG)data, and National Aeronautics and Space Administration Task Load Index(NASA-TLX)scale data of the subjects, the load level of the subjects in different environments is assessed, and then the effect impact index of different cognitive functions is calculated to predict the probability of human error. The results demonstrate that the proposed method for predicting probability of human error in pilots can improve the accuracy of prediction results by using objective data assessment, which instead of experts' subjective evaluations. This method can predict the probability of human error in pilots under the influence of 20 different environmental factors.

    Safety Technology and Engineering
    Research status and prospect of road traffic safety of non-motorized vehicles
    HE Jie, CHEN Weiyu, CHEN Haoze, FANG Zhiming, QIN Pengcheng
    2026, 36(2):  52-65.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1404
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    The situation of road traffic safety of non-motorized vehicles remains severe, and extensive research has been conducted in China and abroad. To comprehensively analyze the research status and prospect, 448 Chinese papers and 860 English papers from 2000 to 2025 were selected from China National Knowledge Infrastructure (CNKI) and Web of Science (WOS). Subsequently, the papers were analyzed for keyword co-occurrence and cluster by CiteSpace, and on this basis, the research hotspots and prospect were summarized. The results indicate that current research shows a significant growth trend, and primarily focuses on four areas: risk of riding behaviors, road traffic accidents, mixed traffic flow conflicts, and traffic management strategies. Future studies should expand into diverse scenarios and deepen the application of multimodal data, with methodological support of computer vision technologies and machine learning algorithms to enhance research capabilities.

    Online monitoring of shaft structure performance driven by digital twins
    JIA Xiaofen, ZHAO Yuchen, ZHAO Baiting, HU Rui, LIANG Zhenhuan
    2026, 36(2):  66-76.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0105
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    To address the current issues of low intelligence level in coal mine working faces and insufficient research on the performance monitoring of shaft structures, a digital twin-based performance monitoring method for vertical shafts is proposed. Firstly, a five-dimensional framework for the digital twin of vertical shafts is proposed based on the operational mechanism and performance monitoring requirements of the shafts. Secondly, a digital twin of the shaft is established by combining virtual-real mapping technology with a finite element surrogate model for grid dimensionality reduction. The structural performance of the vertical shaft is predicted online through artificial neural network technology, where the predicted data is the real-time prediction of shaft structure performance data obtained during the shaft operation process using a shaft structure performance prediction model. The prediction model for the structural performance of the vertical shaft adopts the RBF surrogate model, and the Unity3D virtual engine platform is built to integrate the above functions and achieve online prediction of the structure performance of the vertical shaft. The results indicate that during the operation, by simulating 120 sets of stress and strain data under different working conditions, the average coefficient of determination between predicted and simulated values is 0.995 5, indicating a high correlation between the predicted strain and simulated strain, thus verifying the feasibility of the digital twin framework for vertical shafts. This provides an effective reference for the digital improvement of vertical shafts.

    Experimental study of powder-liquid co-decontamination for aqueous ammonia leak accident
    YUAN Bihe, ZHANG Guangyi, TAN Zhezhe, LEI Chunying
    2026, 36(2):  77-83.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0348
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    In order to address the safety and environmental risks associated with aqueous ammonia leakage accidents in the chemical industry, based on the rich pore structure and physicochemical properties of porous materials, AC and zeolite were selected as the basic raw materials for detergents. The powder detergents AC@AlCl3 and Zeolite@AlCl3 were prepared by impregnating with an AlCl3 solution of varying mass fractions. Using aqueous ammonia as the target contaminant, systematic experiments were conducted involving both individual decontamination and combined powder-liquid decontamination, employing the aforementioned modified powdered decontaminants along with various surfactants. By evaluating indicators such as decontaminant dosage, volume fraction of volatile gas, and the morphology of decontamination products, the effectiveness of individual versus combined decontamination was compared, and the practical performance of the powder-liquid synergistic decontamination strategy was comprehensively assessed. The results demonstrate a significant enhancement in the decontamination capacity of the modified powders, with decontamination efficiencies for aqueous ammonia exceeding 70%. Among the samples, AC@20%AlCl3, combined with a 3% NaHCO3 powder solution, forms a more complete gel-like solid during the decontamination process, and the decontamination efficiency reaches 80%. This approach successfully realizes the goals of high efficiency, cost-effectiveness, and safety in aqueous ammonia decontamination.

    Cascading effect analysis of IMA system for multi-phased mission in SPO mode
    DONG Lei, LIU Jiachen, SUN Zijing, CHEN Xi, WANG Peng
    2026, 36(2):  84-92.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0148
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    To address the problems of state-space explosion and unclear causal relationships in the safety analysis of IMA system under the future SPO mode, multi-phase mission profiles for the SPO mode were first defined, and the resident applications and fault criteria for different mission phases were identified. The concept of CEA was introduced, and a quantitative computational model for cascading fault propagation was developed. Methods for evaluating the probability of cascading faults and the cascade risk coefficient were designed to assess the propagation speed, scope, and impact severity of faults within the IMA system. Finally, a comparative analysis was conducted under an SPO scenario to examine how cascading faults affect the IMA system across different mission phases and initial fault conditions. The results show that the proposed model can characterize both the direct and indirect impacts of faults in the IMA system. When primary flight control and integrated navigation are initial fault events, cascading faults are more likely to occur, indicating that targeted backup, monitoring, or reconfiguration measures for key resident applications are required.

    Experimental study on explosion risk assessment of thermal runaway gas from aviation lithium batteries
    YANG Juan, LIANG Xue, BAO Fangwei, ZHANG Qingsong
    2026, 36(2):  93-101.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0183
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    To improve the accuracy of airworthiness assessment for aviation lithium batteries, this paper evaluated the feasibility of equivalent substitution of propane mixed gas in the explosion containment test of thermal runaway gases of aviation lithium batteries. Based on airworthiness standards, the explosion characteristics of standard volume fraction propane and in-situ thermal runaway gases from lithium batteries at different states of charge (SOC) were experimentally compared and analyzed. Ternary lithium batteries were employed, and a dedicated experimental platform was constructed to systematically measure the explosion temperature, maximum explosion overpressure, and pressure rise rate of the thermal runaway gases under different SOCs. The results indicate that the explosion limit range of the lithium battery thermal runaway gases significantly widens with increasing SOC, with a maximum explosion overpressure of 0.519 8 MPa and an explosion power index of 1.093 9. For propane within the standard volume fraction range (3.85% to 4.25%), the maximum explosion overpressure reached 0.822 5 MPa, with an explosion power index of 1.501 7, its explosion potential being higher than that of thermal runaway gases under most SOC conditions. Directly adopting the standard propane concentration for explosion containment verification may lead to over-testing, resulting in an excessively high safety margin. Propane can serve as a preliminary assessment medium, but for equivalent substitution, the test concentration needs to be optimized in combination with the actual SOC state.

    A nuclear environment monitoring method based on ionizing radiation response characteristics in visual images
    HUANG Youjun, YOU Qiongyu, XU Shoulong, HOU Zhixiong, PENG Guowen
    2026, 36(2):  102-109.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0619
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    This article proposes a nuclear environment monitoring method based on ionizing radiation response characteristics in visual images. Through experimental analysis of the response characteristics of ionizing radiation to visual images, including statistical parameters such as mean, variance, skewness, and kurtosis of pixel values, the relationship between feature data and radiation dose rate was quantified, and the high-precision linear correlation of the fitting was verified. A two-dimensional wavelet packet decomposition is used to analyze high-frequency components in video images, and an algorithm is proposed to extract radiation response signals from complex backgrounds, achieving accurate monitoring of gamma ray radiation dose rates in nuclear environments. The experimental results indicate that within the gamma ray radiation dose rate range of 51.61 Gy/h to 479.24 Gy/h, there is a significant linear relationship between the number of response events and the dose rate. The correlation coefficients of the fitted curves are 0.998 9 and 0.999 3, respectively. In terms of pixel response characteristics, the mean and variance significantly increase with increasing dose rate, while skewness and kurtosis show an exponential downward trend. In addition, the experiment verified the influence of setting the pixel value threshold on radiation dose rate measurement. When the pixel value threshold is 130, the linearity of the fitting results is optimal. By using two-dimensional wavelet packet decomposition, the statistical analysis of high-frequency components in the image has further improved the accuracy of dose rate characterization, especially achieving maximum linearity in the diagonal components. This method can efficiently extract radiation response information in complex environments, achieve precise monitoring of gamma ray dose rates in nuclear environments, and provide technical support for emergency response to nuclear leaks and assessment of radioactive areas.

    Fatigue crack initiation life prediction of thermal pipelines under multi-defect interaction
    MA Shuqi, LIU Xinquan, LYU Shuran
    2026, 36(2):  110-120.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0231
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    To address the challenge of accurately predicting the fatigue crack initiation life caused by surface pitting corrosion in buried thermal pipelines during design, operation, and maintenance, this study employed the finite element method to investigate the influence of pit morphology, defect interaction, and axial loading on the maximum stress concentration factor Kt. An empirical formula for Kt was proposed, and a prediction method for fatigue crack initiation life under soil corrosion was developed. A pipeline in service in Beijing was used as a case study to verify the scientificity and effectiveness of this method. The results indicate that a 10-fold increase in pit depth leads to a 2.84-fold increase in Kt, while a 10-fold reduction in pit circumferential width results in a 4.75-fold increase. Deep and narrow defects characterized by a/c > 0.6 and b/c < 0.6 exert a stronger effect on increasing Kt and significantly shorten crack initiation life. When the defect spacing d=0, Kt reaches 1.03 times that of a single defect. The smaller the defect spacing, the stronger the interaction effects and the lower the crack initiation life. As defect spacing decreases, the fatigue crack initiation life of deep narrow pits is reduced to 0.12 times the original life, whereas shallow wide pits are more sensitive to spacing, with their crack initiation life reduced to 0.83 times the original life. Under conditions of low soil resistivity, low pH, and elevated temperature, crack initiation may occur within 20 years. The crack initiation life of shallow wide pits is more sensitive to soil parameters. Compared with internal pressure loading alone, an axial compressive load of 20 MPa significantly reduces crack initiation life by 0.74 times. Increasing axial tensile load from 20 MPa to 50 MPa results in a further life reduction of 0.82 times.

    Risk assessment model for embankment slope failure in mining goafs
    ZHAO Bo
    2026, 36(2):  121-126.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0206
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    To address the challenges in accurately describing uncertainty and multiple failure modes in the risk assessment of embankment slope failures in goaf areas, a risk assessment model based on an improved T-S fuzzy fault tree approach was proposed. Initially, Gaussian fuzzy numbers were introduced to characterize the failure states and occurrence probabilities of basic events, thereby addressing the over-reliance on precise probabilistic data in conventional fault tree analysis and the insufficient representation of intermediate event states. Subsequently, T-S fuzzy model was employed to replace traditional AND/OR relationships in logic gates, capturing the uncertainty and fuzzy characteristics among events, and thereby deriving the failure probability of slope collapse. Finally, an engineering case study was conducted for validation. The results demonstrate that the proposed approach simplifies the fault tree construction, identifies the key risk factors leading to slope failure, provides a ranking of their influence, and reveal the intrinsic relationships between failure events and various factors.

    Deformation and failure mechanisms of open-pit mine rock slopes under water level fluctuations
    SUN Zuo, TONG Ruipeng, QI Qingjie, LIU Yingjie, GAN Yixiong, MENG Cheng
    2026, 36(2):  127-135.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1577
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    To investigate the instability of rock slopes along joint surfaces in water-impounded abandoned open-pit mines under fluctuating water-level conditions, physical model tests were performed using similar materials containing joints and weak interlayers. The mix proportion of the similar materials was optimized through orthogonal experimental design to ensure that their mechanical and seepage properties corresponded to those of the in-situ rock mass. Multiple types of sensors were embedded in the model to monitor pore water pressure, earth pressure, moisture content, and displacement, enabling systematic observation of the multi-field responses of the slope during water-level fluctuations. Working conditions with different numbers of cycles and varied rates of water-level change were designed to examine the deformation characteristics and failure mechanisms of the slope. The results indicate that certain damage to the slope surface is caused by the scouring effect induced by repeated water-level fluctuations at a constant rate, although internal structural damage is limited. This suggests that overall stability is little influenced by slow, single water-level fluctuations. The rate of water-level change is shown to significantly affect slope behavior, with slope displacement increases positively correlated with the rate of water-level decline. Furthermore, the greater the outward-directed pore water pressure of the slope is, the more significantly it is influenced by the hysteresis effect, and the higher likelihood of slope instability becomes.

    Defect diagnosis method for oil and gas pipelines based on fusion of Welch power spectrum and multi-scale residual network
    LIAO Chunyan, LIANG Wei, LIU Shuanglei, HUANG Tianchang
    2026, 36(2):  136-144.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0599
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    To address the problem of reduced defect classification accuracy caused by noise contamination in the bend detection signals of oil and gas pipelines, this paper proposes an oil and gas elbow defect diagnosis model based on Welch power spectrum feature enhancement and multi-head attention improved dual-branch multi-scale-residual collaborative network. Firstly, the Welch method was used to convert the collected time domain signal into a feature-enhanced power spectrum, showing the energy distribution of the defect signals at different frequencies. Secondly, the multi-scale network branch composed of parallel stacked convolutional layers was responsible for extracting the multi-dimensional features of the signal power spectrum, and the multi-head attention mechanism was used to establish long-term associations between features. Simultaneously, the residual network branch captured the detail information of the signal power spectrum. Finally, the deep concatenation layer fused the features extracted by the dual-branch network to achieve defect classification. The experiment results show that in a high-noise environment, the test accuracy of the proposed model is 91.6%. Compared with the models based on Kaiser windows and flat-top windows, the classification accuracy is improved by 1%~7.9%; compared with convolutional neural network (CNN) and long short-term memory network (LSTM), the accuracy is improved by 36.9% and 10.3% respectively.

    Equivalent permeation aperture identification method for geomembranes based on seepage-sensing structure
    JIN Chenchen, DING Yong, LI Denghua
    2026, 36(2):  145-152.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0588
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    To improve the seepage monitoring level of pumped storage reservoirs, a discrimination method was proposed for seepage caused by geomembrane aperture damage, based on a seepage-sensing structure and the concept of an equivalent seepage aperture. First, the temperature rise difference between dry and wet conditions was acquired through active heating, and a logarithmic linear fit was performed after normalizing the temperature rise difference with respect to the seepage velocity. Then, a linear fit was established between the seepage velocity and the equivalent seepage aperture. The seepage condition was inferred based on field calibration tests combined with the characteristics of distributed temperature sensing (DTS) curve. Finally, laboratory tests were conducted for validation. The results show that the goodness-of-fit (R2) between differential temperature and the equivalent seepage aperture exceeds 0.96, and the relative error of seepage velocity is below 5%. 86% of the residuals between experimental and simulated temperature rise values fall within ±1℃, and the relative error of seepage velocity also remains below 5%, demonstrating the reliability of the simulations.

    Reconstruction and analysis of PNM for free accumulation of rock blocks in fully mechanized top-coal caving goaf of coal mines
    ZHANG Hongshuo, GAO Ke, YU Jiankang, LI Qiwen
    2026, 36(2):  153-162.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1508
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    To accurately characterize freely accumulated rock blocks and pore space properties in fully mechanized top-coal caving goafs, a PNM was introduced. Slice tests of free rock block accumulation in fixed space and corresponding image processing were conducted. Pore network information was extracted using Open-source libraries like OpenPNM and PoreSpy, followed by 3D visual reconstruction and quantitative characterization of PNM to analyze topological geometric and statistical features of the reconstructed model. Results show that with increasing freely accumulated rock block size in fixed space, pore-throat size increases significantly: the average diameters of pores and throats rise from 2.46 mm and 1.41 mm to 3.85 mm and 2.73 mm, respectively, with weak correlation to throat length. The numbers of pores and throats decrease from 3 146 and 6 428 to 1 043 and 2 225, respectively, and the pore coordination numbers concentrate between 2 and 5 (peak at 2). The proportion of pore space increases, and the connectivity of porous media is enhanced. The topological property parameters are approximately positively skewed distribution as a whole, with the peak shewed to the left and the concentrated values in the dataset being relatively small. Two-point correlation function calculations reveal that the relative errors of porosity between the original image data and the reconstructed model are less than 2.5%.

    Prediction model of blasting fragmentation based on GA-QLightGBM quantile regression
    WANG Shuxian, YANG Yi, SHI Yulian, SHEN Yaxi
    2026, 36(2):  163-171.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0434
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    To address the challenges of high uncertainty and complex influencing factors in predicting blast fragmentation in mining operations, this study proposed a LightGBM prediction model GA-QLightGBM that integrated GA optimisation with quantile regression. First, GA was employed to optimise the hyperparameters of LightGBM by simulating the natural selection process (selection, crossover, and mutation), thereby improving the model's predictive accuracy and stability. Then, different quantiles were set to construct prediction intervals for blast fragmentation, enabling the quantification of prediction uncertainty. Finally, the proposed model was applied to mine field datasets to verify its predictive performance and generalisation ability, providing an effective approach for blast fragmentation prediction and uncertainty analysis. The results show that the model achieves a coefficient of determination (R2) of 0.880 and a mean squared error (MSE) of 0.004 in point prediction, outperforming traditional point prediction models. In interval prediction, the prediction interval coverage probability (PICP), prediction interval normalized average width (PINAW), and corrected prediction interval accuracy (CPIA) are 0.947, 0.228, and 0.762, respectively, confirming the accuracy and reliability of GA-QLightGBM model. These findings offer a practical framework for quantifying the uncertainty of blast fragmentation, supporting refined blast design and risk control in mining engineering.

    Public Safety and Emergency Management
    Research on scenario structured representation of accident disaster emergency rescue system:taking coal mine accident rescue as an example
    GUO Hanjun, ZHANG Yuebing, ZHOU Aitao
    2026, 36(2):  172-179.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1614
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    To standardize the scenario representation of accident disaster emergency rescue systems, improve the efficiency of information transmission and the level of scientific decision-making in the emergency rescue process, literature research and case analysis methods were applied to integrate existing theoretical achievements. The scenario elements of the accident disaster emergency rescue system were extracted from three dimensions: system structure composition, interaction between components, and temporal evolution process. The connotation, extension, structure, and function of each element were clarified. A mathematical model was constructed to demonstrate the feasibility of predicting the next state based on the current state and interaction relationship. The results indicate that the proposed scenario element system is consistent with the knowledge element theory framework, and the dynamic evolution characteristics of the accident disaster emergency rescue system can be systematically characterized.

    Study on inhibition effect of active composite powder for methane explosions
    ZHAO Tenglong, WANG Fengxiao, LI Zihao, YIN Xiaotong
    2026, 36(2):  180-188.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0668
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    To obtain the powder suppressant with greater inhibition effect, NaHCO3, Al(OH)3, K2CO3 and NH4H2PO4 were mixed by a compounding method, and a new composite powder was obtained. A visual spherical vessel was applied to study the effects of the composite powder with different mixing ratios on methane explosion overpressure, flame propagation and free radical production. The results indicate that as the mass proportion of NaHCO3, Al(OH)3, K2CO3 and NH4H2PO4 is 1∶1∶2∶1, the inhibition effect of composite powder is significantly greater than that of the single powder. The synergistic mechanisms of the composite powder are as follows: Before 250 ℃, the composite powder undergoes a metathesis reaction, a large number of gases such as H2O, CO2 and NH3 are released. In the early stage of methane explosion, the energy is absorbed and methane is diluted by the gases, so the rapid flame propagation is inhibited. NH4H2PO4 plays a role in absorbing C-containing free radicals during methane combustion. This effect is enhanced when powder is mixed, leading to a further inhibition for methane combustion reaction.

    Effects of particle morphology on transient dispersion and explosion flame propagation of aluminum powder
    QIU Dongyang, CHEN Xianfeng, LIU Lijuan, HUANG Chuyuan, WANG Jun, SUN Xuxu
    2026, 36(2):  189-198.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0582
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    To investigate the influence of particle morphology on the explosion characteristics of aluminum powder, spherical aluminum powder (SAP) and flake aluminum powder (FAP) were selected as research subjects. By combining particle image velocimetry with vertical duct explosion experiments, the effects of particle morphology on transient dispersion behavior and flame propagation characteristics were systematically analyzed. The results show that FAP, due to its larger specific surface area and the asymmetric geometry, exhibits stronger suspension capability and turbulence-inducing effects, leading to a more uniform dispersion state under the same mass concentration. Influenced by enhanced turbulence, increased particle population in the critical ignition zone, and greater suspension stability, FAP demonstrates faster ignition response and significantly promoted flame front wrinkling. At a concentration of 350 g/m3, its flame propagation velocity reaches 44.1 m/s, which is 32.8% higher than that of SAP. In contrast, SAP tends to form localized high-mass concentration regions due to agglomeration, resulting in a white overexposure area accounting for 98.6% during the explosion, indicating a more concentrated heat release behavior.

    Evaluation of emergency management capability for construction safety accidents based on FRAM-BN
    LI Zhijian, SHE Jianjun, LU Cong, GUO Zihao, ZHOU Yilun
    2026, 36(2):  199-208.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1492
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    To scientifically evaluate and enhance construction enterprises' emergency management capabilities for sudden safety incidents, a comprehensive model integrating qualitative analysis and qunatitative evaluation was proposed, addressing the limitations of traditional static assessment methods, which struggle to capture functional coupling and are easily influenced by subiective weighting. First, based on the theory of balanced emergency management throughout the entire process, a complete evaluation indicators system was established by dentifying 12 secondary indicators across four stages, including preparation and prevention, monitoring and early warning, response and disposal, and recovery and learning, and integrating the trajectory intersection theory and catastrophe theory. Subsequently, FRAM was employed to identify key functions and coupling paths among these indicators. An evaluation model was then developed by integrating an improved K-shell algorithm with BN. Finally, the model was applied to a practical engineering case and its effectiveness was validated through expert review and scenario simulations. The results demonstrate that the selected construction enterprise has a comprehensive emergency management capability of 81.682%, indicating its emergency mechanism can effectively respond to and handle various construction safety incidents. Among the capabilities, recovery and learning performs best (90.855%), while monitoring and early warning remains relatively weak (76.616%). Sensitivity analysis shows that professional team development (F3) and on-site command decision-making (F7) contributed most significantly to the overall capability.

    Characteristics of temperature field on fire-unexposed surface of window glass under varying fire locations
    LI Zhihan, ZHANG Guowei, WANG Jiangxue, YU Longfei, LI Junyi
    2026, 36(2):  209-217.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0500
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    To address the challenge of locating the fire source in high-rise building fires, a full-scale indoor fire test platform was constructed and a series of tests were conducted to investigate the feasibility of inferring fire locations from the temperature field on the fire-unexposed surface of window glass in high-rise building fires. By varying the fire location and heat release rate, the temperature field on fire-unexposed surface and fire environment parameters were obtained, and the characteristics of fire-unexposed surface temperature field under different scenarios were analyzed. The results show that window glass regions at higher elevations and on the fire side exhibit significantly higher temperature rise rates under different fire location conditions. At 480 s after ignition, the temperature non-uniformity coefficient of fire-unexposed surface under different fire location conditions is not less than 33.52%, and reductions in the distance between fire location and window lead to a marked increase in the temperature non-uniformity coefficient on the fire-unexposed surface. With increasing heat release rate, the coefficient of variation of the increase in temperature rise rates across different glass regions on the fire-unexposed surface generally exceeds 10%, and this disparity becomes more pronounced with increasing heat release rate. When the normal distance between the fire location and the window decreases, window glass at higher elevations and on the fire side exhibits a greater increase in temperature rise rate. When the radial distance between the fire location and the window decreases, the increase in temperature rise rate at higher elevations is significantly greater than that on the fire side.

    Research on security resource allocation optimization of critical infrastructure
    HUANG Jicheng, CHEN Wenjing, JIA Nan
    2026, 36(2):  218-226.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0519
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    In order to improve the rationality and effectiveness of critical infrastructure security resource allocation, and solve the shortcomings of traditional methods in the balance of security resource allocation and protection effectiveness, an optimization model of critical infrastructure security resource allocation was constructed based on PT, ASD and Stackelberg game theory. Firstly, the ASD-Stackelberg game model was constructed to solve the optimal spatial allocation of security resources within critical infrastructure. Secondly, the PT theory was introduced to describe the bounded rationality characteristics of both attack and defense sides, and the optimal security resource investment threshold was determined. Finally, the nuclear power plant security system was taken as a case study. The verification and analysis results show that compared with the traditional empirical configuration method, the optimal resource allocation scheme output by this model has significantly improved the overall security effectiveness of nuclear power plants by 25.9%, and can accurately identify the optimal amount of security resource investment. This result not only confirms the effectiveness and feasibility of the model in solving the optimal configuration scheme, but also quantitatively establishes its significant superiority in enhancing security protection capabilities.

    Study on suppression effect of dry ice on thermal runaway of lithium-ion battery cells
    LIU Yongcheng, ZHANG Guowei, ZHAO Gangqiang, LIU Chunyuan, YU Longfei, CHEN Zewei
    2026, 36(2):  227-234.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0422
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    To develop a novel and effective fire-extinguishing agent dedicated to lithium-ion batteries, this study established an experimental platform. Experiments were conducted on 20 Ah lithium-ion phosphate batteries to investigate the inhibitory efficacy of dry ice on the thermal runaway of lithium-ion batteries. Experimental results indicate that dry ice can successfully inhibit the thermal runaway process of lithium-ion batteries: specifically, spraying 1.5 kg of dry ice in the experiment effectively blocked the early-stage thermal runaway of the battery. Furthermore, the inhibitory efficacy of dry ice on battery thermal runaway shows a positive correlation with its spray amount—increasing the dry ice spray amount to 2.6 kg enabled successful suppression of the battery's severe thermal runaway stage. In addition, the phase change heat absorption rate of dry ice is positively correlated with the ambient temperature gradient; however, the cooling rate and effective utilization rate of dry ice do not increase with the rise in spray amount or ambient temperature. In the experiment, when the dry ice spray amount was increased from 0.65 kg to 2.6 kg before battery pressure relief, both the cooling rate and effective utilization rate of dry ice exhibited a trend of first increasing and then decreasing. Moreover, as the severity of thermal runaway and ambient temperature increased, the two decreased from 67.5% and 7.8% to 15.4% and 4.1%, respectively. This study may provide a reference for the development of lithium-ion batteries fire-extinguishing agents.

    Occupational Health
    Path analysis of negative emotions in high-noise-exposed male workers based on Bayesian network models
    DUAN Xinyun, LI Linyue, MA Jingxuan, WANG Yongwei
    2026, 36(2):  235-243.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0322
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    In order to explore the influencing pathways of negative emotions among occupational noise-exposed workers, 493 male workers with high noise exposure from five typical manufacturing enterprises were recruited as subjects. Data were collected through occupational health surveys, noise measurements, and psychological scales. Key variables, including age, cumulative noise exposure (CNE), marital status, and nine other factors, were screened using the least absolute shrinkage and selection operator (LASSO) regression, based on which a Bayesian network model was constructed. The results showed that the detection rate of negative emotions among male workers was 5.7%, with an average noise exposure level of 91.5 dB(A). The model identified multiple influencing pathways, and their probability distributions varied across age groups: in the <30 years group, the pathway “age → marital status → negative emotions” was predominant (16.4%); in the 30-39 years group, the direct pathway “age → negative emotions” was most prominent (30.6%); while in the ≥40 years group, the pathway “age → CNE → negative emotions” was dominant (21.5%-29.4%). Moreover, the high CNE group generally exhibited a higher probability of negative emotions than the medium exposure group. The study indicates that negative emotions among male workers under high noise exposure are interactively influenced by factors such as age, CNE, smoking, drinking, and marital status. The Bayesian network model effectively reveals these complex pathway relationships.

    Intelligent Safety Technology
    Impact of human-AI trust on collaborative decision-making quality: mediating role of human-AI shared mental model
    NIU Lixia, LIN Yanhong
    2026, 36(2):  244-252.  doi:10.16265/j.cnki.issn1003-3033.2026.02.1791
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    In order to enhance human-artificial intelligence(AI) collaborative decision-making quality in complex industrial environments, mitigate the deficiency of human trust in AI, and bridge cognitive gaps in human-AI collaboration, based on the theory of mind, the study constructed a model of the relationship between human-AI trust, Human-AI SMM and human-AI collaborative decision-making quality, and task complexity was introduced as a moderating variable. First, hypotheses were proposed based on the theoretical relationships among the variables, and a questionnaire was designed by integrating the human-AI trust scale, Human-AI SMM scale, the human-AI collaborative decision-making quality scale, and the task complexity scale. Then, the questionnaires were distributed to frontline employees of AI-using companies nationwide, and 493 valid samples were collected. Finally, SPSS 26.0, AMOS 24.0 and Process 4.0 were used for data analysis and hypothesis testing on the collected valid samples. The results of the study show that human-AI trust significantly and positively affects human-AI collaborative decision-making quality. Human-AI SMM mediates the relationship between human-AI trust and human-AI collaborative decision-making quality. Task complexity positively moderates the relationship between human-AI trust and Human-AI SMM.

    Evolutionary game research on multi-body dynamic governance of intelligent coal mine safety risks
    REN Lipeng, TONG Ruipeng
    2026, 36(2):  253-261.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0247
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    To improve the current situation of frequent disasters and accidents in coal mines, the game behaviors among various stakeholders in the dynamic governance of intelligent coal mine safety risks were investigated. A tripartite evolutionary game model was constructed involving the government, coal mine enterprises, and miners, to analyze the evolutionary stability among the three parties. Additionally, evolutionary game scenario simulations were employed to mimic the actual context of intelligent coal mine safety risk governance. Through this, the influence processes of factors such as governmental regulatory intensity and benefit-sharing ratio on the strategies of the gaming participants were revealed. The results indicate that governments should appropriately apply reward and punishment mechanisms during the regulation of enterprise safety governance. This approach can enhance corporate attention to safety risk management, reduce regulatory costs, and promote synergistic benefits between government and enterprises. High governance costs tend to reduce corporate enthusiasm for compliance and may encourage opportunistic behavior; therefore, incentive mechanisms and cost-sharing strategies are necessary to alleviate the burden on enterprises. Encouraging miner participation and reducing their involvement costs contribute to faster identification of potential safety risks and help prevent accidents.

    Safety evaluation and control of shield tunnel underpass buildings based on entropy weight cloud model
    WANG Shangang, YU Qunzhou, YU Jingju
    2026, 36(2):  262-270.  doi:10.16265/j.cnki.issn1003-3033.2026.02.0643
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    In order to solve the problems of incomplete index system, low accuracy of calculation results and weak applicability of control measures when evaluating the safety of shield tunneling underpasses, a method for evaluating the safety status of shield tunneling underpasses was studied based on entropy weight cloud model. By analyzing various factors affecting the safety status of the project, it was determined that overall safety level was jointly determined by the original safety level of building and disturbance effect of underpass construction process. An original safety status evaluation index system for buildings was established, which consisted of 13 indicators in three categories: the existing deformation resistance of the building, the healthy and intact state of the building, and the importance of building. A safety evaluation index system for underpass construction process was established, which consisted of 22 indicators in five categories: excavation face instability, displacement of soil on side of shield machine ring, subsequent soil consolidation, construction management level, and relationship between building and tunnel. The weights of each index were determined by entropy weight method, the digital characteristics of the index were determined based on the cloud model, safety level and development trend were determined by FSM algorithm, and the weighted fitting weight value was used to judge the primary and secondary risk control points. Taking a subway project under two buildings as an example, the index system and evaluation method were verified. The results show that original safety status of two buildings and the construction process under two buildings are generally safe, and overall risk is within an acceptable range. For secondary indicators that are not inherent attributes of the project, the factors with weighted fitting weight values exceeding the average level (0.04) are used as key control points, those between 0.02 and 0.04 are used as secondary control points, and those between 0 and 0.02 are used as general control points.