In order to reduce the occurrence of accidents during construction in urban underground spaces, a combined methodology of content analysis and social network analysis was employed to deconstruct human factors in accidents during urban underground space construction for risk reduction. Firstly, based on PAR accident causation model, a tri-dimensional analytical framework of "Subject-Factor-State" was developed for human-induced accidents in urban underground construction. Secondly, authentic accident cases were utilized to encode and extract causal factors, while causal subjects and states were systematically identified. Finally, a structural model of human-induced causation was constructed through network co-occurrence, centrality analysis, and correlation analysis to reveal inherent causal mechanisms. Key findings reveal: Collapse, poisoning, and suffocation constitute the predominant accident types, with 24 high-frequency human factors identified, including 9 core contributing factors. The structural model demonstrates that decision-making managers bear critical safety responsibilities among causal subjects. The core factor "inadequate safety technical disclosure", functions as a pivotal risk hub significantly influencing the causal network. Causal states exhibit strong interdependencies, particularly highlighting the pronounced interaction between information deficiency and other states.

In the scenario of air-ground collaborative autonomous operations, the collision risk of aircraft was assessed to ensure operational safety. The collision risk of parallel routes under autonomous flight was studied based on human factors and the performance of CNS systems. Firstly, an in-depth analysis of the characteristics of autonomous operation scenarios was performed. The Cognitive Reliability and Error Analysis Method (CREAM) model was improved by incorporating cognitive behavior and interactions between pilots and air traffic controllers to assess human reliability in autonomous operations. Subsequently, combined with the CNS performance and human factors, a collision risk model for autonomous operation aircraft was established. The lateral, longitudinal, vertical, and overall collision risks of the aircraft were evaluated separately. The feasibility of this method was validated through a parallel route example, and the impact patterns of human reliability and CNS performance on the collision risk of parallel routes were analyzed. The results indicate that the collision risk values in all three directions and the overall risk remain below the target safety level (5×10^-9). Furthermore, it is demonstrated that improving human cognitive reliability and CNS performance contributes to reducing the spacing between parallel routes, thereby enhancing the safety of autonomous operations.

In order to reduce the accidents in industrial scenarios which were caused by workers'unsafe operation behaviors, meanwhile improve the performance of visual-based action recognition methods in industrial scene with poor lighting, limited field of view and occlusions, an improved decision-making strategy based on self-adaptive ER (S-ER) was introduced in this paper. This strategy could integrate video information and inertial measurement unit (IMU) information effectively. It firstly analyzed video information and IMU information with attention mechanism-based multi-task convolutional 3D (M-C3D) model as well as one-dimensional convolutional neural network (1D-CNN) fused with attention mechanism, then ER theory was introduced to achieve decision-level fusion, where the set of evidence weights and reliability under different environmental conditions was optimized through the firefly optimization algorithm for improving the recognition accuracy and robustness of the model. The effectiveness of the proposed algorithm was verified on the public dataset Multimodal Human Action Dataset from University of Texas at Dallas(UTD-MHAD) and the self-built dataset Multimodal Human Action Dataset from Zhongyuan University of Technology(ZUT-MHAD). The results show that the identification results of S-ER for workers'unsafe behaviors in complex industrial scenarios can reach up to 98.53%, which is 17.52% higher than the maximum value of traditional multimodal fusion methods and single-modality recognition methods.

To explore more efficient fire extinguishing techniques for Chinese liquor warehouses, based on the similarity theory, an experimental bench for liquid CO₂ fire extinguishing with dimensions of 5 000 mm×2 400 mm×2 900 mm was constructed. An in-depth study was conducted on the changes in Chinese liquor quality, temperature distribution, and gas volume fraction during the process of extinguishing Chinese liquor pool fire using liquid CO₂ fire extinguishing systems with different combustion disk diameters. The research results indicate that liquid CO₂ can effectively extinguish Chinese liquor fires. The larger the diameter of the combustion disk, the more significant the change in mass. The larger the diameter of the combustion disk, the higher the temperature that can be reached by the Chinese liquor pool fire, up to 340 ℃. The extinguishing time under three different combustion disc diameters is 32, 36, and 38s respectively, and there is no re-ignition phenomenon. The highest gas volume fraction of CO₂ in the fire scene space can reach 26%. The distribution of CO₂ content at measurement points G₁-G₄ under different combustion disc diameters is as follows: G₄ > G₃ > G₂ > G₁. The distribution of CO content is: G₃ > G₄ > G₁ > G₂. The distribution of O₂ content is G₁ > G₂ > G₃ > G₄.

To solve the challenges in supporting fractured roof coal seam roadways, a rock layer detection recorder was used to conduct tests on the coal seam roadways at Xindeng mine. The analysis focused on the evolution characteristics of surrounding rock fractures. The R value for the direct roof rock and the β coefficient for roof fragmentation were introduced as evaluation indicators for roadway surrounding rock stability. The surrounding rock was categorized into four types: easy to support, relatively easy to support, relatively difficult to support, and difficult to support. Specific support parameters were provided for each category. Zoned support technology was applied in the gas drainage chamber of +90 North wing of Xindeng mine, achieving excellent support results. The study shows that the state of the roof surrounding rock is zoned, with the shallow fractured zone, followed by the fractured-fracture mixed zone, the developed fracture zone, and the intact surrounding rock zone. Through fracture analysis, it is found that the width of the roof fracture zone gradually expands to the deep surrounding rock over time, and the number of fractures also increases. The existing support cannot effectively control the continuous deterioration of the surrounding rock integrity.

In order to understand the characteristics of water transport during spontaneous infiltration and absorption of coal of different rank, coal samples from Mengtai Manlailiang mine, Jiulishan mine, Tiandiwangpo mine, and Pingdingshan No.10 mine were taken as the research objects, The T₂ spectrum of water in the coal sample at different times during the imbibition process was measured by using the low-field NMR experimental system, and the variation of water in the coal sample with time and space during the imbibition process was explored based on the change of water quality in the coal sample. The results show that the wettability of low-rank coal is better than that of high-rank coal and medium-rank coal, and the imbibition capacity of low-rank coal is the largest under the same experimental conditions, followed by high-rank coal, and the imbibition capacity of medium-rank coal is the smallest. According to the change of water in the process of coal sample imbibition with time, the coal sample imbibition process can be divided into three stages: the initial stage of imbibition, the middle stage of imbibition and the late stage of imbibition. In the early stage of imbibition, the sensitivity of low-rank coal to hydraulic action is higher than that of high-rank coal and medium-rank coal, and the imbibition velocity of low-rank coal is the largest, followed by medium-rank coal, and the imbibition velocity of high-rank coal is the smallest. In the middle and late stages of imbibition, the imbibition rate of high-rank coal is larger than that of medium-rank coal. In the process of imbibition and sorption, water will be transported from the pores with smaller pore size to the pores with larger pore size due to capillary force in the micropores/mesopores of the same magnitude, and the resistance of water in the lower rank coal is less than that in the higher rank coal.

Aiming at the problem of non-homogeneity and difficulty in obtaining the mechanical parameters of surrounding rock in the process of coal mining, the experimental device for determining the parameters of loaded coal rock with drilling was developed independently to realize the real-time perception of strength and structure of rock layer. The effects of circumferential pressure, drilling speed, rotational speed and rotational torque on strength of simulated rock specimens were investigated and analyzed by coupling the gray correlation of collected parameters with drilling. Under loaded conditions, stratified specimens of different combinations of types were drilled in order to restore the actual effect of drilling into coal and rock seams in real environments, and to verify the accuracy of identification of compressive strength of specimens by the following drilling parameters. It was shown that the strength of the specimens was positively correlated with the circumferential pressure, rotating torque and drilling speed. The strength of the specimen remained almost constant when the rotational speed varied. The correlations between rotational torque, circumferential pressure, drilling speed, and rotational speed and compressive strength were 0.996, 0.831, 0.739, and 0.347, respectively. The strength of the specimen was linearly related to the rotational torque. By analyzing the features of change in the rotating torque curve, the strength of the rock formation can be identified and thus the location of the stratum boundary can be located.

To investigate the stability of tunnel faces under pipe shed support in deep environments characterized by high stress and high-water pressure, a failure model for the deep tunnel face was established by the variational method. High water pressure and surrounding rock stress were incorporated into the mechanical model, and the external power and internal energy dissipation rates were calculated using the upper limit theorem. The analytical solution for the potential fracture surface of the tunnel faces was derived based on the principle of virtual work. The safety factor of the deep tunnel was solved by Matlab software. The influence of diverse parameters on the failure surface curve was analyzed, and the variation characterstics of safety factor under high stress and high-water pressure environment were discussed. Additionally, the effect of pipe shed support was evaluated. The results indicate that when the surrounding rock strength is low, the failure zone is larger and the longitudinal depth is greater. The high-water pressure and the surrounding rock stress have remarkable influence on the stability of tunnel face. Without considering them, the safety of tunnel face will be overestimated, and the relative error of safety factor can reach more than 60%. Pipe shed support can enhance the stability of deep tunnel face, increasing the safety factor by 79%. Meanwhile, high stress and high-water pressure environment will significantly reduce the effectiveness of pipe shed support. These findings provide theoretical guidance for the support design of deep tunnel, high-stress, and high-water pressure environments.

In order to conduct a comprehensive analysis of the air leakage characteristics in the goaf of shallow coal seams, five factors were selected, including the average length and width of overlying rock fractures, the porosity and thickness of overlying rock fractures, and the pressure difference above and below the well, to establish an index system for the impact of air leakage in the goaf of shallow coal seams. The dominance-based rough set and response surface method were combined to construct an analysis model for the air leakage characteristics and their factor effects in the goaf. Taking a coal mine as an example, empirical analysis was conducted to generate preference class rules for air leakage in the goaf and extract preference class features. Using the 3-factor 3-level response surface method, regression function fitting was performed on the air leakage volume in the goaf of shallow buried coal seams. The results indicate that the porosity of overlying rock layers, thickness of overlying rock layers, and pressure difference above and below the well are the core influencing factors of air leakage in goaf, with a single factor F-value of 96.06-226.82. The F values for the interaction factors of "interaction between overlying rock porosity and overlying rock thickness" and "interaction between overlying rock porosity and wellbore pressure difference" are 62.34 and 24.66, respectively. Compared with a single factor, in the interaction of multiple factors, the interaction between the porosity and thickness of overlying rock layers has a significant impact on air leakage in goaf. Therefore, when conducting analysis and prevention of air leakage in shallow coal seam goaf, it is important to pay attention to the role of individual factor indicators, as well as the interaction of factors that have a significant impact on air leakage.

To enhance the intelligent level and risk-bearing capacity of three gorges locks, first, SNA was used for stakeholder identification and extraction for Three Gorges lock reservation scheduling. Stakeholder network characteristics were characterized by three centrality indicators: degree centrality, betweenness centrality, and closeness centrality. An assessment index system was construct from four dimensions: legality, rationality, feasibility and controllability. Then, based on the potential coupling relationship between the indicators, a BN was used to construct a social risk assessment model for the Three Gorges lock reservation and scheduling mode to quantify the direction and intensity of the role of each indicator. Finally, key factors affecting social stability were identified through a sensitivity analysis. The results show that the social risk level under the scheduling mode of the Three Gorges lock is low. The order of influence of the four first-level indicators on the overall social risk is legality, controllability, feasibility, and rationality. The compliance with rule revision, approval, and issuance, the vulnerability of negative public opinion, the vulnerability of mass incidents, the success rate of appointment, and the coverage of security management strategy are the key factors affecting the overall social risk.