In order to study the invulnerability and key nodes of the metro network in road-rail cooperative urban distribution，so as to support the networking mode of urban distribution and the reliability improvement of the distribution network under road-rail cooperation，the relative network efficiency and relative load entropy were used as the invulnerability measurement indicators，and the network invulnerability changes under different attack modes were studied based on the improved coupling image lattice model first. Secondly，the centrality index of the transportation efficiency of the reaction network and the realistic index of the carrying capacity of the reaction network was selected to construct a comprehensive identification model of key nodes of the network. Then，by analyzing the level of network invulnerability under different index weights，the key node set under the optimal weight value was obtained. Finally，the empirical analysis of the Chengdu metro network was carried out to verify the effectiveness and practicability of the model. The results show that the metro network has a stronger anti-destruction ability in the face of random attacks under the same disturbance intensity. When faced with external disturbances，the relative network efficiency and relative load entropy loss of nodes with a loss of more than 20% is 6.3% and 6.8%，respectively，of which the relative network efficiency loss can reach 56.3%，and the relative load entropy loss can reach 50.2%. Considering the realistic and central indicators，the relative network efficiency loss and the maximum relative load entropy loss caused by each key node are 8.99% and 4.38%，respectively，which need to be paid attention to.

To improve urban response capabilities in dealing with dynamic disasters，a MCMPOP was proposed for planning emergency vehicle paths in dynamic disaster environments. This model considered path safety as a multiplicative weight and vehicle path length and travel time as additive weights. Then，MCMPOP was addressed by improving the RSA. To verify the effectiveness of the improved RSA in solving the MCMPOP，510 simulation experiments were conducted comparing the computer time and solution quality of the Non-dominated Sorting Genetic Algorithm(NSGA)-Ⅱ and the improved RSA. Furthermore，"7·20" Zhengzhou rainstorm event was selected as a case study to validate the model. The results show that，compared to the NSGA-II，the improved RSA can find a complete set of Pareto optimal paths，effectively ensuring the optimality and computational efficiency of the algorithm. By using RSA to solve MCMPOP，it is possible to successfully select Pareto optimal paths with the shortest travel path lengths and the lowest time costs within the acceptable path safety range for emergency vehicles，providing more reliable routes for emergency vehicles and enhancing the urban emergency management capabilities.

To effectively implement safety production investment in bridge construction projects，GRA was used to analyze the correlation between the influencing factors of construction safety behavior from both the project supervision organization and construction units，and then the core causal factors were determined. Subsequently，a SD model was proposed to investigate the interaction mechanisms among the core causal factors. Finally，the vulnerability and resilience of the core causal factors affecting construction safety behavior were analyzed. The results indicated that extreme fines imposed by construction units，high supervision costs for project monitoring organizations，and low initial proportions between parties were the key vulnerability factors of the safety behavior in bridge construction. Reasonable economic fines，appropriate supervision costs，and enhanced training to improve frontline personnel's safety awareness significantly improved the construction safety behavior resilience.

In order to solve the problem of travelling obstacle detection in the context of complex open pit mines，a mining road obstacle detection algorithm based on improved cross-scale feature fusion is proposed. Firstly，to address the problem of unbalanced small target sample categories in the original mine dataset，a data enhancement method based on geometric transformation and weighted Poisson fusion is used to expand the number of samples.Secondly，a cross-stage connectivity network that is more suitable for obstacle detection is proposed in the feature extraction stage to increase the detection scale and improve the algorithm's learning ability of the small target features，and then a 3D parameterless attention (SimAM) and de-weighted Bi-directional feature fusion pyramid network (Bi-FPN) are proposed in the feature fusion stage to improve the multi-scale detection performance by enlarging the predicted feature map and feature receptive field. Finally，to address the problems of sample imbalance and imprecise obstacle bounding box localisation in the training，the quality focal loss function (QFL) and the scalable Intersection and combination ratio loss function (SIoU)，which combines the classification score with the quality prediction of the position to improve the localisation accuracy for dense occlusion targets. The results show that the improved method can effectively identify unstructured road obstacles in open pit mining area under complex background，and in practical application，the detection accuracy reaches 91.88% and the detection speed reaches 68.7 f/s，which has a better performance of small-target and multi-scale detection compared with the mainstream detection methods，and it can satisfy the requirements of obstacle safety detection in the travelling of unmanned mine cards in open pit mining area.

In order to swiftly elucidate the influence of internal parameters on the fracturing performance of a liquid CO₂ fracturing tool and optimize its functionality for enhanced coal seam gas extraction efficiency，a rapid assessment experimental apparatus was designed. A set of 9 orthogonal experiments involving 4 horizontal and 3 influencing factors was conducted utilizing a 38 mm mining-specific fracturing tool. The study analyzed the relative significance of the internal charge quantity in the heating tube，liquid CO₂ filling volume in the main pipe，the thickness of the fracture plate，and the caliber of the release aperture on the fracturing tool's performance. Furthermore，pivotal influencing factors were subjected to fixed-variable experiments to explore their impact patterns on the fracturing performance of the liquid CO₂ fracturing tool. Results indicate that，for the 38 mm mining-specific CO₂ fracturing tool，the thickness of the fracture plate exerts the most substantial influence on the fracturing tool's performance，followed by the internal charge quantity in the heating tube. The impact of the liquid CO₂ filling volume in the main pipe and the caliber of the release aperture is comparatively weaker. The fracturing performance of the liquid CO₂ fracturing tool gradually stabilizes with an increase in the thickness of the fracture plate，reaching a point where the plate does not rupture. When the internal parameters of the 38 mm fracturing tool are set to a CO₂ mass of 0.33 kg，a release caliber of 18 mm，a charge quantity of 60 g，and a fracture plate thickness of 2.0 mm，the tool's fracturing performance corresponds to a TNT(Trinitrotoluene) equivalent of 0.202 kg which is enhanced by 21.9 % compared to the current on-site parameters.

In the new security pattern，the power grid safety management was promoted to transform from the traditional mode to the digital，information，and intelligent mode during the life-cycle of safety production. Based on patent data of China's power grid intelligent security from 2008 to 2023，the patent map was performed using network centrality analysis and main path analysis. Then，key patent technology subgroups were obtained to systematically analyze technological development and key points of power grid intelligent safety. Based on patent maps and expert opinions，the entropy weight-TOPSIS method was used to evaluate the support of China's existing intelligent safety technology community for power grid security and intelligence. The results showed there were 11 key technology communities for the power grid intelligent safety technology，and power grid intelligent safety process technology was the most excellent knowledge group. Among the 11 types of power grid intelligent safety technology communities，technologies including intelligent control，intelligent dispatching，and network communication safety were with higher support for power grid intelligent safety. Intelligent security technology can well support the safety control and stability capabilities in the traditional safety goals of the power grid. Furthermore，it supports the safety governance and active security capabilities in the modern safety goal of the power grid. However，the support for security resilience capabilities was insufficient.

To optimize operator fatigue risk management and reduce the impact of fatigue on operator performance，the monitoring tasks before and after fatigue induction were conducted. Firstly，the fatigue-inducing task of the 2-back paradigm and the monitoring task of the oddball paradigm were designed with the digital main control room of a pressurized-water reactor nuclear power plant，and the control interfaces of low，medium，and high complexity were used. Then，human trials with 23 participants were performed to obtain subjective fatigue ratings，behavioral data，and EEG signals. Moreover，the effectiveness of fatigue induction was verified using relevant fatigue indicators. Finally，the participator's behavioral data and event-related potential P3 components under three different complexity interfaces before and after fatigue induction were analyzed. The results showed that the shortest 2-back task lasting 30 to 60 min induced fatigue. Fatigue or interface complexity increase resulted in a decrease in the monitoring behavior performance，and the maximum performance difference was observed between high-complexity and medium-complexity interfaces under fatigue conditions. Moreover，a 4.9% decrease in accuracy and a 10.4% increase in reaction time were observed. The trend of P3 latency was consistent with that of reaction time，and P3 amplitude increased significantly only under high-complexity interfaces. Based on the performance analysis and event-related potential data，it was concluded that the interface complexity increased the negative impact of fatigue on operators' mental workload.

To address the issues of ambiguous multi-level，multi-link and multi-functional interaction relationships and the adverse coupling effects during operations in confined spaces，FRAM was introduced. Combined with ISM and AHP，the hierarchical structure and judgment methods were optimized and improved. By dividing the risk hierarchical structure，the impact of system function coupling variability was quantified，and the importance of functional units and hierarchical structures was calculated. Through the results of functional variability and coupling loss degree，the input-output phenotype of upstream and downstream functional changes were determined，and the coupling mechanism among system functional elements was clarified. The results show that by applying the risk prevention and control model for operations in confined spaces based on the improved ISM-FRAM-AHP，23 functional units and a 10-layer risk hierarchical functional network are obtained. The maximum values of functional variability and coupling loss degree are 4.36 (external environment F₂₃) and 0.808 4 (formulating operation plans F₂)，indicating a relatively high operation safety risk degree. The functional changes are mainly manifested in sequence，goal and control. Four effective functional barrier measures，physical，symbolic，functional and invisible，are proposed for 8 failure links.

In order to reduce the pedestrian safety problems caused by the lag of the emergency warning system in urban rail transit stations under large passenger flow conditions，the YOLOv5 algorithm was selected to predict passenger flow information. The artificial neural network (ANN) model was used to construct the urban rail transit emergency warning perception system. Firstly，the YOLOv5 algorithm was improved by optimizing the model training hyperparameters and prior frame parameters. Then，the emergency warning perception system was designed by selecting warning indicators，weight analysis and threshold definition. Finally，the self-organizing competitive network emergency warning model based on ANN was constructed by using Matlab software. The data collected by the optimized YOLOv5 algorithm were substituted into the emergency warning perception system through calculation，and the emergency warning perception system was verified by experiments. The results show that the optimized YOLOv5 algorithm can improve the accuracy of pedestrian target monitoring under large passenger flow conditions of urban rail transit by 7.04%. The judgment results obtained by substituting the pedestrian data collected by the optimized YOLOv5 algorithm into the constructed emergency warning perception system are consistent with the actual warning level，which proves the feasibility and effectiveness of the system and helps to improve the emergency warning level of urban rail transit.

In order to develop the measurement of hydrogen sulfide content in coal seams towards informatization，intelligence，and automation，it is necessary to innovate the measurement equipment and technical methods. By analyzing the adsorption characteristics of H₂S in coal seams，the achievements in the development and application of hydrogen sulfide determination devices in recent years were summarized from the aspects of the convenience and accuracy of the construction of hydrogen sulfide determination devices. The current research status of methods for measuring hydrogen sulfide content in coal seams both domestically and internationally was elaborate. Finally，in view of the limitations of the equipment and methods for measuring hydrogen sulfide in coal seams，the future development direction of coal seam hydrogen sulfide measurement technology was discussed，and a technical system for improving the calculation error of coal seam hydrogen sulfide loss was proposed. An integrated coal sample underground crushing and desorption system，an automated desorption gas metering system，an intelligent monitoring and automated data analysis and processing system are constructed. The results show that the coal mine underground sampling method with internal and external double drill pipes，the loss of hydrogen sulfide during drilling and sampling is compensated. The measuring device is equipped with underground direct crushing equipment，filters，negative pressure vacuum tanks，and sensors for direct underground gas extraction and analysis，improving the accuracy of measuring hydrogen sulfide content in coal seams.