To investigate the methane DDT distance and maximum explosion pressure (P_max) in shale fractures，a multi-scale adjustable 3D planar slit detonation system was developed. Experiments with methane-oxygen premixed gas under 4 different hydraulic diameters，along with numerical simulations，were conducted to examine shale gas combustion under high pressure. Results show that methane-oxygen premixed gas can sustain self-propagating explosion within a hydraulic diameter range of 1.9 to 11.43 mm. Both P_max and peak pressure rise rate increase linearly with initial pressure. Under a hydraulic diameter of 11.43 mm，P_max closely approaches theoretical detonation pressure. As the hydraulic diameter decreases，the P_max-to-initial pressure ratio decreases. The initial pressure and the DDT distance follow a power-law relationship. Increasing the initial pressure or reducing the hydraulic diameter can shorten the DDT distance，thereby accelerating the DDT. The simulation shows that methane-oxygen premixed gas explosions can produce an overpressure of 330 MPa，capable of fully fracturing rock cracks.

In order to investigate the impact of drill pipe rotation on coal particles transport efficiency during negative pressure sampling，CFD and DEM were used to explore the effects of drill pipe rotational speed and coal particles mass flow rate on gas-solid flow characteristics. The results show that：the maximum axial airflow velocity inside the drill pipe decreases and stabilizes as the transport distance increases，while the maximum tangential velocity rapidly decays and vanishes. As rotational speed increases，the axial airflow velocity remains largely unchanged，but the tangential velocity significantly increases. With higher rotational speed，the spiral flow of coal particles becomes more pronounced，the length of the vortex region increases，and the length of the suspension region decreases. The number of coal particles entering the drill pipe decreases，and the distribution of particles above 5 m/s increases and becomes more dispersed. During rotation，the actual solid-to-gas ratio inside the drill pipe is lower than the set value，and coal particles transport efficiency increases and then decreases with the rise in rotational speed.

In order to improve the interpretability of excavation deformation prediction，this study developed an interpretable machine-learning model aimed at predicting the deformation of excavation retaining walls. A comprehensive analysis was conducted to evaluate the influence of different feature variables on the prediction outcomes. Firstly，a large number of excavation support structure parameters were used as a dataset，and 80% of the dataset was used to build a prediction model for the maximum lateral deflection of the retaining wall using the XGBoost (eXtreme Gradient Boosting)model. Then，the model was tested based on the remaining 20% of the dataset，and the accuracy of the model was evaluated by four indicators，i.e.，the coefficient of determination，bias factor，mean absolute percentage error，and root mean square error. Finally，combined with the XGBoost model，the SHAP(SHapley Additive exPlanations) method was applied to complete the global explanation of the excavation feature variables，the partial analysis of individual samples，and the analysis of interaction effects of feature variables. The results show that the proposed method can provide both global and local explanations for the deformation prediction of excavation. At the global level，it not only provides the importance ranking of feature variables，but also gives the distribution of SHAP values. At the local level，the deformation prediction results of individual samples are decomposed into the base value and the contribution of each feature variable，which can quantify the impact of individual feature variables.

In order to effectively improve the comprehensive prevention and control ability of coal mine water disaster accidents，the complex network and robustness analysis method were used to explore the key causes of accidents. According to the report of 111 typical coal mine water disaster cases in China in the past 40 years，an unweighted directed network of coal mine water disaster was constructed. The weights of each cause，such as degree，clustering coefficient and betweenness centrality at different scales of the network were calculated，and the key causes were excavated. The damage of intentional attack to the cause network under three different strategies was evaluated，and the optimal solution of systematic prevention and control was sought. The results show that the coal mine water disaster cause network has the characteristics of small world，and the causes are closely related. The attack ranked by degree has the greatest damage to the model. The corresponding key causes include organizing workers to carry out risky operations，failing to implement the management responsibility of water prevention and control technology，failing to carry out water exploration and drainage work as required，illegal organization of production operations，imperfect safety management institutions，inadequate hidden danger investigation，loopholes in coal mine safety supervision and supervision，and failure of higher-level units to perform safety management responsibilities.

To definite the diffusion characteristics of blasting fumes in downward drift filling mining stopes，taking the downhole filling mining method of Longshou Mine in Jinchuan as an example，numerical simulations and field tests were conducted. The spatial distribution of airflow in drifts and layered roads was studied，and the diffusion patterns of CO and NO₂ in drifts were analyzed. Furthermore，the effects of ventilation shaft locations and drift lengths on CO diffusion were explored，and the ventilation parameters of the Longshou Mine were determined. The results indicated that the airflow field in drifts and layered drifts can be divided into the inflow zone，neutral zone，and return zone. The airflow velocity in the drift. shows the S-shaped distribution，with higher velocity at the bottom，lower in the middle，and moderate at the top. In the vertical cross-section of the drift，the CO volume fraction continuously increases with height. While horizontally，it exhibits a "decrease-then-increase" pattern from the inner to outer side. At the drift waistline，the CO diffusion velocity shows a logarithmic decreasing trend with ventilation time.NO₂ is primarily concentrated below the midline of the drift，and its diffusion velocity is significantly faster than that of CO. The CO diffusion rate is negatively correlated with both the distance from the ventilation shaft to the drift entrance and drift length. When the distance between the ventilation shaft and the drift entrance is ≤40 m，and the drift length is ≤55 m，the CO and NO₂ concentrations in the natural ventilation blasting fumes are below the standard limits below after 30 minutes.

To evaluate the seismic resilience of urban group buildings under different demands，an integrated assessment methodology was developed for urban building clusters' earthquake resistance. A tree-augmented naive Bayesian method was employed to construct a BN model that rapidly predicted structural damage states under various target earthquakes through multi-parameter analysis including building types，construction eras，and structural configurations. Multiple resilience evaluation theories and methods-comprising the resilience index method，resilience element rating method，risk-resilience analysis method，and group buildings resilience indicator evaluation method-were integrated to comprehensively assess the seismic resilience of group buildings in a specific street of Fengtai District，Beijing. Comparative analyses were conducted to examine the advantages，limitations，and applicability of these approaches. The results indicate that the resilience index method proves suitable for rapid assessment of building recovery capacity，while the resilience element rating method facilitates intuitive visualization of structural resilience levels. The risk-resilience analysis method demonstrates superior capability in handling disaster uncertainties and stochastic characteristics，whereas the group buildings resilience indicator evaluation method emphasizes the critical influence of functional requirements on comprehensive assessments.

To grasp the development trends in urban emergency management research under extreme circumstances，a systematic review of the main studies and research characteristics in this field has been conducted. Using the scientific knowledge mapping tool VOSviewer software and Web of Science Core Collection (Wos CC) as the data retrieval source，this article performed a visual analysis on research literature on emergency management in extreme situations. The results show that in recent years，the research on urban emergency management in extreme situations has been increasing year by year，but the overall number of articles published is not much，with a total of 145 articles from 2004 to 2024. The United States，China，Australia are among those with the highest number of research papers，making significant contributions to the development of this field. Obvious research teams have been formed，mainly in China and the United States，but there is a lack of international cooperation. Through cluster analysis，the research topics can be summarized into five aspects，namely，disaster prevention management，disaster prediction models，urban vulnerability analysis，smart cities，and the impact of climate characteristics. Currently，as the probability of cities facing extreme risks increases，it is urgent to strengthen international cooperation，fully utilize the latest technologies such as artificial intelligence and big data，and construct a theoretical system for urban emergency management capable of facing extreme situations.

In order to improve the emergency management ability and effect of local governments and promote the modernization of emergency management systems and capacity，the game theory was used to construct a game model. The evolutionary game relationship between audit institutions，local governments and surrounding governments was discussed. The root causes of the three were explored through model stability analysis and numerical simulation. Corresponding countermeasures and suggestions were put forward according to the analysis results. The results show that the benefit of emergency management is the key to the evolution of the behavior of local governments and surrounding governments. In addition，the probability of active supervision by audit institutions and the size of audit costs have an impact on the behavior choices of the two governments，and the willingness of the two governments to participate in emergency management also has an impact on each other. For audit institutions，the cost of auditing and the degree of accountability are key factors that influence their behavioral choices.

In order to effectively identify construction risks and prevent safety accidents，this study investigated the safety evaluation method for metro station construction in confined space under 500 kV high-voltage lines. First，a safety evaluation index system for metro station construction under high-voltage lines was established by integrating AHP and 3MET(Management，Man，Machine，Environment，Technology) method. Then，the weights of indicators were calculated using the IOWA operator，and the cloud model was applied to determine evaluation standard clouds and cloud characteristic values，thereby deriving the comprehensive safety evaluation grade. Finally，the proposed method was validated through a case of the University Town Central Road Station on Chongqing Metro Line 15，with corresponding mitigation measures proposed for high-risk indicators. The results demonstrate that the evaluation model accurately identifies high-risk sources in metro station construction under high-voltage lines，with the safety evaluation grade classified as lower risk，consistent with on-site conditions. Key considerations for safety measures include the electromagnetic field effects of high-voltage lines，risk monitoring and protection，mechanical equipment selection and its safety functions. The application of multi-dimensional layered protective structures could effectively mitigate construction risks under high-voltage environments.

To understand evacuation behavior and psychological characteristics in the event of a sudden fire in an ancient town，and to accurately identify the factors influencing personnel evacuation behavior，a questionnaire survey on evacuation behavior was conducted in an ancient town in Zhejiang Province. The survey focused on three aspects：basic population characteristics，awareness and attitudes toward fire risk in the ancient town，and evacuation behavior. Subsequently，the correlation between evacuation behavior and factors such as age group，frequency of fire drills，and understanding of fire risks in ancient towns was comprehensively analyzed using the Pearson's Chi-square test and eXtreme Gradient Boosting (XGBoost) machine learning algorithm. The results indicate that tourists (77.78%) are more aware of fire risks in the ancient town than local residents and merchants (22.22%). Age has a significant impact on returning behavior. The higher the level of education，the less likely respondents are to engage in overtaking behavior during evacuation (decreasing from 85% to 33%). Individuals who have not proactively familiarized themselves with emergency exits are more likely to exhibit herd and 'habitual' behavior when choosing evacuation exits (increasing from 8% to 33% and from12% to 20%，respectively). Special attention should be given to fire safety training for local residents and merchants. Fire safety management in the ancient town should be strengthened，and evacuation plans tailored to different age groups should be developed to improve evacuation capabilities in the event of a sudden fire in the ancient town.