In order to solve the problem of increasing difficulty of water injection in deep coal seam and poor inhibition effect of emission，based on the theoretical method of wetting modification of coal seam，wetting agent was used to act on gas-bearing coal body to inhibit gas desorption and migration. The fluorocarbon FS-3100 surfactant with strong wettability was used to test the influence of wettability on the gas-water migration process in coal through gas-containing coal desorption test and fracturing fluid displacement flow test，and to explore the change mechanism of coal wettability on gas-containing coal desorption efficiency and flow capacity. The results show that the surface tension of water is reduced to 17.9 mN /m after adding wetting agent in water，and the contact angle of coal water is only 3-3.5°. After the wetting agent was used to modify the coal body，the desorption rate of gas in the coal is significantly reduced. The gas desorption rates of Xinjing and Baode coals are reduced to 46.08% and 39.2%，respectively，which are 8.4% and 9.8% higher than that of water. After the wetting agent acts on the coal body，the displacement flow rate of the Xinjing coal sample increases from 8.59% to 14.10%，and the Baode coal sample increases from 10.65% to 16.67%，and the water injection capacity of the coal body is significantly enhanced. The wetting agent molecules are adsorbed on the surface of the coal matrix，which reduces the interfacial tension between coal and water and the surface energy of the coal body，so that the friction resistance of the water molecules flowing in the pores and fissures of the coal body is reduced，and the water molecules can infiltrate smaller-scale pores and produce stronger water lock effect. Finally，the gas desorption and migration adsorbed on the pores and coal surface are inhibited，and the gas plugging effect is formed.

In order to solve the problems that machine learning exists in the hazard intelligent prediction field of tunnel water inrush，such as relatively simple models and imperfect prediction accuracy，a prediction model based on the stacking ensemble learning was proposed. Firstly，the tunnel water inrush disaster dataset was established by collecting 232 groups of water inrush disaster data from 95 tunnels，and the data was preprocessed. Then，3 base learners and 2 meta learners were selected to train 8 sets of stacking ensemble models in different combinations，and 6 sets of optimal ensemble models were selected. Finally，the optimal stacking ensemble model was selected by comparing and analyzing the prediction results of 6 groups of parameters optimized and stacking ensemble model with the grid search parameters and the 5-fold cross-validation hyperparameter optimization model. The results show that SVM(Support Vector Machine )+NB (Naive Bayes) + LR (Linear Regression) ensemble model is obtained after the optimal single model SVM is improved with the stacking ensemble learning method. Its accuracy，recall，and F₁ score are 0.94，0.91，and 0.92，respectively. The overall prediction effect is better than that of other compative models，and it can accurately predict the hazard level of tunnel water inrush.

To reveal the distribution characteristics of ceiling radiant heat flux in full-scale tunnel fires，the numerical simulation research was carried out. Longitudinal ventilation velocities，heat release rates and effective fire heights were changed. The distribution of ceiling radiant heat flux in road tunnel vehicle fires，the maximum ceiling radiant heat flux and its position were analyzed. The influences of the longitudinal wind speed，the heat release rate，and the effective fire height on each parameter and their important degrees were revealed. Results show that under the natural ventilation，affected by the heat release rate and effective fire height，the radiant heat fluxes under the ceiling above the fire source surface show a uniform distribution，or the law that the middle radiant heat fluxes are low while the two sides are high. Under the longitudinal ventilation，the ceiling radiant heat flux increases and then decreases. The peak value of the heat flux occurs near the center of fire source and the downstream of fire source. At large effective fire source heights，the peak values of the maximum ceiling radiant heat flux are obtained under the condition of wind speed lower than the critical velocity. While reducing the effective fire height and increasing the heat release rate，The peak value of maximum ceiling radiant heat flux individually occurs both when the wind speed is less than and when it is greater than the critical wind speed. When the wind speed below the critical velocity，the maximum ceiling radiant heat flux presents right above the surface of the fire source，and it is weakly affected by the heat release rate，longitudinal ventilation and the effective fire height. When the wind speed above the critical velocity，the maximum ceiling radiant heat flux increases with the heat release rate，and it is less affected by the wind velocity. The research results can provide some reference basis and data supports for tunnel fire prevention and control and tunnel safety design.

To improve the safety of urban medical waste recycling and disposal，an optimization methodology for the medical waste transportation network was proposed，where the facility location，vehicle-routing and vehicle acquisition were simultaneously optimized. Firstly，according to the environmental transmission characteristic of medical waste viruses and uncertainty of urban emergency response time，BP neural network model was used to simulate the dynamic evolution process of risk，and a four-dimensional prediction model was designed. Secondly，introducing vehicle volume and capacity constraints，an optimization model，minimizing the total cost and risk，was developed by two-commodity flow formulation. The solution procedure was also developed by improving the NSGA-II algorithm based on the complexity of model. Finally，a case study in Shanghai and several tests were provided to demonstrate the workability. The computational results show that the new model and approach can provide multiple efficient plans within 672 seconds，and they are sensitive to some parameters. Compared to the traditional risk assessment，new model can provide a reduction of 3.47% and 13.04% in total cost and risk respectively. Using the risk prediction technique，a decrement of 7.41% in total risk can be achieved when comparing to current policy. New algorithm can reduce the CPU time by at least 49.44% and keep stable performance in solving problems of different scales while comparing to traditional multi-objective optimal methods.

In order to reduce the risk of boil-over accidents in storage tanks and develop efficient prevention and control strategies，two-dimensional transient numerical simulations of the boiling process of oil-water two-phase system in closed containers were carried out using Fluent software. The effects of different tank types，initial water layer thickness，oil-water ratio and other factors on the boiling process were analyzed through numerical simulation. The phase distribution，temperature field and hydrodynamic behavior were studied during the whole process of the combustion triggering to the end of the boil-over. The results show that for the same tank type，the higher the water content of the oil，the smaller the intensity of boiling overflow. When the tank boils over，the oil-water interface undergoes violent instability，and the two phases of the medium in the container are interspersed with each other，presenting a chaotic state. The liquid near the tank wall of boils upward first，with the peak temperature of the liquid phase up to 400 K. When the horizontal storage tank boils over，the overall temperature of the liquid phase is lower than that in the vertical storage tank. The onset of boiling overflow in the horizontal tank occurs earlier than in the vertical tank. Therefore，the boiling overflow in the vertical tank is more dangerous.

In order to solve the index ambiguity problem in the risk assessment process of downward layered mining filling body stability，the filling body stability assessment model was constructed. Firstly，12 factors affecting the stability of the filling body，such as cohesion，exposed area，stress ratio，etc.，were selected as risk evaluation indicators to establish the evaluation index system. Secondly，the cloud model theory was introduced to calculate the cloud digital characteristics of each indicator，and the comprehensive weight was obtained by using G1-RF，and a comprehensive evaluation model of the stability of layered mining filler was constructed based on the G1-RF combined empowerment cloud model to determine the stability risk level of the mine filler. Finally，the evaluation method was applied to the stability analysis of the mine filler in the actual project. The results show that the comprehensive evaluation method can effectively solve the problems of indicator ambiguity and weak relevance in the process of risk assessment，more accurately and quickly evaluate the stability of the filling body，and realize the visualization of the risk level.

In order to improve the safety of existing large-span steel grid structure stadiums and gymnasiums，from the three perspectives of foundation，superstructure and enclosure structure，24 factors influencing layer indexes were constructed，and the safety evaluation index system was weighted by game theory comprehensive subjective and objective weighting method. The importance grade of components was divided by load transfer path analysis，and the critical value of safety grade of different indexes was strictly defined，and the matter-element extension evaluation model was established. Based on the matter-element extension model，the data collection and model application of five existing large-span steel grid structure stadiums were carried out，and the stadium was taken as an example for empirical analysis. The results show that the safety grade of the stadium is grade II under the normal load (working conditions 1，2)，but the safety grade is grade III under the extreme load (working condition 3)，and the corrosion and deformation of the components need to be monitored. The agreement rate between the evaluation results of the five existing large-span steel grid structure stadiums model and the on-site inspection results by experts is 91.35%. The research confirms that the model can effectively quantify the structural safety of existing large-span steel grid structure stadiums under complex working conditions.

To reduce traffic accident risks，on-road experiments were conducted to investigate the differences in potential risk perception ability between skilled and unskilled drivers under two typical risk scenarios：dynamic motorcycle-following and parallel overtaking. A wearable eye tracker was employed to collect drivers' dynamic visual parameters，with their visual characteristics analyzed across different scenarios. The results demonstrate that skilled drivers exhibit significantly stronger risk perception abilities than unskilled drivers in both scenarios. Specifically，in the dynamic motorcycle-following scenario，skilled drivers show a higher probability of fixating on distant areas ahead，enabling better prediction of upcoming traffic conditions. In the parallel overtaking scenario，skilled drivers display shorter fixation durations，along with greater horizontal search breadth and vertical search depth. Moreover，the proportion of fixation time on rearview mirrors is significantly higher for skilled drivers compared to unskilled drivers，indicating superior visual search efficiency and enhanced rear traffic monitoring capability. Evaluations using the grey near-optimal comprehensive evaluation method reveal that skilled drivers achieved significantly higher scores in hazard perception ability.

In order to improve the emergency management capability for the purpose of urban underground comprehensive pipeline corridor construction，the general framework of pipeline corridor safety system was established by analyzing the regional emergency management system within the pipeline corridor，utilizing the theory of knowledge synergy，and combining the regional synergistic emergency management system with the scenarios of comprehensive pipeline corridors from the perspective of the application in comprehensive pipeline corridors. The framework was structured around the core of “risk-emergency-crisis”. The work breakdown structure-risk breakdown structure(WBS-RBS) method was adopted to complete the identification and grading of the risk of emergency management of the pipeline corridor. The probability of the risk of emergency management of the pipeline corridor was evaluated using analytic hierarchy process(AHP) method. Finally，the safeguards required for the establishment and operation of the multi-agency emergency knowledge management system of the integrated corridor were described across three dimensions of organization，technology，and supervision. The results show that the knowledge synergy theory is demonstrated to have a great advantage in building a regional collaborative emergency management system model. The safety system framework of the urban comprehensive pipeline corridor is designed to predict all kinds of risks in the structure，equipment and operation of the pipeline corridor. It is also capable of maintaining safety and stability during emergencies.

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.