Respirable dust in coal mine operation space seriously endangers the health of workers. The existing pneumatic spray technology is not effective in reducing and removing respirable dust. To this end，a new supersonic pneumatic atomization technology was developed. The atomization characteristics were studied by experiments and numerical simulation. The transient dust reduction performance of this technology was compared with that of supersonic siphon and internal hybrid pneumatic atomization dust reduction technologies through multi-scale experiments. The results show that the high-speed fine mist domain is formed in the spray field of the new supersonic pneumatic atomization nozzle，and the droplet size and velocity gradually increase with the increase of spray distance. Compared with supersonic siphon and internal mixing pneumatic atomization nozzles，when the pneumatic pressure is 0.3-0.4 MPa and under different water flows，the new nozzles have smaller droplet size，higher droplet movement speed，and higher dust reduction efficiency，which can reach up to 90%. With the increase of pneumatic pressure，the range of high-speed fine mist area formed by the new nozzle increases，and the concentration of micro-mist increases，so that the dust reduction efficiency of small particle size dust increases at different times. When the pneumatic pressure is 0.4 MPa and the water flow rate is 10 L/h，the dust reduction effect of 2.5-10 μm respirable dust is the best.

To promote the all-around cultivation of undergraduate-master-doctoral integrated talents in safety science and engineering in universities，an effective collaborative education system was proposed by integrating curriculum ideological and politics，scientific research，innovation and entrepreneurship (dual innovation)，and industry education. Firstly，based on the current collaboration situation，the issues of the collaborative education system of safety discipline were deeply analyzed in terms of ideological education，science education，creative education，and industry education，and the connotation requirements of "a game of chess" were proposed. Then，a "four-dimensional integration" collaborative education system was developed through ideological and political guidance，research-driven，dual innovation cultivation，and industry-education orientation. Finally，based on the school's "Technology Mine" practical education brand，the practice of the "four-chain parallel" collaborative education system was performed in the case of safety discipline at China University of Mining and Technology-Beijing. The results showed that the collaboration education system for the safety discipline transferring from "four-dimensional integration" to "four-chain parallel" can meet the educational goals of the safety disciplines at different stages from undergraduate to master's to doctoral levels. It can also respond to the times for ideological and political，scientific research，industry，innovation，and entrepreneurship in safety science and engineering.

From the perspective of overall high-quality development and high-level security strategy，in order to realize the integration of new quality and productivity security development，research was carried out on the connotation，basic characteristics and capabilities of new quality and productivity security development. First，based on the triangle model，the connotation of safe development of new quality productivity was explained in combination with specific cases. Secondly，using the method of system engineering，the three-dimensional structural model was constructed，and the essential characteristics of the safe development of new quality productivity were analyzed. Finally，the capacities required for enhancing the safe development of new quality productivity were proposed. The research results indicate that the safe development of new quality productivity should focus on science and technology security，information data security，and risk management in new security fields，which are characterized by basic，overall，dynamic，complex and extensive features. The basic is reflected in the time dimension，the overall，dynamic and complex are manifested in the logic dimension，and the extensive features are embodied in the knowledge dimension. To promote safe development of new quality productivity，it is necessary to enhance strategic ability，leadership ability，collaboration ability，risk management ability，and theoretical innovation ability，corresponding to the three-dimensional structure model.

In order to accurately predict the material demand in the transitional resettlement stage of earthquakes and improve the efficiency and accuracy of emergency material mobilization，the factors that have a great impact on the number of resettled population were determined based on the historical seismic data in China. A prediction model of the resettled population based on GWO-BP was established，which combined with the quantitative relationship between the population and emergency supplies，to predict the material demand in the transitional resettlement stage after the earthquake. The experimental results show that the GWO-BP neural network model exhibits high accuracy and stability in predicting the number of relocated populations，and can effectively predict the number of relocated populations in disaster areas，thereby calculating the corresponding material demand. GWO-BP neural network model has a certain application value in predicting material demand in post-earthquake transitional resettlement stage，and can provide a reference for the decision-making of emergency material procurement after the earthquake.

To prevent tunnel workers' unsafe behaviors，the effects of workers' cognitive biases on their unsafe behaviors and the role of risk perception in this process were investigated. Based on the literature，a conceptual model describing the relationship between workers' cognitive bias，risk perception，and unsafe behaviors was proposed. Moreover，measurement scales in tunnel construction scenarios were designed and a questionnaire survey was conducted. Then，the proposed conceptual model using regression analysis was used to investigate the effects of workers' cognitive bias on their unsafe behaviors. The results showed tunnel workers' cognitive bias positively affected their unsafe behaviors (effect value=0.713) and negatively impacted their risk cognition (effect value=-0.607). Workers' risk cognition negatively affected their unsafe behaviors (effect value=-0.617) and partially mediated the relationship between workers' cognitive bias and their unsafe behaviors (effect value=0.334).

In order to ensure the safe operation of bag dedust system and prevent the occurrence of dust explosion accident，a real-time quantitative risk evaluation model of bag dedust system was proposed based on deviation degree-FCE. Firstly，based on the monitoring data of the pressure difference between inlet and outlet of the dust，box temperature and lock-in ash discharge fault signal collected by the industrial Internet of Things sensor，the deviation degree was introduced to characterize the risk status of the monitoring parameters of the bag dedust system. Then，FCE was used to calculate the risk status of the bag dedust system. The analytic hierarchy process(AHP) and variable weight theory were combined to assign weights to the evaluation indicators. Based on the membership function and weighted average principle of membership degree，the risk of the bag dedust system was quantified by deviation degree，and the risk evaluation result for the bag dedust system was obtained. Finally，the monitoring data of a certain type of bag dedust system was used to verify the effectiveness of the model. The findings demonstrate that when the monitoring value of the evaluation indicators of the bag dedust system gradually approaches the alarm threshold，and the number of indicators approaching the alarm threshold increases，the risk level is higher. The evaluation results are correlated with the actual operation situation，thus validating the efficacy of the model.

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 avoid abnormal attitude problems such as serpentine and axis deviation during shield tunneling affecting construction safety，a large-diameter slurry shield attitude control method combining CatBoost algorithm and MOEAD. A shield posture prediction model was developed with 19 input parameters and 6 output parameters，and the CatBoost algorithm was used to develop a nonlinear mapping relationship between input and output parameters. The SHAP was used to analyze the effects of input parameters on shield posture. The CatBoost-MOEAD shield posture multi-objective optimization model was coupled with the multi-objective optimization algorithm. Then the proposed model performance was validated against the Wuhan Yangtze River large-diameter slurry shield tunnel project. The results showed that the CatBoost prediction model can efficiently predict the posture of large-diameter mud-water shields. The determination coefficients of the six shield posture objectives ranged from 0.931 to 0.974，the root-mean-square errors ranged from 0.030 to 0.880，and the errors ranged from 0.039 to 1.057. The thrust of the propulsion group has the most significant impact on shield attitude among the major construction parameters. The proposed CatBoost-MOEAD multi-objective optimization method for shield attitude had a great performance in optimization effect with a maximum value of 38.86%.

In order to ensure the efficiency of response and disposal and reduce the damage caused by the hazardous gas leaks，it was necessary to quickly and accurately trace the location of the leak point as well as the source strength. In this article，a method of hazard location and source strength determination based on a complex algorithm was proposed. The basis of the algorithm was to compare the difference between the concentration of the monitored gas and the concentration calculated by the atmospheric diffusion model，and take the difference as the objective function，so that the parameter with the smallest objective function value was the optimal result of the source intensity and position. The results show that the complex algorithm can quickly and accurately obtain the location and source strength of the leakage source. Compared with the traditional simplex method，the compound algorithm has no restriction on the selection of initial value. Even if the selected initial value has a large deviation from the true value，the position and intensity of the source can be quickly obtained through the iteration of the complex algorithm，avoiding the shortcoming of the traditional simplex method，which has high requirements on the selection of initial value. A comparison of particle swarm optimization，genetic algorithm，simplex and complex algorithm is made in three aspects: traceability efficiency，traceability accuracy and traceability stability，which depicts that the complex algorithm is progressive. The complex algorithm can be applied to trace sources and determine source strength for continuous and instantaneous releases.

There is a risk of collision in the batch operation of logistics UAVs. To evaluate the collision probability between UAVs in the air，a model was proposed to analyze the collision risk of logistics UAVs in the aerial operation stage. A UAV collision probability model with the double errors of positioning and velocity was proposed based on the conflict zone theory，and the logistics UAV collision probability variations are analyzed from different angles. The key risk factors in small civil UAV accident/incident data were analyzed and identified based on the data from the Federal Aviation Administration of the United States. The UAV safety flight interval model was proposed based on the logistics UAV failure data of 20 thousand flight hours to determine the shortest flight interval under the acceptable safety level. Furthermore，the effects of track angles and wind directions on the collision probability between UAVs under constant flight intervals were investigated. The results showed that the risk for all flight scenarios was acceptable when the shortest safety interval between logistics UAVs exceeded 90.71 m. When the track angle was 30，60，and 90°，the collision probability varied little with the wind direction. Specifically，the collision probability was maintained constantly when the track angle was 90°. The collision probability varied a lot when the angle was 140°，thereby the safe flight of the UAV was sensitive to environmental factors.