In order to better use microwave antireflection technology to safely and efficiently extract coal seam gas，and to explore the influence of coal moisture content change on the antireflection effect under cyclic microwave conditions，firstly，the transverse relaxation time (T₂) spectrum and longitudinal relaxation time (T₁) -T₂ spectrum characterizing the pore structure characteristics of coal samples were obtained by NMR technology. Then，the characteristic parameters of nuclear magnetic resonance were obtained by using T₂ data，and the change of pore structure evolution with water content under cyclic microwave radiation was further clarified. Finally，based on the mechanism of cyclic microwave permeability enhancement，the pore structure evolution mechanism of different water-bearing coal bodies was revealed. The results show that the pore structure of coal with different water saturation is obviously improved under cyclic microwave radiation，and the coal sample with 75% water saturation has a better antireflection effect than other test coal samples. In the process of cyclic microwave radiation promoting the evolution of pores to larger pores，pore blockage occurs due to the thermal fracture of coal，and increasing water saturation can reduce this phenomenon. The cyclic microwave anti-reflection mainly relies on thermal stress and air pressure. With the improvement of coal permeability，the effect of microwave anti-reflection is weakened，and the influence of coal water content is weakened.

In order to reveal the sloshing behavior of vehicle-mounted liquid hydrogen storage tanks and improve their transportation stability，a numerical simulation model of vehicle-mounted liquid hydrogen storage tank sloshing was established. The impact of liquid hydrogen fluid sloshing on the storage tank during braking and turning was studied. The effects of driving speed，longitudinal and lateral acceleration and filling rate on the sloshing behavior of liquid hydrogen in the storage tank were discussed，and a wave-proof plate was designed to suppress the sloshing of liquid hydrogen. The results show that the stable driving speed of the vehicle has little effect on the liquid hydrogen sloshing in the tank. The more urgent the vehicle brakes or turns，the more severe the liquid hydrogen sloshing in the tank，the more serious the impact on the tank，and the longer the time required for the liquid hydrogen to reach a stable state. The closer the filling rate is to 50%，the more severe the sloshing is. As the filling rate increases to 90%，the impact of liquid hydrogen on the storage tank is more significant. However，the higher filling rate reduces the liquid hydrogen movement space and makes the sloshing amplitude more gentle. The anti-wave plate in the tank can effectively separate the liquid hydrogen sloshing space，so that the maximum longitudinal impact force of the tank is reduced by 9.6% and 17.5%，and the maximum lateral impact force is reduced by 34.6%，which significantly reduces the impact on the tank and shortens the liquid hydrogen recovery time.

In order to reduce the number of accidents，casualties and enhance the ability to control the level of accident hazards，and to study the general characteristics and hidden patterns of heavy and large safety accidents in China's chemical production industry，this paper used statistical analysis to comprehensively analyze 41 heavy and large accidents that occurred from 2000 to 2023 in terms of time，region，production stage，type of accidents，causes of accidents and other elements. The results show that the number of accidents shows a fluctuating upward trend in 2007-2019，and July and August are the high incidence period of accident every year. The number of heavy chemical accidents in East China accounts for 52.2% of the whole country，of which 12 accidents occurred in Shandong Province，accounting for 57.1% of the total. The highest proportion of accidents occurred in the formal production stage of enterprises，accounting for 53.6% of the total. The main types of accidents is container explosion. The domino effect exists in accidents，with heavy domino accidents and large domino accidents accounting for 14.63% and 39.02% of the total accidents respectively. There are more accidents with domino effect in heavy and large accidents than those without domino effect，accounting for 53.65%，of which the casualties of accidents with large dominoes account for 40.1% of the total accidents and casualties. The most frequent cause of accident statistics is the illegal execution of production，accounting for 49.3% of the total，and the resulting accidents with domino effect account for 66.6% of the accidents. In response to the problems analyzed in the above accidents，this paper proposes some measures to improve the management system from three perspectives: the company，the equipment and the employees.

To drive multi-stakeholder work safety governance in enterprise-intensive areas such as industrial parks，the dynamic mechanism for forming a multi-stakeholder work safety governance model was explored. Firstly，the key stakeholders involved in the industrial park work safety alliance were identified through text-based data mining. Subsequently，a comprehensive investigation was conducted on the development process and governance model of the work Safety Alliance in Suzhou Industrial Park. Finally，an alliance network was proposed to analyze the translation process based on ANT. Then，the dynamic mechanisms of the Industrial Parks work Safety Alliance were investigated. The results indicated that the benefits of resource exchange could be balanced by developing a work safety resource-sharing platform and proposing a multi-agent governance mechanism in a regional work safety alliance，which can promote multiple stakeholders' collaboration in work safety governance. Furthermore，the active mobilization of core actors，coupled with concerted efforts from both internal and external parties，contributes to the efficient operation of the alliance.

In order to study the effect of liquid CO₂ injection on coal spontaneous combustion heat production and gas release in the gob with high gas content and easy spontaneous combustion，the gas desorption test system was composed of a self-made variable temperature chamber and desorption instrument to simulate the influence of liquid CO₂ injected into a high-temperature point of gob on coal sample temperature and coal gas desorption amount and analyze the change of gas desorption energy of coal sample under corresponding coal body gas pressure and different temperature during the process of "falling to rising" temperature change. The results show that the temperature of the coal sample will stabilize at a lower level，and the gas will stop desorbing within 60 minutes to 100 minutes after the liquid CO₂ is injected. After 100 minutes，the cold energy gradually runs out，and the coal continues to oxidize and heat up，and the gas resumes desorbing with an increasing desorption rate. The cold energy released by the liquefied CO₂ gasification and the CO₂ gas has an excellent inhibitory effect on reducing coal temperature and gas desorption. When the coal sample temperature is between 10 and 30 ℃，the coal is in a low energy state. In this temperature range，the internal coal is more likely to cause the adsorption heat value to stabilize. The decrease in the surface free energy of the coal body will also present a stable trend.

Physical evidence investigation was a necessary means and important link to identify the causes of hazardous chemical incidents. However，the manifestations of hazardous chemical incidents were often explosions and fires，which could easily trigger a domino effect，making physical evidence investigation somewhat difficult. In order to improve the efficiency of on-site inspections and reduce the occurrence of hazardous chemical incidents. MFA method was adopted to conduct on-site intelligence information analysis and explore the application value of MFA theoretical methods in the physical evidence inspection of hazardous chemical incidents based on specific cases. Based on "Jiangsu Xiangshui 3·21 serious Explosion Accident"，"Material Flow Analysis Map" and "Hazardous Substance Distribution Map" were drawn for Tianjiayi Chemical Plant，and material flow analysis research was conducted on the involved enterprises. The results indicate that MFA can identify hazardous areas and substances，providing safety protection reference information for on-site inspectors. It can also provide scope and direction for extracting，inspecting，and identifying on-site physical evidence.

In order to facilitate the rapid formation of a disaster and accident trans-regional collaborative governance community in response to major emergencies，this study employed fsQCA. It investigated fourteen cases by selecting seven conditional variables across three dimensions: Incentives，mechanisms，and guarantees. These variables included value consensus，existential threats，administrative mobilization，collaborative linkage mechanisms，interest equilibrium mechanisms，legal guarantees，and digital intelligence technologies. The study explored the core influencing factors and the complex causal relationships in the formation of the disaster and accident trans-regional collaborative governance community. Configurational analysis identified three patterns of community formation: party-government-led，value-driven，and crisis-triggered，with each pattern corresponding to typical cases in the case database. The findings reveal that collaborative linkage mechanisms are a necessary condition for the formation of emergency management communities，while the other six variables cannot individually serve as necessary conditions. Optimizing the functionality of collaborative linkage mechanisms can effectively promote the development of trans-regional emergency management communities.

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.

To enhance the intelligent system's understanding of individual driving behavior under human-machine interaction driving circumstances，an en-route driving style recognition method based on LDA model was proposed. The method explored vehicle trajectory information from multi-dimensions to quickly extract and identify latent driving style features of drivers. Firstly，the semantic understanding rules of driving behavior were established to discretize continuous trajectory data into semantic vocabularies of driving behavior，considering the scene perception layer，pattern layer，operation layer and vehicle status layer. Secondly，according to topic perplexity and consistency，habitual driving styles were classified into four categories: stable，conservative，moderate and aggressive. Finally，each driver's en-route driving style was identified as a probabilistic combination of the aforementioned driving styles. The results show that the proposed en-route driving style recognition method considers drivers' heterogeneity and explains the phenomenon of the same driver exhibiting different driving styles in varying driving environments. Additionally，this research improves the comprehensiveness and comprehensibility of en-route driving style recognition.

In order to prevent hard landing overrun events of civil aircraft，first，data including kinematics，system performance and other engineering parameters was collected from QAR. Then QAR data processing activities such as the airport segment clustering，sample balancing and statistical feature extraction were carried out. Subsequently，LightGBM model was used to predict the hard landing events of civil aircraft，and compared with extreme gradient boosting (XGBoost)，decision tree (DT) and long short-term memory (LSTM) models. Finally，the shapley additive explanation (SHAP) algorithm was employed to identify the causal mechanisms of hard landing events and to analyze the impact of various flight parameters on the model's prediction results. The result demonstrates that the proposed model not only exhibits high accuracy and precision in predicting hard landing events (accuracy，correctness and recall reaching 99%，92% and 88%，respectively)，but also provides quantitative and visual explanation information for the decision-making process of hard landing prediction for specific flight segments.