In order to solve the problems of imperfect construction of risk classification control mechanism，low informatization level，and insufficient employee participation in the construction of double-prevention mechanism in coal chemical enterprises and build a long-term double-prevention mechanism for enterprises，firstly，the design idea，system architecture，and function module of the digital platform were described in detail. Then，with risk classification control and hidden danger investigation and management as the core，data collection，intelligent analysis，early warning，task distribution，progress tracking，and other functions were integrated to realize the digital management of the whole process of safety production of coal chemical enterprises. Finally，combined with specific cases，the application effect of the double-prevention digital platform in coal chemical enterprises was evaluated. The results show that the platform can provide enterprises with a standardized and intelligent closed-loop management system from the aspects of risk identification and assessment，classification control，and hidden danger investigation and management，and it achieves good application effects in risk management and control，hidden danger investigation，and main responsibility implementation. The platform can grasp the risk dynamics in real time，discover and eliminate hidden dangers in time，improve the emergency response speed，and reduce the accident rate. It can provide a new idea for the informatization and intelligent construction of the double-prevention mechanism of coal-to-oil coal chemical enterprises and provide a reference for the construction of the double-prevention digital platform of other industrial and mining enterprises.

In order to timely and effectively detect the explosives hidden in luggage，packages and individuals，multiple explosives such as trinitrotoluene(TNT)，hexahydro-1，3，5-trinitro-1，3，5-triazine(RDX)，triacetone triperoxide(TATP)，ammonium nitrate(AN)，etc. were detected by FQ and IMS instruments by wiping and aspiration sampling methods. The comparison was mainly made from two aspects: alarm time and recovery time. The experimental results show that under wiping sampling，the average alarm time of FQ is about 2 seconds less than that of IMS，and the average recovery time is about 30 seconds less than that of IMS，which has higher detection efficiency. In the case of aspirated sampling，FQ instruments can detect TNT and TATP，while it is difficult for IMS instruments to detect explosives.

To enhance the accuracy and reliability of geological earthquake disaster events predictions，a predictive model combining knowledge graph with GCN was proposed. Initially，the knowledge graph for geological earthquake disaster events was constructed，and the multi-source disaster-related information was consolidated into structured data. Then，the KGCN model was employed for deep learning of entities and relationships within the knowledge graph，uncovering potential association rules to forecast the evolution of disasters. Finally，the effectiveness of the model was validated through a set of geological earthquake disaster cases. The results show that the predictive model combing knowledge graphs with GCN exhibits excellent effectiveness in forecasting the evolution of geological earthquake disaster events，especially in dealing with complex multi-source data. The information can be efficiently integrated，and potential relationships can be accurately uncovered by the model. Excellent prediction accuracy is achieved in various aspects，including disaster levels，casualty levels，and disaster victim categories. Notably，the accuracy in predicting the disaster emergency response levels reaches 89.92%.

In order to reveal the complex causality between EWSV and their multiple antecedent conditions，and to improve the efficiency of safety governance，a comprehensive model integrating contemporary deterrence theory，protection motivation theory，and social learning theory was constructed from a perspective of complexity theory. Based on this，six antecedent conditions affecting EWSV were identified from three perspectives: leader，coworker，and employee. Then，the fsQCA was used to reveal what configuration of antecedent conditions would lead to high level of EWSV. The results show that a single antecedent condition is insufficient to explain high level of EWSV but safety-specific leader punishment omission and coworker work safety violations(CWSV) play universal roles in forming high level of EWSV. Three types of driving modes composed of five condition configurations can lead to high level of EWSV. Three types of condition configurations lead to non-high level of EWSV. Reducing CWSV and improving employees' perception for formal sanctions are crucial for achieving non-high level of EWSV. Different combinations of multiple antecedent conditions can lead to high level of EWSV，and there is a complex causality (concurrency，equivalence，and asymmetry) between high level of EWSV and their antecedent conditions.

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.

In order to clarify the correlation of eVTOL risk factors，and explore their impact on risk prevention and control in the UAM ecosystem，complex network theory was used to establish a risk evolution model. Based on the UAV accident database at home and abroad and the statistics of general aviation accidents，combined with the operation characteristics of eVTOL in urban low-altitude scenes，35 types of risk factors and 10 types of dangerous events were identified from the perspective of human-machine-environment. Gephi software was used to construct the network model，and the key nodes were evaluated comprehensively by the node degree，proximity centrality，internode centrality and PageRank(PR) algorithm. The key edges were evaluated by the internode number，so as to determine the key risk propagation path. In order to reduce the system risk，the measures to reduce the chain breaking disaster were proposed，and the system safety after chain breaking control was measured by network efficiency index. The results show that there are strong correlations among the eVTOL risk factors in the UAM ecosystem，and there are eight key risk transmission chains. The system safety is improved by 4.74%，16.21% and 18.10% by blocking key human factors，key system technical failure factors and key intermediate dangerous events，respectively.

To clarify the essential characteristics and differences between inherent safety, behavior-based safety, process safety, and functional safety and to promote a virtuous cycle of high-quality development and high-level safety, this study employed literature review and comparative analysis methods to explore their basic connotations and evolution processes, interrelationships, realistic challenges, and development paths based on the safety management paradigm shift. The results indicate that inherent safety is an idealized form of safety. Behavior-based safety is an interdisciplinary field that involves the theories and methods of safety science and behavioral science. Process safety protects humans, machines, and the environment through systematic approaches from a full life cycle perspective. Functional safety aims at preventing unacceptable risks caused by functional failures of systems. The four types of safety, led by inherent safety, involve a gradual progression from concepts to practice. These types of safety share a unified internal structure encompassing the elements of humans, machines, environment and management. The current representative standards cover various industry sectors and focus on accident prevention. In the future, the synergistic effect of the four in safety governance should be fully utilized. By using artificial intelligence technology to empower the new engine of safety production, the four should be continuously improved in specific practices tailored to local conditions.

To quantify the transportation risks associated with biological samples using UAVs, this study first identified 32 risk factors across five dimensions-human, machine, environment, management, and hazard-based on national standards and relevant literature. A BN for risk assessment was constructed using Netica software, with prior probabilities determined through expert knowledge and fuzzy set quantitative analysis. The proposed risk assessment model was then used for bidirectional reasoning and scenario analysis. A case study of a UAV company in Shenzhen was presented to evaluate the transportation risks of biological samples and identify key influencing factors. The results indicate that the risk probability of biological sample transportation, as calculated through forward reasoning, is approximately 2.203×10^-5. The primary risk factors are related to hazardous materials, followed by equipment and facility-related issues. The core risk factors influencing biological sample transportation include the size, quantity and weight of hazardous material packages, the temperature control effectiveness of specialized cold chain logistics boxes, the integrity of emergency response plans, emergency handling capabilities, safety management and education, and the presence of obstacles.

To reveal the characteristics of coal mine accidents in China in recent years，and put forward targeted countermeasures and suggestions for accident prevention，firstly，the major and catastrophic coal mine accidents in China from 2013 to 2023 were collected and analyzed from the aspects of the year，type，month，province and cause of the accident. Secondly，taking "2·22" particularly serious collapse accident in Inner Mongolia Xinjing coal mine as an example，the accident was analyzed based on 24Model. Finally，combined with the above analysis and research results，the accident prevention countermeasures and suggestions in line with the current situation of coal mine safety production in China were put forward. The analysis and research results show that the number of major accidents and deaths in coal mines has shown an overall downward trend，and the level of coal mine safety production in China has significantly improved since the 12^th Five Year Plan. Gas accidents are still the main accidents in coal mines in China，accounting for 51%. The fourth quarter of each year is a period of high incidence of coal mine accidents，accounting for 30.43% of the total number of accidents. Affected by geological conditions and occurrence，accidents often occur in the main coal producing areas. The proportion of accidents caused by unsafe human behavior is as high as 74%. When there are hidden dangers at both the individual and organizational levels and the dual prevention measures are not in place，accidents are likely to occur. Countermeasures and suggestions for reducing coal mine safety accidents are put forward from four dimensions，including safety supervision，strengthening safety through science and technology，team development and safety culture.

In order to effectively curb accidents，strengthen the guidance and support role of safety theory in power safety production，and overcome the mismatch between foreign theories and existing safety theory models that cannot meet the actual needs of complex power safety production，local characteristic power safety production management theories and models were constructed. Based on various advanced causal chains，causes of accidental energy release accidents，nuclear power protection barriers，and 4M barrier theories in China and abroad，combined with the objective reality of the safety production site of the power generation enterprise of CHN Energy Group and years of risk control experience，the reverse thinking of accidents (accident causes) and the positive thinking of risk pre-control (barrier control) were combined to propose the 4M barrier theory of machine & material，man，medium，and management in safety management of power generation enterprises. Through dynamic modeling，the internal accident evolution roots and prevention and control laws were analyzed，and the internal logical relationships of each element were sorted out. The results show that this theoretical model can provide a relatively systematic and new risk pre-control concept and methodology for power generation enterprises to establish a sound safety production risk management system by clarifying the risk and its barrier control objects and analyzing the accident development process and its causes.