In order to study the wall dynamic response and damage characteristics of deep roadway with high geostress in gas explosion accidents，a mathematical model and a physical analysis model of the roadway wall dynamic response damage were established by using LS-Dyna software，and the numerical model was verified. The displacement，stress and damage characteristics of the roadway wall under the dynamic and static loads of gas explosion impact and geostress were analyzed by numerical simulation. The response and damage change of the roadway wall under different geostress conditions (horizontal geostress and vertical geostress) and gas explosion impact loads were investigated. The results show that high geostress causes the initial damage deformation. The stress concentration and initial damage are greatest at the corner，but its dynamic response is smaller than that at the roof. Under the dynamic and static loads of gas explosion impact and geostress，the damage strain of each part of the roadway increases with the increase of geostress，among which the damage degree at the corners is most affected and most serious，followed by the roof position. The increase of geostress makes the initial damage deformation of the roadway wall more serious，but it obviously weakens the propagation of the shock wave in the surrounding rock.

In order to investigate the expansion law of high flow grouting material and the creep mechanical properties and pore structure of coal after grouting，a new nonlinear viscoplastic element was created and a creep mechanical model was constructed. Firstly，the high flow grouting material was prepared and injected into the coal body to simulate the coal body grouting around the borehole. Secondly，mercury injection experiment and uniaxial fractional loading creep test were used to test the pore structure of the coal after grouting and the creep performance of the coal under different stress levels，and the strain variation law of the coal at different creep stages was obtained. Finally，based on the creep test results，a new nonlinear viscoplastic element was constructed and introduced into the Boedin-Thomson model. Finally，the relevant parameters of the creep model were obtained by inversion，the reliability of the model was verified，and the creep instability failure law of the coal after grouting was obtained. The results show that the expansion rate of high flow grouting material is 92% higher than that of ordinary cement material，which effectively improves the shrinkage problem of cement-based grouting material after curing. After the high flow grouting material is injected into the coal body，the critical load of instability failure of the coal body is 15.3 MPa，which improves the stability of the coal body to some extent.

In order to elucidate the impact of varying sleep patterns on cognitive performance，this study leveraged the principle of complementarity among different chronotypes. This approach guided the strategic pairing of personnel for morning，evening，and night shifts，with the goal of enhancing operational safety and efficiency. The research involved a regimen of fixed sleep schedules，subjecting individuals with distinct sleep preferences to 30 hours of sleep deprivation. During this period，participants' HRV and levels of sustained attention were closely monitored. Moreover，the study utilized several established tools to evaluate fatigue in sleep-deprived individuals: the Karolinska Sleepiness Scale (KSS)，the Morningness-Eveningness Questionnaire (MEQ)，and the Pittsburgh Sleep Quality Index (PSQI). Findings revealed that，throughout the sleep deprivation period，individuals with a preference for evening activities exhibited significantly more pronounced variations in HRV time-domain indicators (RMSSD=38.301±17.056，P<0.001). These variations were characterized by greater fluctuation intensity and amplitude，as well as more evident periodicity. KSS scores across all chronotypes show a general upward trend，with those of intermediate chronotypes displaying the highest correlation with HRV frequency-domain indicators (LF/HF=0.769，P<0.05). Morning-oriented individuals demonstrated higher levels of sustained attention between 11:00 AM and 5:00 PM，with accuracy rate linear regression coefficients ranging from 1.5 to 1.7 (×10^-4). In contrast，individuals with intermediate sleep patterns peaked in attention from 7:00 AM to 12:00 PM，while evening-oriented participants exhibited significantly different patterns compared to the other two groups.

To improve the applicability and scalability of the joint reserve model for social emergency supplies，and reduce the reserve risks of the government and manufacturers，raw material suppliers were used to propose a government-led Stackelberg three-tier joint reserve model of government and enterprises under a quantity flexibility contract. In this model，the government and manufacturer engaged in joint a stockpile of physical emergency supplies，while the suppliers were responsible for stockpiling raw materials for the production of emergency supplies. The inverse-order solution method in game theory was used to analyze the optimal reserve quantity of the three parties to balance the expected profit and cost. Moreover，the advantages of the proposed three-tier supply chain model involving government and enterprises were evaluated. Finally，the model performance was validated by numerical simulation and sensitivity analysis. The results demonstrated that the three-tier joint government-enterprise stockpile model not only improved the overall emergency stockpile volume under specific market conditions but also reduced the government's storage risk. Furthermore，it can enhance the profitability of high-performing enterprises and reinforce the structure and efficacy of the emergency stockpile system.

In the application process of blockchain technology，insufficient attention has been paid to the research on safety barriers that are more suitable for preventing complex system safety problems. To solve this problem，firstly，the safety requirements of blockchain itself and the support of safety barrier theory were introduced，which was combined with the security application of blockchain technology in the industrial field. Then，the main safety barrier models within qualitative and quantitative perspectives were summarized，so were the progress of security analysis model of software system and of performance evaluation of safety barrier. Then，the research status of safety precautions related to security risks of blockchain technology was summarized. Finally，in accordance with the trend of coupling coordination in safety barrier models，a research framework of safety barrier models related to the application of blockchain technology was put forward，which was based on the research progress of quantitative methods studying complex system coupling coordination and complex causal mechanism. It was a framework system including safety analysis，situational construction，system modeling，mechanism analysis，effect assessment and implementation path. The results show that the research on the safety barrier models related to blockchain technology should cover static series diagram pattern with Bow-Tie model as core and ARAMIS(Accidental Risk Assessment Methodology for Industries System) and coupling perspective STAMP (Systems Theoretic Accident Model and Processes) models as integrators，dynamic evolution mechanism research that includes dynamic Bayesian network analysis by transforming the static models into BN，and the effect assessment of safety barrier system. The study on coupling coordination and nonlinear causal analysis focusing on entropy deepen this coupling integration research system.

To improve the emergency preparedness and response capabilities of spent fuel reprocessing nuclear accidents，a spent fuel reprocessing nuclear accident emergency scenario based on knowledge meta was proposed to address the uncertainty of the nuclear accident emergency evolution process，the importance of scenario analysis in emergency response decision-making，the complexity of the evolution process，and the difficulty of organization and implementation. The disaster event，causative agent，causal agent，and emergency response were determined，and then a dynamic scenario model for spent fuel reprocessing nuclear emergencies based on a DBN was developed to calculate the occurrence probability of key scenarios，evaluate the development trend of the scenarios，and analyze the evolution laws and paths. Taking the explosion of the high-release liquid storage tank of the Mayak spent fuel reprocessing plant as an example，the process of deduction of the scenario analysis method of the spent fuel reprocessing nuclear accident based on the knowledge meta theory and DBN was performed，and the results were further analyzed. The results showed that: the loss probability of emergency cooling water supply was 73%，the probability of explosion of the high-release waste liquid storage tank was 86%，the probability of radioactive nuclides transferred to animal and plant products and drinking water through multiple pathways was 87%，the probability of long-lived radioactive nuclides deposition in part of the area was 89%，and the probability of the event calming down and dying out was 72%. The probability of the accident contaminating the air，soil，and river was 89%，85%，and 81%，respectively. The probability of affecting public health and safety was 86%. The scenario evolution process is consistent with the emergency response development of the reprocessing storage tank explosion accident and its impact on the public and the environment，validating the model performance.

To address the challenge of extracting pulse signals in fault diagnosis of variable-load gearbox caused by redundant features，a pulse feature extraction method based on CAM was proposed. First，a CAM was designed，which consisted of two stages. In the first stage，a multilayer perceptron was used to simulate the channel dependencies and enhanced the important channel features related to faults. In the second stage，the convolutional layers were employed to learn signal segments related to faults. By recalibrating the features in two stages，the module focused on the critical pulse features. Next，based on CAM，this study proposed a CLDN method for extracting fault features in variable-load gearboxes. CLDN further improved the learning and representation of impulse signals by adaptively recalibrating the features at each layer. Finally，the extracted features were fed into a Softmax classifier to validate the feature extraction effect of the proposed method. The results show that CAM's accuracy is on average 3.8% higher than 4 attention mechanisms like Self-Attention，achieving accurate localization of impulse features. Compared with 7 diagnostic methods such as ResNet34，the accuracy of CLDN is 3.7% to 14.6% higher，which significantly enhances the extraction of fault features.

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).

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.

To standardize the content and quality of urban lifeline operational monitoring services，a standard system for urban lifeline operational monitoring services was proposed. Based on the mature experience of operational monitoring services and "Guidelines for standardization of organizations in service sector—Part 2: Standard system construction"，the proposed standard was divided into a general service basic standard system，service provision standard system，service guarantee standard system，and position standard system. A standardized and systematic operational monitoring service process was developed from the aspects of standard implementation foundation，operation service content，service quality assurance，and job responsibilities，to comprehensively guarantee the quality of urban lifeline operational monitoring services. The results indicated that the urban lifeline operational monitoring services standard system effectively addressed issues，such as untimely early warning responses and overlapping job functions. However，it should be continuously updated and improved in conjunction with industry development trends to fully promote the standard system implementation.