In order to improve the emergency management ability and effect of local governments and promote the modernization of emergency management systems and capacity，the game theory was used to construct a game model. The evolutionary game relationship between audit institutions，local governments and surrounding governments was discussed. The root causes of the three were explored through model stability analysis and numerical simulation. Corresponding countermeasures and suggestions were put forward according to the analysis results. The results show that the benefit of emergency management is the key to the evolution of the behavior of local governments and surrounding governments. In addition，the probability of active supervision by audit institutions and the size of audit costs have an impact on the behavior choices of the two governments，and the willingness of the two governments to participate in emergency management also has an impact on each other. For audit institutions，the cost of auditing and the degree of accountability are key factors that influence their behavioral choices.

In order to effectively identify construction risks and prevent safety accidents，this study investigated the safety evaluation method for metro station construction in confined space under 500 kV high-voltage lines. First，a safety evaluation index system for metro station construction under high-voltage lines was established by integrating AHP and 3MET(Management，Man，Machine，Environment，Technology) method. Then，the weights of indicators were calculated using the IOWA operator，and the cloud model was applied to determine evaluation standard clouds and cloud characteristic values，thereby deriving the comprehensive safety evaluation grade. Finally，the proposed method was validated through a case of the University Town Central Road Station on Chongqing Metro Line 15，with corresponding mitigation measures proposed for high-risk indicators. The results demonstrate that the evaluation model accurately identifies high-risk sources in metro station construction under high-voltage lines，with the safety evaluation grade classified as lower risk，consistent with on-site conditions. Key considerations for safety measures include the electromagnetic field effects of high-voltage lines，risk monitoring and protection，mechanical equipment selection and its safety functions. The application of multi-dimensional layered protective structures could effectively mitigate construction risks under high-voltage environments.

In order to improve the efficiency and accuracy of safety risk management in machinery manufacturing enterprises，the Bayesian network and machine vision technology were combined. Based on improved YOLOv5，Intersection over Union(IoU) values of safety hazard events occurring at the operation site were calculated. By leveraging the audit risk assessment in conjunction with AHP to derive the danger weights，the prior probabilities of the root nodes of Bayesian network were determined. Bayesian network model and design management system were established to realize closed-loop control. A safety risk management model of machinery manufacturing enterprises was constructed and verified by examples. The results show that the model has a more accurate identification and evaluation ability，and can find some potential safety hazards，so as to optimize the current management process. At the same time，the model also successfully realizes the effective combination of qualitative and quantitative analysis，integrates the expert experience and data quantification results，and confirms each other，so that the risk assessment results have a certain improvement in scientificity and reliability，which can provide a practical new idea for safety risk management.

To meet the requirements of the future Trajectory-Based Operation (TBO) mode，improve air traffic safety and efficiency，and obtain executable four-dimensional (4D) trajectory results with multi-point control，this study first established a fundamental 4D trajectory dynamics model by integrating atmospheric environment modeling，aircraft point-mass motion modeling，and performance modeling. Subsequently，a 4D trajectory simulation framework was developed using Simulink to validate the executability of the fundamental dynamics model. Following this，an optimal control-based 4D trajectory waypoint control model was constructed with reference trajectories as optimization targets，where the waypoint control problem was transformed into a nonlinear programming problem through the Radau pseudospectral method. Finally，comparative analyses were conducted using historical flight data from QAR. Results demonstrate that the simulated velocity and mass parameters exhibit zero deviation from QAR records，while median errors in longitude，latitude，and altitude are 0.000 11°，0.001 2°，and 19.24 m，respectively，all satisfying safety separation requirements. Critical parameters including position，time，and heading angle at selected waypoints showed zero deviation. Notably，strict control of 13 waypoints is achieved within a 65-minute flight segment.

To accurately and efficiently detect fires in complex tunnel environments，an enhanced YOLOv8s-based tunnel fire detection algorithm was proposed. Firstly，the Cross-Stage Partial Transformer Block (CSP-PTB) module was introduced to reconstruct the backbone network structure，thereby reducing computational complexity while preserving feature extraction capabilities. Secondly，CBAM was integrated to enhance the perception of the model of key areas and improve the discriminative power of feature representation. Finally，the Normalized Wasserstein Distance (NWD) loss function was employed to optimize the training process，effectively addressing the issue of insufficient detection accuracy for small targets. Experimental results demonstrate that the improved YOLOv8s model achieves a mean average precision (mAP) of 0.848，representing a 2% improvement over the original YOLOv8s model. The recall rate reachs 0.812，marking a significant increase of 9.3% compared to the original model. Additionally，the computational cost (GFLOPS) of the improved model is reduced by 6.7%，achieving dual objectives of performance enhancement and efficiency optimization. Compared with mainstream object detection models such as Faster R-CNN(Faster Region-based Convolutional Neural Network)，SSD(Single Shot MultiBox Detector)，and YOLOv5s，the improved model exhibits superior performance，with mAP improvements of 7.3%，10.1%，and 4.2%，respectively，thus meeting the stringent requirements for tunnel fire detection.

To comprehensively and efficiently analyze and evaluate chemical process risks，a risk analysis and evaluation auxiliary system for chemical processes was designed and developed based on SDG and CBR. The system was integrated with foundational verification functions for layer of protection analysis (LOPA) and safety integrity level (SIL)，enabling semi-quantitative risk analysis and evaluation. Additionally，CBR technology was utilized to effectively preserve and reuse historical case experiences in chemical processes，thereby enhancing the efficacy of HAZOP and the auxiliary evaluation system. The system was applied to conduct a risk evaluation of the propylene oxidation to acrylic acid process. The results demonstrate that the system aligns closely with the independent risk evaluation outcomes of the enterprise，exhibiting strong practicality and reliability. The SDG-CBR coupling reasoning mechanism is verified to overcome the reliance of traditional HAZOP on manual experience，achieving a qualitative-to-semi-quantitative transformation in hazard identification while enhancing evaluation efficiency and accuracy.

To reduce building risks in landslide-prone areas and guide disaster mitigation measures，a comprehensive vulnerability analysis method was proposed based on Entropy Weight Method(EWM)-Analytic Hierarchy Process(AHP) and trapezoidal-semi-trapezoidal membership functions. Using the Sifangbei landslide in Wanzhou District，Chongqing，as a case study. The landslide failure probability was calculated using the Morgenstern-Price and Monte Carlo methods. Field surveys of building attributes were used to analyze landslide hazards and validate the analysis method. The results indicate that the composite model using crack indicators provides reliable vulnerability analysis for buildings in the Sifangbei landslide zone. The proposed method is feasible. The landslide is most dangerous when the reservoir water level drops from 175 m to 145 m. Combined with a 50-year rainfall event，leading to over 7.5 million yuan in economic losses. Vulnerable buildings are mainly located in the middle and rear parts of the landslide and along its right boundary.

To optimize the mixed inert gas fire suppression technique for goafs，the effects of CO₂/N₂ ratio and O₂ volume fraction on the low-temperature oxidation characteristics of coal were investigated. Taking the long flame coal from Dongxia mine in Gansu as the research subject，a temperature-programmed experimental system combined with gas chromatography analysis was employed to carry out low-temperature oxidation experiments under various CO₂/N₂ ratios (ranging from 0∶10 to 10∶0) and O₂ volume fractions (6%，10%，14%，and 18%). The results indicate that at the same O₂ volume fraction，as the CO₂/N₂ ratio increases，the rates of oxygen consumption and CO production of the long-flame coal gradually slow down，with the decline rates increasing as the temperature rises. The apparent activation energy of the long-flame coal increases gradually with the increase in the CO₂/N₂ ratio during the slow oxidation stage，while it initially increases and then decreases during the accelerated and rapid oxidation stages，reaching the maximum value at a CO₂/N₂ ratio of 4∶6.

To improve the application of small-angle inclined piles in collapsible loess areas，finite element models of 2×2 pile groups with three different inclination angles were established. The modulus reduction method was employed to simulate the collapsibility effect of loess，and the influence of loading and soaking sequences on the bearing characteristics of pile groups with different inclination angles was analyzed. The results indicate that，based on the conducted tests of 0，10 and 15° pile groups，under both loading-before-soaking and soaking-before-loading conditions，the displacement of the pile cap and the settlement of the surrounding foundation soil are smaller for inclined pile groups compared to vertical pile groups. Moreover，the inclined pile group is less affected by the water-induced collapsibility of loess. However，the bending moment and shear force of the inclined piles are higher than those of the vertical piles. Compared to the loading-before-soaking condition，the soaking-before-loading condition results in smaller pile cap displacements and soil settlements but larger internal forces in the inclined pile shafts. Additionally，the shaft friction of inclined piles is smaller under the soaking-before-loading condition. Inclined pile groups with larger inclination angles demonstrate superior load-bearing capacity and resistance to loess collapsibility induced by soaking. Pre-soaking treatment of loess foundations effectively enhances the ultimate bearing capacity of pile group foundations.

In order to effectively prevent cross operation accidents in the construction process，firstly，130 cross operation accident cases nationwide from 2010 to 2022 were collected as research objects，and an evaluation system for cross operation in construction was established based on the grounded theory. Then，according to the relationship between the indicators，a spectral clustering algorithm was used to analyze the combination of accident causes. The weight of each cause factor was allocated，and different levels of risk were divided by principal component analysis and analytic hierarchy process. Finally，the Apriori algorithm was used to obtain the correlation chain of each factor in the causative combination. The results show that the evaluation system includes 5 core categories，13 main categories and 40 categories. The core category that has the greatest influence on the risk of cross operation in the construction process is technical management. The 40 categories are grouped into 4 causa l combinations，among which 1 is high risk，1 is medium risk，and 2 are low risk. In addition，for the complex cluster of factors，the key combination of causes is identified and targeted preventive measures are proposed to reduce the probability of cross-operation accidents.