In order to address the issue of missed detections during small target detection of aircraft rivets，an improved YOLOv8n algorithm for the detection of aircraft rivets and their anomalies was proposed. First，by adding a small object detection head，the shallow detail information in the backbone network was better fused，enhancing the model's feature fusion capability and its ability to recognize and locate small rivet targets. Second，the first two convolutions in the backbone network were replaced with SPD-Conv，which reduces information loss during down sampling through the combination of feature map reorganization and non-stride convolutions. Finally，large separable kernel attention (LSKA) was integrated into the spatial pyramid pooling fast (SPPF) module，capturing the dependencies between spatial and channel dimensions by calculating spatial and channel weights on each feature map and adjusting the feature maps to enhance the algorithm's ability to extract and recognize rivet feature information. Ablation experiments and comparative experiments were conducted based on a self-built aircraft rivet dataset. The results show that the proposed algorithm can achieve real-time identification of aircraft rivets and their anomalies，with precision，recall，and mean average precision (mAP) values improved by 6.5%，16%，and 15%，respectively，compared to the YOLOv8n algorithm. The detection performance is also significantly better than other mainstream algorithms.

In order to study the damage characteristics of gas explosion from double explosion sources in roadway wall，the gas explosion model of roadway with double explosion sources was established by using LS-Dyna，and the pressure propagation and impact stress of shock wave in roadway under the gas explosion action of double explosion sources were analyzed. The change of axial pressure in the roadway and the damage to surrounding rock in the symmetrical section were measured when gas explosion with double explosion sources occurred. The research results show that the interaction between the shock waves generated by double explosion sources in the roadway results in a significant disparity in pressure compared to that of a single explosion source. At each axial position where the gas explosions from the double sources occur，there are two distinct pressure peaks，with the magnitude of the first peak negatively correlated with its proximity to the nearest explosion source. The value of the second peak pressure is negatively correlated with its distance from the collision surface where shock waves from two sources meet. The peak pressures before and after this collision were not a simply linear superimposition，but a sharp rise. The damage evolution process on surrounding rock wall surfaces resembles that of diffusion for shock wave pressure propagation and shock stress，although it is lagging these two phenomena. Furthermore，the duration of shock wave action plays a crucial role in determining the thickness of damage inflicted on surrounding rock formations，with roof damage being most severe in roadways subjected to double explosion source gas explosions.

To investigate the methane adsorption mechanism in porous media，a methane adsorption model was constructed using the LAMMPS(Large-scale Atomic/Molecular Massively Parallel Simulator) software. And large-scale molecular dynamics simulations (28.6 nm×14.3 nm×125 nm) were conducted over an extended duration of 1 000 ns to obtain a stable adsorption system. The study primarily focused on exploring the effects of temperature and surface properties of porous media on methane adsorption behavior，revealing the underlying microscopic adsorption mechanism. Additionally，a nano-scale methane adsorption recognition algorithm was developed to precisely identify adsorbed methane molecules within porous media. The results showed that methane adsorption decreases with increasing temperature. The effect of temperature becomes negligible when it exceeds 500 K. When the gas-solid interaction parameter (ϕ) is less than 0.8 (contact angle less than 75.6°)，the surface characteristics of silica have a minimal effect on adsorption capacity.

To accurately identify and evaluate the fire risk in large-scale urban complexes，a fire risk assessment indicators system was constructed，consisting of 32 secondary indicators across six dimensions: building fire protection，fire protection facilities，electrical fire prevention，fire safety management，emergency response and coordination，and fire protection technical services. The order relation method was employed to determine the subjective weights of each indicator，while the entropy weight method was used to calculate the objective weights. Subsequently，a game-theory-based combined weighting approach was utilized to derive integrated weights，and a cloud model was applied to quantitatively analyze the fire risk of a large complex in a specific city. The results demonstrate that this combining model not only mitigates the subjectivity limitations in indicator weighting but also accounts for the fuzziness and randomness in the evaluation process. The primary risks of the large complex stem from fire protection technical services as well as emergency response and coordination，requiring preventive measures. Furthermore，the evaluation results are consistent with the actual situation，validating the feasibility of the proposed model in assessing fire risks for large-scale urban complexes.

To guide healthy travel for cyclists in hot weather，a cycling measurement platform using micro-sensors was developed to collect high-resolution data on cyclists' heart rates，as well as atmospheric particulate matter (i.e.，PM_2.5，PM₁₀，and BC(Black Carbon) on the non-motorized lanes of the Western Third-Ring Expressway in Fuzhou. Statistical analyses were conducted to characterize and interpret variations in cyclists' heart rates. Results indicate that cyclists' average heart rates near residential zones are higher than that of riverside segments，showing strong and sustained associations with all measured particulates. The number of diesel vehicles，ambient temperature，and atmospheric pressure are found to significantly influence the heart rate changes across sections of the entire route，riverside，and residential sections，respectively. Cyclists' heart rates also fluctuate due to varying environmental and topographical conditions along the route. Immediate effects of PM_2.5 and BC on heart rate are observed，while PM₁₀ effects are delayed. Therefore，implementing road-segment-specific control measures for motor vehicles，particularly strict regulation of those emitting pollutants with immediate effects on cyclists，and guiding the selection of routes with better roadside ventilation and higher greenery coverage，can effectively enhance the travel quality for cyclists.

To explore human error in complex emergency rescue scenarios for hazardous chemical accidents in chemical industry parks and improve human reliability in emergency rescue actions，a comprehensive analysis method was established to quantitatively evaluate the human reliability of emergency rescue for hazardous chemical accidents. Firstly，based on the laws，regulations and standards related to the emergency rescue of hazardous chemical accidents，20 emergency behaviors in chemical industry parks were summarized and extracted. Secondly，cognitive reliability and error analysis method(CREAM) was introduced to determine the probability of human error. Analytic hierarchy process(AHP) and entropy weight method were combined to quantify the severity of errors in emergency behaviors. Finally，from the perspectives of possibility and severity，the weak aspects of emergency behaviors in chemical industry parks were explored，and the strategies for enhancing emergency rescue capabilities in chemical industry parks were discussed. The practical application of the method was verified with the example of N chemical industry park. The results show that 20 emergency behaviors were divided into 3 clusters. There are 4 emergency behaviors identified that needed to be prioritized for improvement in the petrochemical zone: risk assessment，fire-fighting，initial disposal of enterprises and rescue of people in distress. For these emergency behaviors，it was proposed that N chemical industry park should focus on optimizing the accident information transmission mechanism，improving decision-making and command effectiveness，and strengthening rapid response and disaster identification capabilities，so as to provide countermeasures and suggestions for improving its emergency rescue capability.

In order to assess the resilience of CPS in airport flight areas and provide a reference for rapid recovery in emergencies，a refined and real-time airport flight area CPS network model with flight area control network as the information network and flight area taxi path network as the physical network was proposed. For CPS network in airfield areas，the connectivity of the network was calculated by selecting the relative values of the largest connected subgraphs. The network's resilience was evaluated by combining robustness，performance loss，and comprehensive resilience indicators. CPS situation in airfield areas under different disturbance recovery strategies was compared to determine the optimal recovery strategy. Taking Xi'an Xianyang Airport flight area CPS as an example，the results show that betweenness perturbation causes the greatest damage to the control network，while degree value perturbation causes the greatest damage to the taxiing path network. Using betweenness recovery can enable faster recovery of CPS resilience in airfield areas，and CPS network of the flight area of the airport shows a higher level of resilience under random perturbation. The research results can simulate and predict relevant nodes and provide certain reference significance for ensuring the safety of flight area operations.

To address the flight safety risks posed by faults in aircraft control systems，a composite framework for fault risk assessment based on IRPN was proposed. This framework comprehensively considered four key risk factors: fault probability，severity，detectability，and risk damping. First，system fault modes were deduced bidirectionally using FMECA-FTA method. Second，human and environmental factors were incorporated，and a Bayesian network approach was employed to construct a hybrid probability model for calculating fault probabilities. Third，fault severity was categorized into three evaluation parameters，which were comprehensively assessed using the Analytic Hierarchy Process and Fuzzy Comprehensive Evaluation methods. Next，utilizing resources such as pilot quick reference manuals and aircraft type design manuals，a criterion-based reasoning method was applied to establish detectability scoring criteria，allowing for a more scientific evaluation of fault mode detectability levels. Finally，the FRAM was introduced to define risk damping coefficients，characterizing the propagation of risk during the evolution of fault risks. The computational validation was carried out with the case of jamming failure mode of aircraft flap seam wing actuation system. The research results show that its IRPN assessment result is 158，which is in perfect agreement with the actual operation. The validity and accuracy of the failure composite risk index calculated by the IRPN composite risk assessment framework are confirmed by the failure mode example simulation and the real verification of unsafe events.

In order to predict coal gas permeability more accurately and ensure coal mine safety production，a prediction model of coal gas permeability based on ISSA-optimized BPNN was constructed. Firstly，the sparrow search algorithm (SSA) was improved by introducing Sine chaotic mapping and Gaussian mutation to enhance its global search capability and local optimization accuracy，thereby optimizing the weight and threshold configuration of BPNN. Secondly，the data on the factors affecting gas permeability were processed using Pearson correlation coefficient matrix and kernel principal component analysis (KPCA) to improve the computational efficiency and accuracy of the model. Three principal components with a cumulative variance of 88.59% were extracted as model inputs，and permeability was used as the output for the experiment. Finally，the model was applied to a coal mine in Shanxi for case verification. The experimental results show that ISSA-BPNN outperforms PSO-BPNN，PSO-SVM，PSO-LSSVM，and SSA-BPNN models in four indicators: mean absolute error (MAE)，mean absolute percentage error (MAPE)，root mean square error (RMSE)，root mean square error (RMSE)，and coefficient of determination (R²). Compared with other models，ISSA-BPNN has reduced MAE by 0.032 7，0.022，0.017 9，and 0.018 2 in the test samples，respectively. MAPE decreases by 5.15%，3.14%，2.76%，and 2.36% respectively. RMSE decreases by 0.031 6，0.027 9，0.018 8，and 0.022 2 respectively. R² increases by 0.077 5，0.065 8，0.040 1，and 0.049 3，respectively. Finally，the case verification shows that its reliability and stability are high in practical applications.

In order to reduce the failure risk of petrochemical storage tanks in coastal areas under the influence of hurricanes，the failure model for vertical cylindrical tanks under wind load was established based on the strength stress interference theory. The critical wind speed for the buckling failure was determined by an example of a crude oil storage tank. For different random distributions of parameters，such as wind speed，the Monte Carlo method was also used to plot the probability curve of shell buckling failure. The buckling failure mechanism under static conditions was investigated，and the failure probability at different loading levels was determined under static conditions. The results show that the critical wind speeds are 60.67，65.38 and 69.79 m/s respectively when the loading levels are 25%，50% and 75% under the same wind load. According to the failure probability curve，the failure probability of the loading level of 25% is significant greater than that at 50%. Therefore，it can be seen that the buckling failure mechanism of the vertical cylindrical storage tank shell is as follows: the loading level is too low，which can easily lead to buckling failure of the storage tank under wind load. The higher the loading level，and the stronger the wind load resistance of the vertical cylindrical storage tank. Appropriate measures can be taken to increase the loading level to resist strong wind loads in the coastal chemical industries.