In order to accurately identify unsafe behaviors during the climbing process of high-altitude workers，this paper proposed an unsafe behavior recognizing method for high climbing workers based on vision，which included the human pose estimation and the one-dimensional convolutional unsafe behavior recognition models. Quantized autoencoder was used to structurally model human key points in human pose estimation，enabling the detection of human key point coordinates. Combining with safety behavior knowledge in high climbing operations，the unsafe behavior recognition model was constructed based on one-dimensional convolutional neural network model，and it was validated by industrial data experiments. Experimental results show that the accuracy of this method is 93.91% and 90.34% on unobstructed and partially obstructed datasets，respectively. Moreover，compared with support vector machines (SVM) and K-nearest neighbor (KNN)，this method has stronger generalization capability.

In order to systematically review the research and development status of safety resilience in the field of civil aviation at home and abroad，and deepen the research on safety resilience in the field of civil aviation，firstly，the concept of aviation safety resilience was explored by reviewing policy documents，standards and research literature related to air transport systems in recent years. Then the research and application of safety resilience in civil aviation airport，air traffic control，flight operation and other fields were discussed. Finally，the existing problems were analyzed and corresponding suggestions and prospects are put forward. The results show that the safety management of civil aviation has formed a relatively perfect system，and the safety resilience covers all stages of safety management before，during and after，but it still cannot meet the needs of perfect connection and integration with the existing safety management system. Current studies focus more on the resilience of airports and route networks. In terms flight operation，more measures are taken to improve safety resilience based on the actual flight operation. The basic research on aviation resilience assessment is relatively lacking，and the research on aviation personnel resilience at operational level is far from enough. In the future，relevant research should be carried out around the individual operation resilience，enrich the basic research of resilience assessment，further deepen the research and form a relatively stable discipline system，pay attention to the connection between safety resilience and safety management system，and assess individual operation resilience from the perspective of safety.

To improve the detection efficiency and automation level of detecting road surface pits and grooves in road safety inspection work, reduce the probability of traffic accidents. A road surface pit and groove hazard intelligent detection model based on an improved YOLOv5s was proposed. This method incorporated the ASFF module into the original YOLOv5s network, replaced the backbone network with the FasterNet network, and further introduced the Efficient Channel Attention (ECA) module. Ablation experiments are conducted to analyze the effect of the improved module on performance of the detection model, to verify the target detection effect, and to develop an interactive visualized detection interface. The results show that the improved model accuracy, recall rate, and average detection accuracy have increased by 4.1%, 9.9% and 5.6% respectively. Compared to the original network, the improvement is significant. It demonstrats good detection performance that meets the application requirements for automated detection of road surface pits and grooves, thereby enhancing inspection efficiency and effectively reducing traffic accidents caused by road surface pits and grooves.

To explore the effects of dust-generating processes and environmental fluids on the spatiotemporal distribution of dust during the regeneration of old industrial buildings, field studies and numerical simulation was used to investigate the dust suppression characteristics inside the construction area under different processes and background wind speeds. The dust source characteristics in the main processes of re-construction of old industrial buildings were clarified by analyzing a large amount of dust data. Typical old industrial buildings were selected for the field studies of sanding and shoveling processes. Numerical simulation was performed to investigate the dust mass concentration distribution under five inlet air velocities and two dust-producing processes and to identify the dust-aggregation zones in the reclaimed construction space of old industrial buildings. The results showed that the maximum dust mass concentration in the grinding process exceeded the limit by 54 and 37 times in the grinding and shoveling process, respectively. Inlet wind speed affected the dust mass distribution of the main impact zones in the construction area and changed the process of dust reaching dynamic equilibrium. Dust-generating process variations impacted on the dust mass concentration distribution. Moreover, the workload increase of a specific process resulted in a proportional increase in downstream dust mass concentrations. This study can provide fundamental knowledge for dust management in the reconstruction of old industrial buildings.

In order to investigate the threshold conditions for pedestrian destabilization, controlled experiments were conducted in three different scenarios, including "two-person collision experiment", "multiple-person collision experiment" and "high-density multiple-person collision experiment". A pedestrian flow model was constructed, considering collision pressure, speed, density and volume. Additionally, experimental videos and collision pressure data were collected by using an unmanned aerial vehicle(UAV)and pressure sensing equipment, respectively. The changing rules of pedestrian trajectory, pedestrian flow characteristics, and collision pressure were obtained by data analysis. On this basis, the segmented Hermite triple interpolation was used to investigate the influence of speed and density on collision pressure. Finally, based on the Van Aerde model, a four-dimensional model of "pressure-speed-density-volume" was constructed by introducing the parameters of collision pressure to judge the threshold conditions of pedestrian flow instability. The results show that pedestrian flow begins at 2.46 persons/m² and reaches complete instability at 3.59 persons/m². During the instability process, the pedestrian may be subjected to the collision pressure ranging from 187.32 N to 258.11 N. The results provide references for the control of the pedestrian flow and the improvement of pedestrian traffic safety.

In order to evaluate the heat strain level of outdoor workers in high temperature environments, a thermal response model was developed based on the Tanabe 65 thermal physiological model and principles of heat transfer by modifying basal metabolic rate and human surface area of the original model. The experimental data in the literature and the Tanabe model were used to verify the effectiveness of the model. The results show that the predicted results of the high temperature human thermal reaction model established under different solar radiation intensities are in good agreement with the experimental results. In an extreme environment of 36 ℃ and high solar radiation intensity, the maximum difference between the simulated value of core temperature and the measured value is less than 0.24 ℃, and the maximum difference between the simulated value of average skin temperature and the measured value is less than 0.3 ℃, which is more accurate than the classic Tanabe model. Thus, the established model can be used to predict human physiological parameters such as human core temperature and skin temperature in hot environments in the presence of solar radiation, and provide reference for the safety assessment of outdoor workers.

To reduce the risk of rear-end collisions in highway tunnels, a tunnel reflective strip space model was proposed based on the tunnel reflective strip characteristics with depth perception information. The effects of spacing between tunnel reflective strips on vehicle distance maintenance were examined through driving simulation tests. Braking headway, minimum headway, following headway, and minimum collision time were selected as evaluation indicators. The results indicated that when the leading vehicle traveled at speeds between 40-80 km/h and the following vehicle approached at a speed 20 km/h higher than the leading vehicle, if the following driver received 3-4 visual stimulations from the reflective strips before the distance between the leading and following vehicles was less than the minimum safe distance, the braking headway, minimum headway, and the time headway under stable car-following conditions was improved by 27.6%-56.6%, 54.2%-60.3%, and 20.1%-31.6%, respectively. Furthermore, the minimum collision time was increased by 34.7%-60.5% once the leading vehicle braked urgently, reducing the probability of a rear-end collision. Therefore, tunnel reflective strips enhance drivers' perception of speed and distance perception ability, reducing the risk of rear-end collisions.

In the early stages of a major disaster, where demand at disaster sites is uncertain, roads are damaged in affected areas, and the fairness and timeliness of rescue operations must be considered, the SNS algorithm is applied to solve the emergency supply distribution model to achieve rapid and effective distribution of emergency supplies. First, an emergency supply distribution model was constructed, with the objective of minimizing the total cost of emergency rescue and the evaluation of humanitarian aid under the background of fuzzy demand and damaged roads. Then, the SNS algorithm was introduced to solve the model, and an improved SNS(ISNS) algorithm with a reinforcement learning rate strategy was proposed. Finally, taking the 2022 Luding Earthquake in Sichuan as an example, the SNS algorithm, ISNS algorithm, discrete particle swarm optimization, genetic algorithm, and simulated annealing algorithm were applied to solve this case, respectively. The results indicate that the ISNS algorithm demonstrates stability. Compared with other algorithms, the total cost of emergency rescue is reduced by at least 6 410 yuan, and the evaluation of the humanitarian aid evaluation target is improved by at least 50.6%, highlighting the superiority of the ISNS algorithm. The ISNS algorithm is beneficial for solving emergency supply distribution problems.

In order to make up for the deficiency of VR technology in safety education theory support and practical effect tests, the relevant influencing factors affecting the effect of engineering safety education were taken as the entry point. SEM was used to establish an analytical framework for the influencing factors of safety education and the cognitive experiments were carried out to test the effect. The results show that the frequency of education, the mode of education, individual initiative, fun and comfort are the main factors affecting the effectiveness of construction safety education. The hybrid mode of "VR + lecture" is the most effective educational method at present, but the use of VR technology still requires personnel assistance. The optimal frequency of education is recommended to be less than 30 days. The main factors of fun, comfort are significantly positively correlated with educational effect, but comfort is more important in the application of construction safety education with VR technology.

To improve the safety risk prediction accuracy of injection-production string, a joint simulation analysis method was used to perform finite element verification of the fatigue crack propagation process of straight-notch compact tensile specimens. Then, a finite element model of fatigue crack propagation of injection-production string with external surface cracks in gas storage was proposed. Moreover, the injection-production strings' fatigue crack propagation behavior was analyzed under alternating pressure loads. The results indicated that the specimen simulations were consistent with the fatigue crack test results, indicating that the joint simulation method had high accuracy in fatigue crack propagation analysis. During the fatigue crack propagation of the injection-production string, the larger the initial crack's length-to-depth ratio or the higher the stress ratio, the faster the crack propagation rate with a critical minimum crack length of 4 mm. Under the same number of pressure load cycles, the larger the initial crack's circumferential angle, the longer the surface crack propagates, and the critical minimum circumferential angle was 45°. The crack consistently propagated along the axis of the pipe string regardless of the initial crack's circumferential angle, and the unstable propagation length was 52 mm. During alternating injection and production in gas storage, the amplitude of the alternating pressure load should be properly controlled to avoid the initiation and propagation of fatigue cracks.