In order to effectively evaluate and control the operational risks of unmanned aerial vehicle(UAV), based on the summary of various risk factors of UAV ground impact, the possible causes of UAV ground impact were analyzed, corresponding control measures were determined, and a safety barrier model combining risk analysis and control technology was established. It can clearly display the logical relationship between the causes of UAV operation safety, mitigation measures and accident consequences. Bow-tie (BT) model was mapped to Bayesian network (BN), each element of BT model was quantified, and the probability of unsafe events was calculated. The results show that the model can clearly show the risk control process and effectively reduce the operational risk of UAV. It provides an efficient and practical method for the operational risk assessment and control of UAV.

Explicit content features of webpages are often unavailable due to distractions such as commercials, insufficient permissions, privacy protection, or deceptive disguises. To address the challenge of classifying webpages with severe content feature deficiency, a method combining graph embedding and extreme gradient boosting(XGBoost) was proposed. This method leveraged implicit relational features in webpage hyperlink networks for multi-classification. Firstly, a hyperlink network was constructed using relationships between webpages. Then, node features were extracted using graph embedding models, and statistical structural features such as clustering coefficients and PageRank values were concatenated to form dense feature vectors. Finally, ensemble learning models, including XGBoost, were trained to classify webpages for prediction. Experiments on a real Wikipedia dataset show that the Struct2Vec*+XGBoost approach achieves excellent classification results, with accuracy, precision, recall, and F₁-score metrics reaching 0.987 5, 0.965 9, 0.971 3, and 0.964 1, respectively. These results are superior to those of comparison models. The findings demonstrate the effectiveness of using implicit link-based features for webpage classification in scenarios with content feature deficiency.

Shield tunnel construction impacts old buildings in urban areas. Extensive building deformation data was collected for Tianjin Metro Line 7’s shield tunnel passing beneath old buildings using automated measurement robots. Machine learning algorithms were applied to analyze the correlation between building instantaneous settlement and shield construction parameters such as average velocity, thrust, grouting volume, shield distance, and grouting pressure. A predictive model for building settlement was established. The results show that old buildings within -50~70 m are affected by shield construction. Differential settlement is significant, with noticeable differences on various facades. Grouting volume, thrust, and average velocity positively correlate with instantaneous settlement, with shield distance having the greatest impact. Reasonable construction parameters ensure building settlement and deformation remain within acceptable limits. The machine learning-based predictive model closely aligns with actual settlement curves, demonstrating robust predictive capabilities. This provides valuable insights for predicting and controlling surface settlement in future shield tunnel projects.

With the development of urbanization, the number and scale of sewage treatment plants are increasing, and the effective collection of odor generated by them is of great significance to prevent odor leakage, protect the environment and reduce energy consumption. The influence of structural parameters (different tube bundle positions, different tube bundle numbers, different pipe diameters) and operating parameters (suction flow) on the internal flow field of the odor collection hood of a sewage treatment plant was studied by numerical simulation. The results show that when the tube bundle is placed at the very edge of the air collecting hood, the number of suction pipes is three, the diameter of pipe is 150 mm, and the suction flow range is 3.63 kg/s to 5.71 kg/s, the airflow structure in the cavity is the best, the odor concentration is the lowest, and the suction effect is the best.

The evaluation of expressway network resilience has been emphasized due to significant global emergencies. Utilizing complex network theory and the resilience triangle model, a dynamic system was developed to assess the comprehensive performance of nodes, incorporating local, global, and social attributes. A method for evaluating the resilience of expressway networks was proposed, consisting of four stages: initial, disruption, recovery, and stabilization. Six disruption and recovery strategies (node degree, eigenvector, betweenness, accessibility, social attributes, and random selection) were applied to analyze the network’s performance using three key indicators: the number of independent paths, network efficiency, and network connectivity. A topological map of the expressway network spanning the provinces of Shanxi, Shandong, Henan, and Hebei were constructed, and the resilience changes under various disruption and recovery strategies were analyzed. The findings indicate that in the initial stage, the expressway network exhibits a relatively high number of independent paths, suggesting robust anti-risk capabilities. During the disruption stage, network efficiency, the number of independent paths, and network connectivity decrease by 94.32%, 98.18%, and 99.63%, respectively, demonstrating the network’s ability to absorb disruptions. In the recovery stage, the accessibility restoration strategy, which results in the smallest resilience triangle area, exhibits the strongest resilience, whereas the random restoration strategy shows the slowest recovery rate, indicating that it should be avoided whenever possible. In the stabilization stage, network efficiency resilience is found to be superior to that of network connectivity and independent path resilience in the expressway network of the four provinces. It is recommended that urban nodes with higher degree values, such as Xinxiang and Puyang, be prioritized for protection to enhance the overall resilience of the expressway network.

A large amount of dredged silt is produced in Taihu Lake every year. In order to realize the resource utilization of solid waste, the feasibility of preparing dredged mud and attapulgite into vertical cutoff wall material was explored, and its impermeability was studied. The permeability resistance and micro-pore structure of dredged mud-attapulgite engineering cutoff wall materials were studied by flexible wall infiltration, water centrifugation and low field nuclear magnetic resonance test. The results show that with the increase of consolidation pressure, the proportion of small holes increases, the proportion of mesoporous holes decreases, the content of free water decreases, and the content of bound water is basically unchanged, and the porosity and hydraulic conductivity of dredged silt-attapulgite decrease gradually with the increase of consolidation pressure. At the consolidation pressure of 100 kPa, the porosity and hydraulic conductivity of the dredging silt-attapulgite cutoff wall material using zinc chloride and butyric acid as the contaminated permeate increase compared with the test using water as the permeate. The reason is that the addition of the polluted permeate reduces the small hole proportion, increases the mesoporous proportion, increases the free water content, and basically keeps the bound water content unchanged.

The identification of aviation accident risk factors through the system-theoretic process analysis(STPA) method is a qualitative analysis process that does not allow for a quantitative assessment of the extent to which each factor contributes to an accident. To address the above problem, a qualitative and quantitative analysis method combining STPA and Bayesian network (BN) was proposed. Taking the JetBlue A320 aircraft flap accident as an example, the control structure model of the flap control system was constructed by STPA method, and the potential unsafe control behaviors and related causal scenarios were analyzed comprehensively. Then, the results of STPA qualitative analysis were transformed into a Bayesian network model that could be quantitatively analyzed, so as to identify the internal interaction logic and the highly influential factors in the accident, and put forward comprehensive safety recommendations. The analysis results show that the main factor leading to the accident is the failure of hydraulic source, while the failure of power transmission unit (PTU) and the leakage of hydraulic line are the main causes of hydraulic source failure, with a critical importance of 0.688 and 0.299, respectively.

In order to study the displacement characteristics of pile and anchor supporting deep foundation pit in seasonal frozen loess area, the horizontal displacement of pile top and pile body and the surface settlement outside the pit under different working conditions were compared by indoor scale model test. The results show that water migration and redistribution occur in the freeze-thaw cycle, and the existence of external water replenishment conditions will accelerate the water migration rate, which makes the displacement of supporting structure and the surface settlement outside the pit much larger than that in the excavation stage. The maximum horizontal displacement of pile top and pile body in the freeze-thaw stage under closed conditions increase by 6~8 times compared with that in the excavation stage, and the surface settlement outside the pit increases by 3 times. Compared with the closed freeze-thaw condition, the horizontal displacement of pile top and pile body increases about 1.4 and 1.2 times, and the surface settlement outside the pit increases 1.5 times. The research results can provide reference for the risk prevention and control of pile and anchor support deep foundation pit construction in this kind of seasonal freezing loess area.

In order to solve the safety problems encountered when aircraft land and taxi on runway surfaces with accumulated water, three-dimensional random uneven half-runway surfaces with different flatness grades were established. The distribution of accumulated water in the landing strip under the influence of runway unevenness was used to investigate the accumulated water distribution characteristic matrix. Moreover, a theoretical model for aircraft landing and taxiing on runways with accumulated water was established, and dynamic simulations were carried out using the Simulink tool to analyze the impact of runways on aircraft landing performance under different accumulated water distribution conditions. The results show that compared with “good” (international roughness index, IRI=1), the landing distance of the runway with “poor” (IRI=5) increases by about 29 m, and the landing distance of the runway with “poor” (IRI=1) increases by 3.7% compared with the ideal smooth road. Moreover, the decrease of road smoothness would aggravate the risk of tire water skiing. If the ground speed of the aircraft is increased from 62 m/s to 82 m/s, the landing distance will directly increase by about 520 m, an increase of about 87%. When the rainfall intensity of 1 mm/min increases from 1 mm/min to 3 mm/min, the landing distance increases by 6.5 m and 7.4 m for each increase in rainfall intensity of 1 mm/min. It is concluded that at the uneven position of the pavement, the greater the grounding speed, the greater the speed when reaching the same position, and the greater the reduction of the adhesion coefficient of the position, up to 11.3%. With the increase of rainfall intensity, the adhesion coefficient decreases gradually. When the rainfall intensity reaches 3 mm/min, the adhesion coefficient decreases by about 20% compared with the dry pavement.

With the rapid development of railway networks in cold regions, frequent subgrade diseases are observed. To investigate the freeze-thaw characteristics and mechanical properties of subgrade soils in cold regions, a series of laboratory tests were conducted. The effects of moisture content, freezing temperature, and freeze-thaw cycles on soil behavior were systematically investigated. The experimental results indicate that the frost heave ratio and thaw settlement coefficient increase consistently with higher moisture content, lower freezing temperatures, and more freeze-thaw cycles. More pronounced moisture migration is observed under conditions of higher initial moisture content and higher freezing temperatures. The upper part of soil samples shows gradual moisture reduction while the lower part exhibits moisture accumulation with increasing freeze-thaw cycles. The freezing temperatures are measured as -1.96, -1.89, -2.17, -2.06 ℃ for initial moisture contents of 8%, 10%, 12%, and 14% respectively, with the lowest freezing temperature occurring at 12% moisture content. The strength variation ranges are determined as 3.63~6.15 MPa with increasing moisture content, 3.26~6.05 MPa with decreasing freezing temperatures, and 4.49~3.68 MPa with increasing freeze-thaw cycles. These findings are considered significant for ensuring the stability and safety of transportation infrastructure in cold regions.