In order to study the stability of the tunnel structure under the airport runway when the aircraft is running, the numerical calculation model of the runway, soil layer and tunnel structure co-deformation was constructed by establishing the six-degree-of-freedom dynamic equation of the “five-point contact” aircraft. The influence of the aircraft type, pavement type and buried depth on the stability of the tunnel structure was analyzed. The results show that the more concentrated the distribution position of the main landing gear wheel is, the greater the influence on the stability of the tunnel structure under different aircraft loads. The attenuation effect of stress diffusion on the flexible tunnel surface is obviously better than that on the rigid tunnel surface, and the deformation degree of the arch top is more significant than other locations. With the increase of the buried depth of the tunnel structure, the disturbance effect of aircraft load on the tunnel structure shows a decreasing trend. When the buried depth of the tunnel structure exceeds${64}\mathrm{\;m}$, the tunnel structure no longer bears the disturbance effect of aircraft load.

In order to address the issue of coordinate base inconsistency in the fusion display of road building information modeling (BIM) models and tilted reality models within existing large-scale 3D geographic information system (GIS) platforms, a high-precision matching method for geographic coordinates between road BIM models and tilted reality models was proposed. Taking into account the distribution characteristics of road bands and the requirements for road maintenance, the model was initially segmented. Subsequently, a spatial distance-weighted least-squares coordinate matching parameter fitting method was developed based on the distribution of characteristic points on the road pavement and asset facility model, with a focus on accurately joining edges of the road pavement in each segment. Real road data was selected for conducting experiments to validate this coordinate matching method. The method effectively resolves bias issues in matching between the road model and tilted reality model, achieving accuracy at millimeter level post-matching, thereby meeting digital maintenance needs as well as dynamic updating requirements for road traffic facilities.

low-temperature fracture is the normal distress of the thin-layer overlay asphalt mixture. To reveal the low-temperature cracking behavior, semicircular bending tests combined with crack observation, digital image correlation and a finite element numerical simulation based on the meso-structure cohesive zone model were carried out. The applicability of the model was verified by the load-displacement curve and crack paths. The results show that the low-temperature cracking behavior of asphalt mixture can be well demonstrated by digital image processing. The simulation of asphalt mixture meso-structure is suitable for analyzing the cracking behavior. Furthermore, the maximum tensile stress and neutral axis positions on the mid-span section are correlated with the properties of the materials.

Seismic soil liquefaction can lead to soil instability and slip, resulting in irreversible and severe damage to bridges. The seismic response of curved bridges in liquefied lateral extension sites is a major concern due to the complex stress state. Three representative far-field seismic waves were selected and applied to a four-span continuous curved bridge from 12 different directions. The maximum tilt angle of the site was set to be the same as the seismic input angle in order to investigate the seismic response behavior of the curved bridge in the liquefaction expansion site and conduct a comparative analysis. The results show that as the far site seismic input gradually changes from${0}^{\circ }$to${180}^{\circ }$, the pile top bending moment of the curved bridge decreases gradually, with the side piers experiencing larger bending moments compared to the secondary center piers and the center piers. When the seismic input wave changes gradually from${180}^{\circ }$to${360}^{\circ }$, the pile top bending moment gradually increases, with the middle pier and the second pier experiencing higher bending moments than the side piers. The maximum bending moment at the bottom of the pier alternates between the middle pier and the second pier as the seismic input angle changes, with the second pier experiencing a significantly higher number of occurrences of the largest bending moment compared to the middle pier. The relative displacement between the pier and beam and the ground shaking input angle exhibits a cyclic trend of initially increasing and then decreasing. Therefore, it is recommended that the location of a bridge project susceptible to ground vibration should be determined based on the type of ground vibration, and corresponding anti-liquefaction measures should be implemented accordingly.

Considering the technical issues related to the construction of extremely small radius and ultra large diameter shield tunnels in stratified strata, taking the shield tunnel project of the Pazhou Station to Beigang Park Station section of the Pearl River Delta intercity rail transit in Guangzhou as the research object, key construction technologies of shield excavation were elaborated in detail. Solutions to outward deviation of the excavation axis because of the small curve radius and strata disturbance caused by the excavation were provided. Built upon the analysis of on-site real-time monitoring data, variation patterns of vertical and horizontal displacements, pore water pressure and soil pressure during the construction of the small radius shield tunnel were revealed. Monitoring data shows that the shield excavation of the turning section in rock layers has little impact on surface settlements. The influence of shield tunneling on the surrounding soil decreases with the increasing distance, the maximum horizontal displacements occur in the area above the tunnel. There is a high similarity in the changing trend of pore pressure and soil pressure and the impact on the soil outside the turning is greater when the shield turns.

Charging infrastructure is essential for promoting the development of electric vehicles, and identifying charging behaviors of electric vehicles is the precondition of optimizing the layout of charging infrastructure. Using the charging data of the Kechuang Base Charging Station in Beijing in 2017, charging behaviors of electric vehicles were explored by descriptive analysis and statistical analysis. Based on the charging power, charging piles were divided into three categories: high(100kW), medium(40kW), and low (${10}\mathrm{\;{kW}}$and${15}\mathrm{\;{kW}}$). Firstly, a descriptive analysis was conducted. It is found that as the charging power decreases, the charging time significantly increases, but usually does not exceed 180 min. 86.5% of customers are company users, mainly consisted of taxi/ ride hailing drivers; electric vehicles are often charged when their state of charge (SOC) are still high. Then, an ordered Logistic model was built to identify the key factors influencing the charging pile choice. Company users, daytime, weekday, charging peak period, and the low starting SOC are found to be able to significantly lead users to adopt the high-power charging piles. The research findings could be used to help optimizing the charging station layout.

In the context of achieving carbon peak and carbon neutrality in transportation, high-precision, fine-grained, and highly feasible real-time prediction methods for motor vehicle energy consumption have become key components in reducing carbon emissions. Addressing the issue of limited universality in traditional regression-based vehicle energy consumption models, a prediction model based on the radial basis function neural network (RBFNN) has been developed. Firstly, the influencing factors of vehicle energy consumption were analyzed, and the influence factor matrix was normalized using the Min-Max standardization method. Then, the grey wolf optimization (GWO) algorithm was employed to optimize the training of the centers of the hidden layer, the width of the Gaussian function, and the weights connecting the hidden layer to the output layer in the RBFNN algorithm. Finally, a comprehensive analysis of the model's prediction accuracy was conducted through horizontal model comparisons and real-world vehicle measurements. The test results demonstrate that the RBFNN algorithm improves prediction accuracy by approximately 12% compared to traditional regression models, achieving an overall accuracy of over 90%. This makes it highly effective in accurately predicting the energy consumption of urban motor vehicles.

To solve the problems of multiple influencing factors, different focuses of participating parties, and inability to quantitatively describe the comparison and selection schemes in the current process of selecting routes for mountainous expressways, based on thorough research on the influencing factors of expressway and railway route selection at home and abroad, the influencing factors of expressway route selection in mountainous areas of China were systematically analyzed and summarized, and four aspects : economy, technology, safety and environment were summarized, totaling 16 specific influencing factors. Based on the Xihe to Tanchang Expressway project, a group of 164 experts from the local government, industry regulatory departments, owners, design, construction, supervision, third-party testing units, and research institutes in the project area were organized to form an expert group. The analytic hierarchy process (AHP) was used to evaluate the importance of 16 route selection influencing factors. The results show that the comprehensive weight average score of the three influencing factors in the environmental indicators is high, reflecting the further strengthening of environmental awareness in the field of engineering construction. To further establish a optimization model for scheme comparison, taking the scheme comparison of the route from the project Dengta Village to Haolin Village as an example, the technique for order preference by similarity to idea solution (TOPSIS) method based on the AHP was used to compare and select schemes. The superiority of the four comparison schemes is 2.84, 0.56, 0.72, and 2. 15, respectively, indicating that scheme 1 is optimal. Based on a comprehensive analysis of the factors affecting the selection of mountainous expressway routes, the research results adopt the AHP-TOPSIS comprehensive evaluation index system model. While fully utilizing expert experience, it can objectively and scientifically

In order to select advanced technologies applicable to civil aircraft, technical characteristics from various fields were integrated to develop an evaluation framework. Five key evaluation dimensions were identified: technology competitiveness, technology readiness assessment, economic impact, engineering methods, and technology standards. From practical case studies, these dimensions were derived and used as the basis for an evaluation index system. A technology application perspective was adopted, utilizing a cloud model and a reverse cloud generator to determine indicator weights. This approach incorporated technical standards from different industries, airworthiness standards, and the entire life cycle of civil aircraft to create comprehensive evaluation guidelines. The results show that this approach effectively compares advanced technologies across different industries, differentiates similar technologies at various levels, and eliminates those that offer no benefit or are unsuitable for civil aircraft. This evaluation approach successfully selects advanced technologies with a high degree of compatibility with civil aircraft.

To explore the process and evolution of large-scale flight delay propagation, and avoid previous research mainly focusing on observing real data and the distribution of delay propagation networks. Drawing inspiration from the classic susceptible-explored-infected-recovered(SEIR) model and taking into account the impact of node closure on large-scale flight delays. Based on this, the state of airport nodes was added to five categories, and a large-scale flight delay propagation model based on susceptible-explored-infected-death-recovered (SEIDR) was constructed and applied to air traffic networks. Using a combination of phase trajectory analysis and related parameter analysis, the propagation threshold and propagation law of large-scale flight delays were obtained, and the influence of propagation parameters between airport nodes on the propagation law of large-scale flight delays was further analyzed. Finally, a large-scale flight delay in 2022 was taken as an example for analysis and verification. The results show that the established model can more accurately describe the evolution process and propagation law of large-scale flight delays.