Cultural relics protection units are important carriers of Chinese outstanding traditional culture. It is of great significance to study the spatial differentiation of cultural relics protection units and the differences in the results of multi-scale driving factors, in order to continuously promote the inheritance of history and culture, and to prosper the development of regional cultural undertakings and cultural industries. Huizhou cultural relics protection units were taken as the research object, and standard deviation ellipse, kernel density estimation and geographic detector methods were used in the analysis of spatial and temporal differentiation and driving factors of cultural relics protection units. The results show that the cultural heritage units in Huizhou region present the time series characteristics of “dispersed-concentrated-dispersed”, and the center of distribution gradually shifts from the middle to the south. The spatial aggregation of cultural heritage units is remarkable, the overall performance of the “V” distribution pattern, specifically concentrated in Shexian County and Jixi County. Natural geographic factors and human geographic factors have an impact on the spatial differentiation of cultural heritage units.

The water absorption and expansion characteristics of the swelling surrounding rock can have adverse effects on the tunnel lining structure, which can easily lead to the induction of various engineering disasters, and impact the progress of the project, as well as the normal operation of the train in subsequent stages. Therefore, the mechanical characteristics and support method selection of such tunnels have always been of great concern. Taking a tunnel passing through expansive mudstone in Inner Mongolia as an example, based on field monitoring and numerical calculation methods, the deformation and failure characteristics of the tunnel lining structure in mudstone tunnel under the original lining conditions were analyzed. Subsequently, the applicability of double-layer preliminary lining in such tunnels was studied from the aspects of support deformation and mechanical properties, and corresponding lining parameter suggestions were proposed. The results indicate that the expansion of mudstone causes the deformation of the original lining structure (single-layer preliminary lining) to reach a magnitude of 309 mm. Such deformation leads to significant encroachment of the lining and necessitated forced arch replacement during the tunnel construction process. In comparison to the single-layer preliminary lining, the double-layer preliminary lining construction method has been found to significantly improve the deformation and stress state of the tunnel in expansive mudstone, achieving a deformation reduction rate that exceeds 63.88%. As the thickness of the secondary preliminary lining increases, the deformation and stress of the preliminary lining gradually decrease, achieving a maximum deformation reduction of 234.5 mm and a compressive stress reduction rate of up to 39% under various conditions. Consequently, the double-layer lining construction method can be considered for tunnels in expansive mudstone, with the thickness of the secondary preliminary lining being reasonably selected based on deformation requirements. The research findings can serve as a valuable reference for similar projects in the future.

In order to study the structural strength of platform fire fighting vehicles, and to address the impact of the structural design of its sub-frame, stabilizers, and booms on the stability and safety of the entire vehicle, ANSYS software simulation was used to study its structural strength, and experimental verification was conducted. A simplified 3D model of the sub-frame with stabilizers, and the booms were established separately, the stress distribution under various working conditions was simulated. Then, an experimental environment was set up for stress testing. The results show that when the entire boom is horizontally extended to the left or right of the fire fighting vehicle, it is more likely to experience the phenomenon of virtual legs, with the values of 22.5 mm and 17.5 mm, respectively. The maximum stress of the boom during the retraction and extension process occurs in the area of the folding arm's variable amplitude hinge point and the overlapping area of the telescopic arm. And the difference between the stress data obtained from experiments and simulations is about 4%. This not only provides good guidance for the security testing of platform fire fighting vehicles, but also verifies the credibility of the simulation method, which is helpful for the structural design and optimization of platform fire fighting vehicles.

The confined space and fluctuating brightness levels inside and outside highway tunnels result in notable disparities in driving behaviors across various sections. It's difficult to achieve differential management of various sections within tunnels due to the challenge of implementing uniform warning and control across the entire roadway. Based on the Tongji road trajectory sharing platform (TJRD TS), continuous microscopic parameters of vehicles were extracted to quantify driving characteristics using eight indicators. This approach was aimed at analyzing the differences in driving behavior and safety risks of vehicles at different tunnel locations. Based on unsupervised learning algorithms, a segmenting method was proposed for highway tunnel sections that considers driving characteristics. Firstly, principal components analysis (PCA) was employed to determine the main features representing driving behavior and traffic safety. Subsequently, the K-means clustering algorithm was utilized to divide the distribution of main features along the tunnel direction into segments. Finally, the rationality of tunnel section division was validated through significance analysis. The results show that the driving behavior and safety vary significantly at different positions within the tunnel. Based on driving characteristics, the tunnel sections are segmented into six parts using PCA-K-means clustering: approach section, entrance section, transition section, middle section, exit section, and departure section. The entrance and transition sections exhibit high variability in speed changes and unstable traffic flow, while conflict frequencies are high in the transition and exit sections, with vehicle deceleration and acceleration reaching peak values of 14.89% and 15.65%, respectively. The research results reveal the evolution pattern of vehicle driving characteristics within tunnels and facilitates effective segmentation of highway tunnels. The research results contribute to the formulation of proactive safety control strategies for tunnel vehicles and the realization of precise vehicle-road cooperative control.

Aiming at the current problem of rail transit feeder buses being affected by competition from shared motorcycles, which has led to a significant loss of passenger flow, the service quality of feeder buses was studied and evaluated in order to enhance the competitiveness of feeder buses. Firstly, a questionnaire was designed to collect passenger satisfaction data, and the object importance of each service index of the feeder bus in the passenger perspective was obtained through the random forest algorithm. The subject importance degree of each service indicator under the experts' perspective was obtained through the analytic hierarchy process(AHP), and the competitive importance degree of the service indicators under the competition with shared motorcycles was obtained. Next, the evaluator weight determination method based on the stakeholder perspective was used to weight the combination of the three importance degrees to obtain the comprehensive importance degree of the feeder bus service indicators, and the importance-performance analysis(IPA) matrix was constructed to classify the indicator improvement priority. Finally, the technique for order preference by similarity to an ideal solution (TOPSIS) was used to confirm the specific priority of the service indicators to be improved by combining the comprehensive importance degree and satisfaction degree. The results show that waiting time, transfer fare and ride congestion are the three most effective indicators for improving the service quality of rail-connected buses, and the priority weights for improvement are 0.368, 0.235, and 0.164, respectively. Among them, the waiting time shows high importance under all three perspectives, and is the most prioritized key factor for improvement. Two service indicators, transfer fare and travel time, have high importance in the expert and competitive perspectives, respectively, suggesting that perspectives other than passenger perceptions can also reveal the key role of different indicators in improving service quality. A proposed comprehensive assessment method based on the importance of service indicators in multiple perspectives and the quantification of improvement priority, which can more accurately assess the service quality of feeder buses and provide the direction of improvement.

In order to improve the prediction accuracy of pedestrian crossing patterns by conventional vehicles in unsignalized crosswalk road sections, a pedestrian crossing pattern prediction model integrating extreme gradient boosting (XGBoost) and multilayer perceptron (MLP) algorithms was proposed. First, the pedestrian-vehicle interaction data in the unsignalized crosswalk section were collected based on the cameras and LiDAR installed on the roadside, and the behavioral characteristics of pedestrians and vehicles were analyzed, and then the factors affecting the pedestrian crossing patterns were screened. Next, the predictive effects of different combinations when used as model inputs were explored. Finally, vehicle speed, vehicle-to-zebra crossing distance, time to collision(TTC) and pedestrian step speed were used as model inputs, and pedestrian crossing patterns were categorized into direct crossing and waiting crossing and used as model outputs, and the XGBoost-MLP model for pedestrian crossing pattern prediction was established. The prediction accuracy of this model for pedestrian crossing patterns reaches 88.65%, which compares with the single XGBoost model and the MLP model, and its accuracy is improved by 3.85% and 2.61% compared to the single XGBoost model and MLP model, respectively.

Due to the complexity and variability of the marine environment as well as the complexity of the dynamic characteristics of the offshore stabilized corridor bridge in a series-parallel hybrid configuration, the analysis of the dynamic characteristics of the offshore stabilized corridor bridge in the working process has always been a key point and a difficult point in the related research process. To address this problem, firstly, the projection matrix and Jacobi matrix of each component of the bridge were derived based on the vector method and Kane's method, as well as the dynamic equations under the generalized coordinate system, and the overall explicit dynamics model of the bridge was derived by using the Kane's method and the principle of virtual work. Secondly, a joint simulation model of MATLAB and Adams was constructed based on Simulink and the simulated motion of the vessel was simulated by the MSS toolbox to simulate the ship's motion as an excitation for analysis. Finally, theoretical calculations and simulation analysis were carried out under two working conditions, with and without personnel and cargo transfer, to verify the correctness of the established model. Further, the effects of loads of different masses on the driving force of the strut chain were investigated, and the compensating effect of the sea-stabilised corridor bridge was analysed. The research results are of guiding significance for the development of the sea-stabilised corridor bridge and its application on real ships.

In order to ensure the regular and punctual operation of civil aviation transportation, the efficient aviation spare parts supply is the fundamental basis. However, the stochastic replenishment lead time and demand aggregates the uncertainty of spare parts supply. An original equipment manufacturer-orientated aviation industry supply chain location-inventory problem under an uncertain environment was investigated. A two-stage stochastic optimization model, including facility location, inventory control, production decisions, etc., was constructed to maximize the supply chain's profit. A novel robust optimization approach was proposed for a resilient supply chain network design under an uncertain environment. The results show that original equipment manufacturer facilities are more likely to establish double-sourcing and multiple-sourcing strategies with the upstream tier suppliers as the supply lead time and demand uncertainty increase and the on-hand inventory and average ordering quantity of tier suppliers increase accordingly. In addition, high uncertainty in spare parts supply and demand leads to declining profits in the aviation industry supply chain, which can be relieved by robust and resilient supply chain design and efficient inventory control. It is concluded that the optimal strategic and tactical decisions of the aviation industry supply chain in the context of supply and demand uncertainty provide an effective solution for the robust and efficient operations of the global aviation industry supply chain.

The issue of gate assignment at modern airports involves coordinating multiple interests, including passenger satisfaction, efficient allocation of airport resources, and control of carbon emissions. A multi-objective nonlinear integer programming model was developed to solve this complex problem, which considering constraints such as flight type, aircraft model, and gate availability. The optimization objectives of model include minimizing passengers' walking distance, maximizing aircraft-gate matching, and minimizing carbon emissions. An improved adaptive genetic algorithm was proposed to solve the gate assignment problem. In the population initialization phase, a combination of random and greedy-perturbation strategies was employed to generate a more diverse initial population. The probabilities of crossover and mutation were adaptively adjusted during the algorithm's iterations. Both crossover-first and mutation-first evolutionary strategies were applied to enhance solution efficiency and global search ability. To validate the effectiveness of the algorithm, some simulation experiments were conducted using operational data from the domestic airport. The improved adaptive genetic algorithm was compared with traditional genetic algorithms and particle swarm optimization algorithms. Results show that the improved algorithm significantly outperforms the others in terms of gate utilization efficiency, passenger satisfaction, and carbon emission control. Furthermore, the effectiveness of the proposed improvement strategies was confirmed through experimental analysis, demonstrating the stability and performance of the algorithm. The proposed model and algorithm provide robust decision support for gate management, contributing to enhanced passenger satisfaction, efficient resource utilization, and sustainable environmental development.

The disruption recovery is regarded as a crucial role in the operation of freighter airlines. To expand the application scenarios of the freight flight network, elements such as mandatory nodes and external arcs were introduced to enhance the applicability of the network. In general, aircraft and cargo were defined in separate networks and are recovered using a sequential solving method. To explore the correlation between each research object and to complete each recovery action, the entity flow was defined to integrate different types of entities in the same network. To solve the problem of crew recovery, constraints such as crew duty and flight qualifications were added to the model, and a mixed integer linear programming model was constructed based on an improved flight network. This model can achieve integrated recovery of aircraft, cargo, and crew. To accurately evaluate the capacity constraints of the cargo aircraft, a unit load device was used to represent the volume of cargo and to improve the relevant models of capacity constraints. An entity aggregation approach was employed to reduce the number of entities to control the model complexity. The model evaluation was performed using operational data provided by a small freighter airline. The results show that the recovery solution causes a 42% reduction in the delay time. In the subsequent simulation experiments, six different disruption scenarios were established for two freighter airlines with multiple fleets. As the disruption rate increases, medium freighter airlines adopt the strategy of re-routing aircraft and rescheduling crew, while large freighter airlines focus on flight delays. The proposed integrated air cargo schedule recovery model based on an improved flight network can solve all the cases exactly in limited time, and the average error is 0.47%.