Aiming at the issue of how to realize the dynamic updating of the digital twin model of historic buildings, a “build-compare-update” updating idea was proposed. Firstly, the shape distribution method was used to draw the shape distribution curve of the digital twin model of the historical building at different time points, based on completing the construction of the digital twin model of the historical building. Secondly, the mean absolute error method was used to assess the similarity of the two models. Furthermore, according to the results of the similarity assessment, the updating strategy for the model of the components of the historic building was set up and the updating of the digital twin model was completed with the help of relevant software. Finally, to validate the design, the arch column component of the Jade Buddha Hall of Hongci Temple was used as a case study. The results show that the proposed idea of updating the historical building model and its implementation method not only lay the foundation for realizing the dynamic updating of the digital twin model of historical buildings, but also provide reference value for the intelligent protection of historical buildings.

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.

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.

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.

The conflict between coal resource extraction and ecological environmental protection is particularly pronounced in the Gaojialiang coal mine of Inner Mongolia. To accurately characterize the deformation extent and evolutionary patterns of mining-induced ground subsidence within the study area, small baseline subset interferometric synthetic aperture radar (SBAS-InSAR) technology combined with Sentinel-1 radar remote sensing data were utilized to obtain the annual average deformation velocity and time-series cumulative deformation over three primary panels. Additionally, the Kriging interpolation method was employed to predict and supplement data in decoherence regions, ensuring comprehensive coverage of the deformation field. The results show that three distinct subsidence zones are identified, spatially correlated with the mined-out areas of panels 203, 301, and 401, respectively. The subsidence is characterized by slow deformation, with a peak annual average deformation velocity of approximately -34 mm/a. The temporal initiation and spatial propagation of subsidence in the three panels align closely with the actual mining sequence and operational conditions. Among these, panel 401 exhibited the largest subsidence area, covering approximately 4.56 km², with a maximum cumulative deformation of -189 mm, followed by panels 301 and 203 in descending order. Ground fractures identified through high-resolution optical remote sensing imagery are consistent with field investigations, predominantly distributed in the zones of maximum deformation intensity. Based on the deformation characteristics and fractures distribution, three high-risk geohazard zones are delineated within the study area. The primary driver of ground subsidence is attributed to longwall mining activities, while geological structures and precipitation infiltration also contributed to the deformation process. SBAS-InSAR technology has good application effects in monitoring large-scale mining-induced ground subsidence, and can provide crucial technical and data support for geological disaster prevention and ecological environment restoration in Gaojialiang mining area.

In order to solve the problems of large heat leakage and unclear stress of the adiabatic support structure in the cryogenic storage tank, a finite element model of a 37.4 m³ storage tank was established by the method of thermal-solid interaction, and the heat transfer, stress and deformation of the tank were analyzed, and the supporting structure was optimized. The results show that the daily evaporation rate of liquid nitrogen is 0.10%/d when the heat leakage through the supporting structure is 62.18 W, and the heat leakage of the supporting structure decreases with the decrease of ambient temperature. The influence of liquid temperature on the storage tank is mainly concentrated in the support structure and the inner tank, and the stress and deformation of the support structure increase greatly after considering the influence of temperature, and the maximum stress of the inner tank is less affected, and the deformation is increased by 11.81 times. When storing liquid hydrogen, the heat transfer of the support structure increases by 26% compared with liquid nitrogen. The topology of the supporting structure under the sliding end was optimized with the minimum heat transfer as the optimization goal. The heat transfer of the “Y” type support structure is reduced by 27.20% and the maximum stress is reduced by 7.73%.

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.

To enhance the long-term displacement prediction accuracy of landslides, the GCformer model was applied to landslide displacement forecasting, and a novel landslide displacement prediction approach grounded in the GCformer model was proposed. This methodology leveraged rainfall and displacement as input variables, utilized the GConv_msk module to capture the global information of the sequence, and combined a linear scaling technique of sequence length to efficiently extract data features. Concurrently, the PatchTST model was employed to automatically extract short-term and long-term signals from the sequence data, in order to obtain more comprehensive historical information and bolster the model's robustness and modeling capability. Finally, the landslide displacement monitoring data from Jinliuping Village and Yuanshitan Village in Huichuan County, Dingxi City, Gansu Province, were utilized for case validation. The findings demonstrate that the proposed model exhibits superior prediction accuracy and reliability. In comparison to the Autoformer model and the FEDformer model, the GCformer model is found to achieve the lowest error in both total displacement and vertical displacement.

The Ordos Basin's marine carbonate reservoirs often experience downhole complexities such as gas invasion, lost circulation, and borehole collapse during drilling. It is particularly important to systematically evaluate the overpressure mechanisms and accurately predict formation pressure for the exploration and development of the target strata. The carbonate reservoir of the Ordovician Majiagou Formation in the eastern Ordos Basin was selected as the research target. Overpressure mechanisms were analyzed using the combination of well log curve analysis, effective stress-acoustic velocity method, acoustic velocity-density method, and comprehensive analysis method. A physical model of elastic modulus for carbonate rock matrix, framework, mixed pore fluid, and saturated fluid rock was established, and combined with the effective stress principle, a method for predicting formation pressure was developed, applicable to the Majiagou Formation in the eastern Ordos Basin. Finally, the model's accuracy was verified using field data. The results indicate that hydrocarbon generation is the primary cause of overpressure in the target reservoir, with undercompaction and structural compression as secondary factors. The new model achieves a relative error of less than 10%, demonstrating strong applicability and high predictive accuracy. The research results provide guidance for the study of hydrocarbon accumulation in the Majiagou Formation in the eastern Ordos Basin.