The mechanical behaviors of Ushaped girders in urban rail transit differ in the spanning and transverse directions, and a dynamic coefficient of 1.40 in the current design code will result in material waste. Considering the bidirectional stressing characteristics, the Ushaped girder of the Nanjing Subway Line S6 Urban Rail Transit was selected as a case study, and a trainbridge coupling dynamic model was established. The effectiveness of the model was verified by comparing the test and calculated results. The dynamic coefficients of the different responses were analyzed by changing the train speed and formation. The results indicate that the girder bottom only bears longitudinal tensile stress but carries both transverse tensile and compressive stresses in the same section. The maximum dynamic coefficients of the deflection, longitudinal stress, and lateral stress were 1.231, 1.216, and 1.362, respectively, in the fulland fixedload cases of the 6car formation. When determining the dynamic coefficients of a singletrack Ushaped girder, the influence of the train formation should be considered, and the values should be distinguished according to the stressing directions. We recommend a value of 1.30 when calculating the deflection and longitudinal stress and 1.40 when calculating the lateral stress. This paper proposes reasonable values for the dynamic coefficients of Ushaped girders and provides a reference for structural optimization.

Traditional steel struts cannot be tensioned, and the construction of concrete struts is complex and generates considerable construction waste during the demolition phase. Therefore, prestressed steel struts capable against tensile and compressive stresses have been invented. The performance evaluation results of mechanics, construction adaptability, and cost with a prestressed steel strut capable against tensile and compressive stresses show that its compression bearing capacity is the same as that of a traditional steel strut and equivalent to that of a concrete strut. Furthermore, its tensile and strut stiffness performances are equivalent to those of a concrete strut and superior to those of a traditional steel strut. Its construction convenience is equivalent to that of a traditional steel strut and 20%30% lower than that of a concrete strut. The first concrete strut replaced by a prestressed steel strut capable against tensile and compressive stresses for metro excavations can not only ensure technical performance but also result in better economic and social benefits.

The complexity of deepexcavation construction arises from the influence of various potential risk factors on the construction procedure. To address this issue, this study introduces an intuitionistic fuzzy TOPSIS method aimed at identifying potential highrisk factors. Initially, potential risk factors were determined through an analysis of the failure modes derived from prior excavation accidents, insights from practical engineering projects, and the expertise of engineering professionals. Subsequently, a risk evaluation hierarchy was established, and weights were assigned to experts and criteria using intuitionistic fuzzy numbers. A practical project involving a deep excavation was conducted to validate the feasibility of the proposed method. The results indicate that the TOPSIS method effectively identified highrisk factors. The developed method serves as a valuable decisionmaking tool for the safety risk analysis and control of excavation construction in similar engineering projects.

Given that the departure capacity of depots has gradually hindered the improvement of the operation level of the main line during morning peak hours, some cities have begun to explore the construction of ATC depots. However, existing calculation methods for vehicle sending and receiving capacity cannot be applied to ATC depots. The throat area capacity calculation method of ATC depots is investigated to compensate for the above shortcomings. First, under the ATC lightsoff mode, the minimum total train departure time is obtained by comparing the total train departure times under different train departure sequences. Second, the maximum throat area passing capacity of the ATC depot is calculated. Finally, using the Guangzhou Luogang depot as a case study, a validation study of the effectiveness of the calculation model of the throat area passing capacity under the ATC lightsoff mode is carried out. The results show that the passing capacities of the throat area under the ATC lightsoff, ATC lighting, train adjustment combination, and train approach modes are 28, 17, 13, and 11 trains/h, respectively; the ATC lightsoff mode has a greater capacity than the other three modes and can better meet the operational demand of the mainline during morning peak hours. The results of this study can serve as a reference for evaluating depot design schemes.

Considering the drawbacks of inconsistent building information modeling (BIM) methods and nonstandard information in rail transit engineering, it is difficult to effectively and uniformly use BIM model data. Therefore, the Industry Foundation Classes (IFC)based BIM component standard library for rail transit engineering was studied. First, the component types, IFC expression of component information, and IFCbased extensibility mechanisms were studied according to the expression requirements of rail transit engineering components. Second, the technology framework of the BIM component standard library for rail transit engineering was proposed, including basic, technical, application, and user layers. Third, the classification and code method in the national standard was used to define the classification and code of these BIM components, and a component information template was proposed to define the component properties and their resource links. Finally, encryption and decryption methods for the BIM component model were applied to ensure the security of the BIM model data. The results showed that the proposed unified BIM component library enabled project participants to use standardized BIM component models to create a project model for rail transit engineering, ensuring the standardization of BIM models.

This study uses multisource big data (e.g., metro card transactions, mobile phone signaling, and points of interest (POIs)) and interpretable machine learning methods (integrating random forest and Shapley additive explanations (SHAP) models) to investigate the nonlinear relationship between stationarea built environments and Chengdu Metro ridership as well as the synergistic effects among built environment variables. The results indicate that the three most important built environment determinants of metro ridership are the floor area ratio, employment density, and road density. Moreover, the SHAP model results reveal the threshold and synergistic effects of the stationarea built environment variables on metro ridership. These findings provide theoretical support and policy insights for transitoriented developmental (TOD) planning and practice.

Aiming at the optimization problem of lasttrain connection planning in urban rail transit networks, which often brings difficulties in successful transfers, this study selects the arrival times of the last trains as decision variables and constructs a mixedinteger linear programming model to minimize the number of failed passenger transfers. To address the high model complexity caused by the expansion of the network scale, a quantum computing method is adopted to solve the proposed model. First, the original model is reconstructed into a twostage problem with a smaller computation scale. Then, the firststage optimization model is transformed into a quadratic unconstrained binary optimization (QUBO) model that can run on a quantum computer. Algorithm development and experimental testing are conducted based on the optical quantum computing technology of the coherent Ising machine. To verify the effectiveness of the proposed method, we consider the Beijing subway network as an example. The quantum computing results are compared with those from commercial solvers, confirming the feasibility of both the model transformation method and the quantum computing approach proposed in this study. These findings provide technical support for the further application of quantum computing in solving complex optimization problems in rail transit.

Studying the distribution characteristics and mechanisms of urban rail transit accidents is important for ensuring operational safety and formulating safety control measures. This study statistically analyzes 425 local and international urban rail transit operation accidents from 1970 to 2022 and compares and analyzes the causes and time distribution characteristics of operation accidents. Based on the cause mechanism and principal component analysis method, a safety evaluation system for urban rail transit operations was constructed, and a combined weight evaluation method based on game theory was proposed. Taking the data of 274 operational accidents in China from 1990 to 2022 as an example, combined with expert scoring, the safety status of urban rail transit operations in China was analyzed from a macro perspective. The results indicated that the factors causing operational accidents included personnel, equipment, and environmental factors. Among them, domestic and foreign operational accidents caused by equipment accounted for the highest proportion of accidents, accounting for 56% and 65% respectively. January, March, July, August, and December were the months with frequent accidents, which were the same as the peak months of passenger flow. The combination weighting method not only considers the amount of information in objective statistical data but also combines the experience accumulation of subjective experts, which makes the evaluation results closer to the actual operation situation and proves the feasibility of the evaluation method.

In the rapid development phase of urban rail transit, issues such as inadequate emergency response and insufficient emergency handling in unexpected events are addressed. This study presents the design of a digital intelligencebased subway safety and emergency assurance system. The design architecture, application scenarios, functionalities, and key technologies of the system are elaborated. This system integrates diverse sources of data, including hydrological, meteorological, and sensor data, and utilizes emerging technologies, such as digital twins, GIS, and BIM. This system manages the entire emergency process of subway operations, including daily safety monitoring, emergency resource management, emergency plan administration, commands, and dispatch. Moreover, it focuses on enhancing capabilities for dealing with three major emergency scenarios: fires, flood prevention, and high passenger flow. This comprehensive development significantly enhances accident prevention, emergency response, and handling efficiency while elevating the levels of digitization and intelligence in the existing emergency management system.

To address the problems of “insufficient maintenance” and “excessive maintenance" in existing maintenance modes, a health status grading evaluation method for subway power supply equipment that considers the importance of indicators is proposed. First, the equipment health value was solved according to a combination of an analytic hierarchy process and fuzzy statistics. The importance of the index was considered, and the health status of the equipment was graded. Finally, a drytype transformer was considered for analysis. The results show that the obtained results can reasonably characterize the health status of the subway power supply equipment, which is consistent with the actual situation, and verify the accuracy and feasibility of the method.