The experiments of this study investigated the effect of the subgrade degree of saturation on the value of the stresses generated on the surface and the middle (vertical and lateral stresses). The objectives of this study can be identified by studying the effect of subgrade layer degree of saturation variation, load amplitude and load frequency on the transmitted stresses through the ballast layer to the subgrade layer and the stress distribution inside it and investigating the excess pore water pressure development in the clay layer in the case of a fully saturated subgrade layer and the change in matric suction in the case of an unsaturated subgrade layer.

Thirty-six laboratory experiments were conducted using approximately half-scale replicas of real railways, with an iron box measuring 1.5 x 1.0 × 1.0 m. Inside the box, a 0.5 m thick layer of clay soil representing the base layer was built. Above it is a 0.2 m thick ballast layer made of crushed stone, and on top of that is a 0.8 m long rail line supported by three 0.9 m (0.1 × 0.1 m) slipper beams. The subgrade layer has been built at the following various saturation levels: 100, 80, 70 and 60%. Experiments were conducted with various frequencies of 1, 2 and 4 Hz with load amplitudes of 15, 25 and 35 kN.

The results of the study demonstrated that as the subgrade degree of saturation decreased from 100 to 60%, the ratio of stress in the lateral direction to stress in the vertical direction generated in the middle of the subgrade layer decreased as well. On average, this ratio changed from approximately 0.75 to approximately 0.65.

The study discovered that as the test proceeded and the number of cycles increased, the value of negative water pressure (matric suction) in the case of unsaturated subgrade soils declined. The frequency of loads had no bearing on the ratio of decline in matric suction values, which was greater under a larger load amplitude than a lower one. As the test progressed (as the number of cycles increased), the matric suction dropped. For larger load amplitudes, there is a greater shift in matric suction. The change in matric suction is greater at higher saturation levels than it is at lower saturation levels. Furthermore, it is seen that the load frequency value has no bearing on how the matric suction changes. For all load frequencies and subgrade layer saturation levels, the track panel settlement rises with the load amplitude. Higher load frequency and saturation levels have a greater impact.

Temperature is an important load for a ballastless track. However, little research has been conducted on the dynamic responses when a train travels on a ballastless track under the temperature gradient. The dynamic responses under different temperature gradients of the slab are theoretically investigated in this work.

Considering the moving train, the temperature gradient of the slab, and the gravity of the slab track, a dynamic model for a high-speed train that runs along the CRTS Ⅲ slab track on subgrade is developed by a nonlinear coupled way in Abaqus.

The results are as follows: (1) The upward transmission of the periodic deformation of the slab causes periodic track irregularity. (2) Because of the geometric constraint of limiting structures, the maximum bending stresses of the slab occur near the end of the slab under positive temperature gradients, but in the middle of the slab under negative temperature gradients. (3) The periodic deformation of the slab can induce periodic changes in the interlayer stiffness and contact status, leading to a large vibration of the slab. Because of the vibration-reduction capacity of the fastener and the larger mass of the concrete base, the accelerations of both the slab and concrete base are far less than the acceleration of the rail.

This study reveals the influence mechanism of temperature gradient-induced periodic deformation in the dynamic responses of the train-track system, and it also provides a guide for the safe service of CRTS Ⅲ slab track.

The safety of high-speed rail operation environments is an important guarantee for the safe operation of high-speed rail. The operating environment of the high-speed rail is complex, and the main factors affecting the safety of high-speed rail operating environment include meteorological disasters, perimeter intrusion and external environmental hazards. The purpose of the paper is to elaborate on the current research status and team research progress on the perception of safety situation in high-speed rail operation environment and to propose directions for further research in the future.

In terms of the mechanism and spatio-temporal evolution law of the main influencing factors on the safety of high-speed rail operation environments, the research status is elaborated, and the latest research progress and achievements of the team are introduced. This paper elaborates on the research status and introduces the latest research progress and achievements of the team in terms of meteorological, perimeter and external environmental situation perception methods for high-speed rail operation.

Based on the technical route of "situational awareness evaluation warning active control," a technical system for monitoring the safety of high-speed train operation environments has been formed. Relevant theoretical and technical research and application have been carried out around the impact of meteorological disasters, perimeter intrusion and the external environment on high-speed rail safety. These works strongly support the improvement of China's railway environmental safety guarantee technology.

With the operation of CR450 high-speed trains with a speed of 400 km per hour and the application of high-speed train autonomous driving technology in the future, new and higher requirements have been put forward for the safety of high-speed rail operation environments. The following five aspects of work are urgently needed: (1) Research the single factor disaster mechanism of wind, rain, snow, lightning, etc. for high-speed railways with a speed of 400 kms per hour, and based on this, study the evolution characteristics of multiple safety factors and the correlation between the high-speed driving safety environment, revealing the coupling disaster mechanism of multiple influencing factors; (2) Research covers multi-source data fusion methods and associated features such as disaster monitoring data, meteorological information, route characteristics and terrain and landforms, studying the spatio-temporal evolution laws of meteorological disasters, perimeter intrusions and external environmental hazards; (3) In terms of meteorological disaster situation awareness, research high-precision prediction methods for meteorological information time series along high-speed rail lines and study the realization of small-scale real-time dynamic and accurate prediction of meteorological disasters along high-speed rail lines; (4) In terms of perimeter intrusion, research a multi-modal fusion perception method for typical scenarios of high-speed rail operation in all time, all weather and all coverage and combine artificial intelligence technology to achieve comprehensive and accurate perception of perimeter security risks along the high-speed rail line and (5) In terms of external environment, based on the existing general network framework for change detection, we will carry out research on change detection and algorithms in the surrounding environment of high-speed rail.

Express freight transportation is in rapid development currently. Owing to the higher speed of express freight train, the deformation of the bridge deck worsens the railway line condition under the action of wind and train moving load when the train runs over a long-span bridge. Besides, the blunt car body of vehicle has poor aerodynamic characteristics, bringing a greater challenge on the running stability in the crosswind.

In this study, the aerodynamic force coefficients of express freight vehicles on the bridge are measured by scale model wind tunnel test. The dynamic model of the train-long-span steel truss bridge coupling system is established, and the dynamic response as well as the running safety of vehicle are evaluated.

The results show that wind speed has a significant influence on running safety, which is mainly reflected in the over-limitation of wheel unloading rate. The wind speed limit decreases with train speed, and it reduces to 18.83 m/s when the train speed is 160 km/h.

This study deepens the theoretical understanding of the interaction between vehicles and bridges and proposes new methods for analyzing similar engineering problems. It also provides a new theoretical basis for the safety assessment of express freight trains.

The aim of this work is to research and design an expert diagnosis system for rail vehicle driven by data mechanism models.

The expert diagnosis system utilizes statistical and deep learning methods to model the real-time status and historical data features of rail vehicle. Based on data mechanism models, it predicts the lifespan of key components, evaluates the health status of the vehicle and achieves intelligent monitoring and diagnosis of rail vehicle.

The actual operation effect of this system shows that it has improved the intelligent level of the rail vehicle monitoring system, which helps operators to monitor the operation of vehicle online, predict potential risks and faults of vehicle and ensure the smooth and safe operation of vehicle.

This system improves the efficiency of rail vehicle operation, scheduling and maintenance through intelligent monitoring and diagnosis of rail vehicle.

This paper aims to analyze the stress and strain distribution on the track wheel web surface and study the optimal strain gauge location for force measurement system of the track wheel.

Finite element method was employed to analyze the stress and strain distribution on the track wheel web surface under varying wheel-rail forces. Locations with minimal coupling interference between vertical and lateral forces were identified as suitable for strain gauge installation.

The results show that due to the track wheel web's unique curved shape and wheel-rail force loading mechanism, both tensile and compressive states exit on the surface of the web. When vertical force is applied, Mises stress and strain are relatively high near the inner radius of 710 mm and the outer radius of 1110 mm of the web. Under lateral force, high Mises stress and strain are observed near the radius of 670 mm on the inner and outer sides of the web. As the wheel-rail force application point shifts laterally toward the outer side, the Mises stress and strain near the inner radius of 710 mm of the web gradually decrease under vertical force while gradually increasing near the outer radius of 1110 mm of the web. Under lateral force, the Mises stress and strain on the surface of the web remain relatively unchanged regardless of the wheel-rail force application point. Based on the analysis of stress and strain on the surface of the web under different wheel-rail forces, the inner radius of 870 mm is recommended as the optimal mounting location of strain gauges for measuring vertical force, while the inner radius of 1143 mm is suitable for measuring lateral force.

The research findings provide valuable insights for determining optimal strain gauge locations and designing an effective track wheel force measurement system.

To optimize train operations, dispatchers currently rely on experience for quick adjustments when delays occur. However, delay predictions often involve imprecise shifts based on known delay times. Real-time and accurate train delay predictions, facilitated by data-driven neural network models, can significantly reduce dispatcher stress and improve adjustment plans. Leveraging current train operation data, these models enable swift and precise predictions, addressing challenges posed by train delays in high-speed rail networks during unforeseen events.

This paper proposes CBLA-net, a neural network architecture for predicting late arrival times. It combines CNN, Bi-LSTM, and attention mechanisms to extract features, handle time series data, and enhance information utilization. Trained on operational data from the Beijing-Tianjin line, it predicts the late arrival time of a target train at the next station using multidimensional input data from the target and preceding trains.

This study evaluates our model's predictive performance using two data approaches: one considering full data and another focusing only on late arrivals. Results show precise and rapid predictions. Training with full data achieves a MAE of approximately 0.54 minutes and a RMSE of 0.65 minutes, surpassing the model trained solely on delay data (MAE: is about 1.02 min, RMSE: is about 1.52 min). Despite superior overall performance with full data, the model excels at predicting delays exceeding 15 minutes when trained exclusively on late arrivals. For enhanced adaptability to real-world train operations, training with full data is recommended.

This paper introduces a novel neural network model, CBLA-net, for predicting train delay times. It innovatively compares and analyzes the model's performance using both full data and delay data formats. Additionally, the evaluation of the network's predictive capabilities considers different scenarios, providing a comprehensive demonstration of the model's predictive performance.

Following the regional restructuring, the number of joint-venture railway companies in which the Group participates has significantly increased. This paper aims to explore the challenges faced by China Railway Group in managing participation in joint-venture railway companies. The study seeks to propose specific approaches to ensure the effective management of these companies, thereby maximizing the benefits of the regional restructuring and supporting the development of a strong transportation country and a modern infrastructure system.

Based on the change in the shareholding relationship between China Railway Group and the joint-venture railway companies, and considering the current situation of the regional restructuring of these companies, as well as the insights from existing literature and typical case studies, this paper proposes some specific paths for effective management of joint-stock railway companies which China Railway Group participated in.

The problems in participation management are the unclear dual leadership role of the party committee, the lack of discourse power, the lack of synergy between shareholders, the increasing risk of sustainable operation of the loss-making companies and the role of dispatched personnel is not fully played. Based on the theories, combined with the existing research and practical cases, the paper proposed specific approaches, such as perfecting top-level system design, maintaining the discourse power, carrying out differentiated management, arranging personnel rationally, arranging shareholders synergy, and innovating methods to provide references for China Railway Group's subsequent management of joint venture railway companies.

This paper contributes to the existing literature by providing a comprehensive analysis of the challenges faced by China Railway Group in managing participation in joint-venture railway companies following the regional restructuring. The study offers novel insights and practical recommendations for addressing these challenges. The findings can serve as valuable references for China Railway Group's subsequent management of joint-venture railway companies which participated in, as well as for other state-owned enterprises facing similar challenges in managing their joint ventures.