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.

In an increasingly interconnected world, transportation infrastructure has emerged as a critical determinant of economic growth and global competitiveness. High-speed rail (HSR), characterized by its exceptional speed and efficiency, has garnered widespread attention as a transformative mode of transportation that transcends borders and fosters economic development. The Kuala Lumpur - Singapore (KL-SG) HSR project stands as a prominent exemplar of this paradigm, symbolizing the potential of HSR to serve as a catalyst for national economic advancement.

This paper is prepared to provide an insight into the benefits and advantages of HSR based on proven case studies and references from global HSRs, including China, Spain, France and Japan.

The findings that have been obtained focus on enhanced connectivity and accessibility, attracting foreign direct investment, revitalizing regional economies, urban development and city regeneration, boosting tourism and cultural exchange, human capital development, regional integration and environmental and sustainability benefits.

The KL-SG HSR, linking Kuala Lumpur and Singapore, epitomizes the potential for HSR to be a transformative agent in the realm of economic development. This project encapsulates the aspirations of two dynamic Southeast Asian economies, united in their pursuit of sustainable growth, enhanced connectivity and global competitiveness. By scrutinizing the KL-SG High-Speed Rail through the lens of economic benchmarking, a deeper understanding emerges of how such projects can drive progress in areas such as cross-border trade, tourism, urban development and technological innovation.

The spatiotemporal compression effect of China-Europe Railway Express (CR-Express) can reduce the flow costs of resources between China's node cities. Additionally, it can break through the limitations of low-added-value marine products, significantly impacting the logistics industry efficiency. However, there are few literature verifying and analyzing its heterogeneity. This study explores the impact of CR-Express on the efficiency of logistics industry in node cities and analyzes the heterogeneity.

First, this study uses panel data to measure the efficiency of node city logistics industry. Secondly, this study discusses the impact of the opening of CR-Express on the efficiency of logistics industry in node cities based on the multi-period differential model. Finally, according to the node city difference, the sample city experimental group is grouped for heterogeneity analysis.

The results show that CR-Express can promote the urban logistics industry efficiency, with an average effect of 4.55%. According to the urban characteristics classification, the heterogeneity analysis shows that the efficiency improvement effect of logistics industry in inland cities is more obvious. The improvement effect of node cities and central cities in central and western China is stronger, especially in the sample of megacities and type I big cities. Compared with non-value chain industrial products, the CR-Express has significant promotion effects on the logistics efficiency of the cities where main goods are value chain products.

Under the background of double cycle development, this paper can provide a scientific basis for the investment benefit evaluation of CR-Express construction and the follow-up route planning.

The China-Europe Railway Express (CR Express) in Chongqing has operated regularly and undergone large-scale development. Its impact on Chongqing's economic growth has become increasingly evident, necessitating further research in this field.

This study employs the opening of CR Express as a quasi-natural experiment, designating Chongqing, which inaugurated the CR Express in 2011, as the treatment group. 13 provinces and cities that had not yet opened the CR Express until 2017 were selected as the control group. Utilizing panel data from 14 provinces across China spanning from 2006 to 2017, the synthetic control method (SCM) is employed to synthetically construct Chongqing. To quantify the difference in economic development levels between Chongqing with the operation of the CR express and Chongqing without its operation. Key metrics such as gross domestic product (GDP), per capita GDP, total retail sales of consumer goods, import and export value and the proportions of the secondary and tertiary industries are employed to measure urban economic development capabilities. Chongqing is designated as the experimental group, and a double-difference model is constructed to regress the operation of the CR Express against economic development capabilities. Robustness tests are conducted to validate the analytical results.

The results indicate that, compared to provinces without the operation of the CR Express, the initiation of the CR Express in Chongqing significantly enhances the economic development level of the city. The opening of the CR Express exhibits a pronounced positive impact on Chongqing's economic development, and these findings remain robust and effective even after parallel trend tests and placebo tests.

The study represents an expansion of the theoretical framework. In contrast to previous studies that relied on a single indicator such as GDP, this study selects six indicators from the dimensions of economy, trade and industry to measure regional economic development capabilities. Furthermore, employing the grey relational analysis method, the study screens these indicators, thereby providing a theoretical basis for the selection of indicators for measuring regional economic development capabilities.

The main objective of the present research is to investigate the benefits of using geogrid reinforcement in minimizing the rate of deterioration of ballasted rail track geometry resting on soft clay and to explore the effect of load amplitude, load frequency, presence of geogrid layer in ballast layer and ballast layer thickness on the behavior of track system. These variables are studied both experimentally and numerically. This paper examines the effect of geogrid reinforced ballast laying on a layer of clayey soil as a subgrade layer, where a half full scale railway tests are conducted as well as a theoretical analysis is performed.

The experimental tests work consists of laboratory model tests to investigate the reduction in the compressibility and stress distribution induced in soft clay under a ballast railway reinforced by geogrid reinforcement subjected to dynamic load. Experimental model based on an approximate half scale for general rail track engineering practice is adopted in this study which is used in Iraqi railways. The investigated parameters are load amplitude, load frequency and presence of geogrid reinforcement layer. A half full-scale railway was constructed for carrying out the tests, which consists of two rails 800 mm in length with three wooden sleepers (900 mm × 90 mm × 90 mm). The ballast was overlying 500 mm thick clay layer. The tests were carried out with and without geogrid reinforcement, the tests were carried out in a well tied steel box of 1.5 m length × 1mwidth × 1 m height. A series of laboratory tests were conducted to investigate the response of the ballast and the clay layers where the ballast was reinforced by a geogrid. Settlement in ballast and clay, was measured in reinforced and unreinforced ballast cases. In addition to the laboratory tests, the application of numerical analysis was made by using the finite element program PLAXIS 3D 2013.

It was concluded that the settlement increased with increasing the simulated train load amplitude, there is a sharp increase in settlement up to the cycle 500 and after that, there is a gradual increase to level out between, 2,500 and 4,500 cycles depending on the load frequency. There is a little increase in the induced settlement when the load amplitude increased from 0.5 to 1 ton, but it is higher when the load amplitude increased to 2 ton, the increase in settlement depends on the geogrid existence and the other studied parameters. Both experimental and numerical results showed the same behavior. The effect of load frequency on the settlement ratio is almost constant after 500 cycles. In general, for reinforced cases, the effect of load frequency on the settlement ratio is very small ranging between 0.5 and 2% compared with the unreinforced case.

Increasing the ballast layer thickness from 20 cm to 30 cm leads to decrease the settlement by about 50%. This ascertains the efficiency of ballast in spreading the waves induced by the track.

The purpose of this paper is to eliminate the fluctuations in train arrival and departure times caused by skewed distributions in interval operation times. These fluctuations arise from random origin and process factors during interval operations and can accumulate over multiple intervals. The aim is to enhance the robustness of high-speed rail station arrival and departure track utilization schemes.

To achieve this objective, the paper simulates actual train operations, incorporating the fluctuations in interval operation times into the utilization of arrival and departure tracks at the station. The Monte Carlo simulation method is adopted to solve this problem. This approach transforms a nonlinear model, which includes constraints from probability distribution functions and is difficult to solve directly, into a linear programming model that is easier to handle. The method then linearly weights two objectives to optimize the solution.

Through the application of Monte Carlo simulation, the study successfully converts the complex nonlinear model with probability distribution function constraints into a manageable linear programming model. By continuously adjusting the weighting coefficients of the linear objectives, the method is able to optimize the Pareto solution. Notably, this approach does not require extensive scene data to obtain a satisfactory Pareto solution set.

The paper contributes to the field by introducing a novel method for optimizing high-speed rail station arrival and departure track utilization in the presence of fluctuations in interval operation times. The use of Monte Carlo simulation to transform the problem into a tractable linear programming model represents a significant advancement. Furthermore, the method's ability to produce satisfactory Pareto solutions without relying on extensive data sets adds to its practical value and applicability in real-world scenarios.

The design goal for the tracking interval of high-speed railway trains in China is 3 min, but it is difficult to achieve, and it is widely believed that it is mainly limited by the tracking interval of train arrivals. If the train arrival tracking interval can be compressed, it will be beneficial for China's high-speed railway to achieve a 3-min train tracking interval. The goal of this article is to study how to compress the train arrival tracking interval.

By simulating the process of dense train groups arriving at the station and stopping, the headway between train arrivals at the station was calculated, and the pattern of train arrival headway was obtained, changing the traditional understanding that the train arrival headway is considered the main factor limiting the headway of trains.

When the running speed of trains is high, the headway between trains is short, the length of the station approach throat area is considerable and frequent train arrivals at the station, the arrival headway for the first group or several groups of trains will exceed the headway, but the subsequent sets of trains will have a headway equal to the arrival headway. This convergence characteristic is obtained by appropriately increasing the running time.

According to this pattern, there is no need to overly emphasize the impact of train arrival headway on the headway. This plays an important role in compressing train headway and improving high-speed railway capacity.