The development of numerical models able to compute the wheel and rail profile wear is essential to improve the scheduling of maintenance operations required to restore the original profile shapes. This work surveys the main numerical models in the literature for the evaluation of the uniform wear of wheel and rail profiles. The standard structure of these tools includes a multibody simulation of the wheel–track coupled dynamics and a wear module implementing an experimental wear law. Therefore, the models are classified according to the strategy adopted for the worn profile update, ranging from models performing a single computation to models based on an online communication between the dynamic and wear modules. Nevertheless, the most common strategy nowadays relies on an iteration of dynamic simulations in which the profiles are left unchanged, with co-simulation techniques often adopted to increase the computational performances. Work is still needed to improve the accuracy of the current models. New experimental campaigns should be carried out to obtain refined wear coefficients and models, while strategies for the evaluation of both longitudinal and transversal wear, also considering the effects of tread braking, should be implemented to obtain accurate damage models.

As the unique power entrance, the pantograph–catenary electrical contact system maintains the efficiency and reliability of power transmission for the high-speed train. Along with the fast development of high-speed railways all over the world, some commercialized lines are built for covering the remote places under harsh environment, especially in China; these environmental elements including wind, sand, rain, thunder, ice and snow need to be considered during the design of the pantograph–catenary system. The pantograph–catenary system includes the pantograph, the contact wire and the interface—pantograph slide. As the key component, this pantograph slide plays a critical role in reliable power transmission under dynamic condition. The fundamental material characteristics of the pantograph slide and contact wire such as electrical conductivity, impact resistance, wear resistance, etc., directly determine the sliding electrical contact performance of the pantograph–catenary system; meanwhile, different detection methods of the pantograph–catenary system are crucial for the reliability of service and maintenance. In addition, the challenges brought from extreme operational conditions are discussed, taking the Sichuan–Tibet Railway currently under construction as a special example with the high-altitude climate. The outlook for developing the ultra-high-speed train equipped with the novel pantograph–catenary system which can address the harsher operational environment is also involved. This paper has provided a comprehensive review of the high-speed railway pantograph–catenary systems, including its progress, challenges, outlooks in the history and future.

An efficient computational approach based on substructure methodology is proposed to analyze the viaduct–pile foundation–soil dynamic interaction under train loads. The train–viaduct subsystem is solved using the dynamic stiffness integration method, and its accuracy is verified by the existing analytical solution for a moving vehicle on a simply supported beam. For the pile foundation–soil subsystem, the geometric and material properties of piles and soils are assumed to be invariable along the azimuth direction. By introducing the equivalent stiffness of grouped piles, the governing equations of pile foundation–soil interaction are simplified based on Fourier decomposition method, so the three-dimensional problem is decomposed into several two-dimensional axisymmetric finite element models. The pile foundation–soil interaction model is verified by field measurements due to shaker loading at pile foundation top. In addition, these two substructures are coupled with the displacement compatibility condition at interface of pier bottom and pile foundation top. Finally, the proposed train–viaduct–pile foundation–soil interaction model was validated by field tests. The results show that the proposed model can predict vibrations of pile foundation and soil accurately, thereby providing a basis for the prediction of pile–soil foundation settlement. The frequency spectra of the vibration in Beijing–Tianjin high-speed railway demonstrated that the main frequencies of the pier top and ground surface are below 100 and 30 Hz, respectively.

This paper develops a dual-indicator discrete method (DDM) for evaluating the system reliability performance of long soil subgrade slopes. First, they are segmented into many slope sections using the random finite element method, to ensure each section statistically contains one potential local instability. Then, the $k$-out-of-$n$ system model is used to describe the relationship between the total number of sections $n$, the acceptable number of failure sections $m$, the reliability of sections $R_{{{\text{sec}}}}$, and the system reliability $R_{{{\text{sys}}}}$. Finally, $m$ and $R_{{{\text{sys}}}}$ are jointly used to assess the system reliability performance. For cases lacking spatial data of soil properties, a simplified DDM is provided in which long subgrade slopes are segmented by the empirical value of section length and $R_{{{\text{sec}}}}$ is substituted by that of cross-sections taken from them. The results show that (1) DDM can provide the probability that the actual number of local instabilities does not exceed a desired threshold. (2) $R_{{{\text{sys}}}}$ decreases with increasing $n$ or decreasing $R_{{{\text{sec}}}}$; that is, it is likely to encounter more local instabilities for longer or weaker subgrade slopes. $n$ is negatively related to the horizontal scale of fluctuation of soil properties and positively related to the total length of subgrade slopes $L$. (3) When $L$ is sufficiently large, there is a considerable opportunity to meet local instabilities even if $R_{{{\text{sec}}}}$ is large enough.

With the rapid development of high-speed railways around the globe, the safety of vehicles running on bridges during earthquakes has been paid more attention to. In the design of railway bridges, in addition to ensuring the safety of the bridge structure in earthquake, the vehicle safety should also be ensured. Previous studies have focused on the detailed analysis of vehicle derailment on bridges, proposing complex numerical algorithms for wheel–rail contact analysis as well as for parametric analysis, but they are inconvenient for designers. Intensity measure (IM) used in performance-based earthquake engineering is introduced in this study. A method to evaluate the vehicle safety on bridges under earthquakes is proposed with respect to the optimal IM. Then, the vehicle derailment case of the Kumamoto earthquake in Japan verifies the decoupling method of vehicle–bridge interaction model. In the assessment of vehicle derailments, eight IMs are systematically compared: the IMs of bridge deck motion are generally better than those of ground motion; the variation coefficient of spectral intensity of the bridge deck is the smallest at different frequencies. Finally, the derailment fragility cloud map is presented to evaluate the vehicle safety on bridges during earthquakes.

Using stochastic dynamic simulation for railway vehicle collision still faces many challenges, such as high modelling complexity and time-consuming. To address the challenges, we introduce a novel data-driven stochastic process modelling (DSPM) approach into dynamic simulation of the railway vehicle collision. This DSPM approach consists of two steps: (i) process description, four kinds of kernels are used to describe the uncertainty inherent in collision processes; (ii) solving, stochastic variational inferences and mini-batch algorithms can then be used to accelerate computations of stochastic processes. By applying DSPM, Gaussian process regression (GPR) and finite element (FE) methods to two collision scenarios (i.e. lead car colliding with a rigid wall, and the lead car colliding with another lead car), we are able to achieve a comprehensive analysis. The comparison between the DSPM approach and the FE method revealed that the DSPM approach is capable of calculating the corresponding confidence interval, simultaneously improving the overall computational efficiency. Comparing the DSPM approach with the GPR method indicates that the DSPM approach has the ability to accurately describe the dynamic response under unknown conditions. Overall, this research demonstrates the feasibility and usability of the proposed DSPM approach for stochastic dynamics simulation of the railway vehicle collision.

The autotransformer (AT) neutral current ratio method is widely used for fault location in the AT traction power network. With the development of high-speed electrified railways, a large number of data show that the relation between the AT neutral current ratio and the distance from the beginning of the fault AT section to the fault point (Q–L relation) is mostly nonlinear. Therefore, the linear Q–L relation in the traditional fault location method always leads to large errors. To solve this problem, a large number of load-related current data that can be used to describe the Q–L relation are obtained through the load test of the electric multiple unit (EMU). Thus, an improved fault location method based on the back propagation (BP) neural network is proposed in this paper. On this basis, a comparison between the improved method and the traditional method shows that the maximum absolute error and the average absolute error of the improved method are 0.651 km and 0.334 km lower than those of the traditional method, respectively, which demonstrates that the improved method can effectively eliminate the influence of nonlinear factors and greatly improve the accuracy of fault location for the AT traction power network. Finally, combined with a short-circuit test, the accuracy of the improved method is verified.