It is of great significance to study the influence of subgrade filling on permafrost temperature field in permafrost area for the smooth construction and safe operation of railway.

The paper builds up the model for the hydrothermal coupling calculation of permafrost using finite element software COMSOL to study how permafrost temperature field changes in the short term after subgrade filling, on which basis it proposes the method of calculation for the concave distortion of freezing front in the subgrade-covered area.

The results show that the freezing front below the subgrade center sinks due to the thermal effect of subgrade filling, which will trigger hydrothermal erosion in case of sufficient moisture inflows, leading to the thawing settlement or the cracking of the subgrade, etc. The heat output of soil will be hindered the most in case of July filling, in which case the sinking and the distortion of the freezing front is found to be the most severe, which the recovery of the permafrost temperature field, the slowest, constituting the most unfavorable working condition. The concave distortion of the freezing front in the subgrade area increases with the increase in temperature difference between the filler and ground surface, the subgrade height, the subgrade width and the volumetric thermal capacity of filler, while decreases with the increase of the thermal conductivity of filler. Therefore, the filler chose for engineering project shall be of small volumetric thermal capacity, low initial temperature and high thermal conductivity whenever possible.

The concave distortion of the freezing front under different working conditions at different times after filling can be calculated using the method proposed.

This paper aims to provide top-level design and basic platform for intelligent application in China high-speed railway.

Based on the analysis for the future development trends of world railway, combined with the actual development needs in China high-speed railway, The definition and scientific connotation of intelligent high-speed railway (IHSR) are given at first, and then the system architecture of IHSR are outlined, including 1 basic platform, 3 business sectors, 10 business fields, and 18 innovative applications. At last, a basic platform with cloud edge integration for IHSR is designed.

The rationality, feasibility and implementability of the system architecture of IHSR have been verified on and applied to the Beijing-Zhangjiakou high-speed railway, providing important support for the construction and operation of the world's first IHSR.

This paper systematically gives the definition and connotation of the IHSR and put forward the system architecture of IHSR for first time. It will play the most important role in the design, construction and operation of IHSR.

This study aims to ensure the operation safety of high speed trains, it is necessary to carry out nondestructive monitoring of the tensile damage of the gearbox housing material in rail time, yet the traditional tests of mechanical property can hardly meet this requirement.

In this study the acoustic emission (AE) technology is applied in the tensile tests of the gearbox housing material of an high-speed rail (HSR) train, during which the acoustic signatures are acquired for parameter analysis. Afterward, the support vector machine (SVM) classifier is introduced to identify and classify the characteristic parameters extracted, on which basis the SVM is improved and the weighted support vector machine (WSVM) method is applied to effectively reduce the misidentification of the SVM classifier. Through the study of the law of relations between the characteristic values and the tensile life, a degradation model of the gearbox housing material amid tensile is built.

The results show that the growth rate of the logarithmic hit count of AE signals and that of logarithmic amplitude can well characterize the stage of the material tensile process, and the WSVM method can improve the classification accuracy of the imbalanced data to above 94%. The degradation model built can identify the damage occurred to the HSR gearbox housing material amid the tensile process and predict the service life remains.

The results of this study provide new concepts for the life prediction of tensile samples, and more further tests should be conducted to verify the conclusion of this research.

This study aims to research the large cross-section tunnel stability evaluation method corrected after considering the thickness-span ratio.

First, taking the Liuyuan Tunnel of Huanggang-Huangmei High-Speed Railway as an example and taking deflection of the third principal stress of the surrounding rock at a vault after tunnel excavation as the criterion, the critical buried depth of the large section tunnel was determined. Then, the strength reduction method was employed to calculate the tunnel safety factor under different rock classes and thickness-span ratios, and mathematical statistics was conducted to identify the relationships of the tunnel safety factor with the thickness-span ratio and the basic quality (BQ) index of the rock for different rock classes. Finally, the influences of thickness-span ratio, groundwater, initial stress of rock and structural attitude factors were considered to obtain the corrected BQ, based on which the stability of a large cross-section tunnel with a depth of more than 100 m during mechanized operation was analyzed. This evaluation method was then applied to Liuyuan Tunnel and Cimushan No. 2 Tunnel of Chongqing Urban Expressway for verification.

This study shows that under different rock classes, the tunnel safety factor is a strict power function of the thickness-span ratio, while a linear function of the BQ to some extent. It is more suitable to use the corrected BQ as a quantitative index to evaluate tunnel stability according to the actual conditions of the site.

The existing industry standards do not consider the influence of buried depth and span in the evaluation of tunnel stability. The stability evaluation method of large section tunnel considering the correction of overburden span ratio proposed in this paper achieves higher accuracy for the stability evaluation of surrounding rock in a full or large-section mechanized excavation of double line high-speed railway tunnels.

For billing purposes, heavy-haul locomotives in Sweden are equipped with on-board energy meters, which can record several parameters, e.g., used energy, regenerated energy, speed and position. Since there is a strong demand for improving energy efficiency in Sweden, data from the energy meters can be used to obtain a better understanding of the detailed energy usage of heavy-haul trains and identify potential for future improvements.

To monitor energy efficiency, the present study, therefore, develops key performance indicators (KPIs), which can be calculated with energy meter data to reflect the energy efficiency of heavy-haul trains in operation. Energy meter data of IORE class locomotives, hauling highly uniform 30-tonne axle load trains with 68 wagons, together with additional data sources, are analysed to identify significant parameters for describing driver influence on energy usage.

Results show that driver behaviour varies significantly and has the single largest influence on energy usage. Furthermore, parametric studies are performed with help of simulation to identify the influence of different operational and rolling stock conditions, e.g., axle loads and number of wagons, on energy usage.

Based on the parametric studies, some operational parameters which have significant impact on energy efficiency are found and then the KPIs are derived. In the end, some possible measures for improving energy performance in heavy-haul operations are given.

With the yearly increase of mileage and passenger volume in China's high-speed railway, the problems of traditional paper railway tickets have become increasingly prominent, including complexity of business handling process, low efficiency of ticket inspection and high cost of usage and management. This paper aims to make extensive references to successful experiences of electronic ticket applications both domestically and internationally. The research on key technologies and system implementation of railway electronic ticket with Chinese characteristics has been carried out.

Research in key technologies is conducted including synchronization technique in distributed heterogeneous database system, the grid-oriented passenger service record (PSR) data storage model, efficient access to massive PSR data under high concurrency condition, the linkage between face recognition service platforms and various terminals in large scenarios, and two-factor authentication of the e-ticket identification code based on the key and the user identity information. Focusing on the key technologies and architecture the of existing ticketing system, multiple service resources are expanded and developed such as electronic ticket clusters, PSR clusters, face recognition clusters and electronic ticket identification code clusters.

The proportion of paper ticket printed has dropped to 20%, saving more than 2 billion tickets annually since the launch of the application of E-ticketing nationwide. The average time for passengers to pass through the automatic ticket gates has decreased from 3 seconds to 1.3 seconds, significantly improving the efficiency of passenger transport organization. Meanwhile, problems of paper ticket counterfeiting, reselling and loss have been generally eliminated.

E-ticketing has laid a technical foundation for the further development of railway passenger transport services in the direction of digitalization and intelligence.

The purpose of the study is to quickly identify significant heterogeneity of surrounding rock of tunnel face that generally occurs during the construction of large-section rock tunnels of high-speed railways.

Relying on the support vector machine (SVM)-based classification model, the nominal classification of blastholes and nominal zoning and classification terms were used to demonstrate the heterogeneity identification method for the surrounding rock of tunnel face, and the identification calculation was carried out for the five test tunnels. Then, the suggestions for local optimization of the support structures of large-section rock tunnels were put forward.

The results show that compared with the two classification models based on neural networks, the SVM-based classification model has a higher classification accuracy when the sample size is small, and the average accuracy can reach 87.9%. After the samples are replaced, the SVM-based classification model can still reach the same accuracy, whose generalization ability is stronger.

By applying the identification method described in this paper, the significant heterogeneity characteristics of the surrounding rock in the process of two times of blasting were identified, and the identification results are basically consistent with the actual situation of the tunnel face at the end of blasting, and can provide a basis for local optimization of support parameters.

In this paper, the C80 special coal gondola car was taken as the subject, and the load test data of the car body at the center plate, side bearing and coupler measured on the dedicated line were broken down to generate the random load component spectrums of the car body under five working conditions, namely expansion, bouncing, rolling, torsion and pitching according to the typical motion attitude of the car body.

On the basis of processing the measured load data, the random load component spectrums were equivalently converted into sinusoidal load component spectrums for bench test based on the principle of pseudo-damage equivalence of load. Relying on the fatigue and vibration test bench of the whole railway wagon, by taking each sinusoidal load component spectrum as the simulation target, the time waveform replication (TWR) iteration technology was adopted to create the drive signal of each loading actuator required for the fatigue test of car body on the bench, and the drive signal was corrected based on the equivalence principle of measured stress fatigue damage to obtain the fatigue test loads of car body under various typical working conditions.

The fatigue test results on the test bench were substantially close to the measured test results on the line. According to the results, the relative error between the fatigue damage of the car body on the test bench and the measured damage on the line was within the range of -16.03%-27.14%.

The bench test results basically reproduced the fatigue damage of the key parts of the car body on the line.

This study aims to propose an adaptive fractional-order sliding mode controller to solve the problem of train speed tracking control and position interval control under disturbance environment in moving block system, so as to improve the tracking efficiency and collision avoidance performance.

The mathematical model of information interaction between trains is established based on algebraic graph theory, so that the train can obtain the state information of adjacent trains, and then realize the distributed cooperative control of each train. In the controller design, the sliding mode control and fractional calculus are combined to avoid the discontinuous switching phenomenon, so as to suppress the chattering of sliding mode control, and a parameter adaptive law is constructed to approximate the time-varying operating resistance coefficient.

The simulation results show that compared with proportional integral derivative (PID) control and ordinary sliding mode control, the control accuracy of the proposed algorithm in terms of speed is, respectively, improved by 25% and 75%. The error frequency and fluctuation range of the proposed algorithm are reduced in the position error control, the error value tends to 0, and the operation trend tends to be consistent. Therefore, the control method can improve the control accuracy of the system and prove that it has strong immunity. Originality/value - The algorithm can reduce the influence of external interference in the actual operating environment, realize efficient and stable tracking of trains, and ensure the safety of train control.

As the strategy of 5G new infrastructure is deployed and advanced, 5G-R becomes the primary technical system for future mobile communication of China's railway. V2V communication is also an important application scenario of 5G communication systems on high-speed railways, so time synchronization between vehicles is critical for train control systems to be real-time and safe. How to improve the time synchronization performance in V2V communication is crucial to ensure the operational safety and efficiency of high-speed railways.

This paper proposed a time synchronization method based on model predictive control (MPC) for V2V communication. Firstly, a synchronous clock for V2V communication was modeled based on the fifth generation mobile communication-railway (5G-R) system. Secondly, an observation equation was introduced according to the phase and frequency offsets between synchronous clocks of two adjacent vehicles to construct an MPC-based space model of clock states of the adjacent vehicles. Finally, the optimal clock offset was solved through multistep prediction, rolling optimization and other control methods, and time synchronization in different V2V communication scenarios based on the 5G-R system was realized through negative feedback correction.

The results of simulation tests conducted with and without a repeater, respectively, show that the proposed method can realize time synchronization of V2V communication in both scenarios. Compared with other methods, the proposed method has faster convergence speed and higher synchronization precision regardless of whether there is a repeater or not.

This paper proposed an MPC-based time synchronization method for V2V communication under 5G-R. Through the construction of MPC controllers for clocks of adjacent vehicles, time synchronization was realized for V2V communication under 5G-R by using control means such as multistep prediction, rolling optimization, and feedback correction. In view of the problems of low synchronization precision and slow convergence speed caused by packet loss with existing synchronization methods, the observer equation was introduced to estimate the clock state of the adjacent vehicles in case of packet loss, which reduces the impact of clock error caused by packet loss in the synchronization process and improves the synchronization precision of V2V communication. The research results provide some theoretical references for V2V synchronous wireless communication under 5G-R technology.