This study aims to solve the problem of weld quality inspection, for the aluminum alloy profile welding structure of high-speed train body has complex internal shape and thin plate thickness (2-4 mm), the conventional nondestructive testing method of weld quality is difficult to implement.

In order to solve this problem, the ultrasonic creeping wave detection technology was proposed. The impact of the profile structure on the creeping wave detection was studied by designing profile structural test blocks and artificial simulation defect test blocks. The detection technology was used to test the actual welded test blocks, and compared with the results of X-ray test and destructive test (tensile test) to verify the accuracy of the ultrasonic creeping wave test results.

It is indicated that that X-ray has better effect on the inspection of porosities and incomplete penetration defects. However, due to special detection method and protection, the detection speed is slow, which cannot meet the requirements of field inspection of the welding structure of aluminum alloy thin-walled profile for high-speed train body. It can be used as an auxiliary detection method for a small number of sampling inspection. The ultrasonic creeping wave can be used to detect the incomplete penetration welds with the equivalent of 0.25 mm or more, the results of creeping wave detection correspond well with the actual incomplete penetration defects.

The results show that creeping wave detection results correspond well with the actual non-penetration defects and can be used for welding quality inspection of aluminum alloy thin-wall profile composite welding joints. It is recommended to use the echo amplitude of the 10 mm × 0.2 mm × 0.5 mm notch as the criterion for weld qualification.

The traction cable is paralleled with the existing traction network of electrified railway through transverse connecting line to form the scheme of long distance power supply for the traction network. This paper aims to study the scheme composition and power supply distance (PSD) of the scheme.

Based on the structure of parallel traction network (referred to as "cable traction network (CTN)"), the power supply modes (PSMs) are divided into cable + direct PSM and cable + autotransformer (AT) PSM (including Japanese mode, French mode and new mode). Taking cable + Japanese AT PSM as an example, the scheme of long distance power supply for CTN under the PSMs of co-phase and out-of-phase power supply are designed. On the basis of establishing the equivalent circuit model and the chain circuit model of CTN, taking the train working voltage as the constraint condition, and based on the power flow calculation of multiple train loads, the calculation formula and process for determining the PSD of CTN are given. The impedance and PSD of CTN under the cable + AT PSM are simulated and analyzed, and a certain line is taken as an example to compare the scheme design.

Results show that the equivalent impedance of CTN under the cable + AT PSM is smaller, and the PSD is about 2.5 times of that under the AT PSM, which can effectively increase the PSD and the flexibility of external power supply location.

The research content can effectively improve the PSD of traction power supply system and has important reference value for the engineering application of the scheme.

This study aims to analyze the development direction of train speed, density and weight in China.

The development of China's railway in the past 40 years can be divided into 3 stages. At the stage of potential tapping and capacity expansion, it is important to improve the train weight and density by upgrading the existing lines, and improving transportation capacity rapidly. At the stage of railway speed increase, the first priority is to increase train speed, reduce the travel time of passenger train, and synchronously take into account the increase of train density and weight. At the stage of developing high-speed railway, train speed, density and weight are co-developing on demand.

The train speed of high-speed railway will be 400 km h^-1, the interval time of train tracking will be 3 min, and the traffic density will be more than 190 pairs per day. The running speed of high-speed freight EMU will reach 200 km h^-1 and above. The maximum speed of passenger train on mixed passenger and freight railway can reach 200 km h^-1. The minimum interval time of train tracking can be compressed to 5 min. The freight train weight of 850 m series arrival-departure track railway can be increased to 4,500-5,000 t and that of 1,050 m series to 5,500-6,400 t. EMU trains should gradually replace ordinary passenger trains to improve the quality of railway passenger service. Small formation trains will operate more in intercity railway, suburban railway and short-distance passenger transportation.

The research can provide new connotations and requirements of railway train speed, density and weight in the new railway stage.

Under the constraints of given passenger service level and coupling travel demand with train departure time, this study optimizes the train operational plan in an urban rail corridor to minimize the numbers of train trips and rolling stocks considering the time-varying demand of urban rail passenger flow.

The authors optimize the train operational plan in a special network layout, i.e. an urban rail corridor with dead-end terminal yard, by decomposing it into two sub-problems: train timetable optimization and rolling stock circulation optimization. As for train timetable optimization, the authors propose a schedule-based passenger flow assignment method, construct the corresponding timetabling optimization model and design the bi-directional coordinated sequential optimization algorithm. For the optimization of rolling stock circulation, the authors construct the corresponding optimization assignment model and adopt the Hungary algorithm for solving the model.

The case study shows that the train operational plan developed by the study's approach meets requirements on the passenger service quality and reduces the operational cost to the maximum by minimizing the numbers of train trips and rolling stocks.

The example verifies the efficiency of the model and algorithm.