Wind and Structures

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Dynamics of high-speed train in crosswinds based on an air-train-track interaction model

  • Zhai, Wanming (Train and Track Research Institute, State Key Laboratory of Traction Power, Southwest Jiaotong University) ;
  • Yang, Jizhong (China Railway Eryuan Engineering Group Co. Ltd.) ;
  • Li, Zhen (Train and Track Research Institute, State Key Laboratory of Traction Power, Southwest Jiaotong University) ;
  • Han, Haiyan (Beijing Urban Construction Design and Development Group Co. Ltd)
  • Received : 2014.11.20
  • Accepted : 2015.01.05
  • Published : 2015.02.25
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Abstract

A numerical model for analyzing air-train-track interaction is proposed to investigate the dynamic behavior of a high-speed train running on a track in crosswinds. The model is composed of a train-track interaction model and a train-air interaction model. The train-track interaction model is built on the basis of the vehicle-track coupled dynamics theory. The train-air interaction model is developed based on the train aerodynamics, in which the Arbitrary Lagrangian-Eulerian (ALE) method is employed to deal with the dynamic boundary between the train and the air. Based on the air-train-track model, characteristics of flow structure around a high-speed train are described and the dynamic behavior of the high-speed train running on track in crosswinds is investigated. Results show that the dynamic indices of the head car are larger than those of other cars in crosswinds. From the viewpoint of dynamic safety evaluation, the running safety of the train in crosswinds is basically controlled by the head car. Compared with the generally used assessment indices of running safety such as the derailment coefficient and the wheel-load reduction ratio, the overturning coefficient will overestimate the running safety of a train on a track under crosswind condition. It is suggested to use the wheel-load reduction ratio and the lateral wheel-rail force as the dominant safety assessment indices when high-speed trains run in crosswinds.

Keywords

Acknowledgement

Supported by : National Natural Science Foundation of China (NSFC)

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