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Train-track-bridge dynamic interaction: a state-of-the-art review

Vehicle system dynamics, 2019-07, Vol.57 (7), p.984-1027 [Peer Reviewed Journal]

2019 The Author(s). Published by Informa UK Limited, trading as Taylor & Francis Group 2019 ;ISSN: 0042-3114 ;EISSN: 1744-5159 ;DOI: 10.1080/00423114.2019.1605085

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  • Title:
    Train-track-bridge dynamic interaction: a state-of-the-art review
  • Author: Zhai, Wanming ; Han, Zhaoling ; Chen, Zhaowei ; Ling, Liang ; Zhu, Shengyang
  • Subjects: dynamic model ; engineering application ; experimental investigation ; safety assessment ; train-bridge dynamic interaction ; Train-track-bridge dynamic interaction
  • Is Part Of: Vehicle system dynamics, 2019-07, Vol.57 (7), p.984-1027
  • Description: Train-track-bridge dynamic interaction is a fundamental concern in the field of railway engineering, which plays an extremely important role in the optimal design of railway bridges, especially in high-speed railways and heavy-haul railways. This paper systematically presents a state-of-the-art review of train-track-bridge dynamic interaction. The evolution process of train-bridge dynamic interaction model is described briefly, from the simplest moving constant force model to the sophisticated train-track-bridge dynamic interaction model (TTBDIM). The modelling methodology of the key elements in the TTBDIM is systematically reviewed, including the train, the track, the bridge, the wheel-rail contact, the track-bridge interaction, the system excitation and the solution algorithm. The significance of detailed track modelling in the whole system is highlighted. The experimental research and filed test focusing on modelling validation, safety assessment and long-term performance investigation of the train-track-bridge system are briefly presented. The practical applications of train-track-bridge dynamic interaction theory are comprehensively discussed in terms of the system dynamic performance evaluation, the system safety assessment and train-induced environmental vibration and noise prediction. The guidance is provided on further improvement of the train-track-bridge dynamic interaction model and the challenging research topics in the future.
  • Publisher: Taylor & Francis
  • Language: English
  • Identifier: ISSN: 0042-3114
    EISSN: 1744-5159
    DOI: 10.1080/00423114.2019.1605085
  • Source: Taylor & Francis Open Access
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