Random simulation method of track irregularities and its application in vehicle-track dynamic analysis

Li Song, Hubing Liu, Lei Xu and Zhiwu Yu

International Journal of Rail Transportation, 2023, vol. 11, issue 2, 169-187

Abstract: Track irregularity holds strong randomicity, evolvability, and large data sets during the long-term operation of a rail line, possessing a significant influence on the dynamic performance of vehicle-track systems. In this work, methods for simulating track random irregularities are developed by combining the track irregularity probability model (TIPM) and the number theory method and by the Karhunen-Loève expansion (KLE). Furthermore, the vehicle-track interaction model considering the interaction between the vehicle, track, and wheel-rail interaction is constructed at a 3-D space, where the multi-rigid-body dynamics, finite method, and wheel-rail contacts are applied to construct matrix-coupled vehicle-track interaction equations. Finally, a unified random vibration analysis framework for the vehicle-track system is presented. From perspectives of the amplitude, power spectral density, and probabilistic distribution, the accuracy and efficiency of TIPM and KLE models in simulating track random irregularities and revealing system dynamics performance are compared and analysed in detail.

Date: 2023
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DOI: 10.1080/23248378.2022.2069170

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