Assessment of overturning risk of high-speed trains in strong crosswinds using spectral analysis approach

Naijie Yan, Xinzhong Chen, Yongle Li

Research output: Contribution to journalArticlepeer-review

17 Scopus citations

Abstract

This study introduces a spectral analysis framework for assessing overturning risk of high-speed trains in strong crosswinds. The wind turbulence relative to moving vehicles is used to model stochastic wind excitation, whose spectral characteristics are determined by a newly introduced general method from the spectrum and coherence function of turbulence relative to ground. The unsteady aerodynamic forces on vehicles are modeled with consideration of longitudinal, lateral and vertical turbulence components. Based on the wind tunnel experiments of a typical China railway high-speed train model, the side and lift force coefficients and aerodynamic admittance functions associated with different turbulence components are extracted, where the effects of spatial coherence of turbulence are explicitly accounted for. The probabilistic overturning risk is then evaluated through unloading rate of wheel-rail contact force, which leads to the determination of probabilistic characteristic wind curve. The results demonstrated that the dynamic wheel-rail contact force induced by track irregularities is lower than that by wind turbulence. In addition to the traditionally considered longitudinal turbulence, the lateral and vertical turbulence components also have great contribution to vehicle response. Adequate modeling of aerodynamic admittance functions is also important for better quantifications of vehicle response and overturning risk.

Original languageEnglish
Pages (from-to)103-118
Number of pages16
JournalJournal of Wind Engineering and Industrial Aerodynamics
Volume174
DOIs
StatePublished - Mar 2018

Keywords

  • Aerodynamic admittance function
  • Crosswind
  • Dynamic response
  • Moving vehicle
  • Overturning risk
  • Unsteady aerodynamic forces

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