Abstract

The railway track, which serves as the direct train support, significantly impacts its safety since the smoothness of the track directly influences safe train operations. Hence, quantifying the track smoothness and determining the optimal train speed threshold post-earthquake can provide critical operational guidance following seismic events. This paper innovatively uses the acceleration, velocity, and displacement-related indicators to quantify track smoothness on bridges after an earthquake. It also conducts correlation, validity, and applicability analyses between these indicators and driving performance, thereby determining the best quantitative indicator for seismic-induced track irregularity from the standpoint of train performance. The research employs linear regression analysis and examines probabilistic statistical properties to determine a quantitative indicator threshold that ensures safe train operations on bridges post-earthquake. Furthermore, it explores the mapping relationship between post-earthquake irregularity and the speed threshold by investigating the relationship between indicator and train speed. The findings revealed a notable logarithmic linear correlation between the indicators quantifying the post-earthquake track smoothness and train operation performance. In addition, velocity-related indicators exhibited the strongest correlation with train operation performance, followed by acceleration and displacement-related indicators. The root-mean-square velocity indicator emerged as the most effective quantifier of seismic-induced track irregularity. The study also found a positive linear relationship between post-earthquake train operating speed and the root-mean-square velocity, assuming identical spatial track geometry conditions. The functional relationship between the post-earthquake speed threshold and the root-mean-square velocity can facilitate rapid evaluations of train operation safety on bridges following earthquakes. This calculation method is user-friendly, conducive to manual computation, and highly applicable to engineering practices.

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