A reliability assessment approach for slab track structure based on vehicle-track dynamics and surrogate model

Abstract

The reliability assessment of rail infrastructure is directly related to the safety and effectiveness of railway transportation and critical for railway management department. This paper presents an approach for service reliability analysis of slab track from the point of view of the vehicle-track system operational safety. The vehicle-track dynamics is simulated by the established finite element model (FEM) and the limit state function (LSF) is defined on the danger of derailment. To reflect the real state of track geometric condition, the track irregularity spectrums (TISs) are extracted from the measured track irregularity data and fitted by the seven-parameter formula. Then, a set of time series can be obtained from the TISs using a binary wavelet-based inversion method and then input to the FEM to obtain the value of LSF. Finally, Monte Carlo simulation (MCS) is used in the calculation of track reliability. To overcome the slow convergence of the vehicle-track models, this study develops a surrogate model based on support vector machine (SVM). It is validated that the established SVM can well approximate the relationship between the track irregularities to the derailment coefficients in terms of small error and high correlation. More importantly, the efficiency is more than 1000 times higher than traditional FEM. This is a pioneering study to incorporate vehicle-track dynamics into the reliability assessment of slab track in service. For a 1024-m section of slab track, results show that its reliability index can satisfy the requirement in specifications.