A hybrid reliability assessment method for slab track with changing structural parameters

Abstract

Changes in the dynamic properties of high-speed rail (HSR) slab track structures can have a great impact on train safety and ride quality. However, the dynamic response of wheel–rail systems, which is related to operational safety, has rarely been considered in existing service reliability assessments of track structures. To solve this problem, a hybrid method was developed, with the serviceability limit state (SLS) first defined with respect to the derailment coefficient (DC) and wheel unloading rate (WUR). In calculating the reliability index, the response surface method and the first-order reliability method were used to solve the implicit expression of wheel–rail force in the SLS equation. To reduce the computation cost, a surrogate model expressing the non-linear mapping of the wheel–rail interaction is proposed. The computation efficiency and accuracy of the hybrid method were compared with Monte Carlo simulation and a back-propagation neural network (BPNN). The computation time of the hybrid method was only 1/8.4 of the BPNN method, while the accuracy of the reliability index was 98% for the DC and 97% for the WUR. The hybrid method was used to assess the reliability of a typical slab track structure under changing stiffness and damping coefficients of the fasteners, cement asphalt mortar and foundation. The stiffness and damping of the fasteners had the most impact on wheel–rail dynamics and track reliability. This research provides new insights into reliability assessments for HSR slab track with respect to train operational safety.