A hybrid method for service reliability assessment of slab track subject to change of structural stiffness and damping

The change of the dynamic properties of high-speed rail (HSR) slab track structure can have a great impact on the ride quality and safety of the trains. However, the dynamic response of the wheel-rail system, which is related to operational safety has rarely been considered in the existing rules of service reliability assessment for track structure. To consider the operational safety in reliability assessment for slab track, this paper proposes a hybrid method, in which the serviceability limit state (SLS) is first defined with respect to the derailment coefficient and wheel unloading rate. In reliability index calculation, the response surface method (RSM) and the first-order reliability method (FORM) are employed to solve the implicit expression of wheel-rail force in the SLS equation. To reduce the computation cost in calculating the wheel-rail force, a surrogate model expressing the nonlinear mapping of the wheel-rail interaction based on support vector regression (SVR) is proposed. The performance of the hybrid method is then verified against the Monte Carlo simulation (MCS) method and the BP neural network-based method from the perspective of computation efficiency and accuracy. It is found that the computation time of the hybrid method is reduced to only 1/8.4 of the BP neural network method, while the accuracy of the reliability index can achieve 98% for derailment coefficient and 97% for wheel unloading rate. Lastly, the hybrid method is applied to assess the reliability of a typical slab track structure under the changing stiffness and damping coefficients of the fasteners, cement asphalt (CA) mortar, and foundation. The results show that the stiffness and damping of fasteners have a larger impact on both wheel-rail dynamics and track reliability, compared to those of CA mortar and foundation. This research can provide new insights into the reliability assessment for HSR slab track with respect to the operational safety of the trains.