Optimisation design of rail profiles for improving wear and RCF performances on a small-radius curve: A case study

Abstract

Wear and rolling contact fatigue (RCF) are regarded as two prominent factors that deteriorate the long-term service performances and aggravate the maintenance costs of metro rails on the small-radius curves, therefore an effective countermeasure against which is needed. In this work, a long-term rail wear and RCF evolution prediction model based on vehicle-track coupled dynamics and surface material wear and fatigue damage theory is performed, in which an enhanced wheel/rail non-Hertzian contact method are involved. On the other hand, a series of candidate rail profiles are constructed and generated by applying Gaussian function correction (GFC) method; An improved non-dominated sorting genetic algorithm-II (NSGA-II) method is applied for the optimisation design of rail profiles, and then we propose two types of rail profiles which take rail wear or RCF as the optimisation objectives. Further, the long-term rail wear and RCF evolution performances due to the raw rail profiles and optimally designed ones are compared. The results demonstrate that the optimised rail profiles contribute profitably to alleviate the wheel flange-rail gauge corner frictional contact, and subsequently, can slow down the wear and RCF development of rails on sharp-radius curves. This study can offer a theoretical inspection for wear- and RCF-resistant design of rail grinding profiles.