Rail profile design optimisation for a broad-gauge heavy haul line

Increasing axle loads and speeds in heavy-haul railway systems have intensified rail and wheel damage, leading to elevated maintenance costs and reduced operational efficiency. A promising solution to this issue without compromising service demands is enhancing wheel – rail interaction through optimisation of rail profiles. This study introduces a rail profile optimisation framework tailored for a broad-gauge heavy-haul network experiencing excessive rail wear, utilising Non-dominated Sorting Genetic Algorithm II (NSGA-II). The framework is designed to minimise wear and rolling contact fatigue (RCF) while maintaining satisfactory and safe vehicle dynamic performance. The framework includes optimisation of both high and low rail profiles for sharp and mild curves, as well as optimisation of two rail profiles for tangent track to improve contact point distribution and reduce hollow wear. The optimisation process is based on in-service profiles to ensure practical grindability and incorporates multi-body simulations (MBS) to assess wheel and rail damage as well as vehicle dynamic behaviour. The results indicate that the optimised profiles substantially reduce wear and RCF across various track sections. Furthermore, long-term wear and RCF evaluation of rail profiles on sharp and mild curves confirm the superior performance of optimised profiles, thereby validating their potential for integration into maintenance practices.