Abstract
A simulation procedure to predict the probability of rail break due to a measured wheel load spectrum is presented. The load distribution includes a representative proportion of high-magnitude dynamic loads generated by out-of-round wheels. Linear elastic fracture mechanics is applied to determine the stress intensities of pre-existing rail head cracks in a continuously welded rail subjected to combined bending and temperature loading. Rail bending moments are evaluated using a validated time-domain model of dynamic vehicle–track interaction. The considered multi-dimensional stochastic parameter space includes field test data of dynamic loads from a wheel impact load detector and crack depths from eddy current data. Meta-models based on poly-harmonic splines are applied to reduce the computational cost of the analysis. Supported by the extensive field test data, the simulation procedure is demonstrated by investigating the influences of freight traffic type, track support stiffness and rail temperature on the probability of a rail break initiated at a pre-existing rail head crack.
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