Stochastic approach to fatigue crack-growth simulation for a railway axle under input data variability

Fatigue crack-growth of mechanical components is stochastic in nature and deterministic approaches do not allow for its complete study. Primary sources of this stochasticity can be: the inherent variability of material properties, the nature of service load fluctuations, the approximations assumed by the algorithms to calculate the main fracture parameters. This work reports a stochastic approach to the fatigue crack-growth in a railway axle under variability of different input parameters. The approach is used to predict the probability distribution of the residual fatigue life of a railway axle in presence of defects taking into account multiple sources of uncertainty.

Automated summary

The study focuses on the stochastic nature of fatigue crack-growth in mechanical components and the prediction of residual fatigue life of a railway axle under different input parameters variability. Various sources of uncertainty are considered in the analysis.