Probabilistic Fatigue Evaluation of Riveted Railway Bridges

Abstract

A probabilistic fatigue assessment methodology for riveted railway bridges is presented. The methodology is applied to a typical, short-span, riveted U.K. railway bridge under historical and present day train loading. On the loading side, the problem is randomized through dynamic amplification and traffic volume; on the resistance side, the S-N curves and the cumulative damage model are treated probabilistically. Model uncertainty is represented by the ratio between actual and calculated stresses, the latter obtained through finite element analysis. Annual response spectra for a fatigue-critical connection are developed through Monte Carlo simulation, which show that there is a continual and accelerating increase in the mean stress range experienced by the connection with time. S-N curves proposed in United States and United Kingdom codes are used in combination with Miner’s rule, to estimate the remaining fatigue life of the connection for different target failure probabilities. Parametric studies revealed that fatigue life estimates exhibit the highest sensitivity to detail classification, to S-N predictions in the region of high endurances, and to model uncertainty. This highlights the importance of field monitoring for old bridges approaching the end of their useful life.