Measurement-informed fatigue-driven reliability analysis for century-old corroded steel rail-bridge integrating Bayesian inference and FORM

Abstract Fatigue damage is a predominant failure mechanism in historical riveted railway bridges, which is intensified by corrosion over time. This paper presents a fatigue-based reliability analysis of a century-old riveted steel railway bridge, decommissioned in 2010 due to significant corrosion-induced fatigue damage. As part of the German Thüringen railway system connecting Wolkramshausen and Erfurt, this bridge serves as a case study for observing a combined influence of fatigue and corrosion on the structural performance. Fatigue life was initially calculated from measured displacements, and later was incorporated into corrosion model (to account for geometry loss) to describe the localised distribution of section loss in future. The results were furthermore compared with those obtained through modified corrosion-induced S–N curves. To be able to make a comparison between these two approaches, a new decomposition between geometry-induced stress amplification and notching effects was developed, which permitted time-dependent notch factors to be determined. With these developments, the reliability evaluation was reassessed over the service life of bridge with Bayesian inference and First Order Reliability Method (FORM). By regulating the analysis based on the real state of the structure, the framework enhances the predictive accuracy of fatigue damage progression and provides insights about how reliability margins develop in the presence of corrosion. The research highlights how structural health monitoring (SHM) data, in combination with uncertainly based approaches and reliability analysis, contributing to more effective maintenance and management strategies for historic structures.