Probabilistic Framework for Future Load Carrying Capacity Estimation of Corroded Metallic Railway Bridges under Heavy Axle Weight Trains

Assessing the future load carrying capacity (characterized on UK railways by means of a route availability number) of historic railway infrastructure under heavy axle weight (HAW) train loads is important for operational and safety reasons. There are, however, considerable difficulties associated with the dual challenges of assessing current condition and potential future rates of degradation. In this paper, a probabilistic assessment framework for estimating the future route availability (RA) number of aging metallic railway bridges is proposed. The methodology is demonstrated with reference to a 37.7-m-long, single-track, three-span, half-through girder, early steel railway bridge. Nonlinear bridge responses to HAW train loads were evaluated using advanced finite-element models accounting for material plasticity, buckling, and potential unstable collapse. Possible failure mechanisms were explored using damage measures related to global and localized performance criteria. Aging of the metallic bridge was modeled assuming that time-dependent nonuniform corrosion dominates the deterioration process. Various model uncertainties, including those governing corrosion, were explicitly accounted for by sampling multiple realizations from a predefined multivariate statistical distribution. Future bridge capacity was quantified in the form of bridge deterioration equations (BDEs), i.e., bridge RA number as a function of age and train speed. Derived BDEs suggest that the bridge currently has sufficient capacity, despite nonuniform corrosion to a maximum depth of approximately 3 mm. However, if further deterioration occurs, HAW traffic accessibility could become compromised in three to four decades. The BDE formulation proposed in this paper provides a straightforward piece of information that can be used to support data-driven decision-making processes for both railway infrastructure owners and freight operators.