A probabilistic framework for future load carrying capacity estimation of corroded metallic railway bridges under heavy axle weight trains

Abstract

Assessing the future load carrying capacity (characterised 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 future Route Availability (RA) number of ageing 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 are 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 localised performance criteria. Ageing of the metallic bridge was modelled assuming that time-dependent non-uniform corrosion dominates the deterioration process. Various model uncertainties, including those governing corrosion, were explicitly accounted for by sampling multiple realisations from a pre-defined 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.

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Identifiers

ORCID for Geoff Watson: orcid.org/0000-0003-3074-5196

ORCID for David Milne: orcid.org/0000-0001-6702-3918

ORCID for William Powrie: orcid.org/0000-0002-2271-0826

ORCID for Mehdi Kashani: orcid.org/0000-0003-0008-0007

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