Impact of rehabilitation on the structural reliability of a steel truss bridge

During the first half of the 20th century, truss bridges were typically designed using the allowable stress method, applying safety factors to indirectly account for uncertainties. Nowadays, structural reliability methods enable direct consideration of uncertainties and quantification of structural safety. Although some studies in the literature have explored the structural reliability of historical truss bridges, there is still a lack of studies and some challenges, particularly regarding accurate representations of loads, geometries, materials, and nonlinear structural behaviour. The present study contributes to this subject by investigating the reliability indices of the main truss in the approach span of a historical long-span Brazilian bridge, built in the early 1900s, considering a failure mode associated with stiffness loss due to buckling. Another novelty of the paper consists in the application of an Adaptive Kriging-Monte Carlo Simulation framework to a rehabilitated historical steel truss bridge, explicitly incorporating geometric and material nonlinearities related to inelastic buckling. In addition, the paper contributes by quantifying the safety gains associated with different structural strengthening scenarios adopted during the rehabilitation process. Two live load models are also comparatively investigated: one follows the semi-probabilistic approach of the NBR 7188 Brazilian standard, considering a 50-year lifespan, yielding a failure probability which is conditional on the occurrence of a specific load combination; the other employs a probabilistic model from the literature for extreme live loads over a 75-year period. The results highlight the substantial influence of strengthening on the reliability of aging bridges on the investigated limit state, exceeding target values found in the literature. The paper also discusses limitations associated with current live load models and the potential benefits of site-specific Weigh-in-Motion data for future reliability assessments of steel truss bridges.