Probabilistic identification of the effects of corrosion propagation on reinforced concrete structures via deflection and crack width measurements

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Springer Netherlands

Abstract

This study presents a probabilistic framework for accurate prediction of the impacts of corrosion propagation on reinforced concrete (RC) structures. The presented framework uses the ensemble Kalman filter (EnKF) coupled with easily acquired measurements of corrosive crack widths and mid-span deflection increases for identifying and calibrating corrosion propagation models. The calibrated models are consequently used to forecast the extent of corrosion propagation in RC structures. To assess the efficacy of the presented framework, data corresponding to the long-term chloride-induced corrosion experiments initiated in 1984 at “Laboratoire des Materiaux et Durabilite des Constructions” (L.M.D.C.) in Toulouse, south-west France are used. The results accentuate the robustness of the presented EnKF approach by being able to identify and calibrate candidate corrosion propagation models capable of predicting, with reasonable accuracy, the experimental measurements of corrosive crack width and mid-span deflection in RC members. © 2019, RILEM.

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Corrosion propagation rate, Data assimilation, Ensemble kalman filter, Reinforced concrete, Uncertainty quantification, Chlorine compounds, Corrosive effects, Forecasting, Kalman filters, Passive filters, Steel beams and girders, Accurate prediction, Chloride induced corrosion, Corrosion propagation, Crack width measurement, Probabilistic framework, Uncertainty quantifications, Cracks

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