Seismic fragility estimates for reinforced concrete bridges subject to corrosion

• Published in: Structural safety Vol. 31; no. 4; pp. 275 - 283
• Main Authors: Choe, Do-Eun, Gardoni, Paolo, Rosowsky, David, Haukaas, Terje
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier Ltd 01.07.2009; Elsevier
• Subjects: Applied sciences; Bridges; Buildings. Public works; Concrete bridges; Corrosion; Drift capacity; Exact sciences and technology; Probabilistic demand models; Reinforced concrete columns; Sensitivity analysis; Shear capacity; Stresses. Safety; Structural analysis. Stresses; USA, California; Shear capacity; Drift capacity; Probabilistic demand models; Sensitivity analysis; Reinforced concrete columns; Corrosion; Demand; Earthquake engineering; Shear strength; Brittleness; Modeling; Reinforced concrete; Bridges; Concrete construction; Drift; Probabilistic model; Application
• DOI: 10.1016/j.strusafe.2008.10.001
• ISSN: 0167-4730

The paper develops novel probabilistic models for the seismic demand of reinforced concrete bridges subject to corrosion. The models are developed by extending currently available probabilistic models for pristine bridges with a probabilistic model for time-dependent chloride-induced corrosion. In particular, the models are developed for deformation and shear force demands. The demand models are combined with existing capacity models to obtain seismic fragility estimates of bridges during their service life. The estimates are applicable to bridges with different combinations of chloride exposure condition, environmental oxygen availability, water-to-cement ratios, and curing conditions. Model uncertainties in the demand, capacity and corrosion models are accounted for, in addition to the uncertainties in the environmental conditions, material properties, and structural geometry. As an application, the fragility of a single-bent bridge typical of current California practice is presented to demonstrate the developed methodology. Sensitivity and importance analyses are conducted to identify the parameters that contribute most to the reliability of the bridge and the random variables that have the largest effect on the variance of the limit state functions and thus are most important sources of uncertainty.