Probabilistic prediction and calibration for residual shear strength of corroded reinforced concrete columns

Abstract

Degradation of shear strength for reinforced concrete (RC) columns caused by steel corrosion is one of the prominent factors for shortening the entire service life of RC structures. In this work, probabilistic prediction and calibration methods for residual shear strength of corroded RC columns were developed by combining theoretical analysis with available experimental data. Deterministic shear strength degradation model accounting for the cross-sectional area reduction and mechanical properties degradation of steel reinforcement and concrete was derived first based on the truss and arch mechanisms. Then probabilistic prediction model was proposed by introducing probabilistic model parameters and systematic error. Meanwhile, probabilistic model parameters regarding the influences of prior variation coefficients and update times were investigated using the Bayesian theory. Moreover, probabilistic method was implemented to calibrate seven available deterministic shear strength models based on probability density function and confidence interval. Results indict that the proposed model can not only quantify the probabilistic characteristics of shear strength and predict the residual shear strength for any given corrosion level and guarantee rate, but also provide a suitable approach for calibrating the applicability of conventional deterministic shear strength models.