Probabilistic Shear Capacity Models for Concrete Members with Internal Composite Reinforcement

Abstract

This paper presents probabilistic models for estimating shear capacity of concrete members reinforced internally with fiber-reinforced polymer (FRP). The application of FRP in concrete structures has steadily gained popularity since the late 1980s; however, the wide range of mechanical properties and various manufacturing processes have made it challenging to unify the design formulation for engineers and code developers. Consequently, the conservative approach has been used to predict structural performance, particularly shear capacity, which has limited its application and resulted in excessive use of materials. In this paper, a robust prediction model is proposed to capture the variety of characteristics of FRPs based on an available database. The database includes various FRPs used as flexural reinforcement for beam members. The model was formulated using the Bayesian parameter estimation method, which takes into account the uncertainties of the parameters that are considered the potential predictors in the model. This paper presents the overall development of the model and provides comparisons with existing models and design equations. The model was formulated for shear capacities without FRP shear reinforcement (flexural reinforcement only). The results indicated that the performance of the proposed model was superior to comparable models.