Efficient parameters to predict the nonlinear behavior of FRP retrofitted RC columns

While fiber-reinforced plastic (FRP) materials have been largely used in the retrofitting of concrete buildings, its application has been limited because of some problems such as de-bonding of FRP layers from the concrete surface. This paper is the part of a wide experimental and analytical investigation about flexural retrofitting of reinforced concrete (RC) columns using FRP and mechanical fasteners (MF). A new generation of MF is proposed, which is applicable for retrofitting of RC columns. Furthermore, generally, to evaluate a retrofitted structure the nonlinear static and dynamic analyses are the most accurate methods to estimate the performance of a structure. In the nonlinear analysis of a structure, accurate modeling of structural elements is necessary for estimation the reasonable results. So for nonlinear analysis of a structure, modeling parameters for beams, columns, and beam-column joints are essential. According to the concentrated hinge method, which is one of the most popular nonlinear modeling methods, structural members shall be modeled using concentrated or distributed plastic hinge models using modeling parameters. The nonlinear models of members should be capable of representing the inelastic response of the component. On the other hand, in performance based design to make a decision about a structure or design a new one, numerical acceptance should be determined. Modeling parameters and numerical acceptance criteria are different for buildings of different types and for different performance levels. In this paper, a new method was proposed for FRP retrofitted columns to avoid FRP debonding. For this purpose, mechanical fasteners were used to achieve the composite behavior of FRP and concrete columns. The experimental results showed that the use of the new method proposed in this paper increased the flexural strength and lateral load capacity of the columns significantly, and a good composition of FRP and RC column was achieved. Moreover, the modeling parameters and acceptance criteria were presented, which were derived from the experimental study in order to use in nonlinear analysis and performance-based design approach.