Seismic Behavior of Exterior Lightweight Concrete Beam-Column Joints Reinforced with Headed Bars

An experimental study was conducted to investigate the performance of high strength lightweight concrete (LWC) in exterior beam-column joints subjected to reverse cyclic loading. Four beam-column joints made of LWC and reinforced with headed bars were tested in the laboratory. Headed rebars were used to compensate for the additional anchorage demand due to the weaker bond strength of LWC. The test variables included the amount of reinforcement in the beam and column, shear reinforcement in the joint, and the flexural capacity ratio. The objective of this research is to evaluate the seismic resistance of the joints for these selected test variables, in terms of deformation, strength, ductility, and energy dissipation characteristics. In this paper it was concluded that the initial failure for all specimens were initiated by forming a plastic hinge in beam within a distance of 2h, where h is the depth of the beam. The flexural capacity ratio controls the degree of damage in the joint. Also, it was concluded that the ductility and strength characteristics of beam-column joints are directly related to the amount of reinforcement in the beam as it was expected in RC joint built with normal weight concrete (NWC). Based on the limited test data of LWC, it can be concluded that high strength LWC can be used as an alternative of NWC by limiting the γ value to 10. A simplified FEM model was developed for Reinforced Concrete (RC) exterior beam-column joint. The proposed model is a conceptual FEM model where the problem was defined by a combination of axial and rotational springs. In addition, an extensive parametric study was performed to evaluate the effect of rectangular hoop confinement and the concrete strength on the shear strength of the RC joint. An empirical expression was developed to determine the shear strength. The predicted model was validated against thirty tested specimens collected from the literature, and the performance of the prediction model was also compared with the SST model and the ACI 352-02 expression.