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Title: Influence of Confinement Modeling on Cyclic Response of Reinforced Concrete Columns

Author(s): S.K. Kunnath

Publication: Symposium Paper

Volume: 238


Appears on pages(s): 81-94

Keywords: analytical modeling; confined concrete; cyclic response; ductility; seismic

DOI: 10.14359/18265

Date: 10/1/2006

Concepts in ductile design have led to an increased interest in understanding the role of confinement in improving the seismic performance of reinforced concrete members. While transverse reinforcement is regarded as a form of passive confinement in RC members, the observed increase in the strength of confined concrete is typically a function of the axial strain levels. Confinement models have been developed by numerous researchers to describe the stress-strain behavior of concrete as a function of certain key parameters that are related to the amount and type of transverse reinforcement. Accurate constitutive models of confined concrete are necessary for direct use in fiber-model based discretization of RC components or for indirect use in hysteresis based phenomenological models. This paper examines the relevance and importance of accurate confinement modeling in predicting the inelastic behavior of well-confined concrete columns. In particular, the influence of incorporating confinement effects in predicting the monotonic and cyclic response of RC columns is investigated. It is analytically demonstrated that the role of the longitudinal reinforcing bars play a more significant role in determining the overall force-deformation behavior of RC components. Detailed fiber-based discretizations that rely entirely on constitutive models are incapable of reproducing post-yield softening and deterioration because of their inability to incorporate complex large deformation behavior of both the longitudinal and the confining reinforcement. Approximate phenomenological models will continue to see widespread use in inelastic analysis of RC structures until these limitations of constitutive-based element models are overcome.


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