AN EMPIRICAL-BASED APPROACH FOR MODELING AND ASSESSMENT OF RC COLUMNS WITH PLAIN BARS

Abstract eng:
There is a growing need for numerical models simulating the non-linear behavior of Reinforced Concrete (RC) elements under seismic loads into inelastic range, and for capacity models assessing the deformation capacity of RC members, with emphasis on non-conforming existing buildings. As far as nonlinear modeling is concerned, several approaches have been proposed by different authors; among them, empirical-based macromodels for lumped plasticity modeling (e.g. Haselton et al., 2008) can represent an effective compromise between accuracy and simplicity. They have the great advantage of providing a complete characterization of the nonlinear response, accounting for all of the deformation mechanisms, and their reliability is based on the use of experimental data. They also allow evaluating error/dispersion measures of the simulated response compared to the experimental data they are based on, which can be suitably used for taking into account modeling uncertainties in seismic fragility analyses of RC frames. With regard to capacity models, different approaches have been proposed for the assessment of the deformation capacity of RC members, also for pre-normative purposes; in particular, as far as the seismic assessment of existing RC buildings is concerned, different capacity models have been developed for the ultimate deformation capacity of nonconforming elements subjected to different failure modes (e.g. Elwood and Moehle, 2005; Zhu et al., 2007). In this study, a nonlinear response macromodel is proposed for a specific type of member, i.e. RC columns with plain bars. To this end, a database of tests on RC columns with plain bars is collected from literature. The specimens have different axial load, material properties, geometry, and longitudinal and transverse reinforcement ratio. Force-displacement data are collected and processed for each specimen. The backbone of the experimental response is evaluated for each test, and predictive equations are developed for characteristics points, namely yielding, maximum strength, ultimate (conventional collapse) and zero resistance conditions, based on a statistical analysis of data.

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