Simplified Nonlinear Simulation of Rectangular Concrete-Filled Steel Tubular Columns
Publication: Journal of Structural Engineering
Volume 147, Issue 6
Abstract
In detailed three-dimensional (3D) finite-element modeling, two-dimensional and/or 3D elements are widely used because of their high accuracy and ease of use despite the high computational cost. In contrast, simplified modeling based on fiber beam element (FBE) formulation is preferred for developing macro models to simulate structural frames due to its simplicity and computational efficiency. As for the FBE simulation of concrete-filled steel tubular (CFST) columns, its accuracy largely depends on the input steel and concrete material models, which should implicitly consider the material nonlinearity and interaction between the steel and concrete components. The authors have previously developed a FBE model for circular CFST columns, and this paper is a continuation of the previous work. In this paper, uniaxial effective stress–strain relationships are developed for the steel and concrete materials in rectangular CFST columns based on rigorous analysis of data generated from 3D finite-element modeling of stub columns. Thus, the material models have implicitly considered the effects of yielding and local buckling of the steel tube and passive confinement to the concrete. Meanwhile, the size effect is also considered in the concrete model. The accuracy of the proposed material models is verified against a database of rectangular CFST stub columns covering a wide range of material and geometric parameters. The developed material models are further used to simulate rectangular CFST slender columns and beam-columns, and a reasonably good agreement is achieved between the experimental and predicted load–deformation curves.
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Data Availability Statement
Some or all data, models, or code that support the findings of this study are available from the corresponding author upon reasonable request.
Acknowledgments
The authors are grateful for the financial support from the Australian Research Council Discovery Grant No. DP170100001.
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Received: Sep 16, 2020
Accepted: Jan 25, 2021
Published online: Mar 24, 2021
Published in print: Jun 1, 2021
Discussion open until: Aug 24, 2021
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