4.5 Article

Prediction of the mechanical performance of compressed circular CFST columns with circumferential debonding gap

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ELSEVIER SCI LTD
DOI: 10.1016/j.jcsr.2023.107988

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Concrete filled steel tube; Circumferential debonding gap; Ultimate load capacity; Reduction coefficient; Ductility; Stiffness; Evolutionary polynomial regression; Accuracy analysis

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In this paper, the experimental parameters and results of compressed circular CFST columns with circumferential debonding gap (CDG) are summarized. Detailed finite element simulation procedures based on ABAQUS are introduced and verified by test results. A database of compressed circular CFST columns with and without CDG is established, and new formulations to predict the mechanical behavior of specimens are derived using Evolutionary Polynomial Regression (EPR) methodology, demonstrating good accuracy and low complexity.
Concrete-filled steel tubular (CFST) structures have been widely used in high-rise buildings and long-span bridges for the high strength and ductility due to the confinement effect of the concrete core provided by the steel tube. This beneficial composite action could be damaged by circumferential debonding gap (CDG), which is nearly unavoidable in real CFST structures. Reliable formulations to predict the influence of CDG on the mechanical performance of compressed circular CFST columns are needed. In this paper, the experimental parameters and results of compressed circular CFST columns with CDG are summarized to discuss the deficiencies of the parameters chosen in the tests. Detailed finite element simulation procedures for compressed circular CFST columns with CDG, based on ABAQUS, are then introduced, verifying their accuracy by test results. Based on the validated finite element models, a database of compressed circular CFST columns with and without CDG, including strength, ductility and stiffness of specimens is established; it is obtained by covering suitable parameter ranges for CDG and CFST structures, in accordance with real applications. Successively, new formulations able to predict the ultimate load capacity, the reduction factor, the ductility and the stiffness of specimens are derived by the Evolutionary Polynomial Regression (EPR) methodology, demonstrating good accuracy and low complexity.

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