Prediction on the axial compression of square concrete – filled steel tubular short column considering the triangular-conner gap deffect

Abstract

This article presents research on developing a formula to determine the axial compression of square concrete – filled steel tubular (CFST) column considering the triangular – conner gap deffect by an artificial intelligence (AI) model. 120 experimental samples collected from experimental studies worldwide are the database of this study. To evaluate the impact of the compression resistance of this type of column, the parameters are analyzed based on the Qlatice regression method. Compared to experimental data, the AI model illustrated the reliability tool when compared with experimental results.