Experimental study of ultra-high-performance fibre-reinforced concrete (UHPFRC)-encased CFST short columns under axial and eccentric compression

• Main Authors: Du, Panwei, Ma, You-Xin, Tan, Kang Hai
• Other Authors: School of Civil and Environmental Engineering
• Format: Article
• Language: English
• Published: 2024
• Subjects: Earth and Environmental Sciences; Composite column; Fibre-reinforced concrete
• Online Access: https://hdl.handle.net/10356/179024
• Institution: Nanyang Technological University

This study presents a comprehensive experimental programme and analysis of ultra-high-performance fibre-reinforced concrete (UHPFRC)-encased concrete-filled steel tube (CFST) columns subjected to axial and eccentric compression. Twelve short columns were tested, with six of them utilising UHPFRC encasement while the other six employing normal strength fibre-reinforced concrete (FRC) encasement for comparison purpose. The study focused on the effects of load eccentricity ratio, concrete encasement type, and steel tube configuration. Key findings from the test results including failure modes, load-deflection behaviour, moment-curvature relationships and curvature ductility were examined. The findings showed that UHPFRC-encased CFST columns exhibited significantly enhanced strength and bending capacity, while FRC-encased columns showed remarkable ductility. A notable shift in failure mode was observed with increasing load eccentricity ratio, transitioning from crushing of concrete to compression, and then to balanced failure. Furthermore, applicability of prevalent design codes such as EC4, AIJ, and ACI 318 in calculating the peak loads of UHPFRC- and FRC-encased CFST columns was assessed. The plastic stress distribution methods in EC4 and AIJ overestimated peak loads, while ACI 318's strain compatibility approach accurately predicted FRC-encased columns but not UHPFRC-encased columns. To address this, modifications of the parameters α and β were incorporated into the ACI design method to reflect the relative brittle nature of UHPFRC, resulting in accurate predictions.