Post-fire performance of steel reinforced concrete columns with different steel sections. Issue 16 (December 2021)

• Record Type: Journal Article
• Authors: Hassani, Meisam; Safi, Mohammad; Rasti Ardakani, Reza; Saedi Daryan, Amir
• Is Part Of: Advances in structural engineering. Volume 24:Issue 16(2021)
• Page Start: 3724
• Page End: 3738
• Publication Date: 2021-12
• Subjects: Steel reinforced concrete columns -- compressive strength -- post-fire performance -- axial deformation -- gene expression programming -- experimental study; Structural engineering -- Periodicals; Construction, Technique de la; Structural engineering; Periodicals; 624.1
• DOI: 10.1177/13694332211036958
• Languages: English
• ISSNs: 1369-4332

Abstract

This study investigates the post-fire performance of steel reinforced concrete composite (SRC) columns used in building construction using experimental compression tests. Four conventional steel sections as I-shaped, Cross, Box, and Plus were considered as the steel core. For fire loading, all fabricated columns were subjected to five target temperatures, including 25°, 250°, 500°, 700°, and 900°C, and then the cooling phase of the columns was done under natural conditions. Then using pressure jacks, the compressive behavior including strength and axial deformation of each of them was measured, and force-deformation curves were plotted and investigated for each SRC column. The results of these tests showed that the compressive strength and the elasticity modulus of the columns decrease at higher temperatures. Also, the effect of the steel core was examined on the compressive strength. Among the tested sections, SRC columns with the Box-steel core showed a more recovery in its compressive strength and elasticity modulus, and hence, its performance was better than SRC columns with the other steel cores. Moreover, SRC columns with the Plus-steel core indicated the weakest compressive strength and elasticity modulus. Finally, some equations were proposed for the prediction of the compressive strength and elasticity modulus of SRC columns at different temperatures by applying gene expression programming (GEP modeling) to the results.