Predicting fire resistance of SRC columns through gene expression programming. (9th November 2020)

• Record Type: Journal Article
• Authors: Hassani, Meisam; Safi, Mohammad; Rasti Ardakani, Reza; Saedi Daryan, Amir
• Is Part Of: Journal of structural fire engineering. Volume 12:Number 2(2021)
• Page Start: 125
• Page End: 140
• Publication Date: 2020-11-09
• Subjects: Gene expression programming -- Predictive model -- Fire resistance -- Steel-reinforced concrete columns; Fire protection engineering -- Periodicals; 628.92205
• DOI: 10.1108/JSFE-04-2020-0013
• Languages: English
• ISSNs: 2040-2317

Abstract

Abstract : Purpose: This paper aims to predict the fire resistance of steel-reinforced concrete columns by application of the genetic algorithm. Design/methodology/approach: In total, 11 effective parameters are considered including mechanical and geometrical properties of columns and loading values as input parameters and the duration of concrete resistance at elevated temperatures as the output parameter. Then, experimental data of several studies – with extensive ranges – are collected and divided into two categories. Findings: Using the first set of the data along with the gene expression programming (GEP), the fire resistance predictive model of steel-reinforced concrete (SRC) composite columns is presented. By application of the second category, evaluation and validation of the proposed model are investigated as well, and the correspondent time-temperature diagrams are derived. Originality/value: The relative error of 10% and the R coefficient of 0.9 for the predicted model are among the highlighted results of this validation. Based on the statistical errors, a fair agreement exists between the experimental data and predicted values, indicating the appropriate performance of the proposed GEP model for fire resistance prediction of SRC columns.