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Advances in Concrete Construction
  Volume 10, Number 4, October 2020, pages 289-299
DOI: https://doi.org/10.12989/acc.2020.10.4.289
 
open access

Postfire reliability analysis of axial load bearing capacity of CFRP retrofitted concrete columns
Bin Cai, Liyan Hao and Feng Fu

 
Abstract
    A reliability analysis of the axial compressive load bearing capacity of postfire reinforced concrete (RC) columns strengthened with carbon fiber reinforced polymer (CFRP) sheets was presented. A 3D finite element (FE) model was built for heat transfer analysis using software ABAQUS. Based on the temperature distribution obtained from the FE analysis, the residual axial compressive load bearing capacity of RC columns was worked out using the section method. Formulas for calculating the residual axial compressive load bearing capacity of the columns after fire exposure and the axial compressive load bearing capacity of postfire columns retrofitted with CFRP sheets were developed. Then the Monte Carlo method was used to analyze the reliability of the axial compressive load bearing capacity of the RC columns retrofitted with CFRP sheets using a code developed in MATLAB. The effects of fire exposure time, load ratio, number of CFRP layers, concrete cover thickness, and longitudinal reinforcement ratio on the reliability of the axial compressive load bearing capacity of the columns after fire were investigated. The results show that within 60 minutes of fire exposure time, the reliability index of the RC columns after retrofitting with two layers of CFRPs can meet the requirements of Chinese code GB 50068 (GB 2001) for safety level II. This method is effective and accurate for the reliability analysis of the axial load bearing capacity of postfire reinforced concrete columns retrofitted with CFRP.
 
Key Words
    CFRP; axial compressive capacity; postfire; reliability; Monte Carlo method
 
Address
Bin Cai: School of Civil Engineering, Jilin Jianzhu University, Changchun, China; School of Mathematics, Computer Science and Engineering, City, University of London, London, UK
Liyan Hao: School of Civil Engineering, Jilin Jianzhu University, Changchun, China
Feng Fu: School of Mathematics, Computer Science and Engineering, City, University of London, London, UK
 
References
    -acc1004002-
 

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