Unified strength model for FRP confined heat-damaged circular and square concrete columns. (1st March 2023)

• Record Type: Journal Article
• Authors: Shayanfar, Javad; Kafshgarkolaei, Hassan Jafarian; Barros, Joaquim A.O.; Rezazadeh, Mohammadali
• Is Part Of: Composite structures. Volume 307(2023)
• Publication Date: 2023-03-01
• Subjects: Heat-damaged concrete columns -- Peak compressive strength -- Unified model -- FRP confinement; Composite construction -- Periodicals; Composites -- Périodiques; 624.18
• DOI: 10.1016/j.compstruct.2022.116647
• Languages: English
• ISSNs: 0263-8223

Abstract

Highlights: A new predictive model is proposed to calculate peak axial strength of FRP confined heat-damaged concrete. A new methodology for reflecting the influence of thermal damage level in confinement-induced improvements is introduced. Proposed regression-based model revealed a suitable predictive performance. Abstract: Although a variety of analytically modeling approaches have been developed to simulate axial response of Fiber-Reinforced Polymer (FRP) confined concrete columns, little effort has been dedicated to the development of simple but robust predictive models for heat-damaged concrete columns with FRP confinement. This study aims to present a new unified strength model for predicting the peak compressive strength of FRP confined heat-damaged concrete with circular/square cross-section columns, applicable to both ambient and elevated temperature conditions. In order to achieve the highest level of reliability and predictive performance, a large database of experimental results available in the literature was assembled. In this model, the influences of column size, sectional non-circularity, and pre-existing thermal-induced damage in terms of confinement-induced improvements were considered in the model establishment based on regression analysis. The reliability of the developed model is demonstrated by simulating experimental counterparts and also comparing it to the predictive performance of existing strength models.