Practical equations for constitutive model of design-oriented FRP-confined concrete rectangular members
Citation
Palanci, M., & Subasi, I. (2024). Practical equations for constitutive model of design-oriented FRP-confined concrete rectangular members. Journal of Building Engineering, 92, 109676.Abstract
The strengthening with Fiber Reinforced Polymer (FRP) offers one of effective solution to increase strength, axial load and deformation capacity of reinforced concrete (RC) members. However, the use of FRP-confined models can diverge in reflecting FRP confinement behavior, and they require significant computational effort and time. Moreover, the use of these models and their impact on member responses is not studied. To address this, several design-oriented FRP-confined concrete models were utilized and compared by using axial load-moment interaction diagrams and the moment-curvature relationship. Comparisons revealed that compressive strength of FRP-confined members could increase to 2.5 times while axial strain capacity could increase 4.0 times compared to unconfined ones depending on FRP-confined model. Based on the statistical analysis of numerous analytical sections covering broad-range properties of FRP material, practical equations were developed for predicting compressive strength and strain at ultimate for the design and analysis of FRP-confined RC sections. The proposed equations were then subjected to a comparison with analytical and various experimental studies, and their impact on the moment-curvature responses was investigated. Results indicated that proposed equations were in a good agreement with analytical models by the correlation coefficient higher than 0.97. The mean residuals between proposed equations and experimental results were also found around the 10 %, showed that proposed model could capture the stress-strain behavior of FRP-confined concrete. Moment-curvature response produced by proposed model and existing FRP-confined models were also found comparable with experimental results. © 2024 Elsevier Ltd