Assessment and modeling of the debonding failure of fabric-reinforced cementitious matrix (FRCM) systems

This paper aims at developing a model that is capable to accurately predict the debonding strains in reinforced concrete (RC) members strengthened with fabric-reinforced cementitious matrix (FRCM) systems. A large database consisting of 393 shear bond specimens strengthened with Polyparaphenylene Benzobisoxazole (PBO), Carbon (C), Glass (G), and Steel (S) FRCM systems was firstly compiled from the published literature. A sensitivity analysis was carried out to identify the key parameters that most affected the debonding mechanism in FRCM. The notable influence of the compressive and tensile strengths of the concrete substrate, the compressive strength of FRCM mortar, and the axial stiffness of FRCM system on the debonding strains in FRCM systems was evidenced. Contrarily, the tensile strength of FRCM mortars showed slight or no impact on the FRCM debonding strains. Based on the results of the sensitivity analysis, three simple models were developed using a multivariate nonlinear regression analysis. The models were then optimized and validated against the experimental results of 41 flexural members strengthened with different types of FRCM systems. Two of the three models proved an excellent prediction performance of the debonding strains with an average predicted-to-experimental strain ratios, epsilon(pred)/epsilon(exp), of 0.99 +/- 0.27 and 1.02 +/- 0.27 with coefficients of variation (COV) of 0.28 and 0.26, respectively. Both models could safely predict the debonding strains in FRCMstrengthened members regardless of the type of FRCM system used. Neglecting the tensile strength of the concrete substrate in the third model resulted in an average epsilon(pred)/epsilon(exp) ratio of 0.85 +/- 0.37 with a COV of 0.44.

Automated summary

This paper developed a model to predict debonding strains in reinforced concrete members strengthened with fabric-reinforced cementitious matrix systems. The study identified key parameters affecting debonding mechanisms and developed three models using nonlinear regression analysis to accurately predict debonding strains. Two of the models demonstrated excellent prediction performance, while neglecting the tensile strength of the concrete substrate in the third model resulted in a lower prediction accuracy.