Time-variant strength capacity model for GFRP bars embedded in concrete

Glass fiber-reinforced polymer (GFRP) concrete reinforcement exhibits high strength, is lightweight, can decrease time of construction, and is corrosion resistant. However, research has shown that chemical reactions deteriorate the GFRP reinforcing bars over time, resulting in a reduced tensile capacity. This paper develops a time-variant probabilistic model to predict the tensile capacity of GFRP bars embedded in concrete. The developed model is probabilistic to properly account for the relevant sources of uncertainties, including the statistical uncertainty in the estimation of the unknown model parameters (because of the finite sample size), the model error associated with the inexact model form (e.g., a linear expression is used when the actual and unknown relations are nonlinear), and missing variables (i.e., the model only includes a subset of the variables that influence the quantity of interest.) The proposed model is based on a general diffusion model, in which water or ions penetrate the GFRP bar matrix and degrade the glass fiber-resin interface. The model indicates that GFRP reinforcement bars with larger diameters exhibit lower rates of capacity loss. The proposed probabilistic model is used to assess the probability of not meeting the tensile strength requirement based on specifications over time and can be used to assess the safety and performance of GFRP reinforced systems. Sensitivity and importance analyses are carried out to explore the effect of the parameters and random variables on the probability estimates.