Prediction model of chloride diffusion in concrete considering the coupling effects of coarse aggregate and steel reinforcement exposed to marine tidal environment

Chloride-induced corrosion of steel reinforcement is one of the significant factors for the durability of the reinforced concrete structures exposed to marine environments. Reinforced concrete is a multiphase composite material composed of mortar, coarse aggregate, and rebar. The coarse aggregate and rebar can both affect the chloride diffusion characteristics of concrete. Nevertheless, the current researches related to the effects of the aforementioned two impact factors on chloride diffusion in concrete either considered the coarse aggregate only, or taken into account the steel bar separately. The coupling effects of coarse aggregate and steel reinforcement on chloride transport in concrete required to be further explored and discussed. In this paper, an in-door physical experiment for chloride diffusion in plain and reinforced concrete specimens exposed to marine tidal environment was carried out. The specimens were cast using different volume fractions of coarse aggregate and diameters of steel reinforcement. The chloride concentrations for experimental specimens were measured at various exposure times, and these measurements were adopted to further investigate the common influences of coarse aggregate volume fraction and blocking effect of rebar on chloride diffusion in concrete. Using the impact factors of coarse aggregate volume fraction f(v), the direct and indirect blocking effect coefficients of rebar alpha(v), beta(r)(Phi/c) to improve the analytical solution of Fick's second law, a prediction model of chloride diffusion in concrete considering the coupling effects of coarse aggregate and steel reinforcement was proposed. The accuracy of this proposed prediction model was validated by comparing the chloride concentrations evaluated by the prediction model with the experimental measurements. The findings are expected to be useful in realistically predicting the durability of reinforced concrete structures. (C) 2019 Elsevier Ltd. All rights reserved.