A Probability-Based Numerical Method for Estimating Effective Diffusion Coefficient in Concrete

Abstract

Reinforced concrete is a common structural material since it is strong, durable and relatively cheap. Of the various deterioration mechanisms of reinforced concrete structures, chloride-induced corrosion of steel reinforcement is of great importance since numerous reinforced concrete structures are exposed to chloride sources. ASCE 2005 Report Card estimates a cost of $9.4 billion a year for 20 years to eliminate deficiencies of 590,750 bridges in the United States, almost half of which are reinforced concrete. A 1998 survey states that 9% of the reinforced concrete bridges in the United States are structurally deficient, primarily due to corrosion of steel reinforcement. Accurate lifetime predictions are of great use for developing efficient strategies to handle the corrosion damage. Since chloride ingress is a transport phenomenon, it is necessary to have an accurate representation of concrete at microscale to obtain adequate lifetime predictions of reinforced concrete structures.

Diffusion, convection, migration and permeation are transport mechanisms in reinforced concrete structures. Chloride ingress into concrete usually occurs by either diffusion or diffusion coupled with another transport mechanism. Diffusion is of interest to this research, since it is the most dominant chloride transport mechanism.

Our objective is to predict service life of reinforced concrete structures. We focus on the estimation of effective diffusion coefficient since it is closely related to the rate of chloride diffusion through concrete. A probability-based numerical method is developed for estimating the effective diffusion coefficient of chloride in concrete. The method has two essential steps. First, virtual concrete specimens are constructed. Each specimen is modeled as a three-phase material consisting of (i) aggregate, (ii) cement paste, and (iii) interfacial transition zones. The algorithm constructing virtual specimens places virtual aggregates at random locations. The aggregates are ellipses of random aspect ratios with noisy boundaries defined by beta translation fields. Second, properties of Ito process are used to estimate the effective diffusion coefficients in virtual specimens and the chloride concentration at arbitrary points of specimens. All numerical results are limited to 2D mortar specimens.