In reinforced concrete (RC) structures, concrete carbonation depth is an important criterion for the deterioration of durability of RC structures. Concrete carbonation is influenced by multiple factors such as chloride attack, crack, concrete compressive strength, etc. However, due to its complex mechanism, most previous studies considered only one or two deterioration factors to estimate the concrete carbonation depth. In this study, therefore, inspection data were collected from 8 buildings, and the Adaptive Neuro-Fuzzy Inference System (ANFIS) algorithm that estimates the concrete carbonation depth of RC structures has been proposed. The proposed ANFIS model provided good estimations on the carbonation depths.

Concrete indicates highly alkaline through hydration reaction of mortars that were attached to the RCA's surface. In this study, the carbonation of concrete incorporating coated RCA was investigated through accelerated carbonation test. As a results, coated RCA was indicated to be better than normal RCA.

Based on the study of chloride migration coefficient and hydration heat evolution, it was found that the use of ternary blended cement was effective to achieve desired service life and minimum crack index. On the other hand, a high level of compressive strength is required for marine concrete mix design.