딥러닝 알고리즘을 이용한 콘크리트의 탄산화 진행 예측

Abstract

As the importance of maintenance of reinforced concrete structures spreads, interest in the durability of structures is increasing. Among them, carbonation of concrete is one of the main deterioration factors of reinforced concrete structures. For quantitative evaluation of carbonation, many researchers are predicting carbonation considering water-cement ratio and environmental requirements. In this study, we studied the parameters based on the concrete made of ordinary Portland cement in the existing experimental data. The depth of carbonation deduced from the learning is applied to the carbonation by applying the deep learning.