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.

• 이형민(한양대학교 건축시스템공학과) | Lee, Hyung Min
• 이한승(한양대학교 에리카캠퍼스 건축학부) | Lee, Han Seung 교신저자