Hyun Kyu Shin1, Ha Young Kim2, Sang Hyo Lee3,*
CMC-Computers, Materials & Continua, Vol.70, No.3, pp. 5059-5071, 2022, DOI:10.32604/cmc.2022.017262
- 11 October 2021
Abstract The durability performance of reinforced concrete (RC) building structures is significantly affected by the corrosion of the steel reinforcement due to chloride penetration, thus, the chloride ion diffusion coefficient should be investigated through experiments or theoretical equations to assess the durability of an RC structure. This study aims to predict the chloride ion diffusion coefficient of concrete, a heterogeneous material. A convolutional neural network (CNN)-based regression model that learns the condition of the concrete surface through deep learning, is developed to efficiently obtain the chloride ion diffusion coefficient. For the model implementation to determine the More >
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