Evaluation model for the resistance and damage characteristics of concrete subjected to freeze-thaw cycles
Khaliunaa Darkhanbat,Inwook Heo,Seung-Ho Choi,Jae Hyun Kim,Kang Su Kim
Abstract
In regions with significant temperature variations, such as during winter, concrete structures are exposed to repeated freeze-thaw cycles, which deteriorate their durability. Freeze-thaw damage manifests as internal microcracking and surface scaling, resulting not only in visible deterioration but also in a reduction in structural capacity, ultimately shortening the service life of the structure. Generally, experimental testing is essential to evaluate the freeze-thaw resistance of concrete mixtures; however, such testing requires substantial time and cost investments. Therefore, developing rapid and reliable evaluation methods that minimize the number of experiments is necessary. In this study, a database of freeze-thaw experimental results for various concrete mixtures was constructed based on previous research, and an artificial neural network (ANN)-based evaluation model was developed to assess the resistance and damage characteristics of concrete subjected to freeze-thaw cycles. Additionally, regression-based estimation equations were proposed. Validation of the proposed ANN model showed high prediction accuracy, with mean error rates of approximately 10.4% for resistance and 10.07% for damage characteristics. Furthermore, the regression-based equations showed mean error rates of approximately 10.0% and 17.04%, indicating reasonable accuracy with a simplified modeling approach. Therefore, the ANN-based model and regression equations developed in this study are expected to serve as useful tools for quantitatively evaluating and predicting the freezethaw resistance and damage characteristics of concrete under various mixture conditions.
Khaliunaa Darkhanbat — Department of Architectural Engineering, University of Seoul, Seoul, Republic of Korea
Inwook Heo — Urban Safety and Security Research Institute, University of Seoul, Seoul, Republic of Korea
Seung-Ho Choi — Department of Disaster Management and Fire Safety Engineering, University of Seoul, Seoul, Republic of Korea
Jae Hyun Kim — Department of Architectural Engineering, University of Seoul, Seoul, Republic of Korea
Kang Su Kim — Department of Architectural Engineering and the Smart City Interdisciplinary Major Program, University of Seoul, Seoul, Republic of Korea
PDF Viewer
Preview is limited to the first 3 pages. Sign in to access the full PDF.
