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Title |
Estimation of Concrete Durability Subjected to Freeze-Thaw Based on Artificial Neural Network
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Authors |
할리오나(Khaliunaa Darkhanbat) ; 허인욱(Inwook Heo) ; 최승호(Seung-Ho Choi) ; 김강수(Kang Su Kim) |
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DOI |
https://doi.org/10.11112/jksmi.2023.27.6.144 |
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Keywords |
콘크리트; 동결융해; 저항성능; 인공신경망; 상대동탄성계수 Concrete; Freeze-thaw; Resistance; Artificial neural network (ANN); Relative dynamic modulus of elasticity(RDME) |
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Abstract |
In this study, a database was established by collecting experimental results on various concrete mixtures subjected to freeze-thaw cycles, based on which an artificial neural network-based prediction model was developed to estimate durability resistance of concrete. A regression analysis was also conducted to derive an equation for estimating relative dynamic modulus of elasticity subjected to freeze-thaw loads. The error rate and coefficient of determination of the proposed artificial neural network model were approximately 11% and 0.72, respectively, and the regression equation also provided very similar accuracy. Thus, it is considered that the proposed artificial neural network model and regression equation can be used for estimating relative dynamic modulus of elasticity for various concrete mixtures subjected to freeze-thaw loads.
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