A model for time-to-cracking of concrete due to chloride induced corrosion using artificial neural network

14th International Conference on Concrete Engineering and Technology

Concha, N.^1,2 ; Oreta, A.W.^1

Civil Engineering Department, De la Salle University, Manila, Philippines^1

Civil Engineering Department, FEU Institute of Technology, Manila, Philippines^2

关键词: Chloride induced corrosion;    Concrete cracking;    Corrosion products;    Cracking of concrete;    Durability design;    Neural network model;    Performance based;    Reinforcement corrosion;   

Others  :  https://iopscience.iop.org/article/10.1088/1757-899X/431/7/072009/pdf
DOI  :  10.1088/1757-899X/431/7/072009

来源: IOP

【 摘 要 】

To monitor the initiation of concrete cracking beyond the service life of the structure, a novel prediction model of time to cracking of concrete cover using artificial neural network (ANN) was developed in this study. Crack mitigation prevents corrosion and crack development to occur in a more rapid phase that is an essential component in performance-based durability design of reinforced concrete structures. Data available in various literatures were used in the development of the ANN model which is a function of compressive strength, tensile strength, concrete cover, rebar diameter, and current density. The neural network model was able to provide reasonable results in time predictions of cracking of concrete protective cover due to formations of corrosion products. The performance of ANN model was also compared to various analytical and empirical models and was found to provide better prediction results. Even with limitations in the available training data, the ANN model performed well in simulating cracking of concrete due to reinforcement corrosion.