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Computers and Concrete
  Volume 23, Number 4, April 2019 , pages 273-279
DOI: https://doi.org/10.12989/cac.2019.23.4.273
 


Prediction of bond strength between concrete and rebar under corrosion using ANN
Amir Shirkhani, Daniel Davarnia and Bahman Farahmand Azar

 
Abstract
    Corrosion of the rebar embedded in concrete has a fundamental role in the determination of life and durability of the concrete structures. Researches have demonstrated that artificial neural networks (ANNs) can effectively predict issues such as expected damage in concrete structures in marine environment caused by chloride penetration, the potential of steel embedded in concrete under the influence of chloride, the corrosion of the steel embedded in concrete and corrosion current density in steel reinforced concrete. In this study, data from different kind of concrete under the influence of chloride ion, are analyzed using the neural network and it is concluded that this method is able to predict the bond strength between the concrete and the steel reinforcement in mentioned condition with high reliability.
 
Key Words
    corrosion of steel; concrete; artificial neural networks; modelling; bond strength
 
Address
Amir Shirkhani, Daniel Davarnia and Bahman Farahmand Azar: Department of Structural Engineering, Faculty of Civil Engineering, University of Tabriz, Tabriz, Iran
 

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