Computers and Concrete

  • 제23권4호
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  • Pages.273-279
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  • 2019
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  • 1598-8198(pISSN)
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  • 1598-818X(eISSN)
테크노프레스 (Techno-Press)
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DOI QR코드

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Prediction of bond strength between concrete and rebar under corrosion using ANN

  • Shirkhani, Amir (Department of Structural Engineering, Faculty of Civil Engineering, University of Tabriz) ;
  • Davarnia, Daniel (Department of Structural Engineering, Faculty of Civil Engineering, University of Tabriz) ;
  • Azar, Bahman Farahmand (Department of Structural Engineering, Faculty of Civil Engineering, University of Tabriz)
  • 투고 : 2017.11.10
  • 심사 : 2019.03.29
  • 발행 : 2019.04.25
⟨ 이전 논문 다음 논문 ⟩

초록

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.

키워드

참고문헌

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