DOI QR코드

DOI QR Code

Dual potential capacity model for predicting failure of RC beams damaged by corrosion of tensile reinforcement

  • Sun-Jin Han (Department of Architectural Engineering, Jeonju University) ;
  • Deuckhang Lee (Department of Architectural Engineering, Chunbuk National University) ;
  • Hyo-Eun Joo (Department of Civil Engineering, The University of Tokyo) ;
  • Kang Su Kim (Department of Architectural Engineering and Smart City Interdisciplinary Major Program, University of Seoul)
  • 투고 : 2023.09.13
  • 심사 : 2024.08.02
  • 발행 : 2024.10.25

초록

This study presents an analysis model to estimate the shear strength of a reinforced concrete (RC) member with corroded tensile reinforcements. The thick-walled cylinder theory was modified to fit the dual potential capacity model to reflect interdependent failure mechanisms, including the degradation effect of bonds in corroded tensile reinforcement. In the proposed model, it is considered that the shear failure of corroded RC members with no proper anchorage detail is primarily dominated by the flexural-bond mechanism, where insufficient bond strength is provided owing to corrosion damage. However, when tensile reinforcements are properly anchored in the end regions using end hooks or mechanical devices, it is assumed that the tied-arch action can be developed as a secondary shear transfer mechanism, even under severe corrosion damage. The proposed model was verified by comparison with shear test results of corroded RC members collected from the literature, and it appeared that the proposed model can estimate their shear strengths with a good level of accuracy, regardless of various anchorage details and corrosion rates in tensile reinforcements.

키워드

과제정보

The first author would like to acknowledge that this work was supported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (No. RS-2023-00220019). The fourth author also would like to express that research was supported by the Basic Study and Interdisciplinary R&D Foundation Fund of the University of Seoul (2023).

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