Bonding behavior and prediction of helically ribbed CFRP bar embedded in ultra high-performance concrete (UHPC)

Sun Jae Yoo, Se Hee Hong, Young Soo Yoon

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

Abstract

In this study, pull-out tests were carried out to evaluate the bond strength of helically ribbed carbon fiber reinforced polymer (CFRP) bars embedded in ultra-high-performance concrete (UHPC). For this purpose, different parameter such as bar profile, embedment length and diameter of the CFRP bar were investigated and the bond strength of ribbed CFRP bar to UHPC were compared with that of the normal strength concrete (NC) and high strength concrete (HC). Also, the failure modes and bonding characteristics of CFRP bar to concrete were presented with combination of the compressive strength of concrete with different cover thickness. The critical cover thickness of concrete for normal strength concrete (NC) and high strength concrete (HC) to prevent splitting failure is 2.5db and 3.5db respectively, and the bond strength of helically ribbed CFRP bar to UHPC is continuously increased as the cover thickness of concrete increased. The bond strength of helically ribbed CFRP bar continued to increase with increasing compressive strength of concrete, and the bond strength of the helically ribbed CFRP bar is more than two times that of the sand coated CFRP bar. In addition, bond strength increased with increasing embedment length (less than 4db of embedded length) and diameter of the CFRP bar. Finally, the experimental results were compared with the bond design codes and the proposed formula, and the modified formula of bond equations with helically ribbed and sand coated were presented and improved the accuracy of the prediction with artificial neural network (ANN).

Original languageEnglish
Article numbere02253
JournalCase Studies in Construction Materials
Volume19
DOIs
Publication statusPublished - 2023 Dec

Bibliographical note

Funding Information:
This work is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant RS-2021-KA163381 ).

Publisher Copyright:
© 2023

Keywords

  • Artificial neural network
  • Bond prediction
  • CFRP bar
  • Critical cover thickness
  • Pull-out test
  • UHPC

ASJC Scopus subject areas

  • Materials Science (miscellaneous)

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