Prediction of time to corrosion-induced concrete cracking based on fracture mechanics criteria

Ian Lau, Chun Qing Li, Guoyang Fu

Research output: Contribution to journalArticleResearchpeer-review

Abstract

A review of the literature shows that current research on corrosion-affected reinforced concrete structures focuses more on strength deterioration than on serviceability deterioration. For corrosion-induced concrete cracking, little research has been based on fracture mechanics criteria and stochastic processes. In this paper, a new methodology is proposed for predicting the time to corrosion-induced concrete cracking based on fracture mechanics criteria. A stochastic model with a nonstationary lognormal process was developed for corrosion-induced concrete cracking, and the first-passage probability method was employed to predict the time-dependent probability of its occurrence. The merit of using a nonstationary lognormal process for corrosion-induced concrete cracking is that it eliminates unrealistic negative values of the normal distribution for inherently positive values of physical parameters. It was found that the diameter of reinforcing steel D, corrosion rate icorr, and effective modulus of elasticity Eef have the most influence on the probability of corrosion-induced concrete cracking. The methodology presented in the paper can serve as a tool for structural engineers and asset managers in making decisions with regard to the serviceability of corrosion-affected concrete structures.

Original languageEnglish
Article number04019069
Number of pages8
JournalJournal of Structural Engineering
Volume145
Issue number8
DOIs
Publication statusPublished - 1 Aug 2019
Externally publishedYes

Keywords

  • Concrete cracking
  • Corrosion
  • First-passage probability
  • Stochastic process
  • Stress intensity

Cite this

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Prediction of time to corrosion-induced concrete cracking based on fracture mechanics criteria. / Lau, Ian; Li, Chun Qing; Fu, Guoyang.

In: Journal of Structural Engineering, Vol. 145, No. 8, 04019069, 01.08.2019.

Research output: Contribution to journalArticleResearchpeer-review

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