Evaluation of stress intensity factor for cast iron pipes with sharp corrosion pits

Weigang Wang, Annan Zhou, Guoyang Fu, Chun Qing Li, Dilan Robert, Mojtaba Mahmoodian

Research output: Contribution to journalArticleResearchpeer-review

17 Citations (Scopus)

Abstract

Underground pipes are essential infrastructure for water, oil and gas transport. The presence of localized pitting corrosion has been identified as one of the main deterioration mechanisms for metal pipes, which, when exposed to external loadings, can easily fail due to intensified stresses at the corrosion pit. The assessment of such an intensified stress field around the pit has been a key focus for decades since it is a major mode of pipe failures. Although stress intensity factors for structures with surface cracks have been extensively studied in literature, there is little study essentially relating the stress intensity factors of pipes with different levels of pitting corrosion. In the present study, a three-dimensional geometrical model for corrosion pits is proposed and a J-integral based finite element method is employed to derive the solutions for stress intensity factors for various pit and pipe geometries. Attempt is also made to derive formulas of maximum stress intensity factors by use of the evolutionary polynomial regression method. It has been found that the maximum stress intensity factor for corrosion pits with high aspect ratio occurs at a different position from those with low aspect ratio. It has also been found that idealization of corrosion pits as surface cracks rather than three-dimensional pits will cause an inaccurate estimate of stress intensity factors for pipes. The results of this study provide a fundamental basis for safety evaluation and life prediction of buried cast iron pipelines.

Original languageEnglish
Pages (from-to)254-269
Number of pages16
JournalEngineering Failure Analysis
Volume81
DOIs
Publication statusPublished - 1 Nov 2017
Externally publishedYes

Keywords

  • Cast iron pipes
  • Evolutionary polynomial regression
  • J-integral
  • Sharp corrosion pit
  • Stress intensity factor

Cite this