Technical Papers
Dec 7, 2017

Reliability-Based Service Life Prediction of Corrosion-Affected Metal Pipes with Mixed Mode Fracture

Publication: Journal of Engineering Mechanics
Volume 144, Issue 2

Abstract

This paper presents a time-dependent reliability method for the assessment of corrosion-affected metal pipe failures. Two nonlinear limit state functions are proposed for brittle and ductile pipes with mixed mode fracture. For brittle materials, a general failure criterion taking into account all three fracture modes is adopted, whereas for ductile materials, the criterion of stress intensity factor is used, based on a newly developed model of elastic fracture toughness. Stochastic models of corresponding load effects are developed and an upcrossing method is used to quantify the probability of failure and predict the remaining service life. A case study is presented to illustrate the proposed method, followed by a sensitivity analysis to investigate the effects of key variables on the probability of pipe failure. The use of Mode I fracture toughness rather than mixed-mode fracture toughness of the pipe is found to underestimate the probability of its failure. The corrosion and internal pressure have the most influence on the probability of failure for both brittle and ductile pipes, whereas pipe internal radius has the least effect. The method presented in this paper can assist pipe engineers and asset managers in developing a risk-informed and cost-effective strategy for better management of corrosion-affected metal pipelines.

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Acknowledgments

Financial support from Australian Research Council under DP140101547, LP150100413, and DP170102211 is gratefully acknowledged.

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Go to Journal of Engineering Mechanics
Journal of Engineering Mechanics
Volume 144Issue 2February 2018

History

Received: Nov 13, 2016
Accepted: Aug 3, 2017
Published online: Dec 7, 2017
Published in print: Feb 1, 2018
Discussion open until: May 7, 2018

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Authors

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Associate Professor, School of Civil Engineering and Architecture, Wuhan Univ. of Technology, Wuhan 430070, China; Lecturer, College of Engineering and Science, Victoria Univ., Melbourne, VIC 8001, Australia. E-mail: [email protected]
Research Fellow, School of Engineering, RMIT Univ., Melbourne, VIC 3000, Australia. E-mail: [email protected]
Chun-Qing Li [email protected]
Professor, School of Engineering, RMIT Univ., Melbourne, VIC 3000, Australia (corresponding author). E-mail: [email protected]

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