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Article | Open Access

Quantifying the influence of corrosion defects on the failure prediction of natural gas pipelines using generalized extreme value distribution (GEVD) model and Copula function with a case study

College of Safety Science and Engineering, Nanjing Tech University, Nanjing 210009, China
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Abstract

Since the corrosion defects in gas pipelines have similar corrosion characteristics to the surrounding soil, the random growth of these defects may be correlated, so we can not simply treat the corrosion defects as completely correlated or independent. Therefore, this paper proposes a method that can accurately calculate the failure probability of the pipeline system considering the correlation of corrosion defects: using MATLAB software to fit the parameters of the GEV model to select an appropriate distribution model; using Monte Carlo simulation (MC), considering different correlation coefficients and quantities, the system failure probability of pipeline corrosion defects is calculated; the results show that the system failure probability of the pipeline and the correlation coefficient are basically linear; when the correlation coefficient is increasing, the pipeline is regarded as an independent. There is a large error between the calculated failure probability of the series system and the actual result; the system failure probability of the pipeline increases with the increase of the assumed number of corrosion defects. When the correlation coefficient is greater than or equal to 0.6, the system failure probability of the pipeline increases significantly. An increase and the system failure probability of the pipeline decreases significantly.

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Emergency Management Science and Technology
Article number: e002

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Cite this article:
Wang C, Zhang L, Tao G. Quantifying the influence of corrosion defects on the failure prediction of natural gas pipelines using generalized extreme value distribution (GEVD) model and Copula function with a case study. Emergency Management Science and Technology, 2024, 4: e002. https://doi.org/10.48130/emst-0024-0002

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Received: 15 November 2023
Accepted: 07 February 2024
Published: 21 March 2024
© 2024 by the author(s).

This article is an open access article distributed under Creative Commons Attribution License (CC BY 4.0), visit https://creativecommons.org/licenses/by/4.0/.