News Release

Reliability assessment method of high grade steel large diameter natural gas transmission pipelines

Peer-Reviewed Publication

KeAi Communications Co., Ltd.

OVERVIEW OF THE PROPOSED RELIABILITY ASSESSMENT METHOD

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Overview of the proposed reliability assessment method

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Credit: Jiang Changliang

With the continuous optimization of China's energy structure and the rapid expansion of natural gas consumption, high grade steel large diameter gas pipelines have become increasingly indispensable in long-distance, high-capacity natural gas transmission systems.

Recent major pipeline failures, however, have revealed the limitations of traditional safety management approaches. To that end, Changliang Jiang from the National Petroleum and Natural Gas Pipeline Network Group proposed a reliability assessment method for high-grade steel large-diameter natural gas transmission pipelines. The method considers the correlations and nonlinear coupling effects among various types of defects.

The main innovations of this method, reported in the Journal of Pipeline Science and Engineering, are as follows:

1. The reliability assessment approach integrates multi-defect coupling analysis, addressing the current gap in engineering application research. A discussion is conducted on globally recognized tensile strain capacity models for pipeline defects, with a focus on summarizing and comparing the parameter selection ranges. This study introduces an Akaike information criterion (AIC)-based automatic optimization approach for Copula function selection, enabling rational modeling of multi-defect dependency structures.

2. The method is structured into three key steps: formulation of the limit state equation, multi-defects nonlinear coupling analysis, and pipeline reliability evaluation.

First, the limit state equations for pipeline corrosion defects and girth welds with inherent defects are established. The Monte Carlo method is employed to derive the marginal probability distribution of individual defects and calculate their respective failure probabilities.

In the second stage, the marginal probability distributions of individual defects are input as basic parameters, and the AIC-based automatic optimization approach for Copula function is incorporated to characterize the correlation between defects. This enables the derivation of the joint probability distribution of defects and their combined failure probability.

The third step involves employing the second-order narrow-bound theory to compute the pipeline failure probability, considering the interactive effects of multiple defects. Ultimately, this framework completes the reliability assessment of the pipeline by integrating failure probabilities under various defect scenarios.

3. A case study on a northeastern China natural gas transmission pipeline validates the method, complemented by sensitivity analyses of defect size mean, standard deviation variations and repair sequences. Results indicate that system failure probability obtained by the proposed method lies between the results of the traditional "maximum defect method" and the "independent series method", demonstrating its capability to better reflect the actual failure risk of high grade large diameter natural gas transmission pipelines under multi-defect conditions.

Moreover, the proposed method effectively reflects realistic risk levels in pipelines with multiple defects and provides practical guidance for risk-informed maintenance prioritization.

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Contact the author: Changliang Jiang, National Petroleum and Natural Gas Pipeline Network Group Co., Ltd., Beijing, China, yuwc01@pipechina.com.cn

The publisher KeAi was established by Elsevier and China Science Publishing & Media Ltd to unfold quality research globally. In 2013, our focus shifted to open access publishing. We now proudly publish more than 200 world-class, open access, English language journals, spanning all scientific disciplines. Many of these are titles we publish in partnership with prestigious societies and academic institutions, such as the National Natural Science Foundation of China (NSFC).


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