4.3 Article

Failure probability assessment of gas transmission pipelines based on historical failure-related data and modification factors

Journal

JOURNAL OF NATURAL GAS SCIENCE AND ENGINEERING
Volume 52, Issue -, Pages 356-366

Publisher

ELSEVIER SCI LTD
DOI: 10.1016/j.jngse.2018.01.049

Keywords

Pipeline; Risk assessment; Failure probability; Qualitative analysis; Statistical data

Funding

  1. National Science & Technology Support Program of China [2015BAK16B02]
  2. National Key Research and Development Program of China (Grant NEB) [2016YFC0802105]

Ask authors/readers for more resources

Evaluation of failure probability is one of the core contents of quantitative risk assessment. An assessment model of gas transmission pipelines failure probability based on historical failure-related data and modification factors is established, which combines a quantitative part to integrate available historical failure-related data, with a qualitative analysis to compensate for a potential lack of precise crisp statistical data. The main idea is to use the modification factors to modify the baseline failure frequency. The baseline failure frequency is estimated from the statistical historical failure-related data. The modification factors are calculated from the segment attributes of the target pipeline using algorithms developed from the analysis of statistical data and analytical models supplemented by pipeline evaluation criteria and expert judgment. The constructed model is applied to a long-distance gas transmission pipeline so that the effectiveness of the proposed model could be demonstrated. The prospect is for more efficient risk management by acting both on historical failure-related data and modification factors of gas transmission pipeline systems.

Authors

I am an author on this paper
Click your name to claim this paper and add it to your profile.

Reviews

Primary Rating

4.3
Not enough ratings

Secondary Ratings

Novelty
-
Significance
-
Scientific rigor
-
Rate this paper

Recommended

No Data Available
No Data Available