Abstract
The formation and development of a dataset for pipeline systems have affected the management and decision-making of pipeline operators. The dataset, combined with a proposed theoretical analysis method, can provide significant improvement for the safe and economic operation of pipelines. On the basis of the pipeline data and its essential impact on pipeline risk assessment, the authors propose for the first time the Staged Bayesian failure model for girth welds of a pipeline, using the “tree-type” accident theory and Bayesian survival analysis method. This model of girth welds is consistent with the distribution of Kaplan–Meier functions and can predict the influence of different factors on the survival probability of girth welds. These new research results can lay the technical foundation for the failure analysis of pipeline girth welds.
Highlights
The rapid growth of population and economies requires increased oil and gas pipeline infrastructure
In recent years, there have been a number of ruptures and leakages of new pipeline girth welds, which have led to serious property damage, environmental pollution, and even casualties [6,7]
This paper is an attempt to set up a framework method of girth-weld prediction with the Bayesian survival-analysis algorithm based on data t, “tree-type” accident-cause theory, and anti-fragile concept to avoid the method of simple data analysis or the traditional risk analysis [19,20]
Summary
The rapid growth of population and economies requires increased oil and gas pipeline infrastructure. This paper is an attempt to set up a framework method of girth-weld prediction with the Bayesian survival-analysis algorithm based on data t, “tree-type” accident-cause theory, and anti-fragile concept to avoid the method of simple data analysis or the traditional risk analysis [19,20]. This framework is aimed to improve the tools of girth-weld failure prediction to reduce accidents and prevent disasters similar to the San Bruno pipeline rupture
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