Probabilistic modeling of hydrogen pipeline failure utilizing limited statistical data

Abstract

The estimation of failure probability is vital for managing pipeline integrity during hydrogen transportation. However, due to the lack of dedicated failure statistics for hydrogen pipelines, accurate probability assessments remain challenging despite numerous national pipeline incident databases. In this work, a quantitative method was developed for assessing hydrogen pipeline failure probabilities, even with extremely limited statistical data. Critical influencing factors and base failure probabilities of hydrogen pipelines were identified with the Pipeline and Hazardous Materials Safety Administration (PHMSA) database. A modified parameter system was proposed to explore the multi-level failure mechanisms associated with structural degradation through statistical analysis tailored to hydrogen pipelines. With integrating Bayesian inference and fuzzy logic analysis, a novel virtual expert system model was developed to employ random sampling analysis for correcting failure probabilities, thereby deriving a correction coefficient. The use of numerical cases illustrates the proposed method's effectiveness and interpretability. This work aims to support decision-making to ensure the safe remaining lifespan of hydrogen pipelines.