An intuitionistic fuzzy probabilistic Petri net method for risk assessment on submarine pipeline leakage failure

Abstract

Under the influence of various factors, the submarine pipelines will be damaged, resulting in oil and gas leakage accidents. It is essential to perform risk assessments to prevent accidents. However, accurate and sufficient historical data usually can not be obtained. To solve this problem, this study proposes a probabilistic Petri net (PPN) method based on intuitionistic fuzzy evidential reasoning (IFER), which can determine the failure probability of basic events through domain expert experience, and quantitatively evaluate the probability of submarine pipeline leakage failure. The main contributes include: according to DNV-RP-F107, a group of intuitionistic fuzzy numbers is defined and an improved probability conversion method is proposed for defuzzification; an IFER approach is proposed, which uses belief structures as expert linguistic terms and transforms them into IFNs to deal with the uncertainty of expert evaluation; a probabilistic Petri net method is proposed to quantitatively calculate the failure probability of top event and identify the critical events. Finally, the proposed intuitionistic fuzzy probabilistic Petri net (IFPPN) method is illustrated by a case study. By comparing with the existing methods, the feasibility of this method is validated, and the evaluation results can provide a reference for the safe operation of the pipeline system.