Human Error Probability Assessment for LNG Bunkering Based on Fuzzy Bayesian Network-CREAM Model

Liquified natural gas (LNG) as a marine fuel has gained momentum the maritime industry moves towards sustainable future. Since unwanted LNG release may lead to severe consequences, performing quantitative risk assessment (QRA) for bunkering operations become mandatory according some regulations. Human error is main contributor risks, and human probabilities (HEPs) are essential inclusion in QRA. However, HEPs data unavailable so far. Therefore, this study attempts infer through on-site safety philosophical factors (SPFs). The cognitive reliability analysis method (CREAM) was adopted basic model modified make it suitable HEP bunkering. Nine common performance condition (CPC) indicators were identified based on fuzzy ranking of 23 SPF (SPFIs). A Bayesian network (BN) built simulate occurrence different contextual control modes (COCOMs), conditional probability table (CPT) COCOM node with 19,683 possible combinations BN developed CREAM’s matrix. prior CPCs evaluated using set theory (FST) acquired from an online questionnaire survey. results showed that 0.009841. This value can be updated re-evaluation SPFIs specific project capture dynamics HEP. innovation work realizing efficient quantification by proposed BN-CREAM model.