Performance Assessment of Safety Barriers in Liquid Hydrogen Bunkering Operations Using Bayesian Network

Abstract Liquid hydrogen (LH2) has gathered interest as an eco-friendly energy carrier for marine transportation, avoiding carbon emissions and supporting sustainable shipping. However, LH2 intrinsic flammable characteristics pose safety concerns towards people and assets. Ensuring the effectiveness of safety barriers is paramount in preventing accidents and mitigating risks associated with LH2 bunkering operations. In this regard, among several quantitative performance assessment methods, Bayesian Networks (BNs) gained momentum, offering a statistical approach able to account for multifaceted safety factors. This paper evaluates safety barriers’ performance by translating Event Tree-Fault Tree diagrams into BNs. BNs incorporate root nodes representing basic events leading to the failure of the safety barriers, assigning failure probabilities from technical literature and Human Reliability Analysis approaches. Conditional Probability Tables quantify dependencies, mapping safety barrier interconnections. A case study on ship-to-ship bunkering affected by a LH2 release is considered to illustrate the application of BNs in the context of safety barriers performance assessment. Findings highlight BNs’ utility in assessing safety barrier performance, providing a tool for regulatory agencies, industry stakeholders, and safety experts to inform LH2 bunkering best practices. This aligns with advancing environmentally responsible LH2 maritime transportation while enhancing safety measures.