Data-driven and scenario-based risk and reliability assessment framework : a case study for hydrogen bunkering

This paper introduces a Data-driven and Scenario-based Risk and Reliability Assessment Framework (DS-RAF) for enhancing the safety of maritime alternative fuels and technologies. The framework combines qualitative and quantitative methods and is demonstrated through a case study on a hydrogen bunkering system across its operational lifespan. An in-house system failure database was developed to support comprehensive risk and reliability assessments. To overcome the limitations of static Failure Modes and Effects Analysis (FMEA), a dynamic FMEA (D-FMEA) was applied, incorporating time-dependent component reliability. This enabled the identification of critical components, P&ID-based design improvements, and optimized replacement intervals. Dynamic Fault Tree Analysis (D-FTA) was further employed to capture sequential and functional dependencies among failures, providing system-level reliability insights. Additionally, scenario-based reliability analysis (S-BRA) using Monte Carlo Simulation (MCS) evaluated the impact of varying failure rates under different operating conditions. Results showed that the original design of the bunkering system degraded to around 50 % reliability after 1000 h. With optimized replacement strategies identified through D-FMEA and D-FTA, the improved configuration maintained around 70 % reliability over 10,000 h. The proposed framework offers a robust, multi-layered, and data-driven approach that enhances accuracy, reduces uncertainty, and supports proactive design and maintenance strategies, advancing the safe adoption of maritime decarbonization initiatives, including hydrogen solutions.