A mechanistic framework for the leakage risk reduction of mobile hydrogen refueling stations based on inherent safety concepts

Abstract

This study presents a mechanistic framework for assessing and mitigating hydrogen leakage risks in Mobile Hydrogen Refueling Stations (MHRS) based on inherent safety concepts. A bow-tie model is proposed to identify potential hazards, event pathways, and consequences. Subsequently, this model is mapped into Bayesian Networks (BN) to enable quantitative risk assessment. Fuzzy set theory is adopted to address the uncertainty of prior probabilities, using a Noisy-MAX model to optimize the BN conditional probabilities. To mitigate leakage risks, a dedicated inherently safer design checklist is developed to identify opportunities for incorporating inherent safety. A case study demonstrates that the leakage potentials decrease from 0.2600 to 0.1997, and the leakage consequences decrease by approximately 22%. This work presents a novel mechanism using inherent safety to reduce the hydrogen leakage risk of MHRS, which is useful for creating an inherently safer MHRS with fundamental and natural robustness against hydrogen leakage.