The transition to alternative fuels in the maritime sector necessitates
innovative ship designs and refueling strategies in order to meet the European Green
Deal 2050 targets on sustainability and emissions. Liquid hydrogen (LH2), as an
energy carrier, presents a compelling option due to its high energy density per unit
mass and zero-carbon emissions potential for fuel cell applications. However, LH2
cryogenic nature (20 K boiling point), low volumetric energy density, and unique
safety concerns related to leakage and flammability, introduce significant
engineering and operational challenges. One pioneering solution for LH2-fueled
passenger vessels is a tank container swap system, subject of the study, which
enables refueling through pre-filled containerized hydrogen tanks, rather than
traditional bunkering; offering logistical advantages and flexibility, while also
raising critical safety considerations that must be assessed and properly quantified.
Recently, the Quantitative Risk Assessment (QRA) methodology has gained
significance as Classification Societies require it for alternative design processes
involving non-conventional fuel system designs. The study focuses on the
Frequency Analysis, which constitutes a key component of QRA. Hazardous
scenarios are identified, and component reliability is established according to
consolidated databases (e.g. HSE, OREDA) widely accepted for LNG systems.
Special attention is given to data consistency issues as a recognized statistical record
for LH2 equipment failure rates is still missing. An influence matrix is composed to
quantitatively evaluate the failure scenario frequencies, highlighting the most
relevant factors and enabling the design of focused mitigation strategies. The
computation provides the estimated frequency of a hydrogen release event, which,
subsequently combined with a Consequence Analysis will help define a safe
operational domain. The study contributes to the ongoing research on LH2 system
design for maritime applications, through a structured Frequency Analysis approach,
essential for effective risk assessment.
