Proceedings of the
The 33rd European Safety and Reliability Conference (ESREL 2023)
3 – 8 September 2023, Southampton, UK
Task Analysis and Human Error Identification to Improve the Liquid Hydrogen Bunkering Process in the Maritime Sector
1Department of Mechanical and Industrial Engineering, NTNU, Norway.
2Department of Civil, Chemical, Environmental and Materials Engineering, University of Bologna, Italy /EADDRESS/
ABSTRACT
Recently, international concern around global warming issue is growing rapidly. Authorities and organizations are implementing strategic tasks towards climate change effects mitigation in different economic areas. Among the various energy solutions, hydrogen has been recognized as a valid alternative to pursue ambitious climate policies. However, hydrogen energy sector is considered as an emerging one. Therefore, the risks that it may pose against specific targets may not be negligible. In the context of maritime shipping, liquid hydrogen (LH2) adoption is a challenging topic since the little is known stems from a parallelism with the well-established use of liquified natural gas (LNG). The unexplored risks and lack of operational experience associated with such infrastructures entail the need to investigate the LH2 value chain, focusing on the bunkering unit, given its crucial role in determining the feasibility of the designed system. In this regard, Human Reliability Analysis (HRA) has been applied to the ship-to-ship bunkering configuration with the aim of identifying the most critical stages of the bunkering process and analyzing how the human contribution affects the operations. The findings show that the transfer unit proved to be the most time significant and human failures led to three main consequences: RPT, icing and operational delay. This work will contribute to lay the foundations for a safe and efficient implementation of H2 technologies in the maritime sector.
Keywords: Liquid hydrogen, Energy transition, Bunkering, Maritime sector, Emerging risk, Human reliability analysis, Task analysis, Human error identification.