Data analytics for hydrogen safety: prediction of Liquid hydrogen release characteristics

Hydrogen can be adopted as a clean alternative to hydrocarbons fuels in the marine sector. Liquid hydrogen (LH2) is an efficient solution to transport and store large amounts of hydrogen, thus it is suitable for the maritime field. Additional safety knowledge is required since this is a new application and emerging risk might arise. Recently, a series of LH2 large-scale release tests was carried out in an outdoor facility as well as in a closed room to simulate spills during a bunkering operation and inside the ship’s tank connection space, respectively. The extremely low boiling point of hydrogen (-253°C) can cause condensation or even solidification of air components, thus enrich with oxygen the flammable mixture. This can represent a safety concern in case of ignition of the flammable mixture of LH2 and solid oxygen, since it was demonstrated that the resulting fire may transition to detonation. In this study, the abovementioned LH2 release experiments were analysed by using an advanced machine learning approach. The aim of this study was to provide critical insights on the oxygen condensation and solidification during an LH2 accidental spill and to evaluate whether the hydrogen concentration within the gas cloud formed due to the LH2 evaporation would reach the lower flammability limit. In particular, a model was developed to predict the possibility and the location of the oxygen phase change and of the hydrogen concentration above the lower flammability limit depending on the operative conditions during the bunkering operation (e.g. LH2 flow rate). The model demonstrated accurate and reliable predicting capabilities. The outcomes of the model can be exploited to select effective safety barriers and adopt the most appropriate safety measures in case of liquid hydrogen leakage.