Impact of thermo-physical model and mixing method on the trans- and supercritical injection simulation of liquid hydrogen

The use of liquid hydrogen (LH 2 ) is anticipated to enhance the volumetric energy density in future energy and transportation systems, though it necessitates storage at extremely low temperatures. This study evaluates for the first time the impact of thermo-physical models and numerical mixing methods on the simulation of liquid hydrogen injection. The injection of cryogenic liquid hydrogen into gaseous helium at supercritical pressure was analysed, with injection temperatures set at 20 K and 30 K. Thermo-physical models based on the Helmholtz free energy were employed and compared with commonly used cubic Peng–Robinson equation of state (EoS). The results indicate that the most significant impact of the thermo-physical model is on density prediction, where the density ratio between the injected fluid and the quiescent fluid dictates the breakdown distance of the liquid hydrogen jet. Differences in the prediction of other parameters, such as heat capacity, thermal conductivity, and viscosity, showed a less significant effect due to the lack of alignment between regions with large gradients and regions with large prediction errors. Additionally, the study compared the commonly used one-fluid multi-species approach with a Volume of Fluid (VoF) approach, both utilising the same EoS. The one-fluid multi-species approach with a conservative scheme resulted in adiabatic mixing, whereas the VoF approach led to a linear temperature variation, aligning more closely with previous studies. The findings provide recommendations for the selection of thermo-physical models and mixing methods in future numerical simulations of liquid hydrogen injection. • One of the first numerical studies of liquid hydrogen injection dynamics. • Systematic quantification of the impact of thermo-physical models. • Reveal the influence of numerical mixing methods. • Suggestions for the use of thermal–physical models and mixing methods for future studies.