Chenyu Lu

Mr. Chenyu Lu


Research Focus & Metrics

Academic Career Length

2Years (2025-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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9 June 2025 in Energies
Verified
Journal Article
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CLChenyu Lu
Chenyu Lu
JYJianfei Yang
Jianfei Yang
JYJian Yuan
Jian Yuan
LFLuoyi Feng
Luoyi Feng
WLWenbo Li
Wenbo Li
JCJing Cao
Jing Cao
The safety performance of liquid hydrogen storage has a significant influence on its large-scale commercial application. Due to the complexity and costs of experimental investigation, computational fluid dynamics (CFD) simulations have been extensively applied to investigate the dynamic behaviors of liquid hydrogen release. The involved physical and chemical models, such as models of species thermodynamic properties and liquid–gas mass transfer, play a major role for the entire CFD model performance. However, comprehensive investigations into their impacts remain insufficient. In this study, CFD models of liquid hydrogen release were developed by using two widely used commercial simulation tools, Fluent and FLACS, and validated against experimental data available in the literature. Comparisons of the model results reveal strong discrepancies in the prediction accuracy of temperature and hydrogen volume fraction between the two models. The impact of the models of thermodynamic properties and liquid–gas mass transfer on the prediction results was subsequently explored by incorporating the FLACS sub-models to Fluent and evaluating the resulting prediction differences in temperatures and hydrogen volume fractions. The results show that the models of thermodynamic properties and liquid–gas mass transfer used in FLACS underestimate the vertical rise height and the highest hydrogen volume fraction of the cloud. Sensitivity analyses on the parameters in these sub-models indicate that the specific heats of hydrogen and nitrogen, in conjunction with the mass flow rate and outflow density of the mass transfer model, have a significant influence on model prediction of temperature.