Modeling and thermodynamic analysis of thermal performance in self-pressurized liquid hydrogen tanks

Wang, H.R.; Wang, B.; Pan, Quanjun; Wu, Yuanfang; Jiang, Lijun; Wang, Z.H.; Gan, Zhihua

doi:10.1016/j.ijhydene.2022.07.027

Cited by 21 publications

(3 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Majumdar et al [2] Finite-volume network flow analysis Self-pressurization; thermodynamic vent system (TVS). Wang et al [5] Multi-node model Effects of fluid properties, initial conditions, and heat leakage on self-pressurization.…”

Section: Modeling Methods Focus Areasmentioning

confidence: 99%

“…Experimental data for self-pressurization processes (i.e., pressure build-up in closed cryogenic space due to addition of external heat) in the MHTB tank [10] are used for the present validation study. Some of these data were also employed for validation by other researchers [5,6]. Two experiments are considered here: (1) a 50%-filled tank with heat leak of 51 W (heat coming from the ambient environment to hydrogen stored in the tank) and initial pressure of 1.116 bar, and (2) a 25%-filled tank with heat leak of 18.8 W and initial pressure of 1.221 bar.…”

Section: Validation Studymentioning

confidence: 99%

“…Al Ghafri et al [4] demonstrated a comparison of predictions of the two-element method with several experimental studies involving liquid hydrogen storage. Using a modified approach, Wang et al [5] explored effects of the vapor temperature, interfacial mass transfer, and heat leakage on the self-pressurization rate.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

The Effect of Liquid Hydrogen Tank Size on Self-Pressurization and Constant-Pressure Venting

Matveev

Leachman

2023

Hydrogen

View full text Add to dashboard Cite

Hydrogen represents a promising renewable fuel, and its broad application can lead to drastic reductions in greenhouse gas emissions. Keeping hydrogen in liquid form helps achieve high energy density, but also requires cryogenic conditions for storage as hydrogen evaporates at temperatures of about 20 K, which can lead to a large pressure build-up in the tank. This paper addresses the unsteady thermal modeling of cryogenic tanks with liquid hydrogen. Considering the liquid and vapor phases in the tank as two nodes with averaged properties, a lumped-element method of low computational cost is developed and used for simulating two regimes: self-pressurization (also known as autogenous pressurization, or pressure build-up in the closed tank due to external heat leaks) and constant-pressure venting (when some hydrogen is let out of the tank to maintain pressure at a fixed level). The model compares favorably (within several percent for pressure) to experimental observations for autogenous pressurization in a NASA liquid hydrogen tank. The two processes of interest in this study are numerically investigated in tanks of similar shapes but different sizes ranging from about 2 to 1200 m3. Pressure and temperature growth rates are characterized in closed tanks, where the interfacial mass transfer manifests initial condensation followed by more pronounced evaporation. In tanks where pressure is kept fixed by venting some hydrogen from the vapor domain of the tank, the initial venting rate significantly exceeds evaporation rate, but after a settling period, magnitudes of both rates approach each other and continue evolving at a slower pace. The largest tank demonstrates a six-times-lower pressure rise than the smallest tank over a 100 h period. The relative boil-off losses in continuously vented tanks are found to be approximately proportional to the inverse of the tank diameter, thus generally following simple Galilean scaling with a few percent deviation due to scale effects. The model developed in this work is flexible for analyzing a variety of processes in liquid hydrogen storage systems, raising efficiencies, which is critically important for a future economy based on renewable energy.

show abstract

Section: Modeling Methods Focus Areasmentioning

confidence: 99%

Section: Validation Studymentioning

confidence: 99%