NUMERICAL MODELLING OF CRYOGENIC TANK CHILLDOWN USING CHARGE-HOLD-VENT AND TANK PRESSURE CONTROL IN NO-VENT FILL OPERATION

Over the last few years, there has been a concerted effort to develop and validate models
aiding the development of cryogenic refueling technologies. This effort is focused on the goal
of one day being able to refuel and store cryogenic propellants in the low gravity environ-
ment of space. The purpose of this research is to leverage the capabilities of some of these
recently developed models to create new ones and model more phenomena related to the
space applications of cryogenics.
The modelling work presented here is focused in the areas of cryogenic tank chilldown
and tank pressure control during storage/transfer. These tools are meant to help inform
future experiments being performed at the Glenn Research Center and elsewhere.
The model focusing on cryogenic tank chilldown provides a transient approach using
the charge-hold-vent (CHV) methodology to calculate the mass and time required to chill
a tank down to a desired temperature. Building on the 1-g Universal No-Vent Fill model
developed by NASA, the model captures the flashing of pooling liquid during the rapid
de-pressurization caused during the vent stage of the chilldown process. The model is com-
pared against two different datasets and successfully predicts pressure response throughout
the process to within 22%.
The thermodynamic vent system (TVS) model has been designed to be seamlessly inte-
grated into the 1-g Universal No-Vent Fill model to predict condensation and heat transfer
provided by the TVS during a no-vent fill. The TVS coil is spatially discretized and the
axial temperature distribution solved for. The model is capable of adapting to a rapidly
lowering or rising fill level that can lower the overall heat removal provided by the TVS.
While the heat removal is of primary importance, by capturing secondary phenomena such
as two-phase pressure drop, the TVS model is also capable of informing design decisions for
future systems. The model is compared against three test cases and predicts heat removal
to within 2%.