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CFD Predictions of Boiling Regime Transitions during Line Chilldown validated against a 1G LN2 Experiment

Introduction Before filling a propellant tank on the ground or in Space, the transfer line between the donor and receiver tanks must be cooled down preferably by sacrificing a minimum amount of the cryogenic fluid. The cryogenic line chill-down process involves a transition between different flow boiling regimes, namely, film boiling, transition film boiling, and nucleate boiling which are complex and may be quite gravity-dependent. Capturing these boiling phenomena and predicting the transition between them in a CFD framework is new and challenging both for 1g and microgravity applications. Materials & Methods The present work addresses this challenge by employing a two-phase Eulerian approach in the context of a homogeneous fluid mixture together with the Lee phase change model to capture the film boiling regime of the chill-down process using ANSYS Fluent®. The nucleate boiling regime is predicted by incorporating an in-house developed sub-grid model that accounts for bubble nucleation, bubble growth, bubble departure diameter, and their shedding frequency. The sub-grid model is encoded and implemented into Fluent via a user-defined function for the wall-fluid heat flux calculations. The mathematical formulation and numerical implementation of the CFD model are described in detail. The coupled CFD-Subgrid model is validated against published experimental data for liquid nitrogen chill-down of a heated stainless-steel pipe in 1g. Results Numerical simulation results show good agreements between the CFD predictions of the wall temperature evolution, rewetting temperature, and transition between film and nucleate boiling, with the experimental measurements published by Darr et al [2] for several different LN2 flowrates in the vertical pipe orientation. The CFD predictions for the wall temperature distribution indicate a rapid quenching of the wall at two upstream and downstream temperature sensing locations as compared to the experimental measurement. The only tuning parameter in the CFD model is the Lee mass transfer coefficient. The CFD Model predicts the Liedenfrost rewetting temperature in close agreement with the experiment. This marks a transition between stable and transitionary flow boiling regimes. The CFD-predicted boiling curve for the downstream sensor location is also compared against its experimental counterpart and indicates that the model is able to predict all the key temperature and heat flux parameters during the transitions from stable to transitionary film boiling to nucleate boiling in close agreement with the experiment. A sequence of predicted volume fraction, and temperature contours depicting these transitions will be presented.

Evaporation Condensation↗

Results of the Second SeaWiFS Data Analysis Round Robin, March 2000 (DARR-00)

The accurate determination of upper ocean apparent optical properties (AOPs) is essential for the vicarious calibration of the Sea-viewing Wide Field-of-view Sensor (SeaWiFS) instrument and the validation of the derived data products. To evaluate the importance of data analysis methods upon derived AOP values, the Second Data Analysis Round Robin (DARR-00) activity was planned during the latter half of 1999 and executed during March 2000. The focus of the study was the intercomparison of several standard AOP parameters: (1) the upwelled radiance immediately below the sea surface, L(sub u)(0(-),lambda); (2) the downward irradiance immediately below the sea surface, E(sub d)(0(-),lambda); (3) the diffuse attenuation coefficients from the upwelling radiance and the downward irradiance profiles, L(sub L)(lambda) and K(sub d)(lambda), respectively; (4) the incident solar irradiance immediately above the sea surface, E(sub d)(0(+),lambda); (5) the remote sensing reflectance, R(sub rs)(lambda); (6) the normalized water-leaving radiance, [L(sub W)(lambda)](sub N); (7) the upward irradiance immediately below the sea surface, E(sub u)(0(-)), which is used with the upwelled radiance to derive the nadir Q-factor immediately below the sea surface, Q(sub n)(0(-),lambda); and (8) ancillary parameters like the solar zenith angle, theta, and the total chlorophyll concentration, C(sub Ta), derived from the optical data through statistical algorithms. In the results reported here, different methodologies from three research groups were applied to an identical set of 40 multispectral casts in order to evaluate the degree to which differences in data analysis methods influence AOP estimation, and whether any general improvements can be made. The overall results of DARR-00 are presented in Chapter 1 and the individual methods used by the three groups and their data processors are presented in Chapters 2-4.

Hooker, Stanford B.↗

SeaWiFS technical report series. Volume 26: Results of the SeaWiFS Data Analysis Round-Robin, July 1994 (DARR-1994)

The accurate determination of upper ocean apparent optical properties (AOP's) is essential for the vicarious calibration of the sea-viewing wide field-of-view sensor (SeaWiFS) instrument and the validation of the derived data products. To evaluate the role that data analysis methods have upon values of derived AOP's, the first Data Analysis Round-Robin (DARR-94) workshop was sponsored by the SeaWiFS Project during 21-23 July, 1994. The focus of this intercomparison study was the estimation of the downwelling irradiance spectrum just beneath the sea surface, E(sub d)(0(sup -), lambda); the upwelling nadir radiance just beneath the sea surface, L(sub u)(0(sup -), lambda); and the vertical profile of the diffuse attenuation coefficient spectrum, K(sub d)(z, lambda). In the results reported here, different methodologies from four research groups were applied to an identical set of 10 spectroradiometry casts in order to evaluate the degree to which data analysis methods influence AOP estimation, and whether any general improvements can be made. The overall results of DARR-94 are presented in Chapter 1 and the individual methods of the four groups are presented in Chapters 2-5. The DARR-94 results do not show a clear winner among data analysis methods evaluated. It is apparent, however, that some degree of outlier rejection is required in order to accurately estimate L(sub u)(0(sup -), lambda) or E(sub d)(0(sup -), lambda). Furthermore, the calculation, evaluation and exploitation of confidence intervals for the AOP determinations needs to be explored. That is, the SeaWiFS calibration and validation problem should be recast in statistical terms where the in situ AOP values are statistical estimates with known confidence intervals.

Hooker, Stanford B.↗

Two-Phase Convection Heat Transfer Correlations for Liquid Hydrogen Pipe Chilldown

Recently, heat transfer correlations based on liquid nitrogen (LN2) and liquid hydrogen (LH2) pipe quenching data were developed to improve the predictive accuracy of lumped node codes like SINDA/FLUINT and the Generalized Fluid System Simulation Program (GFSSP). After implementing these correlations into both programs, updated model runs showed strong improvement in LN2 pipe chilldown modeling but only modest improvement in LH2 modeling. Due to large differences in thermal and fluid properties between the two fluids, results indicated a need to develop a separate set of LH2-only correlations to improve the accuracy of the simulations. This paper presents a new set of two-phase convection heat transfer correlations based on LH2 pipe quenching data. A correlation to predict the bulk vapor temperature was developed after analysis showed that high amounts of thermal nonequilibrium of the liquid and vapor phases occurred during film boiling of LH2. Implemented in a numerical model, the new correlations achieve a mean absolute error of 19.5 K in the predicted wall temperature when compared to recent LH2 pipe chilldown data, an improvement of 40% over recent GFSSP predictions. This correlation set can be implemented in simulations of the transient LH2 chilldown process. Such simulations are useful for predicting the chilldown time and boil-off mass of LH2 for applications such as the transfer of LH2 from a ground storage tank to the rocket vehicle propellant tank, or through a rocket engine feedline during engine startup.

critical heat flux↗