Review of Cryogenic Pool Boiling Critical Heat Flux Databases, Assessment of Models and Correlations, and Development of New Universal Correlation
Despite worldwide interest in a number of applications involving cryogenic fluids that are crucial to future space exploration, there is presently a lack of a large, reliable cryogenic pool boiling critical heat flux (CHF) database that can be used for assessment of accuracy of available predictive tools - model and correlations – or development of new tools. This shortcoming is a primary motivation for the present study, prompting compilation of a new consolidated cryogenic pool boiling CHF database from world literature. The database is used to assess accuracy of previous models and correlations, which are segregated according to ability to predict key operating parameters, such as pressure, surface orientation, and subcooling. A new correlation is constructed which shows very good predictive accuracy, evidenced by a mean absolute error of 16.95%, based on Earth gravity data which comprise a large fraction of the consolidated database. Using a limited subset of datapoints for three cryogens and a reduced gravity range of 0 to 0.7466, the new correlation is further modified with a reduced gravity multiplier to tackle reduced gravity conditions. The modified correlation has a mean absolute error of 17.47%, slightly higher than for Earth gravity alone. Overall, the new correlations are proven far more accurate than all prior models and correlations and therefore constitute new powerful tools for design of cryogenic space systems. It is shown CHF is very sensitive to pressure, increasing with increasing pressure up to maximum before decreasing appreciably toward critical pressure. CHF is also shown to be strongly influenced by surface orientation, being highest for horizontal surfaces and decreasing monotonically with increasing orientation angle, and increasing fairly linearly with increased subcooling.
Additionally, CHF models and correlations are assessed using amassed quenching CHF data that showed overpredictions of data. A new correlation is formulated which includes the effects of surface material and heater thickness to achieve high predictive accuracy for complied quenching CHF database. The new correlation has a mean absolute error and root mean square error of 10.79% and 16.12%, respectively, based on a compiled database. Analysis of complied quenching data showed that CHF is sensitive to the surface material, increasing with increasing thermal conductivity but, the influence of surface material becomes weak with increasing thermal conductivity. CHF is also strongly influenced by heater thickness, increasing with increased heater thickness till it reaches the asymptotic thickness.