Critical heat flux for flow boiling with saturated two-phase inlet in microgravity onboard the International Space Station

This study examines data collected as part of the "Flow Boiling and Condensation Experiment" (FBCE), which collected microgravity flow boiling data onboard the International Space Station (ISS) between February 2022 and July 2022. This study focusses on detailed analysis of critical heat flux (CHF) data for microgravity flow boiling experiments with two-phase mixture inlet, which is unavailable in the literature. n-Perfluorohexane is used in a rectangular channel with a heated length of 114.6 mm, heated width of 2.5 mm, and adiabatic height of 5.0 mm with either single- or double-sided heating. The database covers parametric ranges never before studied in long term microgravity: mass velocity of 249.8 - 1999.9 kg/m2s, 2 s, inlet thermodynamic equilibrium quality of 0.02 - 0.86, and inlet pressure of 120.4 - 200.4 kPa. Image sequences recorded surrounding CHF reveal the periodic passing of a relatively high concentration of liquid, termed high-density fronts, plays a key role in rewetting the wall and facilitating boiling. Trends show CHF is weakly affected by inlet pressure and mass velocity at high mass velocity, and, at low mass velocity, strongly affected by both inlet quality and mass velocity. Upon comparing the new microgravity CHF data with prior Earth-gravity vertical-upflow CHF data, the relatively weak influence of gravity on CHF during flow boiling with two-phase inlet, contrary to subcooled inlet, is established. Intricate observations of flow features suggest a wavy liquid-vapor interface with a central vapor core and boiling within the liquid sub-layer is the primary mechanism of CHF, and the Interfacial Lift-off Model for flow boiling CHF well predicts the present unique database evidenced by 29.2% mean absolute error. The predictive capability of select prior correlations for flow boiling CHF is assessed for the present operating conditions, and one previously proposed by the present authors performed the best with an overall 22.4 % mean absolute error, suggesting its applicability for this unique data.