Critical heat flux in subcooled flow boiling

The critical heat flux (CHF) phenomenon was investigated for water flow in tubes with particular emphasis on the development of methods for predicting CHF in the subcooled flow boiling regime. The Purdue University Boiling and Two-Phase Flow Laboratory (PU-BTPFL) CHF database for water flow in a uniformly heated tube was compiled from the world literature dating back to 1949 and represents the largest CHF database ever assembled with 32,544 data points from over 100 sources. The superiority of this database was proven via a detailed examination of previous databases. The PU-BTPFL CHF database is an invaluable tool for the development of CHF correlations and mechanistic models that are superior to existing ones developed with smaller, less comprehensive CHF databases. In response to the many inaccurate and inordinately complex correlations, two nondimensional, subcooled CHF correlations were formulated, containing only five adjustable constants and whose unique functional forms were determined without using a statistical analysis but rather using the parametric trends observed in less than 10% of the subcooled CHF data. The correlation based on inlet conditions (diameter, heated length, mass velocity, pressure, inlet quality) was by far the most accurate of all known subcooled CHF correlations, having mean absolute and root-mean-square (RMS) errors of 10.3% and 14.3%, respectively. The outlet (local) conditions correlation was the most accurate correlation based on local CHF conditions (diameter, mass velocity, pressure, outlet quality) and may be used with a nonuniform axial heat flux. Both correlations proved more accurate than a recent CHF look-up table commonly employed in nuclear reactor thermal hydraulic computer codes. An interfacial lift-off, subcooled CHF model was developed from a consideration of the instability of the vapor-liquid interface and the fraction of heat required for liquid-vapor conversion as opposed to that for bulk liquid heating. Severe vapor effusion in an upstream wetting front lifts the vapor-liquid interface off the surface, triggering CHF. Since the model is entirely based on physical observations, it has the potential to accurately predict CHF for other fluids and flow geometries which are beyond the conditions for which it was validated