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A ROBUST MECHANISTIC APPROACH TO PREDICTION OF DEPARTURE FROM NUCLEATE BOILING

by Xingang Zhao, Koroush Shirvan, Robert K Salko Jr
Publication Type
Conference Paper
Book Title
Top Fuel 2019
Publication Date
Conference Name
Global Top Fuel 2019
Conference Location
Seattle, Washington, United States of America
Conference Sponsor
American Nuclear Society
Conference Date
-

departure from nucleate boiling (DNB) sets a regulatory limit for licensing pressurized water reactors (PWRs). Under such conditions, the heated surface is permanently blanketed by a vapor film, leading to a sharp deterioration of the heat transfer coefficient at the heater/coolant interface and an abrupt temperature rise. Unfortunately, the path for an accurate, robust prediction of DNB has been elusive due to lack of consensus on its triggering mechanism. This work reviews existing physics-driven modeling tools in the first place. An evolutionary channel-scale mechanistic model that leverages key assumptions in the relatively well-accepted mechanisms of liquid sublayer dryout and near-wall bubble crowding is then proposed. Detailed validation of the proposed model has demonstrated its improved predictive capabilities over previous data/physics-driven models with regard to an extensive DNB-specific CHF test matrix covering a wide range of flow conditions. The unique feature of the proposed model lies in its ability to predict DNB for different heater geometries (including round tube, annulus, and rod bundle), which is essential in deciphering fuel performance metrics from different facilities and reactor types. The proposed model will be further implemented in fuel performance codes to help improve modeling of transient DNB scenarios such as during a reactivity-initiated accident (RIA).