A mechanistic bubble crowding model for predicting critical heat flux in subchannels of a bundle. (March 2020)

• Record Type: Journal Article
• Authors: Liu, Yang; Liu, Wei; Shan, Jianqiang; Zhang, Bo; Leung, L.K.H.
• Is Part Of: Annals of nuclear energy. Volume 137(2020)
• Publication Date: 2020-03
• Subjects: CHF -- Mechanistic model -- Bubble crowding -- Bundle; Nuclear energy -- Periodicals; Nuclear engineering -- Periodicals; 621.4805
• DOI: 10.1016/j.anucene.2019.107085
• Languages: English
• ISSNs: 0306-4549

Abstract

Highlights: A new mechanistic model has been developed for predicting CHF of a bundle. Detailed descriptions of various models of bundle effects on CHF. The application of the new model has been assessed against the bundle CHF experiment. Good prediction accuracy has been demonstrated for the new model in the application. Abstract: A mechanistic model has been developed for predicting critical heat flux (CHF) in subchannels of a bundle. It is based on the bubble crowding phenomena and takes into the account of effects of velocity distributions, turbulent mixing intensity and Prandtl mixing length on CHF in subchannels within the bundle. Several factors are introduced to represent these effects. The model has been applied together with the ATHAS subchannel code for assessing against CHF data obtained with high-pressure water through a 5 × 5 rod bundle having a uniform axial-power profile. Good agreement has been observed between predictions using this mechanistic model and experimental CHF values at operating conditions of Pressurized Water Reactors (PWRs). The average error between predicted and experimental CHF values is 0.76% (an average absolute error of 9.18%) with a standard deviation error of 11.86% for 417 data points.