Assessment of Dryout Heat Flux Correlations for Particle Beds

To assess the coolability of particle bed, which is formed in reactor cavity, it is important to assess the prediction capabilities of Dryout Heat flux correlations. The existing DHF correlations (Sowa et al., Dhir-Catton (a), Dhir-Catton (b), Hardee-Nilson, Ostesen, Shires-Stevens, Lipinski, Jones et al., Dhir-Barleon, Theofanous-Saito, Henry-Fauske) for particle beds are assessed using developed DHF database. Eleven DHF correlations are chosen for assessment based on literature survey. Among them, five are based on flooding correlation, which are used for chemical engineering and others are based on conservation equations. The parameters in DHF correlations are directly substituted into correlations. Totally 202 data are classified into 6 groups based on bed thickness and particle diameter. In each group, prediction capabilities of correlations are assessed and shown by standard deviation and root mean square (RMS) error. Prediction capability of each correlation depends on the data group and none of correlations shows best prediction capability on entire groups. According to present study, even if those correlations show poor prediction capability, Lipinski correlation is best correlation considering entire groups.