Heat Transfer Correlation for Supercritical Carbon Dioxide Flowing in Vertical Bare Tubes

Abstract

Canada among many other countries is in pursuit of developing next generation (Generation IV) nuclear-reactor concepts. One of the main objectives of Generation-IV concepts is to achieve high thermal efficiencies (45–50%). It has been proposed to make use of SuperCritical Fluids (SCFs) as the heat-transfer medium in such Gen IV reactor design concepts such as SuperCritical Water-cooled Reactor (SCWR). An important aspect towards development of SCF applications in novel Gen IV Nuclear Power Plant (NPP) designs is to understand the thermodynamic behavior and prediction of Heat Transfer Coefficients (HTCs) at supercritical (SC) conditions. To calculate forced convection HTCs for simple geometries, a number of empirical 1-D correlations have been proposed using dimensional analysis. These 1-D HTC correlations are developed by applying data-fitting techniques to a model equation with dimensionless terms and can be used for rudimentary calculations. Using similar statistical techniques three correlations were proposed by Gupta et al. [1] for Heat Transfer (HT) in SCCO2. These SCCO2 correlations were developed at the University of Ontario Institute of Technology (Canada) by using a large set of experimental SCCO2 data (∼4,000 data-points) obtained at the Chalk River Laboratories (CRL) AECL. These correlations predict HTC values with an accuracy of ±30% and wall temperatures with an accuracy of ±20% for the analyzed dataset. Since these correlations were developed using data from a single source - CRL (AECL), they can be limited in their range of applicability. To investigate the tangible applicability of these SCCO2 correlations it was imperative to perform a thorough error analysis by checking their results against a set of independent SCCO2 tube data. In this paper SCCO2 data are compiled from various sources and within various experimental flow conditions. HTC and wall-temperature values for these data points are calculated using updated correlations presented in [1] and compared to the experimental values. Error analysis is then shown for these datasets to obtain a sense of the applicability of these updated SCCO2 correlations.