Consistency considerations on a large databank and wide range heat transfer prediction for supercritical water in circular tubes

Abstract

The heat transfer coefficient (HTC) of supercritical water (SCW) shows abnormal behavior when compared with conventional fluids. This behavior is caused by steady variations of thermal–physical properties of SCW around the pseudo-critical point. A large database of heat transfer of SCW flowing in tube and rod bundles was proposed by the Karlsruhe Institute of Technology (Zhao et al., 2017). This databank contains 28,364 high quality experimental data points (nodes) for heat transfer of supercritical water flowing in tubes, covering a wide domain of flow parameters.Additional consistency checks were made in this work on the experimental data using our own developed procedure. This procedure was able to provide hints on the intrinsic reliability of the data and also error levels for almost all experimental nodes.The derived information on error levels made a high-performance methodology of data assimilation and model calibration (Cacuci and Ionescu-Bujor, 2010) subsequently accessible to this domain of experimental data. The BESTEST module (Badea et al., 2011) based on the methodology of data assimilation and model calibration (Cacuci and Ionescu-Bujor, 2010) was used in an iterative manner to optimize a new proposed correlation able to describe with good accuracy a large domain of the databank.