NUMERICAL PREDICTION OF FLOW AND HEAT TRANSFER IN SUPERCRITICAL FLUIDS

Enhancing the thermal physical properties of coolants can be achieved by multiple means. One of the easiest ways is to compress and heat the fluid above the critical point to the supercritical state. Supercritical fluids have the potential to be ideal coolants. For that reason, many Gen-IV reactor designs are considering using supercritical fluids as coolants and working fluids. However, surpassing the critical point introduces complexities in predicting the thermodynamic behavior of these fluids. This has crippled the widespread implementation of supercritical fluids in thermal-sensitive applications like nuclear reactors. Extensive experimental studies have been conducted to understand the complex heat transfer behavior of supercritical fluids and more importantly to unravel the mystery behind the deterioration and enhancement phenomena. These studies serve as a reference to assess the available Computational Fluid Dynamics (CFD) based turbulence models. The current work aims to assess the newly developed advanced Reynolds-Averaged Navier-Stokes (RANS) models for predicting the heat transfer of supercritical fluids. In particular, the prediction capabilities of different advanced Algebraic Heat Flux Models, namely: AHFM-UniPi and AHFM-SC, are tested for two flow conditions within a circular tube. In addition, a sensitivity analysis of the AHFM-SC coefficients is presented, and a new set of coefficients is proposed.