화학공학소재연구정보센터
International Journal of Heat and Mass Transfer, Vol.135, 907-924, 2019
A pragmatic approach for simulating the fluid flow and heat transfer within industrial evaporator vessels
This article presents a pragmatic method for simulating the fluid flow and heat transfer in low-pressure, industrial evaporator systems. The method couples a single phase computational fluid dynamics model with an empirical correlation in order to account for the thermal effects of boiling. Due to the time-constraints often associated with industrial modelling, the method here is developed with the intention that rapid predictions of thermal and flow behaviour can be obtained to inform plant operators of the impact of changing evaporator process and operational configuration within the nuclear industry. The presented model results are compared against data obtained from an experimental rig of a scaled evaporator test section, based at Heriot-Watt University, UK. Tests operate at near-vacuum conditions (5 kPa) and experience a variety of heat transfer regimes, whereby portions of the rig are convectively heated and other regions undergo sub-cooled nucleate boiling. A mesh sensitivity study is performed in order to determine the optimal computational grid size, and demonstrate a sufficient level mesh independence, this is quantified using the GCI method. Additionally, a turbulence sensitivity study is carried out for a number of operational configurations. Finally, various boiling correlations are tested in order to determine the optimal correlation for the application here. Results in this work show that the modelling approach developed predicts temperatures in the various different regions of the rig well, also good agreement is achieved with the experimental data when using the Launder-Sharma K-Epsilon model (Launder and Sharma, 1974). In regions which were predicted to boil, it was found the Gorenflo nucleate boiling correlation (Gorenflo and Kenning, 2009) gave a good all-round approximation to the experimental temperatures. Crown Copyright (C) 2019 Published by Elsevier Ltd. All rights reserved.