A state-of-the-art review on flow boiling at high re duce d pressures

As the state of a fluid approaches the critical point, significant changes of its thermophysical properties are noticed, which can greatly alter the observed transport behavior. In particular, notable variation in the liquid-to-vapor phase-change characteristics occur, with densities of both phases converging to the same value, the reduction of surface tension, and sudden increase of the specific heat capacity, for example. Such variations can lead to the non-satisfactory predictions of operational parameters in heat exchangers, since most of the available predicting methods were developed for synthetic refrigerants at low saturation pressures and temperatures, typical of refrigeration applications. However, it should be noted that applications that involve flow boiling at high reduced pressures are continuously growing, but experimental data at such conditions are scarce, which leads to a lack of predicting models that incorporate such data in their development. Hence, this review focus on flow boiling studies that comprise experiments at reduced pressures between 0.5 and 1 and identify gaps in the literature that are worthy of investigation. Although large discrepancies between data obtained at similar conditions by different groups were found, the rise of reduced pressure generally increases the heat transfer coefficient and decreases both pressure drop and the critical heat flux. A detailed discussion on the mechanisms responsible for the diverse trends that were observed was carried out. Finally, three extensive databases containing experimental results of pressure drop, heat transfer coefficient, and critical heat flux were raised and compared with prediction methods from the literature. Statistical analyses reveal that in general the available methods fail to predict more than 60% of the pressure drop and heat transfer coefficient databases within an error margin of 30%, while for critical heat flux some methods were able to predict more than 70% of the database within the same error margin.(c) 2022 Elsevier Ltd. All rights reserved.