Abo Bibliothek: Guest

ISSN Online: 2377-424X

ISBN Print: 978-1-56700-474-8

ISBN Online: 978-1-56700-473-1

International Heat Transfer Conference 16
August, 10-15, 2018, Beijing, China

VOID FRACTION MEASUREMENTS IN GAS-LIQUID FLOW AND HOW TO USE THEM FOR PROBABILISTIC FLOW MAPS FOR EVAPORATING REFRIGERANTS.

Get access (open in a dialog) DOI: 10.1615/IHTC16.kn.000022
pages 409-423

Abstrakt

In 1998 Thome, Kattan and Favrat [1] proposed for the first time a new heat transfer model based on refrigerant flow patterns. Ten years later, the same team also proposed flow pattern based pressure drop correlations for refrigerant two-phase flow in horizontal tubes [2]. Now, flow pattern based heat transfer and pressure drop correlations are widely accepted. Almost all flow pattern based methods use the void fraction to describe geometrical gas-liquid distribution. To accurately predict heat transfer during evaporation the different flow regimes have to be accurately distinguished. The reasoning being that each flow regime has a different liquid/gas geometrical distribution. The heat transfer in the gas (convection) or in the liquid (convection and pool boiling) has a totally different heat transfer mechanism. Several flow regime maps and correlations exist for defining the different flow regimes [3]. Most of them are based on visual observations with strict discrete separation between flow regimes that are subjectively chosen. We have shown that flow pattern maps can be objectively constructed by using a void fraction probe [4]. After correct calibration this probe can be used to construct a probabilistic flow pattern map. In these maps the transition between different flow regimes is described by the likelihood of a state to be in a flow regime. In this paper, we clearly show that the transition between slug flow and intermittent flow is very sudden in function of vapor quality. On the other hand, the transition from intermittent to annular flow happens over a range of vapor qualities. Based on the insights gained from the two-phase flow characterization, suggestions were made for further improvement of the predictive models.