Flow boiling heat transfer of R134a and low GWP refrigerants in a horizontal micro-scale channel

• Published in: International journal of heat and mass transfer Vol. 108; pp. 2417 - 2432
• Main Authors: Sempértegui-Tapia, Daniel Felipe, Ribatski, Gherhardt
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.05.2017
• Subjects: Heat transfer coefficient; Low GWP; Micro-scale channels; R1234yf; R1234ze(E); R600a; Two-phase flow; R600a; R1234ze(E); R1234yf; Low GWP; Two-phase flow; Heat transfer coefficient; Micro-scale channels
• ISSN: 0017-9310; 1879-2189
• DOI: 10.1016/j.ijheatmasstransfer.2017.01.036

•New experimental data for flow boiling local HTC for low GWP fluids in a single microchannel.•Broad experimental database covering fluids R134a, R1234ze(E), R1234yf and R600a.•Comparison of the experimental data with predictive methods.•Updated version of the predictive method developed by the same research group. The present paper presents an investigation of the effects of the refrigerant type on the heat transfer coefficient during flow boiling inside micro-scale channels. Experimental results for R134a, R1234ze(E), R1234yf and R600a for flow boiling in a circular channel with internal diameter of 1.1mm are presented. The experimental database comprises 3409 data points covering mass velocities ranging from 200 to 800kg/m2s, heat fluxes from 15 to 145kW/m2, saturation temperatures of 31 and 41°C, and vapor qualities from 0.05 to 0.95. The experimental data were parametrically analysed and the effects of the experimental parameters (heat flux, mass velocity, saturation temperature and working fluid) identified. Subsequently, the experimental data were compared against the most quoted predictive methods from literature, including macro and micro-scale methods. Based on the broad database obtained in the present study, an updated version of the predictive method of Kanizawa et al. (2016) was proposed. The updated version provided accurate predictions of the present experimental database, predicting more than 97% and 86% of the results within error bands of ±30 and ±20%, respectively.