Flow boiling heat transfer of R134a in multi microchannels. (July 2017)

• Record Type: Journal Article
• Authors: Fayyadh, E.M.; Mahmoud, M.M.; Sefiane, K.; Karayiannis, T.G.
• Is Part Of: International journal of heat and mass transfer. Volume 110(2017)
• Page Start: 422
• Page End: 436
• Publication Date: 2017-07
• Subjects: Microchannel -- Flow boiling -- Flow patterns -- Heat transfer rates; Heat -- Transmission -- Periodicals; Mass transfer -- Periodicals; Chaleur -- Transmission -- Périodiques; Transfert de masse -- Périodiques; Electronic journals; 621.4022
• DOI: 10.1016/j.ijheatmasstransfer.2017.03.057
• Languages: English
• ISSNs: 0017-9310

Abstract

Highlights: Flow boiling patterns were observed and included bubbly, slug and annular flows. The effect of heat and mass flux on the bubble departure diameter is presented. Flow reversal in the micro channel heat sink was observed and discussed. The dependence of the heat transfer coefficient on heat and mass flux is presented. Comparison with correlations predicting the heat transfer coefficient is included. Abstract: Experiments were conducted to investigate flow boiling heat transfer of R134a in a multi microchannel heat sink. The heat sink consisted of 25 rectangular microchannels with nominal dimensions of 300 µm wide, 700 µm deep ( Dh = 420 µm) and 200 µm separating wall thickness. The heat sink was made of oxygen free copper by CNC machining and was 20 mm long and 15 mm wide. The experiments were conducted at 6.5 bar system pressure and covered a footprint area-based heat flux range 11.46–403.1 kW/m 2 and mass flux range 50–300 kg/m 2 s. A high speed camera was used to capture the flow patterns simultaneously with heat transfer measurements. Three flow patterns were observed namely bubbly, slug and wavy-annular flow when the heat flux increased gradually. The heat transfer coefficient increased with heat flux and there was no mass flux effect. Assessing existing correlations indicated that the correlations of Mahmoud and Karayiannis (2013) and Cooper (1984) predict the data very well with a mean absolute error less than 20% compared to the other correlations.