Correlation for Predicting Two-Phase Flow Boiling Heat Transfer Coefficients for Refrigerant HFO-1234yf

2018-01-0055

04/03/2018

Features
Event
WCX World Congress Experience
Authors Abstract
Content
Author has developed a correlation to predict flow boiling heat transfer coefficients for refrigerant evaporating in an automotive evaporator. This is a first correlation in the open literature for HFO-1234yf to predict heat transfer coefficients for automotive evaporator. The refrigerant mass flux was varied from 500 to 1200 kg/m2.s; heat flux was varied from 2 to 6.2 kW/m2; inlet refrigerant qualities from 0 to 40% and exit qualities of about 95%. The tests were conduct at 4.4 °C and the oil circulation ratio was maintained at 3%.
Experimental data has been used with MINITAB software, Version 16.1.0 to develop this correlation. Multivariate nonlinear regression analysis has been done to develop this correlation. Experimental data along with refrigerant properties, hydraulic diameter that affects Reynolds number, Prandtl number and other appropriate variables have been used to develop this correlation. Details of the newly developed correlation have been presented in the paper. The developed correlation will be used to predict flow boiling heat transfer coefficients for HFO-1234yf for automotive evaporator (laminate evaporators). The following is the developed correlation for HFO-1234yf:
hexp/hl = 2.8738 (1/Xtt)0.109.
The developed correlation predicts the experimentally obtained data within ±23%. Further studies are planned to improve this correlation and to compare predictions with other correlations in the open literature; and to study the influence of amount of lubricant (%) on flow boiling heat transfer coefficients.
Meta TagsDetails
DOI
https://doi.org/10.4271/2018-01-0055
Pages
11
Citation
Mathur, G., "Correlation for Predicting Two-Phase Flow Boiling Heat Transfer Coefficients for Refrigerant HFO-1234yf," SAE Technical Paper 2018-01-0055, 2018, https://doi.org/10.4271/2018-01-0055.
Additional Details
Publisher
Published
Apr 3, 2018
Product Code
2018-01-0055
Content Type
Technical Paper
Language
English