Flow condensation heat transfer and pressure drop of R134a alternative refrigerants R513A and R450A in 0.95-mm diameter minichannels

•Investigated lower global warming potential R134a alternatives R450A and R513A•R513A condensation heat transfer coefficients were 2.6 – 25.6% lower than R134a•R513A condensation pressure drops were 4.5 – 14.0% lower than R134a•R450A condensation heat transfer coefficients were 2.4% higher–12% lower than R134a•R450A pressure drops were 5.0% higher to 9.5% lower than R134a Due to the Kigali amendment to the Montreal Protocol, refrigerants such as R134a are targeted for phasedown or phaseout due to their global warming potential (GWP) and lower GWP refrigerants are being considered to replace R134a. Since the condenser is typically responsible for 50% of the charge of a refrigeration system, it is vital to have a fundamental understanding of the flow condensation heat transfer performance of low GWP refrigerants such as R513A and R450A. Experimental flow condensation heat transfer coefficient data are reported for R134a, R513A, and R450A in seven parallel 0.95 mm diameter mini-channels for a range of mass fluxes (i.e., 200 – 500 kg/m2s) and qualities (i.e., 0.2 – 0.8) at a saturation temperature of 40 °C. The heat transfer coefficient uncertainties for all experiments were ± 6.3 – 21.2%, with an average of ± 9.8%. Condensation heat transfer coefficients for R134a, R513A, and R450A all increased with increasing mass flux and quality. R513A condensation heat transfer coefficients were 2.6 – 25.6% lower than R134a heat transfer coefficients and pressure drops were 4.5 – 14.0% lower than R134a pressure drops. R450A heat transfer coefficients were 2.4% higher than R134a at higher mass fluxes and qualities and up to 11.7% lower than R134a at lower mass fluxes than R134a heat transfer coefficients; R450A pressure drop were comparable to R134a pressure drop (i.e., 5.0% higher to 9.5% lower). The data were compared to three condensation correlations – Shah (2016), Kim and Mudawar (2013), and Cavallini et al. (2011); the data were predicted with mean average errors of 23.4%, 15.9%, and 23.4%, respectively.