Optimization of vapor compression refrigeration cycle considering a binary mixture of working fluids using evolutionary algorithms

Hajabdollahi, Hassan; Shafiey Dehaj, Mohammad

doi:10.22059/ees.2021.244232

Optimization of vapor compression refrigeration cycle considering a binary mixture of working fluids using evolutionary algorithms

Document Type : Research Paper

Authors

Department of Mechanical Engineering, Vali-e-Asr University of Rafsanjan, Rafsanjan Iran

10.22059/ees.2021.244232

Abstract

The mixture of refrigerants including R32, R125, R134a, and R125 are applied in a vapor compression refrigeration cycle. Four design parameters are selected to optimize the total annual cost (TAC) and coefficient of performance (COP) in two steps. Firstly, the cycle is modeled by the mixture of R32 and R125, and secondly is done by a mixture of R134a and R125. It is revealed that COP and TAC are improved by an increase in the percent of R32. Moreover, COP and TAC are improved by an increase of R32 percentage. In the second step, the cycle has the highest COP and lowest TAC, where the pure R134a is applied, and the lowest COP is observed where the refrigerant is composed of 40% and 60% of R134a and R125, respectively. Finally, optimization is performed in the case of R410a (50% R32 and 50% R125), and the results are compared with the first step.

Keywords

References

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