A gep-based model approach for estimating thermodynamic properties of r513a refrigerant

Abstract

The changes in the politic and environmentally are highly effective in refrigerant choices. Nowadays, it is critical using environmentally friendly and energy-efficient refrigerants for a sustainable future. The R513A refrigerant provides both GWP reduction and increases energy efficiency. Accurate estimates of thermodynamic properties of refrigerant are critical when considering the changing of temperature in a small interval. Many data of thermodynamic properties of refrigerants are hard-to-reach data from literature and tables. In the present study, thermodynamic properties such as entropy, enthalpy and density modelled using gene expression programming (GEP). In this context, for R513A new refrigerant determined mathematical equations through gene expression programming. Developed mathematical models for saturation and superheated R513A refrigerant under different temperature and pressure condition compared experimental data obtained from the literature. The results have shown that the GEP model could be considered as an efficient modelling technique for the estimate data of predicting thermodynamic properties of refrigerants.