Thermal Conductivity of Low-GWP Refrigerants Modeling with Multi-Object Optimization

Abstract

In this paper, the procedure of finding the coefficients of an equation to describe the thermal conductivity of refrigerants low in global warming potential (GWP) is transformed into a multi-objective optimization problem by constructing a multi-objective mathematical model based on the Pareto approach. For the first time, the NSGAII algorithm was used to describe a thermophysical property such as thermal conductivity. The algorithm was applied to improve the performance of existing equations. Two objective functions were optimized by using the NSGAII algorithm. The average absolute relative deviation was minimized, while the coefficient of determination was maximized. After the minimization process, the optimal solution located on the Pareto frontier was chosen through a comparative analysis between ten selection methods available in the literature. The procedure generated a new set of coefficients of the studied equation that decreased its average absolute relative deviation by 0.24%, resulting in better performance over the entire database and for fluids with a high number of points. Finally, the system model was compared with existing literature models to evaluate its suitability for predicting the thermal conductivity of low-GWP refrigerants.

Keywords

• HFO
• thermal conductivity
• multi-objective optimization
• refrigerants
• NSGAII