## 5 Results and Discussion
### MT Application  
Like the LT case, the ANN model's accuracy to predict the refrigeration system's energy performance is evaluated, and the comparison results with the experimental data are presented in Figure 9. The comparison between the experimental and modelling results revealed that the accuracy of the ANN model is still acceptable, as happened with the LT circuit. Although the deviation of the predicted results from the straight line is observed, most of the points are still within the \(\pm 10\%\) error band. Therefore, the ANN model can predict the energy parameters of the supermarket refrigeration system at MT application with acceptable accuracy. The field measurement results of the supermarket refrigeration system for R404A and R449A at MT application is shown in Figure 10. The evaluation of the energy parameters as the constant middle condensing temperature of 35 \({}^{\circ}\)C revealed that the supermarket refrigeration system has comparable COP and cooling capacity. However, similar to the LT case, R449A increases the compressor discharge temperature compared to R404A. It is also important to note that the higher temperature for the system using R449A may lead to more significant heat losses from the compressor body, which should be considered when calculating its efficiency. Figure 8: ANN modelling results for (**a**) COP, (**b**) cooling capacity, and (**c**) discharge temperature of the supermarket refrigeration system at LT application. Figure 9: _Cont._Figure 10: Experimental values for (**a**) COP, (**b**) cooling capacity, and (**c**) discharge temperature of the supermarket refrigeration system at MT application. Figure 9: Validation of the (**a**) COP, (**b**) cooling capacity, and (**c**) discharge temperature at MT application. Figure 11 represents the ANN modelling results of the supermarket refrigeration system for R404A and R449A at MT application. The modelling is performed under the same operating conditions to provide a fair comparison between R404A and R449A. It is predicted by the ANN model that the COP of the system using R449A is slightly higher than R404A. At the same time, the cooling capacity is similar for both refrigerants over the middle evaporating temperature range. About 5%, on average, increase in the COP of the system is predicted when the system operated with R449A compared to R404A at MT application. Like the LT application, the compressor discharge temperature for the system operated with R449A is 10 K higher than R404A, while both refrigerants operated within the safe limit recommended by the compressor manufacturer. Finally, the cooling capacity versus COP of the supermarket refrigeration system at LT and MT applications is included in Figure 12 in order to have a complete overview of the comparison. The field measurements showed that the COP of the system for the majority of the measured points varied between 1.2 and 2.4 for the LT application, and it was from 1.5 to 3.0 for the MT case. The system's cooling capacity was between 10 kW and 25 kW for the LT application, and it changed between 50 kW and 95 kW for the MT application. Figure 11: ANN modelling results for (**a**) COP, (**b**) cooling capacity, and (**c**) discharge temperature of the supermarket refrigeration system at MT application. To explain the better cooling capacity of the system at MT application, it should be noted that the displacement of the compressor used at MT was 185 m\({}^{3}\) h\({}^{-1}\). In comparison, it was 84.5 m\({}^{3}\) h\({}^{-1}\) at LT application. Usually, supermarkets have higher cooling requirements in medium (fresh food and drinks) than in low temperature, food freezing. Hence, the higher refrigerant mass flow rate caused by higher refrigerant density is the main reason for the higher cooling capacity of the supermarket refrigeration system. Then, COP is higher at MT applications because the pressure ratio is diminished. Therefore, the specific compression work is significantly reduced, and other influencing parameters such as compressor efficiency improved.