Stanciu, C.; Feidt, M.; Costea, M.; Stanciu, D. Optimization and Entropy Production: Application to Carnot-Like Refrigeration Machines. Entropy2018, 20, 953.
Stanciu, C.; Feidt, M.; Costea, M.; Stanciu, D. Optimization and Entropy Production: Application to Carnot-Like Refrigeration Machines. Entropy 2018, 20, 953.
Stanciu, C.; Feidt, M.; Costea, M.; Stanciu, D. Optimization and Entropy Production: Application to Carnot-Like Refrigeration Machines. Entropy2018, 20, 953.
Stanciu, C.; Feidt, M.; Costea, M.; Stanciu, D. Optimization and Entropy Production: Application to Carnot-Like Refrigeration Machines. Entropy 2018, 20, 953.
Abstract
Several optimization models of irreversible reverse cycle machines have been developed based on different optimization criteria in the literature, most of them using linear heat transfer laws at the source and sink. This raises the issue how close to actual operation conditions they are, since the heat transfer law on the phase-change processes is dependent on ΔT3. This paper addresses this issue by proposing a general model for study and optimization of thermal machines with two heat reservoirs applied to a Carnot-like refrigerator, with non-linear heat transfer laws and internal and external irreversibility. The optimization was performed using First and Second Law of Thermodynamics and Lagrange multipliers method. Thus, several constraints were imposed to the system, also different objective functions were considered, allowing finding the optimum operating conditions, as well as the limited variation ranges of the system parameters. Results show that the nature of the heat transfer laws affects the optimum values of system parameters for obtaining maximum performances and also their magnitude. Sensitivity studies with respect to system several parameters are presented. The results contribute to the understanding of the system limits in operation under different constraints and allow choosing the most convenient variables in given circumstances.
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
