BibTex Citation Data :
@article{ROTASI36687, author = {Matheus Dwinanto}, title = {Pemodelan dan Optimasi Multiobjektif Refrigerator Kompresi Uap Menggunakan Metode Meminimalkan Pembangkitan Entropi}, journal = {ROTASI}, volume = {23}, number = {2}, year = {2021}, keywords = {optimization; refrigerator; entropy generation; genetic algorithm}, abstract = { The vapor compression refrigerators have many applications for cooling and freezing. The advantage of this system has good performance, and can meet the needs of a relatively large cooling capacity with a small system size. But behind its advantages, the energy consumption of this system is high so that energy saving is the main goal of optimization and this will continue to be done in a sustainable manner in the future. In this article, thermodynamic design optimization is presented to minimization entropy generation, minimization total power input, maximization the efficiency of the second law, and maximization the performance coefficient, simultaneously. A multi-objective genetic algorithm is used during the optimization process, and based on the Pareto frontier a decision-making strategy is obtained and then used to determine the final solution. The optimization results show that the method of minimization entropy generation can experience a paradox, where minimizing the entropy generation number of the system will not automatically result in the maximum efficiency of the second law but there is an optimal point which indicates that the generation of entropy is minimum. From the results of thermodynamic design optimization of the refrigerator, the total input power is 0.281 kW, the second law efficiency is 0.311 and coefficient of performance is 2.95. }, issn = {2406-9620}, pages = {36--42} doi = {10.14710/rotasi.23.2.36-42}, url = {https://ejournal.undip.ac.id/index.php/rotasi/article/view/36687} }
Refworks Citation Data :
The vapor compression refrigerators have many applications for cooling and freezing. The advantage of this system has good performance, and can meet the needs of a relatively large cooling capacity with a small system size. But behind its advantages, the energy consumption of this system is high so that energy saving is the main goal of optimization and this will continue to be done in a sustainable manner in the future. In this article, thermodynamic design optimization is presented to minimization entropy generation, minimization total power input, maximization the efficiency of the second law, and maximization the performance coefficient, simultaneously. A multi-objective genetic algorithm is used during the optimization process, and based on the Pareto frontier a decision-making strategy is obtained and then used to determine the final solution. The optimization results show that the method of minimization entropy generation can experience a paradox, where minimizing the entropy generation number of the system will not automatically result in the maximum efficiency of the second law but there is an optimal point which indicates that the generation of entropy is minimum. From the results of thermodynamic design optimization of the refrigerator, the total input power is 0.281 kW, the second law efficiency is 0.311 and coefficient of performance is 2.95.
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