Introducing nanotechnology made a revolution in various industries such as upstream, downstream and energy industries. As a result, developing new types of nanoscale thermal cycles can develop the future of energy systems. The present work investigated a nanoscale irreversible Stirling refrigeration cycle thermodynamically in order to optimize the performance of the aforesaid cycle. In the above-mentioned cycle, an Ideal Maxwell – Boltzmann gas plays a role of a working fl uid. Ideal Maxwell – Boltzmann gas was employed for working fl uid in the cycle. Owing to the quantum limit in fl uence on the gas particles restricted in the fi nite area, the cycle no longer retains the circumstance of perfect regeneration. He 4 is chosen as working fl uid. This paper demonstrates two di ff erent plans in the process of multi-objective optimization; though, the results of each plan are assessed individually. The fi rst scenario constructed with the purpose of maximizing the ecological coe ffi cient of performance (ECOP) , the coe ffi cient of performance ( CO P ) and the dimensionless Ecological function ( ec f ). Furthermore, the second scenario planned with the purpose of maximizing the exergy e ffi ciency ( η e x ) , the coe ffi cient of performance ( CO P ) and the dimensionless Ecological function ( ec f ). All the scenarios in this paper are performed through the multi-objective evolutionary algorithms (MOEA) joined with NSGA II approach. Moreover, to determine the fi nal solution in each scenario three e ff ective decision makers are employed. Deviation of the results obtained in each scenario and each decision maker are calculated individually. Finally, the results of the suggested scenarios were compared to each other, and it reveals that when the exergy e ffi ciency achieved the maximum value, the values of COP, ECOP, and ecf also maximized.
کلید واژگان :Decision making; Stirling; refrigeration cycle; Regenerative loss ;Multi-objective optimization ;NSGA I
ارزش ریالی : 1200000 ریال
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