Developing new technologies like nano-technology improves the performance of the energy industries. Consequently, emerging new groups of thermal cycles in nano-scale can revolutionize the energy systems’ future. This paper presents a thermo-dynamical study of a nano-scale irreversible Stirling engine cycle with the aim of optimizing the performance of the Stirling engine cycle. In the Stirling engine cycle the working fluid is an Ideal Maxwell-Boltzmann gas. Moreover, two different strategies are proposed for a multi-objective optimization issue, and the outcomes of each strategy are evaluated separately. The first strategy is proposed to maximize the ecological coefficient of performance (ECOP), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function (F). Furthermore, the second strategy is suggested to maximize the thermal efficiency (η), the dimensionless ecological function (ecf) and the dimensionless thermo-economic objective function (F). All the strategies in the present work are executed via a multi-objective evolutionary algorithms based on NSGA|| method. Finally, to achieve the final answer in each strategy, three well-known decision makers are executed. Lastly, deviations of the outcomes gained in each strategy and each decision maker are evaluated separately.
کلید واژگان :thermal efficiency, ecological coefficient of performance
ارزش ریالی : 600000 ریال
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