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Exergetic sustainability evaluation and multi-objective optimization of performance of an irreversible nanoscale Stirling refrigeration cycle operating with Maxwell–Boltzmann gas

Author

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  • Ahmadi, Mohammad H.
  • Ahmadi, Mohammad-Ali
  • Maleki, Akbar
  • Pourfayaz, Fathollah
  • Bidi, Mokhtar
  • Açıkkalp, Emin

Abstract

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 fluid. Ideal Maxwell–Boltzmann gas was employed for working fluid in the cycle. Owing to the quantum limit influence on the gas particles restricted in the finite area, the cycle no longer retains the circumstance of perfect regeneration. He4 is chosen as working fluid. This paper demonstrates two different plans in the process of multi-objective optimization; though, the results of each plan are assessed individually. The first scenario constructed with the purpose of maximizing the ecological coefficient of performance (ECOP), the coefficient of performance (COP) and the dimensionless Ecological function (ecf). Furthermore, the second scenario planned with the purpose of maximizing the exergy efficiency (ηex), the coefficient of performance (COP) and the dimensionless Ecological function (ecf). All the scenarios in this paper are performed through the multi-objective evolutionary algorithms (MOEA) joined with NSGA II approach. Moreover, to determine the final solution in each scenario three effective 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 efficiency achieved the maximum value, the values of COP, ECOP, and ecf also maximized.

Suggested Citation

  • Ahmadi, Mohammad H. & Ahmadi, Mohammad-Ali & Maleki, Akbar & Pourfayaz, Fathollah & Bidi, Mokhtar & Açıkkalp, Emin, 2017. "Exergetic sustainability evaluation and multi-objective optimization of performance of an irreversible nanoscale Stirling refrigeration cycle operating with Maxwell–Boltzmann gas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 80-92.
    • Handle: RePEc:eee:rensus:v:78:y:2017:i:c:p:80-92
    DOI: 10.1016/j.rser.2017.04.097
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    References listed on IDEAS

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    Cited by:

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    2. Yin, Yong & Chen, Lingen & Wu, Feng & Ge, Yanlin, 2020. "Work output and thermal efficiency of an endoreversible entangled quantum Stirling engine with one dimensional isotropic Heisenberg model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 547(C).
    3. Jin, Qinglong & Xia, Shaojun & Chen, Lingen, 2023. "A modified recompression S–CO2 Brayton cycle and its thermodynamic optimization," Energy, Elsevier, vol. 263(PE).
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    5. Wu, Haifeng & Liu, Qibin & Xie, Gengxin & Guo, Shaopeng & Zheng, Jie & Su, Bosheng, 2020. "Performance investigation of a novel hybrid combined cooling, heating and power system with solar thermochemistry in different climate zones," Energy, Elsevier, vol. 190(C).
    6. Ahmadi, Mohammad H. & Amin Nabakhteh, Mohammad & Ahmadi, Mohammad-Ali & Pourfayaz, Fathollah & Bidi, Mokhtar, 2017. "Investigation and optimization of performance of nano-scale Stirling refrigerator using working fluid as Maxwell–Boltzmann gases," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 337-350.
    7. Nie, Wenjie & Lü, Ke & Chen, Aixi & He, Jizhou & Lan, Yueheng, 2018. "Performance optimization of single and two-stage micro/nano-scaled heat pumps with internal and external irreversibilities," Applied Energy, Elsevier, vol. 232(C), pages 695-703.
    8. Mehdizadeh-Fard, Mohsen & Pourfayaz, Fathollah, 2018. "A simple method for estimating the irreversibly in heat exchanger networks," Energy, Elsevier, vol. 144(C), pages 633-646.

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