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Journals / International Journal of Intelligent Systems and Applications in Engineering / 2018 / Cilt: 6 - Sayı: 2

Crow Search based Multi-objective Optimization of Irreversible Air Refrigerators

OĞUZ EMRAH TURGUT
Pages
103–112
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

Widely known decision-making theorems of LINMAP, TOPSIS, and Shannon’s entropy theorem have been applied on the Pareto curve constructed by the non-dominated solutions to decide the most favorable solution on the frontier.

📌 3 Key Takeaways

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Objective & Hypothesis:This study proposes the optimum performance of the irreversible air refrigerators through recently developed metaheuristic algorithm called Crow search algorithm by means of finite time thermodynamics.
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Key Findings & Data:Handful of objectives for assessing the performance of the irreversible air refrigerators such as coefficient of performance (COP), exergetic efficiency (ηII) , ecological coefficient of performance (ECOP), thermos economic optimization (F), and thermos ecologic optimization functions (ECF) have been successfully applied on the system.
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Conclusion & Impact:Widely known decision-making theorems of LINMAP, TOPSIS, and Shannon’s entropy theorem have been applied on the Pareto curve constructed by the non-dominated solutions to decide the most favorable solution on the frontier.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Özet

This study proposes the optimum performance of the irreversible air refrigerators through recently developed metaheuristic algorithm called Crow search algorithm by means of finite time thermodynamics. Finite time thermodynamics is based on choosing the optimum pathways for any kind of thermodynamic system in order to reach the maximum efficiency of the thermodynamic cycle. Handful of objectives for assessing the performance of the irreversible air refrigerators such as coefficient of performance (COP), exergetic efficiency (ηII) , ecological coefficient of performance (ECOP), thermos economic optimization (F), and thermos ecologic optimization functions (ECF) have been successfully applied on the system. Three optimization scenarios have been studied for the multi objective optimization of irreversible air refrigerators. First scenario evaluates the concurrent optimization of objectives including exergetic efficiency (ηII), coefficient of performance (COP), and ecological coefficient of performance (ECOP). In second scenario, coefficient of performance (COP), thermos economic parameter (F), and thermos ecological coefficient of performance (ECOP) have been simultaneously maximized to retain optimum working point of the cycle. Third case studies the simultaneous optimization of the imposed objectives such as second law efficiency (ηII), coefficient of performance (COP), and thermos ecological function (ECF). Widely known decision-making theorems of LINMAP, TOPSIS, and Shannon’s entropy theorem have been applied on the Pareto curve constructed by the non-dominated solutions to decide the most favorable solution on the frontier.

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Cite This Article

TURGUT, O. E. (2018). Crow Search based Multi-objective Optimization of Irreversible Air Refrigerators. International Journal of Intelligent Systems and Applications in Engineering, Cilt: 6 - Sayı: 2, 103–112. https://ajindex.com/articles/167202

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References (1)

  1. B. Andersen, P. Salamon R.S. Berry, “Thermodynamics in finite time,” Phys. Today, vol. 9, pp. 62 – 70, 1984. [3] A. thermal systems based on finite time thermodynamics and thermoeconomics Durmayaz, O.S. Sogut, B. Sahin, H. Yavuz, “Optimization of,” Prog. Energy Combust. Sci., vol.30, pp.175- 217, 2004. [4] I., Chen, C. Wu, F. Sun, “Finite time thermodynamic optimization of entropy generation minimization of energy systems,” J. Non- Equilib. Thermodyn., vol. 24, pp.327 – 359, 1999. [5] C. Wu, “Heat exchanger effect on a gas refrigeration cycle,” Energy Convers. Manage, vol. 37, pp.1513 – 1516, 1996. [6] L., Chen, C. Wu, F. Sun, “Cooling load versus COP characteristics for an irreversible air refrigeration cycle,” Energy Convers. Manage, vol. 39, pp.117 – 125. 1998. [7] S., Zhou, L., Chen, F. Sun, C. Wu, “Cooling load density analysis and optimization for an endoreversible air refrigerator,” Open Syst. Inf. Dyn. vol. 8, pp.147 – 155. 2001. [8] J. Luo, L. Chen, F. Sun, C. Wu, “Optimum allocation of heat exchanger inventory of irreversible air refrigeration cycles,” Phys. Scripta, vol.65, pp. 410 – 415. 2002. [9] Chen C.K., and Y.F. Su, “Exergetic efficiency optimization for an irreversible Brayton refrigeration cycle,” Int. J. Therm. Sci., vol. 44, pp.303 – 310, 2005. [10] Y. Tu, L. Chen, F. Sun, C. Wu, “Cooling load and coefficient of performance optimizations for real air-refrigerators,” Appl. Energy, vol. 83, pp.1289-1306, 2006. [11] Z. Yan, G. Lin, “Ecological optimization criterion for an irreversible three-heat source refrigerator,” Appl. Energy, Vol.66, pp.213 – 224, 2000. [12] J. Chen, X. Chen, C. Wu, “Ecological optimization of a multi – stage irreversible combined refrigeration system,” Energ. Convers. [13] F, Angulo – Brown. “An ecological optimization criterion for finite – term heat engines,” J. Appl. Phys., vol. 69, p.7465, 1991. [14] S. Kalaiselvam, V. Balaji, M. Veerappan, S. Iniyan, “Thermo- ecological performance optimization of two stage irreversible refrigerator,” Int. J. Exergy, vol. 6 pp. 200 – 213, 2009. [15] P.A.N. Wouagfack, R. Tchinda, “Performance optimization of three-heat-source irreversible refrigerators based on a new thermoecological criterion,” Int. J. Refrig., vol. 34, pp.1008 – 1015, 2011. [16] Y. Ust, B. Sahin, “Performance optimization of irreversible refrigerators based on a new thermo-ecological criterion,” Int. J. Refrig., vol. 30, pp.527 – 534, 2007 [17] Y. Ust, “Performance analysis and optimization of irreversibl