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Modeling and multi-objective optimization of an R450A vapor compression refrigeration system
KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Applied Thermodynamics and Refrigeration.ORCID iD: 0000-0003-2378-711X
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2019 (English)In: International journal of refrigeration, ISSN 0140-7007, E-ISSN 1879-2081, Vol. 100, p. 141-155Article in journal (Refereed) Published
Abstract [en]

The main objective of this work is to comprehensively investigate R450A behavior in refrigeration systems and subsequently optimize the main operating variables for the first time to reach the maximum performance. For this purpose, a hybrid multi-objective optimization model coupling response surface method and non-dominated sorted genetic algorithm II is established. The regression analysis results reveal a good agreement of experimental data samples with the quadratic polynomial models with a coefficient of determination exceeding 0.97. The optimum results for the first scenario indicate that the reduction in the motor-compressor electrical power consumption and discharge temperature is 18.39% and 53.51%, respectively, and percentage of growth in the refrigerant mass flow rate is 215.57% when the middle evaporator temperature, middle condenser temperature, superheating degree, and subcooling degree change from −14.95 °C to 8.71°C, 31.28 °C to 24.50°C, 13.12 K to 10.49 K, and 15.65 K to 15.66 K, respectively.

Place, publisher, year, edition, pages
Elsevier, 2019. Vol. 100, p. 141-155
Keywords [en]
Central composite design, Multi-objective optimization, Response surface method, Vapor compression system, Zeotropic refrigerant
National Category
Energy Engineering
Identifiers
URN: urn:nbn:se:kth:diva-246454DOI: 10.1016/j.ijrefrig.2019.01.008ISI: 000464974200017Scopus ID: 2-s2.0-85061969797OAI: oai:DiVA.org:kth-246454DiVA, id: diva2:1297215
Note

QC 20190319

Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-10-24Bibliographically approved

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Makhnatch, Pavel

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