Exergy analysis of an ejector-absorption heat transformer using artificial neural network approach

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dc.contributor.authorSözen, Adnan
dc.contributor.authorArcaklioğlu, Erol
dc.date.accessioned2020-06-25T17:43:59Z
dc.date.available2020-06-25T17:43:59Z
dc.date.issued2007
dc.descriptionARCAKLIOGLU, Erol/0000-0001-8073-5207;
dc.description.abstractThis paper proposes artificial neural networks (ANNs) technique as a new approach to determine the exergy losses of an ejector-absorption heat transformer (EAHT). Thermodynamic analysis of the EAHT is too complex due to complex differential equations and complex simulations programs. ANN technique facilitates these complicated situations. This study is considered to be helpful in predicting the exergetic performance of components of an EAHT prior to its setting up in a thermal system where the working temperatures are known. The best approach was investigated using different algorithms with developed software. The best statistical coefficient of multiple determinations (R-2-value) for training data equals to 0.999715, 0.995627, 0.999497, and 0.997648 obtained by different algorithms with seven neurons for the non-dimensional exergy losses of evaporator, generator, absorber and condenser, respectively. Similarly these values for testing data are 0.999774, 0.994039, 0.999613 and 0.99938, respectively. The results show that this approach has the advantages of computational speed, low cost for feasibility, rapid turnaround, which is especially important during iterative design phases, and easy of design by operators with little technical experience. (c) 2006 Elsevier Ltd. All rights reserved.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1016/j.applthermaleng.2006.06.012
dc.identifier.endpage491en_US
dc.identifier.issn1359-4311
dc.identifier.issue2-3en_US
dc.identifier.scopus2-s2.0-33749666544
dc.identifier.scopusqualityQ1
dc.identifier.startpage481en_US
dc.identifier.urihttps://doi.org10.1016/j.applthermaleng.2006.06.012
dc.identifier.urihttps://hdl.handle.net/20.500.12587/3971
dc.identifier.volume27en_US
dc.identifier.wosWOS:000241706500023
dc.identifier.wosqualityQ2
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofApplied Thermal Engineering
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectabsorptionen_US
dc.subjectheat transformeren_US
dc.subjectsimulationen_US
dc.subjectsolar ponden_US
dc.subjectejectoren_US
dc.subjectartificial neural networken_US
dc.titleExergy analysis of an ejector-absorption heat transformer using artificial neural network approachen_US
dc.typeArticle

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