Investigation of thermodynamic properties of refrigerant/absorbent couples using artificial neural networks

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dc.contributor.authorSozen, A
dc.contributor.authorOzalp, M
dc.contributor.authorArcaklioglu, E
dc.date.accessioned2020-06-25T17:40:03Z
dc.date.available2020-06-25T17:40:03Z
dc.date.issued2004
dc.departmentKırıkkale Üniversitesi
dc.descriptionARCAKLIOGLU, Erol/0000-0001-8073-5207
dc.description.abstractThis paper presents a new approach to determine the properties of liquid and two phase boiling and condensing of two alternative refrigerant/absorbent couples (methanol-LiBr and methanol-LiCl), which do not cause ozone depletion for absorption thermal systems (ATSs) using artificial neural networks (ANNs). The back-propagation learning algorithm with three different variants and logistic sigmoid transfer function were used in the network. In order to train the neural network, limited experimental measurements were used as training and test data. In input layer, there are temperatures in the range of 298-498 K (with 25 K increase), pressures (0.1-40 MPa) and concentrations of 2, 7, and 12% of the couples; specific volume is in output layer. After training, it is found that maximum error is less than 3%, average error is about 1% and R-2 values are 99.999%. As seen from the results obtained the thermodynamic properties have been obviously predicted within acceptable errors. This paper shows that values predicted with ANN can be used to define the thermodynamic properties instead of approximate and complex analytic equations. (C) 2004 Elsevier B.V. All rights reserved.en_US
dc.identifier.citationclosedAccessen_US
dc.identifier.doi10.1016/j.cep.2003.12.008
dc.identifier.endpage1264en_US
dc.identifier.issn0255-2701
dc.identifier.issn1873-3204
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-4243075455
dc.identifier.scopusqualityQ1
dc.identifier.startpage1253en_US
dc.identifier.urihttps://doi.org/10.1016/j.cep.2003.12.008
dc.identifier.urihttps://hdl.handle.net/20.500.12587/3229
dc.identifier.volume43en_US
dc.identifier.wosWOS:000224190200008
dc.identifier.wosqualityN/A
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherElsevier Science Saen_US
dc.relation.ispartofChemical Engineering And Processing-Process Intensification
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial neural networken_US
dc.subjectthermodynamic propertiesen_US
dc.subjectozone safe refrigerantsen_US
dc.subjectmethanol-liaren_US
dc.subjectmethanol-LiClen_US
dc.titleInvestigation of thermodynamic properties of refrigerant/absorbent couples using artificial neural networksen_US
dc.typeArticle

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