Modeling of a mechanical cooling system with variable cooling capacity by using artificial neural network

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dc.contributor.authorYilmaz, Sezayi
dc.contributor.authorAtik, Kemal
dc.date.accessioned2024-09-29T15:54:57Z
dc.date.available2024-09-29T15:54:57Z
dc.date.issued2007
dc.departmentKarabük Üniversitesien_US
dc.description.abstractCapacity modification in mechanical cooling systems can be performed by various methods. Changing condenser temperature also changes the capacity of the cooling system. In this study, a series of experiments were performed in order to determine the effects of changing cooling water flow rate (changing condenser temperature) in a mechanical heat pump experimental setup on the cooling capacity of the system. Power consumption, thermal efficiency, coefficient of performance (COP) of the system in various cooling capacities were estimated theoretically by using the data acquired from the experiments performed. Performance values obtained were used for training Artificial neural network (ANN) whose structure was designed for this operation. The Network, which has three layers as input, output, and hidden layer, has one input and four output cells. Six cells were used in hidden layers. Training was continued until the square error became (E < 0.005) in this ANN, for which back propagation algorithm was used for training. Desired error value was achieved in ANN and, ANN was tested with both data used for training ANN and data not used. Resultant low relative error value of the test indicates the usability of ANNs in this area. (c) 2007 Elsevier Ltd. All rights reserved.en_US
dc.identifier.doi10.1016/j.applthermaleng.2007.01.030
dc.identifier.endpage2313en_US
dc.identifier.issn1359-4311
dc.identifier.issue13en_US
dc.identifier.startpage2308en_US
dc.identifier.urihttps://doi.org/10.1016/j.applthermaleng.2007.01.030
dc.identifier.urihttps://hdl.handle.net/20.500.14619/4386
dc.identifier.volume27en_US
dc.identifier.wosWOS:000247862800020en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.language.isoenen_US
dc.publisherPergamon-Elsevier Science Ltden_US
dc.relation.ispartofApplied Thermal Engineeringen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectartificial neural networksen_US
dc.subjectcooling cycleen_US
dc.subjectcondenser temperatureen_US
dc.titleModeling of a mechanical cooling system with variable cooling capacity by using artificial neural networken_US
dc.typeArticleen_US

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