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dc.contributor.authorYoru, Yimaz
dc.contributor.authorKarakoç, Tahir Hikmet
dc.contributor.authorHepbaşlı, Arif
dc.date.accessioned2019-10-20T19:32:25Z
dc.date.available2019-10-20T19:32:25Z
dc.date.issued2010
dc.identifier.issn1742-8297
dc.identifier.urihttps://dx.doi.org/10.1504/IJEX.2010.031239
dc.identifier.urihttps://hdl.handle.net/11421/18481
dc.descriptionWOS: 000275222100003en_US
dc.description.abstractThe main objective of this study is to apply the Artificial Neural Network (ANN) method to a cogeneration system, located in Izmir, Turkey, for exergetic evaluation purposes. The data used are based on the actual operational conditions and the results obtained from this system, which was exergetically analysed by the authors. It consists of three turbines with a total capacity of 13 MW, six spray dryers and two heat exchangers. A comparison between the exergy destruction values obtained from exergy analysis calculations and the ANN method is made. Fast ANN (FANN) package (library) has been chosen as an ANN application to implement into the C++ code named CogeNNExT, which has been written and developed by the authors. From the single output of the ANN (FANN) results, the main exergy destruction rate with 60.96 MW in the exergetic analysis is found to be 61,001 MW with an error of 0.075%. From the two outputs of another ANN result, the mean input and output exergy values are found with errors of 0.438% and 2.211%, respectively.en_US
dc.description.sponsorshipEskisehir Osmangazi University; Anadolu University; Ege Universityen_US
dc.description.sponsorshipThe authors thank Eskisehir Osmangazi University, Anadolu University and Ege University for the support provided. They gratefully acknowledge the technical support provided by Izmir Ege Ceramic Factory in Turkey and especially Managers, Messrs. They thank Bahri Yaman and Ahmet Cirikoglu, for their help in visiting the factory and collecting the cogeneration system data. They are also grateful to Ege University Science Technology and Application Center (EBILTEM), Izmir, Turkey, and Vice Director of the Center, Professor Dr. Cengiz Akdeniz, for supplying the measurement equipment used during this study. The authors thank FANN C++ library developer, Mr. Steffen Nissen, for his fast and easy implemented library. They are also grateful to the four reviewers for the valuable comments, which have been utilised to improve the quality of the paper.en_US
dc.language.isoengen_US
dc.publisherInderscience Enterprises LTDen_US
dc.relation.isversionof10.1504/IJEX.2010.031239en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectCogenerationen_US
dc.subjectExergyen_US
dc.subjectAnnen_US
dc.subjectArtificial Neural Networken_US
dc.subjectGas Turbineen_US
dc.subjectSpray Dryeren_US
dc.subjectFannen_US
dc.subjectFast Artificial Neural Networken_US
dc.titleExergy analysis of a cogeneration system through Artificial Neural Network (ANN) methoden_US
dc.typearticleen_US
dc.relation.journalInternational Journal of Exergyen_US
dc.contributor.departmentAnadolu Üniversitesi, Havacılık ve Uzay Bilimleri Fakültesien_US
dc.identifier.volume7en_US
dc.identifier.issue2en_US
dc.identifier.startpage178en_US
dc.identifier.endpage192en_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US]
dc.contributor.institutionauthorKarakoç, Tahir Hikmet


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