dc.contributor.author | Yoru, Yimaz | |
dc.contributor.author | Karakoç, Tahir Hikmet | |
dc.contributor.author | Hepbaşlı, Arif | |
dc.date.accessioned | 2019-10-20T19:32:25Z | |
dc.date.available | 2019-10-20T19:32:25Z | |
dc.date.issued | 2010 | |
dc.identifier.issn | 1742-8297 | |
dc.identifier.uri | https://dx.doi.org/10.1504/IJEX.2010.031239 | |
dc.identifier.uri | https://hdl.handle.net/11421/18481 | |
dc.description | WOS: 000275222100003 | en_US |
dc.description.abstract | The 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.sponsorship | Eskisehir Osmangazi University; Anadolu University; Ege University | en_US |
dc.description.sponsorship | The 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.iso | eng | en_US |
dc.publisher | Inderscience Enterprises LTD | en_US |
dc.relation.isversionof | 10.1504/IJEX.2010.031239 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Cogeneration | en_US |
dc.subject | Exergy | en_US |
dc.subject | Ann | en_US |
dc.subject | Artificial Neural Network | en_US |
dc.subject | Gas Turbine | en_US |
dc.subject | Spray Dryer | en_US |
dc.subject | Fann | en_US |
dc.subject | Fast Artificial Neural Network | en_US |
dc.title | Exergy analysis of a cogeneration system through Artificial Neural Network (ANN) method | en_US |
dc.type | article | en_US |
dc.relation.journal | International Journal of Exergy | en_US |
dc.contributor.department | Anadolu Üniversitesi, Havacılık ve Uzay Bilimleri Fakültesi | en_US |
dc.identifier.volume | 7 | en_US |
dc.identifier.issue | 2 | en_US |
dc.identifier.startpage | 178 | en_US |
dc.identifier.endpage | 192 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US] |
dc.contributor.institutionauthor | Karakoç, Tahir Hikmet | |