dc.contributor.author | Esen, Hikmet | |
dc.contributor.author | Esen, Mehmet | |
dc.contributor.author | Ozsolak, Onur | |
dc.date.accessioned | 2019-07-27T12:10:23Z | |
dc.date.accessioned | 2019-07-28T09:44:03Z | |
dc.date.available | 2019-07-27T12:10:23Z | |
dc.date.available | 2019-07-28T09:44:03Z | |
dc.date.issued | 2017 | |
dc.identifier.issn | 0952-813X | |
dc.identifier.issn | 1362-3079 | |
dc.identifier.uri | https://dx.doi.org/10.1080/0952813X.2015.1056242 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12418/6885 | |
dc.description | WOS: 000392422400001 | en_US |
dc.description.abstract | In this study, slinky (the slinky-loop configuration is also known as the coiled loop or spiral loop of flexible plastic pipe)type ground heat exchanger (GHE) was established for a solar-assisted ground source heat pump system. System modelling is performed with the data obtained from the experiment. Artificial neural network (ANN) and adaptive neuro-fuzzy inference system (ANFIS) are used in modelling. The slinky pipes have been laid horizontally and vertically in a ditch. The system coefficient of performance (COPsys) and the heat pump coefficient of performance (COPhp) have been calculated as 2.88 and 3.55, respectively, at horizontal slinky-type GHE, while COPsys and COPhp were calculated as 2.34 and 2.91, respectively, at vertical slinky-type GHE. The obtained results showed that the ANFIS is more successful than that of ANN for forecasting performance of a solar ground source heat pump system. | en_US |
dc.description.sponsorship | Scientific Research Projects Administration Unit of Firat University [2009/1498] | en_US |
dc.description.sponsorship | The authors gratefully acknowledge the financial support from the Scientific Research Projects Administration Unit of Firat University for this study performed under the project with [grant number 2009/1498]. | en_US |
dc.language.iso | eng | en_US |
dc.publisher | TAYLOR & FRANCIS LTD | en_US |
dc.relation.isversionof | 10.1080/0952813X.2015.1056242 | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Solar energy | en_US |
dc.subject | ground source heat pump | en_US |
dc.subject | artificial neural network | en_US |
dc.subject | adaptive neuro-fuzzy inference system | en_US |
dc.title | Modelling and experimental performance analysis of solar-assisted ground source heat pump system | en_US |
dc.type | article | en_US |
dc.relation.journal | JOURNAL OF EXPERIMENTAL & THEORETICAL ARTIFICIAL INTELLIGENCE | en_US |
dc.contributor.department | [Esen, Hikmet -- Esen, Mehmet] Firat Univ, Fac Technol, Dept Energy Syst Engn, Elazig, Turkey -- [Ozsolak, Onur] Cumhuriyet Univ, Fac Technol, Dept Mfg Engn, Sivas, Turkey | en_US |
dc.contributor.authorID | ESEN, Mehmet -- 0000-0001-6543-8095; Esen, Hikmet -- 0000-0001-8802-8080 | en_US |
dc.identifier.volume | 29 | en_US |
dc.identifier.issue | 1 | en_US |
dc.identifier.endpage | 17 | en_US |
dc.identifier.startpage | 1 | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |