Analytical and artificial neural network models to estimate the discharge coefficient for ogee spillway

Basit Öğe Kaydı
dc.contributor.authorYarar, Alpaslan
dc.date.accessioned2020-03-26T19:33:51Z
dc.date.available2020-03-26T19:33:51Z
dc.date.issued2017
dc.departmentSelçuk Üniversitesien_US
dc.descriptionInternational Conference on Energy, Environment and Material Systems (EEMS) -- SEP 13-15, 2017 -- Polanica Zdroj, POLANDen_US
dc.description.abstractIn this study, analytical and Artificial Neural Network (ANN) model were used for determine the discharge coefficient of Ogee Spillways. For this aim, discharge coefficients of 11 different heads were calculated by using a test flume having 7.5 cm width, 15 cm depth and 5 m length, in the laboratory. Discharge coefficients were also computed by the formula for the same heads measured in the laboratory to investigate the accuracy of experimental setup. An ANN model was set by using the experimental results in order to estimate the discharge coefficient. Then, the performance of the ANN model was investigated. As the result, the coefficient of determination between ANN model and experimental setup is found R-2 = 0.98. ANN model is show a good consistency with experimental results.en_US
dc.description.sponsorshipOpole Univ Technol, Fac Mech Engn, Ctr Educ, Competence, Innovat & Technol, Republ Poland, Minist Sci & Higher Educ, Oddzial Elektrownia Opole, GiEK S A, Oil Opole, Energetyka Cieplna Opolszczyny SA Jelenia Gora, Warta Cementowniaen_US
dc.identifier.doi10.1051/e3sconf/20171903028en_US
dc.identifier.issn2267-1242en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://dx.doi.org/10.1051/e3sconf/20171903028
dc.identifier.urihttps://hdl.handle.net/20.500.12395/34796
dc.identifier.volume19en_US
dc.identifier.wosWOS:000426609200108en_US
dc.identifier.wosqualityN/Aen_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherE D P SCIENCESen_US
dc.relation.ispartofINTERNATIONAL CONFERENCE ENERGY, ENVIRONMENT AND MATERIAL SYSTEMS (EEMS 2017)en_US
dc.relation.ispartofseriesE3S Web of Conferences
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleAnalytical and artificial neural network models to estimate the discharge coefficient for ogee spillwayen_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

WoS İndeksli Yayınlar Koleksiyonu
Scopus İndeksli Yayınlar Koleksiyonu