Application of ANN to evaluate effective parameters affecting failure load and displacement of RC buildings

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dc.contributor.authorArslan, M. Hakan
dc.date.accessioned2020-03-26T17:37:54Z
dc.date.available2020-03-26T17:37:54Z
dc.date.issued2009
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractThis study investigated the efficiency of an artificial neural network (ANN) in predicting and determining failure load and failure displacement of multi story reinforced concrete (RC) buildings. The study modeled a RC building with four stories and three bays, with a load bearing system composed of columns and beams. Non-linear static pushover analysis of the key parameters in change defined in Turkish Earthquake Code (TEC-2007) for columns and beams was carried out and the capacity curves, failure loads and displacements were obtained. Totally 720 RC buildings were analyzed according to the change intervals of the parameters chosen. The input parameters were selected as longitudinal bar ratio ((l)) of columns, transverse reinforcement ratio (A(sw)/s(c)), axial load level (N/N(o)), column and beam cross section, strength of concrete (f(c)) and the compression bar ratio ('/) on the beam supports. Data from the nonlinear analysis were assessed with ANN in terms of failure load and failure displacement. For all outputs, ANN was trained and tested using of 11 back-propagation methods. All of the ANN models were found to perform well for both failure loads and displacements. The analyses also indicated that a considerable portion of existing RC building stock in Turkey may not meet the safety standards of the Turkish Earthquake Code (TEC-2007).en_US
dc.description.sponsorshipSU-BAPSelcuk University [08 701 030]en_US
dc.description.sponsorshipThe author acknowledges support provided by SU-BAP under Project No. 08 701 030.en_US
dc.identifier.endpage977en_US
dc.identifier.issn1561-8633en_US
dc.identifier.issue3en_US
dc.identifier.scopusqualityQ1en_US
dc.identifier.startpage967en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/23292
dc.identifier.volume9en_US
dc.identifier.wosWOS:000267543300029en_US
dc.identifier.wosqualityQ2en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherCOPERNICUS PUBLICATIONSen_US
dc.relation.ispartofNATURAL HAZARDS AND EARTH SYSTEM SCIENCESen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.selcuk20240510_oaigen_US
dc.titleApplication of ANN to evaluate effective parameters affecting failure load and displacement of RC buildingsen_US
dc.typeArticleen_US

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