Neural network prediction of the ultimate capacity of shear stud connectors on composite beams with profiled steel sheeting

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dc.contributor.authorKoroglu, M. A.
dc.contributor.authorKoken, A.
dc.contributor.authorArslan, M. H.
dc.contributor.authorCevik, A.
dc.date.accessioned2020-03-26T18:42:37Z
dc.date.available2020-03-26T18:42:37Z
dc.date.issued2013
dc.departmentSelçuk Üniversitesien_US
dc.description.abstractIn this paper, the efficiency of different Artificial Neural Networks (ANNs) in predicting the ultimate shear capacity of shear stud connectors is explored. Experimental data involving push-out test specimens of 118 composite beams from an existing database in the literature were used to develop the ANN model. The input parameters affecting the shear capacity were selected as sheeting, stud dimensions, slab dimensions, reinforcement in the slab and concrete compression strength. Each parameter was arranged in an input vector and a corresponding output vector, which includes the ultimate shear capacity of composite beams. For the experimental test results, the ANN models were trained and tested using three layered back-propagation methods. The prediction performance of the ANN was obtained. In addition to these, the paper presents a short review of the codes in relation to the design of composite beams. The accuracy of the codes in predicting the ultimate shear capacity of composite beams was also examined in a comparable way using the same test data. At the end of the study, the effect of all parameters is also discussed. The study concludes that all ANN models predict the ultimate shear capacity of beams better than codes. (C) 2013 Sharif University of Technology. All rights reserved.en_US
dc.description.sponsorshipNecmettin Erbakan University BAP OfficeNecmettin Erbakan University; Selcuk University BAP OfficeSelcuk University [SU-BAP 2007/06201071]en_US
dc.description.sponsorshipThis research was supported by Necmettin Erbakan University BAP Office and Selcuk University BAP Office (SU-BAP 2007/06201071). Some data were taken from the Master of Science Thesis of Mehmet Alpaslan KOROGLU, entitled "The Usage of Earthquake Steel Bars as Shear Connections in Composite Slabs" in Turkish.en_US
dc.identifier.endpage1113en_US
dc.identifier.issn1026-3098en_US
dc.identifier.issue4en_US
dc.identifier.scopusqualityQ3en_US
dc.identifier.startpage1101en_US
dc.identifier.urihttps://hdl.handle.net/20.500.12395/29670
dc.identifier.volume20en_US
dc.identifier.wosWOS:000330338100004en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherELSEVIER SCIENCE BVen_US
dc.relation.ispartofSCIENTIA IRANICAen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.selcuk20240510_oaigen_US
dc.subjectShear studen_US
dc.subjectShear connectionen_US
dc.subjectComposite beamsen_US
dc.subjectPush-out testsen_US
dc.subjectArtificial neural networken_US
dc.titleNeural network prediction of the ultimate capacity of shear stud connectors on composite beams with profiled steel sheetingen_US
dc.typeArticleen_US

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