Neural network model for seismic response of braced buildings

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dc.authoridBozer, Ali/0000-0002-3632-2605
dc.contributor.authorDoran, Bilge
dc.contributor.authorShen, Jiehua 'Jay'
dc.contributor.authorWen, Rou
dc.contributor.authorAkbas, Bulent
dc.contributor.authorBozer, Ali
dc.date.accessioned2025-02-24T17:18:57Z
dc.date.available2025-02-24T17:18:57Z
dc.date.issued2017
dc.departmentFakülteler, Mühendislik Fakültesi, İnşaat Mühendisliği Bölümü
dc.description.abstractNon-ductile, concentrically braced frames are a common lateral force-resisting system used in low-to-moderate seismic regions in the USA. However, their dynamic responses to earthquake ground motions have not been well examined. Structural engineers usually design them conservatively as brittle structures with a small response-modification factor, while building codes restrict their use to low-rise buildings. In this paper, seismic responses of two typical non-ductile concentrically braced frames, one of three storeys and one of nine storeys, were predicted through a neural network model. Twelve input parameters, covering non-linear features from structural components and the uncertain nature of earthquake ground motions, were used in the modelling. Numerical results extracted from thousands of non-linear time-history analyses under one set of moderate ground motions were used to develop the model. Sensitivity analyses were conducted to evaluate the impacts of input parameters on the peak inter-storey drift ratio, designed as an output parameter in the model. The results are shown to be promising considering the uncertainties in both ground motions and the characteristics of structures.
dc.description.sponsorshipAmerican Institute of Steel Construction (AISC)
dc.description.sponsorshipThis paper was made possible in part by the support of the American Institute of Steel Construction (AISC). This support is greatly appreciated. The opinions expressed in this paper are solely those of the authors and do not necessarily reflect the views of Iowa State University and Gebze Institute of Technology, where the authors are employed, or the American Institute of Steel Construction, or other agencies and individuals whose names appear in this paper.
dc.identifier.doi10.1680/jstbu.16.00020
dc.identifier.endpage167
dc.identifier.issn0965-0911
dc.identifier.issn1751-7702
dc.identifier.issue3
dc.identifier.scopus2-s2.0-85011990386
dc.identifier.scopusqualityQ2
dc.identifier.startpage159
dc.identifier.urihttps://doi.org/10.1680/jstbu.16.00020
dc.identifier.urihttps://hdl.handle.net/20.500.14440/935
dc.identifier.volume170
dc.identifier.wosWOS:000393676000002
dc.identifier.wosqualityQ3
dc.indekslendigikaynakWeb of Science
dc.indekslendigikaynakScopus
dc.language.isoen
dc.publisherIce Publishing
dc.relation.ispartofProceedings of the Institution of Civil Engineers-Structures and Buildings
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.snmzKA_WOS_20250201
dc.subjectmathematical modelling
dc.subjectseismic engineering
dc.subjectsteel structures
dc.titleNeural network model for seismic response of braced buildings
dc.typeArticle

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