Determination of reducing coefficient values of semi-rigid frames using artificial neural network

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dc.contributor.authorŞeker S.
dc.contributor.authorÖztürk A.U.
dc.contributor.authorKozanoǧlu C.
dc.date.accessioned2024-07-22T08:20:31Z
dc.date.available2024-07-22T08:20:31Z
dc.date.issued2011
dc.description.abstractLateral rigidity is a great issue in the view of structural analysis in civil engineering applications such as production of buildings, bridges, dams and roads. Furthermore, the connection properties have a remarkable role on the lateral rigidity and the tendency of structures under service loads. In fact, there aren't any structures with perfectly rigid connections between beams and columns. Therefore, all connections performed by construction process can be defined as semi-rigid as, especially connections in steel structures. The effect of connection type on the lateral rigidity values of structures can be determined by reducing coefficients decreasing lateral rigidity with a certain extent. In the scope of this study, connection flexibility is modeled by linear elastic rotational springs for semi-rigid frames. The reducing coefficients are determined by using a computer program. Results are compared to the values predicted by artificial neural network (ANN) analyses. A strong relationship was established between calculated and predicted values. © Association for Scientific Research.
dc.identifier.DOI-ID10.3390/mca16030649
dc.identifier.issn1300686X
dc.identifier.urihttp://akademikarsiv.cbu.edu.tr:4000/handle/123456789/18181
dc.language.isoEnglish
dc.publisherAssociation for Scientific Research
dc.rightsAll Open Access; Gold Open Access
dc.subjectNeural networks
dc.subjectRigidity
dc.subjectBeams and columns
dc.subjectCivil engineering applications
dc.subjectConnection flexibility
dc.subjectConstruction process
dc.subjectLateral rigidity
dc.subjectReducing coefficient
dc.subjectRotational spring
dc.subjectSemi-rigid
dc.subjectRigid structures
dc.titleDetermination of reducing coefficient values of semi-rigid frames using artificial neural network
dc.typeArticle

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