Please use this identifier to cite or link to this item: https://hdl.handle.net/20.500.14279/33051
DC FieldValueLanguage
dc.contributor.authorAbabu, Elvis M.-
dc.contributor.authorMarkou, George-
dc.contributor.authorBakas, Nikolaos P.-
dc.date.accessioned2024-10-09T06:32:39Z-
dc.date.available2024-10-09T06:32:39Z-
dc.date.issued2022-01-01-
dc.identifier.citationProceedings of the 14th International Conference on Agents and Artificial Intelligence (ICAART 2022) - vol. 3, pp. 958-963en_US
dc.identifier.isbn978-989-758-547-0-
dc.identifier.issn21843589-
dc.identifier.urihttps://hdl.handle.net/20.500.14279/33051-
dc.description.abstractThe use of curved I-beams has been increasing throughout the years as the steel forming industry continues to advance. However, there are often design limitations on such structures due to the lack of recommendations and design code formulae for the estimation of the expected deflection of these structures. This is attributed to the lack of understanding of the behaviour of curved I-beams that exhibit extreme torsion and bending. Thus, currently, there are no formulae readily available for practising engineers to use to estimate the deflection of curved beams. Since the design of light steel structures is often governed by serviceability considerations, this paper aims to analyse the properties of curved steel I-beams and their impact on deflection as well as develop an accurate formula that will be able to predict the expected deflection of these beams. By using a combination of an experimentally validated finite element modelling approach and machine learning. Numerous formulae are developed and tested for the needs of this research work. The final proposed formula, which is the first of its kind, was found to have an average error of 4.11% in estimating the midspan deflection on the test dataset.en_US
dc.language.isoenen_US
dc.subjectCurved Beamsen_US
dc.subjectMachine Learningen_US
dc.subjectSteelen_US
dc.subjectFinite Element Methoden_US
dc.subjectDesignen_US
dc.titleUsing Machine Learning and Finite Element Modelling to Develop a Formula to Determine the Deflection of Horizontally Curved Steel I-beamsen_US
dc.typeConference Papersen_US
dc.collaborationUniversity of Pretoriaen_US
dc.collaborationRDC Informaticsen_US
dc.subject.categoryComputer and Information Sciencesen_US
dc.subject.categoryENGINEERING AND TECHNOLOGYen_US
dc.subject.categoryCivil Engineeringen_US
dc.subject.categoryOther Engineering and Technologiesen_US
dc.journalsSubscriptionen_US
dc.countryGreeceen_US
dc.countrySouth Africaen_US
dc.subject.fieldEngineering and Technologyen_US
dc.publicationPeer Revieweden_US
dc.relation.conferenceInternational Conference on Agents and Artificial Intelligenceen_US
dc.identifier.doi10.5220/0010982400003116en_US
dc.identifier.scopus2-s2.0-85175806851-
dc.identifier.urlhttps://api.elsevier.com/content/abstract/scopus_id/85175806851-
dc.relation.volume3en_US
cut.common.academicyearemptyen_US
dc.identifier.spage958en_US
dc.identifier.epage963en_US
item.openairecristypehttp://purl.org/coar/resource_type/c_c94f-
item.openairetypeconferenceObject-
item.cerifentitytypePublications-
item.grantfulltextnone-
item.languageiso639-1en-
item.fulltextNo Fulltext-
crisitem.author.deptDepartment of Civil Engineering and Geomatics-
crisitem.author.facultyFaculty of Engineering and Technology-
crisitem.author.orcid0000-0002-6891-7064-
crisitem.author.parentorgFaculty of Engineering and Technology-
Appears in Collections:Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation
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