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Numerical methods to predict human induced vibrations on low frequency stairs. Part 1: literature review, modelling

2021Journal article Open access
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dc.contributor.authorAndrade, Pedro
dc.contributor.authorSantos, José
dc.contributor.authorMaia, Lino
dc.date.accessioned2022-03-16T08:57:36Z
dc.date.available2022-03-16T08:57:36Z
dc.date.issued2021
dc.description.abstractRecent trends towards slender construction with prominent and exigent architectural requirements often result in low frequency staircases that are significantly flexible and susceptible to unacceptable vibrations, which may promote safety concerns for their users. For structural engineers, however, there is still a lack of understanding, available information and specific design guides for predicting the dynamic behaviour of staircases due to human induced vibrations. To address this problem, this work reviews and applies the main existing numerical methods for predicting vibrations, to evaluate their precision and provide practical guidance when designing flexible staircases. The work developed is presented in a two-part paper. In Part 1, the actual paper, several numerical methods are introduced and a detailed description is given of how these can be employed in a design stage. The distinction between low and high frequency staircases is explained, since it directly influences the structure’s behaviour and, subsequently, the selected method. A description is given of how to simulate walking dynamic loads, which forms the basis of all methods. The group effect is also discussed because it tends to considerably amplify the staircase response. Finally, the different numerical procedures are applied to a practical case and compared. It was observed that, although the four numerical methods were employed with the same staircase, their results were different. The reasons for the higher results of Fourier series walking models are explained. In Part 2, the follow-up paper, the numerical methods are employed on a real staircase, comparing the estimated and experimental results.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAndrade, P., Santos, J., & Maia, L. (2021, December). Numerical methods to predict human induced vibrations on low frequency stairs. Part 1: Literature review, modelling. In Structures (Vol. 34, pp. 575-588). https://doi.org/10.1016/j.istruc.2021.08.017pt_PT
dc.identifier.doi10.1016/j.istruc.2021.08.017pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4146
dc.language.isoengpt_PT
dc.peerreviewedyespt_PT
dc.publisherElsevierpt_PT
dc.relationInstitute of R&D in Structures and Construction
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/pt_PT
dc.subjectGround reaction forcespt_PT
dc.subjectFourier seriespt_PT
dc.subjectSteady-state analysispt_PT
dc.subjectSimplified vibration evaluationpt_PT
dc.subjectGroup effectpt_PT
dc.subjectStep frequencypt_PT
dc.subject.pt_PT
dc.subjectFaculdade de Ciências Exatas e da Engenhariapt_PT
dc.titleNumerical methods to predict human induced vibrations on low frequency stairs. Part 1: literature review, modellingpt_PT
dc.typejournal article
dspace.entity.typePublication
oaire.awardTitleInstitute of R&D in Structures and Construction
oaire.awardURIinfo:eu-repo/grantAgreement/FCT/6817 - DCRRNI ID/UIDB%2F04708%2F2020/PT
oaire.citation.endPage588pt_PT
oaire.citation.startPage575pt_PT
oaire.citation.titleStructurespt_PT
oaire.citation.volume34pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMARTINS NETO DOS SANTOS
person.familyNameSerra Maia
person.givenNameJOSÉ MANUEL
person.givenNameLino Manuel
person.identifierR-000-97W
person.identifier.ciencia-idDE1C-64E5-4284
person.identifier.ciencia-idB711-823E-18C5
person.identifier.orcid0000-0002-6371-0179
person.identifier.scopus-author-id37051068400
project.funder.identifierhttp://doi.org/10.13039/501100001871
project.funder.nameFundação para a Ciência e a Tecnologia
rcaap.rightsopenAccesspt_PT
rcaap.typearticlept_PT
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relation.isAuthorOfPublication3843bbca-e366-4c2f-ba3a-1b950a201d4b
relation.isAuthorOfPublication.latestForDiscoveryabd4b512-8c9b-428c-be89-229c06afb6b8
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