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Numerical methods to predict human induced vibrations on low frequency stairs. Part 2: evaluation by comparing with experimental data

2021Journal article Open access
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dc.contributor.authorAndrade, Pedro
dc.contributor.authorSantos, José
dc.contributor.authorEscórcio, Patrícia
dc.date.accessioned2022-03-15T15:38:37Z
dc.date.available2022-03-15T15:38:37Z
dc.date.issued2021
dc.description.abstractNowadays, vibration serviceability criteria are becoming the governing factor in the design of most modern staircases, because their increasing susceptibility to human induced vibrations. Although more awareness have been raised to the dynamic design of new staircases, there are still few studies found in the literature that compare the different results of numerical methods for predicting vibrations with experimental data, in order to validate the same. Hence, this paper employs the main existing numerical methods to an actual staircase with known liveness, by comparing the predicted results with the experimental data, to evaluate their accuracy when designing flexible staircases. This paper is Part 2 of a set of two papers. In Part 1, the different numerical methods are presented and details are given of how to apply them. To accomplish this, an in-situ staircase dynamic characterisation and several walking tests are performed. The measured vibrations are initially compared with different proposed acceptable limits to confirm that the vi brations exceed the limits. The different numerical methods are then employed and the predicted results are compared with the experimental results. Lastly, the main findings of this work are discussed together with those of diverse researchers who also applied one of these procedures to estimate vibrations. The results obtained showed that, with two of the numerical procedures applied (footfall force time histories and simplified vibration evaluation), it was possible to effectively predict the vibrations, while with the remaining two (Fourier series walking models and steady-state analysis), in general, overestimated responses were predicted.pt_PT
dc.description.versioninfo:eu-repo/semantics/publishedVersionpt_PT
dc.identifier.citationAndrade, P., Santos, J., & Escórcio, P. (2021, December). Numerical methods to predict human induced vibrations on low frequency stairs. Part 2: Evaluation by comparing with experimental data. In Structures (Vol. 34, pp. 1008-1020). Elsevier. https://doi.org/10.1016/j.istruc.2021.08.024pt_PT
dc.identifier.doi10.1016/j.istruc.2021.08.024pt_PT
dc.identifier.urihttp://hdl.handle.net/10400.13/4145
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.subjectVibration acceptable limitspt_PT
dc.subjectExperimental programpt_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 2: evaluation by comparing with experimental datapt_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.endPage1020pt_PT
oaire.citation.startPage1008pt_PT
oaire.citation.titleStructurespt_PT
oaire.citation.volume34pt_PT
oaire.fundingStream6817 - DCRRNI ID
person.familyNameMARTINS NETO DOS SANTOS
person.familyNameEscórcio
person.givenNameJOSÉ MANUEL
person.givenNamePatrícia
person.identifier.ciencia-idDE1C-64E5-4284
person.identifier.orcid0000-0002-2583-009X
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.isAuthorOfPublication7a9e7a45-7ee3-4380-8a84-d5ac6be45af6
relation.isAuthorOfPublication.latestForDiscoveryabd4b512-8c9b-428c-be89-229c06afb6b8
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