On the use of the GP-NARX model for predicting hysteresis effects of bolted joint structures

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dc.contributor.authorde Oliveira Teloli, Rafael [UNESP]
dc.contributor.authorVillani, Luis G.G.
dc.contributor.authorSilva, Samuel da [UNESP]
dc.contributor.authorTodd, Michael D.
dc.contributor.institutionUniversidade Estadual Paulista (Unesp)
dc.contributor.institutionUniversidade Federal do Espírito Santo (UFES)
dc.contributor.institutionUCSD – University of California San Diego
dc.date.accessioned2021-06-25T10:56:06Z
dc.date.available2021-06-25T10:56:06Z
dc.date.issued2021-10-01
dc.description.abstractStructures joined by lap-joints can present complex nonlinear dynamic behavior as a function of the stress to which the lap-joint is subjected, including contact stiffness variations and softening, along with hysteresis effects related to frictional dissipation at the contact interface. Considering applications where the use of non-parametric models that depend only on input and output data is required, this work proposes and details the GP-NARX model's use to approximate systems’ dynamics with hysteresis. Initially, the proposed model's predictive applicability is evaluated on a numerical application involving the Bouc-Wen oscillator with hysteretic damping. Then, this work proposes a GP-NARX model to describe the dynamics of the BERT benchmark, an experimental system that contains a symmetric double bolted joint that is nonlinearly dependent upon the applied excitation amplitudes, presenting as a friction joint's well-known softening effect. The structure also presents data variation related to the presence of uncertainties in the measurement process. Thus, to accommodate the experimental variability, the training step of the GP-NARX model considers several experimental realizations. The results indicate that GP-NARX can make accurate predictions of the response of both investigated applications, emphasizing its practical ability, where the confidence intervals of the proposed model were able to accommodate the noisy experimental data, learning the nonlinear relation between the input and output data points.en
dc.description.affiliationUNESP - Universidade Estadual Paulista Faculdade de Engenharia de Ilha Solteira Departamento de Engenharia Mecânica, Av. Brasil, 56, Ilha Solteira
dc.description.affiliationUFES - Universidade Federal do Espírito Santo Centro Tecnológico Departamento de Engenharia Mecânica, Av. Fernando Ferrari, 514, Goiabeiras
dc.description.affiliationUCSD – University of California San Diego Department of Structural Engineering, 9500 Gilman Dr
dc.description.affiliationUnespUNESP - Universidade Estadual Paulista Faculdade de Engenharia de Ilha Solteira Departamento de Engenharia Mecânica, Av. Brasil, 56, Ilha Solteira
dc.identifierhttp://dx.doi.org/10.1016/j.ymssp.2021.107751
dc.identifier.citationMechanical Systems and Signal Processing, v. 159.
dc.identifier.doi10.1016/j.ymssp.2021.107751
dc.identifier.issn1096-1216
dc.identifier.issn0888-3270
dc.identifier.scopus2-s2.0-85102976374
dc.identifier.urihttp://hdl.handle.net/11449/207494
dc.language.isoeng
dc.relation.ispartofMechanical Systems and Signal Processing
dc.sourceScopus
dc.subjectGP-NARX
dc.subjectHysteretic systems
dc.subjectJointed structures
dc.subjectUncertainties
dc.titleOn the use of the GP-NARX model for predicting hysteresis effects of bolted joint structuresen
dc.typeArtigo

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