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Probabilistic free vibration analysis of functionally graded beams using stochastic finite element methods

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dc.contributor.author Nguyen, Phong T.T
dc.contributor.author Trinh, Luan C.
dc.contributor.author Nguyen, Kien-Trung
dc.date.accessioned 2021-02-10T09:01:20Z
dc.date.issued 2020
dc.identifier.uri http://hdl.handle.net/10344/9760
dc.description peer-reviewed en_US
dc.description.abstract In this study, we use the stochastic finite element method for vibration analysis of functionally graded (FG) Euler-Bernoulli beams considering variability in material properties. The selected FG material consists of a mix of ceramic and metal constituents. The material properties of the FG beams studied are assumed to vary smoothly over the depth according to a power law. Constituent material properties such as the Young’s modulus, mass density and volume fraction index are modeled as random variables. For each simulation of these random parameters, finite element method is employed to estimate natural frequencies of FG beam. Several simulations need to be carried out for propagating overall inputs uncertainty to stochastic frequencies that are approximated as a series in an orthogonal space. The components of series will be determined based on both polynomial chaos expansion (PCE) and stochastic collocation (SC) methods. For PCE, the multivariate Hermite orthogonal functions are derived using Askey scheme. Their coefficients are estimated using both spectral projection, linear regression approaches. Standard tensor product is used to integrate the multi-dimensional integrals. In term of SC method, basis functions are Lagrange interpolation functions formed for known coefficients called collocation points. Postanalysis including reliability, sensitivity and distribution of uncertain frequencies are also studied. These results will also be compared with those of Monte Carlo Simulation. en_US
dc.language.iso eng en_US
dc.publisher Springer en_US
dc.relation.ispartofseries Computational Intelligence Methods for Green Technology and Sustainable Development. GTSD 2020. Advances in Intelligent Systems and Computing, Huang YP., Wang WJ., Quoc H.A., Giang L.H., Hung NL. (eds);1284
dc.relation.uri https://link.springer.com/chapter/10.1007/978-3-030-62324-1_44
dc.rights The original publication is available at www.springerlink.com en_US
dc.subject functionally graded beam en_US
dc.subject stochastic finite element method en_US
dc.subject uncertainty propagation en_US
dc.subject polynomial chaos expansions en_US
dc.subject stochastic collocation en_US
dc.title Probabilistic free vibration analysis of functionally graded beams using stochastic finite element methods en_US
dc.type info:eu-repo/semantics/conferenceObject en_US
dc.type.supercollection all_ul_research en_US
dc.type.supercollection ul_published_reviewed en_US
dc.identifier.doi 10.1007/978-3-030-62324-1_44
dc.identifier.doi 10.1007/978-3-030-62324-1_44
dc.date.embargoEndDate 2021-10-28
dc.embargo.terms 2021-10-28 en_US
dc.rights.accessrights info:eu-repo/semantics/openAccess en_US
dc.internal.rssid 2987126


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