posted on 2021-02-10, 09:01authored byPhong T.T Nguyen, Luan C. Trinh, Kien-Trung Nguyen
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.
History
Publication
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
Publisher
Springer
Note
peer-reviewed
Rights
The original publication is available at www.springerlink.com