The aim of this work is to develop a stochastic multiscale model for polycrystalline materials, which accounts for the uncertainties in the micro-structure. At the finest scale, we model the micro-structure using a random Voronoi tessellation, each grain being assigned a random orientation. Then, we apply a computational homogenization procedure on statistical volume elements to obtain a stochastic characterization of the elasticity tensor at the meso-scale. A random field of the meso-scale elasticity tensor can thus be generated based on the information obtained from the SVE simulations. Finally, using a stochastic finite element method, these meso-scale uncertainties are propagated to the coarser scale. As an illustration we study the resonance frequencies of MEMS micro-beams made of poly-silicon materials, and we show that the stochastic multiscale approach predicts results in agreement with a Monte Carlo analysis applied directly on the fine finite-element model, i.e. with an explicit discretization of the grains. (C) 2015 Elsevier B.V. All rights reserved.
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Shanghai Univ, Dept Math, Shanghai, Peoples R ChinaShanghai Univ, Dept Math, Shanghai, Peoples R China
Wang, Xin
Cao, Liqun
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Chinese Acad Sci, Acad Math & Syst Sci, Inst Computat Math & Sci Engn Comp, LSEC, Beijing 100190, Peoples R ChinaShanghai Univ, Dept Math, Shanghai, Peoples R China
Cao, Liqun
Wong, Yaushu
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Univ Alberta, Dept Math & Stat Sci, Edmonton, AB, CanadaShanghai Univ, Dept Math, Shanghai, Peoples R China