A nonintrusive stochastic multiscale solver

In this paper, we describe a practical nonintrusive multiscale solver that permits consideration of uncertainties in heterogeneous materials without exhausting the available computational resources. The computational complexity of analyzing heterogeneous material systems is governed by the physical and probability spaces at multiple scales. To deal with these large spaces, we employ reduced order homogenization approach in combination with the Karhunen–Loeve expansion and stochastic collocation method based on sparse grid. The resulting nonintrusive multiscale solver, which is aimed at providing practical solutions for complex multiscale stochastic problems, has been verified against the Latin Hypercube Monte–Carlo method. Copyright © 2011 John Wiley & Sons, Ltd.

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