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A Stochastic-deterministic Coupling Method for Multiscale Problems. Application to Numerical Homogenization of Random Materials

机译:多尺度问题的随机确定性耦合方法。在随机材料数值均质化中的应用

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In this paper, we describe a multiscale strategy that allows to couple stochastic and deterministic models. The transition condition enforced between the two models is weak, in the sense that it is based on volume coupling in space (rather than more classical boundary coupling) and on a volume/sample average in the random dimension. The paper then concentrates on the application of this weak coupling technique for the development of a new iterative method for the homogenization of random media. The technique is based on the coupling of the stochastic microstructure to a tentative homogenized medium, the parameters of which are initially chosen at will. Based on the results of the coupled simulation, for which Dirichlet or Neumann boundary conditions are posed at the boundary of the tentative homogenized medium, the parameters of the homogenized medium are then iteratively updated. An example shows the efficiency of the proposed approach compared to the classical KUBC and SUBC approaches in stochastic homogenization.
机译:在本文中,我们描述了一种多尺度策略,允许耦合随机模型和确定性模型。在这两个模型之间强制执行的转换条件是弱的,从某种意义上说,它是基于空间中的体积耦合(而不是更经典的边界耦合)以及随机维度中的体积/样本平均值。然后,本文集中讨论了这种弱耦合技术在开发一种用于随机介质均质化的新迭代方法上的应用。该技术基于随机微观结构与暂定的均质化介质的耦合,该介质的参数最初是随意选择的。根据耦合模拟的结果,对于Dirichlet或Neumann边界条件置于暂态均质介质的边界,然后迭代更新均质介质的参数。一个例子表明,与传统的KUBC和SUBC方法相比,该方法在随机均质化方面的效率更高。

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