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High Dimensional Finite Elements for Elliptic Problems with Multiple Scales and Stochastic Data

机译:具有多个尺度和随机数据的椭圆问题的高尺寸有限元

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摘要

Multiple scale homogenization problems are reduced to single scale problems in higher dimension. It is shown that sparse tensor product Finite Element Methods (FEM) allow the numerical solution in complexity independent of the dimension and of the length scale. Problems with stochastic input data are reformulated as high dimensional deterministic problems for the statistical moments of the random solution. Sparse tensor product FEM give a deterministic solution algorithm of log-linear complexity for statistical moments.
机译:多种均匀化问题降低到更高尺寸的单尺度问题。结果表明,稀疏的张量产品有限元方法(FEM)允许数值溶液,其复杂性独立于尺寸和长度尺度。随着随机解决方案的统计时刻,随着随机输入数据的问题被重构为高维度确定性问题。稀疏的张量产品FEM为统计时刻提供了一种确定的逻辑线性复杂性的确定性解决方案算法。

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