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Energy-minimizing coarse spaces for two-level Schwarz methods for multiscale PDEs

机译:多尺度PDE的两级Schwarz方法的能量最小化粗糙空间

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Two-level overlapping Schwarz methods for elliptic partial differential equations combine local solves on overlapping domains with a global solve of a coarse approximation of the original problem. To obtain robust methods for equations with highly varying coefficients, it is important to carefully choose the coarse approximation. Recent theoretical results by the authors have shown that bases for such robust coarse spaces should be constructed such that the energy of the basis functions is minimized. We give a simple derivation of a method that finds such a minimum energy basis using one local solve per coarse space basis function and one global solve to enforce a partition of unity constraint. Although this global solve may seem prohibitively expensive, we demonstrate that a one-level overlapping Schwarz method is an effective and scalable preconditioner and we show that such a preconditioner can be implemented efficiently using the Sherman-Morrison-Woodbury formula. The result is an elegant, scalable, algebraic method for constructing a robust coarse space given only the supports of the coarse space basis functions. Numerical experiments on a simple two-dimensional model problem with a variety of binary and multiscale coefficients confirm this. Numerical experiments also show that, when used in a two-level preconditioner, the energy-minimizing coarse space gives better results than other coarse space constructions, such as the multiscale finite element approach.
机译:椭圆偏微分方程的两级重叠Schwarz方法将重叠域的局部解与原始问题的粗略近似的全局解结合在一起。为了获得系数变化很大的方程的鲁棒方法,重要的是仔细选择粗略近似。作者最近的理论结果表明,应该为此类鲁棒的粗糙空间构建基础,以使基础函数的能量最小化。我们给出一种方法的简单推导,该方法使用每个粗糙空间基函数一个局部解和一个整体解来实施单位约束的分区,从而找到这种最小能量基础。尽管此全局解决方案似乎代价过高,但我们证明了一个重叠的Schwarz方法是一种有效且可扩展的预处理器,并且我们证明可以使用Sherman-Morrison-Woodbury公式有效地实施这种预处理器。结果是一种优雅,可扩展的代数方法,该方法仅在粗糙空间基础函数的支持下构造鲁棒的粗糙空间。对具有多种二进制和多尺度系数的简单二维模型问题的数值实验证实了这一点。数值实验还表明,在两级预处理器中使用时,能量最小化的粗糙空间比其他粗糙空间结构(如多尺度有限元方法)具有更好的结果。

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