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首页> 外文期刊>SIAM Journal on Numerical Analysis >An iterative substructuring method for Raviart-Thomas vector fields in three dimensions
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An iterative substructuring method for Raviart-Thomas vector fields in three dimensions

机译:三维Raviart-Thomas向量场的迭代子构造方法

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The iterative substructuring methods, also known as Schur complement methods, form one of two important families of domain decomposition algorithms. They are based on a partitioning of a given region, on which the partial differential equation is defined, into nonoverlapping substructures. The preconditioners of these conjugate gradient methods are then given in terms of local problems, defined on individual substructures and pairs of substructures, and, in addition, a global problem of low dimension. An iterative method of this kind is introduced for the lowest order Raviart-Thomas finite elements in three dimensions and it is shown that the condition number of the relevant operator is independent of the number of substructures and grows only as the square of the logarithm of the number of unknowns associated with an individual substructure. The theoretical bounds are confirmed by a series of numerical experiments. [References: 27]
机译:迭代子构造方法(也称为Schur互补方法)形成了域分解算法的两个重要族之一。它们基于给定区域的划分(不定义子结构),在该区域上定义了偏微分方程。然后,根据局部问题给出这些共轭梯度方法的预处理器,这些局部问题定义在单个子结构和子结构对上,此外还涉及一个低维的全局问题。针对三种维中最低阶的Raviart-Thomas有限元引入了这种迭代方法,结果表明相关算子的条件数与子结构数无关,并且仅随着子结构对数的平方增长与单个子结构关联的未知数。理论界限由一系列数值实验证实。 [参考:27]

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