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arXiv 1306.5100math.NAcs.NA
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自适应FEM在非齐次Dirichlet数据下的收敛性与拟最优性

Convergence and Quasi-Optimality of Adaptive FEM with Inhomogeneous Dirichlet Data

Institute for Analysis and Scientific Computing, Vienna University of Technology(维也纳工业大学分析与科学计算研究所)

Michael Feischl, Marcus Page, Dirk Praetorius

AI总结:

本文研究了非齐次Dirichlet数据下自适应低阶FEM求解二阶椭圆PDE的收敛性与拟最优性,采用边基残差误差估计器并证明了二维情况下算法收敛性及拟最优收敛率。

摘要:

我们考虑通过自适应低阶FEM求解具有非齐次Dirichlet数据的二阶椭圆偏微分方程。通常做法是通过节点插值离散化给定的Dirichlet数据。以具有混合Dirichlet-Neumann边界条件的泊松方程作为模型例子。对于误差估计,我们使用基于边的残差误差估计器,将体积残差贡献替换为边振荡。对于二维情况,我们证明了自适应算法即使具有拟最优收敛率也收敛。对于二维和三维情况,我们证明如果将节点插值算子替换为L^2投影或Scott-Zhang拟插值算子,则算法收敛。作为证明的副产品,我们展示了Scott-Zhang算子在网格局部细化时点wise收敛到一个极限算子。这一性质可能在当前应用之外也有独立价值。最后,数值实验总结了本工作。

英文摘要:

We consider the solution of a second order elliptic PDE with inhomogeneous Dirichlet data by means of adaptive lowest-order FEM. As is usually done in practice, the given Dirichlet data are discretized by nodal interpolation. As model example serves the Poisson equation with mixed Dirichlet-Neumann boundary conditions. For error estimation, we use an edge-based residual error estimator which replaces the volume residual contributions by edge oscillations. For 2D, we prove convergence of the adaptive algorithm even with quasi-optimal convergence rate. For 2D and 3D, we show convergence if the nodal interpolation operator is replaced by the L^2-projection or the Scott-Zhang quasi-interpolation operator. As a byproduct of the proof, we show that the Scott-Zhang operator converges pointwise to a limiting operator as the mesh is locally refined. This property might be of independent interest besides the current application. Finally, numerical experiments conclude the work.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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