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CONVERGENCE ANALYSIS OF AN ADAPTIVE INTERIOR PENALTY DISCONTINUOUS GALERKIN METHOD

机译:自适应内罚不连续Galerkin方法的收敛性分析

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摘要

We study the convergence of an adaptive interior penalty discontinuous Galerkin (IPDG) method for a two-dimensional model second order elliptic boundary value problem. Based on a residual-type a posteriori error estimator, we prove that after each refinement step of the adaptive scheme we achieve a guaranteed reduction of the global discretization error in the meshdependent energy norm associated with the IPDG method. In contrast to recent work on adaptive IPDG methods [O. Karakashian and F. Pascal, Convergence of Adaptive Discontinuous Galerkin Approximations of Second-order Elliptic Problems, preprint, University of Tennessee, Knoxville, TN, 2007], the convergence analysis does not require multiple interior nodes for refined elements of the triangulation. In fact, it will be shown that bisection of the elements is sufficient. The main ingredients of the proof of the error reduction property are the reliability and a perturbed discrete local efficiency of the estimator, a bulk criterion that takes care of a proper selection of edges and elements for refinement, and a perturbed Galerkin orthogonality property with respect to the energy inner product. The results of numerical experiments are given to illustrate the performance of the adaptive method.
机译:我们研究了二维模型二阶椭圆边值问题的自适应内罚不连续伽勒金(IPDG)方法的收敛性。基于残差类型的后验误差估计量,我们证明了在自适应方案的每个细化步骤之后,我们都保证了与IPDG方法相关的依赖于网格的能量范数中全局离散误差的保证降低。与自适应IPDG方法的最新研究相反[O. Karakashian和F. Pascal,“二阶椭圆问题的自适应不连续Galerkin逼近的收敛性”,预印本,田纳西大学,诺克斯维尔,田纳西州,2007年],收敛分析不需要三角剖分元素的多个内部节点。实际上,将显示出元件的二等分就足够了。减少错误的性质的证明的主要成分是估计器的可靠性和扰动的离散局部效率,考虑适当选择边缘和元素以进行细化的总体准则以及相对于扰动的Galerkin正交性能量内积。数值实验结果说明了自适应方法的性能。

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