arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1809.03153math.NAcs.NA
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DPG-star方法

The DPG-star method

The Institute for Computational Engineering and Sciences (ICES), The University of Texas at Austin(德克萨斯大学奥斯汀分校计算工程与科学研究所);Portland State University(波特兰州立大学);Technische Universität München(慕尼黑工业大学)

Leszek Demkowicz, Jay Gopalakrishnan, Brendan Keith

AI总结:

本文提出了一种新的有限元方法DPG-star,该方法在某种意义上是断续Petrov-Galerkin方法的对偶方法。DPG方法可以看作是求解过定离散化边值问题的手段,而DPG-star方法则是求解欠定离散化问题的手段。通过将相同的算子方程嵌入到两个不同的鞍点问题中,这两种观点得到了发展。分析这两个问题有许多共同点。与其他方法的比较补充了新视角。值得注意的是,DPG-star和DPG方法可以分别视为$\mathcal{L}\mathcal{L}^\ast$和最小二乘方法的推广。本文详细讨论了DPG-star方法的先验误差分析和后验误差控制。提供了几个数值实验的结果,展示了新方法的本质特征。DPG-star和DPG分析结果的一个显著差异是前者收敛率受一个额外Lagrange乘数变量正则性的影响。

摘要:

本文介绍了一种新的有限元方法DPG-star(以下简称DPG$^*$)。该方法在某种意义上是断续Petrov-Galerkin(DPG)方法的对偶方法。DPG方法可以看作是求解过定离散化边值问题的手段。同样,DPG$^*$方法是求解欠定离散化问题的手段。这两种观点通过将相同的算子方程嵌入到两个不同的鞍点问题中得到发展。这两个问题的分析有许多共同点。与其他文献中方法的比较补充了新的视角。值得注意的是,DPG$^*$和DPG方法可以分别视为$\mathcal{L}\mathcal{L}^\ast$和最小二乘方法的推广。本文详细讨论了DPG$^*$方法的先验误差分析和后验误差控制。提供了几个数值实验的结果,展示了新方法的本质特征。DPG$^*$和DPG分析结果的一个显著差异是前者收敛率受一个额外Lagrange乘数变量正则性的影响。

英文摘要:

This article introduces the DPG-star (from now on, denoted DPG$^*$) finite element method. It is a method that is in some sense dual to the discontinuous Petrov-Galerkin (DPG) method. The DPG methodology can be viewed as a means to solve an overdetermined discretization of a boundary value problem. In the same vein, the DPG$^*$ methodology is a means to solve an underdetermined discretization. These two viewpoints are developed by embedding the same operator equation into two different saddle-point problems. The analyses of the two problems have many common elements. Comparison to other methods in the literature round out the newly garnered perspective. Notably, DPG$^*$ and DPG methods can be seen as generalizations of $\mathcal{L}\mathcal{L}^\ast$ and least-squares methods, respectively. A priori error analysis and a posteriori error control for the DPG$^*$ method are considered in detail. Reports of several numerical experiments are provided which demonstrate the essential features of the new method. A notable difference between the results from the DPG$^*$ and DPG analyses is that the convergence rates of the former are limited by the regularity of an extraneous Lagrange multiplier variable.

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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