arXivDaily arXiv每日学术速递 周一至周五更新
arXiv 1107.4293math.NAcs.NA
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实用DPG方法的分析

An analysis of the practical DPG method

Portland State University(波特兰州立大学);The Institute for Mathematics and its Applications, University of Minnesota(明尼苏达大学数学及其应用研究所)

Jay Gopalakrishnan, Weifeng Qiu

AI总结:

本文对实际实现中的不连续Petrov-Galerkin(DPG)方法进行了完整的误差分析,证明了当试验空间采用p次多项式时,使用r≥p+N(N为空间维数)的多项式近似测试空间可保持最优收敛率,并讨论了刚度矩阵的条件数。

摘要:

在这项工作中,我们对不连续Petrov-Galerkin(DPG)方法进行了完整的误差分析,考虑了其实际实现中的所有近似。具体来说,我们考虑在每个网格单元上使用$p$次多项式试验空间的DPG方法。早期工作表明,存在一个“试验到测试”算子$T$,当应用于试验空间时,定义了一个保证稳定性的测试空间。在DPG公式中,该算子$T$是局部的:可以逐单元应用。然而,为了应用$T$,需要在每个网格单元上求解一个无限维问题。在实际计算中,$T$使用每个网格单元上某个$r > p$次多项式进行近似。我们证明,对于拉普拉斯方程,只要$r \ge p+N$(其中$N$是空间维数,二维或更多),这种近似保持最优收敛率。我们还证明了线性弹性问题的DPG方法有类似结果。文中还包括对DPG方法中刚度矩阵条件数的评论。

英文摘要:

In this work we give a complete error analysis of the Discontinuous Petrov Galerkin (DPG) method, accounting for all the approximations made in its practical implementation. Specifically, we consider the DPG method that uses a trial space consisting of polynomials of degree $p$ on each mesh element. Earlier works showed that there is a "trial-to-test" operator $T$, which when applied to the trial space, defines a test space that guarantees stability. In DPG formulations, this operator $T$ is local: it can be applied element-by-element. However, an infinite dimensional problem on each mesh element needed to be solved to apply $T$. In practical computations, $T$ is approximated using polynomials of some degree $r > p$ on each mesh element. We show that this approximation maintains optimal convergence rates, provided that $r\ge p+N$, where $N$ is the space dimension (two or more), for the Laplace equation. We also prove a similar result for the DPG method for linear elasticity. Remarks on the conditioning of the stiffness matrix in DPG methods are also included.

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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