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Automatically stable discontinuous Petrov-Galerkin methods for stationary transport problems: Quasi-optimal test space norm

机译:用于平稳运输问题的自动稳定的不连续Petrov-Galerkin方法:准最佳测试空间范数

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We investigate the application of the discontinuous Petrov-Galerkin (DPG) finite element framework to stationary convection-diffusion problems. In particular, we demonstrate how the quasi-optimal test space norm improves the robustness of the DPG method with respect to vanishing diffusion. We numerically compare coarse-mesh accuracy of the approximation when using the quasi-optimal norm, the standard norm, and the weighted norm. Our results show that the quasi-optimal norm leads to more accurate results on three benchmark problems in two spatial dimensions. We address the problems associated to the resolution of the optimal test functions with respect to the quasi-optimal norm by studying their convergence numerically. In order to facilitate understanding of the method, we also include a detailed explanation of the methodology from the algorithmic point of view.
机译:我们研究了不连续的Petrov-Galerkin(DPG)有限元框架在平稳对流扩散问题中的应用。特别是,我们证明了准最优测试空间范数如何提高DPG方法相对于消失扩散的鲁棒性。当使用准最佳范数,标准范数和加权范数时,我们在数值上比较近似的粗网格精度。我们的结果表明,准最优范数在两个空间维度上针对三个基准问题产生了更准确的结果。通过数值研究它们的收敛性,我们解决了关于最优测试函数关于拟最优范数的解析的问题。为了促进对方法的理解,我们还从算法的角度对方法进行了详细说明。

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