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Discontinuous Galerkin for Advection with Interface-Centered Reconstruction

机译:不连续Galerkin用于以界面为中心的对流平流

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The Recovery-based Discontinuous Galerkin (RDG) discretization has been shown to be the most accurate among contemporary DG schemes for diffusion on a Cartesian grid. It achieves the order of accuracy 3p + 2 for even p and 3p + 1 for odd p, where p is the order of the polynomial basis. However, the overall performance of a Navier-Stokes simulation, using RDG for viscous terms, is limited to 2p +1 due to the DG discretization for advection. We describe two different approaches to improve the accuracy of the DG discretization for advection. The first option is able to reach a maximal order of 4p + 3, albeit utilizing an enlarged computational stencil. The second one attains 3p +1 without enlarging the stencil. It is also computationally cheaper owing to the lower-order reconstruction.
机译:基于恢复的非连续伽勒金(RDG)离散化已被证明在当代DG方案中在笛卡尔网格上扩散最准确。对于偶数p,它的精度等级为3p + 2,对于奇数p,它的精度等级为3p + 1,其中p是多项式基础的数量级。但是,由于DG对流的离散化,使用RDG作为粘性项的Navier-Stokes模拟的总体性能被限制为2p +1。我们描述了两种不同的方法来提高对流DG离散化的准确性。尽管采用了扩大的计算模板,但第一种选择能够达到4p + 3的最大阶数。第二个在不扩大模板的情况下达到3p +1。由于较低阶的重构,它在计算上也更便宜。

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