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首页> 外文期刊>Journal of Computational Physics >A high order compact least-squares reconstructed discontinuous Galerkin method for the steady-state compressible flows on hybrid grids
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A high order compact least-squares reconstructed discontinuous Galerkin method for the steady-state compressible flows on hybrid grids

机译:高阶压缩最小二乘对混合网格上的稳态可压缩流程重建了不连续的Galerkin方法

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In this paper, a class of new high order reconstructed DG (rDG) methods based on the compact least-squares (CLS) reconstruction [23,24] is developed for simulating the two dimensional steady-state compressible flows on hybrid grids. The proposed method combines the advantages of the DG discretization with the flexibility of the compact least-squares reconstruction, which exhibits its superior potential in enhancing the level of accuracy and reducing the computational cost compared to the underlying DG methods with respect to the same number of degrees of freedom. To be specific, a third-order compact least-squares rDG(p(1)p(2)) method and a fourth-order compact least-squares rDG(p(2)p(3)) method are developed and investigated in this work. In this compact least-squares rDG method, the low order degrees of freedom are evolved through the underlying DG(p(1)) method and DG(p(2)) method, respectively, while the high order degrees of freedom are reconstructed through the compact least-squares reconstruction, in which the constitutive relations are built by requiring the reconstructed polynomial and its spatial derivatives on the target cell to conserve the cell averages and the corresponding spatial derivatives on the face-neighboring cells. The large sparse linear system resulted by the compact least-squares reconstruction can be solved relatively efficient when it is coupled with the temporal discretization in the steady-state simulations. A number of test cases are presented to assess the performance of the high order compact least-squares rDG methods, which demonstrates their potential to be an alternative approach for the high order numerical simulations of steady-state compressible flows. (C) 2018 Elsevier Inc. All rights reserved.
机译:在本文中,开发了基于压缩最小二乘(CLS)重建的一类新的高阶重建DG(RDG)方法[23,24],用于模拟混合网格上的二维稳态可压缩流。所提出的方法将DG离散化的优点与压缩最小二乘重建的灵活性相结合,这在与相同数量的基础DG方法相比,其具有增强精度水平和降低计算成本的优异潜力自由程度。具体地,开发并研究了三阶压缩最小二乘RDG(P(1)P(2))方法和四阶压缩最小二乘RDG(P(2)P(3))方法这项工作。在这种紧凑的最小二乘法RDG方法中,通过底层DG(P(1))方法和DG(P(2))方法,虽然通过底层DG(P(2))方法来演化低阶自由度,而通过较高的自由度压缩最小二乘重建,其中构成关系是通过在目标小区上的重构多项式及其空间衍生物来保护细胞平均值和面部相邻小区上的相应空间衍生物构建。当其与稳态模拟中的时间离散化耦合时,由压缩最小二乘重建导致的大稀疏线性系统可以解决。提出了许多测试用例,以评估高阶压缩最小二乘RDG方法的性能,这表明它们的潜在方法是稳态可压缩流动的高阶数值模拟的替代方法。 (c)2018年Elsevier Inc.保留所有权利。

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