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首页> 外文期刊>Annals of nuclear energy >Hybrid Multi-level solvers for discontinuous Galerkin finite element discrete ordinate diffusion synthetic acceleration of radiation transport algorithms
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Hybrid Multi-level solvers for discontinuous Galerkin finite element discrete ordinate diffusion synthetic acceleration of radiation transport algorithms

机译:不连续Galerkin有限元离散坐标扩散辐射输运综合加速的混合多级解算器。

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摘要

This paper examines two established preconditioners which were developed to accelerate the solution of discontinuous Galerkin finite element method (DG-FEM) discretisations of the elliptic neutron diffusion equation. They are each presented here as a potential way to accelerate the solution of the Modified Interior Penalty (MIP) form of the discontinuous diffusion equation, for use as a diffusion synthetic acceleration (DSA) of DG-FEM discretisations of the neutron transport equation. The preconditioners are both two-level schemes, differing in the low-level space utilised. Once projected to the low-level space a selection of algebraic multigrid (AMG) preconditioners are utilised to obtain a further correction step, these are therefore "hybrid" preconditioners. The first preconditioning scheme utilises a continuous piece wise linear finite element method (FEM) space, while the second uses a discontinuous piece-wise constant space. Both projections are used alongside an element-wise block Jacobi smoother in order to create a symmetric preconditioning scheme which may be used alongside a conjugate gradient algorithm. An eigenvalue analysis reveals that both should aid convergence but the piece-wise constant based method struggles with some of the smoother error modes. Both are applied to a range of problems including some which are strongly heterogeneous. In terms of conjugate gradient (CG) iterations needed to reach convergence and computational time required, both methods perform well. However, the piece-wise linear continuous scheme appears to be the more effective of the two. An analysis of computer memory usage found that the discontinuous piece-wise constant method had the lowest memory requirements. (C) 2016 The Authors. Published by Elsevier Ltd.
机译:本文研究了两个已建立的预处理器,它们被开发来加速椭圆中子扩散方程的不连续Galerkin有限元方法(DG-FEM)离散化的求解。它们在此处分别作为加速求解不连续扩散方程的修正内部罚分(MIP)形式的一种潜在方法,用作中子输运方程的DG-FEM离散化的扩散合成加速度(DSA)。前置条件都是两个级别的方案,所使用的低级空间有所不同。一旦投影到低层空间,便会选择代数多重网格(AMG)预处理器,以获取进一步的校正步骤,因此将其称为“混合”预处理器。第一种预处理方案使用连续的分段线性有限元方法(FEM)空间,而第二种预处理方案使用不连续的分段恒定空间。这两个投影与逐个元素的雅可比平滑器一起使用,以便创建可以与共轭梯度算法一起使用的对称预处理方案。特征值分析表明,两者都应有助于收敛,但基于分段常数的方法在某些较平滑的误差模式下会遇到困难。两者都适用于一系列问题,包括一些严重异类的问题。就达到收敛所需的共轭梯度(CG)迭代和所需的计算时间而言,两种方法都表现良好。但是,分段线性连续方案似乎在两者中更有效。对计算机内存使用情况的分析发现,不连续的分段常数方法具有最低的内存要求。 (C)2016作者。由Elsevier Ltd.发布

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