从稳定欧拉方程高效计算感兴趣的量 I. 基于 $h$ 自适应牛顿-GMG 求解器的双重一致 DWR基于 $h$ 自适应牛顿-GMG 求解器的双一致性 DWR

IF 2.6 3区 物理与天体物理 Q1 PHYSICS, MATHEMATICAL
Jingfeng Wang, Guanghui Hu
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引用次数: 0

摘要

在开发面向目标的网格自适应稳定 DWR 误差估计时,二元一致性是一个重要问题。本文基于稳定欧拉方程的牛顿-GMG 框架深入研究了这一问题。理论上,使用 Petrov-Galerkinscheme 重新描述了数值框架,并在此基础上描述了二元一致性。研究发现,对于具有一般构型的问题,边界修正技术是在我们的数值框架中保持对偶一致性的有效方法。在数值上,我们提出了一种几何多网格方法来求解对偶问题,并设计了一个正则化项来保证迭代的收敛性。从数值实验中可以看出,我们的方法具有以下特点:(1) 对于具有不同配置的问题,可以顺利地获得感兴趣量的稳定数值收敛;(2) 为了准确计算感兴趣量,与双重不一致的方法相比,使用所提出的双重一致 DWR 方法可以大大节省网格。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Towards the Efficient Calculation of Quantity of Interest from Steady Euler Equations I: A Dual-Consistent DWR-Based $h$-Adaptive Newton-GMG Solver
The dual consistency is an important issue in developing stable DWR error estimation towards the goal-oriented mesh adaptivity. In this paper, such an issue is studied in depth based on a Newton-GMG framework for the steady Euler equations. Theoretically, the numerical framework is redescribed using the Petrov-Galerkin scheme, based on which the dual consistency is depicted. It is found that for a problem with general configuration, a boundary modification technique is an effective approach to preserve the dual consistency in our numerical framework. Numerically, a geometrical multigrid is proposed for solving the dual problem, and a regularization term is designed to guarantee the convergence of the iteration. The following features of our method can be observed from numerical experiments, i). a stable numerical convergence of the quantity of interest can be obtained smoothly for problems with different configurations, and ii). towards accurate calculation of quantity of interest, mesh grids can be saved significantly using the proposed dual-consistent DWR method, compared with the dual-inconsistent one.
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来源期刊
Communications in Computational Physics
Communications in Computational Physics 物理-物理:数学物理
CiteScore
4.70
自引率
5.40%
发文量
84
审稿时长
9 months
期刊介绍: Communications in Computational Physics (CiCP) publishes original research and survey papers of high scientific value in computational modeling of physical problems. Results in multi-physics and multi-scale innovative computational methods and modeling in all physical sciences will be featured.
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