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Duality based error estimation in the presence of discontinuities

机译:基于二元的错误估计在不连续性的情况下

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Goal-oriented mesh adaptation, in particular using the dual-weighted residual (DWR) method, is known in many cases to produce very efficient meshes. For obtaining such meshes the (numerical) solution of an adjoint problem is needed to weight the residuals appropriately with respect to their relevance for the overall error. For hyperbolic problems already the weak primal problem requires in general an additional entropy condition to assert uniqueness of solutions; this difficulty is also reflected when considering adjoints to hyperbolic problems involving discontinuities where again an additional requirement (reversibility) is needed to select appropriate solutions.Within this article, an approach to the DWR method for hyperbolic problems based on an artificial viscosity approximation is proposed. It is discussed why the proposed method provides a well-posed dual problem, while a direct, formal, application of the dual problem does not. Moreover, we will discuss a further, novel, approach in which the forward problem need not be modified, thus allowing for an unchanged forward solution. The latter procedure introduces an additional residual term in the error estimation, accounting for the inconsistency between primal and dual problem.Finally, the effectivity of the extended error estimator, assessing the global error by a suitable functional of interest, is tested numerically; and the advantage over a formal estimator approach is demonstrated. (C) 2019 IMACS. Published by Elsevier B.V. All rights reserved.
机译:面向目标的网格适应,特别是使用双加权残差(DWR)方法,在许多情况下是已知的,以产生非常有效的网格。为了获得这种网格,需要伴随问题的(数值)解决方案对其对整体误差的相关性适当地重量残差。对于双曲线问题,已经缺乏原始问题需要一般需要额外的熵条件来断言解决方案的唯一性;当考虑涉及涉及不连续性的双曲线问题时,这种困难也被反映在再次需要额外的要求(可逆性)来选择合适的解决方案。在本文中,提出了一种基于人工粘度近似的双曲线问题DWR方法的方法。讨论了为什么所提出的方法提供了一个良好的双重问题,而直接,正式,应用的双重问题没有。此外,我们将讨论另一个新颖的方法,其中不需要修改前向问题,从而允许不变的前向解决方案。后一种程序在误差估计中引入了额外的残差项,占原始和双问题之间的不一致。最后,在数值上测试了扩展误差估计器的效果,评估全局误差,在数值上进行了测试;并且证明了正式估计方法的优势。 (c)2019 IMACS。由elsevier b.v出版。保留所有权利。

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