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arXiv 1011.0973math.NAcs.NA
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基于平均梯度恢复的间断Galerkin方法求解对流-扩散-反应问题的后验误差估计子

A posteriori error estimator based on gradient recovery by averaging for convection-diffusion-reaction problems approximated by discontinuous Galerkin methods

Université de Lille 1(里尔第一大学);INRIA Lille Nord Europe(法国国家信息与自动化研究所里尔北部分支);Université de Valenciennes et du Hainaut Cambrésis(瓦朗谢纳及康布雷埃斯海诺特大学)

Emmanuel Creusé, Serge Nicaise

AI总结:

针对间断Galerkin方法逼近的对流-扩散-反应问题,提出两种基于平均梯度恢复的后验误差估计子,并证明其可靠性和效率,数值实验验证了理论结果。

摘要:

我们考虑R2区域中某些(各向异性和分段常数)对流-扩散-反应问题,采用任意次多项式的间断Galerkin方法进行逼近。我们提出了两种基于平均梯度恢复的后验误差估计子。结果表明,这些估计子给出了一个上界,其中常数显式已知,直到一些额外的项,这些项保证了可靠性。下界也被建立,其中一种在对流项(或反应项)占主导时是鲁棒的。此外,当恢复的梯度是超收敛时,估计子是渐近精确的。数值测试证实了所提估计子的可靠性和效率。

英文摘要:

We consider some (anisotropic and piecewise constant) convection-diffusion-reaction problems in domains of R2, approximated by a discontinuous Galerkin method with polynomials of any degree. We propose two a posteriori error estimators based on gradient recovery by averaging. It is shown that these estimators give rise to an upper bound where the constant is explicitly known up to some additional terms that guarantees reliability. The lower bound is also established, one being robust when the convection term (or the reaction term) becomes dominant. Moreover, the estimator is asymptotically exact when the recovered gradient is superconvergent. The reliability and efficiency of the proposed estimators are confirmed by some numerical tests.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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