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arXiv 1609.04437math.NAcs.NA

对奇异摄动问题的流线向上/皮尔逊-加尔金离散化的鲁棒后验误差估计器

Robust recovery-type a posteriori error estimators for streamline upwind/Petrov Galerkin discretizations for singularly perturbed problems

Chongqing Jiaotong University(重庆交通大学);Texas A&M International University(德州农工国际大学);Beijing Computational Science Research Center(北京计算科学研究中心);Wayne State University(韦恩州立大学)

Shaohong Du, Runchang Lin, Zhimin Zhang

AI总结:

本文研究了新的双范数下适应性流线向上/皮尔逊-加尔金方法,通过局部平均或加权全局L²投影恢复通量,并引入恢复稳定化过程,开发出对奇异摄动参数ε完全鲁棒的后验误差估计器。

摘要:

本文研究了新的双范数下适应性流线向上/皮尔逊-加尔金方法,通过局部平均或加权全局L²投影恢复通量,并引入恢复稳定化过程,开发出对奇异摄动参数ε完全鲁棒的后验误差估计器。数值实验支持了理论结果,并展示了估计误差与自由度无关地依赖于ε。

英文摘要:

In this paper, we investigate adaptive streamline upwind/Petrov Galerkin (SUPG) methods for singularly perturbed convection-diffusion-reaction equations in a new dual norm presented in [Du and Zhang, J. Sci. Comput. (2015)]. The flux is recovered by either local averaging in conforming $H({\rm div})$ spaces or weighted global $L^2$ projection onto conforming $H({\rm div})$ spaces. We further introduce a recovery stabilization procedure, and develop completely robust a posteriori error estimators with respect to the singular perturbation parameter $\varepsilon$. Numerical experiments are reported to support the theoretical results and to show that the estimated errors depend on the degrees of freedom uniformly in $\varepsilon$.

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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