非光滑抛物型偏微分方程的自适应认证时空还原基方法

IF 1.7 3区 数学 Q2 MATHEMATICS, APPLIED
Marco Bernreuther, Stefan Volkwein
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引用次数: 0

摘要

本文考虑了一个非光滑半线性抛物线偏微分方程(PDE)。在还原基(RB)方法中,使用时空公式开发了一个经过认证的后验误差估计器。该误差估计器采用离散经验插值法(DEIM)作为非光滑性的近似技术。然后,将估计误差分为 RB 和 DEIM 两部分的可分离性指导了自适应 RB-DEIM 算法的开发,将两个离线阶段合二为一。数值实验表明,与传统的 RB 和 RB-DEIM 方法相比,这种新方法具有更强的能力。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An adaptive certified space-time reduced basis method for nonsmooth parabolic partial differential equations

In this paper, a nonsmooth semilinear parabolic partial differential equation (PDE) is considered. For a reduced basis (RB) approach, a space-time formulation is used to develop a certified a-posteriori error estimator. This error estimator is adopted to the presence of the discrete empirical interpolation method (DEIM) as approximation technique for the nonsmoothness. The separability of the estimated error into an RB and a DEIM part then guides the development of an adaptive RB-DEIM algorithm, combining both offline phases into one. Numerical experiments show the capabilities of this novel approach in comparison with classical RB and RB-DEIM approaches.

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来源期刊
CiteScore
3.00
自引率
5.90%
发文量
68
审稿时长
3 months
期刊介绍: Advances in Computational Mathematics publishes high quality, accessible and original articles at the forefront of computational and applied mathematics, with a clear potential for impact across the sciences. The journal emphasizes three core areas: approximation theory and computational geometry; numerical analysis, modelling and simulation; imaging, signal processing and data analysis. This journal welcomes papers that are accessible to a broad audience in the mathematical sciences and that show either an advance in computational methodology or a novel scientific application area, or both. Methods papers should rely on rigorous analysis and/or convincing numerical studies.
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