亥姆霍兹方程HDG离散化的最小残差后验误差估计

IF 6.9 1区 工程技术 Q1 ENGINEERING, MULTIDISCIPLINARY
Liliana Camargo , Sergio Rojas , Patrick Vega
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引用次数: 0

摘要

提出并分析了Helmholtz方程的杂化不连续伽辽金(HDG)离散化的两个后验误差指标。这些指标的建立是为了最小化与原始变量的局部超收敛后处理方案相关的残差,在扩大的离散测试空间的对偶范数中测量。残差最小化问题被重新表述为等价的局部鞍点问题,在渐近区域内得到原始变量的一个超收敛的后处理近似,得到足够正则的精确解,并以最小的计算量得到一个内置残差表示。这两个误差指标都基于频率相关的后处理方案,并验证了未知标量的频率加权h1误差和通量的l2误差的可靠性和效率估计。我们通过特别数值实验来说明我们的理论发现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Minimum-residual a posteriori error estimates for HDG discretizations of the Helmholtz equation
We propose and analyze two a posteriori error indicators for hybridizable discontinuous Galerkin (HDG) discretizations of the Helmholtz equation. These indicators are built to minimize the residual associated with a local superconvergent postprocessing scheme for the primal variable, measured in a dual norm of an enlarged discrete test space. The residual minimization is reformulated into equivalent local saddle-point problems, yielding a superconvergent postprocessed approximation of the primal variable in the asymptotic regime for sufficiently regular exact solutions and a built-in residual representation with minimal computational effort. Both error indicators are based on frequency-dependent postprocessing schemes and verify reliability and efficiency estimates for a frequency-weighted H1-error for the scalar unknown and the L2-error for the flux. We illustrate our theoretical findings through ad-hoc numerical experiments.
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来源期刊
CiteScore
12.70
自引率
15.30%
发文量
719
审稿时长
44 days
期刊介绍: Computer Methods in Applied Mechanics and Engineering stands as a cornerstone in the realm of computational science and engineering. With a history spanning over five decades, the journal has been a key platform for disseminating papers on advanced mathematical modeling and numerical solutions. Interdisciplinary in nature, these contributions encompass mechanics, mathematics, computer science, and various scientific disciplines. The journal welcomes a broad range of computational methods addressing the simulation, analysis, and design of complex physical problems, making it a vital resource for researchers in the field.
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