二阶边值问题系统的非连续伽勒金方法的超收敛性分析

IF 1.9 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
H. Temimi
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引用次数: 0

摘要

在本文中,我们提出了一种解决边界值问题(BVPs)系统的创新方法,即使用新开发的非连续伽勒金(DG)方法,该方法无需辅助变量。这是关于将 DG 方法应用于偏微分方程 (PDE) 的系列论文中的第一篇。通过使用线段法对偏微分方程的每个空间变量连续应用 DG 方法,我们将问题转化为常微分方程(ODE)系统。我们研究了 DG 方法对 ODE 系统的收敛标准,并将误差分析推广到 PDE。我们的分析表明,DG 误差的前导项是由每个元素中特定雅可比多项式的组合决定的。因此,我们证明 DG 解在这些多项式的根上是超收敛的,收敛阶数为 O(hp+2)。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Superconvergence Analysis of Discontinuous Galerkin Methods for Systems of Second-Order Boundary Value Problems
In this paper, we present an innovative approach to solve a system of boundary value problems (BVPs), using the newly developed discontinuous Galerkin (DG) method, which eliminates the need for auxiliary variables. This work is the first in a series of papers on DG methods applied to partial differential equations (PDEs). By consecutively applying the DG method to each space variable of the PDE using the method of lines, we transform the problem into a system of ordinary differential equations (ODEs). We investigate the convergence criteria of the DG method on systems of ODEs and generalize the error analysis to PDEs. Our analysis demonstrates that the DG error’s leading term is determined by a combination of specific Jacobi polynomials in each element. Thus, we prove that DG solutions are superconvergent at the roots of these polynomials, with an order of convergence of O(hp+2).
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来源期刊
Computation
Computation Mathematics-Applied Mathematics
CiteScore
3.50
自引率
4.50%
发文量
201
审稿时长
8 weeks
期刊介绍: Computation a journal of computational science and engineering. Topics: computational biology, including, but not limited to: bioinformatics mathematical modeling, simulation and prediction of nucleic acid (DNA/RNA) and protein sequences, structure and functions mathematical modeling of pathways and genetic interactions neuroscience computation including neural modeling, brain theory and neural networks computational chemistry, including, but not limited to: new theories and methodology including their applications in molecular dynamics computation of electronic structure density functional theory designing and characterization of materials with computation method computation in engineering, including, but not limited to: new theories, methodology and the application of computational fluid dynamics (CFD) optimisation techniques and/or application of optimisation to multidisciplinary systems system identification and reduced order modelling of engineering systems parallel algorithms and high performance computing in engineering.
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