A Dichotomy of Finite Element Spaces and Its Application to an Energy-Conservative Scheme for the Regularized Long Wave Equation

IF 3.2 2区 数学 Q1 MATHEMATICS, APPLIED
Dimitrios Antonopoulos, Dimitrios Mitsotakis
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引用次数: 0

Abstract

SIAM Journal on Numerical Analysis, Volume 64, Issue 5, Page 2079-2099, October 2026.
Abstract. Certain energy-conservative Galerkin discretizations for nonlinear dispersive wave equations have revealed an unusual convergence behavior: optimal convergence is attained when continuous Lagrange finite element spaces of odd polynomial degree are employed, whereas the use of even-degree polynomials leads to reduced convergence rate. The present work demonstrates that this behavior is intrinsic to the structure of the finite element spaces themselves. In particular, it is shown to be closely connected to the standard [math]-projection of derivatives, which possesses a super-approximation property exclusively for odd polynomial degrees. We also examine the implications of this feature for an energy-conservative Galerkin approximation of the regularized long-wave equation where the energy is a cubic functional. Although the resulting scheme conserves both mass and energy, we further show that the impulse is approximated with high accuracy, and we establish a priori error bounds for the associated semidiscrete formulation.
有限元空间的二分法及其在正则长波方程能量守恒格式中的应用
SIAM数值分析杂志,64卷,第5期,2079-2099页,2026年10月。摘要。非线性色散波动方程的能量保守伽辽金离散显示出一种不寻常的收敛行为:当使用奇数次多项式的连续拉格朗日有限元空间时,得到最优收敛,而使用偶数次多项式会导致收敛速度降低。目前的工作表明,这种行为是固有的有限元空间本身的结构。特别地,它被证明与导数的标准[数学]投影密切相关,它具有只对奇多项式次的超逼近性质。我们还研究了这一特征对能量为三次泛函的正则长波方程的能量保守伽辽金近似的含义。虽然所得到的格式既节省了质量又节省了能量,但我们进一步证明了脉冲的近似精度很高,并为相关的半离散公式建立了先验误差界。
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来源期刊
CiteScore
4.80
自引率
6.90%
发文量
110
审稿时长
4-8 weeks
期刊介绍: SIAM Journal on Numerical Analysis (SINUM) contains research articles on the development and analysis of numerical methods. Topics include the rigorous study of convergence of algorithms, their accuracy, their stability, and their computational complexity. Also included are results in mathematical analysis that contribute to algorithm analysis, and computational results that demonstrate algorithm behavior and applicability.
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