Superconvergnce analysis of an energy-stable implicit scheme with variable time steps and anisotropic spatial nonconforming finite elements for the nonlinear Sobolev equations

IF 2.5 2区 数学 Q1 MATHEMATICS, APPLIED Computers & Mathematics with Applications Pub Date : 2025-03-10 DOI:10.1016/j.camwa.2025.03.002
Lifang Pei , Ruixue Li , Jiwei Zhang , Yanmin Zhao
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Abstract

A fully discrete implicit scheme is presented and analyzed for the nonlinear Sobolev equations, which combines an anisotropic spatial nonconforming FEM with the variable-time-step BDF2 such that nonuniform meshes can be adopted in both time and space simultaneously. We prove that the fully discrete scheme is uniquely solvable, possesses the modified discrete energy dissipation law, and achieves second-order accuracy in both temporal and spatial directions under mild meshes conditions (adjacent time-step ratio condition 0<rn:=τnτn1<rmax4.8645 and anisotropic space meshes). The analysis approach involves a priori boundedness of the finite element solution, anisotropic properties of the element, energy projection error, DOC kernels and a modified discrete Grönwall inequality. Theoretical results reveal that the error in H1-norm is sharp in time and optimal or even superconvergent in space. Abundant numerical experiments verify the theoretical results, and demonstrate the efficiency and accuracy of the proposed fully discrete scheme.
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非线性Sobolev方程各向异性空间非协调有限元变时间步长能量稳定隐式格式的超收敛分析
提出并分析了非线性Sobolev方程的全离散隐式格式,该格式将各向异性空间非协调有限元法与变时间步长BDF2相结合,使非均匀网格可以在时间和空间上同时采用。在温和网格条件下(相邻时步比条件0<;rn:=τnτn−1<rmax≈4.8645和各向异性空间网格),证明了全离散格式是唯一可解的,具有改进的离散能量耗散规律,在时间和空间方向上都达到了二阶精度。该分析方法涉及有限元解的先验有界性、单元的各向异性、能量投影误差、DOC核和一个修正的离散Grönwall不等式。理论结果表明,h1 -范数误差在时间上是尖锐的,在空间上是最优甚至超收敛的。大量的数值实验验证了理论结果,并证明了所提出的全离散格式的有效性和准确性。
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来源期刊
Computers & Mathematics with Applications
Computers & Mathematics with Applications 工程技术-计算机:跨学科应用
CiteScore
5.10
自引率
10.30%
发文量
396
审稿时长
9.9 weeks
期刊介绍: Computers & Mathematics with Applications provides a medium of exchange for those engaged in fields contributing to building successful simulations for science and engineering using Partial Differential Equations (PDEs).
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