A priori and a posteriori error analysis for semilinear problems in liquid crystals

IF 1.9 3区 数学 Q2 Mathematics
N. Nataraj, A. Majumdar, Ruma Rani Maity
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引用次数: 0

Abstract

In this paper, we develop a unified framework for the a priori and a posteriori error control of different lowest-order finite element methods for approximating the regular solutions of systems of partial differential equations under a set of hypotheses. The systems involve cubic nonlinearities in lower order terms, non-homogeneous Dirichlet boundary conditions, and the results are established under minimal regularity assumptions on the exact solution. The key contributions include (i) results for existence and local uniqueness of the discrete solutions using Newton-Kantorovich theorem, (ii) a priori error estimates in the energy norm, and (iii) a posteriori error estimates that steer the adaptive refinement process. The results are applied to conforming, Nitsche, discontinuous Galerkin, and weakly over penalized symmetric interior penalty schemes for variational models of ferronematics and nematic liquid crystals. The theoretical estimates are corroborated by substantive numerical results.
液晶半线性问题的先验和后验误差分析
在本文中,我们建立了一个统一的框架,用于在一组假设下逼近偏微分方程组正则解的各种最低阶有限元方法的先验和事后误差控制。该系统涉及低阶三次非线性,非齐次Dirichlet边界条件,结果是在精确解的最小正则性假设下建立的。主要贡献包括(i)使用牛顿-坎托洛维奇定理得到离散解的存在性和局部唯一性的结果,(ii)能量范数的先验误差估计,以及(iii)引导自适应改进过程的后验误差估计。结果适用于铁流体和向列流体变分模型的符合、Nitsche、不连续Galerkin和弱过惩罚对称内惩罚格式。理论估计得到了大量数值结果的证实。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
2.70
自引率
5.30%
发文量
27
审稿时长
6-12 weeks
期刊介绍: M2AN publishes original research papers of high scientific quality in two areas: Mathematical Modelling, and Numerical Analysis. Mathematical Modelling comprises the development and study of a mathematical formulation of a problem. Numerical Analysis comprises the formulation and study of a numerical approximation or solution approach to a mathematically formulated problem. Papers should be of interest to researchers and practitioners that value both rigorous theoretical analysis and solid evidence of computational relevance.
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