二维Monge–Ampère方程正则化有限元离散化的收敛性

IF 2.2 2区 数学 Q1 MATHEMATICS, APPLIED
D. Gallistl, Ngoc Tien Tran
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引用次数: 0

摘要

利用一致椭圆Hamilton-Jacobi-Bellman方程,提出了平面凸域上monge - amp方程的正则化方法。正则化问题具有唯一的强解u ε u_\varepsilon,可以用有限元进行离散化。本文建立了当正则化参数ε \varepsilon趋近于0时,u ε u_\varepsilon对monge - ampontre方程的凸Alexandrov解u u的一致收敛性。提出了一种混合有限元逼近u ε u_\varepsilon的方法,并证明了正则化有限元格式是一致收敛的。可容许的右手边是那些可以用l1l ^1范数中的正连续函数从下逼近的函数。数值实验为奇异解的有效逼近提供了经验证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Convergence of a regularized finite element discretization of the two-dimensional Monge–Ampère equation

This paper proposes a regularization of the Monge–Ampère equation in planar convex domains through uniformly elliptic Hamilton–Jacobi–Bellman equations. The regularized problem possesses a unique strong solution u ε u_\varepsilon and is accessible to the discretization with finite elements. This work establishes uniform convergence of u ε u_\varepsilon to the convex Alexandrov solution u u to the Monge–Ampère equation as the regularization parameter ε \varepsilon approaches 0 0 . A mixed finite element method for the approximation of u ε u_\varepsilon is proposed, and the regularized finite element scheme is shown to be uniformly convergent. The class of admissible right-hand sides are the functions that can be approximated from below by positive continuous functions in the L 1 L^1 norm. Numerical experiments provide empirical evidence for the efficient approximation of singular solutions u u .

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来源期刊
Mathematics of Computation
Mathematics of Computation 数学-应用数学
CiteScore
3.90
自引率
5.00%
发文量
55
审稿时长
7.0 months
期刊介绍: All articles submitted to this journal are peer-reviewed. The AMS has a single blind peer-review process in which the reviewers know who the authors of the manuscript are, but the authors do not have access to the information on who the peer reviewers are. This journal is devoted to research articles of the highest quality in computational mathematics. Areas covered include numerical analysis, computational discrete mathematics, including number theory, algebra and combinatorics, and related fields such as stochastic numerical methods. Articles must be of significant computational interest and contain original and substantial mathematical analysis or development of computational methodology.
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