On the discretization of Laplace's equation with Neumann boundary conditions on polygonal domains

Jeremy Hoskins , Manas Rachh
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引用次数: 2

Abstract

In the present paper we describe a class of algorithms for the solution of Laplace's equation on polygonal domains with Neumann boundary conditions. It is well known that in such cases the solutions have singularities near the corners which poses a challenge for many existing methods. If the boundary data is smooth on each edge of the polygon, then in the vicinity of each corner the solution to the corresponding boundary integral equation has an expansion in terms of certain (analytically available) singular powers. Using the known behavior of the solution, universal discretizations have been constructed for the solution of the Dirichlet problem. However, the leading order behavior of solutions to the Neumann problem is O(tμ) for μ(1/2,1/2) depending on the angle at the corner (compared to O(C+tμ) with μ>1/2 for the Dirichlet problem); this presents a significant challenge in the design of universal discretizations. Our approach is based on using the discretization for the Dirichlet problem in order to compute a solution in the “weak sense” by solving an adjoint linear system; namely, it can be used to compute inner products with smooth functions accurately, but it cannot be interpolated. Furthermore we present a procedure to obtain accurate solutions arbitrarily close to the corner, by solving a sequence of small local subproblems in the vicinity of that corner. The results are illustrated with several numerical examples.

关于多边形域上具有Neumann边界条件的拉普拉斯方程的离散化
本文描述了一类求解具有Neumann边界条件的多边形域上拉普拉斯方程的算法。众所周知,在这种情况下,解在拐角附近具有奇点,这对许多现有方法构成了挑战。如果边界数据在多边形的每条边上都是平滑的,那么在每个角的附近,对应边界积分方程的解具有某些(解析可用的)奇异幂的展开式。利用解的已知行为,构造了Dirichlet问题解的通用离散化。然而,对于μ∈(−1/2,1/2),Neumann问题解的前导阶行为是O(tμ),这取决于角处的角度(与μ>;Dirichlet问题的1/2);这对通用离散化的设计提出了重大挑战。我们的方法基于对狄利克雷问题使用离散化,以便通过求解伴随线性系统来计算“弱意义”上的解;也就是说,它可以精确地计算光滑函数的内积,但不能插值。此外,我们提出了一个程序,通过求解拐角附近的一系列小局部子问题,获得任意接近拐角的精确解。通过几个数值例子说明了结果。
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
Journal of Computational Physics: X
Journal of Computational Physics: X Physics and Astronomy-Physics and Astronomy (miscellaneous)
CiteScore
6.10
自引率
0.00%
发文量
7
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