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Stable MFS Solution to Singular Direct and Inverse Problems Associated with the Laplace Equation Subjected to Noisy Data

LiviuMarin 1
Institute of Solid Mechanics, Romanian Academy, 15 Constantin Mille, Sector 1, PO Box 1-863, RO-010141 Bucharest, Romania. E-mail: marin.liviu@gmail. com

Computer Modeling in Engineering & Sciences 2008, 37(3), 203-242. https://doi.org/10.3970/cmes.2008.037.203

Abstract

In this paper, a meshless method for the stable solution of direct and inverse problems associated with the two-dimensional Laplace equation in the presence of boundary singularities and noisy boundary data is proposed. The governing equation and boundary conditions are discretized by the method of fundamental solutions (MFS), whilst the existence of the boundary singularity is taken into account by subtracting from the original MFS solution the corresponding singular solutions, as given by the asymptotic expansion of the solution near the singular point. However, even in the case when the boundary singularity is accounted for, the numerical solutions obtained by the direct inversion of the associated MFS linear algebraic system are still inaccurate and unstable. Therefore, the regularization of the aforementioned problems is required and this is realized by employing either the Tikhonov regularization method (TRM), or the singular value decomposition (SVD), with the corresponding optimal regularization parameter given by the L-curve method. Numerical experiments show that the proposed method is stable with respect to the noise added into the boundary data, highly accurate and computationally very efficient.

Keywords

Direct and Inverse Problems, Laplace Equation, Singularity Subtraction Technique (SST), Regularization, Method of Fundamental Solutions (MFS).

Cite This Article

, L. (2008). Stable MFS Solution to Singular Direct and Inverse Problems Associated with the Laplace Equation Subjected to Noisy Data. CMES-Computer Modeling in Engineering & Sciences, 37(3), 203–242.



This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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