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Abstract(s)
The method of fundamental solutions (MFS) is a numerical method for solving
boundary value problems involving linear partial differential equations. It is
well known that it can be very effective assuming regularity of the domain and
boundary conditions. The main drawback of the MFS is that the matrices involved
typically are ill-conditioned and this may prevent to achieve high accuracy.
In this work, we propose a new algorithm to remove the ill conditioning of
the classical MFS in the context of Laplace equation defined in planar domains.
The main idea is to expand the MFS basis functions in terms of harmonic
polynomials. Then, using the singular value decomposition and Arnoldi
orthogonalization we define well conditioned basis functions spanning the same
functional space as the MFS's. Several numerical examples show that this
approach is much superior to previous approaches, such as the classical MFS or
the MFS-QR.
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Springer