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Automatically well-conditioned collocation boundary element method for transmission problems based on the Burton--Miller formulation

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arxiv 2312.12787 v2 pith:ESUUHEKI submitted 2023-12-20 math.NA cs.NA

classification math.NAcs.NA
keywords boundaryintegralmethodproblemscollocationformulationmathsfoperator
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abstract

This paper proposes a collocation boundary element method based on the Burton--Miller method for solving transmission problems, which is rapidly convergent within the Krylov subspace solver framework. Our study enhances Burton--Miller-type boundary integral equations tailored for transmission problems by exploiting the Calderon formula. In cases where a single material exists in an unbounded host medium, we demonstrate the formulation of the boundary integral equation such that the underlying integral operator ${\cal A}$ is spectrally well-conditioned. Specifically, ${\cal A}$ can be designed such that ${\cal A}^2$ has only a single eigenvalue accumulation point. Furthermore, we extend this to the multi-material case, proving that the square of the proposed operator has only a few eigenvalues clustering points. When the collocation method is used to discretise the proposed boundary integral equations, the good spectral properties of the integral operator are naturally inherited to the coefficient matrix $\mathsf{A}$ similarly to the Nyst\"om methods; Almost all eigenvalues of $\mathsf{A}^2$ cluster at a few points in the complex plane ensuring the small condition number for $\mathsf{A}$. Through numerical examples of several benchmark problems, we illustrate that our formulation reduces the iteration number required by iterative linear solvers, even in the presence of material junction points.

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  1. Point Jacobi-type preconditioning and parameter tuning for Calderon-preconditioned Burton-Miller method in transmission problems

    math.NA 2025-06 conditional novelty 6.0 of 10

    A new analytic formula for eigenvalue cluster points enables a nearly free diagonal preconditioner and parameter tuning that reduces GMRES iterations in high-contrast 3D transmission problems.

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