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Product Algebras for Galerkin Discretisations of Boundary Integral Operators and their Applications

Published:20 March 2020Publication History
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Abstract

Operator products occur naturally in a range of regularised boundary integral equation formulations. However, while a Galerkin discretisation only depends on the domain space and the test (or dual) space of the operator, products require a notion of the range. In the boundary element software package Bempp, we have implemented a complete operator algebra that depends on knowledge of the domain, range, and test space. The aim was to develop a way of working with Galerkin operators in boundary element software that is as close to working with the strong form on paper as possible, while hiding the complexities of Galerkin discretisations. In this article, we demonstrate the implementation of this operator algebra and show, using various Laplace and Helmholtz example problems, how it significantly simplifies the definition and solution of a wide range of typical boundary integral equation problems.

References

  1. SciPy. [n.d.]. Retrieved from www.scipy.org.Google ScholarGoogle Scholar
  2. Timo Betcke, Alexander Haberl, and Dirk Praetorius. 2019. Adaptive boundary element methods for the computation of the electrostatic capacity on complex polyhedra. J. Comput. Phys. 397 (2019), 108837. DOI:https://doi.org/10.1016/j.jcp.2019.07.036Google ScholarGoogle ScholarCross RefCross Ref
  3. Timo Betcke, Elwin van ’t Wout, and Pierre Gélat. 2017. Computationally efficient boundary element methods for high-frequency Helmholtz problems in unbounded domains. In Modern Solvers for Helmholtz Problems. Springer, 215--243.Google ScholarGoogle Scholar
  4. Annalisa Buffa and Snorre H. Christiansen. 2007. A dual finite element complex on the barycentric refinement. Math. Comp. 76 (2007), 1743--1769.Google ScholarGoogle ScholarCross RefCross Ref
  5. S. N. Chandler-Wilde, D. P. Hewett, and A. Moiola. 2017. Sobolev spaces on non-lipschitz subsets of Rn with application to boundary integral equations on fractal screens. Integr. Equat. Operat. Theory 87, 2 (1 Feb 2017), 179--224.Google ScholarGoogle Scholar
  6. Philippe G. Ciarlet. 2013. Linear and Nonlinear Functional Analysis with Applications. Society for Industrial and Applied Mathematics, Philadelphia, PA.Google ScholarGoogle Scholar
  7. Xavier Claeys and Ralf Hiptmair. 2013. Multi-trace boundary integral formulation for acoustic scattering by composite structures. Commun. Pure Appl. Math. 66, 8 (2013), 1163--1201.Google ScholarGoogle ScholarCross RefCross Ref
  8. Martin Costabel and Ernst Stephan. 1985. A direct boundary integral equation method for transmission problems. J. Math. Anal. Appl. 106, 2 (1985), 367--413.Google ScholarGoogle ScholarCross RefCross Ref
  9. L. Greengard and V. Rokhlin. 1987. A fast algorithm for particle simulations. J. Comput. Phys. 73, 2 (1987), 325--348.Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. Wolfgang Hackbusch. 2015. Hierarchical Matrices: Algorithms and Analysis. Springer Series in Computational Mathematics, Vol. 49. Springer, Heidelberg.Google ScholarGoogle ScholarCross RefCross Ref
  11. Mohamed Ali Hamdi. 1981. Une formulation variationnelle par équations intégrales pour la résolution de l’équation de Helmholtz avec des conditions aux limites mixtes. CR Acad. Sci. Paris, série II 292 (1981), 17--20.Google ScholarGoogle Scholar
  12. R. Hiptmair. 2006. Operator preconditioning. Comput. Math. Appl. 52, 5 (sep 2006), 699--706.Google ScholarGoogle ScholarCross RefCross Ref
  13. Robert C. Kirby. 2010. From functional analysis to iterative methods. SIAM Rev. 52, 2 (2010), 269--293.Google ScholarGoogle ScholarDigital LibraryDigital Library
  14. R. Lipton, D. Rose, and R. Tarjan. 1979. Generalized nested dissection. SIAM J. Numer. Anal. 16, 2 (1979), 346--358.Google ScholarGoogle ScholarDigital LibraryDigital Library
  15. J. C. Nedelec. 1982. Integral equations with non integrable kernels. Integr. Equat. Operat. Theory 5, 1 (1 Dec 1982), 562--572.Google ScholarGoogle Scholar
  16. Stefan A. Sauter and Christoph Schwab. 2011. Boundary Element Methods. Springer Series in Computational Mathematics, Vol. 39. Springer-Verlag, Berlin.Google ScholarGoogle Scholar
  17. Matthew W. Scroggs, Timo Betcke, Erik Burman, Wojciech Śmigaj, and Elwin van ’t Wout. 2017. Software frameworks for integral equations in electromagnetic scattering based on Calderón identities. Comput. Math. Appl. 74, 11 (2017), 2897--2914. DOI:https://doi.org/10.1016/j.camwa.2017.07.049Google ScholarGoogle ScholarDigital LibraryDigital Library
  18. Wojciech Śmigaj, Timo Betcke, Simon Arridge, Joel Phillips, and Martin Schweiger. 2015. Solving boundary integral problems with BEM++. ACM Trans. Math. Software 41, 2 (2015), 1--40.Google ScholarGoogle ScholarDigital LibraryDigital Library
  19. Olaf Steinbach. 2008. Numerical Approximation Methods for Elliptic Boundary Value Problems. Springer, New York.Google ScholarGoogle Scholar
  20. O. Steinbach and W. L. Wendland. 1998. The construction of some efficient preconditioners in the boundary element method. Adv. Comput. Math. 9, 1–2 (1998), 191--216.Google ScholarGoogle ScholarCross RefCross Ref

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  1. Product Algebras for Galerkin Discretisations of Boundary Integral Operators and their Applications

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          cover image ACM Transactions on Mathematical Software
          ACM Transactions on Mathematical Software  Volume 46, Issue 1
          March 2020
          214 pages
          ISSN:0098-3500
          EISSN:1557-7295
          DOI:10.1145/3387915
          Issue’s Table of Contents

          Copyright © 2020 ACM

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          Publication History

          • Published: 20 March 2020
          • Accepted: 1 October 2019
          • Revised: 1 June 2019
          • Received: 1 June 2018
          Published in toms Volume 46, Issue 1

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