Abstract
In this paper, we propose and investigate a new preconditioning technique for diffusion problems with multiple small size high contrast inclusions. The inclusions partitioned into two groups. In the first group inclusions the value of diffusion coefficient can be very small, and in the inclusions of the second group it can be very large. The classical P1 finite element discretization is converted in the special algebraic saddle point system. The solution method combines elimination of the DOFs from the first group of inclusions with the Preconditioned Lanczos method with block diagonal preconditioner for the rest of the DOFs. Condition number estimates for the proposed preconditioner are given.
Acknowledgment
The author is grateful to V. K. Kramarenko for his assistance in the preparation of the paper.
References
[1] R. Bellman, Introduction to matrix analysis (2nd ed.), Society for Industrial and Applied Mathematics Philadelphia, PA, USA, 1997.Suche in Google Scholar
[2] S. Brenner and L. R. Scott, The Mathematical Theory of Finite Element Methods. Springer, New York, 2008.10.1007/978-0-387-75934-0Suche in Google Scholar
[3] Y. Gorb, D. Kurzanova, and Yu. Kuznetsov, A Robust Preconditioner for High-Contrast Problems. ArXiv:1801.01578, 2018.10.1007/978-3-030-42687-3_19Suche in Google Scholar
[4] Y. Gorb, V. Kramarenko and Yu. Kuznetsov, Preconditioned iterative methods for diffusion problems with high-contrast inclusions, (submitted to J. Numer. Lin. Algebra Appl.).10.1002/nla.2243Suche in Google Scholar
[5] Yu. Kuznetsov, Efficient iterative solvers for elliptic finite element problems on nonmatching grids. Russ. J. Numer. Anal. Math. Modelling10 (1995), No. 3, 187–211.10.1515/rnam.1995.10.3.187Suche in Google Scholar
[6] Yu. Kuznetsov, New iterative methods for singular perturbed positive definite matrices. Russ. J. Numer. Anal. Math. Modelling15 (2000), No. 1, 65–71.10.1515/rnam.2000.15.1.65Suche in Google Scholar
[7] Yu. Kuznetsov, Preconditioned iterative methods for algebraic saddle-point problems. J. Numer. Math. 17 (2009), No. 1, 67–75.10.1515/JNUM.2009.005Suche in Google Scholar
[8] Yu. A. Kuznetsov, New homogenization method for diffusion equations. Russ. J. Numer. Anal. Math. Modelling33 (2018), No. 2, 85–93.10.1515/rnam-2018-0008Suche in Google Scholar
[9] G. Marchuk and Yu. Kuznetsov, Iterative methods and quadratic functionals. In: Méthodes de ľInformatique, Vol. -4 (Eds. J.-L. Lions and G. Marchuk) Paris, 1974, pp. 3–132.Suche in Google Scholar
[10] A. Toselli and O. Widlund, Domain decomposition methods — algorithms and theory. Springer Series in Computational Mathematics, Vol. 34. Springer-Verlag, Berlin, 2005.10.1007/b137868Suche in Google Scholar
[11] O. B. Widlund, An extension theorem for finite element spaces with three applications. In: Numerical Techniques in Continuum Mechanics. Notes on Numerical Fluid Mechanics, Vol. 16. 1987, pp. 110–122.10.1007/978-3-322-85997-6_11Suche in Google Scholar
© 2018 Walter de Gruyter GmbH, Berlin/Boston
Artikel in diesem Heft
- Frontmatter
- The approach of ‘successive approximations over characteristic interactions’ for inverse problems of nuclear-geophysical technologies
- Analysis of anticancer efficiency of combined fractionated radiotherapy and antiangiogenic therapy via mathematical modelling
- Preconditioning for diffusion problem with small size high resolution inclusions
- Comparative analysis of vector algorithms for statistical modelling of polarized radiative transfer process
Artikel in diesem Heft
- Frontmatter
- The approach of ‘successive approximations over characteristic interactions’ for inverse problems of nuclear-geophysical technologies
- Analysis of anticancer efficiency of combined fractionated radiotherapy and antiangiogenic therapy via mathematical modelling
- Preconditioning for diffusion problem with small size high resolution inclusions
- Comparative analysis of vector algorithms for statistical modelling of polarized radiative transfer process