Number of the records: 1
Comparison of preconditioned Krylov subspace iteration methods for PDE-constrained optimization problems
- 1.
SYSNO ASEP 0482333 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Comparison of preconditioned Krylov subspace iteration methods for PDE-constrained optimization problems Author(s) Axelsson, Owe (UGN-S) RID
Farouq, S. (SE)
Neytcheva, M. (SE)Number of authors 3 Source Title Numerical Algorithms. - : Springer - ISSN 1017-1398
Roč. 74, č. 1 (2017), s. 19-37Number of pages 19 s. Publication form Online - E Language eng - English Country NL - Netherlands Keywords PDE-constrained optimization problems ; finite elements ; iterative solution methods ; preconditioning Subject RIV BA - General Mathematics OECD category Applied mathematics Institutional support UGN-S - RVO:68145535 UT WOS 000391392300002 EID SCOPUS 84965082158 DOI 10.1007/s11075-016-0136-5 Annotation The governing dynamics of fluid flow is stated as a system of partial differential equations referred to as the Navier-Stokes system. In industrial and scientific applications, fluid flow control becomes an optimization problem where the governing partial differential equations of the fluid flow are stated as constraints. When discretized, the optimal control of the Navier-Stokes equations leads to large sparse saddle point systems in two levels. In this paper, we consider distributed optimal control for the Stokes system and test the particular case when the arising linear system can be compressed after eliminating the control function. In that case, a system arises in a form which enables the application of an efficient block matrix preconditioner that previously has been applied to solve complex-valued systems in real arithmetic. Under certain conditions, the condition number of the so preconditioned matrix is bounded by 2. The numerical and computational efficiency of the method in terms of number of iterations and execution time is favorably compared with other published methods. Workplace Institute of Geonics Contact Lucie Gurková, lucie.gurkova@ugn.cas.cz, Tel.: 596 979 354 Year of Publishing 2018 Electronic address https://link.springer.com/article/10.1007%2Fs11075-016-0136-5
Number of the records: 1