DocumentCode :
3296669
Title :
Parametric model order reduction accelerated by subspace recycling
Author :
Feng, Lihong ; Benner, Peter ; Korvink, Jan G.
Author_Institution :
Dept. of Microsyst. Eng. (IMTEK), Univ. of Freiburg, Freiburg, Germany
fYear :
2009
fDate :
15-18 Dec. 2009
Firstpage :
4328
Lastpage :
4333
Abstract :
Many model order reduction methods for parameterized systems need to construct a projection matrix V which requires computing several moment matrices of the parameterized systems. For computing each moment matrix, the solution of a linear system with multiple right-hand sides is required. Furthermore, the number of linear systems increases with both the number of moment matrices used and the number of parameters in the system. Usually, a considerable number of linear systems has to be solved when the system includes more than two parameters. The standard way of solving these linear systems in case sparse direct solvers are not feasible is to use conventional iterative methods such as GMRES or CG. In this paper, a fast recycling algorithm is applied to solve the whole sequence of linear systems and is shown to be much more efficient than the standard iterative solver GMRES as well as the newly proposed recycling method MKR-GMRES from. As a result, the computation of the reduced-order model can be significantly accelerated.
Keywords :
iterative methods; linear systems; reduced order systems; MKR-GMRES; iterative methods; linear system; moment matrices; parameterized systems; parametric model order reduction method; projection matrix; recycling algorithm; reduced order model; sparse direct solvers; subspace recycling; Acceleration; Character generation; Chemical technology; Equations; Iterative algorithms; Iterative methods; Linear systems; Parametric statistics; Recycling; Reduced order systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Decision and Control, 2009 held jointly with the 2009 28th Chinese Control Conference. CDC/CCC 2009. Proceedings of the 48th IEEE Conference on
Conference_Location :
Shanghai
ISSN :
0191-2216
Print_ISBN :
978-1-4244-3871-6
Electronic_ISBN :
0191-2216
Type :
conf
DOI :
10.1109/CDC.2009.5399717
Filename :
5399717
Link To Document :
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