DocumentCode :
3244532
Title :
A preconditioner construction for domain decomposition analysis of large scale 3D magnetostatic problems
Author :
Kanayama, Hiroshi ; Ogino, Masao ; Sugimoto, Shin-ichiro ; Yao, Qinghe
Author_Institution :
Grad. Sch. of Eng., Kyushu Univ., Fukuoka, Japan
fYear :
2011
fDate :
19-21 April 2011
Firstpage :
1
Lastpage :
4
Abstract :
An iterative domain decomposition method is applied to numerical analysis of 3-dimensional (3D) linear magnetostatic problems taking the magnetic vector potential as an unknown function. The iterative domain decomposition method is combined with the Preconditioned Conjugate Gradient (PCG) procedure and the Hierarchical Domain Decomposition Method (HDDM) which is adopted in parallel computing. Our previously employed preconditioner was the Neumann-Neumann method. Numerical results showed that the method was only effective for smaller problems. In this paper, we consider its improvement with the Balancing Domain Decomposition (BDD) preconditioner.
Keywords :
conjugate gradient methods; iterative methods; magnetostatics; 3D linear magnetostatic problems; Neumann-Neumann method; balancing domain decomposition preconditioner; domain decomposition analysis; hierarchical domain decomposition method; iterative domain decomposition method; large scale 3D magnetostatic problems; magnetic vector potential; numerical analysis; parallel computing; preconditioned conjugate gradient procedure; preconditioner construction; Boolean functions; Data structures; Finite element methods; Magnetic analysis; Magnetic domains; Magnetostatics; Three dimensional displays; Large scale magnetostatic problems; domain decomposition method; the Neumann-Neumann preconditioner; the balancing domain decomposition preconditioner;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Modeling, Simulation and Applied Optimization (ICMSAO), 2011 4th International Conference on
Conference_Location :
Kuala Lumpur
Print_ISBN :
978-1-4577-0003-3
Type :
conf
DOI :
10.1109/ICMSAO.2011.5775641
Filename :
5775641
Link To Document :
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