DocumentCode
808951
Title
A Newton-Raphson algorithm with adaptive accuracy control based on a block-preconditioned conjugate gradient technique
Author
Badics, Zsolt ; Cendes, Zoltan J.
Author_Institution
Ansoft Corp., Pittsburgh, PA, USA
Volume
41
Issue
5
fYear
2005
fDate
5/1/2005 12:00:00 AM
Firstpage
1652
Lastpage
1655
Abstract
A fast Newton-Raphson algorithm is developed for the finite-element solution of nonlinear boundary value problems. The linearized equation systems in the nonlinear iteration steps are solved by a block-preconditioned conjugate gradient (CG) technique, in which the stopping criterion of the CG iteration is adaptively controlled by the nonlinear residual error. The Jacobian matrix is partitioned into linear and nonlinear blocks, thereby allowing the relatively rapid generation of an efficient multiplicative preconditioner for the CG iteration. The results obtained for a magnetostatic and a coupled steady conduction-static thermal problem confirm the effectiveness of the algorithm.
Keywords
Jacobian matrices; Newton-Raphson method; adaptive control; boundary-value problems; computational electromagnetics; conjugate gradient methods; finite element analysis; magnetic fields; polynomial approximation; Jacobian matrix; Newton-Krylov method; Newton-Raphson algorithm; adaptive control; conduction-static thermal problem; conjugate gradient technique; finite element solution; linear equation systems; nonlinear boundary value problems; nonlinear differential equations; nonlinear iteration steps; nonlinear residual error; Adaptive control; Boundary value problems; Character generation; Control systems; Error correction; Finite element methods; Jacobian matrices; Nonlinear control systems; Nonlinear equations; Programmable control; Adaptive control; Newton–Krylov method; Newton–Raphson method; conjugate gradient (CG) methods; nonlinear differential equations;
fLanguage
English
Journal_Title
Magnetics, IEEE Transactions on
Publisher
ieee
ISSN
0018-9464
Type
jour
DOI
10.1109/TMAG.2005.846103
Filename
1430932
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