Accurate reanalysis of structures by a preconditioned conjugate gradient method

A preconditioned conjugate gradient (PCG) method that is most suitable for reanalysis of structures is developed. The method presented provides accurate results efficiently. It is easy to implement and can be used in a wide range of applications, including non‐linear analysis and eigenvalue problems...

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Published inInternational journal for numerical methods in engineering Vol. 55; no. 2; pp. 233 - 251
Main Authors Kirsch, Uri, Kocvara, Michal, Zowe, Jochem
Format Journal Article
LanguageEnglish
Published Chichester, UK John Wiley & Sons, Ltd 20.09.2002
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Summary:A preconditioned conjugate gradient (PCG) method that is most suitable for reanalysis of structures is developed. The method presented provides accurate results efficiently. It is easy to implement and can be used in a wide range of applications, including non‐linear analysis and eigenvalue problems. It is shown that the PCG method presented and the combined approximations (CA) method developed recently provide theoretically identical results. Consequently, available results from one method can be applied to the other method. Effective solution procedures developed for the CA method can be used for the PCG method, and various criteria and error bounds developed for conjugate gradient methods can be used for the CA method. Numerical examples show that the condition number of the selected preconditioned matrix is much smaller than the condition number of the original matrix. This property explains the fast convergence and accurate results achieved by the method. Copyright © 2002 John Wiley & Sons, Ltd.
Bibliography:ark:/67375/WNG-PRKLTMFF-2
ArticleID:NME496
The Alexander von Humboldt Foundation
The Fund for the Promotion of Research at the Technion
Czech Academy of Sciences - No. 107500/00
istex:CCD59A683AE68A65807CEF9839094586FD1D1EF2
BMBF-project - No. 03ZOM3ER
On leave from the Czech Academy of Sciences.
ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0029-5981
1097-0207
DOI:10.1002/nme.496