Improving eigenpairs of automated multilevel substructuring with subspace iterations

Publikationstyp
Journal Article
Date Issued
2013-02-28
Sprache
English
Author(s)
Yin, Jiacong  
Voß, Heinrich 
Chen, Pu  
Institut
Mathematik E-10  
TORE-URI
http://hdl.handle.net/11420/6911
Journal
Computers & structures  
Volume
119
Start Page
115
End Page
124
Citation
Computers and Structures (119): 115-124 (2013)
Publisher DOI
10.1016/j.compstruc.2013.01.004
Scopus ID
2-s2.0-84874706167
Publisher
Elsevier
This paper improves the eigenpair approximations obtained from the automated multilevel substructuring (AMLS) method by subspace iterations. Two variants of AMLS hybrid Subspace Iteration Method (AMLS-SIMa and AMLS-SIMb) are proposed. AMLS-SIMa is a derivative of the basic subspace iteration by utilizing the AMLS approximations as initial vectors. AMLS-SIMb further takes advantage of the AMLS transformed block diagonal stiffness matrix to avoid factorization of the original stiffness matrix. Numerical experiments show that: (a) the error of AMLS approximate eigenpairs can be significantly reduced with just a few iteration steps; (b) AMLS-SIMb is more efficient than AMLS-SIMa with less execution time.
Subjects
AMLS
Eigenvalue
Eigenvector
Subspace iteration
DDC Class
004: Informatik
510: Mathematik