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INTERMEDIATE REDUCTION STEPS IMPROVE AUTOMATED MULTI-LEVEL SUBSTRUCTURING
BibTeX
@MISC{Elssel_intermediatereduction,
author = {K. Elssel and H. Voss},
title = {INTERMEDIATE REDUCTION STEPS IMPROVE AUTOMATED MULTI-LEVEL SUBSTRUCTURING},
year = {}
}
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Abstract
The Automated Multi-Level Substructuring (AMLS) method has been developed to reduce the computational demands of frequency response analysis and has recently been proposed as an alternative to iterative projection methods like Lanczos or Jacobi– Davidson for computing a large number of eigenvalues for matrices of very large di-mension. Based on Schur complements and modal approximations of submatrices on several levels AMLS constructs a projected eigenproblem which yields good approx-imations of eigenvalues at the lower end of the spectrum. In this paper we reduce the cost of AMLS introducing intermediate reduction steps. The efficiency of this approach is demonstrated by a huge gyroscopic eigenvalue problem modelling the dynamic behaviour of a rotating tyre.
Keyphrases
dynamic behaviour frequency response analysis yield good approx-imations huge gyroscopic eigenvalue problem several level amls large di-mension jacobi davidson schur complement computational demand large number intermediate reduction step iterative projection method automated multi-level substructuring modal approximation
