2011
DOI: 10.1016/j.finel.2010.08.009
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Fast approximation of synthesized frequency response functions with automated multi-level substructuring (AMLS)

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Cited by 4 publications
(5 citation statements)
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“…Due to its ability to quickly achieve dramatic reductions in the size of FE models, AMLS has been shown to be quite efficient in frequency response and eigenvalue analysis of real-world engineering problems. 7,[31][32][33][34][35] Nonetheless, the accuracy of the approximate eigenpairs returned by AMLS can be rather low for general algebraic eigenvalue problems. Moreover, as AMSLS is based on nested dissection, its suitability for execution on distributed memory computing environments is limited.…”
Section: Introductionmentioning
confidence: 99%
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“…Due to its ability to quickly achieve dramatic reductions in the size of FE models, AMLS has been shown to be quite efficient in frequency response and eigenvalue analysis of real-world engineering problems. 7,[31][32][33][34][35] Nonetheless, the accuracy of the approximate eigenpairs returned by AMLS can be rather low for general algebraic eigenvalue problems. Moreover, as AMSLS is based on nested dissection, its suitability for execution on distributed memory computing environments is limited.…”
Section: Introductionmentioning
confidence: 99%
“…Once the leaf substructures are reached, AMLS computes a number of eigenmodes from each substructure (e.g., those below a cut‐off threshold) and traverses the elimination tree in an upwards fashion, each time multiplying the interface eigenmodes at the current level with the corresponding block Gaussian elimination matrix. Due to its ability to quickly achieve dramatic reductions in the size of FE models, AMLS has been shown to be quite efficient in frequency response and eigenvalue analysis of real‐world engineering problems 7,31‐35 . Nonetheless, the accuracy of the approximate eigenpairs returned by AMLS can be rather low for general algebraic eigenvalue problems.…”
Section: Introductionmentioning
confidence: 99%
“…The low-frequency modes are extremal eigenvectors of a large and sparse generalized eigenvalue problem (GEP), associated with the free vibrations of the conservative system (no damping). In structural dynamics, the most widely-used eigenvalue solvers include the Lanczos algorithm [4][5][6][7][8][9][10], the subspace iteration method (SIM, [11][12][13][14][15]), the Craig-Bampton (CB, [16,17]) component mode synthesis (CMS, [14,[18][19][20][21]), and the automated multilevel substructuring (AMLS, [22][23][24][25][26]) solver. Dynamic substructuring [27][28][29][30][31] is another name for CMS.…”
Section: Introductionmentioning
confidence: 99%
“…This paper presents a new methodology that tackles this difficulty inherited from the multilevel nature of the structure. In structural dynamics, the prominent eigenvalue solvers include the Shift-Invert Lanczos (SIL [5,6]) solver, the Subspace Iteration Method (SIM [7,8]), Craig-Bampton (CB [9,10]) substructuring technique, and Automated Multilevel Substructuring (AMLS [11,12]). SIL and SIM are iterative solvers that converge to the true eigensolutions whereas CB and AMLS deliver approximate eigenso-lutions.…”
Section: Introductionmentioning
confidence: 99%