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- W286383822 abstract "Abstract Model order reduction techniques are well established in control theory and likewise in structural mechanics, e.g. when dealing with Elastic Multi-Body-Systems. Apart from the reduction method used, the objective lies in finding a minimal reliable model dimension with desired quality. Extensive research has been conducted concerning Krylov-subspace methods. Rational Krylov-subspace methods based on the second-order Arnoldi-algorithm (SOAR) turned out to give promising results. Current investigations are about generating an optimal reduced model by iteratively choosing the expansion points based on a predefined model dimension. Still, the sufficient choice of this initial dimension is uncertain. The novel approach consists of a two-stage strategy and starts with a fairly large reduced model based on a fixed number and distribution of expansion points. By an iterative posttreatment, the dispensable Krylov-modes are truncated. For an efficient and fast calculation, a special reordering scheme for the Krylov-modes is introduced. Numerical experiments at different mechanical models show, that the novel technique is comparatively fast and confidently generates reliable models with a minimal dimension." @default.
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- W286383822 date "2015-01-01" @default.
- W286383822 modified "2023-09-24" @default.
- W286383822 title "Improvement of Krylov-Subspace-Reduced Models by Iterative Mode-Truncation" @default.
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- W286383822 doi "https://doi.org/10.1016/j.ifacol.2015.05.030" @default.
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