Towards an Optimal Substructuring Method for Model Reduction (original) (raw)

Abstract

Substructuring methods have been studied since 1960s. The modes of subsystems associated with the lowest frequencies are typically retained. This mode selection rule is largely heuristic. In this paper, we use a moment-matching analysis tool to derive a new mode selection criterion, which is compatible to the one recently derived by Givoli et al using Dirichlet-to-Neumann (DtN) map as an analysis tool. The improvements of the new mode selection criterion are demonstrated by numerical examples from structural dynamics and MEMS simulation.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Department of Mathematics, University of California at Davis, Davis, CA, 95616, USA
    Zhaojun Bai
  2. Department of Mathematics, University of California at Davis, Davis, CA, 95616, USA
    Ben-Shan Liao

Authors

  1. Zhaojun Bai
  2. Ben-Shan Liao

Editor information

Editors and Affiliations

  1. Computer Science Department, University of Tennessee, 37996-3450, Knoxville, TN, USA
    Jack Dongarra
  2. Department of Informatics and Mathematical Modelling, Technical University of Denmark, DK-2800, Lyngby, Denmark
    Kaj Madsen
  3. Informatics & Mathematical Modeling, Technical University of Denmark, DK-2800, Lyngby, Denmark
    Jerzy Waśniewski

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© 2006 Springer-Verlag Berlin Heidelberg

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Bai, Z., Liao, BS. (2006). Towards an Optimal Substructuring Method for Model Reduction. In: Dongarra, J., Madsen, K., Waśniewski, J. (eds) Applied Parallel Computing. State of the Art in Scientific Computing. PARA 2004. Lecture Notes in Computer Science, vol 3732. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11558958\_33

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