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Advances in Computational Mathematics

, Volume 41, Issue 5, pp 1187–1230 | Cite as

Fast local reduced basis updates for the efficient reduction of nonlinear systems with hyper-reduction

  • David AmsallemEmail author
  • Matthew J. Zahr
  • Kyle Washabaugh
Article

Abstract

Projection-based model reduction techniques rely on the definition of a small dimensional subspace in which the solution is approximated. Using local subspaces reduces the dimensionality of each subspace and enables larger speedups. Transitions between local subspaces require special care and updating the reduced bases associated with each subspace increases the accuracy of the reduced-order model. In the present work, local reduced basis updates are considered in the case of hyper-reduction, for which only the components of state vectors and reduced bases defined at specific grid points are available. To enable local reduced basis updates, two comprehensive approaches are proposed. The first one is based on an offline/online decomposition. The second approach relies on an approximated metric acting only on those components where the state vector is defined. This metric is computed offline and used online to update the local bases. An analysis of the error associated with this approximated metric is then conducted and it is shown that the metric has a kernel interpretation. Finally, the application of the proposed approaches to the model reduction of two nonlinear physical systems illustrates their potential for achieving large speedups and good accuracy.

Keywords

Model reduction Nonlinear dimensionality reduction Reduced basis Hyper-reduction Approximated metric Singular value decomposition Offline/online decomposition Kernel methods 

Mathematics Subject Classfication

65M99 78M34 35Q51 76N99 76H05 

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Copyright information

© Springer Science+Business Media New York 2015

Authors and Affiliations

  • David Amsallem
    • 1
    Email author
  • Matthew J. Zahr
    • 2
  • Kyle Washabaugh
    • 1
  1. 1.Department of Aeronautics and AstronauticsStanford UniversityStanfordUSA
  2. 2.Institute of Computational and Mathematical EngineeringStanford UniversityStanfordUSA

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