Model order reduction methods for geometrically nonlinear structures: a review of nonlinear techniques

Cyril Touzé*, Alessandra Vizzaccaro, Olivier Thomas

*Corresponding author for this work

Research output: Contribution to journalReview article (Academic Journal)peer-review

130 Citations (Scopus)

Abstract

This paper aims at reviewing nonlinear methods for model order reduction in structures with geometric nonlinearity, with a special emphasis on the techniques based on invariant manifold theory. Nonlinear methods differ from linear-based techniques by their use of a nonlinear mapping instead of adding new vectors to enlarge the projection basis. Invariant manifolds have been first introduced in vibration theory within the context of nonlinear normal modes and have been initially computed from the modal basis, using either a graph representation or a normal form approach to compute mappings and reduced dynamics. These developments are first recalled following a historical perspective, where the main applications were first oriented toward structural models that can be expressed thanks to partial differential equations. They are then replaced in the more general context of the parametrisation of invariant manifold that allows unifying the approaches. Then, the specific case of structures discretised with the finite element method is addressed. Implicit condensation, giving rise to a projection onto a stress manifold, and modal derivatives, used in the framework of the quadratic manifold, are first reviewed. Finally, recent developments allowing direct computation of reduced-order models relying on invariant manifolds theory are detailed. Applicative examples are shown and the extension of the methods to deal with further complications are reviewed. Finally, open problems and future directions are highlighted.

Original languageEnglish
Pages (from-to)1141-1190
Number of pages50
JournalNonlinear Dynamics
Volume105
Issue number2
DOIs
Publication statusPublished - 20 Jul 2021

Bibliographical note

Funding Information:
The authors are especially thankful to Alex Haro for detailed discussions we had in January 2021. Walter Lacarbonara is also warmly thanked for inviting the first author to write a review paper on reduction methods. Andrea Opreni and Attilio Frangi are thanked for their major contributions to the developments of efficient writing and coding of the DNF for FE systems and the interesting applications to MEMS as well as first-draft readings. Loïc Salles is thanked for all the discussions and collaborations on the subject and for launching the subject again in January 2019. Yichang Shen is thanked for his involvement in the project. Steve Shaw and David Wagg read first versions of the paper and brought out numerous interesting comments to the authors that helped improving the presentation, they are sincerely thanked for this precious help. Claude Lamarque, Gérard Iooss and Paul Manneville are thanked for the non-countable discussions we had on normal forms in the last years.

Publisher Copyright:
© 2021, The Author(s), under exclusive licence to Springer Nature B.V.

Keywords

  • Geometric nonlinearity
  • Invariant manifold
  • Nonlinear mapping
  • Reduced order modeling
  • Thin structures

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