An adaptive model order reduction with Quasi-Newton method for nonlinear dynamical problems
- verfasst von
- P. S.B. Nigro, M. Anndif, Y. Teixeira, P. M. Pimenta, P. Wriggers
- Abstract
Model Order Reduction (MOR) methods are extremely useful to reduce processing time, even nowadays, when parallel processing is possible in any personal computer. This work describes a method that combines Proper Orthogonal Decomposition (POD) and Ritz vectors to achieve an efficient Galerkin projection, which changes during nonlinear solving (online analysis). It is supported by a new adaptive strategy, which analyzes the error and the convergence rate for nonlinear dynamical problems. This model order reduction is assisted by a secant formulation which is updated by the Broyden-Fletcher-Goldfarb-Shanno (BFGS) formula to accelerate convergence in the reduced space, and a tangent formulation when correction of the reduced space is needed. Furthermore, this research shows that this adaptive strategy permits correction of the reduced model at low cost and small error.
- Organisationseinheit(en)
-
Institut für Kontinuumsmechanik
- Externe Organisation(en)
-
Universidade de Sao Paulo
- Typ
- Artikel
- Journal
- International Journal for Numerical Methods in Engineering
- Band
- 106
- Seiten
- 740-759
- Anzahl der Seiten
- 20
- ISSN
- 0029-5981
- Publikationsdatum
- 19.10.2015
- Publikationsstatus
- Veröffentlicht
- Peer-reviewed
- Ja
- ASJC Scopus Sachgebiete
- Numerische Mathematik, Allgemeiner Maschinenbau, Angewandte Mathematik
- Elektronische Version(en)
-
https://doi.org/10.1002/nme.5145 (Zugang:
Geschlossen)
