Global proper orthogonal decomposition for parametric model reduction of geometrically nonlinear structures

Abstract: Finite element simulations of structures that undergo large deformations can imply long simulation times due to the nonlinearity of the resulting equations of motion and a high number of degrees of freedom. Especially for design studies, where the equations of motion must be solved several times, it is highly desired to reduce the simulation time. The simulation time can be reduced by nonlinear model reduction. Nonlinear model reduction is carried out in two steps: First, the dimension of the problem is reduced by projecting the equations of motion onto a low‐order subspace that is defined by a reduction basis. Second, the evaluation of the nonlinear restoring force term, that originates from large deflections, is accelerated through hyperreduction. The first step can be challenging for design studies spanning large parameter intervals. For those studies, the calculated reduction basis either must be updated several times or must provide a subspace that captures the solution vectors for the whole parameter space. The latter option can be performed by sampling the parameter space, building local reduction bases at these sampling points and then applying a proper orthogonal decomposition on their concatenation. This contribution shows how this procedure is used for parametric model reduction of geometrically nonlinear structures. It demonstrates its accuracy and computation time on a shape‐parameterized beam structure that undergoes large deflections. It turns out that the success of the proposed method is highly dependent on the implementation of the shape parameterization.

Location
Deutsche Nationalbibliothek Frankfurt am Main
Extent
Online-Ressource
Language
Englisch

Bibliographic citation
Global proper orthogonal decomposition for parametric model reduction of geometrically nonlinear structures ; volume:19 ; number:1 ; year:2019 ; extent:4
Proceedings in applied mathematics and mechanics ; 19, Heft 1 (2019) (gesamt 4)

Creator
Meyer, Christian H.
Rixen, Daniel

DOI
10.1002/pamm.201900436
URN
urn:nbn:de:101:1-2022072208083182740631
Rights
Open Access; Der Zugriff auf das Objekt ist unbeschränkt möglich.
Last update
15.08.2025, 7:22 AM CEST

Data provider

This object is provided by:
Deutsche Nationalbibliothek. If you have any questions about the object, please contact the data provider.

Associated

  • Meyer, Christian H.
  • Rixen, Daniel

Other Objects (12)