Comparison of nonlinear methods for reduced-order modeling of geometrically nonlinear structures - ENSTA Paris - École nationale supérieure de techniques avancées Paris
Communication Dans Un Congrès Année : 2022

Comparison of nonlinear methods for reduced-order modeling of geometrically nonlinear structures

Alessandra Vizzaccaro
Loic Salles
Andrea Opreni
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Yichang Shen
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Attilio Alberto Frangi
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Résumé

The aim of this contribution is to review and compare three different methods that have been proposed in order to derive reduced-order models for geometrically nonlinear structures, and relying on a nonlinear technique to better take into account the nonlinearities of the initial problem. The three methods are: implicit condensation, quadratic manifold derived with modal derivatives, and projection onto an invariant manifold, tangent at the origin to the linear eigenspace of the master modes. The methods are briefly reviewed theoretically and then compared with dedicated examples.
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Dates et versions

hal-03778406 , version 1 (15-09-2022)

Identifiants

  • HAL Id : hal-03778406 , version 1

Citer

Cyril Touzé, Alessandra Vizzaccaro, Olivier Thomas, Loic Salles, Andrea Opreni, et al.. Comparison of nonlinear methods for reduced-order modeling of geometrically nonlinear structures. ENOC 2020+2, 10th European Nonlinear Dynamics Conference, Jul 2022, Lyon, France. ⟨hal-03778406⟩
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