Torsion-Bending Coupling in Nonlinear Model Order Reduction

Lucas G.C. Silveira*, Morten H. Hansen

*Kontaktforfatter

Publikation: Kapitel i bog/rapport/konference-proceedingKonferencebidrag i proceedingsForskningpeer review

Abstract

This study investigates the performance of two nonlinear model order reduction techniques, a quadratic manifold and a linear basis augmented with modal derivatives, in predicting the coupling of torsion and bending in a mechanical structure. We demonstrate that the quadratic manifold, which assumes a linear variation of the modal derivatives, overlooks the presence of modal hybridisations. Conversely, the linear basis augmented with modal derivatives successfully captures both the vertical and large angular displacements, even in the presence of modal veerings. We further introduce a simple yet practical selection algorithm for optimising the use of modal derivatives, although this approach reveals limitations in terms of its assumptions and error definition. This investigation highlights the potential of the linear basis method augmented with modal derivatives and prompts further research into improved selection strategies and error definitions, contributing to the advancement of more precise and efficient model order reductions.

OriginalsprogEngelsk
TitelAdvances in Nonlinear Dynamics and Control of Mechanical and Physical Systems : Selected Articles from CSNDD 2023; 15–17 May; Marrakesh, Morocco
RedaktørerMohamed Belhaq
ForlagSpringer Science+Business Media
Publikationsdato2024
Sider255-267
ISBN (Trykt)9789819979578
ISBN (Elektronisk)978-981-99-7958-5
DOI
StatusUdgivet - 2024
Begivenhed5th Conference on Structural Nonlinear Dynamics and Diagnosis, CSNDD 2023 - Marrakesh, Marokko
Varighed: 15. maj 202317. maj 2023

Konference

Konference5th Conference on Structural Nonlinear Dynamics and Diagnosis, CSNDD 2023
Land/OmrådeMarokko
ByMarrakesh
Periode15/05/202317/05/2023
NavnSpringer Proceedings in Physics
Vol/bind301
ISSN0930-8989

Bibliografisk note

Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

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