Normal form theory and nonlinear normal modes: Theoretical settings and applications

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

These lecture notes are related to the CISM course on ”Modal Analysis of nonlinear Mechanical systems”, held at Udine, Italy, from June 25 to 29, 2012. The key concept at the core of all the lessons given during this week is the notion of Nonlinear Normal Mode (NNM), a theoretical tool allowing one to extend, through some well-chosen assumptions and limitations, the linear modes of vibratory systems, to nonlinear regimes. More precisely concerning these notes, they are intended to show the explicit link between Normal Form theory and NNMs, for the specific case of vibratory systems displaying polynomial type nonlinearities. After a brief introduction reviewing the main concepts for deriving the normal form for a given dynamical system, the relationship between normal form theory and nonlinear normal modes (NNMs) will be the core of the developments. Once the main results presented, application of NNMs to vibration problem where geometric nonlinearity is present, will be highlighted. In particular, the developments of reduced-order models based on NNMs expressed asymptotically with the formalism of real normal form, will be deeply presented.

Original languageEnglish
Title of host publicationCISM International Centre for Mechanical Sciences, Courses and Lectures
PublisherSpringer International Publishing
Pages75-160
Number of pages86
DOIs
Publication statusPublished - 1 Jan 2014

Publication series

NameCISM International Centre for Mechanical Sciences, Courses and Lectures
Volume555
ISSN (Print)0254-1971
ISSN (Electronic)2309-3706

Keywords

  • Circular Cylindrical Shell
  • Internal Resonance
  • Invariant Manifold
  • Proper Orthogonal Decomposition
  • Proper Orthogonal Decomposition Mode

Fingerprint

Dive into the research topics of 'Normal form theory and nonlinear normal modes: Theoretical settings and applications'. Together they form a unique fingerprint.

Cite this