Nonlinear Substructuring Using Fixed Interface Nonlinear Normal Modes

Falco, Marco; Mahdiabadi, Morteza Karamooz; Rixen, Daniel J.

doi:10.1007/978-3-319-54930-9_18

Cited by 6 publications

(2 citation statements)

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“…Nonlinear coupling [30,31] and nonlinear modal substructuring [35,55] account for the effects of the nonlinear internal forces considering them as harmonic at the same frequency of the excitation, thus higher harmonics effects are not captured. The same assumption is valid for the procedure discussed in this section, that is meant to couple linear substructures connected through nonlinear connecting elements.…”

Section: Nonlinear Coupling Procedures In the Modal Domainmentioning

confidence: 99%

Nonlinear substructuring in the modal domain: numerical validation and experimental verification in presence of localized nonlinearities

et al. 2021

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In many systems of interest, most of the structure is well approximated as linear but some parts must be treated as nonlinear to get accurate response predictions: significant nonlinear effects are due to the connections between coupled subsystems, such as in automotive or aerospace structures. The present work aims at predicting the nonlinear behavior of coupled systems using a substructuring technique in the modal domain. This study focuses on the effects of nonlinear connections on the dynamics of an assembly in which the coupled subsystems can be considered as linear. Each connection is instead considered as a quasi-linear substructure with stiffness that is function of amplitude or energy. The iterative procedure used here is enhanced with respect to previous works by enforcing a better control of the total energy at each iteration allowing to obtain the solution for a prescribed set of energy levels. Also, the initial guess and the convergence criterion have been modified to speed up the procedure. This technique is applied to a system made of two continuous linear subsystems coupled by nonlinear connections. The numerical results of the coupling are first compared to the ones obtained by using the Harmonic Balance technique on the model of the complete assembly to evaluate its effectiveness and understand the effects of modal truncation. Besides, a nonlinear connecting element, specifically designed in order to have a nearly cubic hardening behavior, is used in an experimental setup. Substructuring results are compared to experimental results measured on the assembled system, in order to evaluate the correlation between mode shapes and the accuracy in the resonance frequency at several excitation levels.

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Section: Nonlinear Coupling Procedures In the Modal Domainmentioning

confidence: 99%

Nonlinear substructuring in the modal domain: numerical validation and experimental verification in presence of localized nonlinearities

et al. 2021

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“…The notion gained increasing attention after the comprehensive formulation in [7], which describes a reduction framework able to capture a system's dynamics in a set of nonlinear modes. The approach's accurate performance has been demonstrated in several applications, including resonance prediction [10] and frequency response approximation [2].…”

Section: Introductionmentioning

confidence: 99%

Parametric Model Order Reduction for Localized Nonlinear Feature Inclusion

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et al. 2021

NODYCON Conference Proceedings Series

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Injecting parametric dependency and treating nonlinear phenomena pose the main challenges when seeking to construct an accurate Reduced Order Model (ROM) of an actual complex system. Also, real-life structures may often comprise multiple components demanding separate treatment. This paper derives a physics-based ROM, reflecting dependencies on system properties and characteristics of the induced excitation. This is achieved utilizing a projection strategy relying on Proper Orthogonal Decomposition. The framework is then coupled with the substructuring approach in [13]. This representation allows integrating localized domains experiencing nonlinearity or damage on the ROM and enables response learning both at a global and a local level. The pROM derived through this fusion can address each component's dynamics separately and apply individual reduction, leading to a modular formulation.

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