On the selection of states to be retained in a reduced-order model

1984 ◽  
Vol 131 (1) ◽  
pp. 15 ◽  
Author(s):  
G.J. Lastman ◽  
N.K. Sinha ◽  
P. Rózsa
Keyword(s):  
Reduced Order Model ◽  
Order Model ◽  
Reduced Order ◽  
Selection Of

A Ranking Method for the Selection of the Interior Modes of Reduced Order Resonant System Models

2014 ◽  
Author(s):  
Ilaria Palomba ◽  
Dario Richiedei ◽  
Alberto Trevisani
Keyword(s):  
Normal Modes ◽  
Reduced Order Model ◽  
Ranking Method ◽  
Resonant System ◽  
Order Model ◽  
Reduced Order ◽  
Design And Optimization ◽  
Optimization Stage ◽  
Dimensional Models ◽  
Selection Of

Resonant system design and optimization is usually supported by finite element models. Large dimensional models are often needed to achieve the desired accuracy in the representation of the vibrational behaviour at the frequency of interest. Unfortunately, large dimensional models are frequently too cumbersome to be actually useful, mainly at the optimization stage. On the other hand, the choice of the most appropriate reduction strategy and dimension for a reduced-order model is generally left to designers’ experience. Having recognized the effectiveness and spreading of the Craig Bampton reduction technique, the aim of this paper is to propose a rigorous ranking method, called Interior Mode Ranking (IMR), for the selection of the interior normal modes of the full order model to be inherited by the reduced order one. The method is aimed at finding the set of interior modes of minimum dimensions which allows achieving a desired level of accuracy of the reduced order model at a frequency of interest. The method is here applied to a resonator widely employed in industry: an ultrasonic welding bar horn, which is usually designed to operate excited in resonance. The results achieved through the application of the IMR method are compared with those yielded by other ranking techniques available in literature in order to prove its effectiveness.

Reduced Order Model for the Geometric Nonlinear Response of Complex Structures

2012 ◽  
Author(s):  
Ricardo Perez ◽  
X. Q. Wang ◽  
Andrew Matney ◽  
Marc P. Mignolet
Keyword(s):  
Degrees Of Freedom ◽  
Nonlinear Behavior ◽  
Reduced Order Model ◽  
Model Parameters ◽  
Complex Structures ◽  
Order Model ◽  
Plate Structures ◽  
Reduced Order ◽  
Nonlinear Static ◽  
Selection Of

This paper focuses on the development of nonlinear reduced order modeling techniques for the prediction of the response of complex structures exhibiting “large” deformations, i.e. a geometrically nonlinear behavior, and modeled within a commercial finite element code. The present investigation builds on a general methodology successfully validated in recent years on simpler beam and plate structures by: (i) developing a novel identification strategy of the reduced order model parameters that enables the consideration of the large number of modes (> 50 say) that would be needed for complex structures, and (ii) extending an automatic strategy for the selection of the basis functions used to represent accurately the displacement field. The above novel developments are successfully validated on the nonlinear static response of a 9-bay panel structure modeled with 96,000 degrees of freedom within Nastran.

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