Uncertain reduced-order modeling via balanced truncation for structural dynamic systems with interval parameters

Author(s):  
Xianjia Chen ◽  
Zhiping Qiu ◽  
Yunlong Li ◽  
Nan Jiang
PAMM ◽  
2016 ◽  
Vol 16 (1) ◽  
pp. 245-246
Author(s):  
Stefanie Tegtmeyer ◽  
Udo Nackenhorst

Author(s):  
Ricardo Perez ◽  
X. Q. Wang ◽  
Marc P. Mignolet

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, which are nonintrusive, i.e., the structure is originally 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 a step-by-step 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 nine-bay panel structure modeled with 96,000 degrees of freedom within Nastran.


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