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research article

Model order reduction for large-scale structures with local nonlinearities

Zhang, Zhenying
•
Guo, Mengwu  
•
Hesthaven, Jan S.  
August 15, 2019
Computer Methods in Applied Mechanics and Engineering

In solid mechanics, linear structures often exhibit (local) nonlinear behavior when close to failure. For instance, the elastic deformation of a structure becomes plastic after being deformed beyond recovery. To properly assess such problems in a real-life application, we need fast and multi-query evaluations of coupled linear and nonlinear structural systems, whose approximations are not straight forward and often computationally expensive. In this work, we propose a linear-nonlinear domain decomposition, where the two systems are coupled through the solutions on the linear-nonlinear interface. After necessary sensitivity analysis, e.g. for structures with a high dimensional parameter space, we adopt a non-intrusive method, e.g. Gaussian processes regression (GPR), to solve for the solution on the interface. We then utilize different model order reduction techniques to address the linear and nonlinear problems individually. To accelerate the approximation, we employ again the non-intrusive GPR for the nonlinearity, while intrusive model order reduction methods, e.g. the conventional reduced basis (RB) method or the static-condensation reduced- basis-element (SCRBE) method, are employed for the solution in the linear subdomain. We provide several numerical examples to demonstrate the effectiveness of our method.

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Type
research article
DOI
10.1016/j.cma.2019.04.042
Web of Science ID

WOS:000470960700022

Author(s)
Zhang, Zhenying
Guo, Mengwu  
Hesthaven, Jan S.  
Date Issued

2019-08-15

Publisher

ELSEVIER SCIENCE SA

Published in
Computer Methods in Applied Mechanics and Engineering
Volume

353

Start page

491

End page

515

Subjects

model order reduction

•

reduced basis method

•

nonlinear structural analysis

•

gaussian process regression

•

port reduction

•

approximation

•

design

•

link

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
MCSS  
Available on Infoscience
November 9, 2018
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/151311
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