Article (Scientific journals)
Bridging proper orthogonal decomposition methods and augmented Newton-Krylov algorithms: An adaptive model order reduction for highly nonlinear mechanical problems
Kerfriden, P.; Gosselet, P.; Adhikari, S. et al.
2011In Computer Methods in Applied Mechanics and Engineering, 200 (5-8), p. 850-866
Peer reviewed
 

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Keywords :
Damage propagation; Hyperreduction; Model order reduction (MOR); Newton/Krylov solver; Projected conjugate gradient; Proper orthogonal decomposition (POD); Conjugate gradient; Proper orthogonal decompositions; Adaptive algorithms; Conjugate gradient method; Topology
Abstract :
[en] This article describes a bridge between POD-based model order reduction techniques and the classical Newton/Krylov solvers. This bridge is used to derive an efficient algorithm to correct, " on-the-fly" , the reduced order modelling of highly nonlinear problems undergoing strong topological changes. Damage initiation problems tackled via a corrected hyperreduction method are used as an example. It is shown that the relevancy of reduced order model can be significantly improved with reasonable additional costs when using this algorithm, even when strong topological changes are involved. © 2010.
Disciplines :
Mechanical engineering
Author, co-author :
Kerfriden, P.;  Cardiff University, Queen's Buildings, The Parade, Cardiff CF24 3AA, Wales, United Kingdom
Gosselet, P.;  Ecole Normale Superieure de Cachan, 61 Avenue du Président Wilson, F-94230 Cachan, France
Adhikari, S.;  Swansea University, Singleton Park, Swansea SA2 8PP, Wales, United Kingdom
Bordas, Stéphane ;  University of Luxembourg > Faculty of Science, Technology and Communication (FSTC) > Engineering Research Unit
Language :
English
Title :
Bridging proper orthogonal decomposition methods and augmented Newton-Krylov algorithms: An adaptive model order reduction for highly nonlinear mechanical problems
Publication date :
2011
Journal title :
Computer Methods in Applied Mechanics and Engineering
ISSN :
0045-7825
Volume :
200
Issue :
5-8
Pages :
850-866
Peer reviewed :
Peer reviewed
Focus Area :
Computational Sciences
Name of the research project :
Towards the next generation surgical simulators
Funders :
Royal Academy of Engineering and Leverhulme Trust Senior Research Fellowship
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