Automatised selection of load paths to ...
Document type :
Article dans une revue scientifique: Article original
Title :
Automatised selection of load paths to construct reduced-order models in computational damage micromechanics: from dissipation-driven random selection to Bayesian optimization
Author(s) :
Goury, Olivier [Auteur]
Deformable Robots Simulation Team [DEFROST ]
Amsallem, David [Auteur]
Stanford University
Bordas, Stéphane Pierre-Alain [Auteur]
Université du Luxembourg = University of Luxembourg = Universität Luxemburg [uni.lu]
Liu, Wing Kam [Auteur]
Northwestern University [Evanston]
Kerfriden, Pierre [Auteur correspondant]
Cardiff School of Engineering
Deformable Robots Simulation Team [DEFROST ]
Amsallem, David [Auteur]
Stanford University
Bordas, Stéphane Pierre-Alain [Auteur]
Université du Luxembourg = University of Luxembourg = Universität Luxemburg [uni.lu]
Liu, Wing Kam [Auteur]
Northwestern University [Evanston]
Kerfriden, Pierre [Auteur correspondant]
Cardiff School of Engineering
Journal title :
Computational Mechanics
Pages :
213–234
Publisher :
Springer Verlag
Publication date :
2016-08
ISSN :
0178-7675
English keyword(s) :
damage mechanics
multiscale
Hyperreduction
model order reduction
computational homogenisation
reduced basis
multiscale
Hyperreduction
model order reduction
computational homogenisation
reduced basis
HAL domain(s) :
Physique [physics]/Mécanique [physics]/Mécanique des structures [physics.class-ph]
English abstract : [en]
In this paper, we present new reliable model order reduction strategies for computational micromechanics. The difficulties rely mainly upon the high dimensionality of the parameter space represented by any load path applied ...
Show more >In this paper, we present new reliable model order reduction strategies for computational micromechanics. The difficulties rely mainly upon the high dimensionality of the parameter space represented by any load path applied onto the representative volume element (RVE). We take special care of the challenge of selecting an exhaustive snapshot set. This is treated by first using a random sampling of energy dissipating load paths and then in a more advanced way using Bayesian optimization associated with an interlocked division of the parameter space. Results show that we can insure the selection of an exhaustive snapshot set from which a reliable reduced-order model (ROM) can be built.Show less >
Show more >In this paper, we present new reliable model order reduction strategies for computational micromechanics. The difficulties rely mainly upon the high dimensionality of the parameter space represented by any load path applied onto the representative volume element (RVE). We take special care of the challenge of selecting an exhaustive snapshot set. This is treated by first using a random sampling of energy dissipating load paths and then in a more advanced way using Bayesian optimization associated with an interlocked division of the parameter space. Results show that we can insure the selection of an exhaustive snapshot set from which a reliable reduced-order model (ROM) can be built.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
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