Model order reduction; POD; elastoplasticity; finite plasticity; non-elliptical PDEs
Abstract :
[en] Projection-based model-order reduction approaches are accurate and fast for simulations with periodic boundary conditions: the use of only a limited number of global basis functions generally provides an excellent accuracy. In contrast to (hyper)elasticity, (hyper)elastoplasticity yields non-elliptical partial differential equations. Consequently, many global basis functions are needed to achieve a reasonable accuracy. The fact that many basis functions are required for hyperelasto- plasticity is not only problematic because a relatively large number of degrees of freedom remains, it also entails the need for many integration points in the online simulations (the stress update must be iteratively computed in each iteration). This contribution investigates two approaches to keep the number of global basis functions of finitely plastically deforming representative volume element simulations small - ultimately in order to keep the number of reduced quadrature
points of the hyperreduction small. This is performed by combining the global basis functions with local interpolation functions. For both extensions, we investigate two ways to identify the global basis functions. Although the results are clearly improved, a truly consistent trend is lacking for the time being. On the other hand, several avenues can be taken to improve the frameworks.
Wu, Ling ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Computational & Multiscale Mechanics of Materials (CM3)
Noels, Ludovic ; Université de Liège - ULiège > Département d'aérospatiale et mécanique > Computational & Multiscale Mechanics of Materials (CM3)
Bordas, Stéphane PA; Unilu - Université du Luxembourg [LU]
Natarajan, Sundar; Indian Institute of Technology, Madras, Chennai
Beex, Lars AA; Unilu - Université du Luxembourg [LU]
Language :
English
Title :
A data-driven reduced-order surrogate model for entire elastoplastic simulations applied to representative volume elements
Publication date :
07 August 2023
Journal title :
Scientific Reports
eISSN :
2045-2322
Publisher :
Nature Publishing Group, London, United Kingdom
Volume :
13
Issue :
1
Pages :
12781
Peer reviewed :
Peer Reviewed verified by ORBi
Tags :
CÉCI : Consortium des Équipements de Calcul Intensif
European Projects :
H2020 - 862015 - MOAMMM - Multi-scale Optimisation for Additive Manufacturing of fatigue resistant shock-absorbing MetaMaterials
Name of the research project :
Multiscale Optimisation for Additive Manufacturing of fatigue resistant shock-absorbing MetaMaterials (MOAMMM)
Funders :
EC - European Commission EU - European Union
Funding number :
862015
Funding text :
This project has received funding from the H2020-EU.1.2.1.-FET Open Programme project MOAMMM under grant No 862015 and the EU's H2020 project DRIVEN under grant No 811099.
Commentary :
This is an open access article distributed under the terms of the Creative Commons CC BY license, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Vijayaraghavan, S., Wu, L., Noels, L. et al. A data-driven reduced-order surrogate model for entire elastoplastic simulations applied to representative volume elements. Sci Rep 13, 12781 (2023). https://doi.org/10.1038/s41598-023-38104-x
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