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3D level set modeling of static recrystallization considering stored energy fields

Authors :
Amico Settefrati
Daniel Pino Muñoz
Benjamin Scholtes
Marc Bernacki
Aurore Montouchet
Nathalie Bozzolo
Isabelle Poitrault
Romain Boulais-Sinou
Centre de Mise en Forme des Matériaux (CEMEF)
MINES ParisTech - École nationale supérieure des mines de Paris
Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre National de la Recherche Scientifique (CNRS)
Transvalor
Transvalor S.A.
Industeel
ArcelorMittal
Creusot Forge
AREVA SFARSTEEL
Source :
Computational Materials Science, Computational Materials Science, Elsevier, 2016, 122, pp.57-71. ⟨10.1016/j.commatsci.2016.04.045⟩
Publication Year :
2016
Publisher :
Elsevier BV, 2016.

Abstract

International audience; In the last decades, many numerical models have been proposed to simulate thermomechanical treatments and their related effects on the microstructure. The present study deals with a relatively recent full field model using the level set method within a finite element framework. The ability of this approach to consider static recrystallization in two and three dimensions with nucleation has been demonstrated in previous studies (Bernacki et al., 2008, 2009). Although accurate, this model lies on a numerical formalism which is rather inefficient from a numerical point of view and do not permit to consider complex 3D aggregates in reasonable computation times. The present paper introduces a new efficient implementation of the static recrystallization (SRX) model which aims to overcome this limitation by taking full advantage of recent numerical developments (Shakoor et al., 2015; Scholtes et al., 2015). Its efficiency is evaluated through large scale 3D simulations of SRX with several thousand of grains. Acceleration factors of up to 40 are obtained, compared with the existing implementation. The predictions in terms of evolution of the recrystallized fraction are also confronted with classical analytic models and experimental results from literature, showing good agreement.

Details

ISSN :
09270256
Volume :
122
Database :
OpenAIRE
Journal :
Computational Materials Science
Accession number :
edsair.doi.dedup.....66924c352da3d2752c20dd38f1c10d89
Full Text :
https://doi.org/10.1016/j.commatsci.2016.04.045