Modeling of dynamic and post-dynamic recrystallization by coupling a full field approach to phenomenological laws. (5th November 2017)

• Record Type: Journal Article
• Authors: Maire, Ludovic; Scholtes, Benjamin; Moussa, Charbel; Bozzolo, Nathalie; Muñoz, Daniel Pino; Settefrati, Amico; Bernacki, Marc
• Is Part Of: Materials & design. Volume 133(2017)
• Page Start: 498
• Page End: 519
• Publication Date: 2017-11-05
• Subjects: Microstructures -- Grain boundaries -- Recrystallization -- Metallic materials -- Finite elements -- Level set; Materials -- Periodicals; Engineering design -- Periodicals; Matériaux -- Périodiques; Conception technique -- Périodiques; Electronic journals; 620.11
• DOI: 10.1016/j.matdes.2017.08.015
• Languages: English
• ISSNs: 0264-1275

Abstract

Abstract: This paper describes a level set framework for the full field modeling of dynamic and post-dynamic recrystallization in a 3D polycrystalline material with an accurate description of grains topology at large deformation and application to 304L austenitic stainless steel. Topological evolutions are simulated based on a kinetic law linking the velocity of the boundaries to the thermodynamic driving forces. Recrystallization is modeled by coupling a level set approach to phenomenological laws describing strain hardening mechanism and nucleation criteria. Although the proposed formalism does not consider crystal plasticity because of its computational costs, it enables to reach outstanding dynamic recrystallization computations in a front-capturing finite element framework comparatively to the state of art. Graphical Abstract: Highlights: 3D full field simulation of dynamic and post-dynamic recrystallization at the polycrystal scale with a good description of grains topology at large deformation (for instance ε > 0.2). Hardening, recovery, nucleation of recrystallized grains and subsequent grain growth simulated within the same unique numerical framework. Simulation of multipass processing and heat treatment possible within the same framework. Optimized numerical cost and increased model robustness leading to state-of-the-art fully 3D recrystallization simulations.