Cellular automata modeling of static recrystallization based on the curvature driven subgrain growth mechanism

2013 ◽  
Vol 48 (20) ◽  
pp. 7142-7152 ◽  
Author(s):  
Fengbo Han ◽  
Bin Tang ◽  
Hongchao Kou ◽  
Jinshan Li ◽  
Yong Feng
Keyword(s):  
Cellular Automata ◽  
Growth Mechanism ◽  
Static Recrystallization ◽  
Subgrain Growth ◽  
Curvature Driven

Cellular Automata Simulation of Textural Evolution during Primary Static Recrystallization of IF Steel

2011 ◽  
Vol 702-703 ◽  
pp. 615-618
Author(s):  
Dong Kyu Kim ◽  
K.H. Jung ◽  
H.W. Lee ◽  
Yong Taek Im
Keyword(s):  
Cellular Automata ◽  
Static Recrystallization ◽  
Grain Morphology ◽  
Interstitial Free ◽  
If Steel ◽  
Probabilistic Cellular Automata ◽  
Cellular Automata Model ◽  
Textural Evolution ◽  
Annealing Texture ◽  
Curvature Driven

A two dimensional probabilistic cellular automata model is used to simulate primary static recrystallization of interstitial free (IF) steel. The present study is to investigate the effect of curvature-driven pressure that is induced by protrusions/retrusions of recrystallization fronts on the microstructural and textural evolution during recrystallization. It was found that local interface migration of protrusions/retrusions of recrystallization fronts could significantly affect the kinetics, grain morphology and annealing texture according to the present investigation.

Simulation of microstructure evolution during recrystallization using a high resolution three dimensional cellular automaton

2004 ◽  
Vol 120 ◽  
pp. 225-230
Author(s):  
P. Mukhopadhyay ◽  
M. Loeck ◽  
G. Gottstein
Keyword(s):  
High Resolution ◽  
Cellular Automata ◽  
Cellular Automaton ◽  
Microstructure Evolution ◽  
Static Recrystallization ◽  
Three Dimensional ◽  
Computation Time ◽  
Recrystallization Process ◽  
Recovery Condition ◽  
Physically Based

A more refined 3D cellular Automata (CA) algorithm has been developed which has increased the resolution of the space and reduced the computation time and can take care of the complexity of recrystallization process through physically based solutions. This model includes recovery, condition for nucleation and orientation dependent variable nuclei growth as a process of primary static recrystallization. Incorporation of microchemistry effects makes this model suitable for simulating recrystallization behaviour in terms of texture, kinetics and microstructure of different alloys. The model is flexible to couple up with other simulation programs on a common database.

Static Recrystallization Modeling With a Cellular Automata Algorithm

2005 ◽  
Author(s):  
Yujie Wu ◽  
Qiang Yu ◽  
Sven K. Esche
Keyword(s):  
Cellular Automata ◽  
Single Phase ◽  
Static Recrystallization ◽  
Volume Fraction ◽  
Mechanical Processing ◽  
Kinetics Analysis ◽  
Multi Scale ◽  
Microstructure Prediction ◽  
Phase Systems ◽  
Cellular Automata Algorithm

This paper reports on one part of a research project supported by NSF, which aims at developing a multi-scale methodology for systematic microstructure prediction in thermo-mechanical processing of metals. Based on combining mesoscopic microstructure models with macroscopic process formulations, the methodology is expected to provide universally applicable and accurate microstructure prediction capabilities. Cellular Automata (CA) models have been widely used in scientific studies of various microstructural phenomena. This paper discusses the modeling of the static recrystallization phenomenon by employing a regular CA algorithm. The recrystallization processes of single-phase systems under different nucleation conditions are simulated followed by the recrystallization kinetics analysis for 200 × 200 two-dimensional lattice. The performed simulations of static recrystallization confirm that the recrystallized volume fractions are time dependent. Furthermore, the simulated microstructures validate the following Johnson-Mehl-Avrami-Kolmogorov (JMAK) model according to which the recrystallized volume fraction is a sigmoidal function of time, and their evolution matches the JMAK equation with the expected exponents.

Modelling of the Microstructure Evolution Using Cellular Automata Framework and WorkFlow Approach

2014 ◽  
Vol 611-612 ◽  
pp. 497-504
Author(s):  
Rafal Golab ◽  
Mateusz Sitko ◽  
Łukasz Madej
Keyword(s):  
Phase Transformation ◽  
Cellular Automata ◽  
Microstructure Evolution ◽  
Static Recrystallization ◽  
Application Framework ◽  
Mechanical Processing ◽  
Complex Solution ◽  
The Subject ◽  
User Friendly

Development of an efficient and user friendly application (framework) for modelling microstructure evolution during thermo-mechanical processing using Cellular Automata (CA) method and WorkFlow approach is the subject of the present work. Description of the major assumptions and functionality of the developed framework is presented first. Then, major assumptions of the implemented cellular automata models dealing with simulation of phase transformation and static recrystallization are presented. Finally, the idea of the WorkFlow methodology is described and used to join the two CA microstructure evolution models into one complex solution. Examples of obtained results of microstructure behaviour during thermo-mechanical processing are also presented within the paper.

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