2017
DOI: 10.1590/1980-5373-mr-2016-0459
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Simulation of CP-Ti Recrystallization and Grain Growth by a Cellular Automata Algorithm: Simulated Versus Experimental Results

Abstract: The application of cellular automata in materials science requires the conversion of the automata's rules and abstract general properties to rules and properties associated with the material and phenomena under study. In this paper we propose a model which uses cellular automata to simulate recrystallization and grain growth during isothermal and non-isothermal treatments of cold worked polycrystalline materials. The algorithm's spatial and temporal scaling is based on known experimental results for recrystall… Show more

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Cited by 15 publications
(10 citation statements)
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“…In the CA and phase-field methods, each cell is assigned a unique grain number for identification. In this case, the misorientation between two cells was calculated using the absolute difference between the grain numbers divided by the maximum grain number, as shown in Equation (4) [ 15 ]. where is the misorientation between cells x , y and x + i , y + j ; grain[ x , y ] is the grain number of cell x , y ; and G max is the maximum grain orientation number.…”
Section: Methodsmentioning
confidence: 99%
See 1 more Smart Citation
“…In the CA and phase-field methods, each cell is assigned a unique grain number for identification. In this case, the misorientation between two cells was calculated using the absolute difference between the grain numbers divided by the maximum grain number, as shown in Equation (4) [ 15 ]. where is the misorientation between cells x , y and x + i , y + j ; grain[ x , y ] is the grain number of cell x , y ; and G max is the maximum grain orientation number.…”
Section: Methodsmentioning
confidence: 99%
“…In a previous CA study, a grain orientation was assigned with a grain number [ 15 ]. This simplicity caused a different misorientation distribution from that described in the methods section of the present report.…”
Section: Introductionmentioning
confidence: 99%
“…A lot of similar research dedicated to the simulation of material morphology evolution during SRX by the CA method can be found in the recent scientific literature. [ 138–142 ] Moreover, different papers were dedicated to a wide range of materials [ 143 ] including, e.g., aluminum, [ 125 ] copper, [ 124 ] low‐carbon steel, [ 109 ] Ni‐based superalloy, [ 144 ] TRIP steel, [ 145 ] or ferritic–pearlitic steel. [ 146 ] In addition, interactions between different phenomena, e.g., phase transformations and recrystallization, can also be recreated (see the case study for DP steels annealing cycle).…”
Section: Ca Models Of Static Recrystallizationmentioning
confidence: 99%
“…Extensive research on the applications of CA to modelling microstructure evolution is continued (Song et al, 2015) and recent focus is on 3D solution and reduction of computing costs by distributed computing; see eg. Lian et al (2018), and on application to different metallic materials as well as experimental validation (Contieri et al, 2017).…”
Section: Full Field Modelsmentioning
confidence: 99%