Simulation of recrystallization in iron single crystals

Salazar, Tatiana Caneda; Assis, Weslley Luiz da Silva; Rios, Paulo Rangel

doi:10.1590/s1516-14392008000100021

Cited by 5 publications

(11 citation statements)

References 28 publications

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“…The difference in the shape of the growing simulation region (cube) and the shape of the growing recrystallized grain in the case examined by Salazar et al [5], spherical, was responsible for this difference. This is even more so because of the "stepped" nature of the moving boundary of the simulation.…”

Section: Measurements Of N L and N A In Pure Iron Compared With Valuementioning

confidence: 88%

“…Simulation details can be found in Ref. [4][5][6][7][8][9]. The simulation employed a 22,300 nuclei uniform randomly located within the matrix at the start of the transformation.…”

Section: Computer Simulationmentioning

confidence: 99%

“…Difficulties of comparing recrystallization evolution in a single crystal pure iron with cellular automata simulation were discussed in depth by Salazar et al [5]. The difference in the shape of the growing simulation region (cube) and the shape of the growing recrystallized grain in the case examined by Salazar et al [5], spherical, was responsible for this difference.…”

Section: Measurements Of N L and N A In Pure Iron Compared With Valuementioning

confidence: 99%

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Stereological analysis of the microstructure of pure iron with random nucleation

Souza

Assis

Rios

et al. 2014

Journal of Materials Research and Technology

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StereologyPure iron a b s t r a c t Microstructural characterization of metallic materials is of paramount importance in the qualification and quantification of their desired final properties. Metallic materials have often been characterized by means of optical and electronic microscopy. Results from these techniques are in most of the cases based on 2D analysis. Stereological methods are then employed to obtain 3D information. However, such methods are based on assumptions and approximations of the real material structure. Therefore, it is essential to know the limitations of these methods. A further complication arises when one wishes to compare real materials with computer simulation results and stereological analytical techniques. In this paper, methods normally applied to real microstructure are applied to microstructures simulated by cellular automata (CA) simulation. Experimental results from microstructural characterization of polycrystalline pure iron were used as the starting point for the simulation. Consequently, we could apply analytical formulae of stereology to experimental data from pure iron and to computer generated microstructures from cellular automata simulation. Comparison of analytical formulae, experimental results and computer simulation provided useful insights on limits of applicability and on the meaning of the stereological analysis.

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Section: Measurements Of N L and N A In Pure Iron Compared With Valuementioning

confidence: 88%

“…Simulation details can be found in Ref. [4][5][6][7][8][9]. The simulation employed a 22,300 nuclei uniform randomly located within the matrix at the start of the transformation.…”

Section: Computer Simulationmentioning

confidence: 99%

Section: Measurements Of N L and N A In Pure Iron Compared With Valuementioning

confidence: 99%

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Stereological analysis of the microstructure of pure iron with random nucleation

Souza

Assis

Rios

et al. 2014

Journal of Materials Research and Technology

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“…The simulation methodology used here was employed before 11,12 . Figure 5 shows the principle underlying the methodology.…”

Section: Computer Simulation Methodologymentioning

confidence: 99%

Computer simulation of simultaneous evolution of individual texture components During recrystallization of an IF steel

et al. 2013

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Computer simulation of simultaneous evolution of individual texture components during recrystallization of an IF steel is carried out. A new methodology has been developed that takes as its starting point experimental data of each texture component evolving during recrystallization. In particular, Magnusson et al. data on IF steel was analyzed in a previous work with the help of the exact analytical tools developed by Rios and Villa for simultaneous transformations. From this analysis parameters such as number of nuclei of each texture component per unit of volume could be obtained and were employed as input for the present computer simulation. From this input 3-d microstructures could then be generated. The methodology proposed here combines experimental data, exact analytical methods and computer simulation and may be employed to extract the maximum information from the experimental data.

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“…In previous papers [18][19][20][21][22][23][24] , cellular automata (CA) simulation of phase transformation/recrystallization in 2-d and 3-d were carried out and compared with KJMA analytical solutions. The purpose of the present paper is to simulate phase transformations/recrystallization in by cellular automata (CA) in order to compare the simulation with the analytical solution by Rios and Villa.…”

Section: Introductionmentioning

confidence: 99%

Inhomogeneous Poisson point process nucleation: comparison of analytical solution with cellular automata simulation

et al. 2009

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Microstructural evolution in three dimensions of nucleation and growth transformations is simulated by means of cellular automata (CA). In the simulation, nuclei are located in space according to a heterogeneous Poisson point processes. The simulation is compared with exact analytical solution recently obtained by Rios and Villa supposing that the intensity is a harmonic function of the spatial coordinate. The simulated data gives very good agreement with the analytical solution provided that the correct shape factor for the growing CA grains is used. This good agreement is auspicious because the analytical expressions were derived and thus are exact only if the shape of the growing regions is spherical.

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Simulation of recrystallization in iron single crystals

Cited by 5 publications

References 28 publications

Stereological analysis of the microstructure of pure iron with random nucleation

Stereological analysis of the microstructure of pure iron with random nucleation

Computer simulation of simultaneous evolution of individual texture components During recrystallization of an IF steel

Inhomogeneous Poisson point process nucleation: comparison of analytical solution with cellular automata simulation

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