A Three-Dimensional Cellular Automata Model for Dendrite Growth with Various Crystallographic Orientations During Solidification

Zhao, Yuhong; Chen, Dengfu; Long, Mujun; Arif, Tansel T.; Qin, Rongshan

doi:10.1007/s11663-013-9960-3

Cited by 13 publications

(4 citation statements)

References 34 publications

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“…However, three-dimensional grain growth [6][7][8][9] can reflect the internal structure of materials more intuitively than two-dimensional grain growth. At present, some researchers are gradually exploring threedimensional space [10][11][12][13] on the basis of two-dimensional research. Wang et al [14] considered the growth mechanism driven by curvature and thermodynamics and used 3D-CA model to simulate the normal austenite grain growth process.…”

Section: Introductionmentioning

confidence: 99%

“…Wang et al [14] considered the growth mechanism driven by curvature and thermodynamics and used 3D-CA model to simulate the normal austenite grain growth process. Zhao et al [13] established an improved 3D-CA model to dynamically simulate the equiaxed grain growth process in the annealing process of metal materials. Guoquan et al [15] used the Monte Carlo method to simulate the grain growth process of two kinds of initial grains (β � 2.96, β � 3.47) with the Weibull distribution.…”

Section: Introductionmentioning

confidence: 99%

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Grain Growth of AZ31 Magnesium Alloy Based on Three‐Dimensional Cellular Automata

Liu

Chu

et al. 2020

Advances in Materials Science and Engineering

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Based on the thermodynamic conversion mechanism and energy transition principle, a three-dimensional cellular automata model of grain growth is established from the aspects of grain orientation, grain size distribution, grain growth kinetics, and grain topology. Also, the effect of temperature on the three-dimensional grain growth process of AZ31 magnesium alloy is analyzed. The results show that the normal growth of three-dimensional grains satisfies the Aboav-weaire equation, the average number of grain planes is between 12 and 14 at 420°C and 2000 CAS, and the maximum number of grain planes is more than 40. Grains of different sizes are distributed normally at different times, most of which are grains with the ratio of grain diameter to average grain diameter R/Rm ≈ 1.0, which meets the minimum energy criterion of grain evolution. The grain of AZ31 magnesium alloy increases in size with the increase of temperature, and the number of grains decreases with the increase in time. The angle between the two-dimensional slices of three-dimensional grains is approximately 120°, which is consistent with that of the traditional two-dimensional cellular automata. The relative error of grain size before and after heat preservation is in the range of 0.1–0.6 μm, which indicates that the 3D cellular automata can accurately simulate the heat preservation process of AZ31 magnesium alloy.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Grain Growth of AZ31 Magnesium Alloy Based on Three‐Dimensional Cellular Automata

Liu

Chu

et al. 2020

Advances in Materials Science and Engineering

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“…In this model, two interface free energy anisotropy parameters were employed in order to simulate the dendrite orientation selection. Zhao et al [23] developed a new tracking neighborhood rule for simulating 3-D dendrite growth in different crystallographic orientations, while the migration of the S/L interface is determined using the phase transition driving force obtained from a thermodynamic database. Zhang et al [24] recently developed a cellular automaton model for describing dendrite growth in multi-component alloys in which the interactions between alloying elements were considered through a coupling of kinetic and thermodynamic calculations.…”

Section: Introductionmentioning

confidence: 99%

Cellular automaton simulation of three-dimensional dendrite growth in Al–7Si–Mg ternary aluminum alloys

Chen

Liu

2015

Computational Materials Science

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a b s t r a c tDue to the extensive applications in the automotive and aerospace industries of Al-7Si-Mg casting alloys, an understanding of their dendrite microstructural formation in three dimensions is of great importance in order to control the desirable microstructure, so as to modify the performance of castings. For this reason, a three-dimensional cellular automaton model (3-D CA) allowing for the prediction of dendrite growth of ternary alloys is presented. The growth kinetics of the solid/liquid (S/L) interface is calculated based on the solutal equilibrium approach. This proposed model introduces a modified decentered octahedron algorithm for neighborhood tracking, in order to eliminate the effects of mesh dependency on dendrite growth. The thermodynamic and kinetic data needed in the simulations are obtained through coupling with the Pandat software package in combination with thermodynamic/kinetic/equilibrium phase diagram calculation databases. The solute interactions between alloying elements are considered in the model. The model was first used to simulate the Al-7Si dendrite, followed by a validation using theoretical predictions. The influence of Mg content on the dendrite growth dynamics and dendrite morphologies was investigated. Also, the model was applied to Al-7Si-0.5Mg dendrite simulation both with and without a consideration of solute interactions between the Si and Mg alloying elements and the effects on dendrite growth process was analyzed using the simulation results. This model was finally used in order to simulate the dendrite growth in different crystallographic orientations in an Al-7Si-0.36Mg ternary alloy during polycrystalline solidification, resulting in a predicted secondary dendrite arm spacing (SDAS) and dendrite volume fraction data that show a reasonable agreement with experimental results. The single dendrite and polycrystalline growth simulations effectively demonstrate the capability of this model in predicting the three-dimensional dendrite microstructure of ternary alloys. Ó 2015 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http:// creativecommons.org/licenses/by-nc-nd/4.0/).

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“…A disadvantage of the approach is that the simulations are time consuming because of the multi-layer mesh. A tracking neighborhood method was proposed by Zhao et al [18]. Following the approach, the centers of the nearest neighbors of the ith cell (nucleus) are considered to potentially belong to the ith grain depending on the grain growth orientation.…”

Section: Introductionmentioning

confidence: 99%

A solution to the problem of the mesh anisotropy in cellular automata simulations of grain growth

Zinovieva

Zinoviev

Ploshikhin

et al. 2015

Computational Materials Science

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A Three-Dimensional Cellular Automata Model for Dendrite Growth with Various Crystallographic Orientations During Solidification

Cited by 13 publications

References 34 publications

Grain Growth of AZ31 Magnesium Alloy Based on Three‐Dimensional Cellular Automata

Grain Growth of AZ31 Magnesium Alloy Based on Three‐Dimensional Cellular Automata

Cellular automaton simulation of three-dimensional dendrite growth in Al–7Si–Mg ternary aluminum alloys

A solution to the problem of the mesh anisotropy in cellular automata simulations of grain growth

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