Stochastic modeling of columnar-to-equiaxed transition in Ti–(45–48at%) Al alloy ingots

Liu, D.R.; Guo, Jingjie; Wu, Shi Ping; Su, Yanqing; Fu, Hengzhi

doi:10.1016/j.msea.2005.09.077

Cited by 16 publications

(7 citation statements)

References 26 publications

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“…Consequently, if both stochastic and deterministic models were used to calculate the CET position for the same nucleation undercooling, the mechanical-blocking fraction for the deterministic model could be obtained independently to give the best agreement between their results. Because the CET observed in macrostructures calculated with the stochastic models, especially those that employ the CA technique, are in good agreement with the actual CET, [23][24][25][26] the blocking fraction derived from the comparison is likely to be a good estimate of the actual fraction.…”

Section: Introductionmentioning

confidence: 97%

Mechanical Blocking Mechanism for the Columnar to Equiaxed Transition

Biscuola

Martorano

2008

Metall Mater Trans A

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Mechanical blocking of the columnar front during the columnar to equiaxed transition (CET) is studied by quantitatively comparing the CET positions obtained with one stochastic model and two deterministic models for the unidirectional solidification of an Al-7 (wt pct) Si alloy. One of the deterministic models is based on the solutal blocking of the columnar front, whereas the other model is based on the mechanical blocking. The solutal-blocking model and the mechanical-blocking model with the traditional blocking fraction of 0.49 give columnar zones larger than those predicted with the stochastic model. When a blocking fraction of 0.2 is adopted, however, the agreement is very good for a range of nucleation undercoolings and number density of equiaxed grains. Therefore, changing the mechanical-blocking fraction in deterministic models from 0.49 to 0.2 seems to model more accurately the mechanical-blocking process that can lead to the CET.

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Section: Introductionmentioning

confidence: 97%

Mechanical Blocking Mechanism for the Columnar to Equiaxed Transition

Biscuola

Martorano

2008

Metall Mater Trans A

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“…Some other authors remark the importance of the mushy on the final structure [13,[18][19][20][21][23][24][25][26][27]. The problem of transitions zones is also treated by some authors [21]. Nevertheless the presented work treats the problem of the grain structure formation during solidification of a steel squared billet using information about the heat removal.…”

Section: Introductionmentioning

confidence: 98%

“…About it, all the models also [2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19][20][21] treat the solidification problem as a function of the nucleation and grain growth. Some authors [16] have simulated this process using parallel computing methods.…”

Section: Introductionmentioning

confidence: 99%

“…Some of them [12,15,17] treat specific problems such as the interruption of grain growth due to some phases or inclusions the solidification of the melt. The problem about the scales for simulation is also treated by some of them including the limits of the graphical representation [18][19][20][21]. Some other authors remark the importance of the mushy on the final structure [13,[18][19][20][21][23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

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Dynamic formation of primary grain structures on squared steel billets produced by continuous casting (computer simulation)

Ramı́rez-López

Muñoz

Palomar-Pardavé

et al. 2016

Int J Adv Manuf Technol

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The present work is dedicated to explain the development of a computational model for simulating the grain structure formed in a squared billet produced by continuous casting. During steel solidification, three different grain structures are formed as a function of the heat removal conditions. The solidification times previously calculated using a finite difference method were used as input data in order to simulate dynamically the evolution of the grain formation. Computational routines for grouping, counting and classifying have been programmed to evidence the influence of the solidification speed on the grain morphology resulted. Criterions based on solidification speed and time on mushy are used to establish the transitions zones between chill, columnar and equiaxed grains. Routines to simulate grain nucleation and growth based on chaos theory have been included to create a graphical cellular automaton on the computer screen to animate the grain structure formation.

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“…Other researchers have been developing models to calculate the geometrical and phase transformation during recrystallization [4,10]. The cellular automaton theory has also been used to create models for phase transformations and simulate the microstructures of grains for different metals [9,11,16,[20][21]. While other researchers have given relevant importance to the simulation scales (micro, meso, and macro) [15].…”

Section: Introductionmentioning

confidence: 99%

Computational algorithms for simulating the grain structure formed on steel billets using cellular automaton and chaos theories

Ramı́rez-López

Soto-Cortés

Gonzalez-Trejo

et al. 2011

Int J Miner Metall Mater

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The development of some computational algorithms based on cellular automaton was described to simulate the structures formed during the solidification of steel products. The algorithms described take results from the steel thermal behavior and heat removal previously calculated using a simulator developed by present authors in a previous work. Stored time is used for displaying the steel transition from liquid to mushy and solid. And it is also used to command computational subroutines that reproduce nucleation and grain growth. These routines are logically programmed using the programming language C++ and are based on a simultaneous solution of numerical methods (stochastic and deterministic) to create a graphical representation of different grain structures formed. The grain structure obtained is displayed on the computer screen using a graphical user interface (GUI). The chaos theory and random generation numbers are included in the algorithms to simulate the heterogeneity of grain sizes and morphologies.

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Stochastic modeling of columnar-to-equiaxed transition in Ti–(45–48at%) Al alloy ingots

Cited by 16 publications

References 26 publications

Mechanical Blocking Mechanism for the Columnar to Equiaxed Transition

Mechanical Blocking Mechanism for the Columnar to Equiaxed Transition

Dynamic formation of primary grain structures on squared steel billets produced by continuous casting (computer simulation)

Computational algorithms for simulating the grain structure formed on steel billets using cellular automaton and chaos theories

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