Influences of Flow Intensity, Cooling Rate and Nucleation Density at Ingot Surface on Deflective Growth of Dendrites for Al-based Alloy

Zhang, Hongwei; Nakajima, Keiji; Wang, Xing; Wang, Aili; He, Jicheng

doi:10.2355/isijinternational.49.1010

Cited by 4 publications

(3 citation statements)

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“…It can calculate just a dendrite tip growth velocity as a function of both the intensity and the orientation of the fluid flow with respect to the dendrite growth direction. 61) For computational efficiency, most researchers use a simplified form (using either a polynominal law or a power law) of the above growth kinetics by a direct interpolation of the velocity versus the undercooling relationship.…”

Section: Mesoscopic-scale Ca (Grain Envelope Evolution)mentioning

confidence: 99%

“…Even in the presence of fluid flow, where each dendrite tip growth velocity is different due to both the effects of the intensity and the orientation of the fluid flow with respect to the dendrite growth direction, it results in the "irregular decentredquadrilateral" growth algorithm for a 2D case. [34][35][36]61) Recently, using the third algorithm, Gandin et al proposed the coupled Cellular Automaton-Finite Element (CA-FE) model, for the prediction of the interaction between the formation of the grain structure and the macrosegregation. This was additionally coupled with the calculation of a solid and liquid flow induced macrosegregation.…”

Section: Mesoscopic-scale Ca (Grain Envelope Evolution)mentioning

confidence: 99%

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Methodological Progress for Computer Simulation of Solidification and Casting

Nakajima

Zhang²,

Oikawa

et al. 2010

ISIJ Int.

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The dramatic progress made over the last 10 to 15 years in the field of "computer simulation of solidification and casting" is greatly due to the supports by academic as well as industrial research. The driving force behind this undertaking was the promise of predictive capabilities that will allow process and material developments. Here, the recent works on modeling were summarized, for the macrosegregation in the macroscale simulation, and the Cellular Automaton, the solidification path combined with the microsegregation, the phase-field model in the meso-scale and micro-scale simulation.

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Section: Mesoscopic-scale Ca (Grain Envelope Evolution)mentioning

confidence: 99%

Section: Mesoscopic-scale Ca (Grain Envelope Evolution)mentioning

confidence: 99%

Methodological Progress for Computer Simulation of Solidification and Casting

Nakajima

Zhang²,

Oikawa

et al. 2010

ISIJ Int.

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“…In the previous work of the authors, 1,2) the effects of the nucleation parameters (including the nucleation density, the nucleation undercooling in bulk and at surface), and the operation parameters (such as the initial concentration of an alloy, the cooling rate, the flow velocity, etc.) on the solidification morphologies are deeply analyzed.…”

Section: Introductionmentioning

confidence: 99%

Restrictions of Physical Properties on Solidification Microstructures of Al-based Binary Alloys by Cellular Automaton

Zhang¹,

Nakajima

Lei³

et al. 2010

ISIJ Int.

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Fig. 1. Dendrite tip growth kinetics predicted by the GGAN model, i.e. Eq. (6), the simplified expressions based on KGT model (Refs. 14), 15)) and the present simplified expression based on GGAN model (Eq. (8)).by CA-FD coupling model. The related physical properties for Al-3mass%Si and Al-3mass%Cu alloy are shown in Tables 1 and 2, others can be found in Ref. 1). A seen, the latent heat of the solidification is regarded as the functions of the solute concentration in order to fit with Kobayashi's model. 8)The cooling rate in intermediate position Ṫ is set as 0.7, 2.3 and 5.0 K/s. The heat transfer coefficient h corresponding to each alloy and Ṫ is obtained beforehand through several attempts. Since this work mainly discusses the influences of the physical properties on the solidification morphologies, most of the nucleation parameters are fixed, such as n V *ϭ200ϫ10 4 m Ϫ2 , DT S ϭ1 K, DT S,s ϭ0.1 K, and DT V,s ϭ 0.1 K, except the nucleation undercooling in the bulk of liquid DT V and the nucleation density at the surface n S *. The former one is changed for the determination of the critical range for the CET, and the latter one is determined by the primary arm spacing, i.e. n S *ϭ1/l 1 , which is related to the cooling rate at the surface, as seen in Table 1.The heat transfer equation combined with microsegregation model and energy balance is adopted to obtain the temperature field. The temperature is then interpolated into CA ISIJ International, Vol. 50 (2010), No. 12 1837 © 2010 ISIJ Table 1. Thermophysical properties of Al-3mass%Si and Al-3mass%Cu alloy. cells. The Gaussian distribution is adopted for the nucleation procedure, the GGAN model for predicting the dendrite tip growth rate of Al-Si and Al-Cu alloys and the decentred square growth algorithm are used for the grain growth procedure. Physical Properties Influencing Heat TransferHeat transfer is the basic stage for the solidification and evolution of the morphologies. Figure 2 plots the cooling curves for Al-3mass%Si and Al-3mass%Cu alloy in the same cooling rate in intermediate position Ṫ. The curves show the same tendency that the slope of the curve becomes smaller temporarily due to the appearance of the primary phase and the eutectic phase. After the completion of the solidification, the slope returns to the original state. Here the cooling rates at the three positions (intermediate, center and surface) are defined by the ratio of the temperature decrease to the solidification time.With different solute in Al melt, the solidification interval is different due to their different slope of the liquidus and different eutectic temperature. As illustrated in the cooling curves in Fig. 2, since the slope of the liquidus for Al-3mass%Si alloy is larger than that for Al-3mass%Cu alloy, with the same solute concentration, the liquidus temperature for Al-3mass%Si alloy is lower. And the eutectic temperature of Al-3mass%Si alloy (577°C) is higher than that of Al-3mass%Cu alloy (548°C). So the solidification interval, resulting from both the decrease of the ...

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