Numerical calculation of microsegregation in coarsened dendritic microstructures

Roósz, András; Halder, E.; Exner, Hans Eckart

doi:10.1179/026708386790328588

Cited by 22 publications

(13 citation statements)

References 8 publications

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“…This work could be extended to examine if the WIRS method is sensitive to a change in the cooling rate or the size in microstructure. This study could be led with directional solidification experiments or directly from the wedge [40] 4.80 · 10 -5 exp (-16,069/T) [41] Si 0.08 · 10 -7 exp (-2856/T) [42] 2.02 · 10 -4 exp (-16,069/T) [42] casting, where a wide range of microstructure sizes and local solidification times can be observed. In this last case, a micro-macro model would be required to be compared to the experimental data.…”

Section: Discussionmentioning

confidence: 99%

Quantification of Microsegregation in Cast Al-Si-Cu Alloys

Ganesan

Thuinet

Dye

et al. 2007

Metall Mater Trans B

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The random sampling approach offers an elegant yet accurate way of validating microsegregation models. However, both instrumental errors and interference from secondary phases complicate the treatment of randomly sampled microprobe data. This study demonstrates that the normal procedure of sorting the data for each element independently can lead to inaccurate estimation of segregation profiles within multicomponent, multiphase, aluminum alloys. A recently proposed alloy-independent approach is shown to more reliably isolate these interferences, allowing more accurate validation of microsegregation models. Application of this approach to examine solidification segregation of a 319-type alloy demonstrated that, for these slowly cooled castings, neither Sr or TiB 2 additions significantly affected coring of Cu within the primary a-Al dendrites. Comparison against predictions of CALPHAD-type Gulliver-Scheil models was less satisfactory. Consideration of back-diffusion and morphology effects through a one-dimensional (1-D) numerical model do not improve the agreement. Possible reasons for the lack of agreement are hypothesized.

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Section: Discussionmentioning

confidence: 99%

Quantification of Microsegregation in Cast Al-Si-Cu Alloys

Ganesan

Thuinet

Dye

et al. 2007

Metall Mater Trans B

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“…Equation [4] can be formulated in analogy to the lever rule for a multicomponent system. The liquid phase L is still considered to be a complete mixture phase.…”

Section: A Mass Balancementioning

confidence: 99%

“…The liquid phase L is still considered to be a complete mixture phase. But as the solid phases j show finite diffusion, the average molar concentration for each component k is used in the mass balance: [4] The general correlation of df with the cross-sectional area A of a phase j can be derived from the definition of A in Eq. [1]: [5] Here, l is the length of the control unit, which corresponds in our model to half of the dendrite arm spacing l. Thus, the differential precipitation df j can be expressed as [6] df j ϭ df j a n iϭ1 df i и a n iϭ1 df i ϭ df j a n iϭ1 df i…”

Section: A Mass Balancementioning

confidence: 99%

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Simulation of macroscopic solidification with an incorporated one-dimensional microsegregation model coupled to thermodynamic software

Pustal¹,

Ludwig²,

Sahm³

et al. 2003

Metall Mater Trans B

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In this article, a numerical model is presented which predicts phase distributions and dendrite arm spacings for a realistic casting within suitable CPU time. Three software components are coupled to perform calculations: (1) an FEM simulation package for the macroscopic temperature field, (2) an FDM code for the microstructure parameters, and (3) a thermodynamic software package for equilibrium calculations at the interfaces. The macrosoftware provides the micromodule with the present temperature at each node of a finite-element grid. At each such node, the micromodule calculates the dendrite arm spacings, the phase amounts, and the diffusion-controlled segregation profiles for the current time-step using equilibrium information from the thermodynamic software. A change of solid fraction and of the phase concentrations results in the release of latent heat and in the change of the heat capacity. These values are used as input parameters in the macrosoftware for the temperature calculation in the next time-step. Simulations have been performed for the ternary alloy AlCu4Mg1 and the results have been compared to "traditional" temperature calculations and to experimentally determined phase fractions and dendrite arm spacings. Measurements have been done by means of an interactive image analysis system over the entire breadth of an ingot casting at four different heights as well as at three different longitudinal cuts.

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“…The coarsening rate of all simulations performed was calculated using the model of Roósz et al, [7] which considers only the ripening of dendrite arms. Coalescence, which dominates toward the end of solidification, is not considered due to the fact that its influence on coarsening is small and, therefore, can be neglected in microsegregation simulations.…”

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confidence: 99%