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Prediction of grain structure in direct-chill cast Al–Zn–Mg–Cu billets using cellular automaton-finite element method

Minseok Kim, Sang-Hwa Lee, Jae-Gil Jung, Kwangjun Eah

2021Progress in Natural Science Materials International18 citationsDOIOpen Access PDF

Abstract

A cellular automaton-finite element (CA-FE) model was used to predict the solidification grain structure of permanent mold cast A7086 alloy. In this model, a Gaussian distribution of nucleation sites was adopted, and the Kurz-Giovanola-Trivedi model was extended to a multicomponent Al–Zn–Mg–Cu alloy system to determine the growth kinetics of the dendrite tip. For describing the Gaussian distribution of nucleation sites on the mold surface, an empirical relationship between the initial cooling rate of the melt and the nucleation density was proposed. Under various casting conditions, the calculated grain structures agreed well with the experimental results. Subsequently, the model was applied to the direct-chill (DC) cast billets, and the simulated grain structures reproduced well the experimental results. This confirmed that the current CA-FE model can be used practically and effectively in DC casting processes.

Topics & Concepts

NucleationMaterials scienceDendrite (mathematics)Finite element methodAlloyCastingCellular automatonMetallurgyGaussianMoldComposite materialThermodynamicsGeometryMathematicsChemistryAlgorithmPhysicsComputational chemistryAluminum Alloy Microstructure PropertiesSolidification and crystal growth phenomenaAluminum Alloys Composites Properties
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