The prediction of solidification behavior is important for optimizing manufacturing processes for metallic products, from traditional methods to advanced technologies, such as additive manufacturing. However, representative computational simulation methods for solidification are challenging to use in practical applications owing to their substantial computational costs. In the present work, a simulation model for solidification was developed based on the Monte Carlo algorithm, which features low computational cost and effectively captures the key aspects of solidification kinetics. The model simultaneously accounts for grain growth, nucleation, and epitaxial growth, reproducing solidification microstructures and quantitative solidification kinetics, consistent with common knowledge and experimental observations. Furthermore, microstructural evolution during practical processes was successfully reproduced at realistic process scales. This model is expected to serve as an effective tool for microstructure design and process optimization in metallic products with broad applications in the field of materials science.
Oh et al. (Mon,) studied this question.
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