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Sparse Thermal Data for CA Modeling by shayan is a document available to read on EtoBox.
The manuscript discusses a novel approach to modeling grain structure in additive manufacturing using cellular automata (CA) that decouples temperature data from heat transport simulations. This method significantly reduces the amount of temperature data needed, improving computational efficiency while maintaining accuracy in predicting grain size and microstructure. The findings suggest that this approach can effectively simulate large solidification domains and address uncertainties in microstructure deve
- Author
- shayan
- Language
- EN