The role of neighborhood density in the random cellular automata model of grain growth

• Autorzy: Czarnecki Michał , Sitko Mateusz , Madej Łukasz
• Języki publikacji: EN

Abstrakty

EN

The paper focuses on adapting the random cellular automata (RCA) method concept for the unconstrained grain growth simulation providing digital microstructure morphologies for subsequent multi-scale simulations. First, algorithms for the generation of initial RCA cells alignment are developed, and then the influence of cells density in the computational domain on grain growth is discussed. Three different approaches are proposed based on the regular, hexagonal, and random cells’ alignment in the former case. The importance of cellular automata (CA) cell neighborhood definition on grain growth model predictions is also highlighted. As a research outcome, random cellular automata model parameters that can replicate grain growth without artifacts are presented. It is identified that the acceptable microstructure morphology of the solid material is obtained when a mean number of RCA cells in the investigated neighborhood is higher than ten.

Słowa kluczowe

EN

random cellular automata; grain growth; digital material representation

• Wydawca: Wydawnictwa AGH
• Czasopismo: Computer Methods in Materials Science
• Rocznik: 2021
• Tom: Vol. 21, No. 3
• Strony: 129--137
• Opis fizyczny: Bibliogr. 21 poz., rys.

Twórcy

autor

Czarnecki Michał

• AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, al. A. Mickiewicza 30, 30-059 Krakow, Poland

• https://orcid.org/0000-0001-8236-8578

autor

Sitko Mateusz

• AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, al. A. Mickiewicza 30, 30-059 Krakow, Poland

• https://orcid.org/0000-0003-0893-8784

autor

Madej Łukasz

• AGH University of Science and Technology, Faculty of Metals Engineering and Industrial Computer Science, al. A. Mickiewicza 30, 30-059 Krakow, Poland

• https://orcid.org/0000-0003-1032-6963

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).