Szczegóły publikacji
Opis bibliograficzny
The role of the cellular automata cell size and time step length in the microstructure evolution model - the static recrystallization case study / Mateusz SITKO, Łukasz MADEJ // Journal of Computational Science ; ISSN 1877-7503. — 2021 — vol. 54 art. no. 101437, s. 1–14. — Bibliogr. s. 13–14, Abstr. — Publikacja dostępna online od: 2021-08-16
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 135637 |
|---|---|
| Data dodania do BaDAP | 2021-09-03 |
| Tekst źródłowy | URL |
| DOI | 10.1016/j.jocs.2021.101437 |
| Rok publikacji | 2021 |
| Typ publikacji | artykuł w czasopiśmie |
| Otwarty dostęp |  |
| Czasopismo/seria | Journal of Computational Science |
Abstract
The paper's main interest is the identification and elimination of major factors that can introduce disturbances in the predictions of the cellular automata (CA) static recrystallization (SRX) model. First, the most important CA SRX model components and major assumptions are shortly presented. Next, the determination of appropriate CA cell size, which is related to the CA space resolution, and CA time step length, is discussed. The new grain nucleation algorithm is also developed and is presented next. This research proved that such an algorithm is insensitive to the CA space size, increasing the model reliability in numerical simulation of SRX. Then, the minimum CA time step length, which does not affect the results and, at the same time, provides acceptable calculation time, is established. Obtained results indicate threshold values for both CA cell size and CA time step length that have to be reached to obtain reliable model predictions. The research outcome highlighted that the CA cell size of 0.375 μm is sufficient to discretize the area of 300 × 300 μm, and provide reliable results in an acceptable computational time. Finally, to accelerate the process of time step length identification, a new adaptation algorithm is also introduced. It is presented that such an algorithm provides reliable results in the shortest possible time.
