Szczegóły publikacji
Opis bibliograficzny
Mesh sensitivity study in the random cellular automata finite element model of dynamic recrystallization / SITKO Mateusz, PAWLIKOWSKI Kacper, PERZYŃSKI Konrad, MADEJ Łukasz // W: ESAFORM 2024 [Dokument elektroniczny] : the 27th international ESAFORM conference on Material Forming : April 24–26, 2024, Toulouse, France / eds. Anna Carla Araujo, [et al.]. — Wersja do Windows. — Dane tekstowe. — Millersville : Materials Research Forum LLC, cop. 2024. — (Materials Research Proceedings ; ISSN 2474-3941 ; vol. 41). — e-ISBN: 978-1-64490-313-1. — S. 2271-2277. — Wymagania systemowe: Adobe Reader. — Biliogr. s. 2275-2276, Abstr. — Publikacja dostępna online od: 2024-04-24
Autorzy (4)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 153001 |
|---|---|
| Data dodania do BaDAP | 2024-05-21 |
| Tekst źródłowy | URL |
| DOI | 10.21741/9781644903131-250 |
| Rok publikacji | 2024 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp | |
| Creative Commons | |
| Czasopismo/seria | Materials Research Proceedings |
Abstract
Predicting microstructure morphology evolution under hot forming conditions and determining final material properties are essential for optimizing metal-forming processes. Cellular Automata (CA) is a widely employed full-field method for modeling microstructure morphology changes during various metal-forming processes. However, at higher temperatures and under conditions of substantial microstructure evolution, the CA method encounters limitations related to computational domain geometry changes. The use of random cellular automata (RCA) offers a more realistic representation of this phenomenon, although it requires additional effort in algorithm optimization for acceptable execution times. This paper contributes to an overarching research effort focused on developing a discontinuous dynamic recrystallization model (DRX) by directly incorporating RCA into the finite element (FE) framework. Different mesh sizes and their impact on the quality of the results are analyzed, and the minimum number of elements that do not degrade the results in the CA model are selected. The investigation aims to enhance the practicality of the proposed model, striking a balance between realistic microstructure representation and computational efficiency.