Szczegóły publikacji
Opis bibliograficzny
Full-field approaches for austenite-ferrite phase transformation simulations / Mariusz WERMIŃSKI, Mateusz SITKO, Łukasz MADEJ // Computer Methods in Materials Science : quarterly / Akademia Górniczo-Hutnicza ; ISSN 2720-4081 . — Tytuł poprz.: Informatyka w Technologii Materiałów ; ISSN: 1641-3948. — 2025 — vol. 25 no. 4, s. 5–29. — Bibliogr. s. 23–29, Abstr. — Publikacja dostępna online od: 2025-12-02
Autorzy (3)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 165110 |
|---|---|
| Data dodania do BaDAP | 2026-01-08 |
| Tekst źródłowy | URL |
| DOI | 10.7494/cmms.2025.4.1029 |
| Rok publikacji | 2025 |
| Typ publikacji | przegląd |
| Otwarty dostęp |  |
| Creative Commons | |
| Czasopismo/seria | Computer Methods in Materials Science |
Abstract
Understanding the local evolution of phase transformations in steels, particularly the γ (austenite) → α (ferrite) transformation, is crucial for controlling the microstructure and properties of steel components. Over recent decades, significant progress has been made in the numerical modeling of this complex phenomenon. This development has been driven by both scientific curiosity and industrial needs, especially in processes such as hot rolling, forging, thermal treatment, etc. The developed models have evolved from simple solutions based on local equilibrium to more complex approaches that consider local heterogeneities. Modern computational approaches, such as Phase-Field (PF), Level-Set (LS), Cellular Automata (CA), Monte Carlo (MC) or Vertex based simulations, allow for the precise reproduction of microstructural evolution considering local instabilities. They also enable the analysis of phase boundary motion in an explicit manner. These techniques also allow for direct integration with thermodynamic data and mechanical models, thereby better capturing the physical mechanisms of phase transformations, such as chemical composition, diffusion resistance, or the influence of deformation. An overview of the state of the art in this area is presented within the paper. The model’s concepts, assumptions, fundamental equations, advantages, limitations, and potential practical applications are summarized. Special attention is given to modeling the γ → α transformation by the Cellular Automata method. The importance of incorporating phenomena such as diffusion, nucleation, and growth is emphasized. The need for consistency between experimental results and simulations is also highlighted.
