Modelling the Evolution of Microstructure During Recrystallisation

This paper discusses the evolution of the microstructure during grain growth and recrystallisation, modelled using the Monte Carlo technique. The properties of alloys and metals subjected to plastic deformation and annealing are significantly influenced by the grain growth and recrystallisation processes. Modelling the recrystallisation process enables the simulation of various driving forces at a fundamental level by defining energy conditions for each individual element. The calculations facilitate the observation of microstructural evolution and the generation of structures consistent with any set of postulates, allowing both the dynamics and the physical processes of grain growth and recrystallisation to be simulated. The paper describes a recrystallisation model based on a two-dimensional array containing 40 000 elements. Each element in the array is assigned a number symbolising the orientation of the grain in which the given element is embedded, along with a value of the free energy of the grain boundary. The internal energy for a given grain is also specified. Four types of nucleation have been modelled. Based on the results obtained, the Monte Carlo technique is considered to be an effective tool for modelling recrystallisation processes, allowing the introduction of many different driving forces. The model presented in the work enables the simulation of the nature of local energy conditions and dynamics.

Authors

Institutions

Publication Details

Journal
Acta Physica Polonica A
Published
2024-12-01
DOI
https://doi.org/10.12693/aphyspola.146.747
Primary Topic
Metallurgy and Material Forming
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Modelling the Evolution of Microstructure During Recrystallisation

Tomasz Walasek
1 links
Acta Physica Polonica A
Metallurgy and Material Forming
article

Modelling the Evolution of Microstructure During Recrystallisation

Tomasz Walasek
article en

Abstract

This paper discusses the evolution of the microstructure during grain growth and recrystallisation, modelled using the Monte Carlo technique. The properties of alloys and metals subjected to plastic deformation and annealing are significantly influenced by the grain growth and recrystallisation processes. Modelling the recrystallisation process enables the simulation of various driving forces at a fundamental level by defining energy conditions for each individual element. The calculations facilitate the observation of microstructural evolution and the generation of structures consistent with any set of postulates, allowing both the dynamics and the physical processes of grain growth and recrystallisation to be simulated. The paper describes a recrystallisation model based on a two-dimensional array containing 40 000 elements. Each element in the array is assigned a number symbolising the orientation of the grain in which the given element is embedded, along with a value of the free energy of the grain boundary. The internal energy for a given grain is also specified. Four types of nucleation have been modelled. Based on the results obtained, the Monte Carlo technique is considered to be an effective tool for modelling recrystallisation processes, allowing the introduction of many different driving forces. The model presented in the work enables the simulation of the nature of local energy conditions and dynamics.

Acta Physica Polonica AVol. 146(6)
Częstochowa University of Technology (PL)
Openalex Percentile: Top 71%
Metallurgy and Material Forming
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.