A Monte Carlo algorithm for single phase normal grain growth with improved accuracy and efficiency

• Published in: Computational materials science Vol. 27; no. 3; pp. 259 - 270
• Main Authors: Yu, Qiang, Esche, Sven K.
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 01.05.2003; Elsevier Science
• Subjects: Computer simulation; Cross-disciplinary physics: materials science; rheology; Exact sciences and technology; Grain boundary; Grain growth; Grain growth kinetics; Materials science; Monte Carlo method; Other heat and thermomechanical treatments; Physics; Single phase materials; Treatment of materials and its effects on microstructure and properties; Grain growth kinetics; Monte Carlo method; Computer simulation; Grain growth; Single phase materials; Grain boundary; Grain size; Grain boundaries; Finite size effect; Digital simulation; Theoretical study; Computerized simulation; Monte Carlo methods; Growth mechanism; Object oriented; Kinetics; Microstructure
• ISSN: 0927-0256; 1879-0801
• DOI: 10.1016/S0927-0256(02)00361-0

A modified two-dimensional Monte Carlo algorithm for single phase normal grain growth is proposed, which was inspired by physical grain growth mechanisms and was designed using object-oriented techniques. It leads to improved agreement of the simulation results with theoretical grain growth models, exhibits a significantly higher computational efficiency and reduces the influence of the seed on the simulation results. It was previously believed that the numerical finite size effects, which cause a lower grain growth exponent in the small grain size regime, are likely to dominate in the early stages of Monte Carlo simulations. In contrast to this conclusion, the modified algorithm proposed here correctly reproduces the theoretical predictions even in the small grain size regime and thus strongly supports the theoretical work on the relationship between self-similarity and grain growth kinetics. It can therefore be concluded that the grain boundary movement mechanism as modeled using the Monte Carlo technique inherently results in parabolic grain growth kinetics.