Simulation of curvature-driven grain growth by using a modified monte carlo algorithm

B. Radhakrishnan, T. Zacharia

Research output: Contribution to journalArticlepeer-review

142 Scopus citations

Abstract

The Monte Carlo (MC) algorithm that currently exists in the literature for simulating curvature-driven grain growth has been modified. The modified algorithm results in an acceleration of the simulated grain growth and an early estimate of the grain growth exponent that is close to the theoretical value of 0.5. The upper limit of grain size distributions obtained with the new algorithm is significantly lower than that obtained with the old, because the new algorithm eliminates grain coalescence during grain growth. The log-normal function provides an excellent fit to the grain size distribution data obtained with the new algorithm, after taking into account the anisotropy in grain boundary energy.

Original languageEnglish
Pages (from-to)167-180
Number of pages14
JournalMetallurgical and Materials Transactions A: Physical Metallurgy and Materials Science
Volume26
Issue number1
DOIs
StatePublished - Jan 1995

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