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.
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Radhakrishnan, B., Zacharia, T. Simulation of curvature-driven grain growth by using a modified monte carlo algorithm. Metall Mater Trans A 26, 167–180 (1995). https://doi.org/10.1007/BF02669802
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DOI: https://doi.org/10.1007/BF02669802