SIMULATION OF CURVATURE-DRIVEN GRAIN-GROWTH BY USING A MODIFIED MONTE-CARLO ALGORITHM

The Monte Carlo (MC) algorithm that currently exists in the literature for simulating curvature-driven grain growth has been modified. The m odified algorithm results in an acceleration of the simulated grain gr owth 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 distrib utions obtained with the new algorithm is significantly lower than tha t obtained with the old, because the new algorithm eliminates grain co alescence during grain growth. The log-normal function provides an exc ellent fit to the grain size distribution data obtained with the new a lgorithm, after taking into account the anisotropy in grain boundary e nergy.