A Monte Carlo Method for Single Phase Normal Grain Growth with Improved Accuracy and Efficiency
Yu, Q. & Esche, S. K.
Computational Materials Science, Vol. 27, No. 3, pp. 259-270, 2003.
Abstract
Modifications to the original two-dimensional Monte Carlo algorithm for single phase normal grain growth are proposed.
This modified algorithm correctly reproduces the kinetics of the microstructure evolution and generates time-invariant normalized grain size distributions for normal grain growth.
Compared with previous implementations of the Monte Carlo algorithm, the modifications described here lead to significantly higher computational efficiency.
Furthermore, they shorten the initial transition region with nonlinear growth characteristics and generate an average grain growth exponent of 0.49 ± 0.01 for the subsequent time region with linear growth.
In addition, they reduce the dependence of the algorithm on the seed.
These improvements can be mainly attributed to the agreement of the proposed algorithm with theoretical grain growth models and the achieved homogenous grain growth over the entire domain.