M. P. Anderson

TL;DR: In this paper, a Monte Carlo procedure is applied to the study of grain growth in two dimensions, where the initial distribution of orientations is chosen at random and the system evolves so as to reduce the number of nearest neighbor pairs of unlike crystallographic orientation.

TL;DR: In this article, the authors analyzed the microstructures produced by the grain growth simulation technique described in the previous paper and found that the grain size distribution function is time invariant when the grain sizes, R, is scaled by the mean grain size, R, and is shown to fit the experimental data better than either the log-normal function or the grain distribution function suggested by Hillert.

TL;DR: In this paper, a modified version of Hillert's grain growth model is presented, in which two distinct types of grains are present, and anisotropic grain boundary energies are modeled by assigning a higher energy to boundaries between like type than to boundaries of unlike type.

TL;DR: In this paper, the microstructure of polycrystalline materials is digitized by dividing the polycrystaline material into small volume elements and storing the spatial location and crystallographic orientation of each element.

TL;DR: In this article, a Monte Carlo computer simulation technique is applied to the problem of recrystallization, in which a continuum system is modeled employing a discrete lattice, and the nucleation rate is chosen as either constant or site saturated.