Large-Scale 3D Model and Quantitative Characterization of Grain Microstrcture Based on Monte Carlo Potts Simulation

In order to improve the statistics of 3D grain microstructure models, a large-scale 3D digital model of microstructures of polycrystalline materials was implemented using Monte Carlo Potts simulation. The quantitative characterization and 3D visualizing of the model were carried out. The results show that the grain size distribution and the grain face number distribution in this model can be fitted approximately by the lognormal function, with an average grain face number of 13.8±0.1, very similar to the polycrystalline microstructure in real material.