Randomly grain growth in metallic materials

Computational modeling of grain structures is a very important topic in materials science. In this work, the development of the computational algorithms for a mathematical model to predict grain nucleation and grain growth is presented. The model place a number of nucleated points randomly in a liquid pool according with the solid and liquid fractions (X_sol and X_liq) of metal solute and the local temperature distribution (SS_I,J). Then these points grows isotropically until obtain a grain structure with straight interfaces. Different grain morphologies such as columnar and equiaxed can be obtained as a function of the temperature distributions and growth directions.