Numerical Simulation of Microstructure Evolution in Solidification Process of Ferritic Stainless Steel with Cellular Automaton

Abstract

In order to study the basic principles of vibration-excited liquid metal nucleation technology, a coupled model to connect the temperature field calculated by ANSYS Fluent and the dendritic growth simulated by cellular automaton (CA) algorithm was proposed. A two-dimensional CA model for dendrite growth controlled by solute diffusion and local curvature effects with random zigzag capture rule was developed. The proposed model was applied to simulate the temporal evolution of solidification microstructures under different degrees of surface undercooling and vibration frequency of the crystal nucleus generator conditions. The simulation results showed that the predicted columnar dendrites regions were more developed, the ratio of interior equiaxed dendrite reduced and the size of dendrites increased with the increase of the surface undercooling degrees on the crystal nucleus generator. It was caused by a large temperature gradient formed in the melt. The columnar-to-equiaxed transition (CET) was promoted, and the refined grains and homogenized microstructure were also achieved at the high vibration frequency of the crystal nucleus generator. The influences of the different process parameters on the temperature gradient and cooling rates in the mushy zone were investigated in detail. A lower cooling intensity and a uniform temperature gradient distribution could promote nucleation and refine grains. The present research has guiding significance for the process parameter selection in the actual experimental.

Cellular Automaton Simulation of Dendrite Growth in Solidification Process of Cr17 Stainless Steel under Mechanical Vibration

“…To calculate the temperature field, the simulation results can date back to existing research work. [ 2,28 ] In this article, the temperature field calculation data was coupled to the CA model, exploiting the displayed linear interpolation method. Cr17 stainless steel was selected as the test material, and the parameters are listed in Table 1 .…”

Grid anisotropy reduction method for cellular automata based solidification models

“…To the best of the authors' knowledge, at this point in time, the study on the improvement in capture rules has not led to further new rules being proposed. The most recent CA studies of solidification have employed the de-centred square algorithm [15,16,31], zigzag [32], and LNSF [33,34] for microstructure modelling, whereas GARED has been used for meso-scale models [35]. However, as discussed earlier, quantitative information such as growth rate and orientation is affected significantly by the grid anisotropy in these methods and the simulation results need to be improved by reducing the grid dominance.…”