Abstract
The phase-field methods were developed mainly for studying solidification of pure materials, being then extended to the solidification of alloys. In spite of phase-field models being suitable for simulating solidification processes, they suffer from low computational efficiency. In this study, we present a numerical technique for the improvement of computational efficiency for computation of microstructural evolution for both pure metal and binary alloy during solidification process. The goal of this technique is for the computational domain to grow around the microstructure and fixed the grid spacing, while solidification advances into the liquid region. In the numerical simulations of pure metal, the phase-field model is based on the energy and phase equations, while, for binary alloy, the said model is based on the concentration and phase equations. Since the thermal diffusivity in the energy equation is much larger than the diffusivity term in phase equation in pure metal system, about twenty eight times the difference between them. The computational domain growth around the microstructure is controlled according with the thermal diffusivity for pure material in the liquid region. In the numerical simulation of dendritic evolution of Fe-C alloy, the idea is similar, i.e., the solute diffusivity in concentration equation is larger than the diffusivity term in phase equation in the liquid region, in this case eleven times the difference in Fe-C alloy system. The computational domain growth is controlled via solute diffusivity in the liquid region. Hence, phase-field model is proposed with an adaptive computational domain for efficient computational simulation of the dendritic growth in a system for both pure metal and binary alloy. The technique enables us to reduce by about an order of magnitude the run time for simulation of the solidification process. The results showed that the microstructure with well-developed secondary arms can be obtained with low computation time.
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