A cellular automaton model for simulating grain structure formation during solidification processes of Ti-45%Al(mole fraction) alloy ingot was developed, based on finite differential method for macroscopic modeling of...A cellular automaton model for simulating grain structure formation during solidification processes of Ti-45%Al(mole fraction) alloy ingot was developed, based on finite differential method for macroscopic modeling of heat transfer and a cellular automaton technique for microscopic modeling of nucleation, growth, solute redistribution and solute diffusion. The relation between the growth velocity of a dendrite tip and the local undercooling, which consists of constitutional, thermal, curvature and attachment kinetics undercooling is calculated according to the Kurz-Giovanola-Trivedi model. The effect of solidification contraction is taken into consideration. The influence of process variables upon the resultant grain structures was investigated. Special moving allocation technique was designed to minimize the computation time and memory size associated with a large number of cells. The predicted grain structures are in good agreement with the experimental results.展开更多
基金Project(50395102) supported by the National Natural Science Foundation of China Project (JC 02 10) supported by theDistinguished Young Fund of Heilongjiang Province of China
文摘A cellular automaton model for simulating grain structure formation during solidification processes of Ti-45%Al(mole fraction) alloy ingot was developed, based on finite differential method for macroscopic modeling of heat transfer and a cellular automaton technique for microscopic modeling of nucleation, growth, solute redistribution and solute diffusion. The relation between the growth velocity of a dendrite tip and the local undercooling, which consists of constitutional, thermal, curvature and attachment kinetics undercooling is calculated according to the Kurz-Giovanola-Trivedi model. The effect of solidification contraction is taken into consideration. The influence of process variables upon the resultant grain structures was investigated. Special moving allocation technique was designed to minimize the computation time and memory size associated with a large number of cells. The predicted grain structures are in good agreement with the experimental results.
