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GUO Zhao, ZHOU Jianxin, SHEN Xu, YIN Yajun, JI Xiaoyuan, WANG Sheng. Numerical Simulation of Dendritic Growth Behavior in Solidification of Superalloy by an Improved Cellular Automaton Method[J]. Materials and Mechanical Engineering, 2020, 44(2): 65-72. DOI: 10.11973/jxgccl202002013
Citation: GUO Zhao, ZHOU Jianxin, SHEN Xu, YIN Yajun, JI Xiaoyuan, WANG Sheng. Numerical Simulation of Dendritic Growth Behavior in Solidification of Superalloy by an Improved Cellular Automaton Method[J]. Materials and Mechanical Engineering, 2020, 44(2): 65-72. DOI: 10.11973/jxgccl202002013
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Numerical Simulation of Dendritic Growth Behavior in Solidification of Superalloy by an Improved Cellular Automaton Method

  • State Key Laboratory of Material Processing and Die&Mould Technology, Huazhong University of Science and Technology, Wuhan 430074, China

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  • Received Date: February 25, 2019
  • Revised Date: January 06, 2020
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    • Abstract
  • An improved cellular automata method, fully considering the combined effect of solute field and thermal diffusion on dendrite growth, was proposed. Based on the 27-point discrete scheme of solute field equation, the numerical simulation of the dendritic growth behavior in multi-element superalloy solidification was carried out and compared with the experimental results. The dendritic growth morphology evolution and the stray grain formation in single crystal blade casting were studied. The results show that increasing the undercooling degree could promote the dendritic growth, but the growth rate of the single crystal dendrite tip gradually decreased with time due to solute enrichment. At low cooling rates, dendrites deviating from the heat flow direction eliminated dendrites with the same orientation as the heat flow. In the process of directional solidification dendritic growth, the stray grains were easy to form in the variable cross-section region with the concave isotherm. The simulation results are consistent with the experimental results and the research results of related literatures, indicating that the improved cellular automaton method is effective and practical.
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    • References (19)
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