Modeling of Abnormal Grain Growth That Considers Anisotropic Grain Boundary Energies by Cellular Automaton Model

被引:4
|
作者
Ye, Liyan [1 ,2 ,3 ]
Mei, Bizhou [2 ]
Yu, Liming [3 ]
机构
[1] Nanchang Univ, Sch Phys & Mat Sci, Nanchang 330031, Jiangxi, Peoples R China
[2] Zhejiang Yiduan Precis Machinery Co Ltd, Adv Equipment & Technol R&D Ctr, Ningbo 315702, Zhejiang, Peoples R China
[3] Tianjin Univ, Sch Mat Sci & Engn, Tianjin 300350, Peoples R China
关键词
anisotropic grain boundary energies; abnormal grain growth; cellular automaton; morphology; growth kinetics; COMPUTER-SIMULATION; KINETICS; RECRYSTALLIZATION;
D O I
10.3390/met12101717
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
A new cellular automaton (CA) model of abnormal grain growth (AGG) that considers anisotropic grain boundary energies was developed in this paper. The anisotropic grain boundary energy was expressed based on two types of grains, which correspond to two components of different crystallographic orientation in textured materials. The CA model was established by assigning different grain boundary energies and grain-growth-driven mechanisms to four types of grain boundaries formed by two types of grains. The grain boundaries formed by different kinds of grains adopted the lowest energy principle, while the grain boundaries formed by the same kind of grains adopted the curvature-driven mechanism. The morphology calculated by the CA model shows the characteristics of AGG. Then, the Johnson-Mehl-Avrami (JMA) model was fitted to predict the growth kinetics. By analyzing the fitting results, the JMA model is capable of predicting the growth kinetics of AGG. The Avrami exponent p decreases from about 1.5 to 1 with the initial number of Type II grains increasing. The investigation of the Hillert model and grain size distribution further indicates that the microstructure evolution is consistent with AGG. Therefore, the analysis of morphology and kinetics indicates that AGG can be fairly well-simulated by the present CA model.
引用
收藏
页数:12
相关论文
共 50 条
  • [1] Modeling the grain growth kinetics by cellular automaton
    Raghavan, S.
    Sahay, Satyam S.
    MATERIALS SCIENCE AND ENGINEERING A-STRUCTURAL MATERIALS PROPERTIES MICROSTRUCTURE AND PROCESSING, 2007, 445 : 203 - 209
  • [2] Simulation of Abnormal Grain Growth Using the Cellular Automaton Method
    Murata, Kenji
    Fukui, Chihiro
    Sun, Fei
    Chen, Ta-Te
    Adachi, Yoshitaka
    MATERIALS, 2024, 17 (01)
  • [3] Persistence of abnormal grain growth in the presence of grain boundary complexion transitions: Thermodynamic analysis and phase field modeling
    De, Partha Sarathi
    Vadlamani, Subramanya Sarma
    Vedantam, Srikanth
    COMPUTATIONAL MATERIALS SCIENCE, 2023, 230
  • [4] Modeling of grain growth under fully anisotropic grain boundary energy
    Hallberg, Hakan
    Bulatov, Vasily V.
    MODELLING AND SIMULATION IN MATERIALS SCIENCE AND ENGINEERING, 2019, 27 (04)
  • [5] Modeling the topological features during grain growth by cellular automaton
    Raghavan, S.
    Sahay, Satyam S.
    COMPUTATIONAL MATERIALS SCIENCE, 2009, 46 (01) : 92 - 99
  • [6] Abnormal grain growth in the Potts model incorporating grain boundary complexion transitions that increase the mobility of individual boundaries
    Frazier, William E.
    Rohrer, Gregory S.
    Rollett, Anthony D.
    ACTA MATERIALIA, 2015, 96 : 390 - 398
  • [7] Phenomenology of Abnormal Grain Growth in Systems with Nonuniform Grain Boundary Mobility
    DeCost, Brian L.
    Holm, Elizabeth A.
    METALLURGICAL AND MATERIALS TRANSACTIONS A-PHYSICAL METALLURGY AND MATERIALS SCIENCE, 2017, 48A (06): : 2771 - 2780
  • [8] A mesoscale cellular automaton model for curvature-driven grain growth
    Y. J. Lan
    D. Z. Li
    Y. Y. Li
    Metallurgical and Materials Transactions B, 2006, 37 : 119 - 129
  • [9] Analysis of grain growth kinetics using the Cellular Automaton method
    Yu, W
    Banks, SP
    Palmiere, EJ
    RECRYSTALLIZATION AND GRAIN GROWTH, VOLS 1 AND 2, 2001, : 333 - 338
  • [10] Study of Grain Growth in a Ni-Based Superalloy by Experiments and Cellular Automaton Model
    Liu, Yan-Xing
    Ke, Zhi-Jiang
    Li, Run-Hua
    Song, Ju-Qing
    Ruan, Jing-Jing
    MATERIALS, 2021, 14 (22)