基于Monte Carlo Potts方法的三维大尺度晶粒组织仿真模型及定量表征

Large-Scale 3D Model and Quantitative Characterization of Grain Microstrcture Based on Monte Carlo Potts Simulation

  • 摘要: 为改善三维晶粒组织可视化模型的统计性,采用Monte Carlo Potts方法建立了材料多晶体组织的一种大尺度三维数字化模型,并实现了其定量表征和三维可视化.逾万晶粒的统计结果表明,该模型的平均晶粒面数为13.8±0.1,晶粒尺寸分布和晶粒面数分布均可用Log-normal函数近似拟合,与实际材料晶粒组织情况相近.

     

    Abstract: In order to improve the statistics of 3D grain microstructure models, a large-scale 3D digital model of microstructures of polycrystalline materials was implemented using Monte Carlo Potts simulation. The quantitative characterization and 3D visualizing of the model were carried out. The results show that the grain size distribution and the grain face number distribution in this model can be fitted approximately by the lognormal function, with an average grain face number of 13.8±0.1, very similar to the polycrystalline microstructure in real material.

     

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