Large-Scale 3D Model and Quantitative Characterization of Grain Microstrcture Based on Monte Carlo Potts Simulation
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摘要: 為改善三維晶粒組織可視化模型的統計性,采用Monte Carlo Potts方法建立了材料多晶體組織的一種大尺度三維數字化模型,并實現了其定量表征和三維可視化.逾萬晶粒的統計結果表明,該模型的平均晶粒面數為13.8±0.1,晶粒尺寸分布和晶粒面數分布均可用Log-normal函數近似擬合,與實際材料晶粒組織情況相近.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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