简介概要

ON THE MONTE CARLO SIMULATION OF NORMAL GRAIN GROWTH

来源期刊:Acta Metallurgica Sinica2008年第4期

论文作者:L.J.Wang X.F.Ma Y.T.Liu X.M.Shen X.J.Guan

Key words:Grain growth; Microstructure; Monte Carlo method; Computer simulation; Grain growth kinetics; Nonlinear regression;

Abstract: The microstructures and their kinetics of normal grain growth are simulated using different Monte Carlo (MC) algorithms.Compared with the relative figures and the theoretical normal grain growth exponents of n=0.5,the effects of some factors of MC algorithm,i.e.the lattice types,the methods of selecting lattice sites,and the neighbors selection for energy calculations,on the simulation results of grain growth are studied. Two methods of regression were compared,and the three-parameter nonlinear regres-sion is much more suitable for fitting the grain growth kinetics.A better model with appropriate factors included triangular lattice,the attempted site randomly selected, and the first and second nearest neighbors for energy calculations is obtained.

详情信息展示

ON THE MONTE CARLO SIMULATION OF NORMAL GRAIN GROWTH

L.J.Wang1,X.F.Ma1,Y.T.Liu1,X.M.Shen1,X.J.Guan1

(1.School of Materials Science and Engineering,Shandong University,Jinan 250061,China)

Abstract:The microstructures and their kinetics of normal grain growth are simulated using different Monte Carlo (MC) algorithms.Compared with the relative figures and the theoretical normal grain growth exponents of n=0.5,the effects of some factors of MC algorithm,i.e.the lattice types,the methods of selecting lattice sites,and the neighbors selection for energy calculations,on the simulation results of grain growth are studied. Two methods of regression were compared,and the three-parameter nonlinear regres-sion is much more suitable for fitting the grain growth kinetics.A better model with appropriate factors included triangular lattice,the attempted site randomly selected, and the first and second nearest neighbors for energy calculations is obtained.

Key words:Grain growth; Microstructure; Monte Carlo method; Computer simulation; Grain growth kinetics; Nonlinear regression;

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