晶粒析出长大的计算机模拟
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摘要
材料科学和计算机技术的进步,使得材料研究正从定性描述进入定量描述阶段。近年来,国内外研究者提出了许多基于蒙特卡洛方法(MC法)和元胞自动机方法(CA法)的晶粒长大的模型,为晶粒长大的研究开辟了一条新途径。为此,本论文应用改进蒙特卡洛方法,模拟了晶粒长大过程。
首先,应用Monte Carlo(MC)法模拟在周期性边界条件下的晶粒长大行为。利用MC法模拟时,晶界处格点的迁移引起晶粒的长大,根据这一主要特征提出一种精确快速的测定晶粒度的新方法—递归统计法,然后采用递归统计方法测量晶粒度,并与截点法比较。结果表明,递归统计法测得的晶粒度比截点法的更精确,而且测量精确度不受模型的格点类型以及晶粒的尺寸、形状等的影响,测量速度比其他统计方法要快。其次,运用Radhakrishnan等人改进的算法重现了正常晶粒长大的模拟过程,接着运用该算法首次研究了弥散相第二相粒子存在情况下的正常晶粒长大,结果表明改进算法一样适合于模拟这种情况下的晶粒生长,而且模拟效率比Srolovitz基本算法高,结果也和理论符合的很好。然后,运用改进的算法探索了异常晶粒长大的过程,经改进的算法运用在异常晶粒长大的模拟上仍然有比较高的模拟效率并且得到与理论符合得比较好的结果。
The advancement of material science and computer technique is changing the research manners of material science, so that more and more quantitative investigation manners will be adopted rather than qualitative investigation manners usually used today along with the developments of computer models and emulation techniques.
In recent years, the experimental literature clearly shows that MC simulation procedure and CA simulation procedure are employed to study grain growth. The researcher combines the manifestation technique of the calculator picture, reappearing material microstructures to turn into process vividly by picture, and develops a new path for the grain growth research.
First, Monte Carlo Method is used to simulate grain growth process under periodic boundary condition. A new improved measurement method of grain size named recursive statistics method is introduced according to the fact that grain growth induced by displacement of single lattice around the grain boundary, and then recursive statistics method is used to measure grain size. Compare it with intercept method, the results show that grain size measured by recursive statistics method is more accurate than the one measured by intercept method, and measuring speed of statistics method is faster than other statistics method's. Secondly, the calculate method which makes use of Radhakrishnan e.t. is used to simulate of normal grain growth, and then made use of this method to study grain growth with mobile particles first time. The research shows that the modify method is similar suitable for the simulation of grain growth with mobile particles, and imitate an efficiency more faster than the Srolovitz's method, results are a nice match for the theories. Then, the modify method is used to simulate abnormal grain growth, and still have a higher emulation efficiency and get to match with theories on the emulation of abnormal grain growth.
首先,应用Monte Carlo(MC)法模拟在周期性边界条件下的晶粒长大行为。利用MC法模拟时,晶界处格点的迁移引起晶粒的长大,根据这一主要特征提出一种精确快速的测定晶粒度的新方法—递归统计法,然后采用递归统计方法测量晶粒度,并与截点法比较。结果表明,递归统计法测得的晶粒度比截点法的更精确,而且测量精确度不受模型的格点类型以及晶粒的尺寸、形状等的影响,测量速度比其他统计方法要快。其次,运用Radhakrishnan等人改进的算法重现了正常晶粒长大的模拟过程,接着运用该算法首次研究了弥散相第二相粒子存在情况下的正常晶粒长大,结果表明改进算法一样适合于模拟这种情况下的晶粒生长,而且模拟效率比Srolovitz基本算法高,结果也和理论符合的很好。然后,运用改进的算法探索了异常晶粒长大的过程,经改进的算法运用在异常晶粒长大的模拟上仍然有比较高的模拟效率并且得到与理论符合得比较好的结果。
The advancement of material science and computer technique is changing the research manners of material science, so that more and more quantitative investigation manners will be adopted rather than qualitative investigation manners usually used today along with the developments of computer models and emulation techniques.
In recent years, the experimental literature clearly shows that MC simulation procedure and CA simulation procedure are employed to study grain growth. The researcher combines the manifestation technique of the calculator picture, reappearing material microstructures to turn into process vividly by picture, and develops a new path for the grain growth research.
First, Monte Carlo Method is used to simulate grain growth process under periodic boundary condition. A new improved measurement method of grain size named recursive statistics method is introduced according to the fact that grain growth induced by displacement of single lattice around the grain boundary, and then recursive statistics method is used to measure grain size. Compare it with intercept method, the results show that grain size measured by recursive statistics method is more accurate than the one measured by intercept method, and measuring speed of statistics method is faster than other statistics method's. Secondly, the calculate method which makes use of Radhakrishnan e.t. is used to simulate of normal grain growth, and then made use of this method to study grain growth with mobile particles first time. The research shows that the modify method is similar suitable for the simulation of grain growth with mobile particles, and imitate an efficiency more faster than the Srolovitz's method, results are a nice match for the theories. Then, the modify method is used to simulate abnormal grain growth, and still have a higher emulation efficiency and get to match with theories on the emulation of abnormal grain growth.
引文
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[1]钟晓征,陈伟元,王豪才,郑军.多晶材料晶粒生长的Monte Carlo计算机模拟方法—Ⅱ.模拟异常晶粒生长[J].功能材料.1999,30(3):236-238.
[2]A.D.ROLLETT,D.J.SROLOVITZZ and M.P.ANDERSON.Simulation and theory of abnormal grain growth—Anisotropic grain boundary energies and mobilites[J].Acta Metall.1989,37(4):1227-1240.
[3]G.S.Grest,M.P.Anderson,D.J.Srolovitz and A.D.Rollett.Abnormal grain growth in three dimensions[J].Scripta Metallurgica.1990,24:661-665.
[4]A.D.ROLLETT,D.J.SROLOVITZ,R.D.DOHERTY and M.P.ANDERSON.Computer simulation of recrystallization in non-uniformly deformed metals[J].Acta Metall.1989,37(2):627-639.
[5]A.D.ROLLETT,D.J.SROLOVITZ,M.P.ANDERSON and R.D.DOHERTY.Computer simulation of recrystallization—Ⅲ.Influence of a dispersion of fine particles[J].Acta metall.mater.1992,40(12):3475-3495.
[6]A.D.ROLLETT,M.J.LUTON and D.J.SROLOVITZ.Microstructural simulation of dynamic recrystallization[J].Acta metall.Mater.1992,40(1):43-55.
[2]高英俊,刘慧,钟夏平.计算机模拟技术在材料科学中的应用[J].广西大学学报(自然科学版),2001,26(4):291。
[3]D.罗伯[德].项金钟,吴兴惠译.计算材料学[M],北京:化学工业出版社,2002.3.
[4]M.P.Anderson,D.J.Srolovitz,G.S.Grest and P.S.Sahni.Computer simulation of grain growth—Ⅰ.Kinetics[J].Acta matall.1984,(32):783-791.
[5]D.J.Srolovitz,M.P.Anderson,P.S.Sahni and G.S.Grest.Computer simulation of grain growth—Ⅱ.Grain size distribution,topology,and local dynamics[J].Acta matall.1984,(32):793-802.
[6]D.J.Srolovitz a,M.P.Andersona,G.S.Gresta and P.S.Sahnib.Computer simulation of grain growth-Ⅲ.Influence of a particle dispersion[J].Acta matall.1984,(32):1429-1438.
[7]G.S.Grest,D.J.Srolovitz and M.P.Anderson.Computer simulation of grain growth—Ⅳ.Anisotropic grain boundary energies[J].Acta matall.1985,(33):509-520.
[8]Song.X.Y,Liu.G.Q.J Mater Sci Technol.1998,(14):506.
[9]Liu.G.Q,Song.X.Y,Yu.H.B,Gu.N.J.Acta Metall Sin.1999,(35):245.
[10]Radhakrishnan.B,Zacharia.T.Simulation ofcuration-driven grain growth by using a modified Monte Carlo algorithem[J].Metall Mater Trans.1995,(26A):167.
[11]Qiang.Yu,Sven.K.Esche.A Monte Carlo algorithm for single phase normal grain growth with improved accuracy and efficiency[J].Computational Material Science.2003,(27):259-270.
[12]Y Satio.The Monte Carlo simulation ofmicrostructural evolution in metals[J].Materials Science and Engineering.1997,(A223):115-124.
[13]C.Moron,M.Mora,A.Garcia.Computers imulation of grain growth kinetics[J].Journal of Magnetism and Magnetic Materials.2000,(215-216):153-155:
[14]H.Afer,N.Rouag,R.Penelle.Onset of abnormal growth related to the crystallographic neighborhood from the texture function.Application to Goss grain growth in magnetic sheets of Fe-3%Si[J].Journal of Crystal Growth.2004,(268):320-327.
[15]E.A.Holm,M.A.Miodownik,A.D.Rollet.On abnormal subgrain growth and the origin of recrystallization nuclei[J].Acta Material.2003,(51):2701-2716.
[16]钟晓征,陈伟元,王豪才,郑军.多晶材料晶粒生长的Monte Carlo计算机模拟方法模拟异常晶粒生长[J].功能材料.1999,30(3):236-238.
[17]D.J.Srolovitz,G.S.Grest and M.P.Anderson.Computer simulation of grain growth—Ⅴ.Abnormal grain growth[J].Acta matall.1985,(33):2233-2247.
[18]D.J.Srolovitz,G.S.Grest and M.P.Anderson.Computer simulation of recrystallization—Ⅰ.Homogeneous nucleation and growth[J].Acta matall.1986,(34):1833-1845..
[19]D.J.Srolovitz,G.S.Grest,M.P.Anderson and A.D.Rollett.Computer simulation of recrystallization—Ⅱ.Heterogeneous nucleation and growth[J].Acta matall.1988,(36):2115-2128.
[20]A.D.Rollett,D.J.Srolovitz,M.P.Anderson and R.D.Doherty.Computer Simulation of recrystallization—Ⅲ.Influence of a dispersion of fine particles[J].Acta mater.1992,(40):3475-3495.
[21]Y.Saito.Monte Carlo simulation of grain boundary precipitation[J].Materials Science and Engineering.1997,(A223):125-133.
[22]E.A.Holm,G.N.Hassold and M.A.Miodownik.On misorientation distribution evolution during anisotropic grain growth[J].Acta material.2001,(49):2981-2991.
[23]K.Mehnert,P.Klimanerk.Monte Carlo simulation of grain growth in textured metals using anisotropic grain boundary[J].Computational Materials Science.1996,(7):103-108.
[24]T.A.Abinandanna,F.Haider and G.Martin.Computer Simulations of Difusional Phase Transformations:Monter Carlo Algorithm and Application to Precipitation of Ordered Phase[J].Acta mater.1998,46(12):4243-4355.
[25]M.I.MENDELEV and D.J.SROLOVITZ.A regular solution model for impurity drag on a migrating grain boundary[J].Acta mater,2001,49:589-597.
[26] H. Zhang, M.I. Mendelev, D.J. Srolovitz. Computer simulation of the elastically driven migration of a flat grain boundary[J]. Acta Materialia, 2004,52:2569-2576.
[27] K. Barmak, J. Kim, C.-S. Kim et al. Grain boundary energy and grain growth in Al films: Comparison of experiments and simulations [J]. Scripta Materialia, 2006,54:1059-1063.
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