((廣西大學(xué) 物理科學(xué)與工程技術(shù)學(xué)院，南寧 530004))
摘 要: 應(yīng)用Monte Carlo(MC)法模擬在周期性邊界條件下的晶粒長(zhǎng)大行為。利用MC法模擬時(shí)，晶界處格點(diǎn)的遷移引起晶粒的長(zhǎng)大，根據(jù)這一主要特征提出一種精確快速的測(cè)定晶粒度的新方法—遞歸統(tǒng)計(jì)法，然后采用遞歸統(tǒng)計(jì)方法測(cè)量晶粒度。結(jié)果表明，遞歸統(tǒng)計(jì)法測(cè)得的晶粒度比截點(diǎn)法的更精確，而且測(cè)量精確度不受模型的格點(diǎn)類型以及晶粒的尺寸、形狀等的影響，測(cè)量速度比其他統(tǒng)計(jì)方法要快。
關(guān)鍵字: 遞歸統(tǒng)計(jì)；晶粒度； Monte Carlo方法；晶粒長(zhǎng)大
（(School of Physical Science and Engineering, Guangxi University, Nanning 530004, China)）
Abstract: Monte Carlo method was used to simulate grain growth process under periodic boundary condition. A new improved measurement method of grain size named recursive statistics method was introduced according to the fact that grain growth induced by displacement of single lattice around the grain boundary, and then the recursive statistics method was used to measure grain size. The results show that the grain size measured by the recursive statistics method is more accurate than the one measured by intercept method; the lattice types of method, sizes and shapes of grains cannot affect the measurement accuracy of the recursive statistics method; and the measuring speed of statistics method is faster than those of other statistics methods.
Key words: recursive statistics method; grain size; Monte Carlo method; grain growth
