遗传算法优化区熔铈的再分配过程  

Application of a Genetic Algorithm to Optimize Redistribution Process in Zone Refining of Cerium

作　　者：黄俊[1,2] 任清波[1] 胡祖麒[1] 刘勋 蒙大桥[3] 

机构地区：[1]中国工程物理研究院,四川江油621908 [2]清华大学,北京100048 [3]表面物理与化学重点实验室,四川江油621908

出　　处：《稀有金属材料与工程》2017年第12期3633-3638,共6页Rare Metal Materials and Engineering

摘　　要：通过冷坩埚感应区熔提纯铈以避免坩埚材料的污染。溶质再分配数值模型结合遗传算法(GA)搜寻优化区熔参数以提高溶质的再分配效率,并考虑变溶质分配系数对计算结果的影响。15次区熔后的化学结果分析显示,具有相近分配系数的Fe和Ni在试棒中部分别降低50%和90%,主要差别为初始含量不同。实验结果和计算结果的主要差别源于后续区熔实验过程中较窄熔区的不稳定。研究结果表明,GA是一种获得最优熔区长度的有力工具,但是需要采取有效办法获得稳定的熔区以促使杂质顺利迁移,另外杂质的初始含量应尽可能降低以获得好的提纯效果。Commercial cerium has been zone refined by induction heating in a cold crucible against the pollution from the crucible materials.A numerical model of solute redistribution during zone refining was integrated into the genetic algorithm（GA） to search after the optimum zone length in different zone passes for increasing the redistribution efficiency of solutes,and the effect of variable distribution coefficient on purification efficiency was also considered in model.The chemical analysis results after 15 zone passes show that the content of Fe and Ni at the center of the sample bar are reduced by 50% and 90%,respectively,and the major difference of these two solutes with close effective distribution coefficient is their initial content.The main difference of experimental results and calculation results is from the instability of shorter zone during later zone passes.Experimental and calculation results show that GA is a powerful tool for looking for optimum of zone lengths in zone passes,but the stability should be maintained in the experiment by an effective method to promote smoothly mobility of solutes in molten zone;the initial content of solutes should be kept as low as possible for getting better purification effect.

关 键 词：铈 冷坩埚 区熔 遗传算法 变分配系数 

分 类 号：TF845[冶金工程—有色金属冶金]