摘要
用Ｎａ３ＡｌＦ６－ＡｌＦ３－ＣａＦ２－ＭｇＦ２－ＬｉＦ－Ａｌ２Ｏ３体系中的低摩尔比（ｎ（ＮａＦ）／ｎ（ＡｌＦ３））电解质进行低温电解实验，以大量的实验数据为学习样本，让网络学习以建立各种电解条件与对应电流效率间的非线性映射，用来预报不同电解条件下的电流效率，研究了各种电解工艺参数对电流效率的影响规律。
This paper presents a new approach to predict current efficiency (CE) of low temperature aluminium electrolysis (LTAE) with the low molar ratio electrolyte of Na 3AlF 6-AlF 3-CaF 2-MgF 2-LiF-Al 2O 3 system. The nonlinear mapping between CE of LTAE and various electrolytic conditions is established according to a number of experimental data to predict CE of LTAE. The effect laws of various electrolytic parameters on CE are also given in the paper.
出处
《矿冶工程》
CAS
CSCD
北大核心
1998年第4期36-39,共4页
Mining and Metallurgical Engineering
基金
国家自然科学基金
关键词
低温铝电解
电流效率
神经网络
炼铝
Low temperature aluminium electrolysis, Neural network, Current efficiency
