基于人工神经网络的磷酸三丁酯络合萃取Np(Ⅳ、Ⅵ)的模拟

Simulation of Complex Extraction of Neptunium(Ⅳ,Ⅵ)With Tributyl Phosphate Based on Artificial Neural Networks

近年来，核燃料后处理的计算机模拟研究成为世界各国研究核燃料后处理工艺过程的重要手段。本工作以磷酸三丁酯为萃取剂、煤油为稀释剂的混合有机萃取剂，在 HNO3介质中络合萃取 Np（Ⅳ、Ⅵ）的体系中，利用BP人工神经网络将萃取平衡分配比和萃取操作条件如初始硝酸浓度、初始 Np（Ⅳ、Ⅵ）浓度、初始U（Ⅵ）浓度及温度进行了关联。建立了该体系下磷酸三丁酯络合萃取 Np（Ⅳ、Ⅵ）的人工神经网络模型，并用该模型计算且检验了不同萃取条件对平衡分配比的影响。结果表明：在25-60℃、水相c0（HNO3）为0.1-11 mol/L、水相初始铀质量浓度为0-210 g/L时，该人工神经网络模型可以对Np（Ⅳ、Ⅵ）萃取分配比进行预测，具有较高的计算精度。经过文献Np（Ⅳ、Ⅵ）萃取平衡分配比实验值检验，其检验平均相对误差在2%以内。

Computer simulation of nuclear fuel reprocessing in recent years becomes an important means of study the nuclear fuel reprocessing process in the world.Tributyl phosphate as the extractant and kerosene as the diluent were selected for the complex extraction of neptunium （Ⅳ,Ⅵ）.By using BP artificial neural networks （ANN ）,the equilibrium distribution ratio was correlated with the extraction operational conditions in the extraction system,such as initial concentration of nitric acid,neptunium （Ⅳ,Ⅵ）and uranium （Ⅵ）,as well as temperature.The ANN model of extraction equilibrium ratio was established.Moreover, the effects of different extraction condition on the equilibrium 〈br〉 distribution ratio were predicted by using the model.The results show that the proposed model can simulate the experimental data and predict the process of extraction well,in the range of experiment conditions,such as 25-60 ℃,0.1-11 mol/L HNO3 and 0-210 g/L U（Ⅵ）.After testing by the Np （Ⅳ,Ⅵ） extraction distribution ratio values from the literature,the mean relative error is less than 2%.