Applications of Diglycolamide Based Solvent Extraction Processes in Spent Nuclear Fuel Reprocessing,Part 1: TODGA

Over the last decade there has been much interest in the applications of diglycolamide (DGA) ligands for the extraction of the trivalent lanthanide and actinide ions from PUREX high active raffinates or dissolved spent nuclear fuel. Of the DGAs, the N,N,N’,N’-tetraoctyldiglycolamide (TODGA) is the best known and most widely studied. A number of new actinide separation processes have been proposed based on extraction with TODGA. This review covers TODGA-based processes and extraction data, specifically focusing on how phase modifiers have been used to increase metal loading and thus enhance the operating process envelopes. Effects of third phase formation and the organic phase speciation are reviewed in this context. Relevant aspects of the extraction chemistry of important solvents (TODGA-modifier-diluent combinations) are described and their performances demonstrated by a consideration of the published flowsheet tests. It is seen that modifiers are successfully enabling the use of TODGA in actinide separation processes but to date the identification and testing of suitable modifiers has been rather empirical. There is a growing understanding of the fundamental chemistry occurring in the organic phase and how that affects extractant speciation and metal loading capacity but studies are still needed if TODGA-based flowsheets are to become an industrially deployable option for minor actinide (MA) recovery processes.     

基于MCD稳健统计分析的变压器油色谱异常值检测及分布特性

由于人为因素以及现场干扰的影响,变压器油色谱在线监测数据在测量和传输中会不可避免地出现偏误,导致异常数据值,使得经典统计方法的结果出现偏差甚至错误。为了解决上述问题,基于稳健统计理论,根据油色谱监测数据异常值的特点,提出了油色谱H2、CO和总烃3类特征气体异常值的最小协方差行列式MCD稳健多元检测方法。利用迭代和Mahalanobis距离的思想构造一个稳健的协方差估计量,并进行异常值检测,然后再将异常数据和正常数据分类处理。针对H2、CO和总烃这3类特征气体的实例统计分析表明,异常值剔除后可有效减少这3种气体的测量值对经典统计方法的干扰,使得油色谱数据的统计规律更加明显。通过对异常值区间的跟踪评估,还可更加明显地反映变压器运行状态的变化。     

变压器油中溶解气体的多智能体故障诊断方法

为解决目前基于油中溶解气体分析(DGA)方法的变压器故障诊断系统中存在的模型单一化、自适应能力差及容易出现误诊和漏诊的问题,在对现有智能故障诊断系统和变压器DGA方法的研究基础上,提出了基于多智能体(Agent)系统的变压DGA智能故障诊断系统协作模型,给出了模型内的主要Agent、黑板、JavaAgent开发环境(JADE)总线的功能,并详细论述了基于多Agent系统的变压器DGA智能故障诊断协作过程,设计了多专家Agent投票诊断算法及基于黑板的资源竞争算法。最后通过应用实例,表明了基于多Agent系统的变压器油中溶解气体智能故障诊断方法的可行性和有效性。     

一种仅由绝缘油气相色谱分析发现的电流互感器缺陷

对一起仅由油中气相色谱分析发现的互感器低能放电故障进行了研究和分析.该设备在绝缘油例行周期检查中发现色谱试验数据异常,将其返厂.在制造厂对故障设备进行了相关常规和诊断性试验,试验数据均在国家规定标准之内,未发现异常;仅有油色谱试验数据依然不合格.后经整体解剖发现,此故障是由互感器一次绕组地屏铜带蹭伤产生的毛刺尖端,在高...     

模糊数学结合BP网络的变压器故障诊断研究

针对油中溶解气体分析(DGA)方法在诊断电力变压器潜伏性故障的研究中存在的不足,采用TOPSIS方法对原始样本集进行优劣排序和聚类,实现了对样本数据的优化,同时极大地缩减了样本集的容量.在此基础上,构建BP网络故障诊断模型.分析证明,此方法与传统的变压器故障诊断的方法相比具有明显的优越性.     

Comparison of MEA and DGA performance for CO2 capture under different operational conditions

Carbon capture and storage from flue gases is the most common method to reduce greenhouse gas emissions. Using a primary amine as the solvent of CO₂ capture unit is popular because of its high activity and ability to be used for streams with low concentration and low partial pressure of CO₂. Monoethanolamine(MEA) and Diglycolamine(DGA) are the most common kinds of primary amines which have been traditionally used in many natural gas sweetening plants. In this research, the capture plant has been designed for these two solvents at various CO₂ concentrations in the feed flue gas. This paper proposes different possible alters to overcome the high energy requirements of capture plant. It also presents the results of technical evaluation of different parameters, in order to design an actual plant with minimum energy requirement. The results of different parameters show that for DGA solvent, there will be an improvement in overall energy usage in the capture plant rather than MEA for some special cases. To gain the practical results, actual stages have been used for absorber and stripper instead of equilibrium stages. Copyright © 2011 John Wiley & Sons, Ltd.     

Complementary geometric formulations for electrostatics

The simultaneous use of a pair of complementary discrete formulations for electrostatic boundary value problems (BVPs) allows to accurately compute electromagnetic quantities, such as capacitance or electrostatic force with a minimum computational effort. In fact, the two formulations provide the upper and lower bounds for these quantities and their averages result quite close to the exact solution even for extremely coarse meshes. Despite the potential benefit to the many three‐dimensional large‐scale applications, taking advantage of this feature is not exploited in practice due to theoretical difficulties in the potential design. The aim of this paper is to fill this gap by rigorously introducing a pair of three‐dimensional complementary geometric formulations to solve electrostatic BVPs on domains covered by conformal polyhedral meshes. In particular, an original formulation based on a vector potential is introduced by using cohomology theory with integer coefficients. It is shown how the so‐called thick links are needed, which are representatives of the second cohomology group generators of the dielectric region. Two easy‐to‐implement graph‐theoretic algorithms to automatically find such a basis with optimal computational complexity are described. Some benchmark problems are presented to show how the simultaneous use of both formulations yields to a sensible computational advantage. Therefore, solvers based on complementary formulations should be embedded in the next‐generation of electromagnetic Computer‐Aided Engineering (CAE) softwares. Copyright © 2010 John Wiley & Sons, Ltd.     

神经网络结构与算法对变压器故障诊断的影响

BP神经网络算法本质上是基于梯度下降的一种迭代学习算法,存在学习收敛速度慢、收敛精度低、易陷入局部极小、学习率难以选取、隐层数及隐层神经元个数难以确定等缺陷。为了选择出更适宜变压器DGA故障诊断的神经网络结构及算法。本文采用了常用的几种智能算法对变压器故障样本进行了诊断性能对比实验。结果得出Levenberg-Marquardt神经网络算法是收敛速度较快的算法,有动量和自适应的梯度下降法是收敛稳定性较佳的算法;网络最优结构设计过程。为用于变压器DGA故障诊断的神经网络的结构和算法提供了系统化的试验方法。     

变压器油中溶解气体分析法应用中存在的问题及产气识别（二）

4变压器各类产气的识别 4．1自然老化产气的识别 自然老化产气与变压器内的水分和氧气含量有关，而他们与制造和维护水平有关，所以每一台变压器运行后所含特征气体的浓度是不同的。根据统计，如果油中乙炔保持为0值，总烃缓慢地上升，平均产气率〈0．1μL／（L·d），则可认为是自然老化。自然老化是可以控制的，控制水平不同，老化程度就不同。     

DGA树脂辅助的循环淋洗技术制备无载体镥［177Lu］

为实现核医学广泛关注的新型医用放射性同位素¹⁷⁷Lu的国产规模化,利用中国绵阳反应堆（CMRR）进行无载体（n.c.a.）¹⁷⁷Lu的制备工艺研究。在常规的镧系树脂分离纯化¹⁷⁷Lu的流程中加入可以吸附洗脱液中金属离子的DGA树脂柱,并通过特殊的流路连接方式,实现淋洗镧系树脂柱洗脱液的“在线”循环。示踪实验和三次生产流程验证表明,第一级分离的废液量降低>86%。质检分析表明,循环淋洗技术制备的无载体¹⁷⁷Lu产品符合质量要求。研究表明,该技术显著降低了镧系树脂分离无载体¹⁷⁷Lu中的放射性酸废液总量,可用于规模化生产工艺。