梯级水电厂集中控制运行模式探索

介绍了清江梯级电厂从单一电厂管理向多电厂集控管理转变的情况及存在的问题,并探讨了改进办法.     

喷射导管技术在深水钻井作业中的应用

深水油气日益成为海洋石油勘探开发的热点，但深水钻井作业面临着许多难题和挑战，喷射导管技术是解决深水浅层钻井难题的技术之一。该技术采用在喷射管柱内下动力钻具的方式，用钻入泥线以下的管串自身重力钻进，喷射到位后利用地层的粘附力和摩擦力稳固住导管，起出送入工具和管内钻具，完成导管的安装。喷射导管技术可避免因水泥浆密度过大而压破地层，也可避免深水由于低温等因素影响固井质量。我国第一口水深超千米的深水井——荔湾3-1-1井利用该技术成功完成了导管的安装，井口装置没有出现井口失稳的问题。随着我国深水勘探步伐的加快，越来越多的深水区块将投入勘探开发，喷射导管技术具有良好的应用前景。     

铝电解槽磁流体稳定性有限元分析

本文采用有限元法求解分层磁流体小扰动方程系统特征值，研究铝电解槽稳定性。研究结果表明，在没有电磁力时，铝液表面波动（内波）是稳定的。存在电磁力时，它会激发铝液表面波动的某些低频长波分量不稳定性，高频短波不受影响。被激发的不稳定波动频率和扰动增长率与电流密度，磁感应强度垂直分量，铝电解槽长宽比，电解质和铝液的密度差，厚度等因素密切相关。减少电流密度，磁感应强度，增加电极距离和铝液厚度可以提高铝电解槽的稳定性。这对铝电解槽优化设计和在线控制有重要意义。     

MPLS交换路由器的设计与实现

MPLS是目前Internet核心网上最看好的技术，基于Crossbar的高速交换技术的发展也很快，但是如何实现2种技术的有机结合以到达最优的性能却有一系列问题需要考虑。本文结合某MPLS路由器的设计项目，综合考虑了当前MPLS的标准以及有关交换结构的最新技术，对实现MPLS交换路由器进行了深入研究，并详细探讨了高速接口、排除和调度以及Crossbar等关键模块的设计和实现方案。     

Lattice Effects and Irreversible Magnetoresistance in Gd Doped La—Ca—Mn—O

The Gd substituting effects for La in La0.67Ca0.33MnO3 has been studied .With increasing the substituting amount of Gd,the phase transition temperature of metal-isolator for the samples decreases,the corresponding peak resistivity increases,the Curie temperature decreases monotonically.The substitution of La-Ca-Mn-O with 11% Gd for La improved the magnetoresistance ratio by an order of magnitude.The effects of substituting Gd can be explained in terms of the lattice effects.An irreversible MR behaviour was observed in Gd-substituting compounds.This effect became marked when the substituting amount of Gd was greater than 7%.A maximum irreversible increment of MR ratio as large as 91% was obtained when Gd substituting amount was 11%.     

HTR-10燃料元件装卸系统冷态调试

10MW高温气冷实验堆（HTR－10）是一座球床堆，由燃料元件装卸系统实现燃料元件的装卸和循环，且不需要停堆，为保证HTR－10的正常运行，燃料元件装卸系统必须安全，可靠，为此，必须对燃料元件装卸系统进行周密，细致的调试试验和验证，本文介绍了燃料元件装卸系统冷调试的主要调试项目，调试方法和调试结果。     

蒙古泰西尔坝碾压混凝土的斜层铺筑法

蒙古泰西尔水电站大坝为碾压混凝土重力坝,文中主要介绍了碾压混凝土斜层浇筑法的基本原理,施工工艺和施工中存在的问题及对策.     

Ta-2．5W焊接工艺试验研究

通过对Ta-2.5W难熔重金属换热管的一系列焊接工艺试验研究,掌握了钽材的特殊焊接技术工艺和要求,满足了今后制造和修复苯胺装置中硫酸蒸发器管束的需要。     

A hierarchical model for structure learning based on the physiological characteristics of neurons

Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability. The characteristics of typical ANN models are fixed connections, with evolved weights, globalized representations, and globalized optimizations, all based on a mathematical approach. This makes those models to be deficient in robustness, efficiency of learning, capacity, anti-jamming between training sets, and correlativity of samples, etc. In this paper, we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing. A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures. The basic characteristics of this model are localized and random connections, field limitations of neuron fan-in and fan-out, dynamic behavior of neurons, and samples represented through different sub-circuits of neurons specialized into different response patterns. At the end of this paper, some important aspects of error correction, capacity, learning efficiency, and soundness of structural representation are analyzed theoretically. This paper has demonstrated the feasibility and advantages of structure learning and representation. This model can serve as a fundamental element of cognitive systems such as perception and associative memory.     

火焰原子吸收法测定高铋物料中的铅

本文介绍了在以高铋物料为基体 ,5 %的HNO3 介质中 ,波长 2 17nm处进行火焰原子吸收法测定铅的试验 ,采用标准加入法进行回收率的试验 ,回收率大于 98% ,特征浓度为 0 .0 7μg/ml,结果令人满意 ,能满足炉前样分析的要求