RC框架外包钢节点角钢延伸的研究

本文根据对角钢在节点核心区边缘处截断的对比试件的试验，分析了不同类型节点的破坏特点、抗剪机理以及抗剪强度；证明角钢在核心区外的延伸是保证角钢销栓力的必要条件。     

脉冲多弧离子源引弧效率的定量检测与过程控制

介绍了一种应用于脉冲多弧离子源镀膜过程控制的电子监控装置．用该装置定量检测脉冲多弧离子源的引弧效率，克服了因停弧带来的膜厚误差的缺点．本文主要叙述了该装置的工作原理及有关电路．     

连续开采下上覆岩层移动的离散元模拟

采用离散元法对走向长壁工作面上覆岩层移动和地表沉陷进行了动态分析和模拟，探讨了离散单元法参数选择问题。通过实例分析，计算结果与实测结果基本一致，并探讨了下沉系数与回采区段尺寸的关系     

优质镁橄榄石砖的研制

以国产天然镁橄榄石为主要原料，研制的镁橄榄石压，具有优良的高温性能和抗芒硝，碱侵蚀性能。已用大量用于大型平板及浮法玻璃熔窑蓄热室中部和冶金工业窑炉。因其价廉，无铬，是中部格子体的优良选材，具有良好的开发应用前景。     

三角网格等值线自动生成方法及程序实现

总结各种等值线生成的方法及特点，详细阐述直接利用三角形网格生成等值线的原理、实现方法，独立开发出基于Windows的功能齐全的Contour绘图包，并嵌入地下水有限元模拟软件，为地下水模拟成果的表示提供了便利.     

Deadbeat control with disturbance rejection

A deadbeat control problem with disturbance rejection is considered for a SISO discrete time plant. Disturbances are supposed to enter into the input to the plant and the output from the plant. The two-degree-of-freedom controllers are employed to internally stabilize the feedback control system, to make the output of the plant track a reference signal and to reject the disturbances in the sense of the deadbeat response. Necessary and sufficient conditions for the problem to have a solution are shown. And the set of all controllers meeting the design requirements are represented using two free polynomials.     

基于SAN系统数据密集型程序的性能分析

数据密集型应用如多媒体、数据库等等的大规模发展对存储系统提出更高的要求．与之相适应的是以SAN为代表的存储网络改变了存储系统完全依赖于主机的模式，整体上提高了存储系统性能、可用性、可扩展性．本文在研究整个SAN存储系统结构的基础上，通过分析和估计SAN系统的各个部分性能，结合数据密集型程序的I／O统计特性，估计各种I／O请求的平均响应时间，说明在SAN系统平台上I／O密集型程序的设计要求，为进一步开发大规模存储网络管理和应用软件打下基础．     

实模式下获取磁盘文件存储地址的一种捷径

简要分析了实模式下磁盘文件访问与BIOS INT13H直接读写扇区的内在联系，给出了在该模式下获取磁盘文件存储地址的一种捷径和实现方法，最后给出了实例和源代码．     

离子注入聚碳酸酯表面力学性能改变研究

将B^ 和O^ 离子分别注人到高分子化合物聚碳酸酯(PC)中，PC的表面显微硬度和耐磨性能均得到了较大提高。用纳米硬度计测量注人前后PC的显微硬度，硬度提高了7～25倍。用球盘式磨损实验机测量注人前后PC的耐磨性能，磨痕的宽度比未注人的窄，最窄的磨痕(或最窄处)为未注人磨痕宽度的1／3～1／2。傅里叶变换红外光谱(FTIR)测试表明，注人前后高分子的结构发生了变化。     

Hybrid accident simulation methodology using artificial neural networks for nuclear power plants

A hybrid accident simulation methodology for nuclear power plants is proposed to enhance the capabilities of compact simulator by introducing artificial neural networks. Two neural networks are trained with the target values obtained from the analyses of detailed computer codes and trained results are combined with the compact simulator to perform the following roles: (i) compensation for inaccuracies of a compact simulator occurring from simplified governing equation and reduced number of physical control volumes, and (ii) prediction of the critical parameter usually calculated from the sophisticated computer code: the autoassociative neural network improves the computational results of the compact simulator up to the accuracy level of detailed best estimate computer code, while the backpropagation neural network predicts the minimum departure from nucleate boiling ratio (DNBR). Simulations are carried out to verify the applicability of the proposed methodology for the loss of flow accidents and the results show that the neural networks can be used as a complementary tool to improve the results of a compact simulator.