Effect of Nb on the Microstructure and Properties of Cold Rolled and Annealed Mo Microalloyed Bainitic Steel

Two kinds of low carbon bainitic steels,Nb-free Mo bearing and Nb + Mo addition steels,were cold rolled and annealed to investigate the effect of micro-alloying element Nb on the microstructure and properties of Mo microalloyed low carbon high strength bainitic steel. No precipitates were observed in Nb-free Mo bearing steel,whereas,two types of precipitates,i.e.,Nb( C,N) and composite( Nb,Mo)( C,N),were observed in the Nb + Mo microalloyed steel,resulting in precipitation strengthening. The strength of Mo bearing steel was improved by addition of Nb under the same annealing conditions. The grain size of Nb addition steel was almost the same as Nb-free steel. Unlike the obvious grain refinement and precipitation strengthening in hot rolling,the increase in yield strength of Nb addition steels in cold rolling and annealing mainly results from the precipitation strengthening,while the effect of grain refinement strengthening can be almost ignored.     

Multi-Dimensional Tunneling in Density-Gradient Theory

The equations of density-gradient theory for describing electron tunneling in multi-dimensions are developed and discussed. The theory is illustrated with an application to tunneling in an STM-like geometry.     

Spherical Harmonics Solutions of Multi-Dimensional Neutron Transport Equation by Finite Fourier Transformation

A method of solution of a monoenergetic neutron transport equation in P_L approximation is presented for x-y and x-y-z geometries using the finite Fourier transformation. A reactor system is assumed to consist of multiregions in each of which the nuclear cross sections are spatially constant. Since the unknown functions of this method are the spherical harmonics components of the neutron angular flux at the material boundaries alone, the three- and two-dimensional equations are reduced to two- and one-dimensional equations, respectively. The present approach therefore gives fewer unknowns than in the usual series expansion method or in the finite difference method. Some numerical examples are shown for the criticality problem.     

大力发展多功能的地质测绘事业

详细阐述了目前地质测绘业面临的新挑战和新机遇,并结合河南省地质测绘总院的实际情况,创新性的提出了大力发展多功能的地质测绘事业的新战略,进而对实现多功能地质测绘事业的途径和方法进行了深刻剖析,为全国的地质测绘事业的发展提供借鉴。     

小波分析在电池钢壳口部裂纹检测中的应用

小波变换可以把噪音信号从有效信号中去除,并对图像进行分解处理;通过多尺度下的基于小波变换,可以检测并表征一个图像信号.利用此信号处理方法,可有效地实时检测与识别电池钢壳口部的裂纹.     

基于XML的联机数据分析系统

本文叙述了联机数据分析系统分析模型、结构和特点，系统采用XML技术对数据结构进行描述，将XML结构与JTree树节点建立一一对应的关系。并将XML文件保存在Native—XML数据库，这样的联机数据分析系统具有较好应用前景。     

大型地区电网调度控制系统海量历史数据处理技术

随着电网规模扩大和集约化运行管理体系的建设,地区电网调度控制系统监控范围急剧增加,传统以商用数据库为基础的历史数据管理技术和早期使用时间序列数据库的历史数据管理技术已不能满足大型地区电网调度运行和各类应用深化拓展的需要.结合商用数据库、文件系统,以时间序列数据库为重要存储手段的海量历史数据处理技术能很好地解决上述问题.文中首先介绍了以时间序列数据库为核心的历史数据管理体系架构,然后阐述了解决大容量、高效率、高可靠问题的关键技术,紧接着介绍了部分依赖历史时序数据的深化应用.该技术已成功应用于苏州电网调度控制系统,它很好地适应了“大运行”的要求,提升了地区电网调度运行水平,为地区智能电网建设提供了有力的技术支撑.     

采用人工蜂群算法求解多维函数极值

文章首先介绍了人工蜂群算法,然后提出了一种采用人工蜂群算法求解多维函数极值的新方法,最后编写出MATLAB程序并选取四个标准测试函数进行实验仿真。通过将实验仿真结果与粒子群算法求解结果和理论最优值进行比较分析,证明了该方法可行,而且具有耗时短,收敛快等优点。     

A Time-Splitting Spectral Method for the Generalized Zakharov System in Multi-Dimensions

The generalized Zakharov system (ZS) couples a dispersive field E (scalar or vectorial) and nondispersive fields with a propagating speed of . In this paper, we extend our one-dimensional time-splitting spectral method (TSSP) for the generalized ZS into higher dimension. A main new idea is to reformulate the multi-dimensional wave equations for the nondispersive fields into a first-order system using a change of variable defined in the Fourier space. The proposed scheme TSSP is unconditionally stable, second-order in time and spectrally accurate in space. Moreover, in the subsonic regime, it allows numerical capturing of the subsonic limit without resolving the small parameters . Numerical examples confirm these properties of this method     

顺序敏感的多源感知数据填补技术

近年来,随着感知网络的广泛应用,感知数据呈爆炸式增长.但是由于受到硬件设备的固有限制、部署环境的随机性以及数据处理过程中的人为失误等多方面因素的影响,感知数据中通常包含大量的缺失值.而大多数现有的上层应用分析工具无法处理包含缺失值的数据集,因此对缺失数据进行填补是不可或缺的.目前也有很多缺失数据填补算法,但在缺失数据较为密集的情况下,已有算法的填补准确性很难保证,同时未考虑填补顺序对填补精度的影响.基于此,提出了一种面向多源感知数据且顺序敏感的缺失值填补框架OMSMVI（order-sensitive missing value imputation framework for multi-source sensory data）.该框架充分利用感知数据特有的多维度相关性：时间相关性、空间相关性、属性相关性,对不同数据源间的相似度进行衡量;进而,基于多维度相似性构建以缺失数据源为中心的相似图,并将已填补的缺失值作为观测值用于后续填补过程中.同时考虑缺失数据源的整体分布,提出对缺失值进行顺序敏感的填补,即：首先对缺失值的填补顺序进行决策,再对缺失值进行填补.对缺失值进行顺序填补能够有效缓解在缺失数据较为密集的情况下,由于缺失数据源的完整近邻与其相似度较低引起的填补精度下降问题;最后,对KNN填补算法进行改进,提出一种新的基于近邻节点的缺失值填补算法NI（neighborhood-based imputation）,该算法利用感知数据的多维度相似性对缺失数据源的所有近邻节点进行查找,解决了KNN填补算法K值难以确定的问题,也进一步提高了填补准确性.利用两个真实数据集,并与基本填补算法进行对比,验证了算法的准确性及有效性.