Computational Fluid Dynamics Study on a Top-Blown Smelting Process with Lance Failure in an Isa Furnace

JOM - The Isa/Ausmelt smelting technology with a top submerged lance (TSL) has been extensively used in copper smelting processes. However, the TSL is extremely vulnerable to damage and failure...     

以奥林匹克精神为纲——中国运动鞋品牌运行之我见

2008年29届奥运会在北京举行，使得有关奥运的话题成为热门中的热门，与运动有关或无关的众多品牌、厂商对北京奥运年均寄予厚望，为赢取更大的收获和提升品牌知名度作最大的努力。其实早在几年前，国内外运动鞋品牌企业就已经大张旗鼓，在产品研发与广告宣传等多方面投入重金，为在这次北京奥运年带来的难得契机中处于市场制高点或明或隐地博杀着。     

含V、N无缝钢管表面外折缺陷产生原因的分析

通过对鞍钢生产的部分批号V、N微合金强化无缝钢管及生产该钢管的原料连铸坯和连轧管坯的表面缺陷进行研究，分析了含V、N钢管表面外折缺陷的成因，提出了改善钢管表面质量的方法。采用改进后工艺生产的无缝管，其表面外折废品量大幅度降低。     

Effectiveness of spatial representation in the formation of network communities: experimental study on community organizer

In this paper, we present and discuss Community Organizer, a system designed to support network communities. The main characteristic of Community Organizer is the use of spatial representations for the relationships among community members including the communications exchanged among these members. These spatial representations reflect the degree of closeness of interests and concerns among the members, and are intended to provide users with clues on how to form network communities. In order to investigate the effectiveness of the proposed spatial representations, we conducted experiments with two different versions of the software. One version offered meaningful spatial representations while the other version did not. The subjects who used the former software version felt a greater sense of ‘community’, enjoyed using the software more, and actively used it longer than the subjects using the latter software version (control condition). These results indicated that the proposed spatial representations are effective in supporting network community formation.     

Sediment Concentration and Its Prediction by Perceptron Kalman Filtering Procedure

Predictions of the discharge and the associated sediment concentration are very useful ingredients in any water resources reservoir design, planning, maintenance, and operation. Although there are many empirical relationships between the discharge and sediment concentration amounts, they need estimation of model parameters. Generally, parameter estimations are achieved through the regression method (RM), which has several restrictive assumptions. Such models are locally valid and their structures and parameter values are questionable from region to others. This paper proposes a new approach for sediment concentration prediction provided that there are measurements of discharge and sediment concentration. The basis of the methodology is a dynamic transitional model between successive time instances based on two variables, namely, discharge and sediment concentration measurements. The transition matrix elements are estimated from the measurements through a special form of the artificial neural networks as perceptrons. The sediment concentration predictions from discharge measurements are achieved through a perceptron Kalman filtering (PKF) technique. In the meantime, this technique also provides temporal predictions. A certain portion of the measurement sequence is employed for the model parameter estimations through training and the remaining part is used for the model verification. Detailed comparisons between RM and PKF approaches are presented and, finally, it is shown that the latter model works dynamically by simulating the observation scatter diagram in the best possible manner with smaller prediction errors. The application of the methodology is performed for the discharge and sediment concentration measurements obtained from the Mississippi River basin at St. Louis, Missouri. It is found that the PKF methodology has smaller average relative, root-mean-square, and absolute errors than RM. Furthermore, graphical representation, such as the scatter and frequency diagrams, indicated that the PKF approach has superiority over the RM.     

叠后记录Radon变换压制干扰方法

在叠加剖面中,下伏反射界面的反射信号同相轴呈连续的或带有限个间断点的连续层状图像,各种干扰则呈无规则的图像。对此剖面的振幅数据进行 Radon 变换,即分别向各方向进行投影,层状图像将产生一定形状的光滑曲线,而干扰数据将相互抵消,其剩余数据呈高斯分布。在Radon 域中通过平滑等方法消除这些呈高斯分布的噪声数据,再经 Radon 逆变换,便可获得信噪比较高的叠加剖面。其结果不改变原叠加剖面的分辨率和信号波形特征。理论与实际剖面的处理结果表明,这是一种良好的压制干扰方法。