高铝高炉渣系的熔化特性

 为了掌握高Al₂O₃条件下(w(Al₂O₃)为15%以上)高炉渣系的熔化特性,利用差式扫描量热仪分析了不同w(MgO)/w(Al₂O₃)、碱度(R)以及w(Al₂O₃)对高铝高炉渣的熔化温度及熔化热的影响。试验结果表明,炉渣熔化开始温度为1 248～1 291 ℃、熔化结束温度为1 432～1 485 ℃、熔化热为137～211 J/g;当w(Al₂O₃)=15%、高w(MgO)/w(Al₂O₃)时,发生了共晶逆反应,导致高炉炉渣熔化开始温度逐渐降低,但由于高炉炉渣的液相线温度基本未变,所以炉渣熔化结束温度基本未发生改变;w(Al₂O₃)为20%时,随着w(MgO)/w(Al₂O₃)的增加,炉渣中易生成熔点较高的镁铝尖晶石,导致高炉炉渣熔化开始温度逐渐增大,与此同时,炉渣液相线温度逐渐降低,导致炉渣熔化结束温度逐渐降低;随着碱度R的增加,高炉炉渣中生成了具有高熔点的化合物、炉渣的液相线温度升高,使得高炉炉渣的熔化开始温度逐渐增加、炉渣熔化结束温度逐渐升高;随着w(Al₂O₃)的增加,发生了共晶逆反应,故炉渣的熔化开始温度逐渐降低,而随着w(Al₂O₃)的增加,炉渣中键能较大的Al—O键增多,需要在更高温度下才能实现炉渣的最终熔化,即熔化结束温度逐渐增加;随着w(MgO)/w(Al₂O₃)、R以及w(Al₂O₃)的增加,炉渣熔化热逐渐增多。分析认为,随着R的增加,炉渣中有高熔点化合物的生成,熔化热增加;随着炉渣中w(Al₂O₃)的增加,炉渣中Al—O键增多,解聚破坏熔渣结构消耗的热量增多;而随着w(MgO)/w(Al₂O₃)增加,高熔点化合物的生成或熔化开始温度降低,造成熔化热增加。     

Viscosity of compressed cold lake bitumen

Viscosity data over a temperature range of 37-115°C and a pressure range of 0-10 MPa gauge are presented for a Cold Lake bitumen sample. These data show that the compression of Cold Lake bitumen results in a significant increase in its viscosity. Results are compared with those from a similar study on an Athabasca bitumen sample. Also presented are two correlations for the effects of pressure and temperature on the viscosity of Cold Lake bitumen.     

Gas hold-up in non-newtonian solutions in a bubble column with internals

Bubble characteristics and gas hold-up were studied in a two phase (air-aqueous CMC solution) bubble column provided with helical coils and straight tubes as internals. The effects of superficial gas velocity, rheological properties, and volume fraction covered by the internals, on gas hold-up were studied. Hold-up values determined directly and by simultaneous pressure drop measurements matched well. Enhancement of gas hold-up values up to 55 per cent was achieved in systems using internals. The gas hold-up results were also compared with the values obtained from correlations reported in the literature.     

飞机碱性电瓶充放电参数测量仪的设计与研究

电瓶是民航飞机可靠供电的最后保证。飞机制造厂家提高了对电瓶的性能和容量检测要求,传统的电瓶充放电装置已经无法满足新的要求。利用单片机技术研制的飞机电瓶参数测试仪,实现了对电瓶各种参数的实时侧量和分析,为飞机电瓶维护和检测提供依据。     

存储器相关概念教学分析

为了改变存储器知识点“学生难学,教师难教”的局面,在教学过程中通过理论联系实际的方法介绍存储器相关概念,期望学生能够加深理解,为后续课程的学习及往后在工程实践中运用相关知识解决实际问题打下坚实的基础。     

带取代基硝酮化合物光环化反应的研究

本工作合成了一系列取代的硝酮类化合物。其中部分化合物仅一侧的苯环上带有取代基,而另部分化合物则两个苯环上均带有取代基。研究工作表明:取代基处于一侧的硝酮类化合物,不论取代基是给出电子或接受电子的,均有利于化合物光环化反应的进行。而当两个苯环分别带有给电子及接受电子的取代基形成推拉结构时,则大大减弱了化合物光环化反应的发生。文章对上述结果进行了初步讨论。     

型腔体组件装配尺寸检测技术分析与运用

为解决型腔体组件装配尺寸的检测问题,以某枪型的型腔体组件为例,分析该型腔体组件的结构特点,设计组合型检测装置,实现准确检测目的.归纳总结了型腔体组件装配尺寸检测技术运用过程中检测装置的设计要领,采用设计与被测型腔体组件相匹配的组合型检测装置,有效解决了型腔体组件装配尺寸检测过程中的定位困难、操作繁琐、检测准确性差等问题.该检测技术对确保型腔体组件装配尺寸的检测稳定性、检测可操作性、检测准确性等方面具有现实的指导意义.     

基于引力搜索算法的分数阶变异时序回归GSA-TSGM(1,1)模型

为了利用分数阶累加算子在灰色短期预测中的高效性能,首次将分数阶累加算子引入变异时序回归模型以期取得更高的预测精度。主要方法如下：首先取湖北省链子崖某监测点1978—1987年的十年数据作为训练集并使用引力搜索算法确定最佳分数阶累加阶数,而1988—1993年的六年数据作为验证集验证提出的模型;其次对比了经典灰色模型GM(1,1)、分数阶累加灰色模型、变异时序回归模型TSGM(1,1)三种灰色模型。结果如下：首先修正了陈西江等人变异时序回归模型仿真时出现的错误,其次表明了相比于其他的模型,基于引力搜索算法的分数阶累加时序回归模型在进行灰色长期预测中具有较高的预测精度。因此,通过分数阶累加算子提高了灰色理论中长期预测模型的精度,为灰色长期预测提供了指导。     

Charge reduction and regeneration in K+, Na+, Mg2+, Ni2+ and Co2+-exchanged Wyoming Bentonite

Controlled calcination of ion-exchanged Wyoming Bentonite in the presence and absence of ammonia leads to layer charge reductions. Detailed chemical analyses of both unexchangeable and exchangeable species lead to the conclusion that in no case is there migration of the original interlamellar cations into the octahedral region of the layers although, in terms of ionic radius alone, Mg²⁺, Ni²⁺ and, possibly Co²⁺, might be expected to do so. The production of unexchangeable Mg, Ni or Co, is identified as resulting from high temperature hydrolysis leading to hydroxide or oxide formation.     

The clustering-based case-based reasoning for imbalanced business failure prediction: a hybrid approach through integrating unsupervised process with supervised process

Case-based reasoning (CBR) is one of the main forecasting methods in business forecasting, which performs well in prediction and holds the ability of giving explanations for the results. In business failure prediction (BFP), the number of failed enterprises is relatively small, compared with the number of non-failed ones. However, the loss is huge when an enterprise fails. Therefore, it is necessary to develop methods (trained on imbalanced samples) which forecast well for this small proportion of failed enterprises and performs accurately on total accuracy meanwhile. Commonly used methods constructed on the assumption of balanced samples do not perform well in predicting minority samples on imbalanced samples consisting of the minority/failed enterprises and the majority/non-failed ones. This article develops a new method called clustering-based CBR (CBCBR), which integrates clustering analysis, an unsupervised process, with CBR, a supervised process, to enhance the efficiency of retrieving information from both minority and majority in CBR. In CBCBR, various case classes are firstly generated through hierarchical clustering inside stored experienced cases, and class centres are calculated out by integrating cases information in the same clustered class. When predicting the label of a target case, its nearest clustered case class is firstly retrieved by ranking similarities between the target case and each clustered case class centre. Then, nearest neighbours of the target case in the determined clustered case class are retrieved. Finally, labels of the nearest experienced cases are used in prediction. In the empirical experiment with two imbalanced samples from China, the performance of CBCBR was compared with the classical CBR, a support vector machine, a logistic regression and a multi-variant discriminate analysis. The results show that compared with the other four methods, CBCBR performed significantly better in terms of sensitivity for identifying the minority samples and generated high total accuracy meanwhile. The proposed approach makes CBR useful in imbalanced forecasting.