Mixed oxide supported hydrodesulfurization catalysts—a review

Support effects form important aspect of hydrodesulfurization (HDS) studies and mixed oxide supports received maximum attention in the last two decades. This review will focus attention on studies on mixed oxide supported Mo and W catalysts. For convenience of discussion, these are divided into Al₂O₃ containing mixed oxide supports, TiO₂ containing mixed oxide supports, ZrO₂ containing mixed oxide supports and other mixed oxide supports containing all the rest. TiO₂ containing mixed oxides received maximum attention, especially TiO₂–Al₂O₃ supported catalysts. A brief discussion about their prospects for application to ultradeep desulfurization is also included. An overview of the available literature with emphasis on research carried out in our laboratory form the contents of this publication.     

Drag coefficient of flow around a sphere: Matching asymptotically the wide trend

An empirical relationship of drag coefficient of flow around a sphere is developed for the entire range of Particle Reynolds numbers reported in the literature from Stokes regime to the condition when turbulent boundary layer prevails. The relationship is obtained using an approach to match asymptotically the wide trend of drag coefficient. The matching approach, which relies on dividing the wide trend into smaller segments that can be combined into an overall relationship, employs regression techniques and thus warrants the best-fit accuracy results. The relationship is calibrated with experimental data available in the literature covering the entire range for Reynolds numbers up to ~ 10⁶. For Reynolds values greater than 10⁶, the relationship renders a drag coefficient of 0.2. The performance of the relationship is tested and compared with other suitable models found in the literature. This relationship is also transformed into an explicit expression for settling velocity calculations.     

The effect of support morphology on the reaction of oxidative dehydrogenation of ethane to ethylene at short contact times

The oxidative dehydrogenation of ethane is carried out in short contact time reactors over Pt and LaMnO₃ based catalysts supported on a large number of different ceramic substrates (45, 60 and 80 ppi foam monoliths and 200, 400, 600, 900 and 1200 cpsi honeycomb monoliths). Experimental results, obtained under the same conditions at varying the C₂H₆/O₂ ratio, showed that the highest performance in terms of ethylene selectivity and yield is always attained on LaMnO₃ catalysts. Furthermore, the results are significantly influenced by the morphology and cell density of the support, with 45 and 60 ppi foams and 400 and 600 cpsi honeycombs giving the best performance. The experimental results are explained by means of geometrical and fluid dynamic considerations on the support, and by means of a 2D mathematical model, which clearly indicates an optimal intermediate cell density for maximising ethylene selectivity and yield.     

Geotechnical properties of the soft soil in Guangzhou College City

The paper describes some geotechnical properties of the soft soils in Guangzhou College City, China, which are difficult to both sample and test. Laboratory and in situ tests were carried out to assess the physical and mechanical indices of the soils. The data were statistically analyzed and linear regression undertaken such that equations could be developed by which the geotechnical properties of the soft soils can be predicted. The statistical validity of the degree of correlation confirmed that using these equations, the mechanical indices can be estimated from physical indices determined by routine testing.      

Composite group vector space method for estimating melting and boiling point of pure organic compound

Composition Group Vector Space (CGVS) method for estimating melting and boiling point T _m , T _b of organic compound has been proposed, and the principle of this method has been elucidated. The models for estimating T _m , T _b have been established and the numerical values of relative parameters have been presented. The average percentage deviations of T _m , T _b estimation are 7.53 and 1.58, respectively, which show that the present method demonstrates significant improvement in applicability to predict the above properties, compared to conventional group methods.     

Multi-label core vector machine with a zero label

Multi-label core vector machine (Rank-CVM) is an efficient and effective algorithm for multi-label classification. But there still exist two aspects to be improved: reducing training and testing computational costs further, and detecting relevant labels effectively. In this paper, we extend Rank-CVM via adding a zero label to construct its variant with a zero label, i.e., Rank-CVMz, which is formulated as the same quadratic programming form with a unit simplex constraint and non-negative ones as Rank-CVM, and then is solved by Frank–Wolfe method efficiently. Attractively, our Rank-CVMz has fewer variables to be solved than Rank-CVM, which speeds up training procedure dramatically. Further, the relevant labels are effectively detected by the zero label. Experimental results on 12 benchmark data sets demonstrate that our method achieves a competitive performance, compared with six existing multi-label algorithms according to six indicative instance-based measures. Moreover, on the average, our Rank-CVMz runs 83 times faster and has slightly fewer support vectors than its origin Rank-CVM.     

基于神经网络和支持向量机的电能质量组合评价

电能质量在当代越来越受到重视.根据电能质量的概述,提炼出电能质量评价指标体系,并基于组合评价的原理,运用BP神经网络和支持向量机对其进行评价,通过检验,证明了评价方法的有效性.     

轻工行业中的变频器系统设计与应用——第5讲 变频器在食品机械中的应用

对食品机械使用变频器后,可以简化传动系统,提高机器运转的稳定性和可靠性,降低机器运转的噪音,大大延长使用寿命和最大限度地降低故障率。同时还可以增加产量、降低成本,最终使产品产量和品质都得到提高,实现利润最大化。     

Evaluation of tile–wall bonding integrity based on impact acoustics and support vector machine

It is well recognized that the impact-acoustic emissions contain information that can indicate the presence of the adhesive defects in the bonding structures. In our previous papers, artificial neural network (ANN) was adopted to assess the bonding integrity of the tile–walls with the feature extracted from the power spectral density (PSD) of the impact-acoustic signals acting as the input of classifier. However, in addition to the inconvenience posed by the general drawbacks such as long training time and large number of training samples needed, the performance of the classic ANN classifier is deteriorated by the similar spectral characteristics between different bonding status caused by abnormal impacts. In this paper our previous works was developed by the employment of the least-squares support vector machine (LS-SVM) classifier instead of the ANN to derive a bonding integrity recognition approach with better reliability and enhanced immunity to surface roughness. With the help of the specially designed artificial sample slabs, experiments results obtained with the proposed method are provided and compared with that using the ANN classifier, demonstrating the effectiveness of the present strategy.     

支持向量机序贯最小优化算法推导的改进

已有文献中的支持向量机SMO算法推导过程计算复杂,该文给出一个简洁推导。整个推导过程没有复杂的计算,除了误差函数外,不需引入其它中间变量。