Surface treatment of titanium dioxide nanopowder using rotary electrode dielectric barrier discharge reactor

Titanium dioxide (TiO2) nanopowder (P-25;Degussa AG) was treated using dielectric barrier discharge (DBD) in a rotary electrode DBD (RE-DBD) reactor.Its electrical and optical characteristics were investigated during RE-DBD generation.The treated TiO2 nanopowder properties and structures were analyzed using x-ray diffraction (XRD) and Fourier-transform infrared spectroscopy (FTIR).After RE-DBD treatment,XRD measurements indicated that the anatase peak theta positions shifted from 25.3° to 25.1°,which can be attributed to the substitution of new functional groups in the TiO2 lattice.The FTIR results show that hydroxyl groups (OH) at 3400 cm-1 increased considerably.The mechanism used to modify the TiO2 nanopowder surface by air DBD treatment was confirmed from optical emission spectrum measurements.Reactive species,such as OH radical,ozone and atomic oxygen can play key roles in hydroxyl formation on the TiO2 nanopowder surface.     

汽车密封件双料一体旋转模具设计

针对PP+TPE汽车密封件设计了大型双料一体旋转注射模,介绍了二次合模的精确定位、可控注射系统、顶出平衡设计。该模具技术能够使两种性能完全不同的材料按照指定区域分布,并且达到塑件尺寸的精度需求,实现同时与钣金、玻璃、塑件等不同材质的零件进行复合配套。本项目实施后,在模具精度、寿命等方面接近或部分达到国外同类产品先进水平,而价格仅为国外产品的40%,性价比优势明显。     

转底炉处理赤泥工艺技术

为了综合利用氧化铝冶炼产生的赤泥，探索在转底炉中直接还原赤泥、磨矿磁选获得高品位直接还原铁。通过实验室试验摸索了转底炉还原工艺参数，并在转底炉工业试验线进行了工业试验。实验室结果表明，赤泥还原后的直接还原铁(DRI)金属化率可达88.6%，磁选后的铁品位可达82.1%，磁选后的铁回收率可达88.9%。工业试验中，转底炉还原后，产品金属化率平均为69.2%，将还原后的DRI磁选获得高品位的DRI产品，磁选后DRI的铁品位为72.8%，磁选后铁回收率达到了85.2%,初步打通了在转底炉中还原赤泥、磁选的工艺路径。     

超临界二氧化碳干气密封相态分布规律与密封性能研究

以超临界二氧化碳干气密封为研究对象，分别以维里方程、Lucas方程描述二氧化碳真实气体效应、黏度的变化，在考虑阻塞流效应的同时，采用有限差分法对考虑离心惯性力效应的Reynolds方程与能量控制方程进行耦合求解，分析讨论了工况参数与槽形结构参数对其相态分布规律与密封性能的影响。研究表明：S-CO₂从密封端面进口至出口的流动过程中，如果工况参数设置合理，将由超临界态逐渐转变为气态，并不会出现液态；较低的进口压力、进口温度以及转速，均会容易导致潜在的凝结流动发生；相比于工况参数对相态分布的影响，槽形参数对相态分布的影响较小，近乎可以忽略；开启力除了随进口温度的升高而减小外，均随进口压力、转速、槽深、螺旋角的增大而增大；泄漏率随进口温度和转速的增大而减小，但其随进口压力、槽深、螺旋角的增大而增大。这些结果为进一步研究超临界二氧化碳干气密封提供了一定的支撑。     

精密磨床转台静压轴承的强健化设计

针对精密磨床转台静压轴承性能仿真数据与其回转精度实测数据不一致的问题，为提高转台静压轴承的设计水平，提出了静压轴承的强健化设计方法。该方法考虑了轴承结构参数在轴承全生命周期内的变化，分析了半径间隙、油腔尺寸、节流比及润滑油黏度在设计、加工、装配和服役4个阶段的变化规律，重点研究了半径间隙在各阶段对轴承性能造成的影响，给出了转台静压轴承的强健化设计流程。通过一个径向轴承的设计实例对该强健化设计方法进行了说明，并将设计结果与传统设计进行了对比。对比的指标是轴承在4个阶段的刚度、承载力和温升，这3个指标对轴承回转精度有直接影响。研究表明：进行强健化设计后，在生命周期内静压轴承的刚度和承载力的变化量为10%~27%，温度的变化量为0.5%~1.6%，较传统设计更能保证转台回转精度的稳定。     

新型矿用旋转筛设计研究

设计一种新型矿用旋转筛,利用7个筛板安装在旋转轴上,通过变频电机带动旋转轴与筛板转动,筛条间距根据物料筛分要求来设计,从而达到对煤矿物料的分级分离目的。根据筛分规格数量,可以串联2个以上旋转筛来使用。通过EDEM和ANSYS仿真,验证设计的合理性;通过样机试验验证,表明可以对煤矿石进行很好的筛分,而且具有节能、环保和成本低等优点。     

回转窑人工智能专家系统的应用实践

根据水泥熟料煅烧过程操作控制原理研发的"回转窑人工智能专家系统"采用了人工智能模拟技术、实时数据清洗技术、控制数据关联匹配技术。该系统由分解炉出口温度自动控制系统、篦速自动控制系统和氨水用量自动控制系统三个模块组成。该系统投运后,分解炉出口温度控制有效率由之前人工控制的平均60%~70%提高至平均80%~95%;篦下压力和二次风温稳定性提高;氨水消耗量下降显著;窑系统投料量增加10 t/h左右,熟料标准煤耗降低2.85 kg/t,熟料强度均有提高。     

实用型气动旋转装夹工作台的设计

该设计实例为一种气动旋转装夹工作台,详细介绍该装置的设计思路,分析其结构和动作原理。该装置在实际应用中,完全满足了特殊工况需求,性能稳定,具有一定的推广价值。     

Shear crack growth in brittle materials modeled by constrained Cosserat elasticity

The propagation of in-plane shear cracks is investigated in brittle microstructured materials modeled by the constrained Cosserat elasticity. This theory introduces characteristic material lengths in order to describe the scale effects that emerge from the underlying microstructure and has proved to be very effective for modeling complex microstructured materials. An exact solution is obtained based on integral transforms and the Wiener-Hopf technique. Numerical results are presented illustrating the dependence of the stress intensity factor and the energy release rate upon the loading profile, the propagation velocity, and the characteristic material lengths of Cosserat elasticity. It is shown that depending on the Cosserat microstructural lengths the limiting crack propagation velocity can be significantly lower than the classical Rayleigh limit. Moreover, strengthening effects are observed when the characteristic material lengths become comparable to the geometrical lengths of the problem, a behavior that has been experimentally verified in fracture of ceramics.     

Hybrid self-inertia weight adaptive particle swarm optimisation with local search using C4.5 decision tree classifier for feature selection problems

ABSTRACT

Feature selection is an important task to improve the classifier’s accuracy and to decrease the problem size. A number of methodologies have been presented for feature selection problems using metaheuristic algorithms. In this paper, an improved self-adaptive inertia weight particle swarm optimisation with local search and combined with C4.5 classifiers for feature selection algorithm is proposed. In this proposed algorithm, the gradient base local search with its capacity of helping to explore the feature space and an improved self-adaptive inertia weight particle swarm optimisation with its ability to converge a best global solution in the search space. Experimental results have verified that the SIW-APSO-LS performed well compared with other state of art feature selection techniques on a suit of 16 standard data sets.