海藻化工以氢氧化钙作为钙化剂的新型钙化工艺研究

研究了海藻化工中以氢氧化钙作为钙化剂的新型钙化工艺,使用氢氧化钙+氯化钙作为褐藻酸钠的钙化剂替代传统的单一氯化钙。确定的双钙钙化工艺条件：每升褐藻酸钠胶液（褐藻酸钠质量浓度为2.5 g/L）,添加氯化钙溶液29.0 mL（质量分数为5%）,添加氢氧化钙溶液13.75 mL（质量分数为5%）,复合钙化剂中氯化钙与氢氧化钙物质的量比为1.19∶1。与传统工艺相比,新型钙化工艺褐藻酸钠的产率未有明显变化,得到的褐藻酸钠粘度稍有降低,粘度由275.1 mPa·s降低至241.3 mPa·s;氯化钙使用量降低40%以上,总钙添加量减少19%。双钙钙化工艺实现了对钙化废水的再利用,废水中钙质量浓度经处理由483 mg/L降到20 mg/L左右,电导率由6.84 mS/cm降至4.28 mS/cm;经脱钙处理的钙化废水回用后对产品褐藻酸钠的产率和粘度没有显著影响。新工艺操作简单,不仅有效减少了钙化废水中离子的引入,同时可以实现低成本地脱钙,脱钙后的废水可以作为冲稀水回收利用,减少了水资源的消耗,为海藻化工行业的减排提供了一条新的工艺途径。     

XJM-KS型浮选机矿化器负压产生机理研究

浮选机矿化器是用于浮选矿浆预处理的重要设备，其性能的优劣直接影响到浮选机的工作效果。文章通过流体力学仿真软件FLUENT对XJM-KS型浮选机矿化器的内部流场进行数值仿真，重点研究了聚焦式喷嘴布置所带来的流场特征。模拟结果表明，高速的矿浆射流能够在混合室内产生-2.43×10Pa的负压区，从而吸入大量的空气，实现空气与矿浆的有效混合与预矿化，与传统的机械搅拌式矿浆预处理装置相比，该矿化器能够大幅度提高预矿化效果。     

Atomistic insight into the hydration and proton conducting mechanisms of the cobalt doped Ruddlesden-Popper structure Sr3Fe2O7-δ

Sr₃Fe₂O_7-δ (SFO) with two-layer Ruddlesden-Popper (R–P) structure has recently been proved to be a promising material for the single phase cathode in proton conducting solid oxide fuel cells (P–SOFCs). To investigate the hydration reactions and proton conducting mechanisms of SFO and cobalt doped SFO (SFCO), both bulk and surface properties were calculated. We conclude that R–P structures have advantages in P–SOFCs. The unique Sr–O–M layer can facilitate the hydration process. Although in Sr–O–F and Sr–O–N layers, it is difficult for the formation and migration of oxygen vacancies, protons are most stable. Furthermore, cobalt doping can not only improve the electronic conductivity but also enhance surface properties of SFCO. The easily exposed Co–Fe–O surface can also facilitate the hydration reactions on the surface. Our work could give an informative insight into the relationships among the doped elements, the R–P structures, the hydration process and the proton conducting properties.     

Prediction of process parameters of water-assisted injection molding based on inverse radial basis function neural network

Because of the introduction of new processing parameters in water-assisted injection molding (WAIM), processes control has become more difficult. First, design of experiment (DOE) was carried out by using optimized Latin hypercubes (Opt LHS). On the basis of this, computational fluid dynamics (CFD) method was used to simulate and calculate hollowed core ratios and wall thickness differences of cooling water pipe at different positions. Then inverse radial basis function (RBF) neural network model reflecting the fitting relationship between processing parameters and molding quality was established, and accuracy of the model was detected by cross validation. Finally, expected molding quality was applied to predict processing parameters, and the obtained molding quality under the predicted processing parameters was verified by computer aided engineering (CAE) simulation and experimental methods. The results showed that mean relative precisions of processing parameters such as melt temperature, delay time, short shot size, water pressure, and mold temperature for inverse RBF model were 98.6%, 93.6%, 98.5%, 93.9%, and 97.9%, respectively, which met the accuracy requirements. Furthermore, compared with expected values of hollowed core ratios and wall thickness differences, the average errors of CAE and experiment were 2.3% and 4.9%, respectively.     

A Distribution‐freeCUSUMChart for Monitoring Variability of AutocorrelatedProcesses

We present a distribution‐free tabular cumulative sum chart for monitoring the variability of an autocorrelated process. A quantity known as the asymptotic variance parameter is employed as a measure of the variability, and a distribution‐free tabular cumulative sum chart is applied to variance estimates calculated from batches of nonoverlapping samples. The proposed chart is applicable to a stationary process with a general marginal distribution and a general autocorrelation structure. It also determines control limits analytically without trial‐and‐error simulations. The performance of the proposed chart is tested on stationary processes with both normal and nonnormal marginals with various autocorrelation structures. Copyright © 2014 John Wiley & Sons, Ltd.     

萃取塔数学模型及过程强化的若干研究进展

萃取塔因生产能力大、占地面积小、密闭性好等优点，在石油、化工、生物、医药和环境工程等多领域被广泛应用。本文从以下几个方面介绍了萃取塔近些年的研究进展：综述了传统萃取塔（脉冲萃取塔、转盘塔与Kühni塔等）的水力学、轴向扩散与传质模型的发展，分析比较了表面张力、传质方向、放大效应等因素对模型的影响；介绍了计算流体动力学（CFD）在萃取塔中单液滴、单相流模拟、液-液两相流模拟、外加能量模拟、与群体平衡模型（PBM）耦合模拟中的应用进展；介绍了国内外设计开发的新型萃取塔，包括改变传统塔的内构件和引入多种外场能量等方式来强化相间传质。研究表明，将先进实验研究方法、准确经验模型和可靠理论计算相结合，将会是萃取塔研究的重要手段和方向。     

一类两性分枝过程条件均值增长率的极限性质

本文主要研究随机环境中配对依赖人口数两性 Galton-Watson 分枝过程的条件均值增长率的极限性质．利用上可加函数的性质，得到配对单元平均增长率的极限性质和该过程条件均值的上界和下界．文中给出了关于过程条件均值增长率的两个序列，利用配对单元平均增长率的性质，获得了这两个序列的极限性质．随机环境中配对依赖人口数两性分枝过程比较复杂，本文的结论推广了现有的研究成果．     

从工艺矿物学角度探讨某低品位铀多金属矿预抛尾的可行性

某超大型复杂铀多金属矿具有有价元素含量低、目的矿物种类多而含量少的特点,为减少选别工作量,降低企业生产成本,有必要对该矿石进行预抛尾。从工艺矿物学角度探讨了预抛尾的可行性,最后建议在-2mm破碎细度下采用螺旋溜槽重选进行预抛尾,使有用矿物得到有效富集,并最终取得良好的选矿指标。     

基于改进NSGA-Ⅱ算法的乙烯裂解炉操作优化

现有的乙烯裂解炉优化通常只针对两个目标函数即产物乙烯和丙烯的收率，并且采用遗传算法的收敛效果一般，故提出一种基于改进NSGA-Ⅱ算法来研究一个多目标运行的解决方案，以此来解决乙烯裂解炉的固定周期操作优化问题，即在增大产物乙烯和丙烯收率的同时减少原料以及蒸汽流量来提高整体运行状况。把具体问题量化为数学模型，分析了原料气烃比、原料流量、出口温度对乙烯和丙烯收率的影响。实验结果表明，相较于原有操作条件，提出的优化方案具有良好的可行性。     

热处理工艺对30MnCrNiMo高强钢组织与性能的影响

借助全自动淬火膨胀仪测定钢的Ac₁、Ac₃相变点,通过对试验钢进行淬火+亚温淬火+回火热处理和淬火+回火热处理,研究了两种热处理工艺下30MnCrNiMo高强钢的组织与性能。结果表明:30MnCrNiMo高强钢的Ac₁、Ac₃相变点分别为653、807 ℃。采用淬火+亚温淬火+回火的热处理工艺所获得的马氏体和铁素体复相组织比直接淬火+回火得到的全马氏体组织更为细小、均匀,试验钢的屈服强度为1499 MPa,伸长率为14.0%,室温、-40 ℃冲击吸收能量分别为35.5和29.5 J,钢的塑性和冲击性能显著提升,有效改善了30MnCrNiMo高强钢的强韧性能。