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。     

Dynamics and workspace analysis of a multi-robot collaborative towing system with floating base

Journal of Mechanical Science and Technology - A multi-robot collaborative towing system fixed on floating base for high load marine work was established in this paper, and its dynamics and...     

Polymers dynamics of the nonfluoro,nano-brush repelling agent with self-stratifying property in water-based coatings

While perfluoroalkyl acids (PFAAs), also known as C8s, are used extensively in textile repellent coatings, concerns have arisen for their carcinogenicity and hazardous effects on the environment. In this study, a novel water-based, nonfluoro, and nanobrush textile repelling agent was prepared by conventional sol–gel chemistry using amorphous fumed silica and n-octyltriethoxysilane as the starting materials. Minimal interaction between the designed repelling agent and marketed water-based resins was confirmed using linear viscosity region (LVR) analysis and asymmetric-flow field-flow fractionation (AF4), suggesting the self-stratification potential of the repelling agent. More specifically, the repelling agent exhibited excellent compatibility and self-stratifying ability with a force-emulsified acrylic-based resin, affording a water contact angle of 104.3° when incorporated at 7% solid content. Performance tests carried out on thermoplastic polyurethane (TPU) revealed excellent adhesion (100/100) of a final formulation, and a significant increase in water contact angle from 80.1° to 103.8° after treatment. In addition, the fouling area after the removal of a submerged sample from a mixture of slurry, polymer, and oil decreased from 48 to 1% when the repelling agent was added. Moreover, the sludge-fouling property remained unchanged after 1000 cycles of abrasion. These findings demonstrate the potential of the described nonfluoro, nanobrush repelling agent as an environmentally safe alternative for use with commercial resins, in turn realizing a fully water-based hydrophobic coating. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2019 , 136, 48003.     

攀西钒钛磁铁矿尾矿制备储水泡沫陶瓷的研究

以攀西钒钛磁铁尾矿和废玻璃为主要原料通过高温烧结法制备储水泡沫陶瓷，研究原料配比和发泡剂（SiC）添加量对材料性能的影响。结果表明:随着钒钛磁铁矿尾矿含量的增加，材料的体积密度及抗压强度逐渐增大，平均气孔孔径逐渐减小；当尾矿添加量为50 wt%，材料的体积吸水率出现极值。当SiC添加量为0.3 wt%，材料内部气孔分布均匀，平均孔径约为2.93 mm。最终以50.0 wt%的钒钛磁铁矿尾矿和50.0 wt%的废玻璃为原料，外加3.0 wt%的石英，0.3 wt%的SiC，3.0 wt%的Na3PO4，在1040℃下制得性能最优的储水泡沫陶瓷，材料的体积密度为0.26 g/cm-3、体积吸水率为56.5%和抗压强度为0.68 MPa。采用SEM、XRD等检测手段研究材料的微观形貌及物相组成，结果表明储水泡沫陶瓷内部由三维立体结构组成，有利于储存水分；材料主要物相包括硅灰石、长石、透辉石和钛铁矿。      

Model Selection for Unsupervised Learning of Visual Context

This study addresses the problem of choosing the most suitable probabilistic model selection criterion for unsupervised learning of visual context of a dynamic scene using mixture models. A rectified Bayesian Information Criterion (BICr) and a Completed Likelihood Akaike’s Information Criterion (CL-AIC) are formulated to estimate the optimal model order (complexity) for a given visual scene. Both criteria are designed to overcome poor model selection by existing popular criteria when the data sample size varies from small to large and the true mixture distribution kernel functions differ from the assumed ones. Extensive experiments on learning visual context for dynamic scene modelling are carried out to demonstrate the effectiveness of BICr and CL-AIC, compared to that of existing popular model selection criteria including BIC, AIC and Integrated Completed Likelihood (ICL). Our study suggests that for learning visual context using a mixture model, BICr is the most appropriate criterion given sparse data, while CL-AIC should be chosen given moderate or large data sample sizes.     

离心泵并联运行工况点的数值求解

建立了求解多台不同型号离心泵并联运行工况点的数学模型,给出了用数值计算中的“二分法”求解该模型的方法,并附有用Exce l计算的实例。