基于灰色关联度的微孔端面机械密封开启力共性影响参数分析

目前微孔端面机械密封采用的几何参数繁多,缺乏明确物理意义。为找出跨孔型的共性几何参数,基于Fluent多相流空化模型,针对矩形孔、菱形孔、椭圆孔端面机械密封,建立密封间隙流体的三维数值计算模型,计算得到144条开启力数据;在分析开启力和几何尺寸之间的关系、额外开启力产生机制的基础上,提出等效长度和等效宽度2个具有物理意义的几何参数;采用灰色关联度分析法,分析和验证等效长度、等效宽度、方向角、面积比对开启力的影响,发现4个因素对3种微孔密封的间隙流体开启力都有影响,但等效长度与等效宽度的影响较方向角、面积比大。     

Rheology of crosslinked entangled polymers: Shear stiffening in oscillatory shear

Polyborosiloxane (PBS) was synthesized from boric acid and hydroxyl-terminated polydimethylsiloxane (PDMS). The oscillatory shear behavior of PBS formed by PDMS with different molecular weight was studied. The relaxation time of PBS was calculated by Doi-Edwards model. Finally, the shear-stiffening mechanism of reversibly crosslinked entangled polymer was obtained. Shear stiffening occurs at lower shear frequencies, which is mainly due to crosslinking bonds and friction between molecules hindering the movement of molecules. The increase in storage modulus at high frequencies is attributed to the resistance caused by entanglement in the stretching process of molecular chains. In addition, the molecular weight is greater and the degree of shear stiffening is higher. Such a conclusion is useful to further study the application of shear stiffening. © 2019 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2020 , 137, 48421.     

电子束诱导沉积钴微米线及其铁磁性

通过电子束诱导沉积的方法制备了钴(Co)微米线,并利用扫描电子显微镜(SEM)、原子力/磁力显微镜(AFM/MFM)以及物性测量系统(PPMS)等手段对Co微米线的沉积尺寸、微结构、铁磁性和电学性质进行了测试和分析。研究结果表明:Co微米线轮廓清晰、均匀性好。在不同的沉积条件下,微米线的实际长度与设定长度基本一致;实际宽度数据呈类梯形分布,半高宽是设定值的2~10倍;实际厚度低于设定厚度的60%。沉积电流对Co微米线的铁磁特性有重要影响。当沉积电流大于0.5 nA时,样品呈现出良好的铁磁特性。另外,电学性能测试结果显示Co微米线呈现绝缘特性。成功制备了室温铁磁绝缘Co微米线,这将有助于深入开展微纳尺度的结构与器件的研究和应用。     

Upscaled DEM-CFD model for vibrated fluidized bed based on particle-scale similarities

Simulation based on discrete element method (DEM) coupled with computational fluid dynamics (CFD), coupled DEM-CFD, is a powerful tool for investigating the details of dense particle–fluid interaction problems such as in fluidized beds and pneumatic conveyers. The addition of a mechanical vibration to a system can drastically alter the particle and fluid flows; however, their detailed mechanisms are not well understood. In this study, a DEM-CFD model based on a non-inertial frame of reference is developed to achieve a better understanding of the influence of vibration in a vibrated fluidized bed. Because the high computational cost of DEM-CFD calculations is still a major problem, an upscaled coarse-graining model is also employed. To realize similar behaviors with enlarged model particles, non-dimensional parameters at the particle scale were deduced from the governing equations. The suitability and limitations of the proposed model were examined for a density segregation problem of a binary system. To reduce the computational costs, we show that the ratio between the bed width and model particle size can be reduced to a minimum value of 100; to obtain similar segregation behaviors, the ratio between the bed height and model particle size is considered unchanged.     

附加外场力对锌锅表层锌液流动和锌渣分布的影响

实测了热镀锌锌锅表层锌液的流速,并分析了锌锅浮渣的分布特点,提出了一种在锌锅锌液上方主动加载外场力作用以驱动锌液流动进而改变锌渣分布的新方法,称为锌渣流动管理方法(DFMS-Dross Flowing Management System)。通过源力加载的方式修正了流体动量守恒方程,建立了锌液流场数值计算模型,模拟了不同外场力加载布局下锌锅表层锌液的流场。结果表明,附加外场力作用可有效促进锌锅表层锌液的切向流动,最大切向流速可达0.8 m/s;表层锌液的切向流动可拖动锌渣跟随流动,进而改变锌渣分布,促进锌锅排渣,证实了DFMS的有效性。模拟结果还表明,锌锅表层锌液的切向流速受外场力加载时间的影响较小,而随加载外场力的增大而增大,但加载外场力的大小对100~200 mm深锌液的流速影响较小。最后,通过定义锌锅表层锌液的排渣时间因子讨论了不同外场力加载方式的排渣效率。     

Sensitivity analysis of Johnson-Cook material parameters on adiabatic shear in different directions

ABSTRACT

This study investigates the effects of strain, strain rates, and forming directions (RD-rolling direction, TD-transverse direction, and ND-normal direction) on adiabatic shear, via dynamic impact compression tests using the Split Hopkinson Pressure Bar (SHPB) apparatus. A modified Johnson-Cook (J-C) constitutive model is proposed, which used to analyse the influence of the constitutive parameters on the sensitivity of adiabatic shear, employing a finite element software. The different sensitivities of adiabatic shear under different directions are explained by combining microscopic analysis and results from mechanical responses. The results show that the sensitivity of adiabatic shear can be related to the time of stress collapse in the following trend: ND?>?TD?>?RD; the sensitivities of these constitutive parameters on adiabatic shear are calculated and compared.     

Images of a First‐Order Spin‐Reorientation Phase Transition in a Metallic Kagome Ferromagnet

First‐order phase transitions, where one phase replaces another by virtue of a simple crossing of free energies, are best known between solids, liquids, and vapors, but they also occur in a wide range of other contexts, including even elemental magnets. The key challenges are to establish whether a phase transition is indeed first order, and then to determine how the new phase emerges because this will determine thermodynamic and electronic properties. Here it is shown that both challenges are met for the spin reorientation transition in the topological metallic ferromagnet Fe₃Sn₂. The magnetometry and variable temperature magnetic force microscopy experiments reveal that, analogous to the liquid–gas transition in the temperature–pressure plane, this transition is centered on a first‐order line terminating in a critical end point in the field‐temperature plane. The nucleation and growth associated with the transition is directly imaged, indicating that the new phase emerges at the most convoluted magnetic domain walls for the high temperature phase and then moves to self‐organize at the domain centers of the high temperature phase. The dense domain patterns and phase coexistence imply a complex inhomogenous electronic structure, which can yield anomalous contributions to the electrical conductivity.     

Quantitative investigation of electromechanical coupling of potassium sodium niobate-based thin films

High-performance environment-friendly piezoelectric potassium sodium niobate (KNN)-based thin films have been emerged as promising lead-free candidates, while their substrate-dependent piezoelectricity faces the lack of high-quality information due to restraints in measurements. Although piezoresponse force microscopy (PFM) is a potential measuring tool, still its regular mode is not considered as a reliable characterization method for quantification. After combining machine-learning enabled analysis using PFM datasets, it is possible to measure piezoelectric properties quantitatively. Here we utilized advanced PFM technology empowered by machine learning to measure and compare the piezoelectricity of KNN based thin films on different substrates. The results provide a better understanding of the relationship between structures and piezoelectric properties of the thin films.     

Prediction and sensitivity analysis of CNTs-modified asphalt’s adhesion force using a radial basis neural network model

Abstract

The expected longer service life of modified asphalt can be jeopardized by different environmental factors, such as moisture, oxidation, etc. which affect the desired properties by altering the adhesive property. An insight into knowledge of the adhesive property of the asphalt can help in providing more durable asphalt pavement. The study attempted to develop different models of adhesive properties of polymers and carbon nanotubes (CNTs) modified asphalt binders. The polymer-CNT modified asphalt is processed to prepare different types of samples, by simulating the damage due to moisture and oxidization, following the corresponding standard method. An Atomic Force Microscopy (AFM) was employed to assess the nanoscale adhesion force of the tested samples following the existing functional group in asphalt. Finally, the study has developed Radial Basis Function Neural Network (RBFNN) as a function of different parameters including; asphalt chemistry (i.e. AFM tip type and constant), type and percentages of polymers and CNTs and different environmental exposures (oxidation, moisture, etc.) to predict the nano adhesion force of asphalt. It is observed that the adhesive property of the Styrene–Butadiene modified asphalt is more consistent compared to the Styrene–Butadiene–Styrene modified asphalt, while the presence of Single-Wall Nanotubes (SWNT) is observed to affect the adhesive properties of asphalt significantly as compared to Multi-Wall Nanotubes (MWNT). The higher accuracy level of RBFNN model also indicates that the functional group (tip-type) adding with the percentages and types of polymers and CNTs significantly affect the adhesive properties of asphalt.