极端工况双矩形腔静压推力轴承动态特性

静压推力轴承动态特性受润滑油黏度、油膜厚度和油腔面积等因素影响, 极端工况运行过程中经常承受阶跃载荷或正弦载荷作用, 突加载荷将导致静压推力轴承动态特性改变, 表现为轴承的抗冲击能力和恢复平衡所需时间的变化. 为获得高速重载微间隙极端工况条件下双矩形腔静压推力轴承动态特性, 分别在不同油膜厚度、不同润滑油黏度以及不同油腔尺寸条件下对双矩形腔静压推力轴承的动态性能进行理论分析, 探讨了阶跃载荷作用下润滑油黏度、油膜厚度和油腔面积对轴承动态性能的影响, 揭示了油膜动态变化规律, 探究了正弦载荷作用下双矩形腔静压推力轴承的稳定性. 结果表明: 润滑油黏度、油膜厚度和油腔尺寸变化对其动态性能有很大的影响. 润滑油黏度越大、油膜厚度越小、油腔面积越大突加载荷作用下润滑油膜抵抗冲击的能力越强, 旋转工作台受到突加外力作用下恢复至平衡状态所用时间越短. 双矩形腔静压推力轴承油膜具有较大的阻尼系数, 轴承具有极强的抵抗正弦加载作用的能力      

Effects of particle size and concentration on bubble coalescence and froth formation in a slurry bubble column

A new approach for simulating the formation of a froth layer in a slurry bubble column is proposed. Froth is considered a separate phase, comprised of a mixture of gas, liquid, and solid. The simulation was carried out using commercial flow simulation software (FIRE v2014) for particle sizes of 60–150 μm at solid concentrations of 0–40 vol%, and superficial gas velocities of 0.02–0.034 m/s in a slurry bubble column with a hydraulic diameter of 0.2 m and height of 1.2 m. Modelling calculations were conducted using a Eulerian–Eulerian multiphase approach with k–ε turbulence. The population balance equations for bubble breakup, bubble coalescence rate, and the interfacial exchange of mass and momentum were included in the computational fluid dynamics code by writing subroutines in Fortran to track the number density of different bubble sizes. Flow structure, radial gas holdup, and Sauter mean bubble diameter distributions at different column heights were predicted in the pulp zone, while froth volume fraction and density were predicted in the froth zone. The model was validated using available experimental data, and the predicted and experimental results showed reasonable agreement. To demonstrate the effect of increasing solid concentration on the coalescence rate, a solid-effect multiplier in the coalescence efficiency equation was used. The solid-effect multiplier decreased with increasing slurry concentration, causing an increase in bubble coalescence efficiency. A slight decrease in the coalescence efficiency was also observed owing to increasing particle size, which led to a decrease in Sauter mean bubble diameter. The froth volume fraction increased with solid concentration. These results provide an improved understanding of the dynamics of slurry bubble reactors in the presence of hydrophilic particles.     

Multistrain edge‐based compartmental model on networks

Multistrain diseases, which are infected through individual contacts, pose severe public health threat nowadays. In this paper, we build competitive and mutative two‐strain edge‐based compartmental models using probability generation function (PGF) and pair approximation (PA). Both of them are ordinary differential equations. Their basic reproduction numbers and final size formulas are explicitly derived. We show that the formula gives a unique positive final epidemic size when the reproduction number is larger than unity. We further consider competitive and mutative multistrain diseases spreading models and compute their basic reproduction numbers. We perform numerical simulations that show some dynamical properties of the competitive and mutative two‐strain models.     

Physics-based plasticity model incorporating microstructure changes for severe plastic deformation

During machining processes, materials undergo severe deformations that lead to different behavior than in the case of slow deformation. The microstructure changes, as a consequence, affect the materials properties and therefore influence the functionality of the component. Developing material models capable of capturing such changes is therefore critical to better understand the interaction process–materials. In this paper, we introduce a new physics model associating Mechanical Threshold Stress (MTS) with Dislocation Density (DD) models. The modeling and the experimental results of a series of large strain experiments on polycrystalline copper (OFHC) involving sequences of shear deformation and strain rate (varying from quasi-static to dynamic) are very similar to those observed in processes such as machining. The Kocks–Mecking model, using the mechanical threshold stress as an internal state variable, correlates well with experimental results and strain rate jump experiments. This model was compared to the well-known Johnson–Cook model that showed some shortcomings in capturing the stain jump. The results show a high effect of rate sensitivity of strain hardening at large strains. Coupling the mechanical threshold stress dislocation density (MTS–DD), material models were implemented in the Abaqus/Explicit FE code. The model shows potentialities in predicting an increase in dislocation density and a reduction in cell size. It could ideally be used in the modeling of machining processes.     

Ensemble-SISPLS近红外光谱变量选择方法

近红外光谱具有高维小样本的特点，变量选择是提高定量分析模型稳健性和可解释性的一种有效方法。确定独立筛选（SIS）是一种基于边际相关性的超高维数据变量选择方法，广泛用于基因微阵列数据的变量选择。SIS具有将数据维度降低至样本大小规模的能力，其降维能力与LASSO相当，在相当宽泛的近似条件下，由于具有安全筛选性质，所有重要变量被保留的概率趋于1。基于确定独立筛选偏最小二乘（SIS-SPLS）的变量选择是一种迭代式的SIS变量选择方法，首先利用SIS方法完成光谱重要变量的初选；然后根据重要变量的边际相关性大小进行逐步前向选择：建立偏最小二乘回归模型，依据贝叶斯信息准则（BIC）确定最终的变量选择结果。SIS-SPLS以逐步前向选择的方式实现对重要变量的增量式筛选，随着潜变量个数的增加及因变量残差的逐步减小，SIS-SPLS方法选择的变量个数将趋于稳定。然而仅以边际相关性对变量重要性进行评价，当光谱变量个数远大于样本数时，该方法也存在选择的变量过多、变量选择结果不够稳健等问题。为进一步提高小样本情况下变量选择的稳健性，将集成学习引入SIS-SPLS方法之中，提出了一种集成SIS-SPLS变量选择方法（Ensemble-SISPLS）。该方法首先对校正集样本进行自助重采样，对采样得到的每一个校正子集分别使用SIS-SPLS方法进行变量筛选，通过投票机制并设置频次阈值对所有校正子集的变量选择结果进行集成，选择出现频次大于给定阈值的变量并建立偏最小二乘回归模型，计算5折交叉验证均方根误差。对频次阈值和潜变量个数两个关键参数使用网格搜索法进行优选，根据子模型的交叉验证均方根误差和变量个数对子模型性能进行综合评价，以最优子模型包含的变量作为最终的变量选择结果。分别在Corn数据集和当归数据集上进行变量选择实验，比较Ensemble-SISPLS，SIS-SPLS和UVE-PLS三种变量选择方法的性能。其中当归数据集共77个样本，样本采自甘肃岷县和渭源县，使用Nicolet-6700型近红外光谱仪扫描得到所有样本的近红外光谱并对当归中的阿魏酸含量进行预测。Ensemble-SISPLS方法在Corn数据集上选择的变量个数、RMSEP和决定系数分别为22，0.000 8和0.999 8；SIS-SPLS方法在Corn数据集上选择的变量个数、RMSEP和决定系数分别为97，0.007 3和0.998 8。Ensemble-SISPLS方法在当归数据集上选择的变量个数、RMSEP和决定系数分别为24，0.018 1和0.996 3；SIS-SPLS方法在当归数据集上选择的变量个数、RMSEP和决定系数分别为38，0.022 6和0.994 3。结果表明，该方法进一步提高了变量选择结果的稳健性和预测能力。Ensemble-SISPLS变量选择方法有效结合了SIS-SPLS较强的变量选择能力和集成学习良好的泛化能力，提高了变量选择的稳健性。此外，由于在子模型的预测能力和变量个数之间进行了折中，一定程度上减少了选择变量的个数，提高了模型的可解释性。     

Size and Shape Effect of Gold Nanoparticles in “Far‐Field” Surface Plasmon Resonance

The “far‐field” surface plasmon resonance (FSPR) of metal nanoparticles, which have built a facile way to emission enhancement of red, green, blue, and white with nice reproducibility, has big potential application in solution‐processed organic light‐emitting diodes (OLEDs). According to the theory of the “far‐field” effect, the reflectivity of the metal surface and the phase shift at the reflection play an important role in enhancing ratio, which strongly relate to the size and shape of nanoparticles. In this work, gold nanospheres with different sizes and nanorods are synthesized in order to determine the size and shape effect of FSPR. The results demonstrate that the one with higher reflectivity in a certain range induces a better emission enhancement in the luminous efficiency and the maximum brightness. The nanoparticles with bigger sizes and shape of rods have higher reflectivity, which is consistent with the simulation based on FSPR effect. The phase shifts of different nanoparticles are optimized by the distance between gold nanoparticles and emitters. The metal NPs with a high reflectivity and the applicable phase shift will have big potential for the emission enhancement in OLEDs.