Cu2O-CuAlO2-Cu基金属陶瓷导电性能研究

通过热压技术制备Cu2O-10CuAlO2-xCu金属陶瓷材料，并对其导电性能进行了研究。结果表明，Cu2O-10CuAlO2-xCu在Cu含量超过15wt．％后呈金属导电性。材料的微观结构观察及物理性能测试表明，金属陶瓷材料的电导率不仅取决于材料的金属相含量，还取决于金属相颗粒尺寸和孔隙率的大小。材料中金属相的颗粒尺寸取决于热压工艺参数，随着热压温度的升高而增大，但随热压压力的升高而减小。     

Seepage safety monitoring model for an earth rock dam under influence of high-impact typhoons based on particle swarm optimization algorithm

Extreme hydrological events induced by typhoons in reservoir areas have presented severe challenges to the safe operation of hydraulic structures. Based on analysis of the seepage characteristics of an earth rock dam, a novel seepage safety monitoring model was constructed in this study. The nonlinear influence processes of the antecedent reservoir water level and rainfall were assumed to follow normal distributions. The particle swarm optimization (PSO) algorithm was used to optimize the model parameters so as to raise the fitting accuracy. In addition, a mutation factor was introduced to simulate the sudden increase in the piezometric level induced by short-duration heavy rainfall and the possible historical extreme reservoir water level during a typhoon. In order to verify the efficacy of this model, the earth rock dam of the Siminghu Reservoir was used as an example. The piezometric level at the SW1-2 measuring point during Typhoon Fitow in 2013 was fitted with the present model, and a corresponding theoretical expression was established. Comparison of fitting results of the piezometric level obtained from the present statistical model and traditional statistical model with monitored values during the typhoon shows that the present model has a higher fitting accuracy and can simulate the uprush feature of the seepage pressure during the typhoon perfectly.     

针铁矿法沉铁过程亚铁离子浓度预测

针对针铁矿法沉铁过程出口亚铁离子浓度离线化验获得,存在很大滞后性,难以实现沉铁过程实时控制的问题,研究反应器出口亚铁离子浓度在线预测方法.本文在分析沉铁过程化学反应机理的基础上,考虑铜离子对反应过程的影响,结合连续搅拌反应器（Continuous stirred tank reactor,CSTR）特性,建立了针铁矿法沉铁过程的机理模型,并提出了基于信息交换的双粒子群搜索算法（Double particle swarm optimization,DPSO）优化选择机理模型的参数,构建基于最小二乘支持向量机（Least squares support vector machine,LS-SVM）的机理模型输出误差的补偿模型,采用并联补集成方式建立了亚铁离子浓度的集成预测模型.工业现场数据验证了所建模型能有效地反映亚铁离子浓度的变化趋势,为针铁矿法沉铁过程的优化控制奠定了基础.     

Aqueous heterophase polymerization of styrene—a study by means of multi-angle laser light scattering

An online multi-angle laser light scattering study of ab initio surfactant-free styrene emulsion polymerization reveals unexpected results regarding the development of the dispersity during the whole reaction starting from mixing styrene and water at reaction temperature. The experimentally observed change in the dispersity, which is an indirect measure of the average characteristic size of the colloidal objects, allows the identification of three characteristic intervals. During interval A the equilibration of styrene in water is characterized by the formation of styrene domains, which increase in number and size until an equilibrium state is reached. This means that there is virtually no homogeneous/molecular styrene in water solution but rather nanodroplets of about 200 nm in diameter (assuming spherical shape) are formed. During interval B, after initiation of the polymerization and particle formation, the dispersity increases again as the average size decreases and the number of scattering objects increases. The polymer particles suck up the monomer from the monomer nanodroplets, which leads to the disappearance of the nanodroplets and to a decrease in the average size. During interval C the average size increases again due to the predominantly growth of the polystyrene particles.     

Pickup (critical) velocity of particles

This work presents experimental results on pickup velocity (critical velocity) measurements for a variety of particulate solids. The present experiments together with previously published experiments of a number of researchers encompass about 100 measurements of 24 materials for a wide range of particle sizes, shapes and densities. Based on the experimental results, three zones are defined by establishing simple relationships between the Reynolds and Archimedes numbers. The empirical relationships were further modified by taking into account the pipe diameter and particle shape (sphericity). The three-zone model was shown to reasonably correlate to Geldart's classification groups.     

A survey on nature-inspired optimization algorithms with fuzzy logic for dynamic parameter adaptation

Metaheuristic optimization algorithms have become a popular choice for solving complex problems which are otherwise difficult to solve by traditional methods. However, these methods have the problem of the parameter adaptation and many researchers have proposed modifications using fuzzy logic to solve this problem and obtain better results than the original methods. In this study a comprehensive review is made of the optimization techniques in which fuzzy logic is used to dynamically adapt some important parameters in these methods. In this paper, the survey mainly covers the optimization methods of Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), and Ant Colony Optimization (ACO), which in the last years have been used with fuzzy logic to improve the performance of the optimization methods.     

Particle filtering for sensor fault diagnosis and identification in nonlinear plants

We propose a novel method for sensor monitoring and fault-tolerant estimation in systems described by general stochastic nonlinear and/or non-Gaussian state-space models. Faults are defined as abruptly occurring calibration errors, causing the sensor readings to be biased or scaled. Actuators and the process itself are assumed to be fault free. The main novelty of the work is an adaptive particle filter, whose configuration changes in order to diagnose sensor faults and to compensate for their effects. The presence, type and magnitude of sensor faults are determined through hypothesis testing and maximum likelihood estimation, based on the difference between the measurements and the particle filter estimates. The validity of the proposed approach was demonstrated through simulations on a drum-boiler model, although its effectiveness is not conditioned on any particular feature of the considered example.     

免疫粒子群算法在城市有轨电车运行调整中的应用研究

针对城市有轨电车运行环境复杂、列车运行调整存在众多约束条件、求解难度大等问题,提出虚站台概念,在此基础上建立了优化的列车运行调整模型.引入免疫系统中的免疫记忆特性和抗体浓度抑制思想,采用免疫粒子群算法对此模型进行求解,并以海珠区环岛新型城市有轨电车实验段数据进行仿真.结果表明,在引入虚站台概念基础上,采用免疫粒子群算法能够有效地解决城市有轨电车运行调整问题,并且其优化能力优于遗传算法.     

基于改进的简化粒子群聚类算法

针对粒子群算法后期收敛速度慢、易陷入局部极值的缺点,提出一种基于粒密度和最大距离积法的简 化粒子群聚类算法.通过采用线性递减与随机分布相结合的惯性权重策略、添加极值扰动算子、优化粒子个体最优位置,使粒子群算法能够快速收敛于全局最优.再把改进后的粒子群算法与K-means算法相结合,解决K-means算法因随机初始聚类中心而导致聚类效果差、不稳定等问题.通过实验分析,该算法的聚类结果准确率更高、收敛速度更快、稳定性更强.     

无机物——聚醋酸乙烯复合乳液粒子结构及主要性能

本文对均聚醋酸乙烯乳液及其与无机物的混合物,无机物——聚醋酸乙烯复合乳液的粒子结构进行了比较,阐述了复合乳液的主要性能。