The influence of sulphate-reducing bacteria biofilm on the corrosion of stainless steel AISI 316

This work investigates microbially-influenced corrosion (MIC) of stainless steel AISI 316 by two sulphate-reducing bacteria, Desulfovibrio desulfuricans and a local marine isolate. The biofilm and pit morphology that developed with time were analyzed using atomic force microscopy (AFM). Electrochemical impedance spectroscopy (EIS) results were interpreted with an equivalent circuit to model the physicoelectric characteristics of the electrode/biofilm/solution interface. D. desulfuricans formed one biofilm layer on the metal surface, while the marine isolate formed two layers: a biofilm layer and a ferrous sulfide deposit layer. AFM images corroborated results from the EIS modeling which showed biofilm attachment and subsequent detachment over time.     

Probabilistic simulation of fire scenarios

A risk analysis tool is developed for computation of the distributions of fire model output variables. The tool, called Probabilistic Fire Simulator (PFS), combines Monte Carlo simulation and CFAST, a two-zone fire model. In this work, the tool is used to estimate the failure probability of redundant cables in a cable tunnel fire, and the failure and smoke filling probabilities in an electronics room during an electronics cabinet fire. Sensitivity of the output variables to the input variables is calculated in terms of the rank order correlations. The use of the rank order correlations allows the user to identify both modelling parameters and actual facility properties that have the most influence on the results. Various steps of the simulation process, i.e. data collection, generation of the input distributions, modelling assumptions, definition of the output variables and the actual simulation, are described.     

基于动态Copula的风光联合出力建模及动态相关性分析

准确描述风力发电和光伏发电的动态相关性及联合出力的波动性,对风光互补系统的出力预测和经济调度具有重要意义。针对现行静态相关系数无法准确描述风光出力相依关系的问题,研究了风光出力的动态相关性,提出了基于动态Copula函数的风光联合出力模型构建方法。结合实测数据建立了8组动态与静态的风光联合出力Copula模型,用动态相关系数描述风光出力的相关性。运用拟合优度检验方法验证了动态Copula模型对比其静态模型的优越性,选出最优模型。最后将该模型应用在数据驱动的风光联合系统中,验证了其合理性与正确性。     

Analysis of class E amplifier with both linear and nonlinear shunt capacitance at any duty cycle,grading coefficient and supply modulation

This work studies the effects of the drain pn capacitance grading coefficient, duty cycle and supply modulation on the operation of class E amplifier. The class E operation analysis with a combination of nonlinear and linear output capacitances is revisited and duty cycle is added to the equations to allow further investigations for optimum class E circuit tuning. The presented analysis method can be used for synthesis as well, where necessary load components are calculated for a transistor with a specific grading coefficient both in the output capacitance and in the nonlinear feedback capacitance. Further, the grading coefficient of the nonlinear output capacitance is varied in the paper while investigating the changes in normalized peak voltages and harmonics. Drain efficiency, supply-to-amplitude modulation (V _dd /AM) and supply-to-phase modulation (V _dd /PM) are studied. It is shown that by varying the device duty cycle, one can scale the optimum load and the level of peak voltages over the switching device. Also, the choice of grading coefficient affects the drain efficiency, V _dd /AM and V _dd /PM behaviour of the class E amplifier. Last, a case study about increasing the efficiency of a class E amplifier with hyperabrupt output junction capacitance is shown.     

Determining a value for mixing: Mixing degree

We have developed a new method to determine the degree of mixing for a given system. The method assumes knowledge of the locations of all or some studied particles both before and after mixing. The method is scalable and gives comparable results for systems with varying shapes and sizes of the mixing space. It can also be used to determine the mixing of only a part of the space studied. Due to the information needed, the method is best suited for simulations, but in some cases it might be possible to use it with real laboratory experiments.     

Effects of measurement errors in predictor selection of linear regression model

Measurement errors may affect the predictor selection of the linear regression model. These effects are studied using a measurement framework, where the variances of the measurement errors can be estimated without setting too restrictive assumptions about the measurement model. In this approach, the problem of measurement is solved in a reduced true score space, where the latent true score is multidimensional, but its dimension is smaller than the number of the measurable variables. Various measurement scales are then created to be used as predictors in the regression model. The stability of the predictor selection as well as the estimated predicted validity and the reliability of the prediction scales is examined by Monte Carlo simulations. Varying the magnitude of the measurement error variance four sets of predictors are compared: all variables, a stepwise selection, factor sums, and factor scores. The results indicate that the factor scores offer a stable method for predictor selection, whereas the other alternatives tend to give biased results leading more or less to capitalizing on chance.     

CFD Simulations of Fire Propagation in Horizontal Cable Trays Using a Pyrolysis Model with Stochastically Determined Geometry

In this paper, a pyrolysis model for a PVC cable is constructed using results from thermogravimetric analysis, microscale combustion calorimeter and cone calorimeter experiments. The pyrolysis model is used to simulate fire propagation in horizontal cable trays. The simulated arrangement corresponds to a cable tray fire experiment from OECD PRISME 2 project. As laying the cables loosely along the horizontal trays is a random process, a novel stochastic method is developed for making the simplified cable tray geometries for the computational fluid dynamics model. In addition, as the simplified cable tray geometry has significantly smaller surface area than a real tray full of cables, the surface area was parametrically adjusted. In contrast to most of the earlier published numerical approaches for simulating cable tray fires, the presented approach does not use empirical correlations for predicting fire propagation and does not require any results from full-scale experiments for calibrating the model. The simulation results are compared to experimental results in terms of heat release rate, mass loss, tray ignition times and lateral flame spread rates. The maximum heat release rate was overpredicted by 8% on average.

     

高校课表编排质量问题研究

课表编排是一门学问,是一门艺术．科学地编排课表,对提高教学质量极为有利．从课表编排存在的问题以及课表编排基本流程着手进行分析研究,得出课表编排所需遵循的原则;贯彻课表编排“以人为本”的管理思想;有利于优化学校教学资源、提高教师教学效果及学生的学习效率,实现高校教学管理的“高标准、精细化”．     

计及预测误差动态相关性的多风电场联合出力不确定性模型

为实现对多风电场联合出力不确定性的精细化建模,提出了计及预测误差动态相关性的多风电场联合出力不确定性建模方法。首先,分析了同区域风电场的出力及出力预测误差动态相关性特征。进一步,针对此特征,引入高维动态藤Copula理论,建立了多风电场预测出力及预测误差的联合分布模型。最终,将以上模型与基于Copula函数的离散卷积法相结合,建立了计及预测误差动态相关性的多风电场联合出力不确定性模型,并以置信区间对多风电场联合出力不确定性进行了离散化表征。仿真结果表明,对比其他模型,所提模型拟合精度更高,拟合过程与预测方法解耦,灵活性更强。     

基于边界特征的高压直流输电长线路故障判别方法

分析了高压直流输电长线路的高频信号衰减作用对目前基于线路边界保护原理的影响。研究了边界的频率特性以及平波电抗器对电流变化率的抑制作用,进而提出了由单端特征频率电流构造的直流线路故障判别方法。在所提出的直流保护方案中,使用特征谐波电流幅值构造启动判据,同时使用特征谐波电流变化量构造保护判据,算法简便且更加充分地利用了基于线路边界的暂态特征。在PSCAD/EMTDC中搭建了双极24脉动直流输电系统模型并进行了仿真分析。结果表明,该判据能准确地区分区内外故障并进行故障选极,受过渡电阻和长线路的影响很小,可以实现全线速动。