Domain reversal and current transport property in BiFeO3 films

The electrical properties and domain reversal in BiFeO₃ ferroelectric films were studied using sandwiched heterostructures and piezoresponse force microscopy. A robust polarization state was observed, combined with a switchable domain pattern and a remanent polarization of approximately 100 μC cm^?2. In addition, domain reversal was explored using scanning probe microscopy. The results show that dipoles could be reversed along the direction of the electric field under a negative tip bias, leading to carrier gathering near the domain walls. The enhanced conductivity near the domain walls was owing to the discontinuous polarization boundary conditions. In addition, typical diode-like current transport properties are sensitive to various temperature conditions, which is attributed to the Schottky barriers at the contact interface. These findings extend the current understanding of domain texture reversal in ferroelectric films and shed light on their potential applications for future ferroelectric random-access memory operations over a wide temperature range.     

Analysis and proposition of limiting current density measurement protocol

Limiting current density at different temperatures, backpressures, and balance gases can be used to separate molecular diffusion resistance, Knudsen diffusion resistance and local transport resistance of membrane electrode assembly (MEA). However, the measurement of limiting current density has no unified protocol. The diverse choices in the literature, either in the control of current or voltage or in the atmosphere like relative humidity and O₂ concentrations, make it difficult to compare the results and identify the true bottleneck hindering the mass transport. In this work, the current-voltage curves obtained by current scanning/stepping and voltage scanning/stepping methods under dilute O₂ of different concentrations and a wide range of relative humidity were measured and analyzed systematically. It is found that the voltage stepping method is superior to the other three ways of control for the reliable determination of the limiting current density. Aided with simultaneous electrochemical impedance spectroscopy measurement, the limiting current density can be determined with pinpoint accuracy. When the limiting current density is just used to qualitatively evaluate different MEA, the voltage scanning method can be used instead for its high time efficiency. The selection of the atmosphere also plays an important role in suppressing the distortion from excessive water and reducing the spurious contribution from proton conduction resistance. It is found that O₂ concentrations at 0.5 vol% and relative humidity at 90% can give the best estimation of O₂ transport resistance in membrane electrode assembly.     

An experimental study of adaptive control for evolutionary algorithms

In this paper, we investigate how adaptive operator selection techniques are able to efficiently manage the balance between exploration and exploitation in an evolutionary algorithm, when solving combinatorial optimization problems. We introduce new high level reactive search strategies based on a generic algorithm's controller that is able to schedule the basic variation operators of the evolutionary algorithm, according to the observed state of the search. Our experiments on SAT instances show that reactive search strategies improve the performance of the solving algorithm.     

A new numerical algorithm to check the observability and bad-data processing ability of the metering scheme

This paper provides a unified approach for the optimization of measurements placements employed for power system online monitoring through state estimation. The proposed methodology, which can be suitable for the mixed measure system, preserves state estimation observability and bad-data processing capability by employing numerical algorithms for observability checking, critical measurements and critical couple identification. First, node injection radix measurements and measurement categories are defined. According to the above definitions, the coefficient matrix can be solved. The analysis on the column vectors of the coefficient matrix can determine each measurement classification. Furthermore, the numbers of each measurement class contains can determine bad-data processing capability. The observability can be checked by the type number of measurements. The proposed method is illustrated with the IEEE39-bus system and the IEEE118-bus system. Results from the case studies are presented to demonstrate that the approach adequately fulfills the desired properties related to observability, bad-data processing, cost, and robustness.     

High-resolution ISAR imaging of fast rotating targets based on pattern-coupled Bayesian strategy for multiple measurement vectors

Very high resolution inverse synthetic aperture radar (ISAR) imaging of fast rotating targets is a complicated task. There may be insufficient pulses or may introduce migration through range cells (MTRC) during the coherent processing interval (CPI) when we use the conventional range Doppler (RD) ISAR technique. With compressed sensing (CS) technique, we can achieve the high-resolution ISAR imaging of a target with limited number of pulses. Sparse representation based method can achieve the super resolution ISAR imaging of a target with a short CPI, during which the target rotates only a small angle and the range migration of the scatterers is small. However, traditional CS-based ISAR imaging method generally faced with the problem of basis mismatch, which may degrade the ISAR image. To achieve the high resolution ISAR imaging of fast rotating targets, this paper proposed a pattern-coupled sparse Bayesian learning method for multiple measurement vectors, i.e. the PC-MSBL algorithm. A multi-channel pattern-coupled hierarchical Gaussian prior is proposed to model the pattern dependencies among neighboring range cells and correct the MTRC problem. The expectation-maximization (EM) algorithm is used to infer the maximum a posterior (MAP) estimate of the hyperparameters. Simulation results validate the effectiveness and superiority of the proposed algorithm.     

Models for solar radiation prediction based on different measurement sites

The modeling of solar radiation for forecasting its availability is a key tool for managing photovoltaic (PV) plants and, hence, is of primary importance for energy production in a smart grid scenario. However, the variability of the weather phenomena is an unavoidable obstacle in the prediction of the energy produced by the solar radiation conversion. The use of the data collected in the past can be useful to capture the daily and seasonal variability, while measurement of the recent past can be exploited to provide a short term prediction. It is well known that a good measurement of the solar radiation requires not only a high class radiometer, but also a correct management of the instrument. In order to reduce the cost related to the management of the monitoring apparatus, a solution could be to evaluate the PV plant performance using data collected by public weather station installed near the plant. In this paper, two experiments are conducted. In the first, the plausibility of the short term prediction of the solar radiation, based on data collected in the near past on the same site is investigated. In the second experiment, the same prediction is operated using data collected by a public weather station located at ten kilometers from the solar plant. Several prediction techniques belonging from both computational intelligence and statistical fields have been challenged in this task. In particular, Support Vector Machine for Regression, Extreme Learning Machine and Autoregressive models have been used and compared with the persistence and the k-NN predictors. The prediction accuracy achieved in the two experimental conditions are then compared and the results are discussed.     

基于射频技术的无刷同步电机励磁电流的检测

无刷同步电机的励磁系统对励磁电流的测量是制约该励磁方式发展的一大障碍。设计了一个射频系统可以用来解决同步电机的励磁电流的测量问题。该系统可以方便地检测到同步电机励磁机的整流二极管的工作状态并且可以动态地显示励磁电流，极大地方便了运行人员做出判断，而且结构简单、方便实用。     

复合材料层合曲梁分层问题的解析解法

根据叠加原理将含有分层的复合材料层合曲梁在横向载荷作用下的受力状态分解为在面受力状态与出面受力状态,再将出面受力状态分解为无分层曲梁受横向载荷状态与含分层曲梁承受附加剪切载荷状态。将分层问题归结为在附加剪切载荷状态中,层合梁附加位移与附加应力的分析,并据此建立了一个简单的力学模型。最后得到了由分层引起的附加位移与应力的解析解答,并用能量释放率方法确定了应力强度因子。     

大型结构试验和结构监测中的数据采集系统

结构试验和结构监测正在向大型化和复杂化发展,与之配套的数据采集系统也要能满足它们不断增长的需求。清华大学土木工程系开发了适用于土木工程结构试验与监测的集成数据采集系统 IMPDAS,它具有测点多,速度快,功能全等优点。它的任务,不仅仅是记录数据,而是集成并且管理数据,将各种数据信息有条理,有重点地反馈给试验者。本文将讨论计算机在大型结构试验和结构监测的数据采集及数据处理分析等方面的应用。     

服务质量测量技术及其应用

文章在概述服务质量测量技术的基础上，介绍了服务质量测量技术的服务质量性能评估、网络推测、网络定位等应用，并给出了服务质量测量的一般数学模型。