电致变色材料的变色机理及其研究进展

电致变色材料是目前公认的最有发展前途的智能材料之一。简要介绍了无机电致变色材料（如WO3、MoO3、NiO、IrOx等）和有机电致变色材料（如紫罗精、稀土酞花菁、聚苯胺等）这两种不同类型的变色材料及其研究现状，阐述了电致变色现象及其变色机理，并展望了其应用前景和发展方向。     

电致变色材料的变色机理及其研究进展

电致变色材料是目前公认的最有发展前途的智能材料之一.简要介绍了无机电致变色材料(如WO3、MoO3、NiO、IrOx等)和有机电致变色材料(如紫罗精、稀土酞花菁、聚苯胺等)这两种不同类型的变色材料及其研究现状,阐述了电致变色现象及其变色机理,并展望了其应用前景和发展方向.     

电致变色性和智能窗的发展及应用

对电致变色现象及机理、电致变色器件的构成、电致变色使用的材料等方面的国内外研究现状及发展趋势作了介绍和论述。最后对电致变色器件的应用前景作了展望。     

基于智能变色的发射率可调型薄膜研究进展

介绍了基于电致变色和热致变色的可变发射率薄膜及器件的基本原理及目前的研究现状,重点总结了三氧化钨(WO3)、导电高分子(CPs)、钙钛矿型复合氧化物(A1-xBxMO3)、二氧化钒(VO2)等四类典型红外发射率可变材料。最后针对电致变色和热致变色分别提出了存在的具体问题,对我国智能变色发射率可调型薄膜及器件的发展进行了展望。     

全固态电致变色智能窗的研究进展

电致变色材料被认为是最有开发前景的智能材料之一,本文结合本实验室的研究成果,简要介绍了电致变色智能窗的结构及变色原理,着重阐述了WO3电致变色材料和固态电解质的最新研究动态,展望了电致变色材料及其器件的应用前景。     

吩噻嗪衍生物电致变色材料的合成及其性能研究

合成了系列10-N取代的吩噻嗪衍生物(phenothiazine derivatives,PDs),利用氢谱、碳谱、红外光谱等方法对其结构进行表征,并使用电化学工作站和紫外光谱对其电化学性质作了初步研究。组装了以PDs作为阳极电致变色材料,紫罗精作为阴极电致变色材料的新型阴极-阳极复合电致变色器件。当施加2.4V电压时器件阴极材料显示蓝色,而施加反向电压时阳极材料显示为红色,颜色可逆转换且其响应时间250ms,循环次数超过104,可实现寻址。PDs作为阳极材料具有优良的电致变色性能并且廉价环保,是一种令人瞩目的新型电致变色阳极材料。     

氧化钼电致变色材料与器件

电致变色材料具有可逆的颜色转变特性,在智能窗、显示器、防眩后视镜、电子纸、军事伪装等领域应用广泛。相对于其它种类的显示器件,电致变色显示器件具有色彩丰富、对比度高、无视盲角、断电后仍显色等优点。作为一种典型的阴极着色电致变色材料,氧化钼具有响应时间短和着色态更接近于人眼对光线的敏感波段等优点,使得由氧化钼组成的电致变色器件具有重要的研究价值。本文简要介绍了电致变色、电致变色材料与器件的定义及其应用,尤其电致变色技术最近在智能手机上得到了示范应用,表明电致变色技术未来有良好的发展前景。然后,详细综述了氧化钼薄膜的制备、氧化钼的改性、氧化钼电致变色器件的研究进展。最后提出了氧化钼电致变色薄膜与器件当前存在的问题和解决的途径,并对其发展前景进行了展望。     

电致变色材料及应用

电致变色材料在大面积信息显示、无功耗贮存及灵巧调光窗口的应用领域，具有良好的前景。本文介绍了电致变色现象及其特点，并对变色机理、材料与器件的制备，以及应用等方面的研究状况作了评述。     

制备WO3电致变色薄膜的低压反应离子镀工艺研究

在电子束蒸发镀膜的基础上,引入低压反应离子镀工艺制备WO3电致变色薄膜,研究不同氧分压对WO3薄膜电致变色特性的影响,实验结果表明制备时选择工作气体氩气分压为2×10-2 Pa,氧分压为4×10-2 Pa时,薄膜具有最好的电致变色特性和最大的变色范围.进而采用低压反应离子镀工艺成功地实现在塑料基板上制备WO3薄膜,并对其电致变色特性进行了研究.同时对比了采用普通电子束蒸发镀膜制备的WO3薄膜的电致变色特性.     

固态电致变色薄膜器件的发展现状

本文较系统地综述了固态电致变色薄膜和电致变色薄膜器件的研究发展，过程及现状。并了电致变色薄膜器件所存在的有关问题。     

Measurement Uncertainty Analysis of Temperature Based Solar Radiation Estimation Models

Solar radiation is the main energy source for activities in the earth. It is important that the solar radiation values are known accurately. In cases where parameters about solar radiation cannot be measured, solar radiation estimation models are used. These are mathematical functions derived from the measured meteorological parameters. In this study, temperature-based estimation models that commonly used in the literature were examined, and uncertainty analysis of the models were applied. These solar radiation estimation models are Allen model, Hargreaves model, Chen model and Bristow–Campbell model. These models calculate the total global solar radiation with the difference between the maximum and minimum air temperatures. Measurement uncertainty budgets of the models and an example calculation can be found in the study.     

线性粘弹性本构方程及其动力学应用研究综述

综述了近年来线粘弹性材料本构方程的研究成果,介绍和讨论了复常数模量模型、标准流变学模型、分数阶导数模型、分数指数模型、微振子模型等典型和常用的五种模型,同时简单介绍了这些模型的动力学应用。     

Automatic spectral analysis with time series models

The increased computational speed and developments in the robustness of algorithms have created the possibility to identify automatically a well-fitting time series model for stochastic data. It is possible to compute more than 500 models and to select only one, which certainly is one of the better models, if not the very best. That model characterizes the spectral density of the data. Time series models are excellent for random data if the model type and the model order are known. For unknown data characteristics, a large number of candidate models have to be computed. This necessarily includes too low or too high model orders and models of the wrong types, thus requiring robust estimation methods. The computer selects a model order for each of the three model types. From those three, the model type with the smallest expectation of the prediction error is selected. That unique selected model includes precisely the statistically significant details that are present in the data     

爆破数学模型浅析

本文系统地论述了爆破块度分布模型，爆破参数优化的经济数学模型和计算机模拟爆破的综合数学模型，分析了评价也各种模型在实际应用中存在的问题，并讨论了发展爆破数学模型的途径。     

Experimental validation of void fraction models for R410A air conditioners

This paper presents the combined void fraction models on the basis of flow pattern to choose suitable models for calculating the two-phase refrigerant mass of R410A air conditioners, and the model is validated experimentally. The existing single void fraction models are also evaluated experimentally. The Taitel–Dukler flow pattern map is recommended to use in the combined void fraction models. The results presented herein show that the calculated refrigerant mass using the combined void fraction models agrees relatively better with the measured refrigerant mass than that of the single void fraction models. T–B model (for intermittent flow) and Premoli model (for annular flow) are recommended for calculating the two-phase refrigerant mass in evaporator, and T–B model (for intermittent flow) and Harms model (for annular flow) are also indicated for calculating the two-phase refrigerant mass in condenser.     

Comparison of different stress-state dependent cohesive zone models applied to thin-walled structures

Two different approaches that explicitly incorporate the stress triaxiality into cohesive zone models applicable to thin-walled structures are compared to identify the relative merits and limitation of these models. The number of model parameters involved, the ease of parameter determination and the predictive capabilities of the models over a wide range of thin-walled geometries are investigated. The first model, proposed recently by the authors, uses basic elastic–plastic constitutive equations combined with a model parameter depending on the average triaxiality in plane stress conditions. The second model incorporates stress-state through exponential dependence of cohesive strength on triaxiality, similar to plane strain studies earlier. The respective parameters for both models are identified and subsequently applied to several notched and precracked specimens. It is shown that in contrast to stress-state independent models, both constraint dependent models are able to predict well failure of a wide range of structures. While the model incorporating triaxiality dependent cohesive parameters has more parameters to be determined, it is not restricted to any specific stress condition and therefore can be extended to arbitrary three-dimensional stress-states.     

Application of finite mixture models for vehicle crash data analysis

Developing sound or reliable statistical models for analyzing motor vehicle crashes is very important in highway safety studies. However, a significant difficulty associated with the model development is related to the fact that crash data often exhibit over-dispersion. Sources of dispersion can be varied and are usually unknown to the transportation analysts. These sources could potentially affect the development of negative binomial (NB) regression models, which are often the model of choice in highway safety. To help in this endeavor, this paper documents an alternative formulation that could be used for capturing heterogeneity in crash count models through the use of finite mixture regression models. The finite mixtures of Poisson or NB regression models are especially useful where count data were drawn from heterogeneous populations. These models can help determine sub-populations or groups in the data among others. To evaluate these models, Poisson and NB mixture models were estimated using data collected in Toronto, Ontario. These models were compared to standard NB regression model estimated using the same data. The results of this study show that the dataset seemed to be generated from two distinct sub-populations, each having different regression coefficients and degrees of over-dispersion. Although over-dispersion in crash data can be dealt with in a variety of ways, the mixture model can help provide the nature of the over-dispersion in the data. It is therefore recommended that transportation safety analysts use this type of model before the traditional NB model, especially when the data are suspected to belong to different groups.     

Macro-level pedestrian and bicycle crash analysis: Incorporating spatial spillover effects in dual state count models

This study attempts to explore the viability of dual-state models (i.e., zero-inflated and hurdle models) for traffic analysis zones (TAZs) based pedestrian and bicycle crash frequency analysis. Additionally, spatial spillover effects are explored in the models by employing exogenous variables from neighboring zones. The dual-state models such as zero-inflated negative binomial and hurdle negative binomial models (with and without spatial effects) are compared with the conventional single-state model (i.e., negative binomial). The model comparison for pedestrian and bicycle crashes revealed that the models that considered observed spatial effects perform better than the models that did not consider the observed spatial effects. Across the models with spatial spillover effects, the dual-state models especially zero-inflated negative binomial model offered better performance compared to single-state models. Moreover, the model results clearly highlighted the importance of various traffic, roadway, and sociodemographic characteristics of the TAZ as well as neighboring TAZs on pedestrian and bicycle crash frequency.     

Probabilistic models of fatigue crack propagation and their experimental verification

To study the fatigue crack growth problems and to emphasize the variability of the growth curves in addition to their average growth trend, three stochastic fatigue crack growth models are presented. These models include the Markov chain model, Yang's power law model and a polynomial model. Experimental work is carried out to produce the required fatigue crack growth data, which are then used for verification of the models. Two sets of statistically meaningful data, one under constant-amplitude loading and the other under random loading, are produced. Numerical study shows that all three models can be used to depict the experimentally obtained fatigue crack growth data with certain degrees of accuracy. However, out of the three models, one is superior to the others concerning a certain data set while the other two models are better for other data sets. Comparison and comments on employing individual model are made at the end of the paper based on experience gained in the present study.