基于稳态卡计法的半球向全发射率测量技术综述

综述了半球向全发射率测量技术研究现状,介绍了基于稳态卡计法的半球向全发射率测量原理,根据对试样加热方式的不同对测量装置进行了分类,并从技术层面剖析了各类测量装置的特点及存在的问题,讨论了基于稳态卡计法半球向全发射率测量技术存在的不足和未来的发展方向。

瞬态卡计法测定涂层的半球总发射率

本文描述了一台瞬态卡计法测定涂层的半球总发射率(?)的装置.用它可以在一次测试过程中连续测定样品在常温和低温相当宽的范围(-130～+140℃)内的半球总发射率值,误差<6%.本文详细地介绍了测试和数据处理方法,分析了误差,并提供了若干金属、阳极氧化铝、涂料型无机涂层和等离子喷涂涂层等样品在不同温度下发射率的测试结果,并进行了讨论.

用稳态卡计法对热控材料半球发射率的测试研究

利用稳态卡计法设计了一种测试材料半球发射率的试验装置,并对其进行了不确定度分析。使用该装置对二次表面镜(OSR)的室温半球发射率进行了测试,测试结果不确定度小于2.00%。同时,使用该装置测试了OSR与一种新型相变材料在190～350 K间的半球发射率。

卡计法热流计测量瞬态热流的试验研究

针对目前使用的热流计主要应用于稳态热平衡试验中外热流的测量,文章对卡计法热流计测量瞬态热流特性进行了试验研究,结果表明卡计法热流计可以用于测量瞬态热流且响应时间较短。

相变材料热物性能测定方法分析

目前关于相变材料(PCM)热物性能的测试方法国内外没有统一标准,造成研究和应用领域的困难。该文介绍了国内外测试相变储能材料热物性的方法的进展和成果,重点对比分析了差示扫描量热法(DSC)、参比温度法及卡计法等常用的相变材料热物性能测定方法的原理和优缺点,探讨了各方法在相变材料热物性测定时的注意事项,为今后该类材料的研究奠定了测试方法基础。

Study on slope reliability method Response Surface Method based on Morgenstern-Price Method

The combination of Morgenstern-Price Method （MPM） with Response Surface Method （RSM） improves the eonventional RSM by replacing Finite-Element Method （FEM） with MPM, which is a type of reliability analysis method-RSM based on MPM, and makes the computing process simpler. The stability of the slope was re-evaluated by use of Monte Carlo method （MCM） and the result contrasted with the fore is the conclusion. The reliability analysis of the artificial slope in Donggang Power Station was carried on, and obtained the reliable charaeteristics, which provided basis for the project.

Comparison of Linearized Kalman Filter and Extended Kalman Filter for Satellite Motion States Estimation

The performance of the conventional Kalman filter depends on process and measurement noise statistics given by the system model and measurements.The conventional Kalman filter is usually used for a linear system,but it should not be used for estimating the state of a nonlinear system such as a satellite motion because it is difficult to obtain the desired estimation results.The linearized Kalman filtering approach and the extended Kalman filtering approach have been proposed for a general nonlinear system.The equations of satellite motion are described.The satellite motion states are estimated,and the relevant estimation errors are calculated through the estimation algorithms of the both above mentioned approaches implemented in Matlab are estimated.The performances of the extended Kalman filter and the linearized Kalman filter are compared.The simulation results show that the extended Kalman filter is much better than the linearized Kalman filter at the aspect of estimation effect.

Nonlinear state estimation for fermentation process using cubature Kalman filter to incorporate delayed measurements

State estimation of biological process variables directly influences the performance of on-line monitoring and op- timal control for fermentation process. A novel nonlinear state estimation method for fermentation process is proposed using cubature Kalman filter （CKF） to incorporate delayed measurements. The square-root version of CI（F （SCKF） algorithm is given and the system with delayed measurements is described. On this basis, the sample-state augmentation method for the SCKF algorithm is provided and the implementation of the proposed algorithm is constructed. Then a nonlinear state space model for fermentation process is established and the SCKF algorithm incorporating delayed measurements based on fermentation process model is presented to implement the nonlinear state estimation. Finally, the proposed nonlinear state estimation methodology is applied to the state estimation for penicillin and industrial yeast fermentation processes. The simulation results show that the on-fine state estimation for fermentation process can be achieved by the proposed method with higher esti- mation accuracy and better stability.

Noise estimation and filtering method of MEMS gyroscope based on EMMAP

Aiming at the problems of low measurement accuracy,uncertainty and nonlinearity of random noise of the micro electro mechanical system(MEMS)gyroscope,a gyroscope noise estimation and filtering method is proposed,which combines expectation maximum(EM)with maximum a posterior(MAP)to form an adpative unscented Kalman filter(UKF),called EMMAP-UKF.According to the MAP estimation principle,a suboptimal unbiased MAP noise statistical estimation model is constructed.Then,EM algorithm is introduced to transform the noise estimation problem into the mathematical expectation maximization problem,which can dynamically adjust the variance of the observed noise.Finally,the estimation and filtering of gyroscope random drift error can be realized.The performance of the gyro noise filtering method is evaluated by Allan variance,and the effectiveness of the method is verified by hardware-in-the-loop simulation.

Accuracy Analysis of Assembly Success Rate with Monte Carlo Simulations

Monte Carlo simulation was applied to Assembly Success Bate (ASK) analyses. ASR of two peg-in-hole robot assemblies was used as an example by taking component parts' sizes, manufacturing tolerances and robot repeatability into account. A statistic arithmetic expression was proposed and deduced in this paper, which offers an alternative method of estimating the accuracy of ASR, without having to repeat the simulations. This statistic method also helps to choose a suitable sample size, if error reduction is desired. Monte Carlo simulation results demonstrated the feasibility of the method.

A New Alternative Method for Checking Total Stations

Today, just by activating a button on the display panel of a total station, one can measure horizontal and vertical angles or calculate distances and coordinates of points. For this reason, it has become necessary to improve the check of a total station in order to respond to its contemporary way of use. The aim of this research is to create a new method for checking total stations using only one check--field, in a different way of the today＇s standards. The basic principle, of the comparison of an instrument＇s measurements to those of another instrument with higher accuracy, is implemented into a mathematical model such as the adjustment of an indoor geodetic network. Thus, the check of the proper function of a total station is applied. An a-priori calculation Of^o of the network＇s adjustment can be calculated by modeling the uncertainties using statistical methods as the random number generators by means of the Monte Carlo method. The prospective ao can then be compared to the a-posteriori ao provided by the adjustment of the measurements which are carried out by using the total station under check.

New Program Projects Selection for TV Companies

Selecting new program projects plays an important role for TV companies. Balanced scorecard （BSC） which links financial and non-financial, tangible and intangible, inward and outward factors can provide an integrated viewpoint for decision makers to select optimal new program projects. This study combines BSC with analytic hierarchy process （AHP） to help Taiwan Residents TV company managers make better decisions in new program projects selection. Moreover, the practical application of the proposed approach is generic and also suitable to be exploited for Taiwan Residents TV companies.

Random Model and Simulation for Nucleation Stage of Emulsion Polymerization

The method of mathematical model and further computer simulation is an effective way to the theoretical study of emulsion polymerization and the scale-up of the reactors. In this work, Monte Carlo method has been used to simulate the nucleation of emulsion polymerization. The effects of emulsifier concentration [S] and initiator concentration [I] on various parameters such as the number of the particles (N p), the average diameter of the latex particles (D p), monomer conversion (x) and average radical number per particle (n) have been studied. The quantitative equations between [S], [I] and N p are in accord absolutely with the classical theory of Smith-Ewart.

A Homogeneous Linear Estimation Method for System Error in Data Assimilation

In this paper, a new bias estimation method is proposed and applied in a regional ensemble Kalman filter （EnKF） based on the Weather Research and Forecasting （WRF） Model. The method is based on a homogeneous linear bias model, and the model bias is estimated using statistics at each assimilation cycle, which is different from the state augmentation methods proposed in pre- vious literatures. The new method provides a good estimation for the model bias of some specific variables, such as sea level pres- sure （SLP）. A series of numerical experiments with EnKF are performed to examine the new method under a severe weather condi- tion. Results show the positive effect of the method on the forecasting of circulation pattern and meso-scale systems, and the reduc- tion of analysis errors. The background error covarianee structures of surface variables and the effects of model system bias on EnKF are also studied under the error covariance structures and a new concept ＇correlation scale＇ is introduced. However, the new method needs further evaluation with more cases of assimilation.

Simulating Particle Swarm Optimization Algorithm to Estimate Likelihood Function of ARMA（1, 1） Model

This paper present a simulation study of an evolutionary algorithms, Particle Swarm Optimization PSO algorithm to optimize likelihood function of ARMA（1, 1） model, where maximizing likelihood function is equivalent to maximizing its logarithm, so the objective function ＇obj.fun＇ is maximizing log-likelihood function. Monte Carlo method adapted for implementing and designing the experiments of this simulation. This study including a comparison among three versions of PSO algorithm “Constriction coefficient CCPSO, Inertia weight IWPSO, and Fully Informed FIPSO”, the experiments designed by setting different values of model parameters al, bs sample size n, moreover the parameters of PSO algorithms. MSE used as test statistic to measure the efficiency PSO to estimate model. The results show the ability of PSO to estimate ARMA＇ s parameters, and the minimum values of MSE getting for COPSO.

Research of Pipeline Pressure Based on the Reliability Theory

The former gas pipeline operating pressure transmission determined mostly according to the determined formula into the corresponding pipeline parameters are obtained, and the parameters of the actual pipeline due to many reasons, such as measurement error, production batch, etc., is not a fixed value. This paper on pipeline integrity established limit state equation, using Monte Carlo method to calculate the gas pipeline in different pressures of reliability, according to the API （American Petroleum Institute） 579 recommended target reliability to determine the operating pressure of the different regions, and design coefficient method, the calculated results are compared, results of calculation reliability is more reasonable and improve the delivery pressure of the area, the pipeline safety management provides the basis.

Calculation model of military aircraft suryiyability to a missile

Since missiles are main threat against aircrafts in air war,a model is proposed for calculating the aircraft survivability to a missile.The hit characteristic of aircraft to a missile is analyzed,and then Monte Carlo method is applied to generate missile detonation location according to its distribution rule.In addition,based on the analysis of fragment trajectory and critical components,the intersection point of these two is determined.Then the kill probability of critical component to a fragment can be calculated,and the aircraft survivability to a missile is obtained accordingly.Finally,the feasibility of the proposed method is demonstrated.Simulation results show that this method captures the basic effects of missile detonation locations on aircraft survivability,which may provide an effective reference to aircraft survivability research.

低温固化热致变色涂层辐射特性

以溶胶凝胶法制备的高纯La_(1-x)Sr_xMnO_3(x=0.125,0.175,0.2)纳米粉末为填料,分别以热塑性丙烯酸树脂和松油醇@乙基纤维素为基料制备成涂层浆料,并涂覆于铝基底表面,再分别以低温120℃和180℃固化La_(1-x)Sr_xMnO_3热致变色涂层.实验表征了纳米粉末的物相,表面形貌,观察了涂层的微观形貌.并利用稳态卡计法测量了热致变色涂层在173~370 K温度范围内全半球发射率随温度的变化.研究结果表明:两种不同树脂为基料的涂层都表现出热致变色特性,其发射率增幅达0.45.由于低温固化涂层制备工艺简单,能够适用于复杂表面的涂覆应用,在航天热控中具有潜在的应用前景.

Evaluating the accuracy performance of Lucas-Kanade algorithm in the circumstance of PIV application

Lucas-Kanade(LK) algorithm, usually used in optical flow filed, has recently received increasing attention from PIV community due to its advanced calculation efficiency by GPU acceleration. Although applications of this algorithm are continuously emerging,a systematic performance evaluation is still lacking. This forms the primary aim of the present work. Three warping schemes in the family of LK algorithm: forward/inverse/symmetric warping, are evaluated in a prototype flow of a hierarchy of multiple two-dimensional vortices. Second-order Newton descent is also considered here. The accuracy & efficiency of all these LK variants are investigated under a large domain of various influential parameters. It is found that the constant displacement constraint, which is a necessary building block for GPU acceleration, is the most critical issue in affecting LK algorithm's accuracy, which can be somehow ameliorated by using second-order Newton descent. Moreover, symmetric warping outbids the other two warping schemes in accuracy level, robustness to noise, convergence speed and tolerance to displacement gradient, and might be the first choice when applying LK algorithm to PIV measurement.

On the Crossing Numbers of K5 × Sn

By connecting the 5 vertices of K5 to other n vertices, we obtain a special family of graph denoted by Hn. This paper proves that the crossing number of Hn is Z（5, n） ＋2n＋ [n/2] ＋1, and the crossing number of Cartesian products of K5 with star Sn is Z（5, n） ＋ 5n ＋ [n/2] ＋ 1.