Visualization Experiments of a Specific Fuel Flow Through Quartz-glass Tubes Under both Sub- and Supercritical Conditions

The present work is a visualization study of a typical kerosene (RP-3) flowing through vertical and horizontal quartz-glass tubes under both suband supercritical conditions by a high speed camera. The experiments are accomplished at temperatures of 300-730 K under pressures from 0.107-5 MPa. Six distinctive two-phase flow patterns are observed in upward flow and the critical point of RP-3 is identified as critical pressure pc=2.33 MPa and critical temperature Tc=645.04 K and it is found that when the fluid pressure exceeds 2.33 MPa the flow can be considered as a single phase flow. The critical opalescence phenomenon of RP-3 is observed when the temperature is between 643.16 K and 648.61 K and the pressure is between 2.308 MPa and 2.366 MPa. The region filled by the critical opalescence in the upward flow is clearly larger than that in the downward flow due to the interaction between the buoyancy force and fluid inertia. Morecover, obvious layered flow phenomenon is observed in horizontal flow under supercritical pressures due to the differences of gravity and density.     

中国民航运输系统性测度研究

对民航运输系统发展程度的有效测度是实现民航运输系统协同发展的前提和基础,从民航运输系统性内涵出发,构建了民航运输系统性测度模型。借助数据包络分析评价方法,建立了民航运输系统总体评价方法,基于协同理论建立了民航运输子系统协调度测度模型和方法。并应用所建立的模型和方法,对中国民航运输系统性状况进行了实证研究。研究结果表明,中国民航系统的有效性有待提高,航空公司系统、机场系统与空管系统两两之间均处于中度协调状态,动态协调度呈现出上升趋势。     

基于分层变块大小运动估计的边信息提取算法(英文)

在分布式视频编码(DVC)中,边信息的质量对视频序列的压缩效果有很大影响。本文中,一种基于分层运动估计的边信息提取算法引入到DVC系统中。首先,采用了两种运动估计模式,向前运动估计和双向运动估计,然后利用分层变块大小运动估计算法获得了比较准确的运动矢量。接着运动矢量滤波器修正了由于局部相似造成的错误运动矢量。最后,选择决策模块更好地处理了帧内插技术中的多种估计模式的问题。这些算法为DVC提供了更好的边信息,提高了DVC系统的性能。实验结果显示,基于这种新算法的DVC系统高于传统视频编码帧内模式 3-4dB,而仅仅低于传统视频编码IBIB模式0.5-1dB。     

Image Smearing Modeling and Verification for Strapdown Star Sensor

To further extend study on celestial attitude determination with strapdown star sensor from static into dynamic field, one prerequisite is to generate precise dynamic simulating star maps. First a neat analytical solution of the smearing trajectory caused by spacecraft attitude maneuver is deduced successfully, whose parameters cover the geometric size of optics, three-axis angular velocities and CCD integral time. Then for the first time the mathematical law and method are discovered about how to synthesize the two formulae of smearing trajectory and the static Gaussian distribution function (GDF) model, the key of which is a line integral with regard to the static GDF attenuated by a factor 1/ L s (L s is the arc length of the smearing trajectory) along the smearing trajectory. The dynamic smearing model is then obtained, also in an analytical form. After that, three sets of typical simulating maps and data are simulated from this dynamic model manifesting the expected smearing effects, also compatible with the linear model as its special case of no boresight rotation. Finally, model validity tests on a rate turntable are carried out, which results in a mean correlation coefficient 0.920 0 between the camera images and the corresponding model simulated ones with the same parameters. The sufficient similarity verifies the validity of the dynamic smearing model. This model, after parameter calibration, can serve as a front-end loop of the ground semi-physical simulation system for celestial attitude determination with strapdown star sensor.     

Asymptotic Performance of Sparse Signal Detection Using Convex Programming Method

The detection of sparse signals against background noise is considered. Detecting signals of such kind is difficult since only a small portion of the signal carries information. Prior knowledge is usually assumed to ease detection. In this paper, we consider the general unknown and arbitrary sparse signal detection problem when no prior knowledge is available. Under a Neyman-Pearson hypothesis-testing framework, a new detection scheme is proposed by combining a generalized likelihood ratio test (GLRT)-like test statistic and convex programming methods which directly exploit sparsity in an underdetermined system of linear equations. We characterize large sample behavior of the proposed method by analyzing its asymptotic performance. Specifically, we give the condition for the Chernoff-consistent detection which shows that the proposed method is very sensitive to the 2 norm energy of the sparse signals. Both the false alarm rate and the miss rate tend to zero at vanishing signal-to-noise ratio (SNR), as long as the signal energy grows at least logarithmically with the problem dimension. Next we give a large deviation analysis to characterize the error exponent for the Neyman-Pearson detection. We derive the oracle error exponent assuming signal knowledge. Then we explicitly derive the error exponent of the proposed scheme and compare it with the oracle exponent. We complement our study with numerical experiments, showing that the proposed method performs in the vicinity of the likelihood ratio test (LRT) method in the finite sample scenario and the error probability degrades exponentially with the number of observations.     

Defect Recognition in Thermosonic Imaging

This work is aimed at developing an effective method for defect recognition in thermosonic imaging.The heat mechanism of thermosonic imaging is introduced,and the problem for defect recognition is discussed.For this purpose,defect existing in the inner wall of a metal pipeline specimen and defects embedded in a carbon fiber reinforced plastic(CFRP) laminate are tested.The experimental data are processed by pulse phase thermography(PPT) method to show the phase images at different frequencies,and the characteristic of phase angle vs frequency curve of thermal anomalies and sound area is analyzed.A binary image,which is based on the characteristic value of defects,is obtained by a new recognition algorithm to show the defects.Results demonstrate good defect recognition performance for thermosonic imaging,and the reliability of this technique can be improved by the method.     

基于区域分割的红外与可见光图像融合算法的研究(英文)

由于红外图像和可见光图像的成像特点不同,因此在航空监视领域红外图像和可见光图像融合有重要的研究意义。由于非下采Contourlet变换具有更好的方向性、较高的逼近精度和更好的稀疏表达性能,能有效的提取图像的特征信息。因此我们在非下采Contourlet域,以空间频率为度量标准对红外图像进行阈值分割,经过分割将红外图像和可见光图像分别划分为目标区域以及背景,随后对红外图像和可见光图像进行边缘检测从而得到边缘区域,针对三个不同区域分别选择不同的融合规则进行融合。通过两组不同灰度差异的红外与可见光图像的实验,将基于像素点,窗口策略的融合算法和本文所提出基于区域算法进行了主观和客观的对比,试验结果表明基于区域分割的红外与可见光图像融合算法不仅能有效提取出红外图像中的目标信息还能有效的保持可见光图像的所反映的光谱信息,因此本文提出的算法是一种有效且可行的图像融合算法。     

基于多岛遗传算法的大型预应力钢丝缠绕承载机架成本优化方法(英文)

预应力钢丝缠绕机架(PWWF)是一种先进结构,是大型装备中价值为高的部件。由于PWWF是变刚度、非线性受力及变形自协调的多体混合结构,其传统的设计方法是极其复杂、反复迭代且成本难以控制。本文提出了基于多岛遗传算法的大型钢丝缠绕机架的成本优化方法。在变张力缠绕理论基础建立了预应力钢丝缠绕承载机架的优化设计流程和优化模型。并给出结合轴向载荷为6000KN的等静压设备机架的优化设计实例。与传统设计方法相比,优化成本降低约了21.6%。该优化结果已通过数值模拟方法验证,并成功应用于实际设备的制造中。结果表明,该优化方法合理、可靠。该方法为超546MN和907MN超大规格多机架结构的成本优化提供指导。     

WMAP extragalactic point sources as potential Space VLBI calibrators

The point source list of the Wilkinson Microwave Anisotropy Probe (WMAP) is a uniform, all-sky catalogue of bright sources with flux density measurements at high (up to 94 GHz) radio frequencies. We investigated the five-year WMAP list to compile a new catalogue of bright and compact extragalactic radio sources to be potentially studied with Very Long Baseline Interferometry at millimeter wavelengths (mm-VLBI) and Space VLBI (SVLBI). After comparing the WMAP data with the existing mm-VLBI catalogues, we sorted out the yet unexplored sources. Using the 41, 61 and 94 GHz WMAP flux densities, we calculated the spectral indices. By collecting optical identifications, lower-frequency radio flux densities and VLBI images from the literature, we created a list of objects which have not been investigated with VLBI at 86 GHz before. With total flux density at least 1 Jy and declination above −40°, we found 37 suitable new targets. It is a nearly 25% addition to the known mm-VLBI sources. Such objects are also potentially useful as phase-reference calibrators for the future Japanese SVLBI mission ASTRO-G at its highest observing frequency (43 GHz). The phase-referencing capability of ASTRO-G would allow long integrations and hence better sensitivity for observing faint target sources close to suitable phase calibrators in the sky.     

Low-frequency Periodic Error Identification and Compensation for Star Tracker Attitude Measurement

The low-frequency periodic error of star tracker is one of the most critical problems for high-accuracy satellite attitude determination.In this paper an approach is proposed to identify and compensate the low-frequency periodic error for star tracker in attitude measurement.The analytical expression between the estimated gyro drift and the low-frequency periodic error of star tracker is derived firstly.And then the low-frequency periodic error,which can be expressed by Fourier series,is identified by the frequency spectrum of the estimated gyro drift according to the solution of the first step.Furthermore,the compensated model of the low-frequency periodic error is established based on the identified parameters to improve the attitude determination accuracy.Finally,promising simulated experimental results demonstrate the validity and effectiveness of the proposed method.The periodic error for attitude determination is eliminated basically and the estimation precision is improved greatly.