表面张力贮箱推进剂管理装置流阻的计算

为了在设计卫星用表面张力贮箱时，正确地计算出推进剂管理装置中液体推进剂的流阻，根据液体的流动特性，研究了卫星用表面张力贮箱推进剂管理装置中推进剂在管道，筛网和一些局部流阻的计算方法，给出了各部分流阻的计算公式，据此实际计算了一个简单的推进剂管理装置，并和实验进行了比较，结果表明理论和实验较为符合。     

板式贮箱内部流动的定常和非定常数值模拟

为了研究微重力环境下板式表面张力贮箱的内部流动规律,对板式贮箱导流板的驱动机理进行了分析,得到了微重力环境下板式贮箱内部定常和非定常流动的基本方程。应用四阶龙格-库塔法对定常流动方程进行求解,得到定常流动时导流板上液带的分布规律;应用MacCormack数值离散方法,对非定常流动方程进行求解,得到了不同时刻导流板上液带的分布规律及液带恢复稳定所需的时间。计算结果为板式贮箱的设计提供了数值依据,奠定了板式贮箱的设计基础。     

大型空间地磁亚暴环境地面模拟试验

空间地磁亚暴环境可以给地球同步轨道卫星带来灾难性后果。文章主要介绍了地磁亚暴环境效应及国内外的相关设备,并根据我国现状,提出进行大型地磁亚暴环境试验的必要性和可行性。     

红外热波成像法测量薄板局部换热系数

通过连续激光调制对薄板试样进行局部周期加热，采用红外扫描测温技术记录动态温度分布。利用博里叶变换分析温度基波相位和幅值变化，进而推算壁面的局部换热系数。介绍了该方法的测量原理，在风洞中对两种不同厚度的薄板进行了实验研究，并对实验结果进行了分析和讨论。     

GPS total electron content and surface latent heat flux variations before the 11 March 2011 M9.0 Sendai earthquake

The present paper describes the variations of the GPS total electron content (TEC) from the International GNSS service network and surface latent heat flux (SLHF) from the Scientific Computing Division of the National Center for Atmospheric Research (NCAR) before the 11 March 2011 M9.0 Sendai earthquake, respectively. The analysis shows pronounced enhancements in the GPS TEC and SLHF a few days prior to the earthquake event. The maximum increase in the GPS TEC was about 30 TECu with an extended spatial distribution on a geomagnetically quiet day (Dst ? −20 nT, between two moderate geomagnetic storms), 8 March, 3 days prior to the earthquake. This giant positive disturbance was possibly associated with the impending disastrous earthquake and contributed from the enhanced solar radiation. Moreover, there were several anomalous regions of SLHF on the global map, but an area of enhanced SLHF very close to the epicenter. The purpose of this paper is to report the existence of the changes in surface and ionosphere, and show the potential application of multi-source data to identify seismic precursors.     

频率标准用超导铌腔内表面处理工艺研究

频率标准用超导铌腔内表面的处理是影响超导腔Q值的最大因素。本文首先通过理论分析确定了超导腔Q与表面剩余电阻的关系,其次通过一系列的表面处理工艺来保证超导腔内表面的剩余电阻尽量小,最后通过实验得到了超导腔的Q值为1.9E9,与理论计算结果相近,证明了表面处理的有效性。     

Hierarchical object oriented classification using very high resolution imagery and LIDAR data over urban areas

Urban land cover information extraction is a hot topic within urban studies. Heterogeneous spectra of high resolution imagery—caused by the inner complexity of urban areas—make it difficult. In this paper a hierarchical object oriented classification method over an urban area is presented. Combining QuickBird imagery and light detection and ranging (LIDAR) data, nine kinds of land cover objects were extracted. The Spectral Shape Index (SSI) method is used to distinguish water and shadow from black body mask, with 100% classification accuracy for water and 95.56% for shadow. Vegetation was extracted by using a Normalized Difference Vegetation Index (NDVI) image at first, and then a more accurate classification result of shrub and grassland is obtained by integrating the height information from LIDAR data. The classification accuracy of shrub was improved from 85.25% to 92.09% and from 82.86% to 97.06% for grassland. More granularity of this classification can be obtained by using this method. High buildings and low buildings can, for example, be distinguished from the original building class. Road class can also be further classified into roads and crossroads. The comparison of the classification accuracy between this method and the traditional pixel-based method indicates that the total accuracy is improved from 69.12% to 89.40%.     

Measuring tidal deformations at Europa’s surface

Key information on Europa’s interior can be gained by monitoring tidally-induced surface deformations from orbiting and landed spacecraft. Such observations would provide constraints on the thickness and rheology of Europa’s ice and liquid water layer, being thus an important tool to characterize basic physical properties of the satellite’s putative subsurface water ocean. Focusing on the outer ice-I layer we will present relations between the interior of Europa and key tidal parameters that can be retrieved from an instrument suite monitoring tidally-induced changes of local gravity, tilt, latitude and strain at the surface. A most promising approach would involve laser altimetry and gravitational field observations from an orbiting spacecraft combined with monitoring of tidally-induced gravity and tilt changes at the surface. However, tidal measurements at the surface may be significantly impeded by instrumental drift, instrument coupling to the surface, local sources of noise and the presumably short life-time of the instruments due to the harsh radiation environment.     

An Adaptive Network-based Fuzzy Inference System for the detection of thermal and TEC anomalies around the time of the Varzeghan,Iran, (Mw = 6.4) earthquake of 11 August 2012

Anomaly detection is extremely important for forecasting the date, location and magnitude of an impending earthquake. In this paper, an Adaptive Network-based Fuzzy Inference System (ANFIS) has been proposed to detect the thermal and Total Electron Content (TEC) anomalies around the time of the Varzeghan, Iran, (M_w = 6.4) earthquake jolted in 11 August 2012 NW Iran. ANFIS is the famous hybrid neuro-fuzzy network for modeling the non-linear complex systems. In this study, also the detected thermal and TEC anomalies using the proposed method are compared to the results dealing with the observed anomalies by applying the classical and intelligent methods including Interquartile, Auto-Regressive Integrated Moving Average (ARIMA), Artificial Neural Network (ANN) and Support Vector Machine (SVM) methods. The duration of the dataset which is comprised from Aqua-MODIS Land Surface Temperature (LST) night-time snapshot images and also Global Ionospheric Maps (GIM), is 62 days. It can be shown that, if the difference between the predicted value using the ANFIS method and the observed value, exceeds the pre-defined threshold value, then the observed precursor value in the absence of non seismic effective parameters could be regarded as precursory anomaly. For two precursors of LST and TEC, the ANFIS method shows very good agreement with the other implemented classical and intelligent methods and this indicates that ANFIS is capable of detecting earthquake anomalies. The applied methods detected anomalous occurrences 1 and 2 days before the earthquake. This paper indicates that the detection of the thermal and TEC anomalies derive their credibility from the overall efficiencies and potentialities of the five integrated methods.