LU—ADI方法在求解跨声速翼型绕流问题中的应用

本文利用LU-ADI方法求解了跨声速范围内的Euler、NS方程。研究了边界的处理和某些求解方法的改进。     

AEDMS工程文件编号的生成算法

工程文件编号生成算法是国航工程文件管理系统（AEDMS）开发的难点。提出的．工程文件编号生成算法包括．工程文件流水号和改版号的指派算法与自动编排算法。前者解决了新旧系统．工程文件编号的兼容问题；后者是一种新的基于关系代数的自动编号算法，其利用元组序号，具有紧凑简单、可靠性好、可维护性好、执行效率高、适用面广的特点。实算结果和AEDMS运行实践表明，此工程文件编号生成算法是可行的。     

一种定量建立主题数据库的算法

本文利用企业模型中的企业活动与实体之间的关系给出了实体组之间的相关系数定义，在此基础上，给出了实体组的分组算法，从而应可以根据主要数据库分划标准把实体划分成实体大组，形成主题数据库。     

高血压鉴别诊断专家系统HEDDS的不精确推理算法

本文在分析著名的医学专家系统MYCIN不精确推理算法的基础上,提出了一种易于在微型计算机上实现的简便有效的不精确推理算法,并就其一些性质进行了讨论。     

两凸平面相贯立体的隐藏线消去法

本文介绍了一种消去两相贯凸平面立体的隐藏线算法。首先利用外法线法单体消隐,然后用线与面比较法作组合消隐计算,逐一确定各个单体上可见棱线在组合体上的可见线段,最后显示或绘制所有的可见棱线段和两体的可见交线,得到消隐后的立体图。本法信息输入量较小,功能较强,不但适用于两相贯的凸平面立体的消隐,而且也适用于两迭加的凸平面立体的消隐。本程序还适用于两体具有共面的情况。     

Development of x-ray mirrors for high-energy astrophysics in czechoslovakia

The grazing incidence X-ray mirrors with diameters between 20 and 240 mm were produced by two different replica techniques. Five mirrors were flown in space experiments. It has been confirmed that the galvanoplastic replica mirrors are well suited for applications in space telescopes and laboratory microscopes.     

基于卫星观测数据的弹道导弹初始状态估计

利用卫星探测数据对大气层外飞行的弹道导弹弹道进行估计。在极大似然估计中,由于卫星探测导弹运动的可观测性较差,使初始点估计变得十分病态,传统的Gauss Newton迭代算法不再适用,而采用较为复杂Levenberg Marquardt算法,分别对单颗卫星和两颗卫星的情况进行了Monte Carlo仿真,得到了各自的归一化残差测量误差(代价函数),结果表明该算法有效。     

基于星体边缘和轨道投影的光学自主导航算法

针对光学导航中存在的通过星体（球体）图像部分边缘点拟合椭圆参数计算轨道参数产生中间误差的问题,提出利用边缘点映射轨道参数的直接投影模型,避免拟合椭圆参数的方法。在小孔成像模型基础上,建立了边缘点与轨道参数的直接投影数学模型,对其映射过程进行了理论推导,利用列文伯格-马夸尔特迭代算法进行求解轨道参数。用实际探测器以及镜头参数进行数值仿真验证,结果表明：该方法在相同边缘点的条件下,轨道精度可以达到5‰。与传统方法相比,这种方法避免了椭圆的拟合过程,减少了引入中间误差过程。     

A modern robust approach to remotely estimate chlorophyll in coastal and inland zones

The chlorophyll concentration of a water body is an important proxy for representing the phytoplankton biomass. Its estimation from multi or hyper-spectral remote sensing data in natural waters is generally achieved by using (i) the waveband ratioing in two or more bands in the blue-green or (ii) by using a combination of the radiance peak position and magnitude in the red-near-infrared (NIR) spectrum. The blue-green ratio algorithms have been extensively used with satellite ocean color data to investigate chlorophyll distributions in open ocean and clear waters and the application of red-NIR algorithms is often restricted to turbid productive water bodies. These issues present the greatest obstacles to our ability to formulate a modern robust method suitable for quantitative assessments of the chlorophyll concentration in a diverse range of water types. The present study is focused to investigate the normalized water-leaving radiance spectra in the visible and NIR region and propose a robust algorithm (Generalized ABI, GABI algorithm) for chlorophyll concentration retrieval based on Algal Bloom index (ABI) which separates phytoplankton signals from other constituents in the water column. The GABI algorithm is validated using independent in-situ data from various regional to global waters and its performance is further evaluated by comparison with the blue-green waveband ratios and red-NIR algorithms. The results revealed that GABI yields significantly more accurate chlorophyll concentrations (with uncertainties less than 13.5%) and remains more stable in different waters types when compared with the blue-green waveband ratios and red-NIR algorithms. The performance of GABI is further demonstrated using HICO images from nearshore turbid productive waters and MERIS and MODIS-Aqua images from coastal and offshore waters of the Arabian Sea, Bay of Bengal and East China Sea.     

Validation of non-linear split window algorithm for land surface temperature estimation using Sentinel-3 satellite imagery: Case study; Tehran Province,Iran

In recent years, land surface temperature (LST) has become critical in environmental studies and earth science. Remote sensing technology enables spatiotemporal monitoring of this parameter on large scales. This parameter can be estimated by satellite images with at least one thermal band. Sentinel-3 SLSTR data provide LST products with a spatial resolution of 1 km. In this research, direct and indirect validation procedures were employed to evaluate the Sentinel-3 SLSTR LST products over the study area in different seasons from 2018 to 2019. The validation method was based on the absolute (direct) evaluation of this product with field data and comparison (indirect) evaluation with the MODIS LST product and the estimated LST using the non-linear split-window (NSW) algorithm. Also, two emissivity estimation methods, (1) NDVI thresholding method (NDVI-THM) and (2) classification-based emissivity method (CBEM), were used to estimate the LST using the NSW method according to the two thermal bands of Sentinel-3 images. Then, the accuracy of these methods in estimating LST was evaluated using field data and temporal changes of vegetation, which the NDVI-THM method generated better results. For indirect evaluation between the Sentinel-3 LST product, MODIS LST product, and LST estimated using NSW, four filters based on spatial and temporal separates between pairs of pixels and pixel quality were used to ensure the accuracy and consistency of the compared pairs of a pixel. In general, the accuracy results of the LST products of MODIS and Sentinel-3, and LST estimated using NSW showed a similar trend for LST changes during the seasons. With respect to the two absolute and comparative validations for the Sentinel-3 LST products, summer with the highest values of bias (?1.24 K), standard deviation (StDv = 2.66 K), and RMSE (2.43 K), and winter with the lowest ones (bias of 0.14 K, StDv of 1.13 K, and RMSE of 1.12 K) provided the worst and best results for the seasons in the period of 2018–2019, respectively. According to both absolute and comparative evaluation results, the Sentinel-3 SLSTR LST products provided reliable results for all seasons on a large temporal and spatial scale over our studied area.