永磁约束电子束轨迹实验研究

通过设计并运用一种直流电子束轨迹简易测量方法,开展了永磁约束电子束轨迹实验研究,得到了永磁铁环对60~80 ke V电子束约束作用的实验数据。结果表明:该测量方法方便有效,结果较为准确;永磁铁对电子束聚焦作用明显,并呈现出一定的规律性。对永磁铁约束电子束研究工作奠定了基础。     

船载遥测设备海上跟踪同步星标校的方法

结合船载遥测设备和测量船的特点,提出船载遥测设备海上跟踪同步星标校的方法,并通过试验数据进行验证。该方法克服了传统近场标校方法中存在的不足,实现了船载遥测设备海上精确标校。     

基于自适应网格的钝头体激波诱导燃烧现象数值模拟研究

钝头体激波诱导燃烧是爆震研究的一个基本问题。针对化学恰当量比的H2/Air预混气在Ma=4.79和Ma=6.46时的激波诱导燃烧现象开展数值模拟研究，采用基于有限体积法的块结构自适应网格加密程序AMROC对带化学反应源项的轴对称Euler方程解耦求解，考察了数值模拟中不同形式的MUSCL重构格式、限制器类型以及化学反应机理等重要因素对模拟结果的影响。结果表明，程序能够根据设定的加密判据较好地实现网格自适应加密，减小总网格量，实现高效数值模拟。通过与实验数据的对比，表明非定常激波诱导燃烧算例的准确程度不仅取决于化学反应机理，也取决于限制器类型，而采用两种不同形式的MUSCL重构格式获得的振荡频率则几乎一致，与试验结果的误差分别为1.17%和0.97%。模拟对比经典的Jachimowski机理和近年来新发展的几种包含压力相关反应步的氢/氧反应机理，模拟结果表明：对于Ma=4.79时的非定常激波诱导燃烧模拟，经典的Jachimowski机理仍然是能够给出与实验结果最接近的反应机理；而对于Ma=6.46时的定常激波诱导燃烧模拟，几种反应机理均能给出与实验吻合较好的结果。     

分析插值误差和斜率的轨迹优化网格细化方法

提出一种基于插值误差和斜率分析的轨迹优化自适应网格细化方法，包括节点插入算法和节点删除算法。节点插入算法分析各个离散节点的控制变量的插值误差。若插值误差较大，则在该节点周围增加节点细化网格；否则，不进行细化。节点删除算法分析各个离散节点处的控制变量斜率。若某个节点的左斜率和右斜率都为零，那么删除该节点；否则，保留该节点。采用三个典型的轨迹优化算例验证了所提出的方法的有效性和特色，并且与其它几种网格细化方法进行了对比。仿真结果表明，本文方法生成的网格规模较小，需要的网格迭代次数较少，能够快速、高精度求解非光滑轨迹优化问题。     

惯性静电约束推力器放电过程数值模拟研究

为了研究惯性静电约束推力器(Inertial Electrostatic Confinement Thruster,IECT)的放电原理和工作机制,采用漂移-扩散流体模拟方法,基于圆柱形惯性静电约束推力器的结构,研究不同栅网线直径、栅网个数、推力器尺寸条件下等离子体放电情况和阴极电压、背景气压对推力器放电的影响。结果表明:在所研究条件下,保证阴极必要的几何透过率的同时,适当增加推力器栅网个数可以提高喷射离子密度,减小羽流发散角;随着阴极电压和背景气压的增大,推力器喷射的等离子体密度增大。但是,压强继续增大会达到临界值,等离子体被约束在推力器内部无法喷出,即喷射模式无法运行,故阴极电压与背景气压对IECT均有较大影响。     

球状三嵌段共聚物在平面薄膜间的自组装

采用动态密度泛函理论（DDFT）对ABA型球状三嵌段共聚物在平板间的相行为进行了模拟研究。考查了不同强度的表面诱导对三嵌段共聚物自组装的影响。通过逐渐增大衬底作用,发现了多种偏离于本体的新结构,如浸润层相、平行柱状相、穿孔层相、层状相。发现浸润层相存在的表面场范围与短链的熵效应密切相关,同时熵效应的大小则依赖于长短链段的长度之比。在很多实际存在的嵌段共聚物中,如果在适当的实验条件下,应可以观察到模拟计算所预言的相结构。     

塞式喷管主喷管角度特性

首先建立了塞式喷管角度特性的研究模型，并运用简化的塞锥设计方法设计塞锥型面，在此基础上，通过连续改变主喷管倾角来研究主喷管倾角对塞式喷管的推力性能的影响，并确定在给定设计条件下的主喷管最佳倾角，还分析研究了底部高度，内膨胀比，总膨胀比，总压和飞行高度与主喷管最佳倾角的关系以及变化规律，针对特定的塞式喷管实验发动机，进行了初步的变角度实验，并与计算结果进行比较和分析。     

An enhanced least squares residual RAIM algorithm based on optimal decentralized factor

The Least Squares Residual (LSR) algorithm is commonly used in the Receiver Autonomous Integrity Monitoring (RAIM). However, LSR algorithm presents high Missed Detection Risk (MDR) caused by a large-slope faulty satellite and high False Alert Risk (FAR) caused by a small-slope faulty satellite. In this paper, the LSR algorithm is improved to reduce the MDR for a large-slope faulty satellite and the FAR for a small-slope faulty satellite. Based on the analysis of the vertical critical slope, the optimal decentralized factor is defined and the optimal test statistic is conceived, which can minimize the FAR with the premise that the MDR does not exceed its allowable value of all three directions. To construct a new test statistic approximating to the optimal test statistic, the Optimal Decentralized Factor weighted LSR (ODF-LSR) algorithm is proposed. The new test statistic maintains the sum of pseudo-range residual squares, but the specific pseudo-range residual is weighted with a parameter related to the optimal decentralized factor. The new test statistic has the same decentralized parameter with the optimal test statistic when single faulty satellite exists, and the difference between the expectation of the new test statistic and the optimal test statistic is the minimum when no faulty satellite exists. The performance of the ODF-LSR algorithm is demonstrated by simulation experiments.     

小倾角同步卫星通信

同步卫星工作寿命必须考虑各种因素,当它接近寿命末期时,尽管星上有效载荷仍能有效工作,但剩余的燃料已无法继续进行南北位置保持,只能进行东西位置保持。这时如果利用该星进行小倾角通信,就能有效地延长卫星工作寿命,节省大笔经费。同时就它给地面卫星通信系统带来的新问题做了深入研究,给出了不同倾角情况下定量分析结果,并针对不同的通信体制,提出了相应的解决方法。     

Characterizing slope correction methods applied to satellite radar altimetry data: A case study around Dome Argus in East Antarctica

Slope correction is important to improve the accuracy of satellite radar elevation measurements by mitigating the slope-induced error (SE), especially over uneven ground surfaces. Although several slope correction methods have been proposed, guidance in the form of stepwise algorithm on how to implement these methods in processing radar altimetric data at the coding level, and the differences among these methods need to be presented and discussed systematically. In this paper, three existing types of slope correction methods—the direct method (DM), intermediate method (IM), and relocation method (RM, further divided into RM1 and RM2)—are described in detail. In addition, their main differences and features for various scientific applications are analyzed. We conduct a systematic experiment with CryoSat-2 Low Resolution Mode (LRM) data in a physically stable area around Dome Argus in East Antarctica, where in-situ measurements were available for comparison. The slope correction is implemented separately using the three methods, with the latest high-accuracy Reference Elevation Model of Antarctica (REMA) as the a-priori topography model. The bias and precision of the slope-corrected CryoSat-2 data results from the RM2 is ?0.18 ± 0.86 m based on the comparison with the field Global Navigation Satellite System (GNSS) data. The results from the RM2 indicate higher precision compared to those from the RM1. According to the correlation analysis of the slope-corrected CryoSat-2 data results (RM1 and RM2), the bias enlarges and the precision becomes worse when the surface slope increases from 0 to 0.85°. After a comprehensively comparative analysis, we find that the results from the RM1 and RM2 are superior in precision (0.93 m and 0.86 m) with respect to the GNSS data. The relatively low precision (1.22 m) from the IM is due to the potential error from the a-priori digital elevation model (DEM). The DM has the lowest precision (2.66 m). Another experiment over rough topography in West Antarctica is carried out for comparison, especially between the RM1 (precision of 15.27 m) and RM2 (precision of 16.25 m). In general, the RM is recommended for the SE elimination among the three methods. Moreover, the RM2 is firstly considered over smooth topography due to the superior performance in bias and precision, while the RM1 is more suggested over the rough topography because of the slightly smaller bias and better precision. The IM relies much on the accuracy of the a-prior DEM and is not usually recommended, because of the strict requirement in the sampling time between the radar altimetry data and the a-priori DEM to avoid any surface change over time.