Ionospheric response to solar and magnetospheric protons during January 15–22, 2005: EAGLE whole atmosphere model results

We present an analysis of the ionosphere and thermosphere response to Solar Proton Events (SPE) and magnetospheric proton precipitation in January 2005, which was carried out using the model of the entire atmosphere EAGLE. The ionization rates for the considered period were acquired from the AIMOS (Atmospheric Ionization Module Osnabrück) dataset. For numerical experiments, we applied only the proton-induced ionization rates of that period, while all the other model input parameters, including the electron precipitations, corresponded to the quiet conditions. In January 2005, two major solar proton events with different energy spectra and proton fluxes occurred on January 17 and January 20. Since two geomagnetic storms and several sub-storms took place during the considered period, not only solar protons but also less energetic magnetospheric protons contributed to the calculated ionization rates. Despite the relative transparency of the thermosphere for high-energy protons, an ionospheric response to the SPE and proton precipitation from the magnetotail was obtained in numerical experiments. In the ionospheric E layer, the maximum increase in the electron concentration is localized at high latitudes, and at heights of the ionospheric F2 layer, the positive perturbations were formed in the near-equatorial region. An analysis of the model-derived results showed that changes in the ionospheric F2 layer were caused by a change in the neutral composition of the thermosphere. We found that in the recovery phase after both solar proton events and the enhancement of magnetospheric proton precipitations associated with geomagnetic disturbances, the TEC and electron density in the F region and in topside ionosphere/plasmasphere increase at low- and mid-latitudes due to an enhancement of atomic oxygen concentration. Our results demonstrate an important role of magnetospheric protons in the formation of negative F-region ionospheric storms. According to our results, the topside ionosphere/plasmasphere and bottom-side ionosphere can react to solar and magnetospheric protons both with the same sign of disturbances or in different way. The same statement is true for TEC and foF2 disturbances. Different disturbances of foF2 and TEC at high and low latitudes can be explained by topside electron temperature disturbances.     

关于去月球，火星及其测量问题

世界人口以级数式或指数式规律增长，而资源则是有限值。本文由此出发，对世界人口平均密度进行计算后，提出必须积极考虑向地球外移民的观点，并对其可能性及存在问题作了详尽的的科学分析。指出：最重要的目标是向火星移民，而月球是这一努力的跳板。对有关测量技术和科学研究作了论述，认为已有的大量工作创设了良好的条件，但仍有许多高难科技问题有待解决。最后，认为中国作为世界。上头号人口大国，必须早日为参加向火星移民作好准备。     

钛合金铣削刀具/工件接触区域温度预测

钛合金（Ti-6Al-4V）因其优良的综合性能广泛应用于航空航天领域中,然而由于其导热系数低、弹性模量低等特性,铣削加工过程中刀具/工件接触区域温度过高,从而导致刀具磨损严重,影响已加工表面质量。因此研究切削过程中刀具/工件接触区域温度具有重要意义。从切削机理出发,将切削区域的3个热源等效为螺旋线热源,其中热流密度计算类比铣削力预测模型中铣削力计算方法,提出包含铣削热系数的热流密度计算模型,并通过实验标定铣削热系数,结果表明热流密度随切削厚度增加接近于线性增加。建立刀具/工件接触区域温度预测模型,通过半人工热电偶测温实验对模型的可行性与准确性进行了验证,实验值与预测值的相对误差在10%之内。提高了刀具/工件接触区域温度的计算精度,并为切削参数的合理选择提供理论基础。     

激光选区熔化成形SiCP/AlSi10Mg复合材料工艺及性能研究

为研究激光选区熔化(SLM)成形技术制备SiC颗粒增强AlSi10Mg复合材料的成形机理,开展了SLM成形工艺参数(扫描间距、扫描速度)对致密度、机械性能等影响情况的研究。结果表明:所制备试样中SiC增强颗粒分布均匀,并与基体具有连续相容的冶金结合界面。当激光扫描速度从900 mm/s升高到2 100 mm/s时,在不同的扫描间距下,复合材料试样致密度均随之降低;当扫描间距在0.09～0.12 mm内变化时,在不同的扫描速度下,致密度变化趋势并不一致;在激光功率490 W、铺粉层厚0.04 mm、扫描间距0.12 mm、扫描速度900 mm/s时,制备的SiC颗粒增强AlSi10Mg复合材料试样得到最佳综合性能(相对密度99.1%,显微硬度198.7 HV0.2,抗拉强度341.9 MPa);在该最佳工艺参数下,成功制备出复杂结构的薄壁零件。研究为SLM成形SiCP/AlSi10Mg复合材料在航空航天和空间领域的应用提供了理论基础和实验依据。     

PMMA激光点火特性研究

采用CO2激光点火实验系统,研究了常压下PMMA的点火过程以及点火延迟时间与点火热流密度的关系。研究结果表明,随点火热流密度的增加,PMMA的点火延迟时间减少;当点火热流密度大于286 W/cm2时,热流密度对点火延迟时间的影响变小;当点火热流密度较低时,点火延迟时间随着热流密度的减小而急剧增加,且存在点火的最低能量阈值。最后,给出了常压下热流密度范围为70～881 W/cm2内的PMMA点火延迟时间与点火热流密度的数学关系式。     

Calibration errors in determining slant Total Electron Content (TEC) from multi-GNSS data

The global navigation satellite system (GNSS) is presently a powerful tool for sensing the Earth's ionosphere. For this purpose, the ionospheric measurements (IMs), which are by definition slant total electron content biased by satellite and receiver differential code biases (DCBs), need to be first extracted from GNSS data and then used as inputs for further ionospheric representations such as tomography. By using the customary phase-to-code leveling procedure, this research comparatively evaluates the calibration errors on experimental IMs obtained from three GNSS, namely the US Global Positioning System (GPS), the Chinese BeiDou Navigation Satellite System (BDS), and the European Galileo. On the basis of ten days of dual-frequency, triple-GNSS observations collected from eight co-located ground receivers that independently form short-baselines and zero-baselines, the IMs are determined for each receiver for all tracked satellites and then for each satellite differenced for each baseline to evaluate their calibration errors. As first derived from the short-baseline analysis, the effects of calibration errors on IMs range, in total electron content units, from 1.58 to 2.16, 0.70 to 1.87, and 1.13 to 1.56 for GPS, Galileo, and BDS, respectively. Additionally, for short-baseline experiment, it is shown that the code multipath effect accounts for their main budget. Sidereal periodicity is found in single-differenced (SD) IMs for GPS and BDS geostationary satellites, and the correlation of SD IMs over two consecutive days achieves the maximum value when the time tag is around 4?min. Moreover, as byproducts of zero-baseline analysis, daily between-receiver DCBs for GPS are subject to more significant intra-day variations than those for BDS and Galileo.     

A Partially Orthogonal EnKF approach to atmospheric density estimation using orbital debris

A key requirement for accurate trajectory prediction and space situational awareness is knowledge of how non-conservative forces affect space object motion. These forces vary temporally and spatially, and are driven by the underlying behavior of space weather particularly in Low Earth Orbit (LEO). Existing trajectory prediction algorithms adjust space weather models based on calibration satellite observations. However, lack of sufficient data and mismodeling of non-conservative forces cause inaccuracies in space object motion prediction, especially for uncontrolled debris objects. The uncontrolled nature of debris objects makes them particularly sensitive to the variations in space weather. Our research takes advantage of this behavior by utilizing observations of debris objects to infer the space environment parameters influencing their motion.The hypothesis of this research is that it is possible to utilize debris objects as passive, indirect sensors of the space environment. We focus on estimating atmospheric density and its spatial variability to allow for more precise prediction of LEO object motion. The estimated density is parameterized as a grid of values, distributed by latitude and local sidereal time over a spherical shell encompassing Earth at a fixed altitude of 400 km. The position and velocity of each debris object are also estimated. A Partially Orthogonal Ensemble Kalman Filter (POEnKF) is used for assimilation of space object measurements to estimate density.For performance comparison, the scenario characteristics (number of objects, measurement cadence, etc.) are based on a sensor tasking campaign executed for the High Accuracy Satellite Drag Model project. The POEnKF analysis details spatial comparisons between the true and estimated density fields, and quantifies the improved accuracy in debris object motion predictions due to more accurate drag force models from density estimates. It is shown that there is an advantage to utilizing multiple debris objects instead of just one object. Although the work presented here explores the POEnKF performance when using information from only 16 debris objects, the research vision is to utilize information from all routinely observed debris objects. Overall, the filter demonstrates the ability to estimate density to within a threshold of accuracy dependent on measurement/sensor error. In the case of a geomagnetic storm, the filter is able to track the storm and provide more accurate density estimates than would be achieved using a simple exponential atmospheric density model or MSIS Atmospheric Model (when calm conditions are assumed).     

低纬100—200km间电子数密度的变化

利用光化平衡模式计算了低纬100—200km间白天电子数密度的变化。求得E-F₁谷区的谷深,谷宽、谷高的变化特征。获得如下结果:a.太阳活动明显影响电子数密度随高度及太阳天顶角的变化,发现太阳活动指数与电子数密度间不仅存在正相关,而且存在负相关;b.太阳活动明显影响E-F₁谷区的形态。在一定太阳活动条件下,对同一太阳赤纬和地理纬度,谷深、谷宽与太阳天顶角的关系难以用一简单函数来表示;c.太阳耀斑、地磁活动对该区电子密度有明显影响;d.在讨论100—200km间电子密度时不能忽略O⁺（2P）和NO的光电离率。     

基于CPHD的双层粒子滤波目标跟踪算法

常规基于势概率假设密度滤波(Cardinalized Probability Hypothesis Density,CPHD)的粒子滤波(Particle Fil? ter,PF)跟踪算法应用于多目标跟踪时,容易遇到因粒子数量增加而带来的运算效率下降、目标数目估计不准的问题。文章基于常规粒子滤波 CPHD跟踪算法,通过部署双层粒子,提出基于势概率假设密度滤波的双层粒子滤波 (Two-Layer Particle Filter-CPHD,TLPF-CPHD)算法,以便提高目标数目及状态估计精度。仿真实验结果证明,相比于常规 PF-CPHD算法,新算法具有更好的目标数目和状态估计准确性。     

航空电机及控制器的温度场仿真分析

对一种航空用高功率密度无刷直流电机,建立电机和控制器一体的三维热仿真模型。根据电机系统内部热交换及传热学相关理论,确定系统内散热系数与热边界条件,利用有限元分析软件ANSYS Workbench对建立的热仿真模型进行温度场仿真与分析,得到了不同环境温度变化情况下电机和控制器的温度场分布和温度对时间变化的曲线。经与试验得到数据进行对比分析,验证了仿真的准确性。这对电机和控制器的设计与温度场计算提供了依据。