Prediction of forming limit curve （FLC） for AI-Li alloy 2198-T3 sheet using different yield functions

The Forming Limit Curve （FLC） of the third generation aluminum-lithium （Al-Li） alloy 2198-T3 is measured by conducting a hemispherical dome test with specimens of different widths. The theoretical prediction of the FLC of 2198-T3 is based on the M-K theory utilizing respectively the von Mises, Hill＇48, Hosford and Barlat 89 yield functions, and the different predicted curves due to different yield functions are compared with the experimentally measured FLC of 2198-T3. The results show that though there are differences among the four predicted curves, yet they all agree well with the experimentally measured curve. In the area near the planar strain state, the predicted curves and experimentally measured curve are very close. The predicted curve based on the Hosford yield function is more accurate under the tension-compression strain states described in the left part of the FLC, while the accuracy is better for the predicted curve based on Hill＇48 yield function under the tension-tension strain states shown in the right part.     

Prediction of forming limit curve (FLC) for Al-Li alloy 2198-T3 sheet using different yield functions

The Forming Limit Curve (FLC) of the third generation aluminum-lithium (Al-Li) alloy 2198-T3 is measured by conducting a hemispherical dome test with specimens of different widths. The theoretical pred...     

面向海洋机动目标跟踪监视的卫星重构组网优化与仿真

摘要： 针对海洋机动目标跟踪监视问题，提出通过卫星相位重构调整进行机动目标搜索跟踪的监视策略，构建地理坐标系下机动目标航位预测模型及基于霍曼转移的卫星调相组网方式，并采用NSGA II算法进行优化求解，对比分析卫星重构组网前后的机动目标发现概率.仿真结果表明：在卫星能量消耗允许范围内进行重构组网，能够有效提升对机动目标的发现概率，为海洋机动目标的搜索跟踪问题提供了一定的方法支持.     

电子设备故障预测与健康管理技术发展新动态

电子设备是各类航空、航天等高新技术装备必不可少的重要组成部分。与机械类设备存在明显退化状态征兆不同，电子设备退化状态无明显的外在表现，尚无有效征兆对其状态进行刻画，对其进行故障预测与健康管理存在一定的困难。针对该问题，梳理了电子设备故障预测与健康管理技术的基本概念和内涵，介绍了电子设备故障预测与健康管理技术的国内外研究现状，分析了当前复杂电子设备故障预测与健康管理技术面临的挑战和对策。在此基础上，结合未来复杂电子设备新特点及该领域最新研究进展，从基于间歇故障特征的健康状态表征、面向故障预测与健康管理的测试性设计和多源特征融合的健康状态评估等方面，提出了电子设备故障预测与健康管理技术发展的新方向。     

Uncertainty propagation for statistical impact prediction of space debris

Predictions of the impact time and location of space debris in a decaying trajectory are highly influenced by uncertainties. The traditional Monte Carlo (MC) method can be used to perform accurate statistical impact predictions, but requires a large computational effort. A method is investigated that directly propagates a Probability Density Function (PDF) in time, which has the potential to obtain more accurate results with less computational effort. The decaying trajectory of Delta-K rocket stages was used to test the methods using a six degrees-of-freedom state model. The PDF of the state of the body was propagated in time to obtain impact-time distributions. This Direct PDF Propagation (DPP) method results in a multi-dimensional scattered dataset of the PDF of the state, which is highly challenging to process. No accurate results could be obtained, because of the structure of the DPP data and the high dimensionality. Therefore, the DPP method is less suitable for practical uncontrolled entry problems and the traditional MC method remains superior. Additionally, the MC method was used with two improved uncertainty models to obtain impact-time distributions, which were validated using observations of true impacts. For one of the two uncertainty models, statistically more valid impact-time distributions were obtained than in previous research.     

PCE方法在空间实验室轨道预报误差分析中的应用

应用多项式混沌展开法(PCE)进行空间实验室轨道预报误差分析。通过构建PCE模型对轨道预报的不确定性传播过程进行近似，进而对轨道预报后航天器位置和速度的误差进行分析。分析了不同PCE模型阶数、预报时长以及样本点的数目对构建PCE模型的影响。综合考虑精度和计算效率，给出了适用于空间实验室轨道预报误差分析的PCE模型。将PCE方法与传统方法进行对比，结果表明PCE方法有较好的非线性近似能力，且计算效率高，验证了PCE方法应用于空间实验室轨道预报误差分析的有效性。     

A novel predictive algorithm for double difference observations of obstructed BeiDou geostationary earth orbit (GEO) satellites

Transmission link disturbances and device failure cause global navigation satellite system (GNSS) receivers to miss observations, leading to poor accuracy in real-time kinematic (RTK) positioning. Previously described solutions for this problem are influenced by the length of the prediction period, or are unable to account for changes in receiver state because they use information from previous epochs to make predictions. We propose an algorithm for predicting double difference (DD) observations of obstructed BeiDou navigation system (BDS) GEO satellites. Our approach adopts the first-degree polynomial function for predicting missing observations. We introduce a Douglas-Peucker algorithm to judge the state of the rover receiver to reduce the impact of predictive biases. Static and kinematic experiments were carried out on BDS observations to evaluate the proposed algorithm. The results of our navigation experiment demonstrate that RTK positioning accuracy is improved from meter to decimeter level with fixed ambiguity (horizontal?<?2?cm, vertical?<?18?cm). Horizontal accuracy is improved by over 50%, and the vertical accuracies of the results of the static and kinematic experiments are increased by 47% and 27% respectively, compared with the results produced by the classical approach. Though as the baseline becomes longer, the accuracy is weakened, our predictive algorithm is an improvement over existing approaches to overcome the issue of missing data.     

飞行状态对太阳能飞机中组件性能的影响

基于光伏组件产生功率模型，研究了太阳能飞机中飞行速度、高度、时间及区域等状态参数影响组件性能的规律。以单晶硅组件及Xihe太阳能飞机为研究对象，当飞机飞行速度增加时，组件产生的功率随之增加但趋于饱和。原因在于速度的增加能有效降低组件的表面温度，但提升是有限的。飞机所需的功率随飞行速度呈现指数增加，且组件产生的功率与飞机所需的功率有能量平衡点。组件产生的功率随飞行高度的增加而增加，但有饱和的趋势。原因在于，当飞行高度上升，大气温度随之下降，组件表面温度下降；同时海拔越高，大气密度和大气通透率越大，太阳辐射增加，从而组件产生的功率增加了；饱和的原因在于组件本身性能的限制。一天之中，组件产生的功率基本以太阳时12点为中心左右近似对称，中午最强；一年中组件性能在夏季最强，冬季最弱。原因在于组件性能主要由所受太阳辐射决定。随着纬度的增加，组件产生的功率减小。原因在于，纬度越高，太阳高度角越小，组件所能接受到的太阳辐射也就越小；纬度越低，组件总产生功率越高且平稳。纬度低的地区更适合太阳能飞机的飞行。该文为太阳能飞机的能量分配、长时间驻空提供一定的帮助。     

The impact of different background errors in the assimilation of satellite radiances and in-situ observational data using WRFDA for three rainfall events over Iran

Satellite radiances and in-situ observations are assimilated through Weather Research and Forecasting Data Assimilation (WRFDA) system into Advanced Research WRF (ARW) model over Iran and its neighboring area. Domain specific background error based on x and y components of wind speed (UV) control variables is calculated for WRFDA system and some sensitivity experiments are carried out to compare the impact of global background error and the domain specific background errors, both on the precipitation and 2-m temperature forecasts over Iran. Three precipitation events that occurred over the country during January, September and October 2014 are simulated in three different experiments and the results for precipitation and 2-m temperature are verified against the verifying surface observations. Results show that using domain specific background error improves 2-m temperature and 24-h accumulated precipitation forecasts consistently, while global background error may even degrade the forecasts compared to the experiments without data assimilation. The improvement in 2-m temperature is more evident during the first forecast hours and decreases significantly as the forecast length increases.