Neural network development for the forecasting of upper atmosphere parameter distributions

This paper presents a neural network modeling approach to forecast electron concentration distributions in the 150–600 km altitude range above Arecibo, Puerto Rico. The neural network was trained using incoherent scatter radar data collected at the Arecibo Observatory during the past two decades, as well as the Kp geomagnetic index provided by the National Space Science Data Center. The data set covered nearly two solar cycles, allowing the neural network to model daily, seasonal, and solar cycle variations of upper atmospheric parameter distributions. Two types of neural network architectures, feedforward and Elman recurrent, are used in this study. Topics discussed include the network design, training strategy, data analysis, as well as preliminary testing results of the networks on electron concentration distributions.     

Ion production and ionization effect in the atmosphere during the Bastille day GLE 59 due to high energy SEPs

The influence of high energy particles, specifically cosmic rays, on atmospheric physics and chemistry is highly discussed. In most of the proposed models the role of ionization in the atmosphere due to cosmic rays is not negligible. Moreover, effect(s) on minor constituents and aerosols are recently observed, specifically over the polar regions during strong solar particle events. According to the recent findings for such effects it is necessary an essential increase of ion production, specifically during the winter period. The galactic cosmic rays are the main source of ionization in the Earth’s stratosphere and troposphere. Occasionally, the atmospheric ionization is significantly enhanced during strong solar energetic particles events, specifically over the polar caps. During the solar cycle 23 several strong ground level enhancements were observed. One of the strongest was the Bastille day event occurred on 14 July 2000. Using a full Monte Carlo 3-D model, we compute the atmospheric ionization, considering explicitly the contribution of cosmic rays with galactic and solar origin, focusing on high energy particles. The model is based on atmospheric cascade simulation with the PLANETOCOSMICS code. The ion production rate is computed as a function of the altitude above the sea level. The ion production rate is computed on a step ranging from 10 to 30?min throughout the event, considering explicitly the spectral and angular characteristics of the high energy part of solar protons as well as their time evolution. The corresponding event averaged ionization effect relative to the average due to galactic cosmic rays is computed in lower stratosphere and upper troposphere at various altitudes, namely 20?km, 15?km, 12?km and 8?km above the sea level in a sub-polar and polar regions. The 24^h and the weekly ionization effects are also computed in the troposphere and low stratosphere. Several applications are discussed.     

新型高空探测系统

研发了一种新型全自动高空探测系统,其利用GPS定位,宽波瓣天线捕捉和低噪声接收的方法替代雷达或无线电经纬仪对高空探测仪进行跟踪定位和获取信息,具有不受低仰角的限制,目标不易丢失,性能价格比高等特点,成功将GPS应用于1680 MHz遥测数据传输体制.利用该系统进行了空中大气电场的探测实验,获得了满意的探测结果.由于系统轻便、操作简单、成本较低以及良好的机动性和可靠性,在近地空间环境探测和高空大气科学探测试验及常规的气象探测中有广阔的应用前景.     

可重复使用空间站补给方案设想

提出了一种基于我国现有液体上面级的可重复使用太空补给方案,可用于空间站补给运送货物及废弃品转运清理。分析了空间站补给运送的任务模式及工作流程。在总结应用特点的基础上,提出了基于上面级的可重复使用空间站补给的发展路线。最后,对相关关键技术进行了初步分析。     

某型教练机机翼整体油箱上壁板腐蚀原因分析和防腐处理措施

介绍了某型教练机多架机翼整体油箱上壁板在特定位置先后发现的不同程度的腐蚀情况,通过分析当地使用环境和结构特点,找出了壁板发生腐蚀的原因,结合飞机在当地的实际使用环境编制了加速腐蚀试验谱,并设计模拟件进行了加速腐蚀试验验证,确定了防腐处理措施.     

先进上面级变轨段姿态解耦控制研究

针对多星部署先进上面级变轨段三轴姿态严重耦合以及主发动机开机引起的较大干扰力矩问题,研究了基于反馈线性化的姿态解耦算法。通过给出上面级多星部署任务中的坐标系和姿态角定义,建立了欧拉角描述的姿态动力学与运动学方程。分析了推力矢量与姿控发动机的控制方案,描述了该方案中主发动机、伺服机构和姿控发动机的配置结构,推导了推力矢量控制中的主发动机摆角计算公式和主发动机工作时质心偏移引起的干扰力矩。基于反馈线性化理论,设计了上面级姿态解耦控制律。算例验证结果表明姿态角速率误差和姿态角误差能够快速趋于1°/s和0.5°。文中设计的姿态解耦控制算法具有良好的稳定性和可行性。     

一种对流层软式飞艇设计体积估算方法的商榷

出于对对流层软式飞艇动态受力平衡的考虑,分别从一般情况、特定任务和限制飞艇地面净重(轻)情况三个角度分析,尝试建立了飞艇设计体积与携带燃油量的数学关系模型,并利用仿真曲线相交的方法,对飞艇设计体积进行区间估算,以此作为设计目标值的依据.     

A model of foreground emission in UV using GALEX deep observations

Foreground emission, mainly airglow and zodiacal light, is a significant contributor in an ultraviolet observation especially from low earth orbit. Its careful estimation and removal are tedious yet unavoidable processes in the study of diffuse UV radiation and by extension interstellar dust studies. Our analysis of deep GALEX observations show that airglow is not only a function of Sun angle but also a strong function of Solar activity at the time of observation. We present here an empirical model of airglow emission, derived from GALEX deep observations, as a function of 10.7 cm Solar flux and Sun angle. We obtained the model by training machine learning models on the data using a variant of the regression algorithm that is both resilient toward outlier data and sensitive to the complexities of the provided data. Our model predictions across various observations show no loss in generalization as well as good agreement with the observed values. We find that the total airglow in an observation is the sum of a baseline part (AG_c) that depends on the Solar flux and Sun angle, and a variable part (AG_v) that depends on the Sun angle and the time of observation with respect to local midnight. We also find that the total airglow can vary between 85 – 390 photon units in FUV and 80 – 465 photon units in NUV.