离子推力器多模式化研究

为了实现离子推力器多模式化,分析了离子推力器功率宽范围调节限制因素,提出了两种宽范围调节策略;针对我国小行星探测任务,完成了30cm多模式离子推力器研制、功率宽范围调节限制条件确定、以及两种调节策略下多模式工作点设计及对比研究。结果显示,通过降低放电室磁场强度可延伸离子推力器最小稳定工作功率,提高束流均匀性,实现离子推力器更宽功率范围多工作点设计;功率宽范围调节主要是屏栅电压和束电流的宽范围调节,二者通过栅极导流系数限制和交叉限制而约束;推力随功率增加呈线性增加关系,比冲随功率的增加总体上呈先快速增加后趋于稳定的趋势;30cm多模式离子推力器在0.25kW～5kW内稳定工作,推力10mN～186mN,比冲1522s～3586s。     

双燃式冲压发动机中超燃燃烧室冷态流场数值模拟

采用Ｍａｃ Ｃｏｒｍ ａｃｋ 矢通分裂格式, 求解雷诺平均的Ｎ－Ｓ方程组, 采用Ｂａｌｄｗ ｉｎ－Ｌｏ－ｍ ａｘ 代数湍流模型和混合长度模型, 模拟超燃燃烧室内两股平行超声速来流的冷态流场, 取得了与试验相一致的结果, 计算表明回流区和射流流动参数对超燃燃烧室流场内波系的变化有着较大的影响。     

发烟机动力装置的试验研究

简要介绍了发烟机及其动力装置,研究并改进了ＷＱＪ－１型小型航空发动机,使之成为满足发烟要求的动力装置。确定了该发动机在新状态下的参数及结构,进行了发烟机的雾油发烟实验,得到了雾油发烟对发动机的影响及影响程度。实验结果表明：将ＷＱＪ－１型小发动机改为发烟机动力装置是可行的。对发烟机的型号研制和扩展小型航空发动机的使用范围有积极促进作用。     

变温热源内可逆布雷顿循环功率密度优化

计人工质与高、低温侧换热器的热阻损失，用有限时间热力学方法，导出了变温热源条件下内可逆布雷顿循环功率密度与压比间的解析式，借助于数值计算，研究了高、低温侧换热器的热导率分配和工质与热源间的热容率匹配对功率最大密度的影响。     

基于粒子群优化的光伏阵列最大功率点跟踪法研究

光伏阵列在局部阴影条件下,出现反向雪崩效应,导致输出功率出现多个局部极大值点,此时常规的最大功率点跟踪（MPPT）失效。基于比较完善的光伏电池遮挡模型,对光伏阵列进行建模,验证其输出功率的多峰特性。提出一种基于粒子群优化算法（PSO）的多峰最大功率点跟踪方法,并积累粒子个体搜索经验,提高跟踪速度。仿真表明,当外界条件变化时,此方法可以快速跟踪光伏模块的最大功率,从而有效地利用能源。     

导弹动力系统最佳预防维修周期的数字仿真

导弹武器系统中有很多是多次使用的可修复杂系统。对于这种复杂系统，尤其是其寿命周期，预防维修时间及事后维修时间为离散分布时，其最佳预防维修周期难以用一般方法求得。针对这种情况，本文利用蒙特卡罗随机模拟法建立了系统计算模型，并通过模拟计算，得出了最佳预防维修周期的数字仿真结果。此结果可为制定导弹武器最佳修复策略提供依据。     

Noise analysis of continuous GPS coordinate time series for CMONOC

The Crustal Movement Observation Network of China (CMONOC) is one of the major scientific infrastructures, mainly using Global Positioning System (GPS) measurements, to monitor crustal deformation in the Chinese mainland. In this paper, decade-long coordinate time series of 26 continuous GPS sites of CMONOC are analyzed for their noise content using maximum likelihood estimation (MLE). We study the noise properties of continuous GPS time series of CMONOC for the unfiltered, filtered solutions and also the common mode signals in terms of power law plus white noise model. In the spatial filtering, we remove for every time series a common mode error that was estimated from a modified stacking of position residuals from other sites within ∼1000 km of the selected site. We find that the common mode signal in our network has a combination of spatially correlated flicker noise and a common white noise with large spatial extent. We demonstrate that for the unfiltered solutions of CMONOC continuous GPS sites the main colored noise is a flicker process, with a mean spectral index of ∼1. For the filtered solutions, the main colored noise is a general power law process, indicating that a major number of the filtered regional solutions have a combination of noise sources or local effects. The velocity uncertainties from CMONOC continuous GPS coordinate time series may be underestimated by factors of 8–16 if a pure white noise model is assumed. In addition, using a white plus flicker noise model, the median values of velocity errors for the unfiltered solutions are 0.16 (north), 0.17 (east) and 0.58 (vertical) mm/yr, and the median values for the filtered solutions are 0.09 (north), 0.10 (east) and 0.40 (vertical) mm/yr.     

Dynamic neighborhood genetic learning particle swarm optimization for high-power-density electric propulsion motor

To maximize the power density of the electric propulsion motor in aerospace application, this paper proposes a novel Dynamic Neighborhood Genetic Learning Particle Swarm Optimization (DNGL-PSO) for the motor design, which can deal with the insufficient population diversity and non-global optimal solution issues. The DNGL-PSO framework is composed of the dynamic neighborhood module and the particle update module. To improve the population diversity, the dynamic neighborhood strategy is first proposed, which combines the local neighborhood exemplar generation mechanism and the shuffling mechanism. The local neighborhood exemplar generation mechanism enlarges the search range of the algorithm in the solution space, thus obtaining high-quality exemplars. Meanwhile, when the global optimal solution cannot update its fitness value, the shuffling mechanism module is triggered to dynamically change the local neighborhood members. The roulette wheel selection operator is introduced into the shuffling mechanism to ensure that particles with larger fitness value are selected with a higher probability and remain in the local neighborhood. Then, the global learning based particle update approach is proposed, which can achieve a good balance between the expansion of the search range in the early stage and the acceleration of local convergence in the later stage. Finally, the optimization design of the electric propulsion motor is conducted to verify the effectiveness of the proposed DNGL-PSO. The simulation results show that the proposed DNGL-PSO has excellent adaptability, optimization efficiency and global optimization capability, while the optimized electric propulsion motor has a high power density of 5.207 kW/kg with the efficiency of 96.12%.     

大气臭氧地基遥感反演的退卷积方法

本文提出了一种大气臭氧地基遥感信息处理的新方法,它利用非线性退卷积方法和等效仪器函数提高光谱分辨率,利用非线性最小二乘法进行大气臭氧反演计算,可以显着提高大气臭氧遥感的可探测高度和精度。     

冲击响应谱（SRS）分析数字化方法探讨

本文介绍了求单自由度二阶系统冲击响应谱（ＳＲＳ）的几种常用的数字化分析方法：直接积分法；快速富氏变换（ＦＦＴ）法；递推法；数字滤波器方法；改进的数字滤波器方法。并比较了它们的优缺点。