碳化硅颗粒增强铝基复合材料及其口盖的研制

采用一种新型的复合材料替代传统的材料应用于航天产品推进舱上的口盖。经过复合材料制备、预镦粗变形、热轧和冷轧、热处理、表面阳极氧化等工艺过程，成功地制备了ＳｉＣｐ／ＬＤ１０复合材料口盖。探讨了制备过程中的工艺选择和工艺参数，并对复合材料板材的性能进行了测试。     

推进剂稳态燃速最优化辨识

考虑侵蚀燃烧对推进剂稳态燃速的影响,将推进剂稳态燃速模型参数辨识问题转化为非线性规划问题求解。采用Powell方法和并行遗传算法组成的混合优化方法,提高了非线性规划问题求解的效率和质量,得到了推进剂稳态燃速模型参数的全局最优辨识值。通过对设计空间的可视化进行优化收敛过程的参数分析,近似得到侵蚀燃烧模型参数的不确定性区间。     

固体填充剂对推进剂力学性能的影响

借助扫描电子显微镜（SEM）及微型动态拉伸装置测试手段，对含固体颗粒填充剂的丁羟复合固体推进剂（HTPB）和硝酸酯增塑的聚醚高能推进剂（NEPE）中的微相结构进行了断口微观形貌观察和推进剂拉伸试件在拉应力作用下的断裂过程分析。结果表明，固体颗粒的形状，粒径尺寸，粒度分布和级配变化，以及固体填料／粘合剂的界面性质等因素对推进剂力学性能有着重要的影响。     

挠性空间结构变形的自适应辨识

本文以空间控制中的挠性结构变形的辨识为背景,以李雅普诺夫稳定性理论为基础,从辨识的一致性原则出发,给出时变参数的自适应辨识算法。该算法具有梯度型递推形式,结构简单、容易实现。计算机模拟结果表明该算法是解决时变参数辨识的一种有效方法。     

旋转条件下固体火箭发动机三维内流场数值模拟

基于颗粒轨道模型,通过运动方程加入过载加速度的方式建立了旋转条件下固体火箭发动机内三维两相流的数值模型,并利用该模型研究了不同的旋转加速度对固体火箭发动机中粒子运动轨迹以及聚集浓度的影响。结果表明,随着发动机旋转速度的增大,粒子的聚集带逐渐向壁面附近扩散,在发动机的轴向附近形成一个无粒子区域,旋转速度越大,无粒子区域越大;当旋转速度增加到一定值,粒子的聚集带向外扩散至壁面上,在前封头附近的壁面上形成一条与发动机母线成一定夹角的高浓度聚集带。     

脉冲微孔喷射技术及其在增材制造方面的应用

介绍了用于制造单分散球形微米级粒子的脉冲微孔喷射技术.根据微滴制备原理,可将其分为适用于低熔点材料的压片式喷射装置及适用于高熔点材料的传动杆式喷射装置,分别阐述了两种方式的脉冲微孔喷射技术的喷射原理、相关特点以及该技术的发展和研究现状.目前,采用脉冲微孔喷射技术已成功制备出金属、半导体及生体材料单分散微粒子,具有粒径均一、圆球度高等优势.通过与其他微米级粒子制备技术,如均匀液滴喷射法、气动式按需喷射法及雾化法相比较,在诸多方面显示出脉冲微孔喷射法的独特优点.与此同时,分别讨论了脉冲微孔喷射技术在增材制造方面的潜在应用,可直接使用微米级粒子作为增材制造用粉体以及液滴沉积成型.鉴于脉冲微孔喷射技术的独特性,可以预见随着研究的不断深入,脉冲微孔喷射技术将在增材制造方面具有更加广阔的发展空间和应用前景.     

The SEVAN Worldwide network of particle detectors: 10 years of operation

The Space Environment Viewing and Analysis Network (SEVAN) aims to improve the fundamental research on particle acceleration in the vicinity of the sun, on space weather effects and on high-energy physics in the atmosphere and lightning initiation. This new type of a particle detector setup simultaneously measures fluxes of most species of secondary cosmic rays, thus being a powerful integrated device for exploration of solar modulation effects and electron acceleration in the thunderstorm atmosphere. The SEVAN modules are operating at the Aragats Space Environmental Center (ASEC) in Armenia, in Croatia, Bulgaria, Slovakia, the Czech Republic (from 2017) and in India. In this paper, we present the most interesting results of the SEVAN network operation during the last decade. We present this review on the occasion of the 10th anniversary of the International Heliophysical Year in 2007.     

Motion prediction of a non-cooperative space target

Capturing a non-cooperative space target is a tremendously challenging research topic. Effective acquisition of motion information of the space target is the premise to realize target capture. In this paper, motion prediction of a free-floating non-cooperative target in space is studied and a motion prediction algorithm is proposed. In order to predict the motion of the free-floating non-cooperative target, dynamic parameters of the target must be firstly identified (estimated), such as inertia, angular momentum and kinetic energy and so on; then the predicted motion of the target can be acquired by substituting these identified parameters into the Euler’s equations of the target. Accurate prediction needs precise identification. This paper presents an effective method to identify these dynamic parameters of a free-floating non-cooperative target. This method is based on two steps, (1) the rough estimation of the parameters is computed using the motion observation data to the target, and (2) the best estimation of the parameters is found by an optimization method. In the optimization problem, the objective function is based on the difference between the observed and the predicted motion, and the interior-point method (IPM) is chosen as the optimization algorithm, which starts at the rough estimate obtained in the first step and finds a global minimum to the objective function with the guidance of objective function’s gradient. So the speed of IPM searching for the global minimum is fast, and an accurate identification can be obtained in time. The numerical results show that the proposed motion prediction algorithm is able to predict the motion of the target.     

FUZZY IDENTIFICATION METHOD BASED ON A NEW OBJECTIVE FUNCTION

Many fuzzy models on modeling and controlmethods have been developed since Takagi-Sugeno model was proposed[1] .The main prob-lems of the fuzzy identifying method based on T-S model appear in the following two aspects:　　 1 It is important what heuristic knowledgeis chosen to acquire the premise structure of theT- S model.This problem is related to the opti-mal partition of input space of premise part andmodeling accuracy.　　 2 Itis crucial whatidentifying method is u-tilized to estimate …