可靠性设计优化的球空间设计法

可靠性设计优化（RBDO）在航空航天等领域已经被广泛应用,具有显著提高可靠性的效果;然而它包含两个迭代循环-总体优化循环和可靠性分析循环,双循环求解方法效率低下甚至难以承受。本文提出一种可以提高可靠性设计优化求解效率的方法-球空间设计法,该方法可以方便地表达搜索区域,最大可能失效点可以从极值点处精确获取;同时,该方法可以将总体优化以及可靠性分析同步进行。本文所提出的球空间法的有效性将通过2个算例进行测试,测试结果表明该方法不仅精度与同类方法持平,求解效率有明显提升,它将会对提高航空航天装备如卫星、火箭、飞行器等产品的可靠性提供更为有效的方法和技术支持。     

惯性坐标系下的旋翼气弹稳定性建模

为了较好地描述直升机铰接式、无铰式及无轴承式旋翼的动力学特性,本文根据Hamilton原理。采用中等变形粱理论,用Chopra的15自由度有限元梁元进行离散,并将挥舞、摆振和变距铰运动作为广义坐标,采用二维准定常气动力模型,直接在惯性坐标系下,建立了旋翼气弹分析的动力学模型,并用Pitt—Peters动态入流模型计入动态入流对稳定性的影响。本文基于惯性坐标系的旋翼气弹建模方法简化了建模,方便地嵌入了动态入流模型。通过与Princeton粱实验数据、ITR旋翼试验数据和直升机分析软件UMARC的计算值的对比,验证了本气弹分析模型的正确性,指出误差来源于气动模型。     

深空合作目标高概率捕获复合扫描策略研究

针对深空目标长距离星间激光通信时间滞后大、光轴抖动明显、不确定区域大的问题,设计了一种基于两级执行机构的抗抖动高概率捕获复合扫描策略。将目标位置不确定区域划分为等大正方形子区域,在子区域内采用光栅扫描,通过快摆镜实现;在子区域间按照光栅螺旋扫描顺序覆盖,通过伺服转台实现子区域间的跳转。然后在考虑光轴抖动的情况下基于遗传算法对子区域大小、扫描光斑重叠大小进行了优化,得到了参数优化后的扫描方案,并通过仿真进行了验证。1000次蒙特卡洛打靶结果表明,在目标位置不确定区域3.6mrad、激光束散角0.1mrad、光轴抖动标准差5μrad的情况下,优化后的扫描方案对目标的捕获概率为99.2%,对不确定区域的扫描时间为41.34s,扫描到目标的平均扫描时间为9.62s。     

B-SURF三维CAD系统及其在无人机研制中的应用

本文所讨论的B-SURF三维CAD系铣包括3-D几何设计与外形数值计算、3-D图形变换及处理、数控绘图与数控加工自动编程等部分,能实现CAD/CAM方面的十个功能。该系统以造型能力较强的重节点非均匀B样条方法为基础,并把重节点的信息应用到后置处理中去,以充分体现出该方法的优越性。系统具有一定的通用性,可用于无人机、轻小型飞机、汽车及其它具有复杂外形产品的几何设计与制造。     

基于Abaqus-Isight的飞机舱门密封件的联合优化设计

为了适应飞机舱门密封件研制周期较短以及正向设计的发展趋势,基于Abaqus-Isight软件对飞机舱门密封件进行仿真分析和优化设计,同时校准了材料参数,提出了两种对飞机舱门密封件的优化设计方法,通过对比得到更优的密封件结构。通过试验得到橡胶与织物的材料参数,基于Abaqus-Isight对材料参数进行校核,通过试验得到的压缩试验曲线对材料参数进行修正,得到与成品试验拟合度更高的材料参数;基于Abaqus-Isight对飞机舱门密封件进行DOE正交试验优化设计,将产品结构参数作为变量,压缩力、接触压力、摩擦损耗能作为优化目标,可以得到局部最优结构;将DOE正交试验结果拟合得到近似模型,通过Isight的近似模型算法得到全局最优结构,综合评估采用近似模型算法能够得到更为优异的结果。     

Very low frequency interferometry for the Chang’E-2 project

Very low frequency interferometry among two astronomical experiments has been proposed and accepted for further study for the second phase of China’s lunar exploration programme (the Chang’E Programme), which is envisaged to operate a lander and a rover on the surface of the moon. This experiment is an interferometer experiment in the very low frequency (VLF, f < 15 MHz) regime of radio frequencies with at least degree-level angular resolution. The goals include observing solar storm activities, Coronal Mass Ejections, Auroral Kilometric Radiation, and planetary radiation in the solar system, studying the origin of Cosmic Rays, spectral properties of pulsars, surveying ionized hydrogen in the Galaxy, and exploring coherent radio emissions.     

Using the radial basis function neural network to predict ionospheric critical frequency of F2 layer over Wuhan

Neural networks (NNs) have been applied to ionospheric predictions recently. This paper uses radial basis function neural network (RBF-NN) to forecast hourly values of the ionospheric F₂ layer critical frequency(f_oF₂), over Wuhan (30.5N, 114.3E), China. The false nearest neighbor method is used to determine the embedding dimension, and the principal component analysis (PCA) is used to reduce noise and dimension. The whole study is based on a sample of about 26,000 observations of f_oF₂ with 1-h time resolution, derived during the period from January 1981 to December 1983. The performance of RBF-NN is estimated by calculating the normalized root-mean-squared (NRMSE) error, and its results show that short-term predictions of f_oF₂ are improved.     

Comparison of ionospheric F2 peak parameters foF2 and hmF2 with IRI2001 at Hainan

Monthly median values of foF2, hmF2 and M(3000)F2 parameters, with quarter-hourly time interval resolution for the diurnal variation, obtained with DPS4 digisonde at Hainan (19.5°N, 109.1°E; Geomagnetic coordinates: 178.95°E, 8.1°N) are used to investigate the low-latitude ionospheric variations and comparisons with the International Reference Ionosphere (IRI) model predictions. The data used for the present study covers the period from February 2002 to April 2007, which is characterized by a wide range of solar activity, ranging from high solar activity (2002) to low solar activity (2007). The results show that (1) Generally, IRI predictions follow well the diurnal and seasonal variation patterns of the experimental values of foF2, especially in the summer of 2002. However, there are systematic deviation between experimental values and IRI predictions with either CCIR or URSI coefficients. Generally IRI model greatly underestimate the values of foF2 from about noon to sunrise of next day, especially in the afternoon, and slightly overestimate them from sunrise to about noon. It seems that there are bigger deviations between IRI Model predictions and the experimental observations for the moderate solar activity. (2) Generally the IRI-predicted hmF2 values using CCIR M(3000)F2 option shows a poor agreement with the experimental results, but there is a relatively good agreement in summer at low solar activity. The deviation between the IRI-predicted hmF2 using CCIR M(3000)F2 and observed hmF2 is bigger from noon to sunset and around sunrise especially at high solar activity. The occurrence time of hmF2 peak (about 1200 LT) of the IRI model predictions is earlier than that of observations (around 1500 LT). The agreement between the IRI hmF2 obtained with the measured M(3000)F2 and the observed hmF2 is very good except that IRI overestimates slightly hmF2 in the daytime in summer at high solar activity and underestimates it in the nighttime with lower values near sunrise at low solar activity.     

GNSS Satellite Autonomous Integrity Monitoring (SAIM) using inter-satellite measurements

Integrity is the ability of Global Navigation Satellite Systems (GNSS) to detect faults in measurements and provide timely warnings to users and operators when the navigation system cannot meet the defined performance standards, which is of great importance for safety of life critical applications. Compared with both Receiver Autonomous Integrity Monitoring (RAIM) and ground based GNSS Integrity Channel (GIC) methods which are widely adopted nowadays, the Satellite Autonomous Integrity Monitoring (SAIM) method can be used to monitor orbit/ephemeris and clock errors, and has advantages in monitoring orbit and clock quality and providing instantaneous responses when faults happen.     

一种新的星载自动识别系统检测概率计算方法

针对现有星载AIS检测概率计算方法没有考虑不同解调算法对检测结果影响的问题,提出了一种基于泊松分布船舶检测模型的星载AIS检测概率计算方法。该方法首先计算混叠信号功率差和频差的联合概率分布,以及算法的解调概率,进而将两者相结合得到表征算法能力的关键参数,代入AIS检测概率模型进行计算,可使得原有模型具有适应不同解调算法的能力。仿真表明该方法可有效应用于实际工程的评估,对星载AIS的系统设计有重要的参考价值。