超跨声速喷流流场的PIV测量

对示踪粒子发生装置和几种粒子的特性进行了实验研究 ,发现压缩空气流中自然存在的润滑油粒子在跟随性、分布的均匀性和稳定性、以及浓度方面对于PIV测量都非常有利。实验成功地应用PIV技术对超跨声速喷流流场进行了测量 ,初步分析了测量结果与理论的差异 ,并分析了实验的可靠性和精度。     

基于随机粒子追踪方法的环形燃烧室点火动态模拟

为了深入研究低排放燃烧室点火联焰规律,在全新的环形模型燃烧室中开展了点火模拟和试验研究。点火模拟采用随机粒子追踪方法,能够基于时均冷态流场的仿真结果快速模拟火焰传播过程。环形燃烧室包含16个中心分级旋流器,仅向预燃级通入丙烷,用于模拟航空发动机低排放燃烧室点火状态下的空气燃油分级。试验采用PIV技术测量3个头部区域流场,利用高速相机拍摄火焰CH*/C2*基团化学发光信号。对多个流量和当量比条件下的联焰过程、联焰时间和传焰速率进行了分析,试验和模拟的结果均表明：环形燃烧室内火焰双向传播,燃烧室内外环流速度差异导致了双向火焰传播速度差,传焰速率随燃烧室湍流速度和当量比的增加而增加。点火模型很好地捕捉了环形燃烧室点火动态,所得传焰速率也符合湍流火焰传播规律,表明该模型具有较强预测能力。     

基于IPSO-Elman神经网络的飞机客舱能耗预测

为了提高飞机客舱使用地面空调制冷时客舱能耗的预测精度,提出了一种改进的粒子群优化（IPSO）Elman神经网络的飞机客舱能耗预测模型。依据对算法中惯性权重与学习因子的收敛域分析,得出了二者合理的取值范围,将粒子到全局最优位置间距离与参数的取值范围相结合,构造了惯性权重与学习因子的动态调节函数,对其进行非线性的动态调节,并引入了变异因子,提出了一种跳出局部最优的策略,防止粒子群优化（PSO）陷入局部最优。将IPSO-Elman应用于Boeing738飞机客舱能耗预测中,与PSO-Elman、Elman算法进行性能比较,仿真结果表明基于IPSO-Elman的客舱能耗预测模型在预测精度和收敛速度方面均有一定的提升。该研究结果为飞机客舱能耗预测模型的建立提供了理论依据,对飞机地面空调的节能与机场电能合理调配提供了支持。     

基于约束优化的舰艇区域防空作战能力需求生成

作战能力需求生成是在满足多约束条件下完成的,寻求约束集是能力需求生成的重点;以舰空导弹区域防空为背景,通过对作战需求约束、能力需求约束、技术发展约束以及其他因素约束进行综合分析,提取制约能力指标生成的约束集,建立舰艇防空作战效能目标函数,采用基于罚函数法的快速粒子群算法进行能力指标的约束优化求解;以最大预警距离为变量,对其他作战能力指标优化前后的曲线图进行仿真验证,定量生成舰艇区域防空作战所需的能力指标值,验证了模型算法的可行性,为舰艇区域防空作战能力需求生成提供了定量化依据。      

碳纤维热导率与其微观结构参数的关系

碳纤维具有多晶多相特性,为了研究微晶结构特性对热导率的影响,本文通过XRD对碳纤维的微观特征结构参数的表征,对导热性能与微观特征结构的关联性进行了研究。研究结果表明,碳纤维热导率随着石墨微晶的基面宽度（L_a）、堆砌厚度（L_c）和平均堆垛层数（N）的增大而增大,随着孔隙率（V_p）的增大而降低。基于Raman图谱的分峰拟合信息,对碳纤维的石墨化度进行分析。结果显示,碳纤维的石墨化度越大,热导率越高。     

Are small-scale field-aligned currents and magnetosheath-like particle precipitation signatures of the same low-altitude cusp?

We examined some 75 observations from the low-altitude Earth orbiting DMSP, Ørsted and CHAMP satellites which were taken in the region of the nominal cusp. Our objective was to determine whether the actually observed cusp locations as inferred from magnetosheath-like particle precipitation (“particle cusp”) and intense small-scale magnetic field variations (“current cusp”), respectively, were identical and were consistent with the statistically expected latitude of the cusp derived from a huge number of charged particle spectrograms (“statistical cusp”).     

矩形截面管道气流中横向运动颗粒的碰壁条件

分析了矩形截面管道气流中横向运动颗粒的运动轨迹及碰壁条件,研究表明颗粒飞出的临界速度随着颗粒直径的增大而减小,当颗粒直径较小时受来流密度、马赫数影响较大,总趋势是来流密度、马赫数越大,颗粒越不容易与上壁面碰撞。但随着颗粒直径的增大,来流条件对颗粒是否碰壁的影响逐渐减弱,决定因素是颗粒直径的大小和颗粒的喷射速度。     

Fault self-repair strategy based on evolvable hardware and reparation balance technology

In the face of harsh natural environment applications such as earth-orbiting and deep space satellites, underwater sea vehicles, strong electromagnetic interference and temperature stress,the circuits faults appear easily. Circuit faults will inevitably lead to serious losses of availability or impeded mission success without self-repair over the mission duration. Traditional fault-repair methods based on redundant fault-tolerant technique are straightforward to implement, yet their area, power and weight cost can be excessive. Moreover they utilize all plug-in or component level circuits to realize redundant backup, such that their applicability is limited. Hence, a novel selfrepair technology based on evolvable hardware（EHW） and reparation balance technology（RBT） is proposed. Its cost is low, and fault self-repair of various circuits and devices can be realized through dynamic configuration. Making full use of the fault signals, correcting circuit can be found through EHW technique to realize the balance and compensation of the fault output-signals. In this paper, the self-repair model was analyzed which based on EHW and RBT technique, the specific self-repair strategy was studied, the corresponding self-repair circuit fault system was designed, and the typical faults were simulated and analyzed which combined with the actual electronic devices. Simulation results demonstrated that the proposed fault self-repair strategy was feasible. Compared to traditional techniques, fault self-repair based on EHW consumes fewer hardware resources, and the scope of fault self-repair was expanded significantly.     

基于自适应容积粒子滤波的车辆状态估计

针对车辆状态估计中由模型的强非线性、噪声的非高斯分布等相关因素导致估计精度下降甚至发散的问题,本文提出了基于自适应容积粒子滤波(Adaptive cubature particle filter,ACPF)的车辆状态估计器。首先基于非稳态动态轮胎模型,构建高维度非线性八自由度车辆模型。其次利用自适应容积卡尔曼滤波(Adaptive cubature Kalman filter,ACKF)算法更新基本粒子滤波(Particle filter,PF)算法的重要性密度函数,以完成自适应容积粒子滤波算法设计。利用车载传感器信息,运用ACPF算法实现对车辆的侧倾角、质心侧偏角等关键状态变量高精度在线观测。搭建Simulink-Carsim联合仿真平台进行了算法的验证,结果表明该算法状态估计精度高于传统无迹粒子滤波(Unscented particle filter,UPF)算法,且算法运算效率高于UPF算法,而传统PF估计值发散。研究结果为实现车辆动力学精准控制提供了理论支持。     

固体发动机喷管出口凝相微粒粒度分布研究

应用激光全息光学诊断方法对固体火箭发动机喷管出口凝相微粒分布进行了测量，并得出了其分布曲线。对凝相微粒数字图像处理算法也进行了研究。