80°三角翼流动显示和涡频测量试验研究

在中国航空工业空气动力研究院FL-5低速风洞进行了80°三角翼流动显示和涡频测量试验研究.介绍了能产生扫描式6片光的旋转镜平行多片光装置;介绍了能产生连续、均匀的示踪粒子且粒子浓度可调的气压式粒子发生器;介绍了测量涡跳动频率的光学方法和用应变天平测量模型抖动频率的方法,并对大迎角和大滚转角时涡跳动频率和模型抖动频率进行了测量,结果表明:a=42°、φ=42°时模型抖动频率(7.2Hz)和涡跳动频率(7.75Hz)接近,模型的抖动可能是由前缘涡的非定常跳动引起的;介绍了流动图像处理的相位平均技术,该技术可用于动态流动显示和测量,并可对动态迟滞效应进行定量分析;介绍了流动显示图像的三维重建技术,该技术可用于显示空间涡的结构并分析其机理.     

基于SP+模型的航空锂离子电池组优化技术研究

随着多电飞机技术与锂离子电池技术的发展,锂离子电池已经广泛应用于航空领域,除作为应急电池外,越来越多地作为动力电池应用于飞机。因飞机对锂离子电池组质量、体积等特性具有很高的要求,需要对其进行优化设计,而采用基于模型的方法开展优化设计可以有效减少成本并缩短周期。由于SP+电化学模型能够准确反映锂离子电池的工作机理,同时具有精度高、计算简便等特点,因此文中采用SP+模型构建锂离子电池组模型并进行了验证。同时,以典型的用电工况为例,开展了航空锂电池组的优化设计,实现了对锂离子电池组质量与体积的优化。     

由太阳爆发事件特征预报地磁暴方法研究

CME是非重现性地磁暴的诱因,通过对太阳耀斑爆发活动的特征与可能引起地磁活动的CME进行统计分析,发现太阳耀斑的强度、位置、持续时间以及耀斑所伴随的太阳质子事件和行星际高能质子通量的增长与CME的特征及可能产生的地磁扰动有着密切的关系.在对数据分析的基础上,建立了基于人工神经网络的预报模式,对太阳耀斑爆发活动所引起的地磁扰动的发生及Ap指数进行了预报,取得了较好的结果.      

基于PCA-MPSO-ELM的空战目标威胁评估

目标威胁评估是空战对抗过程中的关键环节。由于影响空战目标威胁评估的因素复杂多样，且指标之间存在相关性，导致传统的评估算法无法得到准确客观的评估结果。由此，提出了一种基于主成分分析法和改进粒子群算法优化的极限学习机（PCA-MPSO-ELM）的目标威胁评估算法。首先，综合分析了影响目标威胁程度的指标，利用主成分分析法对原始评估指标进行线性变化处理得到综合变量，消除了评估指标之间的相关性，实现了对评估数据的降维；在此基础上，构建ELM神经网络并利用改进的粒子群算法优化极限学习机的输入权值和阈值，提高了目标威胁评估模型的精度。最后，在空战训练测量仪中选取空战对抗数据，利用威胁指数法构造了目标威胁评估样本数据，通过仿真实验分析了PCA-MPSO-ELM算法的精度和实时性，结果表明所提算法可以快速准确地进行空战目标威胁评估。     

Magnetic connectivity and solar energetic proton event intensity profiles at deka-MeV energy

We present an analysis of the time-intensity profiles of 25 solar energetic proton events at 18.2 MeV, modelled by fitting an analytical function form (a modified Weibull function) to the observed intensities. Additionally relying on previous work that characterized the magnetic connectivity between the event-related solar flare and the observer in these events with three angular parameters, we investigate the fit function parameters, the connectivity parameters, and the iron-to-carbon ratio of the events for dependencies and correlations. We find that the fit parameter controlling the basic shape of the profile (parameter a) is not clearly dependent on the connectivity parameters or the Fe/C ratio, suggesting that the profile shapes of neither well and weakly connected nor generally “impulsive” and “gradual” events differ systematically during the early stages of the event at 1 AU. In contrast, the time scaling of the fit function (parameter b) is at least moderately correlated with both the magnetic connectivity parameters and the Fe/C ratio, in that well-connected and iron-rich events are typically shorter in relative duration than weakly connected and nominal-abundance events; intensity rise times display a similar correlation with the connectivity parameters. We interpret the former result as following from the combined effect of various transport processes acting on the particles in interplanetary space, while the latter is essentially consistent with established knowledge regarding the observed dependence of the time-intensity profile shapes of solar energetic particle events on their magnetic connectivity and heavy ion abundances. The desirability of modelling the particle transport effects in detail and extending the analysis to cover higher energies is indicated.     

用于粒子分离器的砂粒反弹特性实验研究

针对砂粒反弹特性所面临的基础问题及其复杂特点,采用实验与理论分析的方法研究砂粒反弹机理。以砂粒与板面碰撞反弹为起点,自行设计了测量砂粒反弹系数的实验系统,并用高速摄影仪捕捉砂粒的运动轨迹,通过图像处理获得不同粒径的砂粒与不同材料的板面碰撞前后的速度矢量。以实验测量数据为基础,理论分析砂粒运动特性,总结砂粒反弹系数与入射角度之间的关系,建立不同材料的砂粒反弹系数的拟合公式,为进一步提高粒子分离器的分离效率提供研究基础与理论支撑。     

无人机参数优化自抗扰编队保持控制器设计

针对无人机编队飞行中的队形保持问题,采用结合粒子群算法的自抗扰控制技术对控制器进行设计,使响应过程具有良好的动态品质和较小的稳态误差。建立三维空间内基于相对误差的无人机编队飞行模型,并在此基础上设计了跟踪微分器、扩展状态观测器和非线性状态反馈自抗扰控制器,采用粒子群算法对控制器中部分参数进行优化整定。仿真结果表明,设计的结合粒子群算法的改进自抗扰控制器具有良好的控制性能,能以较高的精度实现无人机编队保持任务。     

Location layout design of aircraft parts assembly based on MSVR

Location layout of aircraft assembly is an important factor affecting product quality. Most of the existing re-searches use the combination of finite element analysis and intelligent algorithm to optimize the location layout, which are limited by numerical simulation accuracy and the selection and improvement of intelligent algorithms. At present, the analysis and decision-making technology based on field data is gradually applied in aircraft manufacturing. Based on the perception data of intelligent assembly unit of aircraft parts, a regression model of multi-input and multi-output support vector machine with Gauss kernel function as radial basis function is established, and the hyperparameters of the model are optimized by hybrid particle swarm optimization genetic algorithm (PSO-GA). GA-MSVR, PSO-MSVR and PSOGA-MSVR model are constructed respectively, and their results show that PSOGA-MSVR model has the best performance. Finally, the design of the aircraft wing location layout is taken as an example to verify the effectiveness of the method.     

Energization of charged particle in a time-dependent chaotic magnetic field with an implication of the production of seed particles in solar energetic particle events

We investigate the acceleration of charged particles in a time-dependent chaotic magnetic field in this work. In earlier works, it has been demonstrated that in an asymmetric wire-loop current systems (WLCSs), the magnetic field is of chaotic in nature. Furthermore, observations also showed that there exist time-varying current loops and current filaments in solar corona. It is therefore natural to conceive that the magnetic field on the solar surface is chaotic and time-dependent. Here, we develop a numerical model to study the acceleration process of charged particles in a time-varying chaotic magnetic field that is generated by an ensemble of 8 WLCSs. We found that the motion of energetic particles in the system is of diffusive in nature and a power law spectrum can quickly develop. The mechanism examined here may serve as an efficient pre-acceleration mechanism that generates the so-called seed particles for diffusive shock acceleration at a coronal mass ejection (CME) driven shock in large solar energetic particle (SEP) events.     

基于方位信息的组网雷达跟踪滤波研究

干扰对组网雷达目标跟踪系统模型的影响,决定了系统需要用非线性滤波技术进行纯方位跟踪.粒子滤波避免了传统非线性滤波方法的缺陷,但是存在粒子退化,于是用EKF和UKF在每一时刻更新粒子,用更新的粒子及其协方差构造重要性函数,然后重采样.仿真实验表明了这两种改进粒子滤波方法的有效性.