改进的变比热平行混合解析解

鉴于原平行混合准确解牵动到物理过程一般并不经过的临界温度的比热值。在变比热情况容易带来不必要误差，文中推导了只动用总静温、并主要依靠静参数的全套改进解公式，从算例结果看出，原准确误差很小，但改进解不仅更为合理，而且是简明快捷的。所以是先进的。     

HCKF性能评估及其在传递对准中的应用

针对高阶容积卡尔曼滤波(HCKF)算法在传递对准中的应用问题,提出综合运用多变量函数泰勒级数展开和计算复杂度分析的性能评估方法。基于高阶球面-径向容积准则建立HCKF算法模型,并对其估计精度和计算量进行量化和对比分析：HCKF具有5阶泰勒级数展开精度且计算复杂度为O(n 4),综合性能优于高斯厄米特积分滤波(GHQF)和无迹卡尔曼滤波(UKF)。将三种非线性滤波算法应用到舰机大失准角传递对准系统中,摇摆台试验结果表明：HCKF的估计精度比UKF高17%,计算量比GHQF小2个数量级,与HCKF性能评估结果一致。     

多变量线性系统的特征模型及控制方法

对多输入 -多输出高阶线性定常系统从理论上详细推导出了其特征模型 ,并给出了基于特征模型的自适应模糊广义预测控制方案。所建立的特征模型为智能控制器设计和一些高阶对象的低阶控制器设计提供了理论依据 ,特别是为大型空间挠性航天器的控制提供了一种有效的途径。通过对一个航天器控制的仿真研究验证了所给方法的有效性     

多变量线性时变系统的特征模型及自适应模糊控制方法

对于阶数及参数未知的高阶系统，如何设计一个工程上易于实现的低阶控制器，以实现有效的高性能控制，这是目前航天等领域亟待解决的问题。该文采用将对象特征和控制性能要求相结合的方法，对多输入一多输出高阶线性时变系统和一类非线性时变系统从理论上详细推导出了其特征模型，在此基础上设计了基于特征模型的稳定的自适应模糊广义预测控制方案。由于控制结构中使用了分层模糊系统，从而减少了模糊规则数目。通过对一个挠性航天器控制的仿真实验验证了所给方法的有效性。     

某航空发动机机匣的动力学模型修正

利用动力学模型修正技术对某航空发动机机匣的有限元模型进行了修正.通过振动模态测试得到了实际机匣的模态数据用以作为有限元模型 修正的基准.利用频率对单元刚度的灵敏度分析选定了修正区域.在此基础上,应用1阶优化方法对机匣的有限元模型进行修正.研究结果表明:修正后机匣有限元模型的前10阶模态的计算值与实际测试的误差都在29%以内,可以应用在后续的发动机整机动力学分析等方面.      

基于混合求解法的二维多段翼气动噪声特性分析

基于混合求解法,通过对声源区计算域进行分区,研究了二维多段翼不同部件对远场声压级的贡献,给出了声场分布和远场指向性,发现前缘缝翼噪声和主翼尾缘噪声对远场的贡献较小,襟翼后缘噪声的贡献在总声压级中占主导地位,是值得关注的噪声来源。     

The response of the Hermean magnetosphere to the interplanetary magnetic field

The interaction between the solar wind and Mercury is anticipated to be unique because of Mercury’s relatively weak intrinsic magnetic field and tenuous neutral exosphere. In this paper the role of the IMF in determining the structure of the Hermean magnetosphere is studied using a new self-consistent three-dimensional quasi-neutral hybrid model. A comparison between a pure northward and southward IMF shows that the general morphology of the magnetic field, the position and shape of the bow shock and the magnetopause as well as the density and velocity of the solar wind in the magnetosheath and in the magnetosphere are quite similar in these two IMF situations. A Parker spiral IMF case, instead, produces a magnetosphere with a substantial north–south asymmetric plasma and magnetic field configuration. In general, this study illustrates quantitatively the role of IMF when the solar wind interacts with a weakly magnetised planetary body.     

航空发动机排气温度基线建模新方法研究

为实现航空发动机气路性能诊断与预测,提出一种基于堆叠降噪自编码器(Stacked de?noising auto encoder,SDAE)和支持向量回归(Support vector regression,SVR)相结合的航空发动机排气温度(Exhaust gas temperature,EGT)基线建模方法.以CF...     

Gravity Field Recovery from GRACE: Unique Aspects of the High Precision Inter-Satellite Data and Analysis Methods

The very high accuracy of the Doppler and range measurements between the two low-flying and co-orbiting spacecraft of the GRACE mission, which will be at the μm/sec and ≈10 μm levels respectively, requires that special procedures be applied in the processing of these data. Parts of the existing orbit determination and gravity field parameters retrieval methods and software must be modified in order to fully benefit from the capabilities of this mission. This is being done in the following areas: (i) numerical integration of the equations of motion (summed form, accuracy of the predictor-corrector loop, Encke's formulation): (ii) special inter-satellite dynamical parameterization for very short arcs; (iii) accurate solution of large least-squares problems (normal equations vs. orthogonal decomposition of observation equations); (iv) handling the observation equations with high accuracy. Theoretical concepts and first tests of some of the newly implemented algorithms are presented. This revised version was published online in August 2006 with corrections to the Cover Date.     

Human factors quantification via boundary identification of flight performance margin

A systematic methodology including a computational pilot model and a pattern recognition method is presented to identify the boundary of the flight performance margin for quantifying the human factors. The pilot model is proposed to correlate a set of quantitative human factors which represent the attributes and characteristics of a group of pilots. Three information processing components which are influenced by human factors are modeled： information perception, decision making, and action execution. By treating the human factors as stochastic variables that follow appropriate probability density functions, the effects of human factors on flight performance can be investigated through Monte Carlo（MC） simulation. Kernel density estimation algorithm is selected to find and rank the influential human factors. Subsequently, human factors are quantified through identifying the boundary of the flight performance margin by the k-nearest neighbor（k-NN） classifier. Simulation-based analysis shows that flight performance can be dramatically improved with the quantitative human factors.