Stationary flow fields prediction of variable physical domain based on proper orthogonal decomposition and kriging surrogate model

In this paper a new flow field prediction method which is independent of the governing equations, is developed to predict stationary flow fields of variable physical domain. Predicted flow fields come from linear superposition of selected basis modes generated by proper orthogonal decomposition(POD). Instead of traditional projection methods, kriging surrogate model is used to calculate the superposition coefficients through building approximate function relationships between profile geometry parameters of physical domain and these coefficients. In this context,the problem which troubles the traditional POD-projection method due to viscosity and compressibility has been avoided in the whole process. Moreover, there are no constraints for the inner product form, so two forms of simple ones are applied to improving computational efficiency and cope with variable physical domain problem. An iterative algorithm is developed to determine how many basis modes ranking front should be used in the prediction. Testing results prove the feasibility of this new method for subsonic flow field, but also prove that it is not proper for transonic flow field because of the poor predicted shock waves.     

Advanced fractal approach for unsupervised classification of SAR images

Unsupervised classification of Synthetic Aperture Radar (SAR) images is the alternative approach when no or minimum apriori information about the image is available. Therefore, an attempt has been made to develop an unsupervised classification scheme for SAR images based on textural information in present paper. For extraction of textural features two properties are used viz. fractal dimension D and Moran’s I. Using these indices an algorithm is proposed for contextual classification of SAR images. The novelty of the algorithm is that it implements the textural information available in SAR image with the help of two texture measures viz. D and I. For estimation of D, the Two Dimensional Variation Method (2DVM) has been revised and implemented whose performance is compared with another method, i.e., Triangular Prism Surface Area Method (TPSAM). It is also necessary to check the classification accuracy for various window sizes and optimize the window size for best classification. This exercise has been carried out to know the effect of window size on classification accuracy. The algorithm is applied on four SAR images of Hardwar region, India and classification accuracy has been computed. A comparison of the proposed algorithm using both fractal dimension estimation methods with the K-Means algorithm is discussed. The maximum overall classification accuracy with K-Means comes to be 53.26% whereas overall classification accuracy with proposed algorithm is 66.16% for TPSAM and 61.26% for 2DVM.     

俯仰轴飞行品质中频域准则的计算与模拟

简要介绍了军用飞机飞行品质MIL—STD—1797A中有关俯仰轴频域难则的要求和原由。提出了对这些难则的理论计算和模拟试验方法。并以某飞机为例，利用所提出的方法，对其飞行品质进行了计算和模拟。结果表明，所提出的计算和模拟方法是合理的。最后，讨论了驾驶员模型形式对俯仰轴飞行品质的影响。     

基于CompactPCI总线的红外目标跟踪系统

红外目标跟踪方法的理论研究较多,而通用的实时跟踪系统较少。给出了具有CompactPCI总线、并行分布式结构的系统方案,核心是基于标准总线的实时系统,上位机实现卡尔曼预测,DSP并行完成频域转换与相关,CPLD实现总线接口控制。所实现的系统具有运算能力强、通信带宽大、可扩展性和通用性强的特点,实用表明了它的可行性。     

基于CFD/CSD耦合的叶轮机叶片失速颤振计算

为了研究叶轮机叶片的失速颤振特性,发展了一种计算流体力学与计算结构力学(CFD/CSD)时域耦合方法。该方法通过每一物理时刻CFD和CSD的循环迭代实现了耦合计算。在CFD分析中,采用鲁棒性较好的空间离散格式AUSM+-UP,并基于延迟脱体涡模型(DDES)模拟了带分离流动。在结构分析中,通过模态法构建了旋转叶片动力学方程并运用杂交多步方法进行求解。以孤立转子Rotor37为例,计算了不同工况下流场总体与细节参数,与实验结果的对比验证了CFD算法的精度。对某转子叶片进行了颤振特性研究,计算所得的广义位移时间响应曲线表明该叶片在近失速工况下会发生失速颤振,其表现形式为一阶弯曲模态发散且各阶模态之间不耦合。分析表明,流场不稳定和非定常效应是引起失速颤振的关键因素,同时折合频率的降低也会导致原本气动弹性稳定的叶片发生失速颤振。     

时域有限体积法的格式稳定性分析

以模型方程为例,采用MUSCL插值的S-W通量分裂格式,分别结合二步、四步龙格一库塔时间推进格式建立数值求解方法.用Von Neumann傅里叶级数分析方法,通过对不同格式的放大因子及色散因子的计算,分析了时域有限体积法(FVTD)格式的稳定性.     

商务英语模糊语语境顺应性研究

商务英语是国际商务活动的重要语言载体。模糊语在商务英语中有着不可替代的语用功能。以商务活动中的内部沟通语境和对外沟通语境为视角,对在这两种语境下商务英语模糊语的应用规律进行分析研究,应用顺应性理论对其进行解释,阐明在实际应用中应遵循这些规律,做到＂内外有别＂。对准确使用商务英语,提高商务沟通效率以及促进商务英语的教学等方面都有重要的意义。     

自适应DR算法研究

首先介绍了 DR算法的基本思想 ,并分析了现有的 DR算法的不足之处。然后提出了一种自适应 DR算法。最后 ,将提出的这种自适应 DR算法与普通 DR算法进行了比较研究。结果表明 ,自适应 DR算法是十分有效的     

空间机器人神经网络自适应滑模目标操控轨迹跟踪控制

针对参数未知的空间目标操控问题,考虑空间机器人负载不确定性、系统动力学不确定性和环境扰动等因素,为实现操作过程的稳定控制及机器人轨迹的有效跟踪,提出一种基于径向基神经网络估计不确定项的自适应增益非奇异终端滑模变结构控制器。首先基于拉格朗日法建立空间机器人的刚体动力学模型。考虑空间机器人基座姿态主动控制模式,使用径向基神经网络对模型中的不确定项进行估计。进而提出基于神经网络估计的非奇异终端滑模控制器,并针对不确定性和扰动的估计误差设计自适应增益,以期实现空间机器人系统轨迹跟踪控制的收敛。仿真校验结果表明所设计的控制方法具有较好的误差收敛速度和控制精度。     

含有多级驱动机构卫星的多变量频域稳定性分析方法

摘要： 针对含有多级驱动机构卫星的多级复合控制系统,提出一种多变量频域稳定性分析方法.首先,基于小量假设建立含有多级驱动机构卫星一体化线性模型,针对星体和载荷姿态设计单通道输出线性反馈控制器,采用传递函数矩阵的矩阵分式描述,进行多项式矩阵变换得到多通道闭环系统极点分布规律,确定闭环系统多变量频域输入输出稳定性条件.算例和仿真结果表明,该方法能够验证含有多级驱动机构卫星闭环系统稳定性,并为控制器参数设计提供了有效工具.