横掠单圆管流动与换热的热力学优化设计

应用热力学第一、第二定律 ,采用对管外流体温度进行加权平均的方法 ,对选定参数的横掠单圆管流动与换热进行了热力学优化分析。得到了管内 ,管外流体的温度分布图 ,系统的熵产率分布图 ,和一系列优化参数的计算式。     

俯仰敏捷性评估与影响因素研究

建立了现代高机动性能战斗机俯仰敏捷性仿真计算数学模型和机动飞行时的操纵动作，以Ｆ－１６战斗机为例，计算并讨论了初始飞行状态以及飞行控制系统参数对战斗机俯仰敏捷性的影响。结果表明，选择适当的飞行状态，有利于更好地发挥飞机的俯仰敏捷性；降低飞机整体系统的阻尼，将有利于提高飞机的俯仰敏捷性；控制系统有关参数的设计，除考虑飞行品质要求外，还需综合考虑飞机敏捷性等方面的要求。     

信息和熵

介绍了当今信息时代里与之密切相关的理论－熵，分析了不同学科中的熵的概念，熵与信息的关系和功能等，并把滴论用于生命，社会，市场和决策中，深入浅出地分析了信息革命将引起的经济世界的变化。     

应用最大熵谱估计检测微弱信号

频谱分析是数字信号处理的主要内容之一 ,近年来 ,由于最大熵算法的一些优点 ,使它成为现代谱估计中一个比较活跃的领域。最大熵算法是 196 7年由Burg提出来的一种现代谱估计方法。提出了应用最大熵谱估计及LMS自适应算法 ,根据有限数据 ,在频域内提取被淹没在噪声中的有用信号的方法及应用MATLAB语言进行的仿真。     

一种基于联想记忆系统实现图像压缩的新方法

针对传统神经网络用于图像压缩时存在的训练时间长、泛化能力弱等问题,提出一种基于联想记忆型神经网络的图像压缩新方法.利用牛顿前向插值多项式构建联想记忆系统,对图像数据进行建模.首先将图像数据分为多个数据块,然后利用数据块对联想记忆系统进行训练,训练结束后得到该数据块的特征数据,特征数据的数量小于原始数据块,且数值大多在零附近.最后对所有数据块的特征数据重新排序,进行熵编码,从而实现图像数据的压缩.实验结果表明该方法是可行的和有效的,相比传统神经网络,联想记忆系统无需预先训练,不依赖训练集数据和初始值,可以实时编码.      

快速大时间步长熵条件格式的分辨率研究

提出了高分辨率快速大时间步长熵条件格式的构造方法.用激波管问题对一族熵条件格式进行研究.在精度、步长、限制器方面进行了详细的数值实验,研究了同样计算量下各种格式的表现品质.从理论上保证了大时间步长格式的无振荡性质,从具体的数值实验分析中确定了大时间步长格式的分辨率问题.      

基于熵限制的Baldwin-Lomax湍流模型

针对Baldwin-Lomax(BL)模型在模拟超声速复杂流动中的不足,提出一种基于熵限制的新型修正方式.分别采用原始的BL模型(BL-origin)、修正后的BL模型(BL-entropy)以及Wilcox k-ω两方程模型对超声速平板、超声速二维压缩拐角以及膨胀-压缩拐角3个典型算例进行计算,结果表明BL-entropy 能够较好地获取长度尺度进而得到均匀合理的涡粘性分布.同时,该修正方式简单高效并且适用于其他与超声速边界层有关的模型,具有较大的发展潜力.     

Hybrid partition- and network-level scheduling design for distributed integrated modular avionics systems

Distributed Integrated Modular Avionics (DIMA) develops from Integrated Modular Avionics (IMA) and realizes distributed integration of multiple sub-function areas. Time-triggered network provides effective support for time synchronization and information coordination in DIMA systems. However, inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism. To ensure such time determinism and achieve guaranteed real-time performance, system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain. This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication, and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes. Furthermore, incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost. To control such cost, this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible. Finally, two typical cases, including a simple fully connected DIMA system case and an industrial DIMA system case, are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.     

Identification of reduced-order model for an aeroelastic system from flutter test data

Recently, flutter active control using linear parameter varying (LPV) framework has attracted a lot of attention. LPV control synthesis usually generates controllers that are at least of the same order as the aeroelastic models. Therefore, the reduced-order model is required by syn-thesis for avoidance of large computation cost and high-order controller. This paper proposes a new procedure for generation of accurate reduced-order linear time-invariant (LTI) models by using sys-tem identification from flutter testing data. The proposed approach is in two steps. The well-known poly-reference least squares complex frequency (p-LSCF) algorithm is firstly employed for modal parameter identification from frequency response measurement. After parameter identification, the dominant physical modes are determined by clear stabilization diagrams and clustering tech-nique. In the second step, with prior knowledge of physical poles, the improved frequency-domain maximum likelihood (ML) estimator is presented for building accurate reduced-order model. Before ML estimation, an improved subspace identification considering the poles constraint is also proposed for initializing the iterative procedure. Finally, the performance of the proposed procedure is validated by real flight flutter test data.     

基于最小熵准则的频偏估计算法研究

提出了一种基于SEM(Spectrum Entropy Minimization,频谱熵最小化)的频偏估计算法。研究发现,频偏越小,离散信号频谱的熵越小。根据这一性质建立了相关算法,通过一维搜索的方式得到使相位补偿后信号频谱熵最小的频偏估计。仿真结果表明:SEM算法的估计性能能够达到CR(Cramer-Rao,克拉美罗)下界,而且估计的稳定性和鲁棒性较好,具有一定的应用价值。