构建无线自组网仿真场景

计算机仿真是测试评估网络协议性能的基本技术，而无线自组网技术是一项新兴的热门无线网络技术。目前为止还没有文章对无线自组网计算机仿真技术进行综合介绍。因此，本文以构建易用合理的无线自组网仿真场景为目标，从仿真软件、仿真场景和移动模型这三个方面综合说明了构建无线自组网仿真场景的相关技术。本文对三种通用网络仿真软件NS-2，Glomosim和OPNET进行了分析比较，介绍了无线自组网研究中几种典型的仿真场景，最后介绍了常用的几个节点移动模型，分析了移动模型存在的问题及解决方法。本文对构建无线自组网仿真环境具有指导借鉴意义。     

航电系统SCI环型互连的计算机仿真建模

研究可扩展一致性接口 SCI环型互连的计算机仿真问题。作为未来一代航电系统的首选技术 ,SCI互连系统性能的优劣直接影响到飞行器的质量 ,对其性能的评价因此显得尤为重要。文中按照计算机仿真建模的一般方法 ,从 SCI协议的基本原理出发 ,建立了接口和节点模型 ,解决了并发数据交互的仿真时序问题 ,给出了 SCI环型互连的系统仿真模型 ,并通过例子对仿真模型的有效性进行了验证     

基于混沌搜索的三级倒立摆LQ控制器设计

研究利用混沌优化的LQ控制方法对三级倒立摆系统进行闭环控制.首先将混沌变量引入LQ控制器的权矩阵参数域,并进行全局范围内直接寻优,当获得全局近似最优解后,再缩小寻优区间,在次优解附近继续寻优,得到全局最优权矩阵参数.仿真结果表明了该方法的有效性和具有良好的抗干扰能力.     

太阳电池在平流层中的工作性能分析

近年来,临近空间受到广泛关注,多种平流层飞行器被提出,它们大多以太阳电池为 主要的能源获取装置。研究平流层的太阳电池的性能,对平流层的开发和利用具有重要意义 。首先建立了平流层中太阳电池的热环境模型,并结合硅太阳电池的电学模型,得到了 平流层中硅太阳电池的热电耦合分析模型,进而用数值模拟方法对太阳能电池的热学、电学 性能进行了分析和讨论。研究结果表明,平流层热环境的变化对太阳能电池的温度、输出功 率以及电效率都有影响。讨论了风速对太阳电池性能的影响,结果表明随着风速的增 加,太阳电池温度降低、内部温差先增加后减小、发电效率和输出功率都增加。
     

Neural Network aided PMSM multi-objective design and optimization for more-electric aircraft applications

This study uses the Neural Network(NN) technique to optimize design of surfacemounted Permanent Magnet Synchronous Motors(PMSMs) for More-Electric Aircraft(MEA)applications. The key role of NN is to provide dedicated correction factors for the analytical PMSM mass and loss estimation within the entire design space. Based on that, a globally optimal design can be quickly obtained. Matching the analytical estimation with Finite-Element Analysis(FEA) is the main research target of training the NN. ...     

硝基立方烷及其氮杂衍生物的能量特性计算研究

硝基立方烷及其氮杂衍生物是高能量密度材料的重要目标化合物类型之一。据此详细计算分析了硝基立方烷（从二硝基到八硝基立方烷）和四硝基四氮的杂立方烷分别在产单元推进剂，ＨＴＰＢ／Ａｌ，ＰＥＧ／ＮＧ／Ａｌ，ＧＡＰ／ＮＧ／Ａｌ体系中的能量特性。结果表明，硝基取代数大于４的立方烷和四硝基四氮杂立方烷的能量特性明显优于ＨＭＸ。     

基于自适应遗传BP算法神经网络数据融合的空中目标识别

空中目标识别是现代防空作战的重要研究内容。本文利用不同类型目标产生的多类型传感器的数据信息对目标进行识别。为了训练神经网络目标识别分类器,将遗传算法和BP算法相结合,提出了一种新的自适应遗传BP算法,利用这种神经网络来确定指标的权值。仿真试验结果表明,基于自适应遗传BP算法神经网络的识别是一种简单、可靠的目标识别方法,具有很好的目标识别效果。     

Evolution of airports from a network perspective——An analytical concept

Analyzing airports' role in global air transportation and monitoring their development over time provides an additional perspective on the dynamics of network evolution. In order to understand the different roles airports can play in the network an integrated and multi-dimensional approach is needed. Therefore, an approach to airport classification through hierarchi-cal clustering considering several parameters from network theory is presented in this paper. By applying a 29 year record of global flight data and calculating the conditional transition probabil-ities the results are displayed as an evolution graph similar to a discrete-time Markov chain. With this analytical concept the meaning of airports is analyzed from a network perspective and a new airport taxonomy is established. The presented methodology allows tracking the development of airports from certain categories into others over time. Results show that airports of equal classes run through similar stages of development with a limited number of alternatives, indicating clear evolutionary patterns. Apart from giving an overview of the results the paper illustrates the exact data-driven approach and suggests an evaluation scheme. The methodology can help the public and industry sector to make informed strategy decisions when it comes to air transportation infras-tructure.     

复合推进剂侵蚀燃烧特性的κ-ε参数表征

本文从推进剂侵蚀燃烧机理分析出发,综合片型装药发动机中止燃烧试验与相应的燃烧室内流场N-S方程组STMPLE方法数值分析的特点,导出一种由燃面上k~2/ε和p参数表述推行剂侵蚀特性的新方法,并成功地应用于4B丁羟复合药侵蚀特性的研究中.     

Improved predictions of equatorial TEC for real time applications

It is important to use models developed specifically for the equatorial ionospheric estimation for real-time applications, particularly in Satellite Navigation. This work demonstrates a methodology for improved predictions of VTEC in real time using the model developed for the equatorial ionosphere by the authors. This work has been done using TEC data of the low solar activity period of 2005 obtained using dual frequency GPS receivers installed under the GAGAN project of ISRO. For the purpose, the model is first used in conjunction with Kriging technique. Improvement in accuracy is observed when compared with the estimations from the model alone using the measurements as true reference. Further improvement is obtained by Bayesian combination of these estimates with independent Neural Network based predictions. Statistical performance of improvement is provided. An improvement of ∼1 m in confidence level of estimation of VTEC is obtained.