雷诺应力模型的初步应用

针对SSG/LRR-ω雷诺应力模型,选取NASA湍流资源网站上的四个典型算例,即湍流平板边界层流动、带凸起管道流动、翼型尾迹区流动和NACA0012不同攻角绕流,开展初步的验证与确认工作,将部分结果和CFL3D进行对比。对于NACA0012翼型绕流,对比雷诺应力模型和SA模型的升力系数,结果表明:在失速攻角附近,雷诺应力模型明显优于SA模型。在此基础上,将该模型应用于DLR-F6翼身组合体的数值模拟,计算得到的机翼表面典型站位压力分布和实验值吻合良好,同时该模型捕捉到翼身交汇位置的小范围分离。     

基于认知无线电的无线传感网系统设计与实现

为了提高认知无线电传感器网络(CRSN)中的能量使用效率和性能指标,提出了一种新的基于认知无线电的无线传感网系统,该系统中的传感器节点均使用改进的机会频谱接入路由协议,提出的协议能够更好地增加网络的可扩展性和提高网络性能。构建了精确的信道模型以便评估复杂的室内环境不同区域的信号强度,通过实验模拟对提出系统的性能进行评估。模拟结果显示,相比其他两种路由协议,提出的协议在吞吐量、包延迟及总能量消耗方面表现更佳。     

一种基于二分法的无线传感器网络拓扑控制算法

文中针对传感器节点分布不均和拓扑建立时间长的问题,提出了一种基于二分法的拓扑控制算法,每个节点自适应选择发射功率以获得预设的度。仿真显示,与基于均匀功率增量的算法相比,基于二分法的拓扑控制算法大大减少了功率切换次数且形成的拓扑简单,减少了网络拓扑形成时间和平均发射功率。     

基于遭遇角决策的并行双模切换舵减摇控制

结合舵减摇控制中通用线性模型与模糊线性模型的优缺点,采用了一种根据遭遇角的不同自动切换控制器设计模型的并行双模切换舵减摇控制方案。为在线自动辨识遭遇角,提出基于横摇功率谱密度柱状图的神经网络辨识方法。仿真结果表明,该方法辨识精度较高,且比传统重心法节省了在线计算量与存储数据库所需的存储空间,简化了辨识流程。     

军用无线传感器网络体系结构研究

无线传感器网络作为一种全新的监测系统被广泛认为是军用侦查探测系统的发展方向,已经成为国际军事领域研究热点。在总结了几种无线传感器网络体系结构的基础上,针对军用领域特定的性能需求,对这些体系结构进行了比较。     

Network design for time‐constrained delivery

To meet customer demand, delivery companies are offering an increasing number of time‐definite services. In this article, we examine the strategic design of delivery networks which can efficiently provide these services. Because of the high cost of direct connections, we focus on tree‐structured networks. As it may not be possible to identify a tree‐structured network that satisfies all of the delivery guarantees, we allow these guarantees to be violated but seek to minimize the sum of the violations. We establish the complexity of the problem and exploit an empirically identified solution structure to create new neighborhoods which improve solution values over more general neighborhood structures. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

Factors that affect the optimal amount of central control in complex systems

Whereas much of the previous research in complex systems has focused on emergent properties resulting from self‐organization of the individual agents that make up the system, this article studies one vital role of central organization. In particular, four factors are conjectured to be key in determining the optimal amount of central control. To validate this hypothesis, these factors are represented as controllable parameters in a mathematical model. For different combinations of parameter values, the optimal amount of central control is found, either analytically or by computer simulation. The model is shown to provide results that match well with the level of control found across a broad spectrum of specific complex systems. This model also provides general guidelines as to how combinations of these factors affect the desirable level of control and specific guidelines for selecting and evaluating leaders. These results indicate that all of these factors, though not exhaustive, should be considered carefully when attempting to determine the amount of control that is best for a system. © 2008 Wiley Periodicals, Inc. Naval Research Logistics, 2008     

四元数长方矩阵的同时复对角化

利用四元数矩阵的奇异值分解(SVD),对两个四元数长矩阵给出了其同时复对角化的充要条件,进一步对一个四元数长矩阵集合,针对其同时复对角化问题,给出了一系列充分必要条件.     

Strategic capacity decision‐making in a stochastic manufacturing environment using real‐time approximate dynamic programming

In this study, we illustrate a real‐time approximate dynamic programming (RTADP) method for solving multistage capacity decision problems in a stochastic manufacturing environment, by using an exemplary three‐stage manufacturing system with recycle. The system is a moderate size queuing network, which experiences stochastic variations in demand and product yield. The dynamic capacity decision problem is formulated as a Markov decision process (MDP). The proposed RTADP method starts with a set of heuristics and learns a superior quality solution by interacting with the stochastic system via simulation. The curse‐of‐dimensionality associated with DP methods is alleviated by the adoption of several notions including “evolving set of relevant states,” for which the value function table is built and updated, “adaptive action set” for keeping track of attractive action candidates, and “nonparametric k nearest neighbor averager” for value function approximation. The performance of the learned solution is evaluated against (1) an “ideal” solution derived using a mixed integer programming (MIP) formulation, which assumes full knowledge of future realized values of the stochastic variables (2) a myopic heuristic solution, and (3) a sample path based rolling horizon MIP solution. The policy learned through the RTADP method turned out to be superior to polices of 2 and 3. © 2010 Wiley Periodicals, Inc. Naval Research Logistics 2010     

稳定自组织网络结构中单点突变对网络稳定性影响

从战场恶劣环境通信设备无法正常通信的条件下,介绍了一种自组织网络稳定度的模型。通过比较自组织网络结构中微结构和巨结构的优缺点,动态地描述了结构间的聚合和裂解。基于结构分析,考虑单点突变对网络稳定性的影响,从时间因素策略方面,提出了一个基于预测最稳定链路生存时间的一种分布式成群策略。通过合理建模以及优化路由算法,尽可能地维护网络结构的稳定。