一种用于立体供热管网的水力计算方法

为了充分利用新能源的节能潜力,需要提高供热管网模型在非对称、非规则拓扑结构的管网上进行水力计算的能力.本文提出一种立体管网建模方法.该方法无需基于图论搜索基本回路,能够在三维非对称、非规则拓扑结构上直接对热网进行水力工况分析.将该方法与传统方法的建模过程进行详细的比较,并通过具体案例计算验证方法的有效性.     

基于面向对象方法的多源环状管网水力计算

提出一种基于面向对象的方法,以元件的对象属性表达管网的拓扑结构,以对象方法表达水力计算模型,用对象事件反映边界条件变化响应的方法,然后通过遍历整个管网元件对象进行水力计算.对工程中两种常见的多源管网结构进行计算,分析表明,新方法能有效地处理多源环状管网结构、源变化引发的水力平衡问题,计算偏差小,能够充分满足工程计算的需求.     

涡轮动叶冷却结构设计方法Ⅰ:参数化设计

基于冷却结构参数化设计、传统的管网计算方法与新兴的气热耦合数值模拟技术,提出了一套涡轮冷却结构设计方法,并编写了相关的设计程序与计算程序。利用参数化设计方法可以快速而精确地设计冷却结构,管网计算用于指导方案设计,气热耦合数值模拟用于指导详细设计。参数化设计中利用单元设计法程序实现动叶冷却通道快速设计;借助管网计算模型自动生成程序与CFD计算域三维实体快速造型方法,可以快速生成管网计算或在较短的时间内完成CFD计算域精确建模,为热分析计算提供条件。     

涡轮动叶冷却结构设计方法I:参数化设计

基于冷却结构参数化设计、传统的管网计算方法与新兴的气热耦合数值模拟技术,提出了一套涡轮冷却结构设计方法,并编写了相关的设计程序与计算程序.利用参数化设计方法可以快速而精确地设计冷却结构,管网计算用于指导方案设计,气热耦合数值模拟用于指导详细设计.参数化设计中利用"单元设计法"程序实现动叶冷却通道快速设计;借助管网计算模...     

基于最小刚性图代数特性的无线网络拓扑优化算法

对于能量受限的无线传感器网络,拓扑优化能够降低能耗,优化通信链路结构.本文基于最小刚性图原理提出了一种新的拓扑优化算法,算法综合考虑了生成拓扑链路图中通信链路的权值与生成刚性图的代数特性问题,既保证了通信链路较短,有利于延长网络的生命周期,同时使生成的通信链路图结构更加稳定,网络具有较好的鲁棒性.仿真实验表明,与相关算法比较,提出的算法中通信链路较短,具有较好的网络连通性与结构稳定性,同时生成刚性图矩阵的迹较大,具有较好的刚度代数性能.     

红外无损探测中多宗量多热源反演问题的研究

为研究红外无损探测稳态多热源反演逆问题, 建立不同形状的均质与非均质稳态热传导模型, 其中内热源个数、位置、强度、面积均为未知项. 基于数值算法中有限元算法对模型进行离散分析, 化简有限元矩阵方程, 最终转化为对Ax = b高度欠定方程的求解. 首次利用分段多项式谱截断奇异值分解法处理内热源逆问题, 并对算法进行改进, 有效改善了该算法在处理多热源反演时存在的严重的热源叠加效应. 根据反演出的内热源信息, 利用有限元算法计算重构出整个模型内所有节点的温度分布. 运用数值仿真Comsol软件和具体实物实验对算法进行有效性评估, 并验证算法在不同热传导模型中的表现. 结果表明, 算法能够准确反演出多热源各参量信息, 在非均质材料模型中仍能准确地反演出热源项, 并有效重构出模型内温度场. 该算法可应用于材料无损检测及人体红外医学成像等领域.     

一种三相四桥臂拓扑结构的新型矩阵变换器

提出了一种三相四桥臂矩阵变换器的电路拓扑结构,可作为三相四线制交流电压源对三相不平衡负载供电.针对该矩阵变换器的拓扑结构,提出了一种新颖的间接空间矢量调制策略,并推导了开关矢量合成公式,给出了区间选择、占空比计算和输出参考电压设定的方法,最后对该新型电路拓扑进行了仿真研究.结果表明,该拓扑结构能在三相负载不平衡情况下,保证输出电压波形的正弦性和稳定性.     

多块对接网格技术在电磁场散射问题中的应用

采用多块对接网格技术和时域有限体积法(FVTD)研究了典型目标和多体的电磁场散射问题.控制方程采用三维一般曲线坐标系下的时变麦克斯韦方程组.时间方向采用四步Runge-Kutta方法,空间离散采用基于通量雅可比矩阵特征结构的通矢量差分分裂,依赖变量采用MUSCL插值.时间方向的计算精度为2阶,空间方向的计算精度可达3阶.典型算例的雷达散射截面(RCS)的计算结果与理论解吻合很好.对于多体问题计算与文献结果相当一致,说明该算法具有对复杂拓扑结构外形(包括多体问题)进行数值模拟的能力.     

供热管网中管段阻力系数的辨识方法

提出一种新的管网阻力系数辨识方法,利用管网中少量节点处的压力或流量测量值对所有管段内壁粗糙度进行有效辨识,达到获得管段阻力系数的目的.该方法的辨识模型不仅能灵活利用工程手册所推荐的管道粗糙度等先导信息,还可综合利用多种工况下的辨识值,获得更高精度的辨识结果.基于这种辨识模型,提出一种结合遗传算法(GA)和有效集法(AS)的混合算法求解最优化问题.混合算法改善了局部搜索效率,同时具备较好的全局寻优能力.通过对2个案例管网参数的辨识计算,表明新方法可获得精度较高的辨识结果,并且对较大的管网也能得到稳定的计算结果.     

基于随机矩阵的金融网络模型

随机矩阵理论运用于金融领域中研究金融相关系数矩阵的相关性,相关系数矩阵是网络构建中的关键因素,本文将随机矩阵理论与网络构建相结合,研究基于随机矩阵的金融网络模型.本文选取上海证券市场的股票数据,将其中的股票数据分成四个阶段,基于随机矩阵理论,讨论金融相关系数矩阵和随机矩阵的特征值统计性质,并在此基础上对现有的去噪方法进行改进,建立更适合构建金融网络的相关系数矩阵,并构建金融网络模型.然后,基于随机矩阵理论和网络的关键节点分析比较去噪前后的金融网络以及噪声网络,发现对网络去噪后仍保留了原始网络的关键重要的信息,而噪声信息对应的是原始网络中度比较小的节点所代表的信息.最后,基于去噪网络,分析金融网络的拓扑结构,如最小生成树、模体和社团结构,发现改进后的金融网络的拓扑性质更加明显,结构更加紧密.     

二元决策图和故障树相融合的无线传感器网络可靠性分析

为了提高无线传感器分析网络可靠性,提出一种基于二元决策图和故障树相融合的无线传感器网络可靠分析方法;首先根据无线传感器网络拓扑结构建立了故障树模型,然后将无线传感器网络故障树转化为二元决策图结构,最后采用仿真实验分析了不同节点冗余度、不同跳数条件下无线传感器网络的可靠性;仿真结果表明,文章方法的分析结果可以帮助无线传感器网络性能的优化,可以提高无线传感器网络的可靠性。     

Network evolution driven by dynamics applied to graph coloring

An evolutionary network driven by dynamics is studied and applied to the graph coloring problem. From an initial structure, both the topology and the coupling weights evolve according to the dynamics. On the other hand, the dynamics of the network are determined by the topology and the coupling weights, so an interesting structure-dynamics co-evolutionary scheme appears. By providing two evolutionary strategies, a network described by the complement of a graph will evolve into several clusters of nodes according to their dynamics. The nodes in each cluster can be assigned the same color and nodes in different clusters assigned different colors. In this way, a co-evolution phenomenon is applied to the graph coloring problem. The proposed scheme is tested on several benchmark graphs for graph coloring.     

A new green multicast grooming protection algorithm in WDM optical networks

Since optical network carries a lot of traffic, survivability is very important to ensure the service continuity against network failures. Recently, multicast services become more popular to meet the huge multimedia demand in network, so that multicast survivability in optical network has got more attention. However, multicast survivability may lead to more energy consumption due to more redundant backup resources allocated. Since greening network is particularly important with the energy crisis keeping growing, green multicast survivability in optical network is a challenging issue. This paper focuses on the green multicast grooming protection problem in optical network and designs two auxiliary graphs that includes a virtual topology graph and an integrated graph to address the survivable multicast grooming, routing and wavelength assignment. Based on the auxiliary graphs, this paper proposes an efficient heuristic called green multicast grooming algorithm based on spanning path dedicated protection (GMG-SPDP), in which the network reliability and the energy efficiency are jointly taken into account. Simulation results show that, compared to other algorithms, the proposed GMG-SPDP not only has lower blocking probability and higher bandwidth utilization ratio, but also saves more energy.     

Analysis of the Chinese air route network as a complex network

The air route network, which supports all the flight activities of the civil aviation, is the most fundamental infrastructure of air traffic management system. In this paper, we study the Chinese air route network (CARN) within the framework of complex networks. We find that CARN is a geographical network possessing exponential degree distribution, low clustering coefficient, large shortest path length and exponential spatial distance distribution that is obviously different from that of the Chinese airport network (CAN). Besides, via investigating the flight data from 2002 to 2010, we demonstrate that the topology structure of CARN is homogeneous, howbeit the distribution of flight flow on CARN is rather heterogeneous. In addition, the traffic on CARN keeps growing in an exponential form and the increasing speed of west China is remarkably larger than that of east China. Our work will be helpful to better understand Chinese air traffic systems.     

Optical Implementation of Entropy Network Mapped from Binary Feature Tree

An entropy network mapped from a binary feature tree is described and compared with the Hamming net. Implementation of the entropy network includes extracting features from an input and making the decision according to these features. The feature extraction in the first layer of the entropy network is implemented by an optical method. Optical implementation with an incoherent shadow casting correlation system is proposed, and experimental demonstrations are given. The processing capability of the proposed optical system is discussed.     

An improved model for structural vulnerability analysis of power networks

Electric power networks have been studied as a typical example of real-world complex networks. Traditional models for structural vulnerability analysis appear to be all based on physical topological structure. In this paper, we depict a typical power network as a weighted graph based on electrical topology by introducing its bus admittance matrix, which embodies the important characteristics of power networks in a much more realistic structure. Furthermore, the numerical simulation for both the traditional dynamical model and the proposed electrical topological model are investigated based on the IEEE 300 bus system respectively. The comparison demonstrates that the improved model is more precise and highly efficient for the analysis of structural vulnerability of power networks.     

Community detection with consideration of non-topological information

In a network described by a graph, only topological structure information is considered to determine how the nodes are connected by edges. Non-topological information denotes that which cannot be determined directly from topological information. This paper shows, by a simple example where scientists in three research groups and one external group form four communities, that in some real world networks non-topological information (in this example, the research group affiliation) dominates community division. If the information has some influence on the network topological structure, the question arises as to how to find a suitable algorithm to identify the communities based only on the network topology. We show that weighted Newman algorithm may be the best choice for this example. We believe that this idea is general for real-world complex networks.     

Scalable Network Coding for Heterogeneous Devices over Embedded Fields

In complex network environments, there always exist heterogeneous devices with different computational powers. In this work, we propose a novel scalable random linear network coding (RLNC) framework based on embedded fields, so as to endow heterogeneous receivers with different decoding capabilities. In this framework, the source linearly combines the original packets over embedded fields based on a precoding matrix and then encodes the precoded packets over GF(2) before transmission to the network. After justifying the arithmetic compatibility over different finite fields in the encoding process, we derive a sufficient and necessary condition for decodability over different fields. Moreover, we theoretically study the construction of an optimal precoding matrix in terms of decodability. The numerical analysis in classical wireless broadcast networks illustrates that the proposed scalable RLNC not only guarantees a better decoding compatibility over different fields compared with classical RLNC over a single field, but also outperforms Fulcrum RLNC in terms of a better decoding performance over GF(2). Moreover, we take the sparsity of the received binary coding vector into consideration, and demonstrate that for a large enough batch size, this sparsity does not affect the completion delay performance much in a wireless broadcast network.