网络可靠度分析的最小路算法和最小割算法研究

网络可靠度分析是评价城市生命线工程系统整体抗震性能的主要手段。本文分别从最小路和最小割的角度介绍了网络可靠度分析算法,包括:经典不交最小路(割)算法、最小路(割)递推分解算法和改进最小路(割)递推分解算法。在此基础上,通过实例分析,着重进行了改进最小路递推分解算法和改进最小割递推分解算法的对比分析,分析结果表明两种算法在网络单元不同可靠度水平下具有不同的计算效率,并对引起以上区别的三个主要原因进行了分析。     

生命线网络可靠度分析的改进最小路递推分解算法

在生命线网络最小路递推分解算法的基础上,充分利用分解过程中的信息,采用合并节点的方法,快速降低分解出来子网的复杂程度,从而达到大幅度减少分解出来的不交最小路(割)数量和提高计算效率的目的.计算实例分析表明,与最小路递推分解算法相比,改进算法能更为高效地给出网络可靠度,是一种有效的生命线工程网络抗震可靠性分析工具.     

大型城市管网抗震可靠性分析与优化

本文提出了地震作用下供水系统的渗漏模型,发展了地震后带渗漏管网的流分析技术,结合一次二阶矩方法获得了地震后供水管网的功能可靠度。针对供燃气管网系统则提出了一类高效精确的大型网络抗震连通可靠度分析的概率解析算法———递推分解算法。以上述管网抗震可靠性分析理论为基础,分别发展了基于模拟退火算法的供水系统网络拓扑优化分析理论和基于遗传算法的供燃气网络系统拓扑优化理论。     

沈阳市天然气管网系统抗震可靠性优化研究

供气管网系统抗震可靠性优化提供了系统改造决策的依据，是对系统抗震可靠性分析研究的深化。结合供气管网系统抗震分析的递推分解算法，介绍了利用遗传算法进行供气管网系统抗震优化分析的方法，以沈阳市供气管网系统为例，进行了实际工程的优化研究。     

生命线地震工程中的几个基本问题

本文提出了生命线工程系统的抗震设计准则,对生命线工程系统的可靠性进行了讨论,给出了一种地下管网系统可靠性分析的方法。文中提出了一种生命线工程系统受灾程度的定量分析方法。最后还建立了一个计算生命线工程系统直接经济损失和第一次间接经济损失的分析模型。     

分区分类的生命线工程地震直接经济损失研究

生命线工程的震害及损失评估工作对于震害防御和震后地震应急工作有着极其重要的意义。 但是, 生命线工程是一个复杂庞大的网络系统, 目前对其开展的震害及损失评估研究工作存在着很大的局限性和不确定性。 本文充分利用研究较多且较系统的建筑物震害及损失评估结果, 结合历次典型历史地震震害中建筑物和生命线震害情况, 通过分析建筑物损失和生命线工程损失的数量关系, 建立二者之间的关联模型; 通过对人口、 GDP、 土地利用等公里网格数据进行分析, 给出中国大陆地区的分区分类原则, 建立分区分类的生命线工程地震直接经济损失分析模型; 基于GIS软件平台, 开发了生命线工程地震直接经济损失分析模块, 利用该模块, 得出了四川省不同地震烈度下的生命线工程直接经济损失空间分布情况。     

生命线工程网络结构可靠性分析

生命线工程网络是一种复杂的网络结构。采用具叶斯因式分解法和布尔代数中加法形展开定理，计算了生命线工程发生震害时网络结构的可靠度。利用这两种方法进行网络结构可靠性分析，可以使计算工作量大大减少，本文还采用Ｔｒｕｅ ＢＡＳＩＣ语言开发了一套功能完善的生命线工程网络可靠性分析软件。     

供电网络系统的可靠性分析

研究了生命线工程系统中供电网络系统的可靠性分析方法。在元件可靠性分析的基础上,进行供电网络系统工程地震可靠性分析,提出了供电网络系统功能失效分级及失效等级的判定方法,并建立了功能失效系数的概念,给出了供电网络系统功能失效系数的计算方法,从而实现了供电网络系统功能失效分析的定量化。     

生命线工程系统抗震可靠度算法复杂性及简化原则

研究了生命线工程系统抗震可靠度常规算法的适用性，定义了算法的时间复杂性和结构复杂性，分析了使可行算法失效的原因，给出了回路分解公式，提出了优先降低结构复杂性的简化原则。     

地震地质灾害对广州市部分城区工程环境的影响分析

通过震害预测研究,探明地震地质灾害源,应用地理信息系统掌握地震地质灾害源空问分布情况,分析其对工程环境的影响范围和影响程度,有助于政府制定防震减灾规划和城市建设与改造。针对广州市部分城区的地震地质灾害源、建筑物、生命线工程、地震次生灾害源的分布情况,应用基于GIS平台的防震减灾信息管理与地震应急辅助决策系统,分析了该区内地震地质灾害破坏对建筑物、生命线工程和地震次生灾害源的影响。结果表明,城市中的建筑物、生命线工程和地震次生灾害源不同程度地受到地震地质灾害的影响。     

Minimal cut-based recursive decomposition algorithm for seismic reliability evaluation of lifeline networks

In this paper, a new probabilistic analytical approach, the minimal cut-based recursive decomposition algorithm (MCRDA), is presented to evaluate the seismic reliability of large-scale lifeline systems. Based on the minimal cut searching algorithm, the approach calculates the disjoint minimal cuts one by one using the basic procedure of the recursive decomposition method. At the same time, the process obtains the disjoint minimal paths of the system. In order to improve the computation efficiency, probabilistic inequality is used to calculate a solution that satisfies the prescribed error bound. A series of case studies show that MCRDA converges rapidly when the edges of the systems have low reliabilities. Therefore, the approach can be used to evaluate large-scale lifeline systems subjected to strong seismic wave excitation.     

An improved recursive decomposition algorithm for reliability evaluation of lifeline networks

The seismic reliability evaluation of lifeline networks has received considerable attention and been widely studied.In this paper,on the basis of an original recursive decomposition algorithm,an improved analytical approach to evaluate the seismic reliability of large lifeline systems is presented.The proposed algorithm takes the shortest path from the source to the sink of a network as decomposition policy.Using the Boolean laws of set operation and the probabilistic operation principal,a recursive deco...     

A recursive decomposition algorithm for network seismic reliability evaluation

A new probabilistic analytical approach to evaluate seismic system reliability of large lifeline systems is presented in this paper. The algorithm takes the shortest path from the source to the terminal of a node weight or edge weight network as decomposition policy, using the Boolean laws of set operation and probabilistic operation principal, a recursive decomposition process then could be constructed. For a general weight network, the modified Torrieri method (NTR/T method) is introduced to combine with the suggested algorithm. Therefore, the recursive decomposition algorithm may be applied to evaluate the seismic reliability of general lifeline systems. A series of case studies, including a practical district electric power network system and a large urban water supply system, show that the suggested algorithm supplies a useful probabilistic analysis means for the seismic reliability evaluation of large lifeline systems. Copyright © 2002 John Wiley & Sons, Ltd.     

An improved cut-based recursive decomposition algorithm for reliability analysis of networks

In this paper,an improved cut-based recursive decomposition algorithm is proposed for lifeline networks.First,a complementary structural function is established and three theorems are presented as a pr...     

Genetic algorithm for seismic topology optimization of lifeline network systems

Lifeline systems, such as water distribution and gas supply networks, usually cover large areas. For these systems, seismic design is always a difficult problem because of the complexity of large‐scale networks. In this paper, a topology optimization technology for lifeline networks is established. Firstly, in order to speed up the convergence of optimization process, an element investment importance analysis is carried out to evaluate the importance of components to the lifeline network. Then a topology optimization model is established. The aim of the model is to find the least‐cost network topology while the seismic reliability between the sources and each terminal satisfies prescribed reliability constraints. For this optimization problem, a genetic algorithm, which takes network topologies as the individuals of its population, is used to search for the optimal solutions by suitable operators, including selection, crossover and mutation operators. The capacity of the proposed algorithm is illustrated by its applications to a simple example network consisting of 10 nodes and an actual network with 391 nodes located in a large city of China. Copyright © 2008 John Wiley & Sons, Ltd.     

Multi‐scale system reliability analysis of lifeline networks under earthquake hazards

Recent earthquake events evidenced that damage of structural components in a lifeline network may cause prolonged disruption of lifeline services, which eventually results in significant socio‐economic losses in the affected area. Despite recent advances in network reliability analysis, the complexity of the problem and various uncertainties still make it a challenging task to evaluate the post‐hazard performance and connectivity of lifeline networks efficiently and accurately. In order to overcome such challenges and take advantage of merits of multi‐scale analysis, this paper develops a multi‐scale system reliability analysis method by integrating a network decomposition approach with the matrix‐based system reliability (MSR) method. In addition to facilitating system reliability analysis of large‐size networks, the multi‐scale approach enables optimizing the level of computational effort on subsystems; identifying the relative importance of components and subsystems at multiple scales; and providing a collaborative risk management framework. The MSR method is uniformly applied for system reliability analyses at both the lower‐scale (for link failure) and the higher‐scale (for system connectivity) to obtain the probability of general system events, various conditional probabilities, component importance measures, statistical correlation between subsystem failures and parameter sensitivities. The proposed multi‐scale analysis method is demonstrated by its application to a gas distribution network in Shelby County of Tennessee. A parametric study is performed to determine the number of segments during the lower‐scale MSR analysis of each pipeline based on the strength of the spatial correlation of seismic intensity. It is shown that the spatial correlation should be considered at both scales for accurate reliability evaluation. The proposed multi‐scale analysis approach provides an effective framework of risk assessment and decision support for lifeline networks under earthquake hazards. Copyright © 2009 John Wiley & Sons, Ltd.     

Decomposition algorithms for system reliability estimation with applications to interdependent lifeline networks

Reliability and risk assessment of lifeline systems call for efficient methods that integrate hazard and interdependencies. Such methods are computationally challenged when the probabilistic response of systems is tied to multiple events, as performance quantification requires a large catalog of ground motions. Available methods to address this issue use catalog reductions and importance sampling. However, besides comparisons against baseline Monte Carlo trials in select cases, there is no guarantee that such methods will perform or scale well in practice. This paper proposes a new efficient method for reliability assessment of interdependent lifeline systems, termed RAILS, that considers systemic performance and is particularly effective when dealing with large catalogs of events. RAILS uses the state‐space partition method to estimate systemic reliability with theoretical bounds and, for the first time, supports cyclic interdependencies among lifeline systems. Recycling computations across an entire seismic catalog with RAILS considerably reduces the number of system performance evaluations in seismic performance studies. Also, when performance estimate bounds are not tight, we adopt an importance and stratified sampling method that in our computational experiments is various orders of magnitude more efficient than crude Monte Carlo. We assess the efficiency of RAILS using synthetic networks and illustrate its application to quantify the seismic risk of realistic yet streamlined systems hypothetically located in the San Francisco Bay Region.