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。     

生命线工程网络抗震可靠性算法研究

现代城市的迅速发展对生命线工程系统依赖性逐渐增强。地震后生命线工程系统的性能直接决定了灾后生活和生产的恢复以及抢险工作的进行,因此对生命线工程系统进行地震作用下的可靠性分析具有十分重要的意义。本文中主要介绍2种求解大型网络抗震可靠度算法———最小路递推分解算法和最小割递推分解算法。在此基础上,利用这2种算法对沈阳市供气系统进行了分析。研究结果表明,合理选择使用这2种算法可以有效的进行不同地震烈度条件下的大型生命线工程系统的可靠性分析。     

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...     

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.     

网络可靠度分析的最小割递推分解算法

基于不交最小割求解系统失效概率的思想,提出了求解网络系统失效概率的最小割递推分解算法。在此基础上,利用概率不等式给出了失效概率的上、下界,从而可以通过控制上、下界之间的误差来获得计算精度和计算时间之间的平衡。计算实例分析表明,该算法能计算给出中、小型网络失效概率的精确值,并能够高效、高精度地求解出大型复杂网络系统的失效概率。     

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。     

Efficient risk assessment of lifeline networks under spatially correlated ground motions using selective recursive decomposition algorithm

For effective hazard mitigation planning and prompt-but-prudent post-disaster responses, it is essential to evaluate the reliability of infrastructure networks accurately and efficiently. A nonsimulation-based algorithm, termed as a recursive decomposition algorithm (RDA), was recently proposed to identify disjoint cut sets and link sets and to compute the network reliability. This paper introduces a ‘selective’ RDA, which preferentially identifies critical disjoint cut sets and link sets to calculate the probabilities of network disconnection events with a significantly reduced number of identified sets. To this end, the original RDA is improved by replacing the shortest path algorithm with an algorithm that identifies the most reliable path, and by using a graph decomposition scheme based on the probabilities associated with the subgraphs. The critical sets identified by the algorithm are also used to compute conditional probability-based importance measures that quantify the relative importance of network components by their contributions to network disconnection events. This paper also introduces a risk assessment framework for lifeline networks based on the use of the selective RDA, which can consider both interevent and intraevent uncertainties of spatially correlated ground motions. The risk assessment framework and the selective RDA are demonstrated by a hypothetical network example, and the gas and water transmission networks of Shelby County in Tennessee, USA. The examples show that the proposed framework and the selective RDA greatly improve efficiency of risk assessment of complex lifeline networks, which are characterized by a large number of components, complex network topology, and statistical dependence between component failures. Copyright © 2012 John Wiley & Sons, Ltd.     

A disjoint algorithm for seismic reliability analysis of lifeline networks

The algorithm is based on constructing a disjoin kg t set of the minimal paths in a network system. In this paper, cubic notation was used to describe the logic function of a network in a well-balanced state, and then the sharp-product operation was used to construct the disjoint minimal path set of the network. A computer program has been developed, and when combined with decomposition technology, the reliability of a general lifeline network can be effectively and automatically calculated. Supported by: Key Project of Science and Technology from the State Plan Committee, No. 101-9914003     

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.     

基于递归高通滤波的经验模态分解及其在地震信号分析中的应用

将地震信号分解成包含频谱互不重叠的单主周期的分量有利于地震信号的分析.分析了经验模态分解(EMD)中模态混叠的内在原因和已有的解决方法,梳理了解决模态混叠的思路框架,进而提出了一种新的基于输入递归高通滤波的EMD算法.首先用递归高通滤波器将信号预分解成频率由高到低的多个分量,实现信号的等价带通滤波,再用EMD对各带通分量按频率高低逐级递归筛分,获得完备的经验模态分量.通过合成信号和地震信号的仿真实验表明,该算法较好地克服了模态混叠,获得了频谱互不重叠的单主周期分量,并成功用于震相分离和分析,为地震信号分析提供了一种新思路.     

基于改进的风险矩阵法的生命线网络地震脆弱性分析

生命线网络的脆弱性不单单只表示地震发生后对网络作用而产生的后果,还应该包括网络的连通情况。本文在重新确定生命线网络脆弱性定义的基础上,运用风险评估理论中的风险矩阵方法综合考虑生命线网络的连通性能和失效后果两个方面来评价生命线网络的脆弱性,并以一个供气管网为例说明改进的风险矩阵法评价生命线网络脆弱性的有效性和合理性,找出供气管网中脆弱性等级最高的节点,分析其脆弱性等级最高的原因,以便于重点保护,并降低网络的脆弱性。     

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.     

Accurate estimation of acoustic impedance based on spectral inversion

Acoustic impedance is one of the best attributes for seismic interpretation and reservoir characterisation. We present an approach for estimating acoustic impedance accurately from a band‐limited and noisy seismic data. The approach is composed of two stages: inverting for reflectivity from seismic data and then estimating impedance from the reflectivity inverted in the first stage. For the first stage, we achieve a two‐step spectral inversion that locates the positions of reflection coefficients in the first step and determines the amplitudes of the reflection coefficients in the second step under the constraints of the positions located in the first step. For the second stage, we construct an iterative impedance estimation algorithm based on reflectivity. In each iteration, the iterative impedance estimation algorithm estimates the absolute acoustic impedance based on an initial acoustic impedance model that is given by summing the high‐frequency component of acoustic impedance estimated at the last iteration and a low‐frequency component determined in advance using other data. The known low‐frequency component is used to restrict the acoustic impedance variation tendency in each iteration. Examples using one‐ and two‐dimensional synthetic and field seismic data show that the approach is flexible and superior to the conventional spectral inversion and recursive inversion methods for generating more accurate acoustic impedance models.     

Spectral factorization technique for estimation of an ARMA operator for multichannel deconvolution of seismic data

A new spectral factorization method is presented for the estimation of a causal as well as a causally invertible ARMA operator from the correlation sequence of seismic traces. The method has been implemented for multichannel deconvolution of seismic traces with the aim of exploiting the trace-to-trace correlation that exists within seismograms. A layered earth model with a small reflectivity sequence has been considered, and the seismic traces have been considered as the output of a linear system driven by white noise reflection coefficient sequences. The present method is the concatenation of three algorithms, namely Kung's method for state variable ( F , G , H ) realization using a singular value decomposition (SVD) algorithm, Faurre's technique for computation of the strong spectral factor and Leverrier's algorithm for ARMA representation of the spectral factor. The inverted ARMA operator is used as a recursive filter for deconvolution of seismic traces. In the example shown, two traces with a covariance sequence of 160 ms length have been considered for multichannel deconvolution of stacked seismic traces. The results presented, when compared with those obtained from a conventional deconvolution algorithm, have shown encouraging prospects.     

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。     

Seismic reliability assessment of lifeline networks using clustering‐based multi‐scale approach

Seismic reliability assessment of lifeline networks gives rise to various technical challenges, which are mostly caused by a large number of network components, complex network topology, and statistical dependence between component failures. For effective risk assessment and probabilistic inference based on post‐hazard observations, various non‐simulation‐based algorithms have been developed, including the selective recursive decomposition algorithm (S‐RDA). To facilitate the application of such an algorithm to large networks, a new multi‐scale approach is developed in this paper. Using spectral clustering algorithms, a network is first divided into an adequate number of clusters such that the number of inter‐cluster links is minimized while the number of the nodes in each cluster remains reasonably large. The connectivity around the identified clusters is represented by super‐links. The reduced size of the simplified network enables the S‐RDA algorithm to perform the network risk assessment efficiently. When the simplified network is still large even after a clustering, additional levels of clustering can be introduced to have a hierarchical modeling structure. The efficiency and effectiveness of the proposed multi‐scale approach are demonstrated successfully by numerical examples of a hypothetical network, a gas transmission pipeline network, and a water transmission network. Copyright © 2014 John Wiley & Sons, Ltd.     

基于微粒群算法的供水管网抗震优化设计

以管网年费用折算值为优化目标、管网拓扑结构与管径为优化参数、管网节点最低可靠度为约束条件,建立了供水管网抗震优化设计模型。利用微粒群算法对这一模型进行了求解,该算法以管网作为微粒个体,通过不断地更新微粒的位置来搜索最优的管网结构,直到最后给出优化的管网结构。利用上述方法对一典型供水管网进行了抗震优化设计分析,给出了3种不同节点最低可靠度约束条件下的优化改造方案。     

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.