单一震源下生命线系统失效概率分析的新方法(一)--系统可靠路径与失效路径的识别

本文第一部分提出一类识别生命线系统可靠路径与失效路径的新方法，该方法从系统发生概率最大的可靠路径出发，采用递推分解的思路，识别出系统的互斥可靠路径和互斥失效路径，并给出系统失效概率的表达式和失效概率上下界表达式。实例分析表明，该识别方法的计算复杂性较小并具有较高的运算效率。     

随机结构动力可靠度估计算法的对比分析

对比分析了随机结构动力可靠度计算的三种估计算法.渐进展开法是基于Laplace算法对概率积分进行渐进估计的,此法通过计算最大被积分式值对应点,并将其代入概率积分的渐进估计表达式求解失效概率.由于概率积分的主要贡献来自于最大被积分式值对应点的周围,因此本文的重要抽样法假定重要抽样函数的最大似然值等于最大被积分式值对应点值.极值分布-泰勒展开法首先通过结构随机参数的极值分布函数给出失效概率的表达式,随后利用泰勒展开法对失效概率进行估计,其中采用中心差分法对极值分布函数的梯度进行估算.最后应用三种算法和Monte Carlo法对受高斯白噪声激励作用的单自由度随机结构进行了计算,结果表明三种方法不但运算简便,而且对比Monte Carlo法计算效率有显著提高.     

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。     

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。     

结构模糊随机可靠度的实用计算方法

本文以模糊随机变量为基本变量，定义了结构的模糊随机功能函数，分析了结构有效状态与失效状态之间的模糊性，建立了结构的模糊随机极限状态方程。利用序关系给出单失效模式结构的模糊安全准则，讨论了ａ－约束水平条件下单失效模式结构的失效概率、可靠度及可靠指标，进而得出结构的模糊随机失效概率、模糊随机可靠度及模糊可靠指标等。本文给出的具体计算方法和目前设计规范中彩的方法是相对应的。     

基于非确定性分析法的顺层边坡抗震性研究

顺层岩质边坡的抗震性指标大部分都是非确定的,无法用固定阈值衡量。提出基于非确定性分析法的顺层边坡抗震性性能研究,将顺层岩质边坡看作若干个叠加的薄板;运用非确定性分析法计算各个薄板的动力安全系数和动力极限状态方程,并对顺层边坡动力极限状态方程进行求解,可得在地震作用力下顺层边坡动力可靠度指标与顺层边坡失效概率之间的关系;评估地震作用力下顺层边坡整体稳定性,同时综合考量顺岩边坡的最小平均安全系数以及平均失效概率,得出评估结果。实验结果显示,在地震作用力下,顺层边坡坡高、坡角、岩层倾角对顺岩边坡抗震性能影响显著,评估结果与实际结果一致。     

建筑结构不同性能水平失效概率的合理比例关系研究

在基于性能的抗震设计中,为了使结构在整个生命周期内费用达到最小,不仅需要确定各个性能水平的目标失效概率,同时还需要确定不同性能水平目标失效概率之间的合理关系。本文针对这个问题。研究了在结构造价一定的情况下,不同性能水平失效概率的合理比例关系,使得在设计基准期内结构损失达到最小。在本文中,根据我国建筑抗震设计规范的条件,仅考虑“小震不坏”和“大震不倒”两个性能水平。     

钢筋混凝土框架结构造价与失效概率之间的近似关系研究

本文以层间位移角作为结构性能参数,分析了钢筋混凝土框架结构层间变形能力,以及在水平地震作用下层间位移反应。考虑钢筋混凝土框架结构材料强度和几何尺寸以及地震作用的不确定性,得出了在设计基准期内结构的失效概率。同时分析了不同设计参数下结构的最小造价,在此基础上,确定了结构最小造价和失效概率之间的近似关系。目的是为采用“投资—效益“准则确定该类型结构目标性能水平提供分析依据,从而为采用基于性能抗震设计理念制定建筑结构抗震设计规范提供基础研究。本文中,结构失效概率指结构最终极限状态的失效概率。     

失效相关工程系统的可靠度

本文建议用条件概率来考虑工程系统中各结构失效的相关性。为此,提出了条件关联系数的概念和影响条件概率的各种因素,并以抗震工程系统为例给出了具体的估算方法。从而得出了计算失效相关工程系统可靠度的方法。     

框架结构抗震可靠度优化的模型和准则

本以框架结构为研究对象,建议了一个用于结构抗震可靠度优化的模型,把最优结构表达为在给定的材料质量上限值和构件截面尺寸下限值的约束条件下具有最小地震失效概率的结构,模型中的约束函数全部都是设计变量的线性函数,可行域是一个凸域,采用Ｋｕｈｎ－Ｔｕｃｋｅｒ条件推地了最优解必须满足的准则,据此可以构造出优化的迭代格式,中讨论了优化准则的物理意义,给出目标函数对设计变量偏导数的解析求解过程。     

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...     

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.     

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.     

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     

An analytical solution for the probabilistic response of sdof non-linear random systems subjected to variable amplitude cyclic loading

Design for a specific ductile failure mode is assuming a rǒle of increasing importance for earthquake-resistant structures. This necessitates an accurate assessment of the distribution of overstrength in the structure, in order that the predefined failure mode can be realized. Consequently, the variability of the response for a given variability in the salient material properties, such as yield strength for steel structures, should be assessed and accounted for. In this paper an analytical method is proposed for the evaluation of the probability density function of the response of a single-degree-of-freedom hysteretic system with random parameters subject to a variable amplitude cyclic load history. A simple algorithm is derived which may be used to obtain the system response as a function of the system parameters. This response function may then be used to evaluate the displacement response probability density function when given the probability density function of the system parameters. Results derived from this procedure are verified against Monte Carlo simulation. It is shown that accurate response statistics are obtained at a fraction of the computing cost of simulation techniques.     

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。     

Neuro‐control of seismically excited steel structure through sensitivity evaluation scheme

The neuro‐controller training algorithm based on cost function is applied to a multi‐degree‐of‐freedom system; and a sensitivity evaluation algorithm replacing the emulator neural network is proposed. In conventional methods, the emulator neural network is used to evaluate the sensitivity of structural response to the control signal. To use the emulator, it should be trained to predict the dynamic response of the structure. Much of the time is usually spent on training of the emulator. In the proposed algorithm, however, it takes only one sampling time to obtain the sensitivity. Therefore, training time for the emulator is eliminated. As a result, only one neural network is used for the neuro‐control system. In the numerical example, the three‐storey building structure with linear and non‐linear stiffness is controlled by the trained neural network. The actuator dynamics and control time delay are considered in the simulation. Numerical examples show that the proposed control algorithm is valid in structural control. Copyright © 2001 John Wiley & Sons, Ltd.     

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.