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.     

基于区间方法的岩质边坡稳定性非概率可靠性分析

在综合分析岩土参数区间性的基础上,通过引入区间分析方法和非概率可靠性思想,建立岩质边坡稳定的非概率可靠性模型,并针对区间运算结果扩张问题,引入区间截断法和区间优化法,对边坡非概率可靠性指标进行较为精确的求解。然后,以湖北某岩质高边坡为实例,进一步探讨了岩体参数变异性对岩质边坡稳定的非概率可靠性指标的影响规律。     

Effect of connecting rain barrels on the storage size reduction

In this article, the possibility of sharing rain barrels and the potential benefit of reducing storage size through physical and non‐physical connections of rain barrels in a community are investigated. Using the concepts of homogeneous/heterogeneous users in rainwater harvesting systems (RWHS), two simple cases of a community composed of four prospective users are examined. The first is performed with the users who have the same mean and variance in water demands (homogeneous users), and the second is with the users with different means and variances (heterogeneous users). To take account for the rainfall characteristics in different places, historical records from six cities in the USA are used for storage–reliability–yield analysis. The result indicates that required total storage can be reduced by connecting multiple rain barrels. In addition, a significant difference is found between homogeneous and heterogeneous user groups. Homogeneous users do not achieve a substantial benefit from connecting their rain barrels; these users may even be disadvantaged by sharing. In contrast, heterogeneous users receive benefit by reducing the total required storage. Most benefit is expected between users with maximum difference in mean water demands. The reduction in storage size was as considerable as 37% in this study. The quantity of storage reduction depends on locations and target reliabilities. Knowledge of the benefits and limitations of rain barrel connections can improve RWHS performance through ability to customize a network plan for individual users. Copyright © 2011 John Wiley & Sons, Ltd.     

Markovian modeling of seismic damage accumulation

Analysis of civil structures at the scale of life‐cycle requires stochastic modeling of degradation. Phenomena causing structures to degrade are typically categorized as aging and point‐in‐time overloads. Earthquake effects are the members of the latter category this study deals with in the framework of performance‐based earthquake engineering (PBEE). The focus is structural seismic reliability, which requires modeling of the stochastic process describing damage progression, because of subsequent events, over time. The presented study explicitly addresses this issue via a Markov‐chain‐based approach, which is able to account for the change in seismic response of damaged structures (i.e. state‐dependent seismic fragility) as well as uncertainty in occurrence and intensity of earthquakes (i.e. seismic hazard). The state‐dependent vulnerability issue arises when the seismic hysteretic response is evolutionary and/or when the damage measure employed is such that the degradation increment probabilistically depends on the conditions of the structure at the time of the shock. The framework set up takes advantage also of the hypotheses of classical probabilistic seismic hazard analysis, allowing to separate the modeling of the process of occurrence of seismic shocks and the effect they produce on the structure. It is also discussed how the reliability assessment, which is in closed‐form, may be virtually extended to describe a generic age‐ and state‐dependent degradation process (e.g. including aging and/or when aftershock risk is of interest). Illustrative applications show the options to calibrate the model and its potential in the context of PBEE. Copyright © 2015 John Wiley & Sons, Ltd.     

Full probabilistic design of slopes in spatially variable soils using simplified reliability analysis method

ABSTRACT

A simplified reliability analysis method is proposed for efficient full probabilistic design of soil slopes in spatially variable soils. The soil slope is viewed as a series system comprised of numerous potential slip surfaces and the spatial variability of soil properties is modelled by the spatial averaging technique along potential slip surfaces. The proposed approach not only provides sufficiently accurate reliability estimates of slope stability, but also significantly improves the computational efficiency of soil slope design in comparison with simulation-based full probabilistic design. It is found that the spatial variability has considerable effects on the optimal slope design.     

Effect of 2D spatial variability on slope reliability: A simplified FORM analysis

To meet the high demand for reliability based design of slopes, we present in this paper a simplified HLRF(Hasofere Linde Rackwitze Fiessler) iterative algorithm for first-order reliability method(FORM). It is simply formulated in x-space and requires neither transformation of correlated random variables nor optimization tools. The solution can be easily improved by iteratively adjusting the step length. The algorithm is particularly useful to practicing engineers for geotechnical reliability analysis where standalone(deterministic) numerical packages are used. Based on the proposed algorithm and through direct perturbation analysis of random variables, we conducted a case study of earth slope reliability with complete consideration of soil uncertainty and spatial variability.     

A sequential sparse polynomial chaos expansion using Bayesian regression for geotechnical reliability estimations

Polynomial chaos expansions (PCEs) have been widely employed to estimate failure probabilities in geotechnical engineering. However, PCEs suffer from two deficiencies: (a) PCE coefficients are solved by the least-square minimization method which easily causes overfitting issues; (b) building a high order PCE is often computationally expensive. In order to overcome the aforementioned drawbacks, the Bayesian regression technique is employed to evaluate PCE coefficients, which not only provides a sparse solution but also avoids overfitting. With the aid of the predictive means and variances given by Bayesian analysis, a learning function is proposed to sequentially select the most informative samples that are critical to build a PCE. This sequential learning scheme can highly enhance the computational efficiency of PCEs. Besides, importance sampling (IS) is incorporated into the sequential learning (SL)-PCEs to deal with geotechnical problems with small failure probabilities. The proposed method of SL-PCE-IS is applied to three illustrative examples, which shows that the improved PCE method is more effective and efficient than the common PCEs method, leading to accurate estimations of small failure probabilities using fewer training samples.     

深层搅拌桩复合地基承载力可靠性研究

根据从国内收集的31组深层搅拌桩复合地基承载力试验数据,利用试计比归一化的方法简化处理随机参数影响,分析试计比的统计特性参数,采用JC法进行复合地基孙载力可靠性分析,给出各工况下的可靠指标。     

Variability of levee failure mechanisms subject to heavy rainfalls,case studies in Taiwan

In this study, the failure mechanisms for Chiuliao 1st Levee and Gueishan Levee in Taiwan were re-examined comprehensively considering the uncertainty of different parameters. Results have shown that for Chiuliao 1st Levee, the slope sliding failure has a higher coefficient of variation (COV). For Gueishan Levee, retaining wall sliding and overturning failure have higher values of COV instead. It can also be found that the scouring depths affect the stability of the levee significantly, therefore, a protecting system for the backfill material may be necessary to increase the stability of the levee effectively.     

边坡稳定可靠性的随机有限元分析

随机有限元法可以处理土性参数的变异性和空间相关性。对二阶摄动随机有限元法的摄动理论和程序进行了研究，提出了偏导矩阵的组集方法，采用正态分布随机变量的正交变换法来提高计算效率。考虑土性参数随机场作用和土性指标之间的互相关性，建立边坡局部抗剪和总体稳定性可靠度的随机有限元分析模型，对某实际土坡进行了可靠度计算，计算结果较为符合实际。