Matrix-based system reliability method and applications to bridge networks

Kang, Woo‐Hyoung; Song, Junho; Gardoni, Paolo

doi:10.1016/j.ress.2008.02.011

Cited by 170 publications

(80 citation statements)

References 13 publications

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“…There are some analytical approaches that are sometimes used for lifeline risk assessment, e.g. [4,5], but those are generally applicable to only specific classes of lifeline reliability problems. Hence, many past research works use simulation-based approaches instead of analytical approaches for lifeline risk assessment, e.g.…”

Section: Introductionmentioning

confidence: 99%

Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment

Jayaram

Baker

2010

Earthq Engng Struct Dyn

134

102

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SUMMARYProbabilistic seismic risk assessment for spatially distributed lifelines is less straightforward than for individual structures. While procedures such as the 'PEER framework' have been developed for risk assessment of individual structures, these are not easily applicable to distributed lifeline systems, due to difficulties in describing ground-motion intensity (e.g. spectral acceleration) over a region (in contrast to ground-motion intensity at a single site, which is easily quantified using Probabilistic Seismic Hazard Analysis), and since the link between the ground-motion intensities and lifeline performance is usually not available in closed form. As a result, Monte Carlo simulation (MCS) and its variants are well suited for characterizing ground motions and computing resulting losses to lifelines. This paper proposes a simulation-based framework for developing a small but stochastically representative catalog of earthquake ground-motion intensity maps that can be used for lifeline risk assessment. In this framework, Importance Sampling is used to preferentially sample 'important' ground-motion intensity maps, and K -Means Clustering is used to identify and combine redundant maps in order to obtain a small catalog. The effects of sampling and clustering are accounted for through a weighting on each remaining map, so that the resulting catalog is still a probabilistically correct representation. The feasibility of the proposed simulation framework is illustrated by using it to assess the seismic risk of a simplified model of the San Francisco Bay Area transportation network. A catalog of just 150 intensity maps is generated to represent hazard at 1038 sites from 10 regional fault segments causing earthquakes with magnitudes between five and eight. The risk estimates obtained using these maps are consistent with those obtained using conventional MCS utilizing many orders of magnitudes more ground-motion intensity maps. Therefore, the proposed technique can be used to drastically reduce the computational expense of a simulationbased risk assessment, without compromising the accuracy of the risk estimates. This will facilitate computationally intensive risk analysis of systems such as transportation networks. Finally, the study shows that the uncertainties in the ground-motion intensities and the spatial correlations between ground-motion intensities at various sites must be modeled in order to obtain unbiased estimates of lifeline risk.

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Section: Introductionmentioning

confidence: 99%

Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment

Jayaram

Baker

2010

Earthq Engng Struct Dyn

134

102

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“…In an application of the method to a bridge transportation network [20], for example, the uncertain earthquake magnitude was considered as the CSRV for the numerical example. The conditional independence of the component events given S = s enables constructing p(s) efficiently by use of the same matrix procedure as developed originally for independent components.…”

Section: Review Of Matrix-based System Reliability Methodsmentioning

confidence: 99%

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

Song

2009

Earthq Engng Struct Dyn

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SUMMARYRecent 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

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“…Zhao proposed a moment-based method for structural system reliability assessment which is applicable to both series and non-series systems [23]. Kang proposed a matrix-based system reliability (MSR) method to estimate the probabilities of complex system events by simple matrix calculations [9].…”

Section: Introductionmentioning

confidence: 99%

A copula-based method for reliability sensitivity analysis of structural system with correlated failure modes

Lü

Zhu

2015

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Matrix-based system reliability method and applications to bridge networks

Cited by 170 publications

References 13 publications

Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment

Efficient sampling and data reduction techniques for probabilistic seismic lifeline risk assessment

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

A copula-based method for reliability sensitivity analysis of structural system with correlated failure modes

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