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

SUMMARY 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 propo...

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Bibliographic Details
Published in:Earthquake engineering & structural dynamics 2012-10, Vol.41 (13), p.1861-1882
Main Authors: Lim, Hyun-Woo, Song, Junho
Format: Article
Language:English
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Summary:SUMMARY 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.
ISSN:0098-8847
1096-9845
DOI:10.1002/eqe.2162