A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
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.
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.
Seismic reliability assessment of lifeline networks using clustering‐based multi‐scale approach
Lim, Hyun‐Woo (author) / Song, Junho (author) / Kurtz, Nolan (author)
Earthquake Engineering & Structural Dynamics ; 44 ; 355-369
2015-03-01
15 pages
Article (Journal)
Electronic Resource
English
Seismic Reliability Assessment of Lifeline Systems
| British Library Conference Proceedings | 2014
Seismic Reliability Assessment of Critical Lifeline Equipment
| British Library Conference Proceedings | 1999
Research on seismic reliability algorithms of lifeline networks
| British Library Online Contents | 2006
Seismic reliability of lifeline systems
| British Library Conference Proceedings | 2001
Lifeline Services Seismic Disruption Assessment
| British Library Conference Proceedings | 1999