Efficient reliability and uncertainty assessment on lifeline networks using the survival signature
Feng, Geng and Reed, Sean and Patelli, Edoardo and Beer, Michael and Coolen, Frank P.A.; Stefanou, George and Papadrakakis, M. and Papadopoulos, Vissarion, eds. (2017) Efficient reliability and uncertainty assessment on lifeline networks using the survival signature. In: UNCECOMP 2017 - Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering. National Technical University of Athens, GRC, pp. 90-99. ISBN 9786188284449 (https://doi.org/10.7712/120217.5354.16865)
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Abstract
Lifeline networks, such as water distribution and transportation networks, are the backbone of our societies, and the study of their reliability of them is required. In this paper, a survival signature-based reliability analysis method is proposed to analyse the complex networks. It allows to consider all the characters of the network instead of just analysing the most critical path. What is more, the survival signature separates the system structure from its failure distributions, and it only needs to be calculated once, which makes it efficient to analyse complex networks. However, due to lack of data, there often exists imprecision within the network failure time distribution parameters and hence the survival signature. An efficient algorithm which bases on the reduced ordered binary decision diagrams (BDD) data structure for the computation of survival signatures is presented. Numerical example shows the applicability of the approaches.
ORCID iDs
Feng, Geng, Reed, Sean, Patelli, Edoardo ORCID: https://orcid.org/0000-0002-5007-7247, Beer, Michael and Coolen, Frank P.A.; Stefanou, George, Papadrakakis, M. and Papadopoulos, Vissarion-
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Item type: Book Section ID code: 72208 Dates: DateEvent17 June 2017PublishedSubjects: Social Sciences > Industries. Land use. Labor > Risk Management Department: Faculty of Engineering > Civil and Environmental Engineering Depositing user: Pure Administrator Date deposited: 30 Apr 2020 09:35 Last modified: 11 Nov 2024 15:21 Related URLs: URI: https://strathprints.strath.ac.uk/id/eprint/72208