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)

[thumbnail of Feng-etal-ECCOMAS-2017-Efficient-reliability-and-uncertainty-assessment-on-lifeline]
Preview
 Text. Filename: Feng_etal_ECCOMAS_2017_Efficient_reliability_and_uncertainty_assessment_on_lifeline.pdf
Final Published Version
Download (1MB)| Preview

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.

CORE (COnnecting REpositories)