Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | UNCECOMP 2017 |
| Untertitel | Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering |
| Herausgeber/-innen | George Stefanou, M. Papadrakakis, Vissarion Papadopoulos |
| Seiten | 90-99 |
| Seitenumfang | 10 |
| ISBN (elektronisch) | 9786188284449 |
| Publikationsstatus | Veröffentlicht - 2017 |
| Veranstaltung | 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017 - Rhodes Island, Griechenland Dauer: 15 Juni 2017 → 17 Juni 2017 |
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.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Theoretische Informatik und Mathematik
- Informatik (insg.)
- Angewandte Informatik
- Mathematik (insg.)
- Theoretische Informatik
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UNCECOMP 2017: Proceedings of the 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering. Hrsg. / George Stefanou; M. Papadrakakis; Vissarion Papadopoulos. 2017. S. 90-99.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Efficient reliability and uncertainty assessment on lifeline networks using the survival signature
AU - Feng, Geng
AU - Reed, Sean
AU - Patelli, Edoardo
AU - Beer, Michael
AU - Coolen, Frank P.A.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
KW - Binary decision diagrams
KW - Imprecision
KW - Lifeline networks
KW - Reliability analysis
KW - Survival signature
KW - Uncertainty assessment
UR - http://www.scopus.com/inward/record.url?scp=85043460246&partnerID=8YFLogxK
U2 - 10.7712/120217.5354.16865
DO - 10.7712/120217.5354.16865
M3 - Conference contribution
AN - SCOPUS:85043460246
SP - 90
EP - 99
BT - UNCECOMP 2017
A2 - Stefanou, George
A2 - Papadrakakis, M.
A2 - Papadopoulos, Vissarion
T2 - 2nd International Conference on Uncertainty Quantification in Computational Sciences and Engineering, UNCECOMP 2017
Y2 - 15 June 2017 through 17 June 2017
ER -