Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019 |
| Herausgeber/-innen | Michael Beer, Enrico Zio |
| Seiten | 1357-1364 |
| Seitenumfang | 8 |
| ISBN (elektronisch) | 9789811127243 |
| Publikationsstatus | Veröffentlicht - 2020 |
| Veranstaltung | 29th European Safety and Reliability Conference, ESREL 2019 - Leibniz University Hannover, Hannover, Deutschland Dauer: 22 Sept. 2019 → 26 Sept. 2019 |
Abstract
The resilience of complex systems such as gas turbines, industrial plants, or critical infrastructure networks is of increasingly higher interest to engineers. Instead of solely concentrating on the robustness of systems and their ability to withstand certain threats, research is more and more focused on their ability to recover from these events as well. Appropriate quantitative measures of resilience can support decision-makers seeking to improve or to design complex systems. In this paper, a previously developed comprehensive and adaptable resilience-based decision-making method is extended to handle higher-dimensional problems subject to monetary constraints. The technique applies a grid search algorithm for systemic risk measures to significantly reduce the computational effort. In order to demonstrate its usefulness, the extended decision-making procedure is applied to a functional model of a multistage high-speed axial compressor.
ASJC Scopus Sachgebiete
- Ingenieurwesen (insg.)
- Sicherheit, Risiko, Zuverlässigkeit und Qualität
- Sozialwissenschaften (insg.)
- Sicherheitsforschung
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Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019. Hrsg. / Michael Beer; Enrico Zio. 2020. S. 1357-1364.
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Multidimensional resilience decision-making on a multistage high-speed axial compressor
AU - Salomon, Julian
AU - Behrensdorf, Jasper
AU - Broggi, Matteo
AU - Weber, Stefan
AU - Beer, Michael
N1 - Funding information: The authors kindly thank the German Research Foundation (DFG) for the financial support to accomplish the research project D5 “Resilience Based Decision Criteria for Optimal Regeneration” within the Collaborative Research Center (CRC) 871 - Regeneration of Complex Capital Goods. In a previous work within the Collaborative Research Center 871, funded by the German Research Foundation Miro et al. (2018) provide a functional model of the four-stage high-speed axial compressor of the Institute for Turbomachinery and Fluid Dynamics at Leibniz Universität Hannover, representing its reliability characteristic and functionality. For detailed information about this axial compressor see: Braun and Se-ume (2006); Hellmich and Seume (2008); Sie-mann et al. (2016).
PY - 2020
Y1 - 2020
N2 - The resilience of complex systems such as gas turbines, industrial plants, or critical infrastructure networks is of increasingly higher interest to engineers. Instead of solely concentrating on the robustness of systems and their ability to withstand certain threats, research is more and more focused on their ability to recover from these events as well. Appropriate quantitative measures of resilience can support decision-makers seeking to improve or to design complex systems. In this paper, a previously developed comprehensive and adaptable resilience-based decision-making method is extended to handle higher-dimensional problems subject to monetary constraints. The technique applies a grid search algorithm for systemic risk measures to significantly reduce the computational effort. In order to demonstrate its usefulness, the extended decision-making procedure is applied to a functional model of a multistage high-speed axial compressor.
AB - The resilience of complex systems such as gas turbines, industrial plants, or critical infrastructure networks is of increasingly higher interest to engineers. Instead of solely concentrating on the robustness of systems and their ability to withstand certain threats, research is more and more focused on their ability to recover from these events as well. Appropriate quantitative measures of resilience can support decision-makers seeking to improve or to design complex systems. In this paper, a previously developed comprehensive and adaptable resilience-based decision-making method is extended to handle higher-dimensional problems subject to monetary constraints. The technique applies a grid search algorithm for systemic risk measures to significantly reduce the computational effort. In order to demonstrate its usefulness, the extended decision-making procedure is applied to a functional model of a multistage high-speed axial compressor.
KW - Complex systems
KW - Decision-making
KW - Multidimensionality
KW - Resilience
UR - http://www.scopus.com/inward/record.url?scp=85089200482&partnerID=8YFLogxK
U2 - 10.3850/978-981-11-2724-3_0992-cd
DO - 10.3850/978-981-11-2724-3_0992-cd
M3 - Conference contribution
AN - SCOPUS:85089200482
SP - 1357
EP - 1364
BT - Proceedings of the 29th European Safety and Reliability Conference, ESREL 2019
A2 - Beer, Michael
A2 - Zio, Enrico
T2 - 29th European Safety and Reliability Conference, ESREL 2019
Y2 - 22 September 2019 through 26 September 2019
ER -