Resilience decision-making for complex systems

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dc.identifier.uri http://dx.doi.org/10.15488/10618
dc.identifier.uri https://www.repo.uni-hannover.de/handle/123456789/10696
dc.contributor.author Salomon, Julian
dc.contributor.author Broggi, Matteo
dc.contributor.author Kruse, Sebastian
dc.contributor.author Weber, Stefan
dc.contributor.author Beer, Michael
dc.date.accessioned 2021-03-25T06:34:04Z
dc.date.available 2021-03-25T06:34:04Z
dc.date.issued 2020
dc.identifier.citation Salomon, J.; Broggi, M.; Kruse, S.; Weber, S.; Beer, M.: Resilience decision-making for complex systems. In: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering 6 (2020), Nr. 2, 20901. DOI: https://doi.org/10.1115/1.4044907
dc.description.abstract Complex systems-such as gas turbines, industrial plants, and infrastructure networks- are of paramount importance to modern societies. However, these systems are subject to various threats. Novel research does not only focus on monitoring and improving the robustness and reliability of systems but also focus on their recovery from adverse events. The concept of resilience encompasses these developments. Appropriate quantitative measures of resilience can support decision-makers seeking to improve or to design complex systems. In this paper, we develop comprehensive and widely adaptable instruments for resilience-based decision-making. Integrating an appropriate resilience metric together with a suitable systemic risk measure, we design numerically efficient tools aiding decision-makers in balancing different resilience-enhancing investments. The approach allows for a direct comparison between failure prevention arrangements and recovery improvement procedures, leading to optimal tradeoffs with respect to the resilience of a system. In addition, the method is capable of dealing with the monetary aspects involved in the decision-making process. Finally, a grid search algorithm for systemic risk measures significantly reduces the computational effort. In order to demonstrate its wide applicability, the suggested decision-making procedure is applied to a functional model of a multistage axial compressor, and to the U-Bahn and S-Bahn system of Germany's capital Berlin. Copyright © 2020 by ASME. eng
dc.language.iso eng
dc.publisher New York, NY [u.a.] : American Society of Mechanical Engineers (ASME)
dc.relation.ispartofseries ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part B: Mechanical Engineering 6 (2020), Nr. 2
dc.rights CC BY 4.0 Unported
dc.rights.uri https://creativecommons.org/licenses/by/4.0/
dc.subject resilience eng
dc.subject complex systems eng
dc.subject resilience-based decision-making eng
dc.subject multistage axial compressor eng
dc.subject.ddc 620 | Ingenieurwissenschaften und Maschinenbau ger
dc.title Resilience decision-making for complex systems
dc.type article
dc.type Text
dc.relation.essn 2332-9017
dc.relation.issn 2332-9025
dc.relation.doi https://doi.org/10.1115/1.4044907
dc.bibliographicCitation.issue 2
dc.bibliographicCitation.volume 6
dc.bibliographicCitation.firstPage 20901
dc.description.version publishedVersion
tib.accessRights frei zug�nglich


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