Resilience Assessment under Imprecise Probability

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Autoren

Externe Organisationen

  • University of Wollongong
  • The University of Liverpool
  • Tongji University
  • Technische Universität Dortmund
  • Southeast University (SEU)
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Details

OriginalspracheEnglisch
Aufsatznummer04024025
Seitenumfang14
FachzeitschriftASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering
Jahrgang10
Ausgabenummer2
Frühes Online-Datum28 März 2024
PublikationsstatusVeröffentlicht - Juni 2024

Abstract

Resilience analysis of civil structures and infrastructure systems is a powerful approach to quantifying an object's ability to prepare for, recover from, and adapt to disruptive events. The resilience is typically measured probabilistically by the integration of the time-variant performance function, which is by nature a stochastic process as it is affected by many uncertain factors such as hazard occurrences and posthazard recoveries. Resilience evaluation could be challenging in many cases with imprecise probability information on the time-variant performance function. In this paper, a novel method for the assessment of imprecise resilience is presented, which deals with resilience problems with nonprobabilistic performance function. The proposed method, producing lower and upper bounds for imprecise resilience, has benefited from that for imprecise reliability as documented in the literature, motivated by the similarity between reliability and resilience. Two types of stochastic processes, namely log-Gamma and lognormal processes, are employed to model the performance function, with which the explicit form of resilience is derived. Moreover, for a planning horizon within which the hazards may occur for multiple times, the incompletely informed performance function results in "time-dependent imprecise resilience,"which is dependent on the duration of the service period (e.g., life cycle) and can also be handled by applying the proposed method. Through examining the time-dependent resilience of a strip foundation in a coastal area subjected to groundwater intrusion in a changing climate, the applicability of the proposed resilience bounding method is demonstrated. The impact of imprecise probability information on resilience is quantified through sensitivity analysis.

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Resilience Assessment under Imprecise Probability. / Wang, Cao; Beer, Michael; Faes, Matthias G.R. et al.
in: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, Jahrgang 10, Nr. 2, 04024025, 06.2024.

Publikation: Beitrag in FachzeitschriftArtikelForschungPeer-Review

Wang, C, Beer, M, Faes, MGR & Feng, DC 2024, 'Resilience Assessment under Imprecise Probability', ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, Jg. 10, Nr. 2, 04024025. https://doi.org/10.1061/AJRUA6.RUENG-1244
Wang, C., Beer, M., Faes, M. G. R., & Feng, D. C. (2024). Resilience Assessment under Imprecise Probability. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering, 10(2), Artikel 04024025. https://doi.org/10.1061/AJRUA6.RUENG-1244
Wang C, Beer M, Faes MGR, Feng DC. Resilience Assessment under Imprecise Probability. ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2024 Jun;10(2):04024025. Epub 2024 Mär 28. doi: 10.1061/AJRUA6.RUENG-1244
Wang, Cao ; Beer, Michael ; Faes, Matthias G.R. et al. / Resilience Assessment under Imprecise Probability. in: ASCE-ASME Journal of Risk and Uncertainty in Engineering Systems, Part A: Civil Engineering. 2024 ; Jahrgang 10, Nr. 2.
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T1 - Resilience Assessment under Imprecise Probability

AU - Wang, Cao

AU - Beer, Michael

AU - Faes, Matthias G.R.

AU - Feng, De Cheng

N1 - Funding Information: The research described in this paper was supported by the Career Development Fellowship for Cao Wang from the University of Wollongong. This support is gratefully acknowledged.

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N2 - Resilience analysis of civil structures and infrastructure systems is a powerful approach to quantifying an object's ability to prepare for, recover from, and adapt to disruptive events. The resilience is typically measured probabilistically by the integration of the time-variant performance function, which is by nature a stochastic process as it is affected by many uncertain factors such as hazard occurrences and posthazard recoveries. Resilience evaluation could be challenging in many cases with imprecise probability information on the time-variant performance function. In this paper, a novel method for the assessment of imprecise resilience is presented, which deals with resilience problems with nonprobabilistic performance function. The proposed method, producing lower and upper bounds for imprecise resilience, has benefited from that for imprecise reliability as documented in the literature, motivated by the similarity between reliability and resilience. Two types of stochastic processes, namely log-Gamma and lognormal processes, are employed to model the performance function, with which the explicit form of resilience is derived. Moreover, for a planning horizon within which the hazards may occur for multiple times, the incompletely informed performance function results in "time-dependent imprecise resilience,"which is dependent on the duration of the service period (e.g., life cycle) and can also be handled by applying the proposed method. Through examining the time-dependent resilience of a strip foundation in a coastal area subjected to groundwater intrusion in a changing climate, the applicability of the proposed resilience bounding method is demonstrated. The impact of imprecise probability information on resilience is quantified through sensitivity analysis.

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KW - Imprecise information

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ER -

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