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A control-guided failure restoration framework for the design of resilient engineering systems

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  • Yodo, Nita
  • Wang, Pingfeng

Abstract

When failures are inevitable, a resilient system is expected to restore ideal performance in a timely manner. The resilience of a system can be improved by enhancing the post-failure restoration ability of the system. In order to determine whether resilience in a system is sufficient towards a certain failure, a set of design parameters and performance equations describing the system behavior are essential in performing a resilience assessment. However, in implicit system applications, one of the main concerns is that there are no clearly defined system equations to describe system performance. To overcome this challenge, this paper presents a control-guided failure restoration (CGFR) framework, which combines dynamic system modeling and resilience analysis. Since there are no clearly defined system equations in implicit systems, the dynamic system modeling in the proposed framework is equipped with an artificial neural network to learn system behaviors. To demonstrate the feasibility of the proposed approach, a power transmission system is employed as a case study. The presented study aims to encourage the development of advanced failure restoration strategies for resilient engineered systems.

Suggested Citation

  • Yodo, Nita & Wang, Pingfeng, 2018. "A control-guided failure restoration framework for the design of resilient engineering systems," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 179-190.
    • Handle: RePEc:eee:reensy:v:178:y:2018:i:c:p:179-190
    DOI: 10.1016/j.ress.2018.05.018
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    References listed on IDEAS

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    1. Ouyang, Min & Wang, Zhenghua, 2015. "Resilience assessment of interdependent infrastructure systems: With a focus on joint restoration modeling and analysis," Reliability Engineering and System Safety, Elsevier, vol. 141(C), pages 74-82.
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    5. Yu, Soonyoung & Kim, Sung-Wook & Oh, Chang-Whan & An, Hyunuk & Kim, Jin-Man, 2015. "Quantitative assessment of disaster resilience: An empirical study on the importance of post-disaster recovery costs," Reliability Engineering and System Safety, Elsevier, vol. 137(C), pages 6-17.
    6. Timothy Matisziw & Alan Murray & Tony Grubesic, 2010. "Strategic Network Restoration," Networks and Spatial Economics, Springer, vol. 10(3), pages 345-361, September.
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    Cited by:

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    3. Yasir Mahmood & Tanzina Afrin & Ying Huang & Nita Yodo, 2023. "Sustainable Development for Oil and Gas Infrastructure from Risk, Reliability, and Resilience Perspectives," Sustainability, MDPI, vol. 15(6), pages 1-22, March.
    4. Adel Mottahedi & Farhang Sereshki & Mohammad Ataei & Ali Nouri Qarahasanlou & Abbas Barabadi, 2021. "The Resilience of Critical Infrastructure Systems: A Systematic Literature Review," Energies, MDPI, vol. 14(6), pages 1-32, March.

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