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Deterioration modeling and maintenance assessment using physics-informed stochastic Petri nets: Application to torrent protection structures

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  • Chahrour, Nour
  • Nasr, Mohamad
  • Tacnet, Jean-Marc
  • Bérenguer, Christophe

Abstract

Mountain territories are remarkably exposed to natural phenomena such as torrential floods, arising due to climate and geophysical environmental changes. Protection structures deteriorate with time due to the harsh phenomena they are subjected to since their construction. If not regularly maintained, the level of protection offered by these structures will be reduced. The methodology presented in this paper integrates physics-based and dependability models for monitoring the state evolution of protection structures and improving maintenance decision-making processes. The modeling approach proposed is based on (1) physics-based modeling for identifying the probabilistic laws of the transition times between the defined states of the structure depending on its behavior over time and (2) a decision aiding method based on Petri nets, which helps in choosing the best maintenance strategy while considering budgetary constraints. This approach is applied on a check dam located within a series of check dams in the Manival torrent in Saint-Ismier, France.

Suggested Citation

  • Chahrour, Nour & Nasr, Mohamad & Tacnet, Jean-Marc & Bérenguer, Christophe, 2021. "Deterioration modeling and maintenance assessment using physics-informed stochastic Petri nets: Application to torrent protection structures," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    • Handle: RePEc:eee:reensy:v:210:y:2021:i:c:s0951832021000855
    DOI: 10.1016/j.ress.2021.107524
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    References listed on IDEAS

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    Cited by:

    1. Chahrour, Nour & Bérenguer, Christophe & Tacnet, Jean-Marc, 2024. "Incorporating cascading effects analysis in the maintenance policy assessment of torrent check dams against torrential floods," Reliability Engineering and System Safety, Elsevier, vol. 243(C).
    2. Chiachío, Manuel & Saleh, Ali & Naybour, Susannah & Chiachío, Juan & Andrews, John, 2022. "Reduction of Petri net maintenance modeling complexity via Approximate Bayesian Computation," Reliability Engineering and System Safety, Elsevier, vol. 222(C).
    3. Xu, Yanwen & Kohtz, Sara & Boakye, Jessica & Gardoni, Paolo & Wang, Pingfeng, 2023. "Physics-informed machine learning for reliability and systems safety applications: State of the art and challenges," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Yan, R. & Dunnett, S.J. & Jackson, L.M., 2022. "Model-Based Research for Aiding Decision-Making During the Design and Operation of Multi-Load Automated Guided Vehicle Systems," Reliability Engineering and System Safety, Elsevier, vol. 219(C).
    5. Zhou, Jianfeng & Reniers, Genserik, 2022. "Petri-net based cooperation modeling and time analysis of emergency response in the context of domino effect prevention in process industries," Reliability Engineering and System Safety, Elsevier, vol. 223(C).
    6. Sun, Qinying & Ma, Haiqun, 2024. "Modelling and performance analysis of the COVID-19 emergency collaborative process based on a stochastic Petri net," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    7. Rose, Rodrigo L. & Mugi, Sohan R. & Saleh, Joseph Homer, 2023. "Accident investigation and lessons not learned: AcciMap analysis of successive tailings dam collapses in Brazil," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    8. Liu, Shuanglei & Li, Weijun & Gao, Peng & Sun, Yibo, 2022. "Modeling and performance analysis of gas leakage emergency disposal process in gas transmission station based on Stochastic Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 226(C).

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