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Piecewise Deterministic Markov Processes based approach applied to an offshore oil production system

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  • Zhang, Huilong
  • Innal, Fares
  • Dufour, François
  • Dutuit, Yves

Abstract

This paper is keeping with the topic of two papers which treated dynamic reliability problems and were presented in previous conferences. Its aim is to confirm the potentialities of a method which combines the high modeling ability of the piecewise deterministic processes and the great computing power inherent to the Monte Carlo simulation. This method is now applied to a simplified but realistic offshore oil production system which is a hybrid system combining continuous-time and discrete-time dynamics. The results thus obtained have been compared with those given by an ad hoc Petri net model for comparison and validation purposes.

Suggested Citation

  • Zhang, Huilong & Innal, Fares & Dufour, François & Dutuit, Yves, 2014. "Piecewise Deterministic Markov Processes based approach applied to an offshore oil production system," Reliability Engineering and System Safety, Elsevier, vol. 126(C), pages 126-134.
    • Handle: RePEc:eee:reensy:v:126:y:2014:i:c:p:126-134
    DOI: 10.1016/j.ress.2014.01.016
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    References listed on IDEAS

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    1. Signoret, Jean-Pierre & Dutuit, Yves & Cacheux, Pierre-Joseph & Folleau, Cyrille & Collas, Stéphane & Thomas, Philippe, 2013. "Make your Petri nets understandable: Reliability block diagrams driven Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 113(C), pages 61-75.
    2. Boiteau, M. & Dutuit, Y. & Rauzy, A. & Signoret, J.-P., 2006. "The AltaRica data-flow language in use: modeling of production availability of a multi-state system," Reliability Engineering and System Safety, Elsevier, vol. 91(7), pages 747-755.
    3. Marseguerra, M. & Zio, E. & Devooght, J. & Labeau, P.E., 1998. "A concept paper on dynamic reliability via Monte Carlo simulation," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 47(2), pages 371-382.
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    Citations

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    Cited by:

    1. Bhardwaj, U. & Teixeira, A.P. & Guedes Soares, C., 2022. "Bayesian framework for reliability prediction of subsea processing systems accounting for influencing factors uncertainty," Reliability Engineering and System Safety, Elsevier, vol. 218(PA).
    2. Silva, L.M.R. & Guedes Soares, C., 2023. "Robust optimization model of an offshore oil production system for cost and pipeline risk of failure," Reliability Engineering and System Safety, Elsevier, vol. 232(C).
    3. Wang, Weikai & Chen, Xian, 2023. "Piecewise deterministic Markov process for condition-based imperfect maintenance models," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    4. Lin, Yan-Hui & Li, Yan-Fu & Zio, Enrico, 2018. "A comparison between Monte Carlo simulation and finite-volume scheme for reliability assessment of multi-state physics systems," Reliability Engineering and System Safety, Elsevier, vol. 174(C), pages 1-11.
    5. Zhao, Xian & Li, Rong & Cao, Shuai & Qiu, Qingan, 2023. "Joint modeling of loading and mission abort policies for systems operating in dynamic environments," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    6. Arismendi, Renny & Barros, Anne & Grall, Antoine, 2021. "Piecewise deterministic Markov process for condition-based maintenance models — Application to critical infrastructures with discrete-state deterioration," Reliability Engineering and System Safety, Elsevier, vol. 212(C).
    7. Anil Kr. Aggarwal & Vikram Singh & Sanjeev Kumar, 2017. "Availability analysis and performance optimization of a butter oil production system: a case study," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 8(1), pages 538-554, January.
    8. Leimeister, Mareike & Kolios, Athanasios, 2018. "A review of reliability-based methods for risk analysis and their application in the offshore wind industry," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1065-1076.
    9. Anis Ben Abdessalem & Romain Azaïs & Marie Touzet-Cortina & Anne Gégout-Petit & Monique Puiggali, 2016. "Stochastic modelling and prediction of fatigue crack propagation using piecewise-deterministic Markov processes," Journal of Risk and Reliability, , vol. 230(4), pages 405-416, August.

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