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Dependencies in event trees analyzed by Petri nets

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  • Nývlt, OndÅ™ej
  • Rausand, Marvin

Abstract

This paper discusses how non-marked Petri nets can be used to model and analyze event trees where the pivotal (branching) events are dependent and modeled by fault trees. The dependencies may, for example, be caused by shared utilities, shared components, or general common cause failures that are modeled by beta-factor models. These dependencies are cumbersome to take into account when using standard event-/fault tree modeling techniques, and may lead to significant errors in the calculated end-state probabilities of the event tree if they are not properly analyzed. A new approach is proposed in this paper, where the whole event tree is modeled by a non-marked Petri net and where P-invariants, representing the structural properties of the Petri net, are used to obtain the frequency of each end-state of the event tree with dependencies. The new approach is applied to a real example of an event tree analysis of the Strahov highway tunnel in Prague, Czech Republic, including two types of dependencies (shared Programmable Logic Controllers and Common Cause Failures).

Suggested Citation

  • Nývlt, OndÅ™ej & Rausand, Marvin, 2012. "Dependencies in event trees analyzed by Petri nets," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 45-57.
  • Handle: RePEc:eee:reensy:v:104:y:2012:i:c:p:45-57
    DOI: 10.1016/j.ress.2012.03.013
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    References listed on IDEAS

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    1. C Ibáñez-Llano & A Rauzy & E Meléndez & F Nieto, 2009. "Minimal cutsets-based reduction approach for the use of binary decision diagrams on probabilistic safety assessment fault tree models," Journal of Risk and Reliability, , vol. 223(4), pages 301-311, December.
    2. P Škňouřilová & R Briš, 2008. "Coloured Petri nets and a dynamic reliability problem," Journal of Risk and Reliability, , vol. 222(4), pages 635-642, December.
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    Cited by:

    1. Li, Weijun & Sun, Qiqi & Zhang, Jiwang & Zhang, Laibin, 2024. "Quantitative risk assessment of industrial hot work using Adaptive Bow Tie and Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 242(C).
    2. Jianing Wu & Shaoze Yan, 2014. "An approach to system reliability prediction for mechanical equipment using fuzzy reasoning Petri net," Journal of Risk and Reliability, , vol. 228(1), pages 39-51, February.
    3. Gonçalves, P. & Sobral, J. & Ferreira, L.A., 2017. "Unmanned aerial vehicle safety assessment modelling through petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 167(C), pages 383-393.
    4. 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).
    5. Arthur H.A. Melani & Carlos A. Murad & Adherbal Caminada Netto & Gilberto F.M. Souza & Silvio I. Nabeta, 2019. "Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets," Energies, MDPI, vol. 12(10), pages 1-28, May.

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