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Complex accident scenarios modelled and analysed by Stochastic Petri Nets

Author

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  • Nývlt, OndÅ™ej
  • Haugen, Stein
  • Ferkl, Lukáš

Abstract

This paper is focused on the usage of Petri nets for an effective modelling and simulation of complicated accident scenarios, where an order of events can vary and some events may occur anywhere in an event chain. These cases are hardly manageable by traditional methods as event trees – e.g. one pivotal event must be often inserted several times into one branch of the tree. Our approach is based on Stochastic Petri Nets with Predicates and Assertions and on an idea, which comes from the area of Programmable Logic Controllers: an accidental scenario is described as a net of interconnected blocks, which represent parts of the scenario. So the scenario is firstly divided into parts, which are then modelled by Petri nets. Every block can be easily interconnected with other blocks by input/output variables to create complex ones. In the presented approach, every event or a part of a scenario is modelled only once, independently on a number of its occurrences in the scenario. The final model is much more transparent then the corresponding event tree. The method is shown in two case studies, where the advanced one contains a dynamic behavior.

Suggested Citation

  • Nývlt, OndÅ™ej & Haugen, Stein & Ferkl, Lukáš, 2015. "Complex accident scenarios modelled and analysed by Stochastic Petri Nets," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 539-555.
    • Handle: RePEc:eee:reensy:v:142:y:2015:i:c:p:539-555
    DOI: 10.1016/j.ress.2015.06.015
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    Cited by:

    1. Taleb-Berrouane, Mohammed & Khan, Faisal & Amyotte, Paul, 2020. "Bayesian Stochastic Petri Nets (BSPN) - A new modelling tool for dynamic safety and reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    2. Cheng, Ruijun & Zhou, Jin & Chen, Dewang & Song, Yongduan, 2016. "Model-based verification method for solving the parameter uncertainty in the train control system," Reliability Engineering and System Safety, Elsevier, vol. 145(C), pages 169-182.
    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. Raoni, Rafael & Secchi, Argimiro R., 2019. "Procedures to model and solve probabilistic dynamic system problems," Reliability Engineering and System Safety, Elsevier, vol. 191(C).

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