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Stochastic hybrid automata model for dynamic reliability assessment

Author

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  • G A Pérez Castañeda
  • J-F Aubry
  • N Brinzei

Abstract

A dynamic hybrid system is described by a set of continuous variables and a set of discrete events interacting together. The reality also requires taking into account component failures and the stochastic behaviour of the system. Some events or variables then take a stochastic character. The current paper presents the concept of a stochastic hybrid automaton (SHA) and its abilities to handle interactions between component failures, physical variables of the process, and operating modes of the system. Its use as a tool for Monte Carlo simulation that allows the evaluation of dependability parameters in a dynamic context is proposed. As a validation, the SHA approach has been applied to a benchmark problem studied by some other authors using different techniques (continuous cell-to-cell mapping technique, stochastic Petri nets, and piecewise deterministic Markov processes). The main interest is to show how the dependency between the probability distribution of a component failure and a physical continuous variable (temperature) may be handled. As an illustration of its other abilities, the SHA approach has been applied to a second application including particular components with multiple ageing modes. In this example the main interest is to highlight the problems of the modelling and the dependability assessment of a hybrid dynamic system.

Suggested Citation

  • G A Pérez Castañeda & J-F Aubry & N Brinzei, 2011. "Stochastic hybrid automata model for dynamic reliability assessment," Journal of Risk and Reliability, , vol. 225(1), pages 28-41, March.
  • Handle: RePEc:sae:risrel:v:225:y:2011:i:1:p:28-41
    DOI: 10.1177/1748006XJRR312
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    Cited by:

    1. Babykina, Génia & Brînzei, Nicolae & Aubry, Jean-François & Deleuze, Gilles, 2016. "Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton," Reliability Engineering and System Safety, Elsevier, vol. 152(C), pages 115-136.

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