Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton. (August 2016)

• Record Type: Journal Article
• Authors: Babykina, Génia; Brînzei, Nicolae; Aubry, Jean-François; Deleuze, Gilles
• Is Part Of: Reliability engineering & system safety. Volume 152(2016:Aug.)
• Page Start: 115
• Page End: 136
• Publication Date: 2016-08
• Subjects: Dynamic reliability -- Stochastic Hybrid Automaton -- Automata composition -- Monte Carlo simulations -- Sequence analysis -- Reliability assessment -- Power plant subsystem -- Steam generator dynamics; Reliability (Engineering) -- Periodicals; System safety -- Periodicals; Industrial safety -- Periodicals; Fiabilité -- Périodiques; Sécurité des systèmes -- Périodiques; Sécurité du travail -- Périodiques; 620.00452
• DOI: 10.1016/j.ress.2016.03.009
• Languages: English
• ISSNs: 0951-8320

Abstract

Abstract: The paper proposes a modeling framework to support Monte Carlo simulations of the behavior of a complex industrial system. The aim is to analyze the system dependability in the presence of random events, described by any type of probability distributions. Continuous dynamic evolutions of physical parameters are taken into account by a system of differential equations. Dynamic reliability is chosen as theoretical framework. Based on finite state automata theory, the formal model is built by parallel composition of elementary sub-models using a bottom-up approach. Considerations of a stochastic nature lead to a model called the Stochastic Hybrid Automaton. The Scilab/Scicos open source environment is used for implementation. The case study is carried out on an example of a steam generator of a nuclear power plant. The behavior of the system is studied by exploring its trajectories. Possible system trajectories are analyzed both empirically, using the results of Monte Carlo simulations, and analytically, using the formal system model. The obtained results are show to be relevant. The Stochastic Hybrid Automaton appears to be a suitable tool to address the dynamic reliability problem and to model real systems of high complexity; the bottom-up design provides precision and coherency of the system model. Abstract : Highlights: A part of a nuclear power plant is modeled in the context of dynamic reliability. Stochastic Hybrid Automaton is used as an input model for Monte Carlo simulations. The model is formally built using a bottom-up approach. The behavior of the system is analyzed empirically and analytically. A formally built SHA shows to be a suitable tool to approach dynamic reliability.