Modeling and simulation of a controlled steam generator in the context of dynamic reliability using a Stochastic Hybrid Automaton
| Autor: | Nicolae Brinzei, Gilles Deleuze, Génia Babykina, Jean-François Aubry |
|---|---|
| Přispěvatelé: | Centre de Recherche en Automatique de Nancy (CRAN), Centre National de la Recherche Scientifique (CNRS)-Université de Lorraine (UL), Management des Risques Industriels (EDF R&D MRI), EDF R&D (EDF R&D), EDF (EDF)-EDF (EDF) |
| Jazyk: | angličtina |
| Rok vydání: | 2016 |
| Předmět: |
Mathematical optimization
Computer science 020209 energy Monte Carlo method 02 engineering and technology 7. Clean energy Industrial and Manufacturing Engineering System model Monte Carlo simulations [SPI.AUTO]Engineering Sciences [physics]/Automatic Modeling and simulation dynamic reliability 0202 electrical engineering electronic engineering information engineering Dependability Hybrid automaton Safety Risk Reliability and Quality Finite-state machine events sequences analysis Control engineering power plant subsystem [INFO.INFO-PF]Computer Science [cs]/Performance [cs.PF] Hybrid system steam generator dynamics Probability distribution Stochastic Hybrid Automaton reliability assessment |
| Zdroj: | Reliability Engineering and System Safety Reliability Engineering and System Safety, Elsevier, 2016, 152, pp.115-136. ⟨10.1016/j.ress.2016.03.009⟩ |
| ISSN: | 0951-8320 1879-0836 |
| DOI: | 10.1016/j.ress.2016.03.009⟩ |
| Popis: | International audience; 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Full Text from ScienceDirect