A general framework for dependability modelling coupling discrete-event and time-driven simulation

• Published in: Reliability engineering & system safety Vol. 199; pp. 106904 - 22
• Main Authors: Chiacchio, Ferdinando, Iacono, Alessandra, Compagno, Lucio, D'Urso, Diego
• Format: Journal Article
• Language: English
• Published: Barking Elsevier Ltd 01.07.2020; Elsevier BV
• Subjects: Block diagrams; Discrete event systems; Dynamic reliability; Expert systems; Failure analysis; Fault tree analysis; Industrial engineering; Industrial plants; Industrial safety; Mathematical models; Mitigation; Monte carlo simulation; Multi-state systems modelling; Probabilistic risk assessment; Reliability analysis; Reliability engineering; Repairable dynamic fault trees; Risk assessment; Safety engineering; Simulation; Simulation analysis; Stochastic hybrid automaton; Stochasticity; Working conditions; Dynamic reliability; Repairable dynamic fault trees; Monte carlo simulation; Multi-state systems modelling; Stochastic hybrid automaton
• ISSN: 0951-8320; 1879-0836
• DOI: 10.1016/j.ress.2020.106904

•Comparison between dynamic fault tree and stochastic hybrid fault tree automaton.•Description of behaviours and constraints of the dynamic gates in a repairable dynamic fault tree.•Algorithm flow-chart of the discrete event and time driven simulation engine.•Matlab® implementation of a software library (SHyFTOO) for the simulation of SHyFTA.•Analysis of several stand-by configurations, including a daily load sharing of a vessel feed pump system. Analysis of complex failure scenarios and mitigation procedures of an industrial plant is one of the most important activity for the safety of the factory, the personnel and the surrounding areas. The dependability assessment of such systems is fulfilled by risk experts who, adopting well-known Reliability, Availability, Maintenance and Safety (RAMS) techniques, design and solve the stochastic failure model of the system. Traditional techniques like Fault Tree Analysis (FTA) or Reliability Block Diagrams (RBD) are of easy implementation but unrealistic, due to their simplified hypotheses that assume the components malfunction to be independent from each other and from the system working conditions. Dynamic Probabilistic Risk Assessment (DPRA) is the umbrella framework encompassing new mathematical and simulation formalisms aiming to relax the constraints of traditional techniques and increase the accuracy of dependability assessment. At the state of the art, DPRA cannot boast a well-defined methodology because the nature of a dynamic reliability problem can be so complex to require an ad-hoc modelling and resolution. Moreover, one of the main issues encountered by risk-practitioners is that there is a small support in terms of available tools or expert systems, specifically designed for DPRA problems. To tackle this lack, this paper presents the conception of general framework for the modelling and the simulation of a Stochastic Hybrid Fault Tree Automaton (SHyFTA), one of the most promising DPRA methodologies, able to combine Dynamic Fault Tree (DFT) with the deterministic model of the system process. The logic of the repairable DFT gates and the concepts for the implementation of a simulation engine combining Discrete Event Simulation (DES) and Time Driven Simulation (TDS) are illustrated and, a Matlab® toolbox library (SHyFTOO) has been coded and tested with a thorough validation campaign. Finally, a common case study in industrial engineering has been modelled and analysed under different stand-by configurations in order to demonstrate the modelling flexibility of the toolbox.