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

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  • Chiacchio, Ferdinando
  • Iacono, Alessandra
  • Compagno, Lucio
  • D'Urso, Diego

Abstract

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.

Suggested Citation

  • Chiacchio, Ferdinando & Iacono, Alessandra & Compagno, Lucio & D'Urso, Diego, 2020. "A general framework for dependability modelling coupling discrete-event and time-driven simulation," Reliability Engineering and System Safety, Elsevier, vol. 199(C).
    • Handle: RePEc:eee:reensy:v:199:y:2020:i:c:s0951832019303655
    DOI: 10.1016/j.ress.2020.106904
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    References listed on IDEAS

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    1. Fan, Mengfei & Zeng, Zhiguo & Zio, Enrico & Kang, Rui & Chen, Ying, 2018. "A stochastic hybrid systems model of common-cause failures of degrading components," Reliability Engineering and System Safety, Elsevier, vol. 172(C), pages 159-170.
    2. Manno, G. & Chiacchio, F. & Compagno, L. & D'Urso, D. & Trapani, N., 2014. "Conception of Repairable Dynamic Fault Trees and resolution by the use of RAATSS, a Matlab® toolbox based on the ATS formalism," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 250-262.
    3. Aizpurua, J.I. & Catterson, V.M. & Papadopoulos, Y. & Chiacchio, F. & D'Urso, D., 2017. "Supporting group maintenance through prognostics-enhanced dynamic dependability prediction," Reliability Engineering and System Safety, Elsevier, vol. 168(C), pages 171-188.
    4. Durga Rao, K. & Gopika, V. & Sanyasi Rao, V.V.S. & Kushwaha, H.S. & Verma, A.K. & Srividya, A., 2009. "Dynamic fault tree analysis using Monte Carlo simulation in probabilistic safety assessment," Reliability Engineering and System Safety, Elsevier, vol. 94(4), pages 872-883.
    5. Chiacchio, F. & D’Urso, D. & Manno, G. & Compagno, L., 2016. "Stochastic hybrid automaton model of a multi-state system with aging: Reliability assessment and design consequences," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 1-13.
    6. Chiacchio, Ferdinando & D’Urso, Diego & Famoso, Fabio & Brusca, Sebastian & Aizpurua, Jose Ignacio & Catterson, Victoria M., 2018. "On the use of dynamic reliability for an accurate modelling of renewable power plants," Energy, Elsevier, vol. 151(C), pages 605-621.
    7. Liu, Jie & Zio, Enrico, 2017. "System dynamic reliability assessment and failure prognostics," Reliability Engineering and System Safety, Elsevier, vol. 160(C), pages 21-36.
    8. Merle, G. & Roussel, J.-M. & Lesage, J.-J., 2011. "Algebraic determination of the structure function of Dynamic Fault Trees," Reliability Engineering and System Safety, Elsevier, vol. 96(2), pages 267-277.
    9. Gascard, Eric & Simeu-Abazi, Zineb, 2018. "Quantitative Analysis of Dynamic Fault Trees by means of Monte Carlo Simulations: Event-Driven Simulation Approach," Reliability Engineering and System Safety, Elsevier, vol. 180(C), pages 487-504.
    10. 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.
    11. Chiacchio, F. & Compagno, L. & D'Urso, D. & Manno, G. & Trapani, N., 2011. "Dynamic fault trees resolution: A conscious trade-off between analytical and simulative approaches," Reliability Engineering and System Safety, Elsevier, vol. 96(11), pages 1515-1526.
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    Cited by:

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    2. Xu, Jinjin & Wang, Rongxi & Liang, Zeming & Liu, Pengpeng & Gao, Jianmin & Wang, Zhen, 2023. "Physics-guided, data-refined fault root cause tracing framework for complex electromechanical system," Reliability Engineering and System Safety, Elsevier, vol. 236(C).
    3. Xu, Jintao & Gui, Maolei & Ding, Rui & Dai, Tao & Zheng, Mengyan & Men, Xinhong & Meng, Fanpeng & Yu, Tao & Sui, Yang, 2023. "A new approach for dynamic reliability analysis of reactor protection system for HPR1000," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    4. Zhou, Siwei & Ye, Luyao & Xiong, Shengwu & Xiang, Jianwen, 2022. "Reliability analysis of dynamic fault trees with Priority-AND gates based on irrelevance coverage model," Reliability Engineering and System Safety, Elsevier, vol. 224(C).
    5. Famoso, Fabio & Brusca, Sebastian & D'Urso, Diego & Galvagno, Antonio & Chiacchio, Ferdinando, 2020. "A novel hybrid model for the estimation of energy conversion in a wind farm combining wake effects and stochastic dependability," Applied Energy, Elsevier, vol. 280(C).

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