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Dynamic fault trees resolution: A conscious trade-off between analytical and simulative approaches

Author

Listed:
  • Chiacchio, F.
  • Compagno, L.
  • D'Urso, D.
  • Manno, G.
  • Trapani, N.

Abstract

Safety assessment in industrial plants with ‘major hazards’ requires a rigorous combination of both qualitative and quantitative techniques of RAMS. Quantitative assessment can be executed by static or dynamic tools of dependability but, while the former are not sufficient to model exhaustively time-dependent activities, the latter are still too complex to be used with success by the operators of the industrial field.

Suggested Citation

  • 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.
  • Handle: RePEc:eee:reensy:v:96:y:2011:i:11:p:1515-1526
    DOI: 10.1016/j.ress.2011.06.014
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    Citations

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    Cited by:

    1. Chemweno, Peter & Pintelon, Liliane & Van Horenbeek, Adriaan & Muchiri, Peter, 2015. "Development of a risk assessment selection methodology for asset maintenance decision making: An analytic network process (ANP) approach," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 663-676.
    2. Ge, Daochuan & Lin, Meng & Yang, Yanhua & Zhang, Ruoxing & Chou, Qiang, 2015. "Quantitative analysis of dynamic fault trees using improved Sequential Binary Decision Diagrams," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 289-299.
    3. 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.
    4. 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.
    5. Son, Kwang Seop & Kim, Dong Hoon & Kim, Chang Hwoi & Kang, Hyun Gook, 2016. "Study on the systematic approach of Markov modeling for dependability analysis of complex fault-tolerant features with voting logics," Reliability Engineering and System Safety, Elsevier, vol. 150(C), pages 44-57.
    6. 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.
    7. Raoni, Rafael & Secchi, Argimiro R., 2019. "Procedures to model and solve probabilistic dynamic system problems," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    8. Chemweno, Peter & Pintelon, Liliane & Muchiri, Peter Nganga & Van Horenbeek, Adriaan, 2018. "Risk assessment methodologies in maintenance decision making: A review of dependability modelling approaches," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 64-77.
    9. 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).
    10. Chiacchio, F. & Cacioppo, M. & D'Urso, D. & Manno, G. & Trapani, N. & Compagno, L., 2013. "A Weibull-based compositional approach for hierarchical dynamic fault trees," Reliability Engineering and System Safety, Elsevier, vol. 109(C), pages 45-52.
    11. Sejin Baek & Gyunyoung Heo, 2021. "Application of Dynamic Fault Tree Analysis to Prioritize Electric Power Systems in Nuclear Power Plants," Energies, MDPI, vol. 14(14), pages 1-17, July.

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