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Quantitative evaluation of Pandora Temporal Fault Trees via Petri Nets

Kabir, Sohag; Papadopoulos, Yiannis; Walker, Martin


Sohag Kabir

Martin Walker


© 2015, IFAC (International Federation of Automatic Control) Hosting by Elsevier Ltd. All rights reserved. Using classical combinatorial fault trees, analysts are able to assess the effects of combinations of failures on system behaviour but are unable to capture sequence dependent dynamic behaviour. Pandora introduces temporal gates and temporal laws to fault trees to allow sequence-dependent dynamic analysis of events. Pandora can be easily integrated in model-based design and analysis techniques; however, the combinatorial quantification techniques used to solve classical fault trees cannot be applied to temporal fault trees. Temporal fault trees capture state and therefore require a state space solution for quantification of probability. In this paper, we identify Petri Nets as a possible framework for quantifying temporal trees. We describe how Pandora fault trees can be mapped to Petri Nets for dynamic dependability analysis and demonstrate the process on a fault tolerant fuel distribution system model.


Kabir, S., Papadopoulos, Y., & Walker, M. (2015). Quantitative evaluation of Pandora Temporal Fault Trees via Petri Nets. IFAC Proceedings Volumes/ International Federation of Automatic Control, 48(21), 458-463.

Journal Article Type Article
Conference Name IFAC-PapersOnLine
Acceptance Date May 8, 2015
Publication Date Sep 1, 2015
Deposit Date Feb 29, 2016
Publicly Available Date Nov 23, 2017
Journal IFAC-PapersOnLine
Print ISSN 1474-6670
Electronic ISSN 2405-8963
Publisher Elsevier
Peer Reviewed Peer Reviewed
Volume 48
Issue 21
Pages 458-463
Keywords Dependability analysis, Fault tree analysis, Stochastic petri nets, Temporal fault nets
Public URL
Publisher URL
Additional Information This is the accepted manuscript version of a paper published in IFAC-Papersonline, 2015, v.48 issue 21.


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Copyright Statement
© 2016 IFAC. Originally published in IFAC-PapersOnline, vol. 48, no. 21 by Elsevier Ltd. (DOI 10.1016/j.ifacol.2015.09.569)

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