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Effective Static and Dynamic Fault Tree Analysis

  • Ola Bäckström
  • Yuliya Butkova
  • Holger Hermanns
  • Jan Krčál
  • Pavel Krčál
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9922)

Abstract

Fault trees constitute one of the essential formalisms for static safety analysis of various industrial systems. Dynamic fault trees (DFT) enrich the formalism by support for time-dependent behaviour, e.g., repairs or dynamic dependencies. This enables more realistic and more precise modelling, and can thereby avoid overly pessimistic analysis results. But analysis of DFT is so far limited to substantially smaller models than those required for instance in the domain of nuclear power safety. This paper considers so called SD fault trees, where the user is free to express each equipment failure either statically, without modelling temporal information, or dynamically, allowing repairs and other timed interdependencies. We introduce an analysis algorithm for an important subclass of SD fault trees. The algorithm employs automatic abstraction techniques effectively, and thereby scales similarly to static analysis algorithms, albeit allowing for a more realistic modelling and analysis. We demonstrate the applicability of the method by an experimental evaluation on fault trees of nuclear power plants.

Keywords

Diesel Engine Failure Probability Basic Event Fault Tree Mission Time 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Notes

Acknowledgments

This work is partly supported by the ERC Advanced Investigators Grant 695614 (POWVER), by the EU 7th Framework Programme under grant agreement no. 318490 (SENSATION) and 288175 (CERTAINTY), by the DFG Transregional Collaborative Research Centre SFB/TR 14 AVACS, by the CDZ project 1023 (CAP), and by the Czech Science Foundation, grant No. P202/12/G061.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  1. 1.Lloyd’s Register ConsultingStockholmSweden
  2. 2.Computer ScienceSaarland UniversitySaarbrückenGermany

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