Rare Event Simulation for Non-Markovian Repairable Fault Trees

Carlos E. Budde*, Marco Biagi, Raúl E. Monti, Pedro R. D’Argenio, Mariëlle Stoelinga

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)
9 Downloads (Pure)

Abstract

Dynamic fault trees (DFT) are widely adopted in industry to assess the dependability of safety-critical equipment. Since many systems are too large to be studied numerically, DFTs dependability is often analysed using Monte Carlo simulation. A bottleneck here is that many simulation samples are required in the case of rare events, e.g. in highly reliable systems where components fail seldomly. Rare event simulation (RES) provides techniques to reduce the number of samples in the case of rare events. We present a RES technique based on importance splitting, to study failures in highly reliable DFTs. Whereas RES usually requires meta-information from an expert, our method is fully automatic: By cleverly exploiting the fault tree structure we extract the so-called importance function. We handle DFTs with Markovian and non-Markovian failure and repair distributions—for which no numerical methods exist—and show the efficiency of our approach on several case studies.

Original languageEnglish
Title of host publicationTools and Algorithms for the Construction and Analysis of Systems
Subtitle of host publication26th International Conference, TACAS 2020, Held as Part of the European Joint Conferences on Theory and Practice of Software, ETAPS 2020, Dublin, Ireland, April 25–30, 2020, Proceedings
EditorsArmin Biere, David Parker
Place of PublicationCham
PublisherSpringer Singapore
Pages463-482
Number of pages20
VolumeI
ISBN (Electronic)978-3-030-45190-5
ISBN (Print)978-3-030-45189-9
DOIs
Publication statusPublished - 17 Apr 2020

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
Volume12078
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Keywords

  • Dynamic fault trees
  • Rare event simulation
  • System reliability analysis

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