Abstract

Fault trees (FT) are a popular industrial method for reliability engineering, for which Monte Carlo simulation is an important technique to estimate common dependability metrics, such as the system reliability and availability. A severe drawback of Monte Carlo simulation is that the number of simulations required to obtain accurate estimations grows extremely large in the presence of rare events, i.e., events whose probability of occurrence is very low, which typically holds for failures in highly reliable systems. This paper presents a novel method for rare event simulation of dynamic fault trees with complex repairs that requires only a modest number of simulations, while retaining statistically justified confidence intervals. Our method exploits the importance sampling technique for rare event simulation, together with a compositional state space generation method for dynamic fault trees. We demonstrate our approach using two parameterized sets of case studies, showing that our method can handle fault trees that could not be evaluated with either existing analytical techniques, nor with standard simulation techniques.
LanguageUndefined
Place of PublicationEnschede
PublisherCentre for Telematics and Information Technology (CTIT)
Number of pages14
StatePublished - 10 Mar 2017

Publication series

NameCTIT technical report series
PublisherUniversity of Twente, Centre for Telematics and Information Technology (CTIT)
No.TR-CTIT-17-02
ISSN (Print)1381-3625

Keywords

  • IR-104411
  • EWI-27862
  • Rare event simulation
  • Fault Tree Analysis
  • Monte Carlo Simulation
  • Importance sampling
  • Dynamic Fault Trees

Cite this

Ruijters, E. J. J., Reijsbergen, D. P., de Boer, P-T., & Stoelinga, M. I. A. (2017). Rare event simulation for dynamic fault trees. (CTIT technical report series; No. TR-CTIT-17-02). Enschede: Centre for Telematics and Information Technology (CTIT).
Ruijters, Enno Jozef Johannes ; Reijsbergen, D.P. ; de Boer, Pieter-Tjerk ; Stoelinga, Mariëlle Ida Antoinette. / Rare event simulation for dynamic fault trees. Enschede : Centre for Telematics and Information Technology (CTIT), 2017. 14 p. (CTIT technical report series; TR-CTIT-17-02).
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Ruijters, EJJ, Reijsbergen, DP, de Boer, P-T & Stoelinga, MIA 2017, Rare event simulation for dynamic fault trees. CTIT technical report series, no. TR-CTIT-17-02, Centre for Telematics and Information Technology (CTIT), Enschede.

Rare event simulation for dynamic fault trees. / Ruijters, Enno Jozef Johannes; Reijsbergen, D.P.; de Boer, Pieter-Tjerk; Stoelinga, Mariëlle Ida Antoinette.

Enschede : Centre for Telematics and Information Technology (CTIT), 2017. 14 p. (CTIT technical report series; No. TR-CTIT-17-02).

Research output: Book/ReportReport

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AU - Stoelinga,Mariëlle Ida Antoinette

PY - 2017/3/10

Y1 - 2017/3/10

N2 - Fault trees (FT) are a popular industrial method for reliability engineering, for which Monte Carlo simulation is an important technique to estimate common dependability metrics, such as the system reliability and availability. A severe drawback of Monte Carlo simulation is that the number of simulations required to obtain accurate estimations grows extremely large in the presence of rare events, i.e., events whose probability of occurrence is very low, which typically holds for failures in highly reliable systems. This paper presents a novel method for rare event simulation of dynamic fault trees with complex repairs that requires only a modest number of simulations, while retaining statistically justified confidence intervals. Our method exploits the importance sampling technique for rare event simulation, together with a compositional state space generation method for dynamic fault trees. We demonstrate our approach using two parameterized sets of case studies, showing that our method can handle fault trees that could not be evaluated with either existing analytical techniques, nor with standard simulation techniques.

AB - Fault trees (FT) are a popular industrial method for reliability engineering, for which Monte Carlo simulation is an important technique to estimate common dependability metrics, such as the system reliability and availability. A severe drawback of Monte Carlo simulation is that the number of simulations required to obtain accurate estimations grows extremely large in the presence of rare events, i.e., events whose probability of occurrence is very low, which typically holds for failures in highly reliable systems. This paper presents a novel method for rare event simulation of dynamic fault trees with complex repairs that requires only a modest number of simulations, while retaining statistically justified confidence intervals. Our method exploits the importance sampling technique for rare event simulation, together with a compositional state space generation method for dynamic fault trees. We demonstrate our approach using two parameterized sets of case studies, showing that our method can handle fault trees that could not be evaluated with either existing analytical techniques, nor with standard simulation techniques.

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KW - Fault Tree Analysis

KW - Monte Carlo Simulation

KW - Importance sampling

KW - Dynamic Fault Trees

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Ruijters EJJ, Reijsbergen DP, de Boer P-T, Stoelinga MIA. Rare event simulation for dynamic fault trees. Enschede: Centre for Telematics and Information Technology (CTIT), 2017. 14 p. (CTIT technical report series; TR-CTIT-17-02).