Analysis of non-Markovian repairable fault trees through rare event simulation

Fil: D'Argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.

Detalles Bibliográficos
Autores principales: Budde, Carlos E., D'Argenio, Pedro Ruben, Monti, Raúl Enrique, Stoelinga, Mariëlle
Otros Autores: 0000-0002-8528-9215
Formato: publishedVersion article
Lenguaje:Inglés
Publicado: 2023
Materias:
Fault tree analysis
Rare event simulation
Statistical model checking
System reliability
Análisis de árboles de fallas
Simulación de eventos raros
Confiabilidad de sistemas
Acceso en línea:http://hdl.handle.net/11086/546760
https://doi.org/10.1007/s10009-022-00675-x
Aporte de:
Repositorio Digital Universitario (UNC) de Universidad Nacional de Córdoba
id I10-R141-11086-546760
record_format dspace
spelling I10-R141-11086-5467602023-08-31T13:16:53Z Analysis of non-Markovian repairable fault trees through rare event simulation Budde, Carlos E. D'Argenio, Pedro Ruben Monti, Raúl Enrique Stoelinga, Mariëlle 0000-0002-8528-9215 0000-0001-8807-1548 0000-0002-6964-1426 0000-0001-6793-8165 Fault tree analysis Rare event simulation Statistical model checking System reliability Análisis de árboles de fallas Simulación de eventos raros Confiabilidad de sistemas info:eu-repo/semantics/publishedVersion Fil: D'Argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: D'Argenio, Pedro Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: D'Argenio, Pedro Ruben. Saarland University. Department of Computer Science; Germany. Fil: Budde, Carlos E. University of Trento. Department of Information Engineering and Computer; Italy. Fil: Monti, Raúl Enrique. University of Twente; The Netherlands. Fil: Stoelinga, Mariëlle. University of Twente; The Netherlands. Fil: Stoelinga, Mariëlle. Radboud University. Department of Software Science; The Netherlands. Dynamic fault trees (DFTs) 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 seldom fail. Rare event simulation (RES) provides techniques to reduce the number of samples in the case of rare events. In this article, we present a RES technique based on importance splitting to study failures in highly reliable DFTs, more precisely, on a variant of repairable fault trees (RFT). Whereas RES usually requires meta-information from an expert, our method is fully automatic. For this, we propose two different methods to derive the so-called importance function. On the one hand, we propose to cleverly exploit the RFT structure to compositionally construct such function. On the other hand, we explore different importance functions derived in different ways from the minimal cut sets of the tree, i.e., the minimal units that determine its failure. We handle RFTs with Markovian and non-Markovian failure and repair distributions—for which no numerical methods exist—and implement the techniques on a toolchain that includes the RES engine FIG, for which we also present improvements. We finally show the efficiency of our approach in several case studies. This work was partially supported by the EU Grant Agreement 101008233 (MISSION), ANPCyT PICT-2017-3894 RAFTSys), and SeCyT project 33620180100354CB (ARES). Funded also by the EU Grant Agreement 101067199 (ProSVED). info:eu-repo/semantics/publishedVersion Fil: D'Argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina. Fil: D'Argenio, Pedro Ruben. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Fil: D'Argenio, Pedro Ruben. Saarland University. Department of Computer Science; Germany. Fil: Budde, Carlos E. University of Trento. Department of Information Engineering and Computer; Italy. Fil: Monti, Raúl Enrique. University of Twente; The Netherlands. Fil: Stoelinga, Mariëlle. University of Twente; The Netherlands. Fil: Stoelinga, Mariëlle. Radboud University. Department of Software Science; The Netherlands. 2023-03-22T17:44:53Z 2023-03-22T17:44:53Z 2022 article http://hdl.handle.net/11086/546760 https://doi.org/10.1007/s10009-022-00675-x eng Atribución 4.0 Internacional http://creativecommons.org/licenses/by/4.0/ ISSN 1433-2779 eISSN 1433-2787
institution Universidad Nacional de Córdoba
institution_str I-10
repository_str R-141
collection Repositorio Digital Universitario (UNC)
language Inglés
topic Fault tree analysis
Rare event simulation
Statistical model checking
System reliability
Análisis de árboles de fallas
Simulación de eventos raros
Confiabilidad de sistemas
spellingShingle Fault tree analysis
Rare event simulation
Statistical model checking
System reliability
Análisis de árboles de fallas
Simulación de eventos raros
Confiabilidad de sistemas
Budde, Carlos E.
D'Argenio, Pedro Ruben
Monti, Raúl Enrique
Stoelinga, Mariëlle
Analysis of non-Markovian repairable fault trees through rare event simulation
topic_facet Fault tree analysis
Rare event simulation
Statistical model checking
System reliability
Análisis de árboles de fallas
Simulación de eventos raros
Confiabilidad de sistemas
description Fil: D'Argenio, Pedro Ruben. Universidad Nacional de Córdoba. Facultad de Matemática, Astronomía, Física y Computación; Argentina.
author2 0000-0002-8528-9215
author_facet 0000-0002-8528-9215
Budde, Carlos E.
D'Argenio, Pedro Ruben
Monti, Raúl Enrique
Stoelinga, Mariëlle
format publishedVersion
article
author Budde, Carlos E.
D'Argenio, Pedro Ruben
Monti, Raúl Enrique
Stoelinga, Mariëlle
author_sort Budde, Carlos E.
title Analysis of non-Markovian repairable fault trees through rare event simulation
title_short Analysis of non-Markovian repairable fault trees through rare event simulation
title_full Analysis of non-Markovian repairable fault trees through rare event simulation
title_fullStr Analysis of non-Markovian repairable fault trees through rare event simulation
title_full_unstemmed Analysis of non-Markovian repairable fault trees through rare event simulation
title_sort analysis of non-markovian repairable fault trees through rare event simulation
publishDate 2023
url http://hdl.handle.net/11086/546760
https://doi.org/10.1007/s10009-022-00675-x
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AT montiraulenrique analysisofnonmarkovianrepairablefaulttreesthroughrareeventsimulation
AT stoelingamarielle analysisofnonmarkovianrepairablefaulttreesthroughrareeventsimulation
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