Efficient Monte Carlo algorithm for rare failure event simulation

Edoardo Patelli, Siu Kui Au

Research output: Chapter in Book/Report/Conference proceedingConference contribution book

5 Citations (Scopus)

Abstract

Studying failure scenarios allows one to gain insights into their cause and consequence, providing information for effective mitigation, contingency planning and improving system resilience. A new efficient algorithm is here proposed to solve applications where an expensive-to-evaluate computer model is involved. The algorithms allows to generate the conditional samples for the Subset simulation by representing each random variable by an arbitrary number of hidden variables. The resulting algorithm is very simple yet powerful and it does not required the use of the Markov Chain Monte Carlo method. The proposed algorithm has been implemented in a open source general purpose software, OpenCossan allowing the solution of large scale problems of industrial interest by taking advantages of High Performance Computing facilities. The applicability and flexibility of the proposed approach is shown by solving a number of different problems.

Original languageEnglish
Title of host publication12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015
Place of PublicationVancouver
PublisherUniversity of British Columbia
Number of pages8
ISBN (Electronic)9780888652454
Publication statusPublished - 15 Jul 2015
Event12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2012 - Vancouver, Canada
Duration: 12 Jul 201515 Jul 2015

Publication series

Name12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015

Conference

Conference12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2012
CountryCanada
CityVancouver
Period12/07/1515/07/15

Keywords

  • Monte Carlo methods
  • failure scenarios
  • Markov Chain Monte Carlo method
  • computer model
  • algorithms
  • reliability analysis
  • contingency planning

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  • Cite this

    Patelli, E., & Au, S. K. (2015). Efficient Monte Carlo algorithm for rare failure event simulation. In 12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015 (12th International Conference on Applications of Statistics and Probability in Civil Engineering, ICASP 2015). University of British Columbia.