Issue |
2014
SNA + MC 2013 - Joint International Conference on Supercomputing in Nuclear Applications + Monte Carlo
|
|
---|---|---|
Article Number | 03306 | |
Number of page(s) | 2 | |
Section | 3. Monte Carlo Methods for Simulation: c. Acceleration Techniques for Monte Carlo Simulations | |
DOI | https://doi.org/10.1051/snamc/201403306 | |
Published online | 06 June 2014 |
Modeling and Estimating Small Unreliabilities for Static Networks with Dependent Components
1 School of Mathematics and Statistics, The University of New South Wales, Sydney, NSW 2052, Australia
2 DIRO, Université de Montreal, Pav. Aisenstadt, C.P. 6128, Succ. Centre-Ville, Montréal (Québec), H3C 3J7, Canada
3 INRIA Rennes Bretagne Atlantique, Campus Universitaire de Beaulieu, 35042 Rennes Cedex, FRANCE
We study static network reliability models in which the component failures are not independent. To model the dependence and also to develop effiective simulation methods that estimate the system unreliability, we extend the static model into an auxiliary dynamic model where the components fail at random time, according to a Marshall-Olkin multivariate exponential distribution. We examine and compare diffierent versions of this model and develop efficient unreliability estimation methods based on conditional Monte Carlo and on a generalized splitting methodology.
Key words: Monte Carlo / reliability / dependence / rare events / splitting / Marshall-Olkin / copula / Lévy subordinator
© Owned by the authors, published by EDP Sciences, 2014