Estimating a failure probability using a combination of variance-reduction techniques
Document Type
Conference Proceeding
Publication Date
2-16-2016
Abstract
Consider a system that is subjected to a random load and having a corresponding random capacity to withstand the load. The system fails when the load exceeds capacity, and we consider efficient simulation methods for estimating the failure probability. Our approaches employ various combinations of stratified sampling, Latin hypercube sampling, and conditional Monte Carlo. We construct asymptotically valid upper confidence bounds for the failure probability for each method considered. We present numerical results to evaluate the proposed techniques on a safety-analysis problem for nuclear power plants, and the simulation experiments show that some of our combined methods can greatly reduce variance.
Identifier
84962787667 (Scopus)
ISBN
[9781467397438]
Publication Title
Proceedings Winter Simulation Conference
External Full Text Location
https://doi.org/10.1109/WSC.2015.7408201
ISSN
08917736
First Page
621
Last Page
632
Volume
2016-February
Recommended Citation
Nakayama, Marvin K., "Estimating a failure probability using a combination of variance-reduction techniques" (2016). Faculty Publications. 10676.
https://digitalcommons.njit.edu/fac_pubs/10676
