Variance reduction for estimating a failure probability with multiple criteria
Document Type
Conference Proceeding
Publication Date
7-2-2016
Abstract
We consider a system subjected to multiple loads with corresponding capacities to withstand the loads, where both loads and capacities are random. The system fails when any load exceeds its capacity, and the goal is to apply Monte Carlo methods to estimate the failure probability. We consider various combinations of variance-reduction techniques, including stratified sampling, conditional Monte Carlo, and Latin hypercube sampling. Numerical results are presented for an artificial safety analysis of a nuclear power plant, which illustrate that the combination of all three methods can greatly increase statistical efficiency.
Identifier
85014290698 (Scopus)
ISBN
[9781509044863]
Publication Title
Proceedings Winter Simulation Conference
External Full Text Location
https://doi.org/10.1109/WSC.2016.7822098
ISSN
08917736
First Page
302
Last Page
313
Grant
CMMI-1200065
Fund Ref
National Science Foundation
Recommended Citation
Alban, Andres; Darji, Hardik A.; Imamura, Atsuki; and Nakayama, Marvin K., "Variance reduction for estimating a failure probability with multiple criteria" (2016). Faculty Publications. 10398.
https://digitalcommons.njit.edu/fac_pubs/10398
