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Title: Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion

Abstract

The goal of this project is to develop statistical methods and tools that can be used to rigorously calculate achieved DPs on individual material strata and then aggregate these to the facility and state levels. In particular, this project is evaluating the utility of stochastic ("Monte Carlo") methods as a potentially more powerful and flexible option to the analytical solutions traditionally employed by IAEA statisticians.

Authors:
;
Publication Date:
Research Org.:
Brookhaven National Lab. (BNL), Upton, NY (United States)
Sponsoring Org.:
International Atomic Energy Agency; USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA-20)
OSTI Identifier:
1561261
Report Number(s):
BNL-211980-2019-INRE
DOE Contract Number:  
SC0012704
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION; MOnte Carlo; safeguards; stratum; IAEA

Citation Formats

Gazze, Chris, and Gomera, Jose. Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion. United States: N. p., 2019. Web. doi:10.2172/1561261.
Gazze, Chris, & Gomera, Jose. Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion. United States. doi:10.2172/1561261.
Gazze, Chris, and Gomera, Jose. Fri . "Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion". United States. doi:10.2172/1561261. https://www.osti.gov/servlets/purl/1561261.
@article{osti_1561261,
title = {Stochastic Approaches for Calculating and Aggregating Detection Probabilities for Nuclear Material Diversion},
author = {Gazze, Chris and Gomera, Jose},
abstractNote = {The goal of this project is to develop statistical methods and tools that can be used to rigorously calculate achieved DPs on individual material strata and then aggregate these to the facility and state levels. In particular, this project is evaluating the utility of stochastic ("Monte Carlo") methods as a potentially more powerful and flexible option to the analytical solutions traditionally employed by IAEA statisticians.},
doi = {10.2172/1561261},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2019},
month = {8}
}