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Title: Data for Training and Testing Radiation Detection Algorithms in an Urban Environment

Abstract

The US government routinely performs radiological response deployments to search for the presence of illicit nuclear materials (e.g., highly enriched uranium and weapons-grade plutonium) in a specified area. The deployments can be intelligence driven, in support of law enforcement, and for planned events such as WrestleMania, presidential inaugurations, or political conventions. In a typical deployment, radiation detection systems carried by human operators or mounted on vehicles move in a clearing pattern through the search area. Search teams rely on radiation detection algorithms running on these systems in real time to alert them to the presence of an illicit threat source. The detection and identification of sources is complicated by large variation of natural radiation background throughout a search area and the potential presence of localized non-threat sources such as patients undergoing treatment with medical isotopes. As a result, detection algorithms must be carefully balanced between missing real sources (false negatives) and reporting too many false alarms (false positives).The purpose of this data set is to spur innovations in detecting, identifying, and localizing nuclear materials inurban search missions.

Creator(s)/Author(s):
; ; ; ; ; ; ; ;
Publication Date:
DOE Contract Number:  
DE-AC05-00OR2272
Product Type:
Dataset
Research Org.:
Oak Ridge National Lab. (ORNL), Oak Ridge, TN (United States). Oak Ridge Leadership Computing Facility (OLCF)
Sponsoring Org.:
National Nuclear Security Administration (NNSA), Office of Nonproliferation and Verification Research and Development (NA-22); Office of Science (SC), Advanced Scientific Computing Research (ASCR) (SC-21)
Subject:
07 ISOTOPE AND RADIATION SOURCES; 46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION
Keywords:
data competition, radiation detection, radiation detection algorithm, Monte Carlo Particle Transport
OSTI Identifier:
1597414
DOI:
10.13139/ORNLNCCS/1597414

Citation Formats

Nicholson, Andrew, Peplow, Douglas E, Anderson-Cook, Christine M, Greulich, Christopher R, Ghawaly, James M, Myers, Kary L, Archer, Daniel E, Willis, Michael J, and Quiter, Brian J. Data for Training and Testing Radiation Detection Algorithms in an Urban Environment. United States: N. p., 2020. Web. doi:10.13139/ORNLNCCS/1597414.
Nicholson, Andrew, Peplow, Douglas E, Anderson-Cook, Christine M, Greulich, Christopher R, Ghawaly, James M, Myers, Kary L, Archer, Daniel E, Willis, Michael J, & Quiter, Brian J. Data for Training and Testing Radiation Detection Algorithms in an Urban Environment. United States. doi:10.13139/ORNLNCCS/1597414.
Nicholson, Andrew, Peplow, Douglas E, Anderson-Cook, Christine M, Greulich, Christopher R, Ghawaly, James M, Myers, Kary L, Archer, Daniel E, Willis, Michael J, and Quiter, Brian J. 2020. "Data for Training and Testing Radiation Detection Algorithms in an Urban Environment". United States. doi:10.13139/ORNLNCCS/1597414. https://www.osti.gov/servlets/purl/1597414. Pub date:Wed Feb 05 00:00:00 EST 2020
@article{osti_1597414,
title = {Data for Training and Testing Radiation Detection Algorithms in an Urban Environment},
author = {Nicholson, Andrew and Peplow, Douglas E and Anderson-Cook, Christine M and Greulich, Christopher R and Ghawaly, James M and Myers, Kary L and Archer, Daniel E and Willis, Michael J and Quiter, Brian J},
abstractNote = {The US government routinely performs radiological response deployments to search for the presence of illicit nuclear materials (e.g., highly enriched uranium and weapons-grade plutonium) in a specified area. The deployments can be intelligence driven, in support of law enforcement, and for planned events such as WrestleMania, presidential inaugurations, or political conventions. In a typical deployment, radiation detection systems carried by human operators or mounted on vehicles move in a clearing pattern through the search area. Search teams rely on radiation detection algorithms running on these systems in real time to alert them to the presence of an illicit threat source. The detection and identification of sources is complicated by large variation of natural radiation background throughout a search area and the potential presence of localized non-threat sources such as patients undergoing treatment with medical isotopes. As a result, detection algorithms must be carefully balanced between missing real sources (false negatives) and reporting too many false alarms (false positives).The purpose of this data set is to spur innovations in detecting, identifying, and localizing nuclear materials inurban search missions.},
doi = {10.13139/ORNLNCCS/1597414},
journal = {},
number = ,
volume = ,
place = {United States},
year = {2020},
month = {2}
}