Characterization of gamma-ray background outside of the High Flux Isotope Reactor

Static gamma-ray measurements collected between September 2017 and March 2018 in the vicinity of the High Flux Isotope Reactor (HFIR) and the Radiochemical Engineering Development Center (REDC) at Oak Ridge National Laboratory are presented. Temporal events are identified and tracked, including radi...

Full description

Saved in:
Bibliographic Details
Published in:Journal of radioanalytical and nuclear chemistry 2018-10, Vol.318 (1), p.361-367
Main Authors: Nicholson, Andrew D., Archer, Daniel E., Garishvili, Irakli, Stewart, Ian R., Willis, Michael J.
Format: Article
Language:English
Subjects:
Algorithms
Background radiation
Chemistry
Chemistry and Materials Science
Computer simulation
Data integration
Data transfer (computers)
Diagnostic Radiology
Environmental radioactivity
Gamma rays
Gamma-ray background
Hadrons
Heavy Ions
Inorganic Chemistry
Multisensor fusion
Nuclear Chemistry
Nuclear Physics
NUCLEAR PHYSICS AND RADIATION PHYSICS
Physical Chemistry
Radiation detection
Radioactive materials
Radioactive substances
Radiochemistry
Research facilities
Tracking
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Static gamma-ray measurements collected between September 2017 and March 2018 in the vicinity of the High Flux Isotope Reactor (HFIR) and the Radiochemical Engineering Development Center (REDC) at Oak Ridge National Laboratory are presented. Temporal events are identified and tracked, including radioactive material transfers, rain events, and 41 Ar emissions. The remaining data is used to determine the average background and its variation. These results will be used to benchmark Monte Carlo transport models of the HFIR/REDC vicinity and provide training data for material transfer tracking algorithms and data fusion algorithms to determine HFIR operational status under the Multi-Informatics for Nuclear Operations Scenarios program.
ISSN:0236-5731
1588-2780
DOI:10.1007/s10967-018-6097-5