Source type estimation using noble gas samples

Eslinger, Paul W.; Lowrey, Justin D.; Miley, Harry S.; Rosenthal, William S.; Schrom, Brian T.

doi:10.1016/j.jenvrad.2020.106439

Title: Source type estimation using noble gas samples

Journal Article · 30 September 2020 · Journal of Environmental Radioactivity

DOI: https://doi.org/10.1016/j.jenvrad.2020.106439 · OSTI ID:1669160

Eslinger, Paul W. ^[1]; Lowrey, Justin D. ^[1];

^[1]; Rosenthal, William S. ^[1]; Schrom, Brian T. ^[1]

Pacific Northwest National Lab. (PNNL), Richland, WA (United States)

A Bayesian source-term algorithm recently published by Eslinger et al. (2019) extended previous models by including the ability to discriminate between classes of releases such as nuclear explosions, nuclear power plants, or medical isotope production facilities when multiple isotopes are measured. Using 20 release cases from a synthetic data set previously published by Haas et al. (2017), algorithm performance was demonstrated on the transport scale (400–1000 km) associated with the radionuclide samplers in the International Monitoring System. Inclusion of multiple isotopes improves release location and release time estimates over analyses using only a single isotope. The ability to discriminate between classes of releases does not depend on the accuracy of the location or time of release estimates. For some combinations of isotopes, the ability to confidently discriminate between classes of releases requires only a few samples.

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Research Organization:: Pacific Northwest National Laboratory (PNNL), Richland, WA (United States)

Sponsoring Organization:: USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation; USDOE Office of Electricity (OE), Advanced Grid Research & Development. Power Systems Engineering Research

Grant/Contract Number:: AC05-76RL01830

OSTI ID:: 1669160

Alternate ID(s):: OSTI ID: 1674954

Report Number(s):: PNNL-SA-152251; TRN: US2203972

Journal Information:: Journal of Environmental Radioactivity, Vol. 225; ISSN 0265-931X

Publisher:: ElsevierCopyright Statement

Country of Publication:: United States

Language:: English

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