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Title: Indirect Estimation of Radioactivity in Containerized Cargo

Abstract

Detecting illicit nuclear and radiological material in containerized cargo challenges the state of the art in detection systems. Current systems are being evaluated and new systems envisioned to address the need for the high probability of detection and extremely low false alarm rates necessary to thwart potential threats and extremely low nuisance and false alarm rates while maintaining necessary to maintain the flow of commerce impacted by the enormous volume of commodities imported in shipping containers. Maintaining flow of commerce also means that primary inspection must be rapid, requiring relatively indirect measurements of cargo from outside the containers. With increasing information content in such indirect measurements, it is natural to ask how the information might be combined to improved detection. Toward this end, we present an approach to estimating isotopic activity of naturally occurring radioactive material in cargo grouped by commodity type, combining container manifest data with radiography and gamma spectroscopy aligned to location along the container. The heart of this approach is our statistical model of gamma counts within peak regions of interest, which captures the effects of background suppression, counting noise, convolution of neighboring cargo contributions, and down-scattered photons to provide physically constrained estimates of counts due tomore » decay of specific radioisotopes in cargo alone. Coupled to that model, we use a mechanistic model of self-attenuated radiation flux to estimate the isotopic activity within cargo, segmented by location within each container, that produces those counts. We demonstrate our approach by applying it to a set of measurements taken at the Port of Seattle in 2006. This approach to synthesizing disparate available data streams and extraction of cargo characteristics holds the potential to improve primary inspection using current detection capabilities and to enable simulation-based evaluation of new candidate detection systems.« less

Authors:
; ; ; ; ; ;
Publication Date:
Research Org.:
Pacific Northwest National Lab. (PNNL), Richland, WA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1001085
Report Number(s):
PNNL-SA-62721
Journal ID: ISSN 1350-4487; RMEAEP; TRN: US1100269
DOE Contract Number:  
AC05-76RL01830
Resource Type:
Journal Article
Resource Relation:
Journal Name: Radiation Measurements, 46(1):10-20; Journal Volume: 46; Journal Issue: 1
Country of Publication:
United States
Language:
English
Subject:
72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS; CARGO; CONTAINERS; DECAY; DETECTION; EVALUATION; GAMMA SPECTROSCOPY; PHOTONS; PROBABILITY; RADIATION FLUX; RADIOACTIVE MATERIALS; RADIOACTIVITY; RADIOISOTOPES; STATISTICAL MODELS; TRADE; nuclear measurements, nuclear monitoring techniques, portal monitoring, gamma-ray spectral analysis, gamma-ray spectroscopy

Citation Formats

Jarman, Kenneth D., Scherrer, Chad, Smith, Eric L., Chilton, Lawrence, Anderson, K. K., Ressler, Jennifer J., and Trease, Lynn L. Indirect Estimation of Radioactivity in Containerized Cargo. United States: N. p., 2011. Web. doi:10.1016/j.radmeas.2010.09.001.
Jarman, Kenneth D., Scherrer, Chad, Smith, Eric L., Chilton, Lawrence, Anderson, K. K., Ressler, Jennifer J., & Trease, Lynn L. Indirect Estimation of Radioactivity in Containerized Cargo. United States. doi:10.1016/j.radmeas.2010.09.001.
Jarman, Kenneth D., Scherrer, Chad, Smith, Eric L., Chilton, Lawrence, Anderson, K. K., Ressler, Jennifer J., and Trease, Lynn L. Sat . "Indirect Estimation of Radioactivity in Containerized Cargo". United States. doi:10.1016/j.radmeas.2010.09.001.
@article{osti_1001085,
title = {Indirect Estimation of Radioactivity in Containerized Cargo},
author = {Jarman, Kenneth D. and Scherrer, Chad and Smith, Eric L. and Chilton, Lawrence and Anderson, K. K. and Ressler, Jennifer J. and Trease, Lynn L.},
abstractNote = {Detecting illicit nuclear and radiological material in containerized cargo challenges the state of the art in detection systems. Current systems are being evaluated and new systems envisioned to address the need for the high probability of detection and extremely low false alarm rates necessary to thwart potential threats and extremely low nuisance and false alarm rates while maintaining necessary to maintain the flow of commerce impacted by the enormous volume of commodities imported in shipping containers. Maintaining flow of commerce also means that primary inspection must be rapid, requiring relatively indirect measurements of cargo from outside the containers. With increasing information content in such indirect measurements, it is natural to ask how the information might be combined to improved detection. Toward this end, we present an approach to estimating isotopic activity of naturally occurring radioactive material in cargo grouped by commodity type, combining container manifest data with radiography and gamma spectroscopy aligned to location along the container. The heart of this approach is our statistical model of gamma counts within peak regions of interest, which captures the effects of background suppression, counting noise, convolution of neighboring cargo contributions, and down-scattered photons to provide physically constrained estimates of counts due to decay of specific radioisotopes in cargo alone. Coupled to that model, we use a mechanistic model of self-attenuated radiation flux to estimate the isotopic activity within cargo, segmented by location within each container, that produces those counts. We demonstrate our approach by applying it to a set of measurements taken at the Port of Seattle in 2006. This approach to synthesizing disparate available data streams and extraction of cargo characteristics holds the potential to improve primary inspection using current detection capabilities and to enable simulation-based evaluation of new candidate detection systems.},
doi = {10.1016/j.radmeas.2010.09.001},
journal = {Radiation Measurements, 46(1):10-20},
number = 1,
volume = 46,
place = {United States},
year = {Sat Jan 01 00:00:00 EST 2011},
month = {Sat Jan 01 00:00:00 EST 2011}
}