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Title: Classification of background suppression profiles for low background RPM data

Abstract

Suppression of the ambient gamma background radiation by traffic structure and cargo is a well-understood and studied effect for deployed radiation portal monitors (RPM). For effective analysis of measured RPM profiles with the objective of inferring the spatial characteristics of radiation sources, it is important to account for the effects of background suppression. In this report we analyze background suppression for a test dataset from vehicle RPMs at a sample port and estimate the distributions of suppression amplitudes and shapes. Cluster analysis of standardized and normalized profiles is used to obtain the dominant suppression shapes in the sample field data. We determine that a large fraction of non-alarm RPM occupancies are represented by a small number of suppression shapes. This fraction increases when the signal-to-noise ratio of an occupancy profile is improved by the addition of signals for multiple RPM detectors located at the same height. The calculated suppression shapes from RPM data can be used along with source models in the process of spatial profile analysis both in the field or offline. This background suppression analysis is an important step in improving the effectiveness of the RPM profile analysis methodology which is currently being investigated and may lead tomore » methods that reduce the number of secondary inspections as well as to decision support tools that aid operators in evaluating RPM data that do not contain spectral information.« less

Authors:
 [1];  [2]
  1. Sandia National Lab. (SNL-CA), Livermore, CA (United States)
  2. Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA), Office of Defense Nuclear Nonproliferation (NA-20)
Contributing Org.:
Oak Ridge National Laboratory (ORNL), Oak Ridge, TN (United States)
OSTI Identifier:
1465873
Report Number(s):
SAND2016-6676
645219
DOE Contract Number:  
AC04-94AL85000
Resource Type:
Technical Report
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; 98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL PROTECTION

Citation Formats

Shokair, Isaac R., and Homan, Rossitza. Classification of background suppression profiles for low background RPM data. United States: N. p., 2016. Web. doi:10.2172/1465873.
Shokair, Isaac R., & Homan, Rossitza. Classification of background suppression profiles for low background RPM data. United States. doi:10.2172/1465873.
Shokair, Isaac R., and Homan, Rossitza. Fri . "Classification of background suppression profiles for low background RPM data". United States. doi:10.2172/1465873. https://www.osti.gov/servlets/purl/1465873.
@article{osti_1465873,
title = {Classification of background suppression profiles for low background RPM data},
author = {Shokair, Isaac R. and Homan, Rossitza},
abstractNote = {Suppression of the ambient gamma background radiation by traffic structure and cargo is a well-understood and studied effect for deployed radiation portal monitors (RPM). For effective analysis of measured RPM profiles with the objective of inferring the spatial characteristics of radiation sources, it is important to account for the effects of background suppression. In this report we analyze background suppression for a test dataset from vehicle RPMs at a sample port and estimate the distributions of suppression amplitudes and shapes. Cluster analysis of standardized and normalized profiles is used to obtain the dominant suppression shapes in the sample field data. We determine that a large fraction of non-alarm RPM occupancies are represented by a small number of suppression shapes. This fraction increases when the signal-to-noise ratio of an occupancy profile is improved by the addition of signals for multiple RPM detectors located at the same height. The calculated suppression shapes from RPM data can be used along with source models in the process of spatial profile analysis both in the field or offline. This background suppression analysis is an important step in improving the effectiveness of the RPM profile analysis methodology which is currently being investigated and may lead to methods that reduce the number of secondary inspections as well as to decision support tools that aid operators in evaluating RPM data that do not contain spectral information.},
doi = {10.2172/1465873},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Jul 01 00:00:00 EDT 2016},
month = {Fri Jul 01 00:00:00 EDT 2016}
}

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