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Title: Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials

Abstract

Aerial gamma ray surveys are important for those working in nuclear security and industry for determining locations of both anthropogenic radiological sources and natural occurrences of radionuclides. During an aerial gamma ray survey, a low flying aircraft, such as a helicopter, flies in a linear pattern across the survey area while measuring the gamma emissions with a sodium iodide (NaI) detector. Currently, if a gamma ray survey is being flown in an area, the only way to correct for geologic sources of gamma rays is to have flown the area previously. This is prohibitively expensive and would require complete national coverage. This project’s goal is to model the geologic contribution to radiological backgrounds using published geochemical data, GIS software, remote sensing, calculations, and modeling software. K, U and Th are the three major gamma emitters in geologic material. U and Th are assumed to be in secular equilibrium with their daughter isotopes. If K, U, and Th abundance values are known for a given geologic unit the expected gamma ray exposure rate can be calculated using the Grasty equation or by modeling software. Monte Carlo N-Particle Transport software (MCNP), developed by Los Alamos National Laboratory, is modeling software designed tomore » simulate particles and their interactions with matter. Using this software, models have been created that represent various lithologies. These simulations randomly generate gamma ray photons at energy levels expected from natural radiologic sources. The photons take a random path through the simulated geologic media and deposit their energy at the end of their track. A series of nested spheres have been created and filled with simulated atmosphere to record energy deposition. Energies deposited are binned in the same manner as the NaI detectors used during an aerial survey. These models are used in place of the simplistic Grasty equation as they take into account absorption properties of the lithology which the simplistic equation ignores.« less

Authors:
 [1]; ;  [2];  [2];  [2];  [2]
  1. National Security Technologies, LLC
  2. University of Nevada, Las Vegas
Publication Date:
Research Org.:
Nevada Test Site/National Security Technologies, LLC (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1233217
Report Number(s):
DOE/NV/25946-2303
DOE Contract Number:
DE-AC52-06NA25946
Resource Type:
Conference
Resource Relation:
Conference: This poster was presented in front of graduate students in physics at the University of Nevada, Las Vegas, and then presented at the HiPSEC NNSA annual review. The reviewers were from national labs and DOE/NNSA.
Country of Publication:
United States
Language:
English
Subject:
46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND TECHNOLOGY; aerial gamma ray survey; anthropegenic radiological sources; radionuclides; aircraft; GIS; remote sensing; K; U; Th; NaI, Grasty equation; Monte Carlo N-Particle Transport software; modeling softwar; geologic media; lithology

Citation Formats

Malchow, Russell L., Haber, Daniel University of Nevada, Las Vegas, Burnley, Pamela, Marsac, Kara, Hausrath, Elisabeth, and Adcock, Christopher. Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials. United States: N. p., 2015. Web.
Malchow, Russell L., Haber, Daniel University of Nevada, Las Vegas, Burnley, Pamela, Marsac, Kara, Hausrath, Elisabeth, & Adcock, Christopher. Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials. United States.
Malchow, Russell L., Haber, Daniel University of Nevada, Las Vegas, Burnley, Pamela, Marsac, Kara, Hausrath, Elisabeth, and Adcock, Christopher. Thu . "Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials". United States. doi:. https://www.osti.gov/servlets/purl/1233217.
@article{osti_1233217,
title = {Predictive Modeling of Terrestrial Radiation Exposure from Geologic Materials},
author = {Malchow, Russell L. and Haber, Daniel University of Nevada, Las Vegas and Burnley, Pamela and Marsac, Kara and Hausrath, Elisabeth and Adcock, Christopher},
abstractNote = {Aerial gamma ray surveys are important for those working in nuclear security and industry for determining locations of both anthropogenic radiological sources and natural occurrences of radionuclides. During an aerial gamma ray survey, a low flying aircraft, such as a helicopter, flies in a linear pattern across the survey area while measuring the gamma emissions with a sodium iodide (NaI) detector. Currently, if a gamma ray survey is being flown in an area, the only way to correct for geologic sources of gamma rays is to have flown the area previously. This is prohibitively expensive and would require complete national coverage. This project’s goal is to model the geologic contribution to radiological backgrounds using published geochemical data, GIS software, remote sensing, calculations, and modeling software. K, U and Th are the three major gamma emitters in geologic material. U and Th are assumed to be in secular equilibrium with their daughter isotopes. If K, U, and Th abundance values are known for a given geologic unit the expected gamma ray exposure rate can be calculated using the Grasty equation or by modeling software. Monte Carlo N-Particle Transport software (MCNP), developed by Los Alamos National Laboratory, is modeling software designed to simulate particles and their interactions with matter. Using this software, models have been created that represent various lithologies. These simulations randomly generate gamma ray photons at energy levels expected from natural radiologic sources. The photons take a random path through the simulated geologic media and deposit their energy at the end of their track. A series of nested spheres have been created and filled with simulated atmosphere to record energy deposition. Energies deposited are binned in the same manner as the NaI detectors used during an aerial survey. These models are used in place of the simplistic Grasty equation as they take into account absorption properties of the lithology which the simplistic equation ignores.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Thu Jan 01 00:00:00 EST 2015},
month = {Thu Jan 01 00:00:00 EST 2015}
}

Conference:
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