Abstract

The ability to map and estimate the activity of radiological source distributions in unknown three-dimensional environments has applications in the prevention and response to radiological accidents or threats as well as the enforcement and verification of international nuclear non-proliferation agreements. Such a capability requires well-characterized detector response functions, accurate time-dependent detector position and orientation data, a digitized representation of the surrounding 3D environment, and appropriate image reconstruction and uncertainty quantification methods. We have previously demonstrated 3D mapping of gamma-ray emitters with free-moving detector systems on a relative intensity scale using a technique called Scene Data Fusion (SDF). Here we characterize the detector response of a multi-element gamma-ray imaging system using experimentally benchmarked Monte Carlo simulations and perform 3D mapping on an absolute intensity scale. We present experimental reconstruction results from hand-carried and airborne measurements with point-like and distributed sources in known configurations, demonstrating quantitative SDF in complex 3D environments.

Details

Title
Free-moving Quantitative Gamma-ray Imaging
Author
Hellfeld, Daniel 1 ; Bandstra, Mark S. 1 ; Vavrek, Jayson R. 1 ; Gunter, Donald L. 2 ; Curtis, Joseph C. 1 ; Salathe, Marco 1 ; Pavlovsky, Ryan 1 ; Negut, Victor 1 ; Barton, Paul J. 1 ; Cates, Joshua W. 1 ; Quiter, Brian J. 1 ; Cooper, Reynold J. 1 ; Vetter, Kai 3 ; Joshi, Tenzing H. Y. 1 

 Lawrence Berkeley National Laboratory, Nuclear Science Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551) 
 Gunter Physics, Inc., Lisle, USA (GRID:grid.184769.5) 
 Lawrence Berkeley National Laboratory, Nuclear Science Division, Berkeley, USA (GRID:grid.184769.5) (ISNI:0000 0001 2231 4551); University of California, Berkeley, Department of Nuclear Engineering, Berkeley, USA (GRID:grid.47840.3f) (ISNI:0000 0001 2181 7878) 
Publication year
2021
Publication date
2021
Publisher
Nature Publishing Group
e-ISSN
20452322
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2582277358
Copyright
© This is a U.S. Government work and not under copyright protection in the US; foreign copyright protection may apply 2021. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.