N4D1  Instrumentation for Homeland and National Security, Aerial and Ground Surveys

Thursday, Nov. 5  16:30-18:10  Town and Country

Session Chair:  John Mattingly, North Carolina State University, United States; William Pitts, Pacific Northwest National Laboratory, United States

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(16:30) N4D1-1, Direction-Sensitive Radiation Detection System for Unmanned Aerial Vehicles

E. M. Becker, A. T. Farsoni, S. A. Czyz

Nuclear Engineering and Radiation Health Physics, Oregon State University, Corvallis, OR, USA
Many devices and methods for radiation source localization exist, including scanning using simple detectors, mapping using large-volume detectors, and Compton imaging using 3-D position sensitive detectors. However, these devices are typically expensive and the methods used require long periods of time to generate a direction or location. The Radiation Compass, currently being developed at Oregon State University, is a low-cost detector designed for use on an unmanned aerial vehicle and will generate a most probable source direction that will be used to guide the motion of the UAV. The prototype detection system is composed of sixteen detection elements based on a BGO crystal coupled to a SiPM and arranged in a circular array. A certain pattern of radiation count rates is generated in each element based on the active shielding of detection elements on opposite sides of the array. The most probable direction of the radiation source will be generated based on the count rate pattern with a given confidence using a symmetry-finding method and an iterative library-matching method, both using maximum likelihood statistical estimation, which will be compared for accuracy and speed.

(16:50) N4D1-2, Characterization of an Advanced Airborne Radiation Detector System for the ARES Project

B. J. Quiter1, M. S. Bandstra1, T. H. Joshi1, J. S. Maltz1,2, A. Zoglauer2, K. Vetter1,2

1Lawrence Berkeley National Laboratory, Berkeley, CA, United States
2University of California, Berkeley, CA, United States
The Airborne Radiological Enhanced-sensor System (ARES) Advanced Technology Demonstration (ATD) has the goal of improving capabilities to detect, localize, track, and identify illicit radiological and/or nuclear material in airborne search scenarios. The Department of Homeland Security divided the project into two separate research and development tasks that are being supported; hardware development and advanced algorithms. The hardware task developed four synchronized arrays of 26 CsI(Na) detectors, a suite of contextual sensors, and a 'prior' database that provides additional context on search areas. The algorithm teams are developing new algorithms that leverage the contextual sensors and the modernized detector system. Their efforts are focused in three areas: improving detection algorithms for CsI(Na) detectors; improving awareness of background fluctuations due to variability in the composition and topography of terrain; and leveraging the imaging capabilities of the detector and the contextual sensors to improve the ability to localize and track static and moving gamma-ray sources. This paper will highlight the efforts of the team working in support of the Domestic Nuclear Detection Office (DNDO) to characterize the R&D products and to assess and highlight technological advances and the potential for further performance improvements that could result from the ARES ATD.

(17:10) N4D1-3, Reconstruction of the Spatial Distribution of Radioactive Contamination from Aerial Survey and from a Stationary Array of Directional Detectors

L. E. Sinclair1, F. A. Marshall2, R. Fortin1

1Geological Survey of Canada, Natural Resources Canada, Ottawa, Ontario, Canada
2Department of Mathematics and Statistics, Queen's University, Kingston, Ontario, Canada
Natural Resources Canada has responsibility for mobile survey in response to radiological emergencies in Canada. The team maintains both aerial and truckborne survey systems based on large-volume NaI(Tl) detectors integrated with instrumentation for geolocation and for environmental monitoring. In 2012, the team participated in a series of experiments in which radiological dispersal devices (RDDs) were detonated, spreading radioactivity over distances of up to 2 km. Both aerial and truckborne surveys were conducted shortly following the blasts. The aerial measurements cover a large field of view, resulting in reconstructed surface activity concentration which is averaged over an area with radius proportional to the survey altitude. The truckborne surveys resolve more finely the spatial variability. However, they suffer from incomplete coverage of the experimental area. We have developed novel methods to treat both datasets. A deconvolution method applied to the aerial data can resolve finer spatial variations. This includes recovery of the magnitude of radioactivity in localized hot spots. Thus, this method is of importance both scientifically, for understanding the behaviour of RDDs, and also operationally, for safety in using aerial data to guide ground teams in a recovery operation. In the truckborne setup, four detectors are oriented vertically in a self-shielding configuration to provide an azimuthal direction reading. A mobile traverse with one system in different locations at different times was treated as a stationary array of multiple systems in different locations at a single time. A regression method was applied to the relative counts in each detector of this array, to determine the spatial distribution of radioactivity extending some distance away from the traverse. Here, we present these new methods for spatial reconstruction, and show results for distributed radioactivity obtained from both synthetic and real data.

(17:30) N4D1-4, Reconstruction of Background Radiation Emissivity of Urban Structures Using a Truck-Based Detector Array

J. S. Maltz1, J. C. Curtis1,2, M. S. Bandstra1, S. S. Huh1, B. J. Quiter1

1Nuclear Sciences Division, LBNL, Berkeley, CA, USA
2Department of Nuclear Engineering, University of California, Berkeley, Berkeley, CA, USA
Modeling and optimizing radiological threat detection problems in urban areas is facilitated through prior characterization of background activity distributions. The background emissivity of static objects such as buildings and roads is highly dependent on the composition of these elements of urban scenes. We perform a feasibility study to determine whether truck-based (non-imaging) detector measurements can be used to estimate the relative contributions of potassium-40, uranium and thorium (KUT) to the background emissions of surfaces. To do this, we simulate a simple urban scene, and assign realistic KUT compositions to structures. The detectors on the truck are completely characterized in terms of spectral response versus angle of incidence using Monte Carlo simulation of all three background components, with each component being expressed as a spectral basis function. The truck moves along a trajectory through this environment and measures the background activity. Assuming knowledge of the position of surfaces (as would be determined using 3D maps or optical survey data), we estimate the KUT composition. We show that the inverse problem is sufficiently well-conditioned to solve for the K-40 component, but not for reconstructing the much smaller relative activities due to U and Th. We propose weighting and regularization schemes to enable improved estimation of these components.

(17:50) N4D1-5, Direction-Finding Gamma Spectrometer Using Pixelated GYGAG(Ce) Ceramic Scintillators on Si Photodiode Arrays

E. L. Swanberg1, N. J. Cherepy1, P. R. Beck1, Z. M. Seeley1, B. M. Wihl1, S. L. Hunter1, S. E. Fisher1, S. A. Payne1, J. Kindem2

1Lawrence Livermore National Laboratory, Livermore, CA, USA
2Cokiya, Inc., Poway, CA, USA
We are working to integrate a novel ceramic oxide scintillator, (Gd,Y, Ce)(Ga,Al) Garnet (GYGAG), with Si photodiode arrays originally designed and used for medical imaging. We achieve resolution for our best pixels of 3.4% at 662 keV and sum the output of up to 1024 pixels while still maintaining resolution of <5%. In our most recent design, we have incorporated an Intel Edison microcontroller into our detector. This gives us improved computational performance, data throughput, wireless connectivity, and standalone operation of the detector system with data retrieval whenever desired. We have also made substantial improvements to the user interface and direction-sensing capabilities of the system.