Reconstruction of the spatial distribution of radioactive contamination from aerial survey and from a stationary array of directional detectors

Mapping radioactive contamination using aerial survey measurements is an area under active investigation today. The radiometric aerial survey technique has been extensively applied following reactor accidents and also would provide a key tool for response to a malicious radiological or nuclear incident. Methods exist to calibrate the aerial survey system for quantification of the concentration of natural radionuclides, which can provide guidance. However, these methods have anticipated a spatial distribution of the source which is large in comparison to the survey altitude. In rapid emergency-response aerial surveys of areas of safety concern, deposits of relatively small spatial extent may be expected. The activity of such spatially restricted hot spots is underestimated using the traditional methods. We present here a spatial deconvolution method which can recover some of the variation smoothed out by the averaging due to survey at altitude. We show that the method can recover the true spatial distribution of concentration of a synthetic source. We then apply the method to real aerial survey data collected following detonation of a radiological dispersal device. The findings and implications of the deconvolution are then discussed by reference to a groundbased truckborne survey over the same contamination.

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“…This spatial deconvolution method has been presented previously at conferences by this group [15,16], however, this is the first full write-up.…”

Section: Introductionmentioning

confidence: 99%

Spatial deconvolution of aerial radiometric survey and its application to the fallout from a radiological dispersal device

Sinclair

Fortin

2019

Journal of Environmental Radioactivity

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“…For the purpose of measuring 1.6 MeV emissions, these spectra were sufficient, but in general, the truck geometry was far from the finished article. With more trials of simulated truck design, this iterative procedure will produce a better representation of the truck mass distribution, and for published results, this was achieved [10]. Within the scope of this dissertation, however, the systematic uncertainty on the mass distribution will dominate the uncertainty on the reconstructions of Chapters 4 and 5.…”

Section: Obtaining An Accurate Model Of the Simulated Truck Design Usmentioning

confidence: 97%

“…In particular, the directional spectrometer is self-shielding, which means that the individual logs attenuate the signal from each other, depending on the orientation of the detection system with respect to the centre of mass of the source distribution in the sensitive Only one-dimensional approximations are possible for single-detector systems like the RadEye systems of Health Canada [9]. The potential of the directional system has been explored in recent times, particularly for the cases of point-and distributedsource reconstructions [10,11].…”

Section: Directional Systemsmentioning

confidence: 99%

“…Another synthetic dataset was an extended rectangular source distribution. Results for this dataset were obtained from an independent analysis [10]. The truck design that was used in the analysis was a variation on the same design as the trucks used in the other analyses of this dissertation.…”

Section: Extended Rectangular Source Distributionmentioning

confidence: 99%

“…The true surface activity concentration is 61 kBq/m 2 . Rectangle region is defined to be bounded by 320 m < x < 340 m and 40 m < y < 460 m. It is enclosed by a black contour [10](used under permissions to copy or modify and distribute).…”

Section: Extended Rectangular Source Distributionmentioning

confidence: 99%

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Reconstruction of the Spatial Distribution of Surface Activity Concentration for an In-Situ, Gamma-Ray, Truck-Borne Survey

Marshall¹

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In 2012, three test detonations of a radiological dispersal device (RDD) were performed at the experimental proving ground of Defence Research and Development Canada (DRDC) in Suffield, Alberta. These were the first outdoor detonations of a radioactive source in an outdoor environment. The purpose of these exercises was to characterize the effects of an RDD in the uncontrolled environment, so as to properly model the contamination as it would likely appear in the real situation of a terrorist attack. For example, wind transport affects the plume deposition distribution. A number of government research teams were involved in the experiments. The RDD source was 140 La. A suite of in-situ instruments were set up to monitor the blast dynamics and the plume deposition distribution. The Nuclear Emergency Response Team (NERT) of Natural Resources Canada performed two mobile surveys of the plume distribution to reconstruct a map of the spatial distribution of surface activity concentration at the time of the blast. One of these was an airborne survey, which involves using detectors of thallium-activated sodium iodide (Na(Tl)) to measure the count rate of gamma emissions from the distributed source. The survey provides a detailed map of the surface activity concentration, but only based on estimations associated with large spatial resolution. To improve on this, the truck-borne survey is essential because its sensitivity is confined to a more localized area of space, and its detection system is directional (it is called a directional spectrometer). With four standing crystals of NaI(Tl), this detection system offers data that, with the aid of Monte Carlo, can be used to reconstruct an averaged measure of the local surface activity concentration around the survey path of the truck. Using the Electron Gamma Shower code of the National Research Council of Canada (EGSnrc), the sensitivity of the truck-borne spectrometer was determined for finite disc sources of successively increasing size. The asymptote value of the sensitivity was used in a conversion factor to scale all the count rate values of the truck path into average values of the surface activity concentration. The result of

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Reconstruction of the spatial distribution of radioactive contamination from aerial survey and from a stationary array of directional detectors

Cited by 2 publications

References 1 publication

Spatial deconvolution of aerial radiometric survey and its application to the fallout from a radiological dispersal device

Spatial deconvolution of aerial radiometric survey and its application to the fallout from a radiological dispersal device

Reconstruction of the Spatial Distribution of Surface Activity Concentration for an In-Situ, Gamma-Ray, Truck-Borne Survey

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