Radiation mapping, through the detection of ionising gamma-ray emissions, is an important technique used across the nuclear industry to characterise environments over a range of length scales. In complex scenarios, the precise localisation and activity of radiological sources becomes difficult to determine due to the inability to directly image gamma photon emissions. This is a result of the potentially unknown number of sources combined with uncertainties associated with the source-detector separation—causing an apparent ‘blurring’ of the as-detected radiation field relative to the true distribution. Accurate delimitation of distinct sources is important for decommissioning, waste processing, and homeland security. Therefore, methods for estimating the precise, ‘true’ solution from radiation mapping measurements are required. Herein is presented a computational method of enhanced radiological source localisation from scanning survey measurements conducted with a robotic arm. The procedure uses an experimentally derived Detector Response Function (DRF) to perform a randomised-Kaczmarz deconvolution from robotically acquired radiation field measurements. The performance of the process is assessed on radiation maps obtained from a series of emulated waste processing scenarios. The results demonstrate a Projective Linear Reconstruction (PLR) algorithm can successfully locate a series of point sources to within 2 cm of the true locations, corresponding to resolution enhancements of between 5× and 10×.

Radioactive Source Localisation via Projective Linear Reconstruction

Abstract This study determines the minimal detection time (MDT) needed for successful localization of radioactive hot spots during nuclear decommissioning work. An automated XY stage, equipped with a CdZnTe (CZT) spectrometer, was used to identify and localize hot spots of 241Am, 137Cs, and 60Co in a 1.7 × 1.7-m area. The stage served as a preliminary test platform for the development of an automated robotic characterization platform [Autonomous Robotic platform for CHaractERization (ARCHER) robot]. The dependence of the MDT on the detector efficiency and background (BKG) level was examined. For low BKG environments, the MDT for 137Cs was 871 ms and resulted in an error of the source localization of 14.21 mm and an error of the activity of 6.85%. For elevated BKG levels, the MDT increased to 15 526 ms. The 137Cs source was localized with an error of 34.13 mm and an error of the source activity of −7.04%. The MDT determination method used here offers a valuable approach for decreasing total scanning times while avoiding missing the presence of hot spots.

Minimal Detection Time for Localization of Radioactive Hot Spots in Low and Elevated Background Environments Using a CZT Gamma-Ray Spectrometer

This work is dedicated to ability of a coplanar cadmium zinc telluride (CZT) detector to identify lost/orphan radioactive sources hidden inside soil layers. Considering point-like sources placed in soil and the CZT detector fixed on an unmanned ground vehicle (UGV), relevant measurement geometries were proposed. Full-energy peak efficiency (FEPE) calibrations of the CZT detector were prepared using the MCNP6.1 radiation transport code. In order to check the simulation set-up, control measurements were performed and compared with the Monte Carlo simulations. FEPEs obtained were used for estimations of minimum detectable activities (MDA) and their dependencies on the source depth in soil. Thereafter, field tests of the CZT detector were performed. Within field measurements, radioactive sources with known activities slightly above the MDA values were placed in upper layers of soil of a grassed meadow. The meadow surface was scanned by the CZT detector mounted on a mobile ground robotic platform remotely controlled by an operator. Results of the radiation mapping with the CZT detector were depicted as maps of count rates. On the basis of the maps created, positions of shielded sources were clearly revealed. 

Identification of shielded sources using a CZT detector and an unmanned ground vehicle

Cd1−xZnxTe (0 ≤ x ≤ 0.1) ingots were obtained by Bridgman’s method using two different speeds in order to find the optimal conditions for single-crystalline growth. Crystalline quality was studied by chemical etching, the elemental composition by wavelength dispersive spectroscopy (WDS), tellurium (Te) precipitates/inclusions concentration by differential scanning calorimetry (DSC), optical transmission by Fourier transformed infrared spectrometry (FTIR), and band gap energy (Egap) by photoluminescence (PL). It was observed that the ingots grown at a lower speed were those of the best crystalline quality, having at most three grains of different crystallographic orientation. The average dislocations density in all of them were similar and correspond to materials of good quality. EPMA results indicated that the homogeneity in the composition was excellent in the ingots central part. The concentration of Te precipitates/inclusions in all ingots was below the instrument (DSC) detection limit, 0.25% wt/wt. In the case of wafers from Cd0.96Zn0.04Te and Cd0.90Zn0.10Te ingots, the optical transmission was better than that of commercial materials and varied between 60% and 70%, while for pure CdTe, the transmission range was between 50% and 55%, the latter being decreased by the presence of Te precipitates/inclusions. The band gap energy Eg of different wafers was experimentally obtained by PL measurements at 76 K. We observed that Eg increased with the Zn concentration of the wafers, following a linear regression comparable to those proposed in the literature, and consistent with the results obtained with other techniques.

https://www.mdpi.com/1996-1944/14/15/4207/pdf

Crystalline Quality, Composition Homogeneity, Tellurium Precipitates/Inclusions Concentration, Optical Transmission, and Energy Band Gap of Bridgman Grown Single-Crystalline Cd1−xZnxTe (0 ≤ x ≤ 0.1)

Semiconductor CdZnTe gamma spectrometers allow the implementation of new radiation monitoring technologies. However, the energy resolution from 5 to 10 keV and the small size of the detector may result in the detector being unable to resolve photopeaks with very close energies. Algorithms deduce the source identity from the spectrum and must rely on a well-established peak separation in cases where multiple sources are involved. Some techniques exist, but they are computationally expensive, both in memory and processor speed. Typically they can lead to critical performance problems when run on single board computers. To solve this problem, spectral deconvolution methods such as Gold or Richardson-Lucy algorithmshave been proposed, that somewhat resolve the complex spectrum. The realized functions of spectra processing implemented in the ROOT CERN allow solving the indicated contradictions. The article presents the results of using ROOT CERN on a single-board computer for analyzing the spectra measured with a CdZnTe spectrometer. The results show that the spectral deconvolution methods used have high accuracy and efficiency in the deconvolution of complex spectra.

Analysis of gamma-ray spectrum obtained with cdznte-detectors using the root cern software framework

The use of a CZT detector with robotic systems.

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The use of a CZT detector with robotic systems.