Radio-imagers, mainly dedicated to biological and medicine applications, can be used to reconstruct 2D mapping of radioactivity on a surface. The resulting image, called Digital Autoradiography (DA), gives a non destructive analysis of radioactivity.
Recently, a new scope for the radio-imagers has emerged: nuclear facilities decommissioning. Indeed, in such context, surface contamination need to be accurately localized and characterized in terms of activity and radionuclide identification. DA method appears to be a suitable candidate for this issue.
Currently, various radio-imagers are commercialized, mainly for research purposes, but up to now, there is no device able to investigate surface contamination at the scale of a facility. The MAUD project (Measurement by Digital Autoradiography) aims at designing a new in situ device able to assist in the dismantling process of nuclear facilities. For this purpose, three DA technologies are currently investigated: 1) Cyclone™, a laser used to read phosphor screen and developed by Perkin Elmer, 2) Beaver™, the Gas Detector designed by AI4R company and 3) µ-imager™ DFINE, the Solid Scintillation Detector developed by Biospace Lab.
Autoradiographic measurements of a rock sample containing natural Uranium, and of samples artificially labeled with 3H and 14C, have been acquired using the three radio-imagers quoted above, with an exposure time of 1 hour. The present study proposes a comparison of the resulting images, in terms of qualitative and quantitative results, in order to identify the strength and the weakness of each device.
A preliminary study has shown that a linear correlation should be expected between the counting of the Beaver™ and the DFINE one. It will also be possible to estimate the efficiency of each detector for the three kinds of radionuclide tested.
This work has been performed within the Investments for the future program of the French Government and operated by the French National Radioactive Waste Management Agency (Andra). These researches are also funded by CEA.