Abstract
The use of gamma-ray imaging has become established in the nuclear industry, especially in the fields of decommissioning and clean-up, for identifying the origins of elevated gamma dose rates. Since their first use in the mid 1990s, gamma-ray imaging devices, such as the Babcock RadScan, have been used to produce colour overlay plots that indicate, in two dimensions, the locations and distribution of radioactive contaminants. This information is invaluable in helping project managers to plan clean-up and shielding activities, ensuring that all work carried out is cost effective and ALARP. Recent work undertaken by Babcock demonstrates the capability to generate 3D maps of dose rate fields from the output of gamma-ray imaging work. The combination of gamma-ray imaging survey and resultant dose map is a very powerful tool for planning decommissioning. The conventional gamma-ray image provides an unambiguous identification of the origins of the dose rates present whilst the 3D dose map allows the dose uptake to personnel to be determined. Furthermore, the ability to quantify the effect of clean-up or shielding on the dose rates is possible, providing project teams with a metric for determining the best option available. A simple procedure is followed to generate 3D dose maps from gamma-ray imaging data. Firstly a model of the plant area is constructed. This model can be generated from existing plant drawings, from laser scan surveys, or from simple physical measurements taken on plant. The model includes information about the shielding properties of the plant structures, and can be easily modified to demonstrate the effect of adding more shielding, or of reducing any of the source terms. The data from a gamma-ray imager, such as RadScan, are analysed to generate distributions of radionuclide specific activities. These activities are entered into the model and form the source term. The advantage of using a gamma ray imager to generate the source term is that the location and distribution of the source is accurately represented in the model, thus ensuring that accurate dose maps are generated. Once the model has been completed it is analysed using a radiation transport modelling code such as Attila to produce the 3D dose maps (although other codes are available which could perform the same function). This paper describes an example of how this technique has been used to generate 3D dose maps for a customer and builds on earlier work with RadScan which provides quantitative in-cell assay.
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