Allan Simpson, Anthony Clarkson, Simon Gardner, Ramsey Al Jebali, Ralf Kaiser, David Mahon, Julian Roe, Matthew Ryan, Craig Shearer, Guangliang Yang
Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine 2020 MarAlternate treatment routes for radioactive waste are a key research area for much of the nuclear industry, with potentially significant savings available through volume reduction of waste. Achieving this requires a full and demonstrable understanding of waste product behaviour. For this purpose, the UK's National Nuclear Laboratory (NNL) has been collaborating with the University of Glasgow and Lynkeos Technology to develop passive techniques for analysis of waste containers over a number of years. In this instance, novel muon tomographic techniques have been applied to the analysis of thermally treated nuclear waste surrogates as part of a project to build and deploy a first of a kind muon imaging system for nuclear waste. The system has been deployed at NNL's Central Laboratory, Cumbria, UK, to analyse products from a series of thermal treatment technology trials, funded by the Nuclear Decommissioning Authority (NDA) through the Direct Research Portfolio (DRP). Analysis of the waste products using this technique has proven the value of muon analysis in the development of waste management technologies, proving an ability to understand the homogeneity of products and direct further destructive testing. Results from three different thermal treatment trials are presented, with three different surrogate intermediate level waste (ILW) forms in each. Copyright © 2020 Elsevier Ltd. All rights reserved.
Allan Simpson, Anthony Clarkson, Simon Gardner, Ramsey Al Jebali, Ralf Kaiser, David Mahon, Julian Roe, Matthew Ryan, Craig Shearer, Guangliang Yang. Muon tomography for the analysis of in-container vitrified products. Applied radiation and isotopes : including data, instrumentation and methods for use in agriculture, industry and medicine. 2020 Mar;157:109033
PMID: 32063328
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