| Article | |
| Title | Statistical sampling applied to the radiological characterization of historical waste |
| Author(s) | Zaffora, Biagio (CERN) ; Magistris, Matteo (CERN) ; Saporta, Gilbert (CNAM, Paris) ; La Torre, Francesco Paolo (CERN) |
| Publication | 2016 |
| Number of pages | 11 |
| In: | EPJ Nuclear Sci. Technol. 2 (2016) 34 |
| DOI | 10.1051/epjn/2016031 |
| Subject category | Health Physics and Radiation Effects |
| Abstract | The evaluation of the activity of radionuclides in radioactive waste is required for its disposal in final repositories. Easy-to-measure nuclides, like γ-emitters and high-energy X-rays, can be measured via non-destructive nuclear techniques from outside a waste package. Some radionuclides are difficult-to-measure (DTM) from outside a package because they are α- or β-emitters. The present article discusses the application of linear regression, scaling factors (SF) and the so-called “mean activity method” to estimate the activity of DTM nuclides on metallic waste produced at the European Organization for Nuclear Research (CERN). Various statistical sampling techniques including simple random sampling, systematic sampling, stratified and authoritative sampling are described and applied to 2 waste populations of activated copper cables. The bootstrap is introduced as a tool to estimate average activities and standard errors in waste characterization. The analysis of the DTM Ni-63 is used as an example. Experimental and theoretical values of SFs are calculated and compared. Guidelines for sampling historical waste using probabilistic and non-probabilistic sampling are finally given. |
| Copyright/License | © 2016-2025 B. Zaffora et al. (License: CC-BY-4.0) |
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