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A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties
Material activation can sometimes cause large heterogeneities in the distribution of radioactivity (hotspots). Moreover, the sample geometry parameters are not always well known. When performing gamma-spectroscopy to quantify the radionuclide inventory in activated materials, often predefine...
Autores principales: | , , , , |
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Lenguaje: | eng |
Publicado: |
2020
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Acceso en línea: | https://dx.doi.org/10.1016/j.apradiso.2019.108953 http://cds.cern.ch/record/2699588 |
_version_ | 1780964502436577280 |
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author | Frosio, Thomas Menaa, Nabil Bertreix, Philippe Rimlinger, Maeva Theis, Chris |
author_facet | Frosio, Thomas Menaa, Nabil Bertreix, Philippe Rimlinger, Maeva Theis, Chris |
author_sort | Frosio, Thomas |
collection | CERN |
description | Material activation can sometimes cause large heterogeneities in the distribution of radioactivity (hotspots). Moreover, the sample geometry parameters are not always well known. When performing gamma-spectroscopy to quantify the radionuclide inventory in activated materials, often predefined models are used to represent the sample geometry (dimensions, source-to-detector distance, material type) and their activity distribution, for efficiency calibration. This simplification causes uncertainties of the efficiency curves associated with the model and consequently, to the activity results. In this paper, we develop a new approach, based on ISOCS/LabSOCS to quantify and reduce uncertainties originating from the geometry model. The theory is described in this document and an experimental case is discussed. |
id | oai-inspirehep.net-1763240 |
institution | Organización Europea para la Investigación Nuclear |
language | eng |
publishDate | 2020 |
record_format | invenio |
spelling | oai-inspirehep.net-17632402022-08-10T12:12:24Zdoi:10.1016/j.apradiso.2019.108953http://cds.cern.ch/record/2699588engFrosio, ThomasMenaa, NabilBertreix, PhilippeRimlinger, MaevaTheis, ChrisA novel technique for the optimization and reduction of gamma spectroscopy geometry uncertaintiesMaterial activation can sometimes cause large heterogeneities in the distribution of radioactivity (hotspots). Moreover, the sample geometry parameters are not always well known. When performing gamma-spectroscopy to quantify the radionuclide inventory in activated materials, often predefined models are used to represent the sample geometry (dimensions, source-to-detector distance, material type) and their activity distribution, for efficiency calibration. This simplification causes uncertainties of the efficiency curves associated with the model and consequently, to the activity results. In this paper, we develop a new approach, based on ISOCS/LabSOCS to quantify and reduce uncertainties originating from the geometry model. The theory is described in this document and an experimental case is discussed.oai:inspirehep.net:17632402020 |
spellingShingle | Frosio, Thomas Menaa, Nabil Bertreix, Philippe Rimlinger, Maeva Theis, Chris A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
title | A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
title_full | A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
title_fullStr | A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
title_full_unstemmed | A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
title_short | A novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
title_sort | novel technique for the optimization and reduction of gamma spectroscopy geometry uncertainties |
url | https://dx.doi.org/10.1016/j.apradiso.2019.108953 http://cds.cern.ch/record/2699588 |
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