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A Bayesian framework to update scaling factors for radioactive waste characterization

  • Published:2020-05 Issue: Volume:159 Page:109092
  • ISSN:0969-8043
  • Container-title:Applied Radiation and Isotopes
  • language:en
  • Short-container-title:Applied Radiation and Isotopes

Author:

Zaffora Biagio,Demeyer Severine,Magistris Matteo,Ronchetti Elvezio,Saporta Gilbert,Theis Chris

Publisher

Elsevier BV

Subject

Radiation

Reference13 articles.

1. Statistical Inference;Casella,2001

2. Bayesian Data Analysis;Gelman,2013

3. Monte Carlo sampling methods using Markov chains and their applications;Hastings;Biometrika,1970

4. Strategy and Methodology for Radioactive Waste Characterization;Iaea,2007

5. No. NW-T-1.18. Determination and Use of Scaling Factors for Waste Characterization in Nuclear Power Plants;Iaea,2009

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1. The ability to manage uncertainty for solid radioactive waste characterization in the UK nuclear industry;Nuclear Engineering and Technology;2024-07

2. Advances toward sustainable radioactive waste conditioning and storage practices;Nuclear Waste Management Facilities;2024

3. Coupling gamma ray spectrometry and tomography in a Bayesian frame;Nuclear Instruments and Methods in Physics Research Section A: Accelerators, Spectrometers, Detectors and Associated Equipment;2021-02

4. Statistical Methodologies for Scaling Factor Implementation: Part 1. Overview of Current Scaling Factor Method for Radioactive Waste Characterization;Journal of Nuclear Fuel Cycle and Waste Technology(JNFCWT);2020-12-30
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