Sampling strategy and statistical analysis for radioactive waste characterization

Nadia Perot (1, 2) , Alexandre Le Cocguen , Dominique Carré (3) , Hervé Lamotte (4) , Anne Duhart-Barone , Ingmar Pointeau (5)

1 LEMS - Laboratoire d'études et de modélisations des systèmes
2 SESI - Service d'Etudes des Systèmes Innovants
3 LabSIC - Laboratoire des Sciences de l'Information et de la Communication
4 CEA-DES (ex-DEN) - CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire)
5 LMTE - Laboratoire de Modélisation des Transferts dans l'Environnement

This paper describes the methodology we have developed to define a sampling strategy adapted to operational constraints in order to characterize the dihydrogen flow rate of 2714 nuclear waste drums produced by radiolysis reaction of organic mixed with α-emitters. The objective was to perform few but relevant measurements. Thus, a sample of only 38 drums has been selected to be measured. Statistical analysis of drum measurement data of dihydrogen rate provided an estimation of the mean and the upper bound of the physical quantity of interest which gave a good convergence with global measurements from the ventilation system of the facility. Thereafter, performing a factorial data analysis has demonstrated the representativeness of the measurement data set and the sampling strategy assumption validity. Moreover, it provided information that has been used for a regression analysis to develop a linear prediction model of dihydrogen flow rate production for the waste drum characterization.

Mots clés: statistical analysis; sampling strategy; risk analysis; radioactive waste characterisation

Domaines: Analyse de données, Statistiques et Probabilités [physics.data-an]

Nadia Perot, Alexandre Le Cocguen, Dominique Carré, Hervé Lamotte, Anne Duhart-Barone, et al.. Sampling strategy and statistical analysis for radioactive waste characterization. Nuclear Engineering and Design, inPress. ⟨cea-02319106⟩