Sampling strategy and statistical analysis for radioactive waste characterization

Autor: Nadia Perot, Dominique Carré, Ingmar Pointeau, Alexandre Le Cocguen, Anne Duhart-Barone, Hervé Lamotte
Přispěvatelé: Laboratoire d'études et de modélisations des systèmes (LEMS), CEA Cadarache, Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Service d'Etudes des Systèmes Innovants (SESI), Département Etude des Réacteurs (DER), CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-CEA-Direction des Energies (ex-Direction de l'Energie Nucléaire) (CEA-DES (ex-DEN)), Laboratoire des Sciences de l'Information et de la Communication (LabSIC), Université Paris 13 (UP13)-Université Sorbonne Paris Cité (USPC), Commissariat à l'énergie atomique et aux énergies alternatives (CEA), Laboratoire de Modélisation des Transferts dans l'Environnement (LMTE), Service Mesures et modélisation des Transferts et des Accidents graves (SMTA), Département Technologie Nucléaire (DTN), Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Commissariat à l'énergie atomique et aux énergies alternatives (CEA)-Département Technologie Nucléaire (DTN)
Jazyk: angličtina
Rok vydání: 2019
Předmět:
FOS: Computer and information sciences
Nuclear and High Energy Physics
Factorial
risk analysis
020209 energy
FOS: Physical sciences
Sample (statistics)
02 engineering and technology
Drum
01 natural sciences
Upper and lower bounds
010305 fluids & plasmas
Methodology (stat.ME)
statistical analysis
0103 physical sciences
0202 electrical engineering
electronic engineering
information engineering
General Materials Science
Safety
Risk
Reliability and Quality
Process engineering
Waste Management and Disposal
Statistics - Methodology
business.industry
Mechanical Engineering
Radioactive waste
Sampling (statistics)
Regression analysis
sampling strategy
radioactive waste characterisation
Data set
Nuclear Energy and Engineering
Physics - Data Analysis
Statistics and Probability
Environmental science
business
Data Analysis
Statistics and Probability (physics.data-an)
[PHYS.PHYS.PHYS-DATA-AN]Physics [physics]/Physics [physics]/Data Analysis
Statistics and Probability [physics.data-an]
Zdroj: Nuclear Engineering and Design
Nuclear Engineering and Design, Elsevier, In press
Nuclear Engineering and Design, inPress
ISSN: 0029-5493
1872-759X
Popis: International audience; 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.
Databáze: OpenAIRE
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