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  4. Applying SHARK-X to perform data assimilation with the LWR-PROTEUS Phase II integral experiments
 
research article

Applying SHARK-X to perform data assimilation with the LWR-PROTEUS Phase II integral experiments

Siefman, Daniel  
•
Hursin, Mathieu
•
Perret, Gregory
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March 1, 2020
Progress In Nuclear Energy

Data assimilation methods have recently been implemented in the sensitivity analysis and uncertainty quantification tool SHARK-X. This paper presents how they were used with sensitivity coefficients and randomly-sampled nuclear data to simulate integral parameters from the LWR-PROTEUS Phase II experiment. The adjusted calculated values of the integral parameters showed small differences between the two implemented data assimilation methods, GLLS and MOCABA. The differences were statistically significant, but were caused by round-off errors. The experiment was also analyzed to search for sources of bias in the simulations. Analysis of the chi-squared parameter showed that many of the integral parameters have biases that were inconsistent with their high correlation. This indicates that the bias likely arose from sources other than nuclear data, like the modeling of the fuel burnup, the 2D model in CASMO-5M, or from experimental methods. The nuclear data adjustments were analyzed and ranked according to how they improved the computational bias and reduced its uncertainty.

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Type
research article
DOI
10.1016/j.pnucene.2020.103245
Web of Science ID

WOS:000517851500008

Author(s)
Siefman, Daniel  
Hursin, Mathieu
Perret, Gregory
Pautz, Andreas  
Date Issued

2020-03-01

Publisher

PERGAMON-ELSEVIER SCIENCE LTD

Published in
Progress In Nuclear Energy
Volume

121

Article Number

103245

Subjects

Nuclear Science & Technology

•

data assimilation

•

nuclear data

•

casmo-5m

•

spent fuel

•

proteus

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cross-section adjustment

•

uncertainty analysis

Editorial or Peer reviewed

REVIEWED

Written at

EPFL

EPFL units
LRS  
Available on Infoscience
March 18, 2020
Use this identifier to reference this record
https://infoscience.epfl.ch/handle/20.500.14299/167370
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