Generation of fission yield covariances to correct discrepancies in the nuclear data libraries

Abstract Fission yield uncertainties and correlations should be considered in the uncertainty quantification of burnup responses — e.g. isotopic inventory, effective neutron multiplication factor k eff . Although nuclear data libraries generally provide independent fission yield uncertainties along with the best estimates, currently they lack complete covariance matrices. In addition, several inconsistencies were detected amongst the current fission yield evaluated uncertainties, which could impact on uncertainty quantification (UQ) studies. As a part of this work, we introduced fission yield correlations to sort out the data inconsistency found in the JEFF-3.1.1 fission yield library. Such correlations are produced using an iterative generalised least square (GLS) updating technique, with conservation equations acting as fitting models. The process revises the fission yield estimates and covariances according to reliable evaluations, when available, or conservation criteria. We chose to work with the PWR fuel rod model of the REBUS international program to test the new covariances, since experimental uncertainties on several concentrations are available. We propagated the original and updated fission yield covariances using a sampling approach and we quantified the uncertainty of k eff and nuclide densities in the chosen burnup problem. The response uncertainty for k eff and nuclide densities showed a sharp drop when using the new set of fission yield covariance matrices.

[1]  D. Aldama,et al.  Handbook of Nuclear Data for Safeguards: Database Extensions, August 2008 , 2008 .

[2]  M. Herman,et al.  ENDF-6 Formats Manual Data Formats and Procedures for the Evaluated Nuclear Data File ENDF/B-VI and ENDF/B-VII Written by the Members of the Cross Sections Evaluation Working Group Last Revision Edited by , 2009 .

[3]  G. Van den Eynde,et al.  Fission yield covariance generation and uncertainty propagation through fission pulse decay heat calculation , 2014 .

[4]  Donald L. Smith,et al.  Probability, statistics, and data uncertainties in nuclear science and technology , 1991 .

[5]  N. García-Herranz,et al.  Propagation of statistical and nuclear data uncertainties in Monte Carlo burn-up calculations , 2008 .

[6]  D. R. Weaver,et al.  A new evaluation of fission product yields and the production of a new library (UKFY2) of independent and cumulative yields , 1991 .

[7]  Ian C Gauld,et al.  Investigation of Inconsistent ENDF/B-VII.1 Independent and Cumulative Fission Product Yields with Proposed Revisions , 2015 .

[8]  J. Gentle.  Random number generation and Monte Carlo methods , 1998 .

[9]  N. M. Larson,et al.  ENDF/B-VII.1 Nuclear Data for Science and Technology: Cross Sections, Covariances, Fission Product Yields and Decay Data , 2011 .

[10]  G. V. D. Eynde,et al.  Advanced Method for Calculations of Core Burn-Up, Activation of Structural Materials, and Spallation Products Accumulation in Accelerator-Driven Systems , 2012 .

[11]  O. Cabellos,et al.  Inventory calculation and nuclear data uncertainty propagation on light water reactor fuel using ALEPH-2 and SCALE 6.2 , 2015 .

[12]  Mark B. Chadwick,et al.  Estimation of 239Pu independent and cumulative fission product yields from the chain yield data using a Bayesian technique , 2013 .