2017
DOI: 10.1051/epjconf/201714609023
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Fission yield covariances for JEFF: A Bayesian Monte Carlo method

Abstract: Abstract. The JEFF library does not contain fission yield covariances, but simply best estimates and uncertainties. This situation is not unique as all libraries are facing this deficiency, firstly due to the lack of a defined format. An alternative approach is to provide a set of random fission yields, themselves reflecting covariance information. In this work, these random files are obtained combining the information from the JEFF library (fission yields and uncertainties) and the theoretical knowledge from … Show more

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Cited by 6 publications
(3 citation statements)
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“…The two approaches were used to determine the thermal cumulative fission yields of the Neodymium isotopes for 235 U. Prior covariance matrix was generated by randomly varying model parameters of the GEF code [20]. The obtained covariance matrix was then modified by adding defect model contributions calculated as the difference between the evaluated values from JEFF-3.…”
Section: A Methodologymentioning
confidence: 99%
“…The two approaches were used to determine the thermal cumulative fission yields of the Neodymium isotopes for 235 U. Prior covariance matrix was generated by randomly varying model parameters of the GEF code [20]. The obtained covariance matrix was then modified by adding defect model contributions calculated as the difference between the evaluated values from JEFF-3.…”
Section: A Methodologymentioning
confidence: 99%
“…Covariance matrix assessment depends on the evaluation process and its validity assumes that all measurements are statistically in agreement. These last years, different covariance matrices have been suggested but the experimental part of those are neglected in covariance evaluation [1] [2][3] [4] or applications [5] [6]. In the first part we present an assessment methodology based on statistical test.…”
Section: Introductionmentioning
confidence: 99%
“…Nevertheless, the covariance matrix depends on the evaluation process and its existence assumes that all measurements are statistically in agreement. These last years, different covariance matrices have been suggested but the experimental part of those are not taken into account [1][2][3][4][5][6].…”
Section: Introductionmentioning
confidence: 99%