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A Bayesian Monte Carlo method for fission yield covariance information
Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
Paul Scherrer Inst, Reactor Phys & Syst Behav Lab, Villigen, Switzerland..
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2016 (English)In: Annals of Nuclear Energy, ISSN 0306-4549, E-ISSN 1873-2100, Vol. 95, 125-134 p.Article in journal (Refereed) PublishedText
Abstract [en]

The present work proposes a Bayesian method to combine theoretical fission yields with a set of reference data. These two sources of information are merged using a Monte Carlo process, and leads to a so-called Bayesian Monte Carlo update. Examples are presented for the independent fission yields of four major actinides, using the GEF code as a source of theoretical calculations and an evaluated library of fission yields for the reference data. The impact of the updated fission yields and their covariances is shown for two distinct applications: a UO2 pincell with burn-up up to 40 GWD/tHM and decay heat calculations of a thermal neutron pulse on U-235 and Pu-239.

Place, publisher, year, edition, pages
2016. Vol. 95, 125-134 p.
Keyword [en]
Fission yields, GEF, Bayesian update, Burn-up
National Category
Subatomic Physics
Identifiers
URN: urn:nbn:se:uu:diva-300428DOI: 10.1016/j.anucene.2016.05.005ISI: 000379369100014OAI: oai:DiVA.org:uu-300428DiVA: diva2:951579
Available from: 2016-08-09 Created: 2016-08-09 Last updated: 2016-08-09Bibliographically approved

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Koning, Arjan J.
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Applied Nuclear Physics
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