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Nuclear Data Uncertainties for Typical LWR Fuel Assemblies and a Simple Reactor Core
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2017 (English)In: Nuclear Data Sheets, ISSN 0090-3752, E-ISSN 1095-9904, Vol. 139, 1-76 p.Article in journal (Refereed) Published
Abstract [en]

Abstract The impact of the current nuclear data library covariances such as in ENDF/B-VII.1, JEFF-3.2, JENDL-4.0, SCALE and TENDL, for relevant current reactors is presented in this work. The uncertainties due to nuclear data are calculated for existing PWR and BWR fuel assemblies (with burn-up up to 40 GWd/tHM, followed by 10 years of cooling time) and for a simplified PWR full core model (without burn-up) for quantities such as k ∞ , macroscopic cross sections, pin power or isotope inventory. In this work, the method of propagation of uncertainties is based on random sampling of nuclear data, either from covariance files or directly from basic parameters. Additionally, possible biases on calculated quantities are investigated such as the self-shielding treatment. Different calculation schemes are used, based on CASMO, SCALE, DRAGON, MCNP or FISPACT-II, thus simulating real-life assignments for technical-support organizations. The outcome of such a study is a comparison of uncertainties with two consequences. One: although this study is not expected to lead to similar results between the involved calculation schemes, it provides an insight on what can happen when calculating uncertainties and allows to give some perspectives on the range of validity on these uncertainties. Two: it allows to dress a picture of the state of the knowledge as of today, using existing nuclear data library covariances and current methods.

Place, publisher, year, edition, pages
2017. Vol. 139, 1-76 p.
National Category
Subatomic Physics
Identifiers
URN: urn:nbn:se:uu:diva-316069DOI: 10.1016/j.nds.2017.01.001ISI: 000393254900002OAI: oai:DiVA.org:uu-316069DiVA: diva2:1076838
Available from: 2017-02-24 Created: 2017-02-24 Last updated: 2017-11-29Bibliographically approved

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Sjöstrand, HenrikHernandez Solis, Augusto

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