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Monte Carlo integral adjustment of nuclear data libraries: experimental covariances and inconsistent data
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. (Reactiongroup)ORCID iD: 0000-0002-7595-8024
Uppsala University, Disciplinary Domain of Science and Technology, Physics, Department of Physics and Astronomy, Applied Nuclear Physics. (Reactiongroup)ORCID iD: 0000-0001-5007-2975
2019 (English)In: EPJ Web of Conferences, ISSN 2101-6275, E-ISSN 2100-014X, Vol. 211, no 07007Article in journal (Refereed) Published
Abstract [en]

Integral experiments can be used to adjust nuclear data libraries. Here a Bayesian Monte Carlo method based on assigning weights to the different random files is used. If the experiments are inconsistent within them-self or with the nuclear data it is shown that the adjustment procedure can lead to undesirable results. Therefore, a technique to treat inconsistent data is presented. The technique is based on the optimization of the marginal likelihood which is approximated by a sample of model calculations. The sources to the inconsistencies are discussed and the importance to take into account correlation between the different experiments is emphasized. It is found that the technique can address inconsistencies in a desirable way.

Place, publisher, year, edition, pages
EDP Sciences, 2019. Vol. 211, no 07007
National Category
Physical Sciences
Identifiers
URN: urn:nbn:se:uu:diva-378726DOI: 10.1051/epjconf/201921107007ISI: 000501343100034OAI: oai:DiVA.org:uu-378726DiVA, id: diva2:1294841
Conference
WONDER-2018: 5th edition of the International Workshop On Nuclear Data Evaluation for Reactor Applications,Aix-en-Provence, France, 8-12 October 2018
Funder
Swedish Research CouncilAvailable from: 2019-03-08 Created: 2019-03-08 Last updated: 2020-01-14Bibliographically approved

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Publisher's full texthttps://www.epj-conferences.org/articles/epjconf/abs/2019/16/epjconf_wonder2019_07007/epjconf_wonder2019_07007.html

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Sjöstrand, HenrikSchnabel, Georg
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CiteExportLink to record
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