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On the use of integral experiments for uncertainty reduction of reactor macroscopic parameters within the TMC methodology
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Tillämpad kärnfysik. (Nuclear Research Group)
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Tillämpad kärnfysik. (Nuclear Reactions Group)ORCID-id: 0000-0002-7595-8024
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Tillämpad kärnfysik. (Nuclear Reactions Group)
Uppsala universitet, Teknisk-naturvetenskapliga vetenskapsområdet, Fysiska sektionen, Institutionen för fysik och astronomi, Tillämpad kärnfysik. (Nuclear Reaction Group)
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2016 (Engelska)Ingår i: Progress in nuclear energy (New series), ISSN 0149-1970, E-ISSN 1878-4224, Vol. 88, s. 43-52Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

The current nuclear data uncertainties observed in reactor safety parameters for some nuclides call for safety concerns especially with respect to the design of GEN-IV reactors and must therefore be reduced significantly. In this work, uncertainty reduction using criticality benchmark experiments within the Total Monte Carlo methodology is presented. Random nuclear data libraries generated are processed and used to analyze a set of criticality benchmarks. Since the calculated results for each random nuclear data used are different, an algorithm was used to select (or assign weights to) the libraries which give a good description of experimental data for the analyses of the benchmarks. The selected or weighted libraries were then used to analyze the ELECTRA reactor. By using random nuclear data libraries constrained with only differential experimental data as our prior, the uncertainties observed were further reduced by constraining the files with integral experimental data to obtain a posteriori uncertainties on the k(eff). Two approaches are presented and compared: a binary accept/reject and a method of assigning file weights based on the likelihood function. Significant reductions in (PU)-P-239 and Pb-208 nuclear data uncertainties in the k(eff) were observed after implementing the two methods with some criticality benchmarks for the ELELIRA reactor. (C) 2015 Elsevier Ltd. All rights reserved.

Ort, förlag, år, upplaga, sidor
2016. Vol. 88, s. 43-52
Nyckelord [en]
Nuclear data, uncertainty reduction, binary accept/reject, file weights, Total Monte Carlo, criticality benchmarks, ELECTRA
Nationell ämneskategori
Subatomär fysik
Forskningsämne
Fysik med inriktning mot tillämpad kärnfysik
Identifikatorer
URN: urn:nbn:se:uu:diva-264410DOI: 10.1016/j.pnucene.2015.11.015ISI: 000372564400006OAI: oai:DiVA.org:uu-264410DiVA, id: diva2:860196
Forskningsfinansiär
VetenskapsrådetTillgänglig från: 2015-10-11 Skapad: 2015-10-11 Senast uppdaterad: 2017-12-01Bibliografiskt granskad
Ingår i avhandling
1. Nuclear data uncertainty quantification and data assimilation for a lead-cooled fast reactor: Using integral experiments for improved accuracy
Öppna denna publikation i ny flik eller fönster >>Nuclear data uncertainty quantification and data assimilation for a lead-cooled fast reactor: Using integral experiments for improved accuracy
2015 (Engelska)Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
Abstract [en]

For the successful deployment of advanced nuclear systems and optimization of current reactor designs, high quality nuclear data are required. Before nuclear data can be used in applications they must first be evaluated, tested and validated against a set of integral experiments, and then converted into formats usable for applications. The evaluation process in the past was usually done by using differential experimental data which was then complemented with nuclear model calculations. This trend is fast changing due to the increase in computational power and tremendous improvements in nuclear reaction models over the last decade. Since these models have uncertain inputs, they are normally calibrated using experimental data. However, these experiments are themselves not exact. Therefore, the calculated quantities of model codes such as cross sections and angular distributions contain uncertainties. Since nuclear data are used in reactor transport codes as input for simulations, the output of transport codes contain uncertainties due to these data as well. Quantifying these uncertainties is important for setting safety margins; for providing confidence in the interpretation of results; and for deciding where additional efforts are needed to reduce these uncertainties. Also, regulatory bodies are now moving away from conservative evaluations to best estimate calculations that are accompanied by uncertainty evaluations.

In this work, the Total Monte Carlo (TMC) method was applied to study the impact of nuclear data uncertainties from basic physics to macroscopic reactor parameters for the European Lead Cooled Training Reactor (ELECTRA). As part of the work, nuclear data uncertainties of actinides in the fuel, lead isotopes within the coolant, and some structural materials have been investigated. In the case of the lead coolant it was observed that the uncertainty in the keff and the coolant void worth (except in the case of 204Pb), were large, with the most significant contribution coming from 208Pb. New 208Pb and 206Pb random nuclear data libraries with realistic central values have been produced as part of this work. Also, a correlation based sensitivity method was used in this work, to determine parameter - cross section correlations for different isotopes and energy groups.

Furthermore, an accept/reject method and a method of assigning file weights based on the likelihood function are proposed for uncertainty reduction using criticality benchmark experiments within the TMC method. It was observed from the study that a significant reduction in nuclear data uncertainty was obtained for some isotopes for ELECTRA after incorporating integral benchmark information. As a further objective of this thesis, a method for selecting benchmark for code validation for specific reactor applications was developed and applied to the ELECTRA reactor. Finally, a method for combining differential experiments and integral benchmark data for nuclear data adjustments is proposed and applied for the adjustment of neutron induced 208Pb nuclear data in the fast energy region.

Ort, förlag, år, upplaga, sidor
Uppsala: Acta Universitatis Upsaliensis, 2015. s. 85
Serie
Digital Comprehensive Summaries of Uppsala Dissertations from the Faculty of Science and Technology, ISSN 1651-6214 ; 1315
Nyckelord
Total Monte Carlo, ELECTRA, nuclear data, uncertainty propagation, integral experiments, nuclear data adjustment, uncertainty reduction
Nationell ämneskategori
Subatomär fysik
Identifikatorer
urn:nbn:se:uu:diva-265502 (URN)978-91-554-9407-0 (ISBN)
Disputation
2015-12-17, polhemsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, Uppsala, 09:15 (Engelska)
Opponent
Handledare
Tillgänglig från: 2015-11-24 Skapad: 2015-10-30 Senast uppdaterad: 2016-01-13

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Alhassan, ErwinSjöstrand, HenrikHelgesson, PetterÖsterlund, MichaelPomp, StephanKoning, Arjan J.
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Progress in nuclear energy (New series)
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