Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations

The ANSWERS Software Service is developing a number of techniques to better understand and quantify uncertainty on calculations of the neutron multiplication factor, k-effective, in nuclear fuel and other systems containing fissile material. The uncertainty on the calculated k-effective arises from...

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Main Authors: Ware Tim, Dobson Geoff, Hanlon David, Hiles Richard, Mason Robert, Perry Ray
Format: Article
Language:English
Published: EDP Sciences 2017-01-01
Series:EPJ Web of Conferences
Online Access:https://doi.org/10.1051/epjconf/201714606023
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spelling doaj-21b4fc7196244961ba3d6a2e0ad0ff672021-08-02T13:57:56ZengEDP SciencesEPJ Web of Conferences2100-014X2017-01-011460602310.1051/epjconf/201714606023epjconf-nd2016_06023Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculationsWare Tim0Dobson Geoff1Hanlon David2Hiles Richard3Mason Robert4Perry Ray5ANSWERS Software Service, Amec Foster Wheeler, Kings Point House, Queen Mother Square, Poundbury, DorchesterANSWERS Software Service, Amec Foster Wheeler, Kings Point House, Queen Mother Square, Poundbury, DorchesterANSWERS Software Service, Amec Foster Wheeler, Kings Point House, Queen Mother Square, Poundbury, DorchesterANSWERS Software Service, Amec Foster Wheeler, Kings Point House, Queen Mother Square, Poundbury, DorchesterANSWERS Software Service, Amec Foster Wheeler, Kings Point House, Queen Mother Square, Poundbury, DorchesterANSWERS Software Service, Amec Foster Wheeler, Kings Point House, Queen Mother Square, Poundbury, DorchesterThe ANSWERS Software Service is developing a number of techniques to better understand and quantify uncertainty on calculations of the neutron multiplication factor, k-effective, in nuclear fuel and other systems containing fissile material. The uncertainty on the calculated k-effective arises from a number of sources, including nuclear data uncertainties, manufacturing tolerances, modelling approximations and, for Monte Carlo simulation, stochastic uncertainty. For determining the uncertainties due to nuclear data, a set of application libraries have been generated for use with the MONK10 Monte Carlo and the WIMS10 deterministic criticality and reactor physics codes. This paper overviews the generation of these nuclear data libraries by Latin hypercube sampling of JEFF-3.1.2 evaluated data based upon a library of covariance data taken from JEFF, ENDF/B, JENDL and TENDL evaluations. Criticality calculations have been performed with MONK10 and WIMS10 using these sampled libraries for a number of benchmark models of fissile systems. Results are presented which show the uncertainty on k-effective for these systems arising from the uncertainty on the input nuclear data.https://doi.org/10.1051/epjconf/201714606023
collection DOAJ
language English
format Article
sources DOAJ
author Ware Tim
Dobson Geoff
Hanlon David
Hiles Richard
Mason Robert
Perry Ray
spellingShingle Ware Tim
Dobson Geoff
Hanlon David
Hiles Richard
Mason Robert
Perry Ray
Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations
EPJ Web of Conferences
author_facet Ware Tim
Dobson Geoff
Hanlon David
Hiles Richard
Mason Robert
Perry Ray
author_sort Ware Tim
title Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations
title_short Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations
title_full Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations
title_fullStr Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations
title_full_unstemmed Determining the nuclear data uncertainty on MONK10 and WIMS10 criticality calculations
title_sort determining the nuclear data uncertainty on monk10 and wims10 criticality calculations
publisher EDP Sciences
series EPJ Web of Conferences
issn 2100-014X
publishDate 2017-01-01
description The ANSWERS Software Service is developing a number of techniques to better understand and quantify uncertainty on calculations of the neutron multiplication factor, k-effective, in nuclear fuel and other systems containing fissile material. The uncertainty on the calculated k-effective arises from a number of sources, including nuclear data uncertainties, manufacturing tolerances, modelling approximations and, for Monte Carlo simulation, stochastic uncertainty. For determining the uncertainties due to nuclear data, a set of application libraries have been generated for use with the MONK10 Monte Carlo and the WIMS10 deterministic criticality and reactor physics codes. This paper overviews the generation of these nuclear data libraries by Latin hypercube sampling of JEFF-3.1.2 evaluated data based upon a library of covariance data taken from JEFF, ENDF/B, JENDL and TENDL evaluations. Criticality calculations have been performed with MONK10 and WIMS10 using these sampled libraries for a number of benchmark models of fissile systems. Results are presented which show the uncertainty on k-effective for these systems arising from the uncertainty on the input nuclear data.
url https://doi.org/10.1051/epjconf/201714606023
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