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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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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