A stochastic method to propagate uncertainties along large cores deterministic calculations

Deterministic uncertainty propagation methods are certainly powerful and time-sparing but their access to uncertainties related to the power map remains difficult due to a lack of numerical convergence. On the contrary, stochastic methods do not face such an issue and they enable a more rigorous acc...

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Main Authors: Volat Ludovic, Gastaldi Bernard, Santamarina Alain
Format: Article
Language:English
Published: EDP Sciences 2018-01-01
Series:EPJ Nuclear Sciences & Technologies
Online Access:https://doi.org/10.1051/epjn/2018015
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spelling doaj-ea041823dffc432cb75fe85219ca00ab2021-03-02T09:14:40ZengEDP SciencesEPJ Nuclear Sciences & Technologies2491-92922018-01-0141210.1051/epjn/2018015epjn170067A stochastic method to propagate uncertainties along large cores deterministic calculationsVolat LudovicGastaldi BernardSantamarina AlainDeterministic uncertainty propagation methods are certainly powerful and time-sparing but their access to uncertainties related to the power map remains difficult due to a lack of numerical convergence. On the contrary, stochastic methods do not face such an issue and they enable a more rigorous access to uncertainty related to the PFNS. Our method combines an innovative transport calculation chain and a stochastic way of propagating uncertainties on nuclear data: first, our calculation scheme consists in the calculation of assembly self-shielded cross sections and a pin-by-pin flux calculation on the whole core. Validation was done and the required CPU time is suitable to allow numerous calculations. Then, we sample nuclear cross sections with consistent probability distribution functions with a correlated optimized Latin Hypercube Sampling. Finally, we deduce the power map uncertainties from the study of the output response functions. We performed our study on the system described in the framework of the OECD/NEA Expert Group in Uncertainty Analysis in Modelling. Results show the 238U inelastic scattering cross section, the 235U PFNS, the elastic scattering cross section of 1H and the 56Fe cross sections as major contributors to the total uncertainty on the power map: the power tilt between central and peripheral assemblies using COMAC-V2 covariance library amounts to 5.4% (1σ) (respectively 7.4% (1σ) using COMAC-V0).https://doi.org/10.1051/epjn/2018015
collection DOAJ
language English
format Article
sources DOAJ
author Volat Ludovic
Gastaldi Bernard
Santamarina Alain
spellingShingle Volat Ludovic
Gastaldi Bernard
Santamarina Alain
A stochastic method to propagate uncertainties along large cores deterministic calculations
EPJ Nuclear Sciences & Technologies
author_facet Volat Ludovic
Gastaldi Bernard
Santamarina Alain
author_sort Volat Ludovic
title A stochastic method to propagate uncertainties along large cores deterministic calculations
title_short A stochastic method to propagate uncertainties along large cores deterministic calculations
title_full A stochastic method to propagate uncertainties along large cores deterministic calculations
title_fullStr A stochastic method to propagate uncertainties along large cores deterministic calculations
title_full_unstemmed A stochastic method to propagate uncertainties along large cores deterministic calculations
title_sort stochastic method to propagate uncertainties along large cores deterministic calculations
publisher EDP Sciences
series EPJ Nuclear Sciences & Technologies
issn 2491-9292
publishDate 2018-01-01
description Deterministic uncertainty propagation methods are certainly powerful and time-sparing but their access to uncertainties related to the power map remains difficult due to a lack of numerical convergence. On the contrary, stochastic methods do not face such an issue and they enable a more rigorous access to uncertainty related to the PFNS. Our method combines an innovative transport calculation chain and a stochastic way of propagating uncertainties on nuclear data: first, our calculation scheme consists in the calculation of assembly self-shielded cross sections and a pin-by-pin flux calculation on the whole core. Validation was done and the required CPU time is suitable to allow numerous calculations. Then, we sample nuclear cross sections with consistent probability distribution functions with a correlated optimized Latin Hypercube Sampling. Finally, we deduce the power map uncertainties from the study of the output response functions. We performed our study on the system described in the framework of the OECD/NEA Expert Group in Uncertainty Analysis in Modelling. Results show the 238U inelastic scattering cross section, the 235U PFNS, the elastic scattering cross section of 1H and the 56Fe cross sections as major contributors to the total uncertainty on the power map: the power tilt between central and peripheral assemblies using COMAC-V2 covariance library amounts to 5.4% (1σ) (respectively 7.4% (1σ) using COMAC-V0).
url https://doi.org/10.1051/epjn/2018015
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