A correlated sampling technique has been implemented to estimate the impact of cross section modifications on the neutron transport and in Monte Carlo simulations in one single calculation. This implementation has been coupled to a Total Monte Carlo approach which consists in propagating nuclear data uncertainties with random cross section files. | Uncertainty propagation based on correlated sampling technique for nuclear data applications EPJ Nuclear Sci. Technol. 6 8 2020 Nuclear Sciences c A. Laureau et al. published by EDP Sciences 2020 amp Technologies https epjn 2020003 Available online at https REGULAR ARTICLE Uncertainty propagation based on correlated sampling technique for nuclear data applications Axel Laureau 1 Vincent Lamirand 1 2 Dimitri Rochman 2 and Andreas Pautz 3 1 Laboratory for Reactor Physics and Systems behaviour LRS Ecole Polytechnique F ed erale de Lausanne EPFL 1015 Lausanne Switzerland 2 Laboratory for Reactor Physics and Thermal Hydraulics LRT Paul Scherrer Institut PSI 5232 Villigen Switzerland 3 Nuclear Energy and Safety Research Division NES Paul Scherrer Institut PSI 5232 Villigen Switzerland Received 2 September 2019 Received in final form 15 November 2019 Accepted 16 January 2020 Abstract. A correlated sampling technique has been implemented to estimate the impact of cross section modifications on the neutron transport and in Monte Carlo simulations in one single calculation. This imple- mentation has been coupled to a Total Monte Carlo approach which consists in propagating nuclear data uncertainties with random cross section files. The TMC-CS Total Monte Carlo with Correlated Sampling approach offers an interesting speed-up of the associated computation time. This methodology is detailed in this paper together with two application cases to validate and illustrate the gain provided by this technique the highly enriched uranium iron metal core reflected by a stainless-steel reflector HMI-001 benchmark and the PETALE experimental programme in the CROCUS zero-power light water reactor. 1 Introduction approach which uses a representation of the cross section uncertainties as a set of cross sections with a given dis- Reactor studies require nuclear data as an input of the persion 4 . Then the propagation of these cross sections calculations through
