Local correlated sampling Monte Carlo calculations in the TFM neutronics approach for spatial and point kinetics applications - Archive ouverte HAL Access content directly
Journal Articles EPJ N - Nuclear Sciences & Technologies Year : 2017

Local correlated sampling Monte Carlo calculations in the TFM neutronics approach for spatial and point kinetics applications

(1) , (1) , (1)
1

Abstract

These studies are performed in the general framework of transient coupled calculations with accurate neutron kinetics models. This kind of application requires a modeling of the influence on the neutronics of the macroscopic cross-section evolution. Depending on the targeted accuracy, this feedback can be limited to the reactivity for point kinetics, or can take into account the redistribution of the power in the core for spatial kinetics. The local correlated sampling technique for Monte Carlo calculation presented in this paper has been developed for this purpose, i.e. estimating the influence on the neutron transport of a local variation of different parameters such as sodium density or fuel Doppler effect. This method is associated to an innovative spatial kinetics model named Transient Fission Matrix, which condenses the time-dependent Monte Carlo neutronic response in Green functions. Finally, an accurate estimation of the feedback effects on these Green functions provides an on-the-fly prediction of the flux redistribution in the core, whatever the actual perturbation shape is during the transient. This approach is also used to estimate local feedback effects for point kinetics resolution.
Fichier principal
Vignette du fichier
Laur.pdf (799.11 Ko) Télécharger le fichier
Origin : Publisher files allowed on an open archive
Loading...

Dates and versions

cea-02305849 , version 1 (04-10-2019)

Licence

Attribution - CC BY 4.0

Identifiers

Cite

Axel Laureau, Laurent Buiron, Bruno Fontaine. Local correlated sampling Monte Carlo calculations in the TFM neutronics approach for spatial and point kinetics applications. EPJ N - Nuclear Sciences & Technologies, 2017, 3, pp.16. ⟨10.1051/epjn/2017011⟩. ⟨cea-02305849⟩
41 View
89 Download

Altmetric

Share

Gmail Facebook Twitter LinkedIn More