MODELLING ASTRID-LIKE SODIUM-COOLED FAST REACTOR WITH SERPENT-DYN3D CODE SEQUENCE

¹ University of Cambridge, Department of Engineering, Cambridge Nuclear Energy Centre, Trumpington Street, CB2 1PZ, Cambridge, UK
² Helmholtz-Zentrum Dresden-Rossendorf, Reactor Safety Division, Institute of Resource Ecology, Bautzner Landstraße 400, 01328 Dresden, Germany

wojciech@rydlewicz.pl
e.fridman@hzdr.de
es607@cam.ac.uk

Published online: 22 February 2021

Abstract

This study explores the feasibility of applying the Serpent-DYN3D sequence to the analysis of Sodium-cooled Fast Reactors (SFRs) with complex core geometries, such as the ASTRIDlike design. The core is characterised by a highly heterogeneous configuration and was likely to challenge the accuracy of the Serpent-DYN3D sequence. It includes axially heterogeneous fuel assemblies, non-uniform fuel assembly heights and large sodium plena. Consequently, the influence of generation and correction methods of various homogenised, few-group crosssections (XS) on the accuracy of the full-core nodal diffusion DYN3D calculations is presented. An attempt to compare the approximate time effort spent on models preparation against the accuracy of the result is made. Results are compared to reference full-core Serpent MC (Monte Carlo) solutions. Initially, XS data was generated in Serpent using traditional methods (2D single assemblies and 2D super-cells). Full core calculations and MC simulations offered a moderate agreement. Therefore, XS generation with 2D fuel-reflector models and 3D single assembly models was verified. Super-homogenisation (SPH) factors for XS correction were applied. In conclusion, the performed work suggests that Serpent-DYN3D sequence could be used for the analysis of highly heterogeneous SFR designs similar to the studied ASTRID-like, with an only small penalty on the accuracy of the core reactivity and radial power distribution prediction. However, the XS generation route would need to include the correction with SPH factors and generation of XS with various MC models, for different core regions. At a certain point, there are diminishing returns to using more complex XS generation methods, as the accuracy of full-core deterministic calculations improves only slightly, while the time effort required increases significantly.