MACROSCOPIC CROSS SECTIONS GENERATION BY MONTE CARLO CODE MCS FOR FAST REACTOR ANALYSIS

Ulsan National Institute of Science and Technology (UNIST) 50 UNIST-gil, Ulsan 44919, Republic of Korea

tungnguyen@unist.ac.kr
hyunsuklee@unist.ac.kr
dxndxnwww@unist.ac.kr
dosvutheam8@unist.ac.kr
trantuan@unist.ac.kr
deokjung@unist.ac.kr

Published online: 22 February 2021

Abstract

Recent researches have become more interested in the feasibility of using Monte Carlo (MC) code to generate multi-group (MG) cross sections (XSs) for fast reactor analysis using nodal diffusion codes. The current study, therefore, presents a brief methodology for MG XSs generation by the in-house UNIST MC code MCS, which can be compatibly utilized in nodal diffusion codes, PARCS and RAST-K. The applicability of the methodology is quantified on the sodium fast reactor (SFR) ABR-1000 design with a metallic fuel from the OECD/NEA SRF benchmark. The few-group XSs generated by MCS with a two-dimensional (2D) fuel assembly geometry are well consistent with those of SERPENT 2. Furthermore, the simulation of beginning-of-cycle (BOC) steady-state three-dimensional (3D) whole-core problem with PARCS and RAST-K is conducted using the generated 24-group XSs by MCS. The nodal diffusion solutions, including the core k_eff, power profiles and various of reactivity parameters, are compared to reference whole-core results obtained by MC code MCS. Overall, the code-to-code comparison indicates a reasonable agreement between deterministic and stochastic codes, with the difference in k_eff less than 100 pcm and the root-mean-square (RMS) error in assembly power less than 1.15%. Therefore, it is successfully demonstrated that the employment of the MG XSs generation by MCS for nodal diffusion codes is feasible to accurately perform analyses for fast reactors.