MCS

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The Recommended Publication for Citing

Hyunsuk Lee, Wonkyeong Kim, Peng Zhang, Azamat Khassenov, Yunki Jo, Jinsu Park, Jiankai Yu, Matthieu Lemaire, Deokjung Lee*, “MCS – A Monte Carlo Particle Transport Code for Large-Scale Power Reactor Analysis,” Annals of Nuclear Energy, Accepted for Publication. (2019)
Jaerim Jang, Wonkyeong Kim, Sanggeol Jeong, Eun Jeong, Jinsu Park, Matthieu Lemaire, Hyunsuk Lee, Yongmin Jo, Peng Zhang, Deokjung Lee, “Validation of UNIST Monte Carlo Code MCS for Criticality Safety Analysis of PWR Spent Fuel Pool and Storage Cask,” Annals of Nuclear Energy, 114: 495-509. https://doi.org/10.1016/j.anucene.2017.12.054 (2018)

Introduction

The Monte Carlo code MCS is under developement at Ulsan National Institute of Science and Technology (UNIST) since 2013. The target of MCS is to solve complex whole-core problems with high-fidelity and high-performance, through the use of multi-physics coupling with thermal-hydraulic and fuel performance codes, On-The-Fly Doppler broadening of neutron cross-sections and depletion module. Basic capabilities of MCS include treatment of 3D whole core geometry with universe and lattice and neutron physics treatment with probability-table, free-gas treatment, S(a,b) and Doppler broadening Rejection Correction.

Overview

Monte Carlo Code MCS
• Language: Fortran 2003
• Purpose
– Large Scale Reactor Analysis with accelerated Monte Carlo simuation
– University research: MC methodology development, advanced reactor design
• General 3-D geometry
• Nuclear Data
– ENDF-B/VII.0 and ENDF-B/VII.1
– Continuous energy and multi-group
– Double indexing method
• Physics
– Resonance upscattering (DBRC, FESK)
– Probability table method

- S(α,β)
– On the fly Doppler broadening
– CTF Coupling
• Acceleration
– MOC and MC Hybrid solver
– Modified power iteration
– Wielandt method
– CMFD
• Prallelism
– Parallel fission bank
• Depletion
– CRAM , MEM, Krylov Subspace