Nuclear Engineering and Technology

Korean Nuclear Society (한국원자력학회)
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Real variance estimation in iDTMC-based depletion analysis

  • Inyup Kim (Department of Nuclear & Quantum Engineering, Korea Advanced Institute of Science and Technology) ;
  • Yonghee Kim (Department of Nuclear & Quantum Engineering, Korea Advanced Institute of Science and Technology)
  • Received : 2023.05.02
  • Accepted : 2023.07.31
  • Published : 2023.11.25
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Abstract

The Improved Deterministic Truncation of Monte Carlo (iDTMC) is a powerful acceleration and variance reduction scheme in the Monte Carlo analysis. The concept of the iDTMC method and correlated sampling-based real variance estimation are briefly introduced. Moreover, the application of the iterative scheme to the correlated sampling is discussed. The iDTMC method is utilized in a 3-dimensional small modular reactor (SMR) model problem. The real variances of burnup-dependent criticality and power distribution are evaluated and compared with the ones obtained from 30 independent iDTMC calculations. The impact of the inactive cycles on the correlated sampling is also evaluated to investigate the consistency of the correlated sample scheme. In addition, numerical performances and sensitivity analysis on the real variance estimation are performed in view of the figure of merit of the iDTMC method. The numerical results show that the correlated sampling accurately estimates the real variances with high computational efficiencies.

Keywords

Acknowledgement

This research was supported by the National Research Foundation of Korea (NRF) Grant funded by the Korean Government (MSIP) (2021M2D2A2076383)

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