Real variance estimation in iDTMC-based depletion analysis

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 corre-lated 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.

Automated summary

The Improved Deterministic Truncation of Monte Carlo (iDTMC) is a powerful acceleration and variance reduction scheme in Monte Carlo analysis. In this paper, the concept of the iDTMC method and correlated sampling-based real variance estimation are introduced. The application of the iterative scheme to correlated sampling is also discussed. The iDTMC method is applied to a 3-dimensional small modular reactor (SMR) model problem, and the real variances of burnup-dependent criticality and power distribution are evaluated and compared.