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Spectral analysis for convergence assessment in Monte Carlo criticality calculation

Ueki, Taro  

In Monte Carlo criticality calculation, the formation of a confidence interval is based on the central limit theorem for a series of tallies from generations in equilibrium. A fundamental assertion of the theorem is the convergence in distribution (CID) of an interpolated standardized time series (ISTS) of tallies. This article reports a spectral analysis approach to ISTS in order to assess the convergence of tallies in terms of CID. Numerical results are demonstrated for a preliminary model of uranium-concrete debris.

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