An Orthonormally Weighted Standardized Time Series for the Error Estimation of Local Tallies in Monte Carlo Criticality Calculation

An orthonormally weighted standardized time series (OWSTS) was investigated for the statistical error estimation of local tallies in Monte Carlo criticality calculation. Unlike the original implementation of a standardized time series, the computation of standard deviation via OWSTS can be made free of the grouping of iteration cycles into batches. The characteristic aspect of OWSTS is the application of an arbitrary number of weighting functions to a standardized series of tallies such that asymptotically independent and unbiased estimates are produced based on the statistics of Brownian bridge. In the present work, a trigonometric set of weighting functions is extended and applied to local power tallies in the three-dimensional model of a pressurized water reactor core. Numerical results demonstrate that the OWSTS error estimation is unbiased for a sufficiently large number of iteration cycles.