@inproceedings{9b41152dbff44d54aa292ac23663be51,
title = "Metrics for diagnosing undersampling in Monte Carlo tally estimates",
abstract = "This study explored the potential of using Markov chain convergence diagnostics to predict the prevalence and magnitude of biases due to undersampling in Monte Carlo eigenvalue and flux tally estimates. Five metrics were applied to two models of pressurized water reactor fuel assemblies and their potential for identifying undersampling biases was evaluated by comparing the calculated test metrics with known biases in the tallies. Three of the five undersampling metrics showed the potential to accurately predict the behavior of undersampling biases in the responses examined in this study.",
keywords = "Convergence metrics, Monte Carlo, SCALE, Tally biases, Undersampling",
author = "Perfetti, {Christopher M.} and Rearden, {Bradley T.}",
year = "2015",
language = "English",
series = "Mathematics and Computations, Supercomputing in Nuclear Applications and Monte Carlo International Conference, M and C+SNA+MC 2015",
publisher = "American Nuclear Society",
pages = "268--280",
booktitle = "Mathematics and Computations, Supercomputing in Nuclear Applications and Monte Carlo International Conference, M and C+SNA+MC 2015",
note = "Mathematics and Computations, Supercomputing in Nuclear Applications and Monte Carlo International Conference, M and C+SNA+MC 2015 ; Conference date: 19-04-2015 Through 23-04-2015",
}