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Kernel density estimated Monte Carlo global flux tallies

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Scopus citations

Abstract

The Kernel Density Estimator (KDE) is used to represent Monte Carlo (MC) tallies. Two new neutron flux estimators and their variances are developed, namely the KDE-collision and KDE-track-length. These new estimators are capable of estimating the flux at any point within a given domain without any bin structure. The strength of these two estimators is illustrated with numerical examples in 1D geometry. Convergence properties of the KDE estimators are discussed and the KDE estimators are compared with the Functional Expansion Tally (FET) and the conventional Histogram tally. The results show that the KDE tallies compare favorably with the FET and Histogram tallies with respect to accuracy and convergence rate.

Original languageEnglish
Title of host publicationAmerican Nuclear Society - International Conference on Mathematics, Computational Methods and Reactor Physics 2009, M and C 2009
Pages341-353
Number of pages13
StatePublished - 2009
Externally publishedYes
EventInternational Conference on Mathematics, Computational Methods and Reactor Physics 2009, M and C 2009 - Saratoga Springs, NY, United States
Duration: May 3 2009May 7 2009

Publication series

NameAmerican Nuclear Society - International Conference on Mathematics, Computational Methods and Reactor Physics 2009, M and C 2009
Volume1

Conference

ConferenceInternational Conference on Mathematics, Computational Methods and Reactor Physics 2009, M and C 2009
Country/TerritoryUnited States
CitySaratoga Springs, NY
Period05/3/0905/7/09

Keywords

  • Convergence of Monte Carlo tallies
  • KDE
  • Monte Carlo tallies

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