GPU Acceleration of Mean Free Path Based Kernel Density Estimators for Monte Carlo Neutronics Simulations

Burke, TImothy P.¹  Kiedrowski, Brian C.¹  Martin, William R.¹  Brown, Forrest B.¹ 

[1]Los Alamos National Lab. (LANL), Los Alamos, NM (United States)

关键词: MONTE CARLO METHOD;    MATHEMATICAL SOLUTIONS;    KERNELS;    MEAN FREE PATH;    COMPUTERIZED SIMULATION;    COMPARATIVE EVALUATIONS;    REACTION KINETICS;    CALCULATION METHODS;    NEUTRON TRANSPORT;    ACCURACY;    DATA COVARIANCES;    INTERFACES;    RESOLUTION;    TWO-DIMENSIONAL CALCULATIONS;    SLABS;    ONE-DIMENSIONAL CALCULATIONS;    ALGORITHMS;    OPTIMIZATION KDE;    OpenMC;   

DOI  :  10.2172/1226887
RP-ID  :  LA-UR--15-29020
PID  :  OSTI ID: 1226887
Others  :  TRN: US1500899

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来源: SciTech Connect

【 摘 要 】

Kernel Density Estimators (KDEs) are a non-parametric density estimation technique that has recently been applied to Monte Carlo radiation transport simulations. Kernel density estimators are an alternative to histogram tallies for obtaining global solutions in Monte Carlo tallies. With KDEs, a single event, either a collision or particle track, can contribute to the score at multiple tally points with the uncertainty at those points being independent of the desired resolution of the solution. Thus, KDEs show potential for obtaining estimates of a global solution with reduced variance when compared to a histogram. Previously, KDEs have been applied to neutronics for one-group reactor physics problems and fixed source shielding applications. However, little work was done to obtain reaction rates using KDEs. This paper introduces a new form of the MFP KDE that is capable of handling general geometries. Furthermore, extending the MFP KDE to 2-D problems in continuous energy introduces inaccuracies to the solution. An ad-hoc solution to these inaccuracies is introduced that produces errors smaller than 4% at material interfaces.