Brian C. Kiedrowski

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

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.

GPU Acceleration of Mean Free Path Based Kernel Density Estimators in Monte Carlo Neutronics Simulations with Curvilinear Geometries

KDEs show potential reducing variance for global solutions (flux, reaction rates) when compared to histogram solutions.

Validation of MCNP6.1 for Criticality Safety of Pu-Metal, -Solution, and -Oxide Systems

Guidance is offered to the Los Alamos National Laboratory Nuclear Criticality Safety division towards developing an Upper Subcritical Limit (USL) for MCNP6.1 calculations with ENDF/B-VII.1 nuclear data for three classes of problems: Pu-metal, -solution, and -oxide systems. A benchmark suite containing 1,086 benchmarks is prepared, and a sensitivity/uncertainty (S/U) method with a generalized linear least squares (GLLS) data adjustment is used to reject outliers, bringing the total to 959 usable benchmarks. For each class of problem, S/U methods are used to select relevant experimental benchmarks, and the calculational margin is computed using extreme value theory. A portion of the margin of sub criticality is defined considering both a detection limit for errors in codes and data and uncertainty/variability in the nuclear data library. The latter employs S/U methods with a GLLS data adjustment to find representative nuclear data covariances constrained by integral experiments, which are then used to compute uncertainties in keff from nuclear data. The USLs for the classes of problems are as follows: Pu metal, 0.980; Pu solutions, 0.973; dry Pu oxides, 0.978; dilute Pu oxide-water mixes, 0.970; and intermediate-spectrum Pu oxide-water mixes, 0.953.

Calculating alpha Eigenvalues in a Continuous-Energy Infinite Medium with Monte Carlo

The {alpha} eigenvalue has implications for time-dependent problems where the system is sub- or supercritical. We present methods and results from calculating the {alpha}-eigenvalue spectrum for a continuous-energy infinite medium with a simplified Monte Carlo transport code. We formulate the {alpha}-eigenvalue problem, detail the Monte Carlo code physics, and provide verification and results. We have a method for calculating the {alpha}-eigenvalue spectrum in a continuous-energy infinite-medium. The continuous-time Markov process described by the transition rate matrix provides a way of obtaining the {alpha}-eigenvalue spectrum and kinetic modes. These are useful for the approximation of the time dependence of the system.

Testing for the photon doppler broadening data sampling bug in MCNP5/X

Los Alamos National Laboratory, an affirmative action/equal opportunity employer, is operated by the Los Alamos National Security, LLC for the National Nuclear Security Administration of the U.S. Department of Energy under contract DE-AC52-06NA25396. By acceptance of this article, the publisher recognizes that the U.S. Government retains a nonexclusive, royalty-free license to publish or reproduce the published form of this contribution, or to allow others to do so, for U.S. Government purposes. Los Alamos National Laboratory requests that the publisher identify this article as work performed under the auspices of the U.S. Department of Energy. Los Alamos National Laboratory strongly supports academic freedom and a researcher’s right to publish; as an institution, however, the Laboratory does not endorse the viewpoint of a publication or guarantee its technical correctness. Title: