Forrest B. Brown

Monte Carlo methods for radiation transport analysis on vector computers

The development of advanced computers with special capabilities for vectorized or parallel calculations demands the development of new calculational methods. The very nature of the Monte Carlo process precludes direct conversion of old (scalar) codes to the new machines. Instead, major changes in global algorithms and careful selection of compatible physics treatments are required. Recent results for Monte Carlo in multigroup shielding applications and in continuous-energy reactor lattice analysis have demonstrated that Monte Carlo methods can be successfully vectorized. The significant effort required for stylized coding and major algorithmic changes is worthwhile, and significant gains in computational efficiency are realized. Speedups of at least twenty to forty times faster than CDC-7600 scalar calculations have been achieved on the CYBER-205 without sacrificing the accuracy of standard Monte Carlo methods. Speedups of this magnitude provide reductions in statistical uncertainties for a given amount of computing time, permit more detailed and realistic problems to be analyzed, and make the Monte Carlo method more accessible to nuclear analysts. Following overviews of the Monte Carlo method for particle transport analysis and of vector computer hardware and software characteristics, both general and specific aspects of the vectorization of Monte Carlo are discussed. Finally, numerical results obtained from vectorized Monte Carlo codes run on the CYBER-205 are presented.

Lecture Notes on Criticality Safety Validation Using MCNP & Whisper

Training classes for nuclear criticality safety, MCNP documentation. The need for, and problems surrounding, validation of computer codes and data area considered first. Then some background for MCNP & Whisper is given--best practices for Monte Carlo criticality calculations, neutron spectra, S(α,β) thermal neutron scattering data, nuclear data sensitivities, covariance data, and correlation coefficients. Whisper is computational software designed to assist the nuclear criticality safety analyst with validation studies with the Monte Carlo radiation transport package MCNP. Whispers methodology (benchmark selection – Cks, weights; extreme value theory – bias, bias uncertainty; MOS for nuclear data uncertainty – GLLS) and usage are discussed.

Lecture Notes on Sensitivity-Uncertainty Based Nuclear Criticality Safety Validation

This document is a collection of lecture notes for sensitivity-uncertainty analysis of nuclear criticality safety validation. The use of and results from MCNP and Whisper are included.

Criticality Calculations with MCNP6 - Practical Lectures

These slides are used to teach MCNP (Monte Carlo N-Particle) usage to nuclear criticality safety analysts. The following are the lecture topics: course information, introduction, MCNP basics, criticality calculations, advanced geometry, tallies, adjoint-weighted tallies and sensitivities, physics and nuclear data, parameter studies, NCS validation I, NCS validation II, NCS validation III, case study 1 - solution tanks, case study 2 - fuel vault, case study 3 - BW Describe how cross section data impact Monte Carlo and deterministic codes; Describe the importance of validation of computer codes and how it is accomplished; Describe the methodology supporting Monte Carlo codes and deterministic codes; Describe pitfalls of Monte Carlo calculations; Discuss the strengths and weaknesses of Monte Carlo and Discrete Ordinants codes; The diffusion theory model is not strictly valid for treating fissile systems in which neutron absorption, voids, and/or material boundaries are present. In the context of these limitations, identify a fissile system for which a diffusion theory solution would be adequate.

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.

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: