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Parallel implicit Monte Carlo in C++

Description: The authors are developing a parallel C++ Implicit Monte Carlo code in the Draco framework. As a background and motivation for the parallelization strategy, they first present three basic parallelization schemes. They use three hypothetical examples, mimicking the memory constraints of the real world, to examine characteristics of the basic schemes. Next, they present a two-step scheme proposed by Lawrence Livermore National Laboratory (LLNL). The two-step parallelization scheme they develop is based upon LLNL`s two-step scheme. The two-step scheme appears to have greater potential compared to the basic schemes and LLNL`s two-step scheme. Lastly, they explain the code design and describe how the functionality of C++ and the Draco framework assist the development of a parallel code.
Date: December 31, 1998
Creator: Urbatsch, T.J. & Evans, T.M.
Partner: UNT Libraries Government Documents Department

An enhanced geometry-independent mesh weight window generator for MCNP

Description: A new, enhanced, weight window generator suite has been developed for MCNP{trademark}. The new generator correctly estimates importances in either an user-specified, geometry-independent orthogonal grid or in MCNP geometric cells. The geometry-independent option alleviates the need to subdivide the MCNP cell geometry for variance reduction purposes. In addition, the new suite corrects several pathologies in the existing MCNP weight window generator. To verify the correctness of the new implementation, comparisons are performed with the analytical solution for the cell importance. Using the new generator, differences between Monte Carlo generated and analytical importances are less than 0.1%. Also, assumptions implicit in the original MCNP generator are shown to be poor in problems with high scattering media. The new generator is fully compatible with MCNP`s AVATAR{trademark} automatic variance reduction method. The new generator applications, together with AVATAR, gives MCNP an enhanced suite of variance reduction methods. The flexibility and efficacy of this suite is demonstrated in a neutron porosity tool well-logging problem.
Date: December 31, 1997
Creator: Evans, T.M. & Hendricks, J.S.
Partner: UNT Libraries Government Documents Department

Milagro Version 2 An Implicit Monte Carlo Code for Thermal Radiative Transfer: Capabilities, Development, and Usage

Description: We have released Version 2 of Milagro, an object-oriented, C++ code that performs radiative transfer using Fleck and Cummings' Implicit Monte Carlo method. Milagro, a part of the Jayenne program, is a stand-alone driver code used as a methods research vehicle and to verify its underlying classes. These underlying classes are used to construct Implicit Monte Carlo packages for external customers. Milagro-2 represents a design overhaul that allows better parallelism and extensibility. New features in Milagro-2 include verified momentum deposition, restart capability, graphics capability, exact energy conservation, and improved load balancing and parallel efficiency. A users' guide also describes how to configure, make, and run Milagro2.
Date: February 15, 2006
Creator: Urbatsch, T.J. & Evans, T.M.
Partner: UNT Libraries Government Documents Department

1-D Equilibrium Discrete Diffusion Monte Carlo

Description: We present a new hybrid Monte Carlo method for 1-D equilibrium diffusion problems in which the radiation field coexists with matter in local thermodynamic equilibrium. This method, the Equilibrium Discrete Diffusion Monte Carlo (EqDDMC) method, combines Monte Carlo particles with spatially discrete diffusion solutions. We verify the EqDDMC method with computational results from three slab problems. The EqDDMC method represents an incremental step toward applying this hybrid methodology to non-equilibrium diffusion, where it could be simultaneously coupled to Monte Carlo transport.
Date: August 2000
Creator: Evans, T. M.; Urbatsch, T. J. & Lichtenstein, H.
Partner: UNT Libraries Government Documents Department

A microdosimetric study of {sup 10}B(n,{alpha}){sup 7}Li and {sup 157}Gd(n,{gamma}) reactions for neutron capture therapy

Description: This paper presents the microdosimetric analysis for the most interesting cell survival experiment recently performed at the Brookhaven National Laboratory (BNL). In this experiment, the cells were first treated with a gadolinium (Gd) labeled tumor-seeking boronated porphyrin (Gd-BOPP) or with BOPP alone, and then irradiated with thermal neutrons. The resulting cell survival curves indicate that the {sup 157}Gd(n,{gamma}) reactions is very effective in cell killing. The death of a cell treated with GD-BOPP were attributed to either the {sup 10}B(n,{alpha}) {sup 7}Li reactions or the {sup 157}Gd(n,{gamma}) reactions (or both). However, the quantitative relationship between the two types of reaction and the cell survival fraction was not clear. This paper presents the microdosimetric analysis for the BNL experiment based on the measured experimental parameters, and the results clearly suggest a quantitative relationship between the two types of reaction and the cell survival fraction. The results also suggest new research in Gadolinium neutron capture therapy (GDNCT) which may lead to a more practical modality than the boron neutron capture therapy (BNCT) for treating cancers.
Date: December 31, 1996
Creator: Wang, C.K.C.; Sutton, M.; Evans, T.M. & Laster, B.H.
Partner: UNT Libraries Government Documents Department

Geometrically-compatible 3-D Monte Carlo and discrete-ordinates methods

Description: This is the final report of a three-year, Laboratory Directed Research and Development (LDRD) project at the Los Alamos National Laboratory (LANL). The purpose of this project was two-fold. The first purpose was to develop a deterministic discrete-ordinates neutral-particle transport scheme for unstructured tetrahedral spatial meshes, and implement it in a computer code. The second purpose was to modify the MCNP Monte Carlo radiation transport code to use adjoint solutions from the tetrahedral-mesh discrete-ordinates code to reduce the statistical variance of Monte Carlo solutions via a weight-window approach. The first task has resulted in a deterministic transport code that is much more efficient for modeling complex 3-D geometries than any previously existing deterministic code. The second task has resulted in a powerful new capability for dramatically reducing the cost of difficult 3-D Monte Carlo calculations.
Date: December 31, 1998
Creator: Morel, J.E.; Wareing, T.A.; McGhee, J.M. & Evans, T.M.
Partner: UNT Libraries Government Documents Department