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Title: Quicksilver: A Proxy App for the Monte Carlo Transport Code Mercury

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1393337
Report Number(s):
LLNL-CONF-734494
DOE Contract Number:
AC52-07NA27344
Resource Type:
Conference
Resource Relation:
Conference: Presented at: IEEE Cluster, Workshop on Representative Applications, Honolulu, HI, United States, Sep 05 - Sep 08, 2017
Country of Publication:
United States
Language:
English
Subject:
97 MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE

Citation Formats

Richards, D F, Bleile, R C, Brantley, P S, Dawson, S A, McKinley, M S, and O'Brien, M J. Quicksilver: A Proxy App for the Monte Carlo Transport Code Mercury. United States: N. p., 2017. Web.
Richards, D F, Bleile, R C, Brantley, P S, Dawson, S A, McKinley, M S, & O'Brien, M J. Quicksilver: A Proxy App for the Monte Carlo Transport Code Mercury. United States.
Richards, D F, Bleile, R C, Brantley, P S, Dawson, S A, McKinley, M S, and O'Brien, M J. Fri . "Quicksilver: A Proxy App for the Monte Carlo Transport Code Mercury". United States. doi:. https://www.osti.gov/servlets/purl/1393337.
@article{osti_1393337,
title = {Quicksilver: A Proxy App for the Monte Carlo Transport Code Mercury},
author = {Richards, D F and Bleile, R C and Brantley, P S and Dawson, S A and McKinley, M S and O'Brien, M J},
abstractNote = {},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Fri Jul 07 00:00:00 EDT 2017},
month = {Fri Jul 07 00:00:00 EDT 2017}
}

Conference:
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  • An update on the development and validation of the MERCURY Monte Carlo particle transport code is presented. MERCURY is a modern, parallel, general-purpose Monte Carlo code being developed at the Lawrence Livermore National Laboratory. During the past year, several major algorithm enhancements have been completed. These include the addition of particle trackers for 3-D combinatorial geometry (CG), 1-D radial meshes, 2-D quadrilateral unstructured meshes, as well as a feature known as templates for defining recursive, repeated structures in CG. New physics capabilities include an elastic-scattering neutron thermalization model, support for continuous energy cross sections and S ({alpha}, {beta}) molecular boundmore » scattering. Each of these new physics features has been validated through code-to-code comparisons with another Monte Carlo transport code. Several important computer science features have been developed, including an extensible input-parameter parser based upon the XML data description language, and a dynamic load-balance methodology for efficient parallel calculations. This paper discusses the recent work in each of these areas, and describes a plan for future extensions that are required to meet the needs of our ever expanding user base.« less
  • The new physics, algorithmic and computer science capabilities of the Mercury general-purpose Monte Carlo particle transport code are discussed. The new physics and algorithmic features include in-line energy deposition and isotopic depletion, significant enhancements to the tally and source capabilities, diagnostic ray-traced particles, support for multi-region hybrid (mesh and combinatorial geometry) systems, and a probability of initiation method. Computer science enhancements include a second method of dynamically load-balancing parallel calculations, improved methods for visualizing 3-D combinatorial geometries and initial implementation of an in-line visualization capabilities.
  • Two enhancements to the combinatorial geometry (CG) particle tracker in the Mercury Monte Carlo transport code are presented. The first enhancement is a hybrid particle tracker wherein a mesh region is embedded within a CG region. This method permits efficient calculations of problems with contain both large-scale heterogeneous and homogeneous regions. The second enhancement relates to the addition of parallelism within the CG tracker via spatial domain decomposition. This permits calculations of problems with a large degree of geometric complexity, which are not possible through particle parallelism alone. In this method, the cells are decomposed across processors and a particlesmore » is communicated to an adjacent processor when it tracks to an interprocessor boundary. Applications that demonstrate the efficacy of these new methods are presented.« less
  • Validation of the problem definition and analysis of the results (tallies) produced during a Monte Carlo particle transport calculation can be a complicated, time-intensive processes. The time required for a person to create an accurate, validated combinatorial geometry (CG) or mesh-based representation of a complex problem, free of common errors such as gaps and overlapping cells, can range from days to weeks. The ability to interrogate the internal structure of a complex, three-dimensional (3-D) geometry, prior to running the transport calculation, can improve the user's confidence in the validity of the problem definition. With regard to the analysis of results,more » the process of extracting tally data from printed tables within a file is laborious and not an intuitive approach to understanding the results. The ability to display tally information overlaid on top of the problem geometry can decrease the time required for analysis and increase the user's understanding of the results. To this end, our team has integrated VisIt, a parallel, production-quality visualization and data analysis tool into Mercury, a massively-parallel Monte Carlo particle transport code. VisIt provides an API for real time visualization of a simulation as it is running. The user may select which plots to display from the VisIt GUI, or by sending VisIt a Python script from Mercury. The frequency at which plots are updated can be set and the user can visualize the simulation results as it is running.« less