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Title: Compact Mesh Generator

Abstract

The CMG is a small, lightweight, structured mesh generation code. It features a simple text input parser that allows setup of various meshes via a small set of text commands. Mesh generation data can be output to text, the silo file format, or the API can be directly queried by applications. It can run serially or in parallel via MPI. The CMG includes the ability to specify varius initial conditions on a mesh via mesh tags.

Authors:
;
Publication Date:
Research Org.:
Lawrence Livermore National Lab. (LLNL), Livermore, CA (United States)
Sponsoring Org.:
USDOE
OSTI Identifier:
1231046
Report Number(s):
CMG; 002152MLTPL00
UCRL-C0DE-233871
DOE Contract Number:
W-7405-Eng-48
Resource Type:
Software
Software Revision:
00
Software Package Number:
002152
Software Package Contents:
Media Directory; Software Abstract; Media includes 1 CD-ROM
Software CPU:
MLTPL
Open Source:
No
Source Code Available:
No
Related Software:
Generating the makefiles requires qmake, which is available freely from Trolltech, and is pre-installed on most systems. Generation of documentation requires doxygen.
Country of Publication:
United States

Citation Formats

Grover, Benjamin T., and Nissen, III, Walter I. Compact Mesh Generator. Computer software. Vers. 00. USDOE. 2 Feb. 2007. Web.
Grover, Benjamin T., & Nissen, III, Walter I. (2007, February 2). Compact Mesh Generator (Version 00) [Computer software].
Grover, Benjamin T., and Nissen, III, Walter I. Compact Mesh Generator. Computer software. Version 00. February 2, 2007.
@misc{osti_1231046,
title = {Compact Mesh Generator, Version 00},
author = {Grover, Benjamin T. and Nissen, III, Walter I.},
abstractNote = {The CMG is a small, lightweight, structured mesh generation code. It features a simple text input parser that allows setup of various meshes via a small set of text commands. Mesh generation data can be output to text, the silo file format, or the API can be directly queried by applications. It can run serially or in parallel via MPI. The CMG includes the ability to specify varius initial conditions on a mesh via mesh tags.},
doi = {},
year = {Fri Feb 02 00:00:00 EST 2007},
month = {Fri Feb 02 00:00:00 EST 2007},
note =
}

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  • Simplicial mesh shape-quality can be improved by optimizing an objective function based on tetrahedral shape measures. If the objective function is formulated in terms of all elements in a given mesh rather than a local patch, one is confronted with a large-scale, nonlinear, constrained numerical optimization problem. We investigate the use of six general-purpose state-of-the-art solvers and two custom-developed methods to solve the resulting large-scale problem. The performance of each method is evaluated in terms of robustness, time to solution, convergence properties, and scalability on several two- and three-dimensional test cases.

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