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Title: Recursive Spoke Darts: Local Hyperplane Sampling for Delaunay and Voronoi Meshing in Arbitrary Dimensions.

Abstract

Abstract not provided.

Authors:
;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1408355
Report Number(s):
SAND2016-10992C
Journal ID: ISSN 1877-7058; 648746
DOE Contract Number:
AC04-94AL85000
Resource Type:
Conference
Resource Relation:
Journal Volume: 163; Conference: Proposed for presentation at the 25th International Meshing Roundtable held September 27-30, 2016 in Washington, DC.
Country of Publication:
United States
Language:
English

Citation Formats

Ebeida, Mohamed Salah, and Rushdi, Ahmad. Recursive Spoke Darts: Local Hyperplane Sampling for Delaunay and Voronoi Meshing in Arbitrary Dimensions.. United States: N. p., 2016. Web. doi:10.1016/j.proeng.2016.11.033.
Ebeida, Mohamed Salah, & Rushdi, Ahmad. Recursive Spoke Darts: Local Hyperplane Sampling for Delaunay and Voronoi Meshing in Arbitrary Dimensions.. United States. doi:10.1016/j.proeng.2016.11.033.
Ebeida, Mohamed Salah, and Rushdi, Ahmad. 2016. "Recursive Spoke Darts: Local Hyperplane Sampling for Delaunay and Voronoi Meshing in Arbitrary Dimensions.". United States. doi:10.1016/j.proeng.2016.11.033. https://www.osti.gov/servlets/purl/1408355.
@article{osti_1408355,
title = {Recursive Spoke Darts: Local Hyperplane Sampling for Delaunay and Voronoi Meshing in Arbitrary Dimensions.},
author = {Ebeida, Mohamed Salah and Rushdi, Ahmad},
abstractNote = {Abstract not provided.},
doi = {10.1016/j.proeng.2016.11.033},
journal = {},
number = ,
volume = 163,
place = {United States},
year = 2016,
month =
}

Conference:
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  • Computing a Voronoi or Delaunay tessellation from a set of points is a core part of the analysis of many simulated and measured datasets: N-body simulations, molecular dynamics codes, and LIDAR point clouds are just a few examples. Such computational geometry methods are common in data analysis and visualization; but as the scale of simulations and observations surpasses billions of particles, the existing serial and shared-memory algorithms no longer suffice. A distributed-memory scalable parallel algorithm is the only feasible approach. The primary contribution of this paper is a new parallel Delaunay and Voronoi tessellation algorithm that automatically determines which neighbormore » points need to be exchanged among the subdomains of a spatial decomposition. Other contributions include periodic and wall boundary conditions, comparison of our method using two popular serial libraries, and application to numerous science datasets.« less
  • A method for automatic generation of unstructured grids comprised of tetrahedra is discussed. Delaunay approach for tetrahedral grid generation is used. Particular attention is given to the boundary constraining problem. A simple and robust algorithm for the boundary constraining by successive use of boundary edge swapping, tetrahedral edge swapping and direct subdivision of tetrahedra is used. Small modifications allow to apply the method for viscous grid generation as well. Grid examples demonstrate efficiency of the method.
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