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AUTOMATED ADAPTIVE DATA CENTER GENERATION FOR MESHLESS METHODS

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Date Issued:
2006
Abstract/Description:
Meshless methods have recently received much attention but are yet to reach their full potential as the required problem setup (i.e. collocation point distribution) is still significant and far from automated. The distribution of points still closely resembles the nodes of finite volume-type meshes and the free parameter, c, of the radial-basis expansion functions (RBF) still must be tailored specifically to a problem. The localized meshless collocation method investigated requires a local influence region, or topology, used as the expansion medium to produce the required field derivatives. Tests have shown a regular cartesian point distribution produces optimal results, however, in order to maintain a locally cartesian point distribution a recursive quadtree scheme is herein proposed. The quadtree method allows modeling of irregular geometries and refinement of regions of interest and it lends itself for full automation, thus, reducing problem setup efforts. Furthermore, the construction of the localized expansion regions is closely tied up to the point distribution process and, hence, incorporated into the automated sequence. This also allows for the optimization of the RBF free parameter on a local basis to achieve a desired level of accuracy in the expansion. In addition, an optimized auto-segmentation process is adopted to distribute and balance the problem loads throughout a parallel computational environment while minimizing communication requirements.
Title: AUTOMATED ADAPTIVE DATA CENTER GENERATION FOR MESHLESS METHODS.
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Name(s): Mitteff, Eric, Author
Divo, Eduardo, Committee Chair
University of Central Florida, Degree Grantor
Type of Resource: text
Date Issued: 2006
Publisher: University of Central Florida
Language(s): English
Abstract/Description: Meshless methods have recently received much attention but are yet to reach their full potential as the required problem setup (i.e. collocation point distribution) is still significant and far from automated. The distribution of points still closely resembles the nodes of finite volume-type meshes and the free parameter, c, of the radial-basis expansion functions (RBF) still must be tailored specifically to a problem. The localized meshless collocation method investigated requires a local influence region, or topology, used as the expansion medium to produce the required field derivatives. Tests have shown a regular cartesian point distribution produces optimal results, however, in order to maintain a locally cartesian point distribution a recursive quadtree scheme is herein proposed. The quadtree method allows modeling of irregular geometries and refinement of regions of interest and it lends itself for full automation, thus, reducing problem setup efforts. Furthermore, the construction of the localized expansion regions is closely tied up to the point distribution process and, hence, incorporated into the automated sequence. This also allows for the optimization of the RBF free parameter on a local basis to achieve a desired level of accuracy in the expansion. In addition, an optimized auto-segmentation process is adopted to distribute and balance the problem loads throughout a parallel computational environment while minimizing communication requirements.
Identifier: CFE0001321 (IID), ucf:47032 (fedora)
Note(s): 2006-08-01
M.S.M.E.
Engineering and Computer Science, Department of Mechanical, Materials, and Aerospace Engineering
Masters
This record was generated from author submitted information.
Subject(s): meshless methods
radial-basis functions
quadtree
octree
parallel computing
Persistent Link to This Record: http://purl.flvc.org/ucf/fd/CFE0001321
Restrictions on Access: public
Host Institution: UCF

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