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Genetic algorithm based tomographic flow visualization
| dc.creator | Lyons, Donald Paul | |
| dc.date.accessioned | 2012-06-07T22:49:33Z | |
| dc.date.available | 2012-06-07T22:49:33Z | |
| dc.date.created | 1997 | |
| dc.date.issued | 1997 | |
| dc.identifier.uri | https://hdl.handle.net/1969.1/ETD-TAMU-1997-THESIS-L96 | |
| dc.description | Due to the character of the original source materials and the nature of batch digitization, quality control issues may be present in this document. Please report any quality issues you encounter to digital@library.tamu.edu, referencing the URI of the item. | en |
| dc.description | Includes bibliographical references. | en |
| dc.description | Issued also on microfiche from Lange Micrographics. | en |
| dc.description.abstract | A new nonlinear tomographic flow visualization technique for use in limited data situations is developed using techniques from the emerging field of evolutionary computing. The new technique uses both pure and hybrid genetic algorithms from the field of evolutionary computing. For verification of the technique, both axisymmetric and asymmetric phantom density fields are tested for a limited number of projections under interferometric visualization. For the hybrid genetic algorithm, investigations are conducted to determine the appropriate degree of hybridization for use in flow visualization. This new method can provide an alternative to common reconstruction algorithms for use in limited data cases as well as provide a direct reconstruction method for data generated from nonlinear projection mechanisms. | en |
| dc.format.medium | electronic | en |
| dc.format.mimetype | application/pdf | |
| dc.language.iso | en_US | |
| dc.publisher | Texas A&M University | |
| dc.rights | This thesis was part of a retrospective digitization project authorized by the Texas A&M University Libraries in 2008. Copyright remains vested with the author(s). It is the user's responsibility to secure permission from the copyright holder(s) for re-use of the work beyond the provision of Fair Use. | en |
| dc.subject | mechanical engineering. | en |
| dc.subject | Major mechanical engineering. | en |
| dc.title | Genetic algorithm based tomographic flow visualization | en |
| dc.type | Thesis | en |
| thesis.degree.discipline | mechanical engineering | en |
| thesis.degree.name | M.S. | en |
| thesis.degree.level | Masters | en |
| dc.type.genre | thesis | en |
| dc.type.material | text | en |
| dc.format.digitalOrigin | reformatted digital | en |
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