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Michael S. Triantafyllou. Patrikalakis, Alexander Marinos Charles Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science 2011-03-07T15:16:16Z 2011-03-07T15:16:16Z 2010 2010 http://hdl.handle.net/1721.1/61567 703263028 Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2010. Cataloged from PDF version of thesis. Includes bibliographical references (p. 95-96). In this thesis, I design and evaluate methods to optimize the visualization of vortex-induced vibration (VIV) in marine risers. VIV is vibration experienced by marine risers in offshore drilling platforms due to ocean current flows, and appears to be perpendicular to the direction of such flows. VIV causes oil companies large capital losses, supply chain disruption, and environmental and brand name damage. For these reasons, both researchers and manufacturers try to improve their models of VIV, while creating risers more resilient to it. The first step to understanding VIV is rapid visualization, ie. the ability to efficiently visualize large amounts of simulated and field data. In this thesis, I evaluate high and low level heuristics that optimize the run-time performance of applications by taking advantage of 64 -bit machines with large memory stores. Such heuristics include the introduction of object-oriented programming (OOP) with classes, dynamic binary loading, and source code management. I demonstrate that using these techniques allows speedups of many orders of magnitude, depending on the type of optimization and the structure of the input data. Finally, I reengineer an existing collection of disparate visualizations to take advantage of these heuristics, and achieve a run-time speedup of two orders of magnitude in most visualizations. by Alexander Marinos Charles Patrikalakis. M.Eng. 96 p. eng Massachusetts Institute of Technology M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission. http://dspace.mit.edu/handle/1721.1/7582 Electrical Engineering and Computer Science. Visualization of vibration experienced in offshore platforms Thesis application/pdf Publication unknown unknown <Publication xmlns="https://www.openaire.eu/cerif-profile/1.1/" id="fec4a142-925e-4a47-917a-fcf8be9cce15"> <Type xmlns="https://www.openaire.eu/cerif-profile/vocab/COAR_Publication_Types">http://purl.org/coar/resource_type/c_1843</Type> <Language>eng</Language> <Title>Visualization of vibration experienced in offshore platforms</Title> <PublishedIn> <Publication> </Publication> </PublishedIn> <PublicationDate>2010</PublicationDate> <Authors> <Author> <DisplayName>Patrikalakis, Alexander Marinos Charles</DisplayName> <Affiliation> <OrgUnit> </OrgUnit> </Affiliation> </Author> </Authors> <Editors> </Editors> <Publishers> <Publisher> <DisplayName>Massachusetts Institute of Technology</DisplayName> <OrgUnit /> </Publisher> </Publishers> <License>http://dspace.mit.edu/handle/1721.1/7582</License> <Keyword>Electrical Engineering and Computer Science.</Keyword> <Abstract>In this thesis, I design and evaluate methods to optimize the visualization of vortex-induced vibration (VIV) in marine risers. VIV is vibration experienced by marine risers in offshore drilling platforms due to ocean current flows, and appears to be perpendicular to the direction of such flows. VIV causes oil companies large capital losses, supply chain disruption, and environmental and brand name damage. For these reasons, both researchers and manufacturers try to improve their models of VIV, while creating risers more resilient to it. The first step to understanding VIV is rapid visualization, ie. the ability to efficiently visualize large amounts of simulated and field data. In this thesis, I evaluate high and low level heuristics that optimize the run-time performance of applications by taking advantage of 64 -bit machines with large memory stores. Such heuristics include the introduction of object-oriented programming (OOP) with classes, dynamic binary loading, and source code management. I demonstrate that using these techniques allows speedups of many orders of magnitude, depending on the type of optimization and the structure of the input data. Finally, I reengineer an existing collection of disparate visualizations to take advantage of these heuristics, and achieve a run-time speedup of two orders of magnitude in most visualizations.</Abstract> <Access xmlns="http://purl.org/coar/access_right" > </Access> </Publication>