DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry
Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013.
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| Format: | Thesis |
| Language: | eng |
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Massachusetts Institute of Technology
2014
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| Online Access: | http://hdl.handle.net/1721.1/85496 |
| _version_ | 1811080017597169664 |
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| author | Sharma, Samvaran |
| author2 | Russ Tedrake. |
| author_facet | Russ Tedrake. Sharma, Samvaran |
| author_sort | Sharma, Samvaran |
| collection | MIT |
| description | Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013. |
| first_indexed | 2024-09-23T11:24:22Z |
| format | Thesis |
| id | mit-1721.1/85496 |
| institution | Massachusetts Institute of Technology |
| language | eng |
| last_indexed | 2024-09-23T11:24:22Z |
| publishDate | 2014 |
| publisher | Massachusetts Institute of Technology |
| record_format | dspace |
| spelling | mit-1721.1/854962019-04-10T17:36:37Z DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry Utilitizing partially-observable fluid state for more efficient underwater control Dynamic Adaptive Real-Time Particle Image Velocimetry Sharma, Samvaran Russ Tedrake. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science. Electrical Engineering and Computer Science. Thesis: M. Eng., Massachusetts Institute of Technology, Department of Electrical Engineering and Computer Science, 2013. Cataloged from PDF version of thesis. Includes bibliographical references (pages 65-67). Particle Image Velocimetry (PIV) is a technique that allows for the detailed visualization of fluid flow. By performing computational analysis on images taken by a high-sensitivity camera that monitors the movement of laser-illuminated tracer particles over time, PIV is capable of producing a vector field describing instantaneous velocity measurements of the fluid captured in the field of view. Nearly all PIV implementations perform offline processing of the collected data, a feature that limits the scope of the applications of this technique. Recently, however, researchers have begun to explore the possibility of using FPGAs or PCs to greatly improve the efficiency of these algorithms in order to obtain real-time speeds for use in feedback loops. Such approaches are very promising and can help expand the use of PIV into previously unexplored fields, such as high performance Unmanned Aerial Vehicles (UAVs). Yet these real-time algorithms have the potential to be improved even further. This thesis outlines an approach to make real-time PIV algorithms more accurate and versatile in large part by applying principles from another emerging technique called adaptive PIV, and in doing so will also address new issues created from the conversion of traditional PIV to a real-time context. This thesis also documents the implementation of this Dynamic Adaptive Real- Time PIV (DARTPIV) algorithm on a PC with CUDA parallel computing, and its performance and results analyzed in the context of normal real-time PIV. by Samvaran Sharma. M. Eng. 2014-03-06T15:46:12Z 2014-03-06T15:46:12Z 2013 2013 Thesis http://hdl.handle.net/1721.1/85496 871001670 eng 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 67 pages application/pdf Massachusetts Institute of Technology |
| spellingShingle | Electrical Engineering and Computer Science. Sharma, Samvaran DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry |
| title | DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry |
| title_full | DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry |
| title_fullStr | DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry |
| title_full_unstemmed | DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry |
| title_short | DARTPIV : Dynamic Adaptive Real-Time Particle Image Velocimetry |
| title_sort | dartpiv dynamic adaptive real time particle image velocimetry |
| topic | Electrical Engineering and Computer Science. |
| url | http://hdl.handle.net/1721.1/85496 |
| work_keys_str_mv | AT sharmasamvaran dartpivdynamicadaptiverealtimeparticleimagevelocimetry AT sharmasamvaran utilitizingpartiallyobservablefluidstateformoreefficientunderwatercontrol AT sharmasamvaran dynamicadaptiverealtimeparticleimagevelocimetry |