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http://hdl.handle.net/1903/7699
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| Title: | Problems in Spatiotemporal Chaos |
| Authors: | Cornick, Matthew Tyler |
| Advisors: | Ott, Edward |
| Department/Program: | Physics |
| Type: | Dissertation |
| Sponsors: | Digital Repository at the University of Maryland
University of Maryland (College Park, Md.) |
| Keywords: | 0605
Physics, General
0605
Physics, General
rotation; magnetohydrodynamics; dynamo; state estimation; Rayleigh-Benard convection; Kalman filter |
| Issue Date: | 26-Nov-2007 |
| Abstract: | In this thesis we consider two problem areas involving spatiotemporally chaotic systems.
In Part I we investigate data assimilation techniques applicable to large systems. Data assimilation refers to the process of estimating a system's state from a time series of measurements (which may be noisy or incomplete) in conjunction with a model for the system's time evolution. However, for practical reasons, the high dimensionality of large spatiotemporally chaotic systems prevents the use of classical data assimilation techniques such as the Kalman filter. Here, a recently developed data assimilation method, the local ensemble transform Kalman Filter (LETKF), designed to circumvent this difficulty is applied to \RaBen convection, a prototypical spatiotemporally chaotic laboratory system. Using this technique we are able to extract the full temperature and velocity fields from a time series of shadowgraphs from a Rayleigh-Benard convection experiment. The process of estimating fluid ... |
| URI: | http://hdl.handle.net/1903/7699 |
| Appears in Collections: | Physics Theses and Dissertations
UM Theses and Dissertations
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Size | Format | No. of Downloads |
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| umi-umd-4976.pdf | | 2351Kb | Adobe PDF | 66 | View/Open |
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