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dc.contributor.advisor Sorensen, Danny C.
dc.creatorSun, Kai
dc.date.accessioned 2009-06-04T08:02:27Z
dc.date.available 2009-06-04T08:02:27Z
dc.date.issued 2006
dc.identifier.urihttps://hdl.handle.net/1911/17920
dc.description.abstract In this thesis, we propose a spatial domain decomposition method and model reduction techniques for the solution of linear-quadratic parabolic optimal control problems. Such problems arise directly from many applications such as the data assimilation, circuit design and oil reservoir modeling. The motivation for this work is threefold. First, we attempt to address the storage issue in numerically solving the parabolic optimal control problem. Secondly, spatial domain decomposition leads to parallelism. Therefore, data can be decomposed uniformly by assigning subdomains to each processor. Finally, for large-scale problems, the subproblems on the subdomains are still very large. Model reduction techniques applied to the subproblems are expected to dramatically reduce the size of the subproblems and save computational time.
dc.format.extent 44 p.
dc.format.mimetype application/pdf
dc.language.iso eng
dc.subjectMathematics
dc.title Spatial domain decomposition and model reduction for parabolic optimal control problems
dc.type.genre Thesis
dc.type.material Text
thesis.degree.department Mathematics
thesis.degree.discipline Natural Sciences
thesis.degree.grantor Rice University
thesis.degree.level Masters
thesis.degree.name Master of Arts
dc.identifier.citation Sun, Kai. "Spatial domain decomposition and model reduction for parabolic optimal control problems." (2006) Master’s Thesis, Rice University. https://hdl.handle.net/1911/17920.


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