Blackbox Stencil Interpolation Method for model reduction
Name
824796573-MIT.pdf
Description
Full printable version
Size
1.01 MB
Format
Adobe PDF
Checksum (MD5)
ba9517064c2c0603e07ebf6255f08469
Author(s)
Chen, Han, S.M. Massachusetts Institute of Technology
Advisor(s)
Qiqi Wang.
Date Issued
2012
Publisher
Massachusetts Institute of Technology
Abstract
Model reduction often requires modifications to the simulation code. In many circumstances, developing and maintaining these modifications can be cumbersome. Non-intrusive methods that do not require modification to the source code are often preferred. This thesis proposed a new formulation of machine learning, Black-box Stencil Interpolation Method, for this purpose. It is a non-intrusive, data-oriented method to infer the underlying physics that governs a simulation, which can be combined with conventional intrusive model reduction techniques. This method is tested on several problems to investigate its accuracy, robustness, and applicabilities.
Description
Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2012.
Cataloged from department-submitted PDF version of thesis. This electronic version was submitted and approved by the author's academic department as part of an electronic thesis pilot project. The certified thesis is available in the Institute Archives and Special Collections.
Includes bibliographical references (p. 87-89).
Subjects
Aeronautics and Astronautics.
MIT Department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
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