New methods for sensitivity analysis of chaotic dynamical systems

Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013.

Bibliographic Details
Main Author: Blonigan, Patrick Joseph
Other Authors: Qiqi Wang.
Format: Thesis
Language:eng
Published: Massachusetts Institute of Technology 2013
Subjects:
Online Access:http://hdl.handle.net/1721.1/82478
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author Blonigan, Patrick Joseph
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author_facet Qiqi Wang.
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spelling mit-1721.1/824782019-04-11T11:31:50Z New methods for sensitivity analysis of chaotic dynamical systems Blonigan, Patrick Joseph Qiqi Wang. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Massachusetts Institute of Technology. Department of Aeronautics and Astronautics. Aeronautics and Astronautics. Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2013. 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. Cataloged from department-submitted PDF version of thesis Includes bibliographical references (p. 103-104). Computational methods for sensitivity analysis are invaluable tools for fluid dynamics research and engineering design. These methods are used in many applications, including aerodynamic shape optimization and adaptive grid refinement. However, traditional sensitivity analysis methods break down when applied to long-time averaged quantities in chaotic dynamical systems, such as those obtained from high-fidelity turbulence simulations. Also, a number of dynamical properties of chaotic systems, most notably the "Butterfly Effect", make the formulation of new sensitivity analysis methods difficult. This paper will discuss two chaotic sensitivity analysis methods and demonstrate them on several chaotic dynamical systems including the Lorenz equations and a chaotic Partial Differential Equation, the Kuramoto-Sivshinsky equation. The first method, the probability density adjoint method, forms a probability density function on the strange attractor associated with the system and uses its adjoint to find gradients. This was achieved using a novel numerical method in which the attractor manifold, instead of a region of phase space, is discretized. The second method, the Least Squares Sensitivity method, finds some "shadow trajectory" in phase space for which perturbations do not grow exponentially. This method is formulated as a quadratic programing problem with linear constraints. Several multigrid-in-time methods to solve the KKT system arising from this optimization problem will be discussed in depth. While the probability density adjoint method is better suited for smaller systems and reduced order models, least squares sensitivity analysis, solved with a multigrid-in-time method could be applied to higher dimensional systems such as high fidelity fluid flow simulations. by Patrick Joseph Blonigan. S.M. 2013-11-18T20:40:26Z 2013-11-18T20:40:26Z 2013 2013 Thesis http://hdl.handle.net/1721.1/82478 862226253 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 104 p. application/pdf Massachusetts Institute of Technology
spellingShingle Aeronautics and Astronautics.
Blonigan, Patrick Joseph
New methods for sensitivity analysis of chaotic dynamical systems
title New methods for sensitivity analysis of chaotic dynamical systems
title_full New methods for sensitivity analysis of chaotic dynamical systems
title_fullStr New methods for sensitivity analysis of chaotic dynamical systems
title_full_unstemmed New methods for sensitivity analysis of chaotic dynamical systems
title_short New methods for sensitivity analysis of chaotic dynamical systems
title_sort new methods for sensitivity analysis of chaotic dynamical systems
topic Aeronautics and Astronautics.
url http://hdl.handle.net/1721.1/82478
work_keys_str_mv AT bloniganpatrickjoseph newmethodsforsensitivityanalysisofchaoticdynamicalsystems