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Massachusetts Institute of Technology

New methods for sensitivity analysis of chaotic dynamical systems

Abstract

dc:description.abstract

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.

Degree

thesis:*
Department dc:contributor.department
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2013

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Blonigan, Patrick Joseph
Advisor dc:contributor.advisor
  • Qiqi Wang.

Subjects

dc:subject × 1

Rights

dc:rights
Statement dc:rights
  • 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
http://hdl.handle.net/1721.1/82478
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/82478

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Blonigan, Patrick Joseph. New methods for sensitivity analysis of chaotic dynamical systems. Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/82478