2026-09-19T08:52:46Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/824812022-01-13T07:53:53Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Qiqi Wang.
Gomez, Steven A
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics.
Massachusetts Institute of Technology. Department of Aeronautics and Astronautics
2013-11-18T20:40:48Z
2013-11-18T20:40:48Z
2013
2013
http://hdl.handle.net/1721.1/82481
862228721
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. 85-86).
This thesis presents two approaches for efficiently computing the "climate" (long- time average) sensitivities for dynamical systems. Computing these sensitivities is essential to performing engineering analysis and design. The first technique is a novel approach to solving the "climate" sensitivity problem for periodic systems. A small change to the traditional adjoint sensitivity equations results in a method which can accurately compute both instantaneous and long-time averaged sensitivities. The second approach deals with the recently developed Least Squares Sensitivity (LSS) method. A multigrid algorithm is developed that can, in parallel, solve the discrete LSS system. This generic algorithm can be applied to ordinary differential equations such as the Lorenz System. Additionally, this parallel method enables the estimation of climate sensitivities for a homogeneous isotropic turbulence model, the largest scale LSS computation performed to date.
by Steven A. Gomez.
S.M.
86 p.
eng
Massachusetts Institute of Technology
M.I.T. theses are protected by
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http://dspace.mit.edu/handle/1721.1/7582
Aeronautics and Astronautics.
Parallel multigrid for large-scale least squares sensitivity
Parallel multigrid for large-scale LSS
Thesis
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<Abstract>This thesis presents two approaches for efficiently computing the "climate" (long- time average) sensitivities for dynamical systems. Computing these sensitivities is essential to performing engineering analysis and design. The first technique is a novel approach to solving the "climate" sensitivity problem for periodic systems. A small change to the traditional adjoint sensitivity equations results in a method which can accurately compute both instantaneous and long-time averaged sensitivities. The second approach deals with the recently developed Least Squares Sensitivity (LSS) method. A multigrid algorithm is developed that can, in parallel, solve the discrete LSS system. This generic algorithm can be applied to ordinary differential equations such as the Lorenz System. Additionally, this parallel method enables the estimation of climate sensitivities for a homogeneous isotropic turbulence model, the largest scale LSS computation performed to date.</Abstract>
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