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Adjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problems

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dc.contributor.authorAlexe, Mihaien
dc.contributor.committeechairSandu, Adrianen
dc.contributor.committeememberRibbens, Calvin J.en
dc.contributor.committeememberCao, Yangen
dc.contributor.committeememberde Sturler, Ericen
dc.contributor.committeememberBorggaard, Jeffrey T.en
dc.contributor.departmentComputer Scienceen
dc.date.accessioned2014-03-14T21:10:09Zen
dc.date.adate2011-04-14en
dc.date.available2014-03-14T21:10:09Zen
dc.date.issued2011-03-18en
dc.date.rdate2011-04-14en
dc.date.sdate2011-03-29en
dc.description.abstractAdaptivity in both space and time has become the norm for solving problems modeled by partial differential equations. The size of the discretized problem makes uniformly refined grids computationally prohibitive. Adaptive refinement of meshes and time steps allows to capture the phenomena of interest while keeping the cost of a simulation tractable on the current hardware. Many fields in science and engineering require the solution of inverse problems where parameters for a given model are estimated based on available measurement information. In contrast to forward (regular) simulations, inverse problems have not extensively benefited from the adaptive solver technology. Previous research in inverse problems has focused mainly on the continuous approach to calculate sensitivities, and has typically employed fixed time and space meshes in the solution process. Inverse problem solvers that make exclusive use of uniform or static meshes avoid complications such as the differentiation of mesh motion equations, or inconsistencies in the sensitivity equations between subdomains with different refinement levels. However, this comes at the cost of low computational efficiency. More efficient computations are possible through judicious use of adaptive mesh refinement, adaptive time steps, and the discrete adjoint method. This dissertation develops a complete framework for fully discrete adjoint sensitivity analysis and inverse problem solutions, in the context of time dependent, adaptive mesh, and adaptive step models. The discrete framework addresses all the necessary ingredients of a state–of–the–art adaptive inverse solution algorithm: adaptive mesh and time step refinement, solution grid transfer operators, a priori and a posteriori error analysis and estimation, and discrete adjoints for sensitivity analysis of flux–limited numerical algorithms.en
dc.description.degreePh. D.en
dc.identifier.otheretd-03292011-175733en
dc.identifier.sourceurlhttp://scholar.lib.vt.edu/theses/available/etd-03292011-175733/en
dc.identifier.urihttp://hdl.handle.net/10919/37515en
dc.publisherVirginia Techen
dc.relation.haspartAlexe_M_D_2011.pdfen
dc.rightsIn Copyrighten
dc.rights.urihttp://rightsstatements.org/vocab/InC/1.0/en
dc.subjectInverse problemsen
dc.subjectAdjoint Methoden
dc.subjectAdaptive Mesh Refinementen
dc.subjectAutomatic Differentiationen
dc.titleAdjoint-based space-time adaptive solution algorithms for sensitivity analysis and inverse problemsen
dc.typeDissertationen
thesis.degree.disciplineComputer Scienceen
thesis.degree.grantorVirginia Polytechnic Institute and State Universityen
thesis.degree.leveldoctoralen
thesis.degree.namePh. D.en

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