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dc.contributor.advisorQiqi Wang.en_US
dc.contributor.authorTalnikar, Chaitanya Anilen_US
dc.contributor.otherMassachusetts Institute of Technology. Computation for Design and Optimization Program.en_US
dc.date.accessioned2017-02-16T16:44:08Z
dc.date.available2017-02-16T16:44:08Z
dc.date.copyright2015en_US
dc.date.issued2015en_US
dc.identifier.urihttp://hdl.handle.net/1721.1/106965
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, School of Engineering, Center for Computational Engineering, Computation for Design and Optimization Program, 2015.en_US
dc.descriptionCataloged from PDF version of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 75-79).en_US
dc.description.abstractDesign optimization with high-fidelity turbulent flow simulations can be challenging due to noisy and expensive objective function evaluations. The noise decays slowly as computation cost increases, therefore is significant in most simulations. It is often unpredictable due to chaotic dynamics of turbulence, in that it can be totally different for almost identical simulations. This thesis presents a modified parallel Bayesian optimization algorithm designed for performing optimization with high-fidelity simulations. It strives to find the optimum in a minimum number of evaluations by judiciously exploring the design space. Additionally, to potentially augment the optimization algorithm with the availability of a gradient, a massively parallel discrete unsteady adjoint solver for the compressible Navier-Stokes equations is derived and implemented. Both the methods are demonstrated on a large scale transonic fluid flow problem in a turbomachinery component.en_US
dc.description.statementofresponsibilityby Chaitanya Anil Talnikar.en_US
dc.format.extent79 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectComputation for Design and Optimization Program.en_US
dc.titleMethods for design optimization using high fidelity turbulent flow simulationsen_US
dc.typeThesisen_US
dc.description.degreeS.M.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Computation for Design and Optimization Program.en_US
dc.identifier.oclc938678972en_US


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