{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/68407"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/68407","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Quantification of structural uncertainties in RANS turbulence models","abstract":"This thesis presents an approach for building a statistical model for the structural uncertainties in Reynolds averaged Navier-Stokes (RANS) turbulence models. This approach solves an inference problem by comparing the results of RANS calculations to direct numerical simulation. The adjoint method is used to efficiently solve an inverse problem to determine the RANS turbulent viscosity field that most accurately reproduces the mean flow field computed by direct numerical simulation. The discrepancy between the inferred turbulent viscosity and the turbulent viscosity predicted by RANS is modeled as a Gaussian random field. Finally, the uncertainty in the turbulent viscosity field is propagated to the quantities of interest. Results are first presented for turbulent flow through a straight channel. To model the uncertainty in more complex flows, the procedure is repeated for a collection of flows through randomly generated geometries.","abstract_html":"This thesis presents an approach for building a statistical model for the structural uncertainties in Reynolds averaged Navier-Stokes (RANS) turbulence models. This approach solves an inference problem by comparing the results of RANS calculations to direct numerical simulation. The adjoint method is used to efficiently solve an inverse problem to determine the RANS turbulent viscosity field that most accurately reproduces the mean flow field computed by direct numerical simulation. The discrepancy between the inferred turbulent viscosity and the turbulent viscosity predicted by RANS is modeled as a Gaussian random field. Finally, the uncertainty in the turbulent viscosity field is propagated to the quantities of interest. Results are first presented for turbulent flow through a straight channel. To model the uncertainty in more complex flows, the procedure is repeated for a collection of flows through randomly generated geometries.","abstract_has_math":false,"creators":["Dow, Eric Alexander"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics.","school":null,"contributors":[],"advisors":["Qiqi Wang."],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011","date_published":"2011","updated_at":"2026-07-22T22:21:03Z","subjects":["Aeronautics and Astronautics."],"languages":["eng"],"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."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/68407","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Qiqi Wang."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. 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To model the uncertainty in more complex flows, the procedure is repeated for a collection of flows through randomly generated geometries."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["S.M."]},{"key":"dc:title","label":"Title","values":["Quantification of structural uncertainties in RANS turbulence models"]}]}],"canonical_facts":{"dc:contributor.advisor":["Qiqi Wang."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Aeronautics and Astronautics."],"dc:creator":["Dow, Eric Alexander"],"dc:date.accessioned":["2012-01-12T19:25:00Z"],"dc:date.available":["2012-01-12T19:25:00Z"],"dc:date.issued":["2011"],"dc:description":["Thesis (S.M.)--Massachusetts Institute of Technology, Dept. of Aeronautics and Astronautics, 2011.","Cataloged from PDF version of thesis.","Includes bibliographical references (p. 69-70)."],"dc:description.abstract":["This thesis presents an approach for building a statistical model for the structural uncertainties in Reynolds averaged Navier-Stokes (RANS) turbulence models. This approach solves an inference problem by comparing the results of RANS calculations to direct numerical simulation. The adjoint method is used to efficiently solve an inverse problem to determine the RANS turbulent viscosity field that most accurately reproduces the mean flow field computed by direct numerical simulation. The discrepancy between the inferred turbulent viscosity and the turbulent viscosity predicted by RANS is modeled as a Gaussian random field. Finally, the uncertainty in the turbulent viscosity field is propagated to the quantities of interest. Results are first presented for turbulent flow through a straight channel. To model the uncertainty in more complex flows, the procedure is repeated for a collection of flows through randomly generated geometries."],"dc:description.degree":["S.M."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/68407"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"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. 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