Aspects of Reduced-Order Modeling of Turbulent Channel Flows: From Linear Mechanisms to Data-Driven Approaches

Aspects of Reduced-Order Modeling of Turbulent Channel Flows: From Linear Mechanisms to Data-Driven Approaches

<p>This thesis concerns three key aspects of reduced-order modeling for turbulent shear flows. They are linear mechanisms, nonlinear interactions, and data-driven techniques. Each aspect is explored by way of example through analysis of three different problems relevant to the broad area of tu...

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Bibliographic Details
Main Author: McMullen, Ryan Michael
Format: Others
Language:en
Published: 2020
Online Access:https://thesis.library.caltech.edu/13730/2/mcmullen_thesis_submitted.pdf
McMullen, Ryan Michael (2020) Aspects of Reduced-Order Modeling of Turbulent Channel Flows: From Linear Mechanisms to Data-Driven Approaches. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/wayx-eh75. https://resolver.caltech.edu/CaltechTHESIS:05282020-161209039 <https://resolver.caltech.edu/CaltechTHESIS:05282020-161209039>

Internet

https://thesis.library.caltech.edu/13730/2/mcmullen_thesis_submitted.pdf
McMullen, Ryan Michael (2020) Aspects of Reduced-Order Modeling of Turbulent Channel Flows: From Linear Mechanisms to Data-Driven Approaches. Dissertation (Ph.D.), California Institute of Technology. doi:10.7907/wayx-eh75. https://resolver.caltech.edu/CaltechTHESIS:05282020-161209039 <https://resolver.caltech.edu/CaltechTHESIS:05282020-161209039>

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