Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 7 of 7 for “"Closure Modeling"”.
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Closure Modeling for Accelerated Multiscale Evolution of a 1-Dimensional Turbulence Model
Accelerating the simulation of turbulence to stationarity is a critical challenge in various engineering applications. This study presents an innovative equation-free multiscale approach combined with a machine learning technique to address this challenge in the context of the one-dimensional …
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Data-Driven Variational Multiscale Reduced Order Modeling of Turbulent Flows
… reduced order model (ROM) accuracy: (I) adding closure terms to the standard ROM; (II) using Lagrangian data to improve the ROM basis. Following strategy (I), we propose a new data-driven reduced order model (ROM) framework that centers around the hierarchical structure of the variational …
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Three-dimensional Integral Boundary Layer Method for Viscous Aerodynamic Analysis
… contributions in both the physical and numerical modeling aspects. First, this thesis presents novel closure modeling strategies for 3D IBL and develops a new set of closure models, which were lacking in previous 3D IBL methods. Original 3D boundary layer data sets have been generated and form the …
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Multiscale Modeling and Simulation of Turbulent Geophysical Flows
… in numerical weather prediction and climate modeling as well as in numerous critical areas and industries, such as agriculture, construction, tourism, transportation, weather-related disaster management, and sustainable energy technologies. Oceanic and atmospheric flows display an enormous …
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Reduced-Order Modeling of Complex Engineering and Geophysical Flows: Analysis and Computations
… low computational cost required by reduced-order modeling and the complexity of the targeted flows, appropriate closure modeling strategies need to be employed. In this dissertation, we put forth two new closure models for the proper orthogonal decomposition reduced-order modeling of structurally …
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Commutation Error in Reduced Order Modeling
We investigate the effect of spatial filtering on the recently proposed data-driven correction reduced order model (DDC-ROM). We compare two filters: the ROM projection, which was originally used to develop the DDC-ROM, and the ROM differential filter, which uses a Helmholtz operator to attenuate …
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Scientific Machine Learning for Dynamical Systems: Theory and Applications to Fluid Flow and Ocean Ecosystem Modeling
… deep learning framework to learn time-delayed closure parameterizations for missing dynamics. We find that our neural closure models increase the long-term predictive capabilities of existing models, and require smaller networks when using non-Markovian over Markovian closures. They efficiently …