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Showing 1 to 20 of 140 for “"Reduced Order Models"”.
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Large Eddy Simulation Reduced Order Models
… filtering to develop a large eddy simulation reduced order model (LES-ROM) framework for fluid flows. Proper orthogonal decomposition is utilized to extract the dominant spatial structures of the system. Within the general LES-ROM framework, two approaches are proposed to address the …
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Optimal reservoir management using adaptive reduced-order models
… to thousands of reservoir simulation runs. Reduced-order models (ROM) are considered powerful techniques to address computational challenges associated with reservoir management decision-making. In this sense, they represent perfect alternatives that trade off accuracy for speed in a …
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Dynamical Reduced-Order Models for High-Dimensional Systems
… the same: high dimensionality. The goal of reduced-order modeling is to reduce the number of unknowns in a system while minimizing the loss of accuracy in the approximate solution. Ideal model-order reduction techniques are optimal compromises between computational tractability and solution …
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Ensemble-based reservoir history matching using hyper-reduced-order models
… burden in reservoir flow modeling, a reduced-order modeling procedure based on hyper-reduction is presented. The procedure consists of three components: state reduction, constraint reduction, and nonlinearity treatment. State reduction based on proper orthogonal decomposition (POD) is …
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An augmented basis method for reduced order models of turbulent flow
Submission published under a 24 month embargo labeled 'U of I Access', the embargo will last until 2024-05-01
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Shape Matching for Reduced Order Models of High-Speed Fluid Flows
… Therefore, creating computationally inexpensive models that can capture complex fluid behaviors is a long-sought-after goal. As a result, methods to construct these reduced order models (ROMs) have seen increasing research interest. Still, parameter dependent high-speed flows that contain shock …
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Iterative Solution Methods for Reduced-Order Models of Parameterized Partial Differential Equations
… equations (PDEs) using techniques of reduced-order modeling. Parameterized equations of this type arise in numerous mathematical models. In some settings, e.g. sensitivity analysis, design optimization, and uncertainty quantification, it is necessary to compute discrete solutions of …
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Filter Based Stabilization Methods for Reduced Order Models of Convection-Dominated Systems
… stabilization methods to design new regularized reduced order models (ROMs) for under-resolved simulations of unsteady, nonlinear, convection-dominated systems. The new ROMs proposed are variable delta filtering applied to the evolve-filter-relax ROM (V-EFR ROM), variable delta filtering applied …
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Standing Balance of Legged Robots: Leveraging Reduced Order Models to Improve Balancing Performance
… we compared this proposed model to the existing models in push recovery simulations using two optimal control frameworks: trajectory optimization and a nonlinear model predictive control. We also examined the implementation of nonlinear model predictive controllers on a simulated one legged …
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Reduced order models for fluid-structure interaction systems by mixed finite element formulation
… frequencies. This formulation is introduced in order to compute the coupled frequencies without the contamination of nonphysical spurious non-zero frequencies. Furthermore, gravitational forces are introduced to include the coupled sloshing mode. In addition, u/p mixed formulation is the first …
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Stability and Bifurcation Analyses of Reduced-Order Models of Forced and Natural Circulation BWRs
It is hoped that results of this study are of value in demonstrating the safety features of current BWRs, and in improved design of future natural circulation BWR systems.
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Study of reduced order models for vortex-induced vibration and comparison with CFD results
… behaves when trying to control vibrations; a reduced order model may be an effective way to study the system dynamics. Developing a data driven model from simulation and/or experimental results can be difficult, but there are existing phenomenological models that attempt to describe VIV, …
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Reduced-Order Models for the Prediction of Unsteady Heat Release in Acoustically Forced Combustion
This work presents novel formulations for models describing acoustically forced combustion in three disjoint regimes; highly turbulent, laminar, and the moderately turbulent flamelet regime. Particular emphasis is placed on simplification of the models to facilitate analytical solutions while still …
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Development of reduced-order models of the ion impact distribution function in magnetized plasma sheaths
Submission original under an indefinite embargo labeled 'Open Access'. The submission was exported from vireo on 2023-09-01 without embargo terms
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Development of Reduced-Order Models for Lift and Drag on Oscillating Cylinders with Higher-Order Spectral Moments
… such a simulation. On the other hand, lower- or reduced-order models provide an alternative for determining structural response to forcing by fluid flow. The objective of this thesis is to provide a consistent approach for the development of reduced-order models for the lift and drag on …
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Modeling and Simulation of Nonlinearly Loaded Electromagnetic Systems via Reduced Order Models - A Case Study: Energy Selective Surfaces
L'abstract è presente nell'allegato / the abstract is in the attachment
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Inverse problems in thermoacoustics
… which are not readily approximated by models suitable to formulation within CFD. Hence, the methods discussed and developed in this book will likely be useful for a long time to come, in both research and practice. [. . . ] It seems to me that eventually the most effective ways of …
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Model order reduction for stochastic models of biomolecular systems with time-scale separation
… in the analysis of systems to obtain dynamical models with reduced dimensions. In deterministic systems, methods to obtain such reduced-order models are well defined by the singular perturbation or averaging techniques. However, model reduction of stochastic systems remains an ongoing area of …
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A hierarchy of microgrid models with some applications
… dissertation proposes a hierarchy of microgrid models that can be utilized for power system analysis and control design purposes. The microgrid models are classified according to time resolution and, consequently, according to complexity and computational cost as well. Our approach involves …
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Damage Reduction Strategies for a Falling Humanoid Robot
… These strategies were used on two and three link reduced order models to simulate a fall from standing height of a humanoid robot. The results of these simulations were then used on a full degree of freedom robot, Viginia Tech's humanoid robot ESCHER, to validate the efficacy of these strategies. …
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