Searched for: subject:"Proper%5C+orthogonal%5C+decomposition"
(1 - 18 of 18)
document
Alsayyari, F.S. (author), Perko, Z. (author), Tiberga, M. (author), Kloosterman, J.L. (author), Lathouwers, D. (author)
We present an approach to build a reduced-order model for nonlinear, time-dependent, parametrized partial differential equations in a nonintrusive manner. The approach is based on combining proper orthogonal decomposition (POD) with a Smolyak hierarchical interpolation model for the POD coefficients. The sampling of the high-fidelity model to...
journal article 2021
document
Alsayyari, F.S. (author)
Large-scale complex systems require high-fidelity models to capture the dynamics of the system accurately. For example, models of nuclear reactors capture multiphysics interactions (e.g., radiation transport, thermodynamics, heat transfer, and fluid mechanics) occurring at various scales of time (prompt neutrons to burn-up calculations) and...
doctoral thesis 2020
document
Alsayyari, F.S. (author), Tiberga, M. (author), Perko, Z. (author), Lathouwers, D. (author), Kloosterman, J.L. (author)
We use a novel nonintrusive adaptive Reduced Order Modeling method to build a reduced model for a molten salt reactor system. Our approach is based on Proper Orthogonal Decomposition combined with locally adaptive sparse grids. Our reduced model captures the effect of 27 model parameters on k<sub>eff</sub> of the system and the spatial...
journal article 2020
document
Rezaeiha, Abdolrahim (author), Kotsonis, M. (author)
Wind tunnel measurements are performed to investigate the potential for mitigation of aerodynamic load fluctuations on airfoils, as the main source of fatigue for wind turbines, using plasma actuators. The experiment consists of aerodynamic force measurements using six strain gauges and 2-component velocity measurements using particle image...
journal article 2020
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Alsayyari, F.S. (author), Perko, Z. (author), Lathouwers, D. (author), Kloosterman, J.L. (author)
Large-scale complex systems require high fidelity models to capture the dynamics of the system accurately. The complexity of these models, however, renders their use to be expensive for applications relying on repeated evaluations, such as control, optimization, and uncertainty quantification. Proper Orthogonal Decomposition (POD) is a...
journal article 2019
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Sajadi, B. (author), Wahls, S. (author), Hemert, Simon van (author), Belardinelli, P. (author), Steeneken, P.G. (author), Alijani, F. (author)
Despite numerous theoretical investigations on the mechanical properties of graphene, an accurate identification of its material behavior is still unattained. One hypothesis for this uncertainty is that modeling graphene as a static membrane cannot describe the strong coupling between mechanics and thermodynamics of this structure. Therefore,...
journal article 2019
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Gedikli, Ersegun Deniz (author), Nord, Torodd Skjerve (author), Hendrikse, H. (author), Ziemer, Gesa (author)
Pressures at the ice-structure interface during model-scale ice-structure interaction are often measured with tactile sensors. Resulting datasets usually include large volume of data along with some measurement error and noise; therefore, it is inherently hard to extract the hidden fluctuating pressures in the system. Identifying the...
journal article 2019
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Cheng, L. (author)
Modern computational and experimental techniques can represent the detailed dynamics of complex systems using large numbers of degrees of freedom. To facilitate human interpretation or the optimal design of control systems, however, reduced-order models (ROMs) are required. Conventional reduced-order modeling techniques, such as those based on...
doctoral thesis 2017
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Ghavamian, F. (author), Tiso, P. (author), Simone, A. (author)
We demonstrate a Model Order Reduction technique for a system of nonlinear equations arising from the Finite Element Method (FEM) discretization of the three-dimensional quasistatic equilibrium equation equipped with a Perzyna viscoplasticity constitutive model. The procedure employs the Proper Orthogonal Decomposition-Galerkin (POD-G) in...
journal article 2017
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Jansen, J.D. (author), Durlofsky, L.J. (author)
Many aspects of reservoir management can be expected to benefit from the application of computational optimization procedures. The focus of this review paper is on well control optimization, which entails the determination of well settings, such as flow rates or bottom hole pressures, that maximize a particular objective function. As is the case...
journal article 2016
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Violato, D.V. (author)
To meet the increasingly stringent noise regulation, aircraft manufacturers are searching for solutions to jet noise. This, which constitutes a significant amount of the total noise emitted by civil aircrafts, is generated by the mixing processes between the exhaust flow leaving the engine and the atmosphere. A detailed understanding of such...
doctoral thesis 2013
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Kaleta, M.P. (author), Hanea, R.G. (author), Heemink, A.W. (author), Jansen, J.D. (author)
Gradient-based history matching algorithms can be used to adapt the uncertain parameters in a reservoir model using production data. They require, however, the implementation of an adjoint model to compute the gradients, which is usually an enormous programming effort. We propose a new approach to gradient-based history matching which is based...
journal article 2010
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Humble, R.A. (author)
A fundamental experimental study is carried out to investigate the unsteady flow organization of an incident shock wave/turbulent boundary layer interaction at Mach 2.1. Planar and tomographic particle image velocimetry (PIV) are used in combination with data processing using the proper orthogonal decomposition (POD), complemented with hot-wire...
doctoral thesis 2009
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Van Doren, J. (author), Markovinovic, R. (author), Jansen, J.D. (author)
During the design of development concepts for the exploitation of oil and gas reservoirs, frequent use is made of numerical simulation of the flow of multi-phase fluids through porous rock. Recently, increased attention has been paid to systematic optimization of well positions and operating parameters (rates, pressures) over the life of the...
conference paper 2006
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Müller, H. (author), Volkwein, S. (author)
Proper orthogonal decomposition (POD) is a powerful technique for model reduction of linear and non-linear systems. It is based on a Galerkin type discretization with basis elements created from the system itself. In this work POD is used to derive low-order models for a so-called lambda-omega system that is a universal model to investigate two...
conference paper 2006
document
Van Doren, J. (author), Markovinovic, R. (author), Jansen, J.D. (author)
During the design of development concepts for the exploitation of oil and gas reservoirs, frequent use is made of numerical simulation of the flow of multi-phase fluids through porous rock. Recently, increased attention has been paid to systematic optimization of well positions and operating parameters (rates, pressures) over the life of the...
conference paper 2006
document
Moon, Y.J. (author), Bae, Y.M. (author), Cho, M.H. (author)
In the present study, aerodynamic noise from a forward-facing step is numerically investigated for Reynolds number based on the step height, Reh=8,000 and flow Mach number, M=0.03. A three-dimensional flow over the forward-facing step is calculated by the incompressible large eddy simulation (LES), while its acoustic field is solved by the...
conference paper 2006
document
Kahlbacher, M. (author), Volkwein, S. (author)
Proper orthogonal decomposition (POD) is a powerful technique for model reduction of linear and non-linear systems. It is based on a Galerkin type discretization with basis elements created from the system itself. In this work POD is applied to estimate scalar parameters in elliptic partial differential equations. The parameter estimation is...
conference paper 2006
Searched for: subject:"Proper%5C+orthogonal%5C+decomposition"
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