Results 31 to 40 of about 22,976 (267)
The Rapid Establishment of Large Wind Fields via an Inverse Process
Applied Sciences, 2019 Physical-approach-based wind forecasts have the merit of a heavily reduced uncertainty in predictions, but very often suffer from a prohibitively lengthy numerical computation time, if high spatial resolutions are required.
Shanxun Sun, Shi Liu, Guangchao Zhang
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Non-Intrusive Reduced-Order Modeling Based on Parametrized Proper Orthogonal Decomposition
Energies, 2023 A new non-intrusive reduced-order modeling method based on space-time parameter decoupling for parametrized time-dependent problems is proposed. This method requires the preparation of a database comprising high-fidelity solutions.
Teng Li +4 more
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Energy preserving model order reduction of the nonlinear Schr\"odinger equation [PDF]
, 2018 An energy preserving reduced order model is developed for two dimensional nonlinear Schr\"odinger equation (NLSE) with plane wave solutions and with an external potential.
Karasözen, Bülent, Uzunca, Murat
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Mathematics in Engineering, 2022 This work describes the implementation of a data-driven approach for the reduction of the complexity of parametrical partial differential equations (PDEs) employing Proper Orthogonal Decomposition (POD) and Gaussian Process Regression (GPR).
Giulio Ortali +2 more
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Energies, 2019 Though the proper orthogonal decomposition (POD) method has been widely adopted in flow analysis, few publications have systematically studied the influence of different POD processing methods on the POD results.
Lei Shi, Hongwei Ma, Lixiang Wang
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Modal Analysis of Fluid Flows: An Overview [PDF]
, 2017 Simple aerodynamic configurations under even modest conditions can exhibit complex flows with a wide range of temporal and spatial features. It has become common practice in the analysis of these flows to look for and extract physically important ...
Brunton, SL +9 more
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Density Matrix Renormalization for Model Reduction in Nonlinear Dynamics
, 2007 We present a novel approach for model reduction of nonlinear dynamical systems based on proper orthogonal decomposition (POD). Our method, derived from Density Matrix Renormalization Group (DMRG), provides a significant reduction in computational effort ...
A. C. Antoulas +9 more
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Asymptotic Stability of POD based Model Predictive Control for a semilinear parabolic PDE [PDF]
, 2013 In this article a stabilizing feedback control is computed for a semilinear parabolic partial differential equation utilizing a nonlinear model predictive (NMPC) method.
Alla, Alessandro, Volkwein, Stefan
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Analysis of POD and EPOD for Unsteady Flow Field of Wind Turbine Airfoil
Shanghai Jiaotong Daxue xuebao, 2022 The profile flow around the wind turbine airfoil has a significant impact on the overall performance and the noise of a wind turbine. In this paper, a combination method of large eddy simulation (LES) and the solution of Ffowcs Williams and Hawkings (FW ...
SUN Chong, TIAN Tian, ZHU Xiaocheng, DU Zhaohui
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A Randomized Proper Orthogonal Decomposition Method for Reducing Large Linear Systems [PDF]
, 2015 The proper orthogonal decomposition (POD) method is a powerful tool for reducing large data systems which can quickly overwhelm modern computing tools. In this thesis we provide a link between randomized projections and statistical methods by introducing
Marvin, Brad
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