Results 31 to 40 of about 1,914,780 (311)
Induction motor speed control using reduced-order model
Automatika, 2018 Induction machines have a highly nonlinear model with only partial state information. The unavailability of all states and the presence of unknown disturbances make controller design and proving closed-loop stability challenging tasks.
A. Sabir, S. Ibrir
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Convolutional Autoencoders for Reduced-Order Modeling
CoRR, 2021 In the construction of reduced-order models for dynamical systems, linear projection methods, such as proper orthogonal decompositions, are commonly employed. However, for many dynamical systems, the lower dimensional representation of the state space can most accurately be described by a \textit{nonlinear} manifold.
Sreeram Venkat +2 more
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Wall‐based reduced‐order modelling [PDF]
International Journal for Numerical Methods in Fluids, 2015 SummaryIn this work, we propose a novel approach to model order reduction for incompressible fluid flows, which focuses on the spatio‐temporal description of the stresses on the surface of a body, that is, of the wall shear stress and of the wall pressure.
Lasagna, Davide, Tutty, Owen
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Fast prediction of the performance of the centrifugal pump based on reduced-order model
Energy Reports, 2023 In the present paper, the prediction of the performance of a centrifugal pump is investigated based on proper orthogonal decomposition (POD) reduced-order model (ROM).
Zhiguo Wei +4 more
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Reduced Order Modeling of an Industrial Feeder Model
IFAC Proceedings Volumes, 2003 Models of glaes furnaces are described by a set of nonlinear partial differential equâtioris which govern the mass, momentum and energy balances and a numberof non-linear functions of the independent scalais which describe the dependent variables like viscosities and densities in a fluid.
Astrid, P., Weiland, S., Twerda, A.
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Arnoldi model order reduction for electromagnetic wave scattering computation [PDF]
, 2007 This paper presents a model order reduction (MOR) algorithm for the volume integral equation formulation of electromagnetic wave scattering. We apply the Arnoldi algorithm to circumvent the computational complexity associated with the numerical solution ...
Bradley, Patrick +5 more
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Reduced-Order Model Development for Airfoil Forced Response
International Journal of Rotating Machinery, 2008 Two new reduced-order models are developed to accurately and rapidly predict geometry deviation effects on airfoil forced response. Both models have significant application to improved mistuning analysis.
Jeffrey M. Brown, Ramana V. Grandhi
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SolarPACES Conference Proceedings, 2023 We present a Reduced Order Method approach to the heat exchange and loses in a simulated 3D cavity of CSP tower receivers. We validate the method in a 2D Boussinesq model problem for natural convection monitoring temperature, pressure and velocity for ...
Juan Valverde +5 more
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Laguerre-Gram reduced-order modeling [PDF]
IEEE Transactions on Automatic Control, 2005 We present an efficient model reduction procedure based on the Laguerre description of the system to be approximated. Using a one-order operator defined in the Laplace domain we construct a pencil of functions and formulate the problem as the minimization of the L/sub /spl infin///sup 2/(/spl Ropf//sup +/) criterion. The use of a weight function in the
Ahmed Amghayrir +4 more
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Generative adversarial reduced order modelling
Scientific ReportsAbstractIn this work, we present GAROM, a new approach for reduced order modeling (ROM) based on generative adversarial networks (GANs). GANs attempt to learn to generate data with the same statistics of the underlying distribution of a dataset, using two neural networks, namely discriminator and generator.
Coscia, Dario +2 more
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