Results 31 to 40 of about 26,791,362 (287)
Two-to-one resonant multi-modal dynamics of horizontal/inclined cables. Part II : internal resonance activation, reduced-order models and nonlinear normal modes [PDF]
, 2007 Resonant multi-modal dynamics due to planar 2:1 internal resonances in the nonlinear, finite-amplitude, free vibrations of horizontal/inclined cables are parametrically investigated based on the second-order multiple scales solution in Part I [1].
Rega, Giuseppe, Srinil, Narakorn
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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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Causal and stable reduced-order model for linear high-frequency systems [PDF]
, 2008 With the ever-growing complexity of high-frequency systems in the electronic industry, formation of reduced-order models of these systems is paramount.
Deschrijver, D +6 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
doaj +1 more source
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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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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Determining Reduced Order Models for Optimal Stochastic Reduced Order Models
, 2015 The use of parameterized reduced order models(PROMs) within the stochastic reduced order model (SROM) framework is a logical progression for both methods. In this report, five different parameterized reduced order models are selected and critiqued against the other models along with truth model for the example of the Brake-Reuss beam. The models are: a
Matthew Bonney, Matthew Brake
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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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Finite element reduced order models for nonlinear vibrations of piezoelectric layered beams with applications to NEMS [PDF]
, 2012 This article presents a finite element reduced order model for the nonlinear vibrations of piezoelectric layered beams with application to NEMS. In this model, the geometrical nonlinearities are taken into account through a von Kármán nonlinear strain ...
O. Thomas +5 more
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Development of a Reduced Order Model for Fuel Burnup Analysis
Energies, 2020 Fuel burnup analysis requires a high computational cost for full core calculations, due to the amount of the information processed for the total reaction rates in many burnup regions. Indeed, they reach the order of millions or more by a subdivision into
Christian Castagna +4 more
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