Results 21 to 30 of about 1,899,215 (187)
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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Linear Reduced-Order Model Predictive Control
IEEE Transactions on Automatic Control, 2022 Model predictive controllers use dynamics models to solve constrained optimal control problems. However, computational requirements for real-time control have limited their use to systems with low-dimensional models. Nevertheless, high-dimensional models arise in many settings, for example discretization methods for generating finite-dimensional ...
Joseph Lorenzetti +3 more
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Approximate deconvolution reduced order modeling [PDF]
Computer Methods in Applied Mechanics and Engineering, 2017 This paper proposes a large eddy simulation reduced order model(LES-ROM) framework for the numerical simulation of realistic flows. In this LES-ROM framework, the proper orthogonal decomposition(POD) is used to define the ROM basis and a POD differential filter is used to define the large ROM structures.
Xie, X. +3 more
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Data-driven reduced order modeling for mechanical oscillators using Koopman approaches
Frontiers in Applied Mathematics and Statistics, 2023 Data-driven reduced order modeling methods that aim at extracting physically meaningful governing equations directly from measurement data are facing a growing interest in recent years. The HAVOK-algorithm is a Koopman-based method that distills a forced,
Charlotte Geier +4 more
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Reduced order modeling of fluid flows using convolutional neural networks
Journal of Fluid Science and Technology, 2023 Application of machine learning is currently one of the hottest topics in the fluid mechanics field. While machine learning seems to have a great possibility, its limitations should also be clarified.
Koji FUKAGATA
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Reduced order modeling of delayed PEEC circuits [PDF]
, 2011 We propose a novel model order reduction technique that is able to accurately reduce electrically large systems with delay elements, which can be described by means of neutral delayed differential equations.
Antonini, Giulio +5 more
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Reduced-order modeling for unsteady transonic flows around an airfoil [PDF]
, 2008 High-transonic unsteady flows around an airfoil at zero angle of incidence and moderate Reynolds numbers are characterized by an unsteadiness induced by the von Kármán instability and buffet phenomenon interaction.
Bourguet, Rémi +2 more
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Computational fluid dynamics modeling of a wafer etch temperature control system
Digital Chemical Engineering, 2023 Next-generation etching processes for semiconductor manufacturing exploit the potential of a variety of operating conditions, including cryogenic conditions at which high etch rates of silicon and very low etch rates of the photoresist are achieved. Thus,
Henrique Oyama +5 more
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A Comparison of Data‐Driven Approaches to Build Low‐Dimensional Ocean Models
Journal of Advances in Modeling Earth Systems, 2021 We present a comprehensive inter‐comparison of linear regression (LR), stochastic, and deep‐learning approaches for reduced‐order statistical emulation of ocean circulation.
Niraj Agarwal +4 more
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Neural Network-Based Model Reduction of Hydrodynamics Forces on an Airfoil
Fluids, 2021 In this paper, an artificial neural network (ANN)-based reduced order model (ROM) is developed for the hydrodynamics forces on an airfoil immersed in the flow field at different angles of attack.
Hamayun Farooq +3 more
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