Results 21 to 30 of about 24,860,274 (294)
POD-Based Model-Order Reduction for Discontinuous Parameters
Fluids, 2022 Reduced-order models (ROMs) based on proper orthogonal decomposition (POD) are widely used in industry. Due to the rigid requirements on the input data, these methods struggle with discontinuous parameters, e.g., optional rear spoiler on a car.
Niklas Karcher
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Model reduction based on regional pole and covariance equivalentrealizations [PDF]
, 1999 Copyright [1999] IEEE. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of Brunel University's products or services.
Wang, Z, Unbehauen, H
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Parametric Model Order Reduction Using pyMOR [PDF]
, 2021 9 pages, 6 ...
Mlinarić, P., Rave, S., Saak, J.
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Model Order Reduction by Using Improved Approximation Techniques
Scientific Journal of King Faisal University: Basic and Applied Sciences, 2020 A simplified approach for model order reduction (MOR) is presented in this article using the balanced singular perturbation approximation (BSPA) approach applicable to large-scale linear dynamical (LSLD) systems.
Santosh Kumar Suman, Awadhesh Kumar
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REDUCED-ORDER MODELLING OF PARAMETERIZED TRANSIENT FLOWS IN CLOSED-LOOP SYSTEMS [PDF]
EPJ Web of Conferences, 2021 In this paper, two Galerkin projection based reduced basis approaches are investigated for the reduced-order modeling of parameterized incompressible Navier-Stokes equations for laminar transient flows. The first approach solves only the reduced momentum
German Péter +3 more
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On the model order reduction of confined plasticity [PDF]
AIP Conference Proceedings, 2016 Forming processes usually involve irreversible plastic transformations. The calculation in that case becomes cumbersome when large parts and processes are considered. Recently Model Order Reduction techniques opened new perspectives for an accurate and fast simulation of mechanical systems. In some processes, plastic deformations remain very localized,
NASRI, Mohamed Aziz +5 more
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Efficient Wildland Fire Simulation via Nonlinear Model Order Reduction
Fluids, 2021 We propose a new hyper-reduction method for a recently introduced nonlinear model reduction framework based on dynamically transformed basis functions and especially well-suited for transport-dominated systems.
Felix Black +2 more
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Model-order reduction for hyperbolic relaxation systems
International Journal of Nonlinear Sciences and Numerical Simulation, 2022 Abstract We propose a novel framework for model-order reduction of hyperbolic differential equations. The approach combines a relaxation formulation of the hyperbolic equations with a discretization using shifted base functions. Model-order reduction techniques are then applied to the resulting system of coupled ordinary differential ...
Sara Grundel, Michael Herty
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Error estimation of a proper orthogonal decomposition reduced model of a permanent magnet synchronous machine [PDF]
, 2014 Model order reduction methods, like the proper orthogonal decomposition (POD), enable to reduce dramatically the size of a finite element (FE) model.
MAC, Hung +2 more
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Symplectic Model Order Reduction with Non-Orthonormal Bases
Mathematical and Computational Applications, 2019 Parametric high-fidelity simulations are of interest for a wide range of applications. However, the restriction of computational resources renders such models to be inapplicable in a real-time context or in multi-query scenarios.
Patrick Buchfink +2 more
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