Results 11 to 20 of about 4,816,952 (284)
Adaptive Data-Driven Model Order Reduction for Unsteady Aerodynamics
Fluids, 2022 A data-driven adaptive reduced order modelling approach is presented for the reconstruction of impulsively started and vortex-dominated flows. A residual-based error metric is presented for the first time in the framework of the adaptive approach.
Peter Nagy, Marco Fossati
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Randomized model order reduction [PDF]
Advances in Computational Mathematics, 2019 Singular value decomposition (SVD) has a crucial role in model order reduction. It is often utilized in the offline stage to compute basis functions that project the high-dimensional nonlinear problem into a low-dimensionsl model which is, then, evaluated cheaply. It constitutes a building block for many techniques such as e.g.
Alla A., Kutz J. N.
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Model Order Reduction of Microactuators: Theory and Application
Actuators, 2023 This paper provides an overview of techniques of compact modeling via model order reduction (MOR), emphasizing their application to cooperative microactuators.
Arwed Schütz, Tamara Bechtold
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A partitioned model order reduction approach to rationalise computational expenses in nonlinear fracture mechanics. [PDF]
Comput Methods Appl Mech Eng, 2013 Kerfriden P +4 more
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State Residualisation and Kron Reduction for Model Order Reduction of Energy Systems
Applied Sciences, 2023 Greater numbers of power electronics (PEs) converters are being connected to energy systems due to the development of renewable energy sources, high-voltage transmission, and PE-interfaced loads. Given that power electronics-based devices and synchronous
Xianxian Zhao +4 more
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Parametric model-order-reduction development for unsteady convection
Frontiers in Physics, 2022 A time-averaged error indicator with POD-hGreedy is developed to drive parametric model order reduction (pMOR) for 2D unsteady natural convection in a high-aspect ratio slot parameterized with the Prandtl number, Rayleigh number, and slot angle with ...
Ping-Hsuan Tsai +2 more
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Model order reduction for gas and energy networks
Journal of Mathematics in Industry, 2021 To counter the volatile nature of renewable energy sources, gas networks take a vital role. But, to ensure fulfillment of contracts under these circumstances, a vast number of possible scenarios, incorporating uncertain supply and demand, has to be ...
Christian Himpe +2 more
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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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MORLAB—The Model Order Reduction LABoratory [PDF]
, 2021 17 pages, 6 figures, 5 ...
Benner, Peter, Werner, Steffen W. R.
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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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