Results 11 to 20 of about 1,373,381 (258)
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
doaj +1 more source
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.
openaire +2 more sources
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
doaj +1 more source
Model order reduction of solidification problems
8th European Congress on Computational Methods in Applied Sciences and Engineering, 2022 Advection driven problems are known to be difficult to model with a reduced basis because of a slow decay of the Kolmogorov $N$-width. This paper investigates how this challenge transfers to the context of solidification problems and tries to answer when and to what extend reduced order models (ROMs) work for solidification problems.
Florian Arbes +3 more
openaire +5 more sources
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
doaj +1 more source
Randomized Local Model Order Reduction [PDF]
SIAM Journal on Scientific Computing, 2018 31 pages, 14 figures, 1 table, 1 ...
Andreas Buhr, Kathrin Smetana
openaire +3 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source