Results 11 to 20 of about 24,860,274 (294)
Model Order Reduction in Neuroscience [PDF]
CoRR, 2020 The human brain contains approximately $10^9$ neurons, each with approximately $10^3$ connections, synapses, with other neurons. Most sensory, cognitive and motor functions of our brains depend on the interaction of a large population of neurons. In recent years, many technologies are developed for recording large numbers of neurons either sequentially
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Model order reduction for gas and energy networks [PDF]
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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Model Order Reduction Technique Applied on Harmonic Analysis of a Submerged Vibrating Blade [PDF]
International Journal of Applied Mechanics and Engineering, 2019 As part of an ongoing study into hydropower runner failure, a submerged, vibrating blade is investigated both experimentally and numerically. The numerical simulations performed are fully coupled acoustic-structural simulations in ANSYS Mechanical.
E. Tengs +3 more
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MORLAB—The Model Order Reduction LABoratory [PDF]
, 2021 17 pages, 6 figures, 5 ...
Benner, P. ; https://orcid.org/0000-0003-3362-4103 +1 more
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, 2020 An increasing complexity of models used to predict real-world systems leads to the need for algorithms to replace complex models with far simpler ones, while preserving the accuracy of the predictions.
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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 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
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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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Randomized Local Model Order Reduction [PDF]
SIAM Journal on Scientific Computing, 2018 31 pages, 14 figures, 1 table, 1 ...
Andreas Buhr, Kathrin Smetana
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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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