Results 1 to 10 of about 4,793,633 (336)
Reduced order modeling and model order reduction for continuum manipulators: an overview [PDF]
Frontiers in Robotics and AI, 2023 Soft robot’s natural dynamics calls for the development of tailored modeling techniques for control. However, the high-dimensional configuration space of the geometrically exact modeling approaches for soft robots, i.e., Cosserat rod and Finite Element ...
S.M.H. Sadati +4 more
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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: A Comparison between Integer and Non-Integer Order Systems Approaches [PDF]
Entropy, 2019 In this paper, classical and non-integer model order reduction methodologies are compared. Non integer order calculus has been used to generalize many classical control strategies. The property of compressing information in modelling systems, distributed
Riccardo Caponetto +3 more
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Physics-informed two-tier neural network for non-linear model order reduction [PDF]
Advanced Modeling and Simulation in Engineering SciencesIn recent years, machine learning (ML) has had a great impact in the area of non-intrusive, non-linear model order reduction (MOR). However, the offline training phase often still entails high computational costs since it requires numerous, expensive ...
Yankun Hong, Harshit Bansal, Karen Veroy
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Model order reduction for left ventricular mechanics via congruency training. [PDF]
PLoS ONE, 2020 Computational models of the cardiovascular system and specifically heart function are currently being investigated as analytic tools to assist medical practice and clinical trials.
Paolo Di Achille +5 more
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GENETIC ALGORITHM-PID CONTROLLER FOR MODEL ORDER REDUCTION PANTOGRAPHCATENARY SYSTEM [PDF]
Applied Computer Science, 2021 Controlling the contact force between the pantograph and the catenary has come to be a requirement for improving the performances and affectivity of high-speed train systems Indeed, these performances can also significantly be decreased due to the fact ...
Nasir A. AL-AWAD +2 more
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Active-learning-based nonintrusive model order reduction
Data-Centric Engineering, 2023 Model order reduction (MOR) can provide low-dimensional numerical models for fast simulation. Unlike intrusive methods, nonintrusive methods are attractive because they can be applied even without access to full order models (FOMs).
Qinyu Zhuang +3 more
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Statistically Inspired Passivity Preserving Model Order Reduction
IEEE Access, 2023 The continuous scaling of the on-chip devices and interconnects increases the complexity of the design space and becomes a crucial factor in the fabrication of modern integrated circuits.
Namra Akram +3 more
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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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