Results 81 to 90 of about 3,862 (118)

Reduced Order Modelling — Methods and Constraints

2004
There is growing attention for methods to reduce the state space dimension of a model, especially in the area of circuit simulation and electromagnetics. Applying these techniques to substructures which behave linearly or weakly non-linearly can dramatically speed up the computations in simulation of complex electronic structures.
Heres, P.J., Schilders, W.H.A.
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On Synthesis of Reduced Order Models

2011
A framework for model reduction and synthesis is presented, which enables the re-use of reduced order models in circuit simulation. Two synthesis techniques are considered for obtaining the circuit representation (netlist) of the reduced model: (1) by means of realizing the reduced transfer function and (2) by unstamping the reduced system matrices ...
Ionutiu, R., Rommes, J.
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Reduced-Order Modeling (ROM)

2016
Wie in Kapitel 4 erlautert, ist die Losung der Euler-Gleichungen abhangig von den gewahlten Anfangs- und Randbedingungen.
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Reduced Order Modeling

2023
Zulkeefal Dar, Joan Baiges, Ramon Codina
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Reduced-Order Models for Nonlinear Unsteady Aerodynamics

AIAA Journal, 2000
Two reduced-order modeling approaches for the evaluation of nonlinear aerodynamic forces based on CFD computations are presented. These reducedorder models (ROMs) provide a means for rapid calculation of frequency-domain generalized aerodynamic forces, which can be used in traditional flutter analysis scheme, to calculate flutter characteristics about ...
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Reduced-Order Modelling of Dispersion

2008
We present low complexity models for the transport of passive scalars for environmental applications. Multi-level analysis has been used with a reduction in dimension of the solution space at each level. Similitude solutions are used in a non-symmetric metric for the transport over long distances.
Jean-Marc Brun, Bijan Mohammadi
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Inverse Reduced-Order Modeling

2015
We propose a general probabilistic formulation of reduced-order modeling in the case the system state is hidden and characterized by some uncertainty. The objective is to integrate noisy and incomplete observations in the process of building a reduced-order model. We call this problematic inverse reduced-order modeling.
Héas, Patrick, Herzet, Cédric
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Reduced Order Models for Eigenvalue Problems

2006
Two main approaches are known for the reduced order modelling of linear time-invariant systems: Krylov subspace based and SVD based approximation methods. Krylov subspace based methods have large scale applicability, but do not have a global error bound.
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Reduced order and surrogate models for gravitational waves

Living Reviews in Relativity, 2022
Manuel Tiglio, Aaron Villanueva
exaly  

Reduced-Order Models

2017
Tomomichi Sugihara, Katsu Yamane
openaire   +1 more source