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Reduced Order Modelling — Methods and Constraints
2004There 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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Reduced‐order modelling of an adaptive mesh ocean model
International Journal for Numerical Methods in Fluids, 2008AbstractA novel proper orthogonal decomposition (POD) model has been developed for use with an advanced unstructured mesh finite‐element ocean model, the Imperial College Ocean Model (ICOM, described in detail below), which includes many recent developments in ocean modelling and numerical analysis.
Fang, F. +6 more
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A reduced-order modeling of pattern formations.
CoRRChemical and biochemical reactions can exhibit surprisingly different behaviours from multiple steady-state solutions to oscillatory solutions and chaotic behaviours. Such behaviour has been of great interest to researchers for many decades. The Briggs-Rauscher, Belousov-Zhabotinskii and Bray-Liebhafsky reactions, for which periodic variations in ...
Hausenblas, Erika +1 more
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Reduced Order Models for Eigenvalue Problems
2006Two 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 Models for Coupled Problems
2010info:eu-repo/semantics ...
Filomeno Coelho, Rajan +5 more
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A POD-Galerkin reduced order model for a LES filtering approach
Journal of Computational Physics, 2021Annalisa Quaini, Gianluigi Rozza
exaly