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Search results for: REDUCED ORDER SYSTEMS.
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Automated Reduced Model Order Selection
PublicationThis letter proposes to automate generation of reduced-order models used for accelerated -parameter computation by applying a posteriori model error estimators. So far,a posteriori error estimators were used in Reduced Basis Method (RBM) and Proper Orthogonal Decomposition (POD) to select frequency points at which basis vectors are generated. This letter shows how a posteriori error estimators can be applied to automatically select...
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Reduced order model of 2d system
PublicationA new method of modelling is developed for static and dynamic analysis of two-dimensional elastic bodies. In the analysis, an elastic body is divided into strips. For each one-dimensional strip the reduced modal model is build up. The modal model contains appropriate number of inputs and outputs to connect lumped interaction that occur between strips. Proposed method of modelling enables to obtain more accurate and more simple...
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Reduced-order models in the finite element analysis
PublicationA novel technique of incorporating macromodels into finite element electromagnetic analysis of waveguide components is presented. Macromodels are generated by using a model order reduction algorithm (ENOR), which results in significant decrease of the number of variables, that describe the computational region. Proposed technique allows for using a few independent macromodels as well as to duplicating one macromodel in many subregions...
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Reduced order models of refined Yee´s cells.
PublicationArtykuł opisuje nowe podejście zwiększające dokładność metody różnic skończonych za pomocą lokalnego zagęszczenia siatki. Obszar niewiele większy niż pojedyncza komórka Yee jest pokrywany gęstą siatką, a jej makromodel jest stworzony metodą redukcji rzędu modelu równań stanu w dziedzinie częstotliwości. Makromodele są użyte w metodach różnic skończonych w dziedzinie częstotliwości i czasu całej struktury. Inaczej niż w przypadku...
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Reduced order models in computational electromagnetics (in memory of Ruediger Vahldieck)
PublicationThis paper reviews research of Ruediger Vahldieck's group and the group at the Gdansk University of Technology in the area of model order reduction techniques for accelerating full-wave simulations. The applications of reduced order models to filter design as well as of local and nested(multilevel) macromodels for solving 3D wave equations and wave-guiding problems using finite difference and finite element methods are discussed.
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Regularized Local Multivariate Reduced-Order Models With Nonaffine Parameter Dependence
PublicationThis paper addresses a singular problem, not yet discussed in the literature, which occurs when parametric reduced-order models are created using a subspace projection approach with multiple concatenated projection bases. We show that this technique may lead to the appearance of localized artifacts in the frequency characteristics of a system, even when the reduced-order projection basis is rich enough to describe the original...
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Comparison of Compact Reduced Basis Method with Different Model Order Reduction Techniques
PublicationDifferent strategies suitable to compare the performance of different model order reduction techniques for fast frequency sweep in finite element analysis in Electromagnetics are proposed and studied in this work. A Frobenius norm error measure is used to describe how good job a reduced-order model is doing with respect to the true system response. In addition, the transfer function correct behavior is monitored by studying the...
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Fractional Order Models of Dynamic Systems
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Adaptive Sampling for Non-intrusive Reduced Order Models Using Multi-Task Variance
PublicationNon-intrusive reduced order modeling methods (ROMs) have become increasingly popular for science and engineering applications such as predicting the field-based solutions for aerodynamic flows. A large sample size is, however, required to train the models for global accuracy. In this paper, a novel adaptive sampling strategy is introduced for these models that uses field-based uncertainty as a sampling metric. The strategy uses...
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Experiments on Preserving Pieces of Information in a Given Order in Holographic Reduced Representations and the Continuous Geometric Algebra Model
PublicationGeometric Analogues of Holographic Reduced Representations (GAc, which is the continuous version of the previously developed discrete GA model) employ role-filler binding based on geometric products.Atomic objects are real-valued vectors in n-dimensional Euclidean space and complex statements belong to a hierarchy of multivectors. The property of GAc and HRR studied here is the ability to store pieces of information in a given...