• Smart Structures and Systems
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• v.18 no.1
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• pp.1-16
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• 2016

Model Order Reduction (MOR) denotes the theory by which one tries to catch a model of order lower than that of the real model. This is conveniently pursued in view of the design of an efficient structural control scheme, just passive within this paper. When the nonlinear response of the reference structural system affects the nature of the reduced model, making it dependent on the visited subset of the input-output space, standard MOR techniques do not apply. The mathematical theory offers some specific alternatives, which however involve a degree of sophistication unjustified in the presence of a few localized nonlinearities. This paper suggests applying standard MOR to the linear parts of the structural system, the interface remaining the original unreduced nonlinear components. A case study focused on the effects of a helicopter land crash is used to exemplify the proposal.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.2
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• pp.144-149
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• 2006

This paper deals with a balanced model reduction for uncertain nonlinear systems via T-S fuzzy approach. We define a generalized controllability/observability gramian and obtain a balanced state space model using generalized gramians which can be obtained from solutions of linear matrix inequalities. We present a balanced model reduction scheme by truncating not only state variables but also uncertain elements. An upper bound of the model reduction error will also be suggested. In order to demonstrate the efficacy of our method, a numerical example will be presented.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.30 no.4
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• pp.329-334
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• 2017

The structures, which are made up with the huge number of degrees-of-freedom and the assembly of substructures, have a great complexity. In order to increase the computational efficiency, the analysis models have to be simplified. Many substructuring techniques have been developed to simplify large-scale engineering problems. The techniques are very powerful for solving nonlinear problems which require many iterative calculations. In this paper, a modal derivatives-based model order reduction method, which is able to capture the stretching-bending coupling behavior in geometrically nonlinear systems, is adopted and investigated for its performance evaluation. The quadratic terms in nonlinear beam theory, such as Green-Lagrange strains, can be explained by the modal derivatives. They can be obtained by taking the modal directional derivatives of eigenmodes and form the second order terms of modal reduction basis. The method proposed is then applied to a co-rotational finite element formulation that is well-suited for geometrically nonlinear problems. Numerical results reveal that the end-shortening effect is very important, in which a conventional modal reduction method does not work unless the full model is used. It is demonstrated that the modal derivative approach yields the best compromised result and is very promising for substructuring large-scale geometrically nonlinear problems.

• Interaction and multiscale mechanics
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• v.6 no.4
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• pp.395-409
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• 2013

Molecular dynamics (MD) systems are highly nonlinear and nonlocal, and the conventional model order reduction methods are ineffective for MD systems. The RBF-POD method (Lee and Chen, 2013) employed a radial basis function (RBF) approximated potential energies and inter-atomic forces of MD systems under the framework of the proper orthogonal decomposition (POD) method for the reduced-order modeling of MD systems. In this work, we focus on the numerical procedures of the RBF-POD method and demonstrate how to apply this approach to the modeling of ds-DNA molecules under stretching and bending conditions.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.6
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• pp.1047-1054
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• 2007

This paper presents a high efficiency direct instantaneous torque control (DITC) of Switched Reluctance Motor(SRM) based on the nonlinear model. The DITC method can reduce the high inherent torque ripple of SRM drive system, but drive efficiency is somewhat low due to the high current and switching loss during commutations. In order to reduce a torque ripple, a fast torque reference trajectory is selected at every instantaneous rotor position. Based on the nonlinear model of SRM, the developing torque by one phase is fixed and the other phase is regulated for minimum switchings of phase switch and variation of torque. The switching during commutation can be reduced and fast commutation can be obtained in the proposed method. As a result, drive efficiency could be improved as well as torque ripple reduction. The validity of proposed method is verified by computer simulations and comparative experiments.

• Journal of Advanced Research in Ocean Engineering
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• v.1 no.3
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• pp.168-175
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• 2015

This study consists of an experimental investigation of the reduction of the second-order roll motion of a semi-submersible platform in head sea conditions by adding hull damping. The second-order heave drift force and roll drift moment are known to be the main triggers that induce the list angle (Hong et al., 2010). Hong et al. (2013) used numerical calculations to show the possibility of reducing the list angle by changing the pontoon shape and adding a damping device on the hull. One of their findings was that the reduction in the list angle due to the increase in pontoon surface damping was significant. A series of model tests were carried out with a 1:50 scaled model of semi-submersible at the KRISO wave basin. The experiments indicated that adding damping on the hull surface effectively suppressed the list angle.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Journal of applied mathematics & informatics
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• v.25 no.1_2
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• pp.293-304
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• 2007

In this paper, we present a Krylov subspace based projection method for reduced-order modeling of large scale bilinear multi-input multi-output (MIMO) systems. The reduced-order bilinear system is constructed in such a way that it can match a desired number of moments of multi-variable transfer functions corresponding to the kernels of Volterra series representation of the original system. Numerical examples report the effectiveness of this method.

• Proceedings of the KSR Conference
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• 2008.11b
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• pp.805-814
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• 2008

This study focused on the resilient modulus prediction model, which is the functions of mean effective principal stress and axial strain, for three types of railroad trackbed materials such as crushed stone, weathered soil, and crushed-rock soil mixture. The model is composed with the maximum Young's modulus and nonlinear values for higher strain in parallel with dynamic shear modulus. The maximum values is modeled by model parameters, $A_E$ and the power of mean effective principal stress, $n_E$. The nonlinear portion is represented by modified hyperbolic model, with the model parameters of reference strain, ${\varepsilon}_r$ and curvature coefficient, a. To assess the performance of the prediction models proposed herein, the elastic response of a test trackbed near PyeongTaek, Korea was evaluated using a 3-D nonlinear elastic computer program (GEOTRACK) and compared with measured elastic vertical displacement during the passages of freight and passenger trains. The material types of sub-ballasts are crushed stone and weathered granite soil, respectively. The calculated vertical displacements within the sub-ballasts are within the order of 0.6mm, and agree well with measured values with the reasonable margin. The prediction models are thus concluded to work properly in the preliminary investigation.

• Journal of Institute of Control, Robotics and Systems
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• v.10 no.12
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• pp.1148-1154
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• 2004

The goal of this paper is to verity that the gradual reduction of drug dose (GRDD), which has already been shown by authors to be effective for a simplified HIV infection model, still works for a more realistic model. While the simplified HIV infection model does not take into account an helper-independent CTL, the five state nonlinear model proposed by Wodarz describes the dynamics of both helper-dependent and helper-independent CTL in HIV infection. In this paper, it is shown that, by applying GRDD to Wodarz's five state HIV infection model, the state of HIV infected patient converges to that of non-progressor whose immune response is excited so that his symptom would not be developed into AIDS. Roughly speaking, GRDD is 'slow reduction of dose after the maximum dose for a certain period.' It turns out that an equilibrium representing non-progressor is locally asymptotically stable for the most values of drug dosage, which is required to hold in order to apply GRDD. Simulation results establish that GRDD is still considerably effective both for an AIDS patient and a patient who has been on HAART for a long time.