• Journal of the Institute of Electronics Engineers of Korea SC
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• v.40 no.5
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• pp.326-332
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• 2003

This paper deals with a model reduction for linear systems with time varying delayed states. A generalized controllability and observability gramians are defined and obtained by solving linear matrix inequalities. Using the generalized controllability and observability gramians, the balanced state space equation is realized. The reduced model can be obtained by truncating states in the balanced realization and the upper bound of model approximation error is also presented. In order to demonstrate efficacy of the suggested method, a numerical example is performed.

• KIEAE Journal
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• v.14 no.5
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• pp.123-130
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• 2014

In order for effective heat island reduction policies to be proposed, this research made use of the land usage and land coverage and Temperature of cities, Coordinate axis data within 500 meters of nationwide automatic weather stations (478 points) in order to analyze the correlation of summertime temperatures through multiple regression analysis. This research also developed a model and empirically analyzed the urban heat island reduction effect of factors that affect regional temperatures. Heat islands cause environment deterioration and therefore can harm citizens' health, and also affects the city's metabolism process. Thus in order to restrain regional temperature rises the conclusion was drawn that consideration to increase forest areas on part of land usage planning is needed. Appropriate policy measures to regulate traffic related factors are also needed to restrain regional temperature rises. In order for future heat island reduction this research proposes a way to set up more effective policies and urban sustainability improvement strategies, and is significant in that it makes use of detailed data such as land usage and land coverage, Temperature of cities, Coordinate axis in analyses.

• 제어로봇시스템학회:학술대회논문집
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• 1997.10a
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• pp.1766-1769
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• 1997

Fast and accurate distillation design requires a model that significantly reduces the problem size withour loss of accruacy is especially suitable for rela-time applicatoins. the reduced order model is obtained by use of Principal Component Anlysis(PCA). Then the extended Kalman filter and the Recursie Predictiuon Error(RPE) mehtod are appliced to identify the model parameters and the feed compostion form the measuremenets of the coumn. as a consequence it is found that the model reduction thechique can account for the dynamics of the rigorous distillation model and not only the model parameters, bu also the feed compostion can be identified efficiently. this technique is applied to industrial operation data verify the performance of reduced order model.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.23 no.2
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• pp.153-163
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• 2010

In this paper a frequency response analysis using Krylov subspace-based model reduction and its design sensitivity analysis with respect to design variables are presented. Since the frequency response and its design sensitivity information are necessary for a gradient-based optimization, problems of high computational cost and resource may occur in the case that frequency response of a large sized finite element model is involved in the optimization iterations. In the suggested method model order reduction of finite element models are used to calculate both frequency response and frequency response sensitivity, therefore one can maximize the speed of numerical computation for the frequency response and its design sensitivity. As numerical examples, a semi-monocoque shell and an array-type $4{\times}4$ MEMS resonator are adopted to show the accuracy and efficiency of the suggested approach in calculating the FRF and its design sensitivity. The frequency response sensitivity through the model reduction shows a great time reduction in numerical computation and a good agreement with that from the initial full finite element model.

• Journal of Korean Society for Atmospheric Environment
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• v.22 no.6
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• pp.912-921
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• 2006

This study examines greenhouse gas reduction potentials in cement manufacturing industry of Korea. An energy system model in the MARKAL (MARKet ALlocation) modeling framework was used in order to identify appropriate energy technologies and to quantify their possible implications In terms of greenhouse gas reduction. The model is characterized as mathematical tool for the long term energy system analysis provides an useful informations on technical assessment. Four scenarios are developed that covers the ti me span from 2000 to 2020. Being technology as a fundamental driving factor of the evolution of energy systems, it is essential to study the basic mechanisms of technological change and its role in developing more efficient, productive and clean energy systems. For this reasons, the learning curves on technologies for greenhouse gas reduction is specially considered. The analysis in this study shows that it is not easy to mitigate greenhouse gas with low cost in cement manufacturing industry under the current cap and trade method of Kyoto protocol.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2014.10a
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• pp.106-109
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• 2014

In order to obtain dynamic behaviors of complex structures, it demands large amounts computational cost and time to perform the numerical analysis. The model reduction method helps these problems by dividing the full model into primary and unnecessary parts. In this research, we perform the modal analysis using the dynamic substructuring method, which is one of the model reduction methods, in order to obtain the dynamic characteristics of the cylindrical structures efficiently. To select the master degrees of freedom (dofs), we consider the mode shapes of the cylindrical structures. And then, we identify the validity of the dynamic substructuring method by applying the method to the simple cylinder and core support barrel (CSB) which is one of the reactor internals with the cylindrical shape. The results demonstrate that the dynamic characteristics from the dynamic substructuring method are well matched with the original method.

• 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.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.64-68
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• 1996

In this note, we propose the discrete model reduction method over disc-type analytic domains. We define Hankel singular value over the disc that is mapped by standard bilinear mapping. And GSPA(generalized singular perturbation approximation) and DT(direct truncation) are generalized to GSPA and DT over a disc. Furthermore we show that the reduced order model over a smaller domain has a smaller L$_{\infty}$ norm error bound..

• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.11
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• pp.68-74
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• 1998

This paper deals with a model reduction problem for the linear systems with state delay. After defining the controllability/observability Gramians, the concept of a balanced model for the linear systems with state delay is introduced. Based on solutions of linear matrix inequalities, the model reduction method with guaranteed error bounds is developed. In order to demonstrate the efficacy of teh suggested method, a numerical example is also performed.

• International Journal of Control, Automation, and Systems
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• v.2 no.3
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• pp.384-389
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• 2004

Recently a method of model reduction for discrete systems has been proposed in the literature based on a new impulse response Gramian. In this method, the system matrix$A_r$ of a reduced model is computed by approximating the reduced-order impulse response Gramian. The remaining matrices $b_r$ and $c_r$ are obtained so that various initial Markov parameters and time-moments of the original system are preserved in the reduced model. In this paper a different approach is presented based on the recursive relationship among the impulse response Gramians.