• Journal of Korean Society of Coastal and Ocean Engineers
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• v.19 no.3
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• pp.205-212
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• 2007

Parabolic approximation wave models based on $Pad{\acute{e}}$ approximants are analyzed in order to calculate wave transformation. In this study a $Pad{\acute{e}}(2,2)$ parabolic approximation model is developed to increase the accuracy of computation in comparison with the existing models. Numerical studies on a constant sloping bed show that the new model proves to allow for much more successful treatment of large angles of incidence than is possible using the previously available models.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.25 no.9
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• pp.1423-1431
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• 2001

Based on the exponential intervening variable, a new two-point approximation method is presented. This introduces the shifting level into each exponential intervening variable to avoid the lack of def inition of the conventional exponential intervening variables due to zero-or negative-valued design variables. Then a new quadratic approximation whose Hessian matrix has only diagonal elements of different values is proposed in terms of these intervening variables. These diagonal elements are determined in a closed form that corrects the typical error in the approximate gradient of the TANA series due to the lack of definition of exponential type intervening variables and their incomplete second-order terms. Also, a correction coefficient is multiplied to the pre-determined quadratic term to match the value of approximate function with that of the previous point. Finally, in order to show the numerical performance of the proposed method, a sequential approximate optimizer is developed and applied to solve six typical design problems. These optimization results are compared with those of TANA-3. These comparisons show that the proposed method gives more efficient and reliable results than TANA-3.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.31 no.4
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• pp.490-495
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• 2007

This research aims to examine accuracy and efficiency of the first four moments corresponding to mean, standard deviation, skewness, and kurtosis, which are estimated by a function approximation moment method (FAMM). In FAMM, the moments are estimated from an approximating quadratic function of a system response function. The function approximation is performed on a specially selected experimental region for accuracy, and the number of function evaluations is taken equal to that of the unknown coefficients for efficiency. For this purpose, three error-minimizing conditions are utilized and corresponding canonical experimental regions constructed accordingly. An interpolation function is then obtained using a D-optimal design and then the first four moments of it are obtained as the estimates for the system response function. In order to verify accuracy and efficiency of FAMM, several non-linear examples are considered including a polynomial of order 4, an exponential function, and a rational function. The moments calculated from various coefficients of variation show very good accuracy and efficiency in comparison with those from analytic integration or the Monte Carlo simulation and the experimental design technique proposed by Taguchi and updated by D'Errico and Zaino.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.6
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• pp.3661-3666
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• 2015

The paper describes the integrated design system using MDO and approximation technique. In MDO related research, final target is an integrated and automated MDO framework systems. However, in order to construct the integrated design system, the prerequisite condition is how much save computational cost because of iterative process in optimization design and lots of data information in CAD/CAE integration. Therefore, this paper presents that an efficient approximation method, Adaptive approximation, is a competent strategy via MDO framework systems.

• Journal of the Korean Institute of Telematics and Electronics S
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• v.34S no.9
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• pp.50-59
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• 1997

This paper is on the generalized singular perturbation approximation (GSPA) preserving the discrete positive real property. We transform the discrete positive real(PR) system into a stochastically banlanced system and get the reduced order discrete system from the GSPA of the full order stochastically balanced system. eSPECIALLY, WHEN THE FREE PARAMETER OF THE gspa IS .+-.1, we show that the reduced order discrete system retains stability, minimality, and positive real and stochstically balancing properties. And we derived the .inf.-norm error bound with the reduced order discrete strictly positive real(SPR) system by the proposed method. Finally, we give an example to ascertain the properties of the proposed reduced order discrete system and to compare with the conventional methods.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.33 no.10
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• pp.396-401
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• 1984

This paper present a method of using simplified models for deriving suboptimal controllers to the original higher-order systems. Routh approximation method is a very useful technique for reducing the order of a linear systems. This method dose not require a knowlege of system eigenvalues and eigenvectors and possesses many desirable features such as preservation of reduced order model stability and minimum computational requirements. These properties are utilized to derive suboptimal controllers in this paper. In order to implement htese ocntrollers on the original system, the relationship between the state vectors of the original system and the reduced order models is required. A procedure fir evaluating an approximate aggregation matrix is also developed. A numerical example is given for the illustration of this method, shich is compared with the existing Model aggregation method in the resultant figures.

• Journal of the Korean Society of Fisheries and Ocean Technology
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• v.19 no.1
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• pp.71-78
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• 1983

A method is given for obtaining low-order models for a linear time-invariant system of high-order by minimizing a functional of the reduction error between the output response of the original system and the low-order model. The method is based on the Astrom's algorithm for the evaluation of complex integrals and the conjugate gradient method of Fletcher-Reeves. An example illustrating the application of this method is given for approximation of a 4-th order system to be used in the load frequency control of generator systems.

• Proceedings of the Korean Nuclear Society Conference
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• 1996.05a
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• pp.34-39
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• 1996

A consistent general order nodal method for solving the 3-D neutron diffusion equation in (x-y-z) geometry has ben derived by using a weighted integral technique and expanding the spatial variables by the Legendre orthogonal series function. The equation set derived can be converted into any order nodal schemes. It forms a compact system for general order of nodal moments. The method utilizes the analytic solutions of the transverse-integrated quasi -one dimensional equations and a consistent expansion for the spatial variables so that it renders the use of an approximation for the transverse leakages no necessary. Thus, we can expect extremely accurate solutions and the solution would converge exactly when the mesh width is decreased or the approximation order is increased since the equation set is consistent mathematically.

• Proceedings of the KSME Conference
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• 2004.11a
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• pp.567-572
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• 2004

In this research, a stable walking pattern generation method for a biped robot is presented. A biped robot is considered as constrained multibody system by several kinematic joints. The proposed method is based on the optimized polynomial approximation of the trunk motion along the moving direction. Foot motions can be designed according to the ground condition and walking speed. To minimize the deviation from the desired ZMP, the trunk motion is generated by the fifth order polynomial approximation. Walking simulation for a virtual biped robot is performed to demonstrate the effectiveness and validity of the proposed method. The method can be applied to the biped robot for stable walking pattern generation.

• Korean Management Science Review
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• v.15 no.2
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• pp.125-142
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• 1998

The aggregation on linear large-scale dynamic systems is examined in this paper and a "two-step" approach is proposed. In this procedure, the aggregated system consists of two subsystems. The first subsystem represents aggregation through the retainment of dominant eigenvalues of the original system, leading to a first approximation of the desired output of the original system. The purpose of augmenting it with a second subsystem is to provide an estimation of the error on the first approximation, thus permitting a second correction to the output approximation and resulting in an output approximation of greater accuracy. Optimization techniques are discussed for the determination of unknown parameters in the aggregated system. These techniques use minimization principles of certain suitable performance indices and are developed for both single input-single output and multiple input-multiple output system. Numerical examples illustrating these procedures are given and the results are compared with those obtained using existing methods. Finally, a pharmacokinetics problem is studied from the aggregation point of view.