• Proceedings of the Korea Concrete Institute Conference
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• 2004.11a
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• pp.421-424
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• 2004

Model updating is a very active research field, in which significant efforts has been invested in recent years. Model updating methodologies are invariably successful when used on noise-free simulated data, but tend to be unpredictable when presented with real experimental data that are-unavoidably-corrupted with uncorrelated noise content. In this paper, Reanalysis using frequency response functions for correlating and updating dynamic systems is presented. A transformation matrix is obtained from the relationship between the complex and the normal frequency response functions of a structure. The transformation matrix is employed to calculate the modified damping matrix of the system. The modified mass and stiffness matrices are identified from the normal frequency response functions by using the least squares method. Full scale pseudo dynamic pier test is employed to illustrate the applicability of the proposed method. The result indicate that the damping matrix of correlated finite element model can be identified accurately by the proposed method. In addition, the robustness of the new approach uniformly distributed measurement noise is also addressed.

• Journal of the Korea Safety Management & Science
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• v.22 no.4
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• pp.45-52
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• 2020

Recently, a multi facility, multi product and multi period industrial problem has been widely investigated in Supply Chain Network(SCN). One of keys issues in the current SCN research area involves minimizing both production and distribution costs. This study deals with finding an optimal solution for minimizing the total cost of production and distribution problems in supply chain network. First, we presented an integrated mathematical model that satisfies the minimum cost in the supply chain. To solve the presented mathematical model, we used a genetic algorithm with an excellent searching ability for complicated solution space. To represent the given model effectively, the matrix based real-number coding schema is used. The difference rate of the objective function value for the termination condition is applied. Computational experimental results show that the real size problems we encountered can be solved within a reasonable time.

• Nuclear Engineering and Technology
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• v.53 no.8
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• pp.2616-2628
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• 2021

The results of effective irradiation swelling in a wide range of burnup levels are numerically obtained for an inert matrix fuel, which are verified with DART model. The fission gas swelling of fuel particles is calculated with a mechanistic model, which depends on the external hydrostatic pressure. Additionally, irradiation and thermal creep effects are included in the inert matrix. The effects of matrix creep strains, external hydrostatic pressure and temperature on the effective irradiation swelling are investigated. The research results indicate that (1) the above effects are coupled with each other; (2) the matrix creep effects at high temperatures should be involved; and (3) ranged from 0 to 300 MPa, a remarkable dependence of external hydrostatic pressure can be found. Furthermore, an explicit multi-variable mathematic model is established for the effective irradiation swelling, as a function of particle volume fraction, temperature, external hydrostatic pressure and fuel particle fission density, which can well reproduce the finite element results. The mathematic model for the current volume fraction of fuel particles can help establish other effective performance models.

• Health Policy and Management
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• v.10 no.4
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• pp.99-115
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• 2000

This study was conducted to get a resonable set of budget allocation to public health programs. Matrix Delphi technique was used to obtain the logic of study results and eventually to form a human model which could predict opinion of professionals on budget allocation. Thirty-two professionals in academic and governmental area responded to Delphi survey. Questionnaire was developed using matrix formation, and the matrix was formed by 6 decision criteria on budget allocation and 26 public health programs. The decision criteria are as following: size of problem(morbidity), severity of problem, social equity, importance of prevention, technical feasibility and efficiency of programs. Severity of problem dropped out of the model because it had significant correlation with the size of problem. A total score of each program was obtained by weighting the relative importance of each criteria which also were given by survey respondents. These total scores indicate that the most important public health program is vaccination for infants and children in terms of budget allocation. Monitoring communicable diseases, mental health program, and anti-smoking program are the next. In addition, respondents were asked of the desirable budget size of each program. The result was rearranged by multiple regression model using the scores of each decision criteria. In this process, the current budget size of central government was provided to the respondents, and included in the model. h set of desirable budgets modified using tile model was obtained. Considering the current size of budget, tile results of the model is very different from that of the total score. Managing dementia is ranked the first. Health promotion program for the elderly, rehabilitation of the disabled and monitoring communicable diseases are the next. The need to increase the budget of vaccination for the infants and children was not found as so high. The matrix structure in Delphi survey gave us the precise basis to make optimal decision, and made it possible to develop an opinion predicting model. However the plentifulness and diversity of professional opinions were not fully obtained due to the limited number of decision criteria.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.26 no.2
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• pp.99-112
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• 2013

This paper presents a subspace system identification for estimating the stiffness matrix and flexural rigidities of a shear building. System matrices are estimated by LQ decomposition and singular value decomposition from an input-output Hankel matrix. The estimated system matrices are converted into a real coordinate through similarity transformation, and the stiffness matrix is estimated from the system matrices. The accuracy and the stability of an estimated stiffness matrix depend on the size of the associated Hankel matrix. The estimation error curve of the stiffness matrix is obtained with respect to the size of a Hankel matrix using a prior finite element model of a shear building. The sizes of the Hankel matrix, which are consistent with a target accuracy level, are chosen through this curve. Among these candidate sizes of the Hankel matrix, more proper one can be determined considering the computational cost of subspace identification. The stiffness matrix and flexural rigidities are estimated using the Hankel matrix with the candidate sizes. The validity of the proposed method is demonstrated through the numerical example of a five-story shear building model with and without damage.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.19 no.10
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• pp.1021-1027
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• 2009

Finite element models of dynamic systems can be updated in two stages. In the first stage, mass and stiffness matrices are updated neglecting damping. In the second stage, a damping matrix is estimated with the mass and stiffness matrices fixed. Methods to estimate a damping matrix for this purpose are proposed in this paper. For a system with proportional damping, a damping matrix is estimated using the modal parameters extracted from the measured responses and the modal matrix calculated from the mass and stiffness matrices from the first stage. For a system with non-proportional damping, a damping matrix is estimated from the impedance matrix which is the inverse of the FRF matrix. Only one low or one column of the FRF matrix is measured, and the remaining FRFs are synthesized to obtain a full FRF matrix. This procedure to obtain a full FRF matrix saves time and effort to measure FRFs.

• Journal of the Korean Statistical Society
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• v.23 no.1
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• pp.167-178
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• 1994

To estimate coefficient matrix in autoregressive model, usually ordinary least squares estimator or unconditional maximum likelihood estimator is used. It is unknown that for univariate AR(p) model, unconditional maximum likelihood estimator gives better power property that ordinary least squares estimator in testing for unit root with mean estimated. When autoregressive model contains multiple unit roots and unconditional likelihood function is used to estimate coefficient matrix, the seperation of nonstationary part and stationary part of the eigen-values in the estimated coefficient matrix in the limit is developed. This asymptotic property may give an idea to test for multiple unit roots.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.27 no.8
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• pp.98-104
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• 2013

AC machines are in wide use in industry and d-q transformation from 3 phase of a, b, c is commonly used to analyze these kinds of machines. The equivalent circuits of d and q axis are, however, generally cross coupled and difficult to analyze. In this study, a modeling technique of AC machine including induction and PM synchronous motors using matrix vector is proposed. With that model, it can not only explain the AC machines physically but also make it simple to analyze them. The separating process of d and q components is not needed in this model and this model can be applied to analyze asymmetric motors like IPMSM machine. With this technique, the model becomes simple, easy to understand physically, and yields results that are the same as those from other models. These simulation results of the proposed model for induction motor are compared with those of other models to verify the method proposed.

• Journal of Institute of Control, Robotics and Systems
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• v.20 no.8
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• pp.822-827
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• 2014

This paper presents a robust observer-based output feedback control for stabilization of linear time invariant systems with polytopic uncertainties. To this end, this paper not only finds a robust observer gain but also suggests how to determine the model used in the observer, which is not obvious due to model uncertainties in the conventional observer design method. The robust observer gain and the observer model are selected in a way that the whole closed-loop is stable by solving LMIs and BMIs (Linear Matrix Inequalities and Bilinear Matrix Inequalities). A simulation example shows that the proposed robust observer-based output feedback control successfully leads to closed-loop stability.

• Journal of the Ergonomics Society of Korea
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• v.14 no.2
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• pp.33-39
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• 1995

The inverse Kinematics can be used for representing the motion of human body model. In order to find the final figure of the human body model with given target position, we can uwe the formula x=J .THETA. , where J is the Jacobian matrix of x=f( .THETA.), of the Inverse Kinematics. In this formula, f has so complicated form that it is difficult to calcuate the Jacobian matrix J by expanding all formulae exactly. In this paper, a numerical method that calculates the Jacobian matrix is proosed. The simulation results obtained by using the simple human model reprsent that the proposed. The simulation results obtained by using the simple human model represent that the proposed method is useful for generating the final figure of the body model.