• Proceedings of the Korean Geotechical Society Conference
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• 2009.03a
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• pp.1043-1052
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• 2009

To derive easily the coefficient of permeability from several other soil properties, the estimation model of coefficient of permeability was proposed using linear regression analysis. The coefficient of permeability is one of the major factors to evaluate the soil characteristics. The study area is located in Kangwon-do Pyeongchang-gun Jinbu-Myeon. Soil samples of 45 spots were taken from the study area and various soil tests were carried out in laboratory. After selecting the soil factor influenced by the coefficient of permeability through the correlation analysis, the estimation model of coefficient of permeability was developed using the linear regression analysis between the selected soil factor and the coefficient of permeability from permeability test. Also, the estimation model of coefficient of permeability was compared with the results from permeability test and empirical equation, and the suitability of proposed model was proved. As the result of correlation analysis between various soil factors and the coefficient of permeability using SPSS(statistical package for the social sciences), the largest influence factor of coefficient of permeability were the effective grain size, porosity and dry unit weight. The coefficient of permeability calculated from the proposed model was similar to that resulted from permeability test. Therefore, the proposed model can be used in case of estimating the coefficient of permeability at the same soil condition like study area.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.701-705
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• 2008

Design analysis and computer experiments (DACE) model is widely used to express efficiently the nonlinear responses in the field of engineering design. Kriging model, a DACE model, can approximately replace a simulation model that is very expensive or highly nonlinear. The kriging model is composed of the summation of a global model and a local model representing deviation from global model. The local model is determined by correlation coefficient of the pre-sampled points, where determination of the correct correlation coefficient has an effect on accuracy and robustness of the kriging model. Therefore, robustness of the correlation coefficient is explored with respect to degrees of the global model. Then we propose the range of correlation coefficient to make correct and robust kriging model and the influence of the correlation coefficients on the degrees of global model with respect to the nonlinearity of the pre-sampled responses.

• Journal of the Korean Data and Information Science Society
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• v.28 no.2
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• pp.461-471
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• 2017

In this paper we propose a feature selection method identifying important features in the semivarying coefficient model. One important issue in semivarying coefficient model is how to estimate the parametric and nonparametric components. Another issue is how to identify important features in the varying and the constant effects. We propose a feature selection method able to address this issue using generalized cross validation functions of the varying coefficient least squares support vector regression (LS-SVR) and the linear LS-SVR. Numerical studies indicate that the proposed method is quite effective in identifying important features in the varying and the constant effects in the semivarying coefficient model.

• Journal of Astronomy and Space Sciences
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• v.29 no.4
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• pp.363-374
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• 2012

This paper studies the problem of tracking a re-entry vehicle (RV) in order to predict its impact point on the ground. Re-entry target dynamics combined with super-high speed has a complex non-linearity due to ballistic coefficient variations. However, it is difficult to construct a database for the ballistic coefficient of a unknown vehicle for a wide range of variations, thus the reliability of target tracking performance cannot be guaranteed if accurate ballistic coefficient estimation is not achieved. Various techniques for ballistic coefficient estimation have been previously proposed, but limitations exist for the estimation of non-linear parts accurately without obtaining prior information. In this paper we propose the ballistic coefficient ${\beta}$ model-based interacting multiple model-extended Kalman filter (${\beta}$-IMM-EKF) for precise tracking of an RV. To evaluate the performance, other ballistic coefficient model based filters, which are gamma augmented filter, gamma bootstrapped filter were compared and assessed with the proposed ${\beta}$-IMM-EKF for precise tracking of an RV.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.37 no.2
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• pp.177-185
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• 2013

A new theoretical derailment coefficient model of wheel-climb derailment is proposed to consider the influence of wheel unloading. The derailment coefficient model is based on the theoretical derailment model of a wheelset that was developed to predict the derailment induced by train collisions. Presently, in domestic derailment regulations, a derailment coefficient of 0.8 is allowable using Nadal's formula, which is for a flange angle of $60^{\circ}$ and a friction coefficient of 0.3. However, theoretical studies focusing on different flange angles to justify the derailment coefficient of 0.8 have not been conducted. Therefore, this study theoretically explains a derailment coefficient of 0.8 using the proposed derailment coefficient model. Furthermore, wheel unloading of up to 50% is accepted without a clear basis. Accordingly, the correlation between a wheel unloading of 50% and a derailment coefficient of 0.8 is confirmed by using the proposed derailment coefficient model. Finally, the validity of the proposed derailment coefficient model is demonstrated through dynamic simulations.

• Journal of Korea Water Resources Association
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• v.37 no.12
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• pp.1055-1063
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• 2004

An unsteady flow model is developed that allows variable roughness coefficient for each computational point according to its spatial position and the discharge. A step function or a power function can be used for functional relation between the discharge and the Manning's roughness coefficient. The model is applied to the reach of the South Han River between the Chungju Dam and Paldang Dam, and model parameters are estimated by optimization. Estimated parameters of both the step function model and the Power function model show that Manning's roughness coefficient decreases as the discharge increases. This tendency is more noticeable for the upstream reach of Yeoju compared to the downstream reach. It turns out that the stages calculated by the variable roughness coefficient model agree better with the observed ones than those by the conventional fixed parameter model.

• 한국전산유체공학회:학술대회논문집
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• 2007.10a
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• pp.162-166
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• 2007

In the present study, the pressure coefficient of a cubic building model is numerically simulated. Three turbulence models of standard ${\kappa}-{\varepsilon}$, RNG ${\kappa}-{\varepsilon}$ and LES are adopted and the results are compared with the available experimental data. From the results, it has been found that RNG ${\kappa}-{\varepsilon}$ turbulence model and LES turbulence model were shown to predict fairly well the experimental pressure coefficient. In contrast, the results of the standard ${\kappa}-{\varepsilon}$ turbulence model showed large discrepancies in pressure coefficient on the side and top surfaces of the cubic building, which limits the applicability of the standard ${\kappa}-{\varepsilon}$ turbulence model on wind engineering.

• Journal of the Korean Data and Information Science Society
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• v.28 no.5
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• pp.1167-1177
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• 2017

The censored regression using the pseudo-response variable proposed by Buckley and James has been one of the most well-known models. Recently, the varying coefficient regression model has received a great deal of attention as an important tool for modeling. In this paper we propose a censored varying coefficient regression model using Buckley-James method to consider situations where the regression coefficients of the model are not constant but change as the smoothing variables change. By using the formulation of least squares support vector machine (LS-SVM), the coefficient estimators of the proposed model can be easily obtained from simple linear equations. Furthermore, a generalized cross validation function can be easily derived. In this paper, we evaluated the proposed method and demonstrated the adequacy through simulate data sets and real data sets.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2007.05a
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• pp.103-108
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• 2007

This paper presents a friction model to realize self-excited vibration of multi-body systems. The friction coefficient is modeled with a spline function in most commercial codes. Even if such a function resolves the problem of discontinuity in friction force, it cannot realize self-excited vibration phenomena. Furthermore, as the relative velocity approaches zero, the friction coefficient approaches zero with the conventional model. So, slip occurs when small force is applied to the system. To avoid these problems a new friction model is proposed in this study. With the new friction model, the self-excited vibration can be realized since the friction coefficient changes with the relative velocity. Furthermore, the slip phenomena could be reduced significantly with the proposed model.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.17 no.6 s.123
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• pp.524-530
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• 2007

This paper presents a friction model to realize self-excited vibration of multi-body systems. The friction coefficient is modeled with a spline function in most commercial codes. Even if such a function resolves the problem of discontinuity in friction force, it cannot realize self-excited vibration phenomena. Furthermore, as the relative velocity approaches zero, the friction coefficient approaches zero with the conventional model. So, slip occurs when small force is applied to the system. To avoid these problems a new friction model is proposed in this study. With the new friction model, the self-excited vibration can be realized since the friction coefficient changes with the relative velocity. Furthermore, the slip phenomena could be reduced significantly with the proposed model.