• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.7 s.250
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• pp.757-764
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• 2006

Isothermal cyclic stress-strain deformation and thermomechanical deformation (TMD) of 429EM stainless steel were analyzed using a rheological model employing a bi-linear model. The proposed model was composed of three parameters: elastic modulus, yield stress and tangent modulus. Monotonic stress-strain curves at various temperatures were used to construct the model. The yield stress in the model was nearly same as 0.2% offset yield stress. Hardening relation factor, m, was proposed to relate cyclic hardening to kinematic hardening. Isothermal cyclic stress-strain deformation could be described well by the proposed model. The model was extended to describe TMD. The results revealed that the hi-linear thermomechanical model overestimates the experimental data under both in-phase and out-of-phase conditions in the temperature range of $350-500^{\circ}C$ and it was due to the enhanced dynamic recovery effect.

• Journal of the Korean Society of Safety
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• v.33 no.1
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• pp.81-87
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• 2018

The seismic response, the natural frequencies and the mode shapes of an offshore wind turbine with twisted tripod substructure subject to various pile-ground interactions are discussed in this paper. The acceleration responses of the tower head by four historical earthquakes are presented as the seismic response, while the other loads are assumed as ambient loads. For the pile-ground interactions, the fixed, linear and nonlinear models are employed to simulate the interactions and the p-y, t-z and Q-z curves are utilized for the linear and nonlinear models. The curves are designed for stiff, medium and soft clays, and thus, the seven types of the pile-ground interactions are used to compare the seismic response, the acceleration of the tower head. The mode shapes are similar to each other for all types of pile-ground interactions. The natural frequencies, however, are almost same for the three clay types of the linear model, while the natural frequency of the fixed support model is quite different from that of the linear interaction model. The wind turbine with the fixed support model has the biggest magnitude of acceleration. In addition, the nonlinear model is more sensitive to the stiffness of clay than the linear pile-ground interaction model.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.65 no.5
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• pp.851-856
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• 2016

Wind speed is heavily fluctuated and quite local than other weather elements. It is difficult to improve the accuracy of prediction only in a numerical prediction model. An MOS (Model Output Statistics) technique is used to correct the systematic errors of the model using a statistical data analysis. The Most of previous MOS has used a linear regression model for weather prediction, but it is hard to manage an irregular nature of prediction of wind speed. In order to solve the problem, a nonlinear regression method using SVR (Support Vector Regression) is introduced for a development of MOS for wind speed prediction. Experiments are performed for KLAPS (Korea Local Analysis and Prediction System) re-analysis data from 2007 to 2013 year for Jeju Island and Busan area in South Korea. The MLR and SVR based linear and nonlinear methods are compared to each other for prediction accuracy of wind speed. Also, the comparison experiments are executed for the variation in the number of UM elements.

• Korean System Dynamics Review
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• v.8 no.2
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• pp.253-273
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• 2007

To measure the effect of school zone on housing cost, Linear Regression Model is widely used, and school zone is known as a key determinant of housing cost in Korea. However, when the Hierarchical Linear Model (HLM) is applied with the same data, school effect on housing cost becomes statistically non-significant. It is because HLM effectively separates the effect of individual housing's attributes from the group effect. In sum, the housing cost of Kangnam, where good public schools are located, is apparently is higher than that of Kangbuk. However, the school effect on housing cost (Level 2) becomes non-significant when individual housing's attributes (Level 1) are controlled with HLM.

• Journal of the Korean Operations Research and Management Science Society
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• v.19 no.3
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• pp.111-129
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• 1994

In this study, we develope a revised model as well as application of decision problem under ambiguity based on the subjectively weighted linear utility medel. Bayes'rule is used when there are ambiguous probabilities on a decision problem and test information is available. A procedure for assessing the ambiguity aversion function is also presented. Decision problem of chemical corporation is used for an illustration of the application of the subjectively weighted linear utility model using Bayesian approach. We present the optimal decisiond using newly developed model. We also perform the sensitivity analysis to assure ourselves about the conclusion we obtianed on degree of ambiguity aversion due to characterize parameter of subjectively weighted linear utility model.

• Journal of the Korean Statistical Society
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• v.27 no.4
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• pp.407-420
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• 1998

This paper is concerned with selecting covariates to be included in building linear random effects models designed to analyze clustered response normal data. It is based on a Bayesian approach, intended to propose and develop a procedure that uses probabilistic considerations for selecting premising subsets of covariates. The approach reformulates the linear random effects model in a hierarchical normal and point mass mixture model by introducing a set of latent variables that will be used to identify subset choices. The hierarchical model is flexible to easily accommodate sign constraints in the number of regression coefficients. Utilizing Gibbs sampler, the appropriate posterior probability of each subset of covariates is obtained. Thus, In this procedure, the most promising subset of covariates can be identified as that with highest posterior probability. The procedure is illustrated through a simulation study.

• Journal of Korean Society for Quality Management
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• v.34 no.2
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• pp.122-128
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• 2006

One feature of a computer simulation experiment, different from a physical experiment, is that the output is often deterministic. Moreover the codes are computationally very expensive to run. This paper deals with the design and analysis of computer experiments(DACE) which is a relatively new statistical research area. We model the response of computer experiments as the realization of a stochastic process. This approach is basically the same as using a spatial linear model. Applications to the optimal mechanical designing and model calibration problems are illustrated. Algorithms for selecting the best spatial linear model are also proposed.

• 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.

• Smart Structures and Systems
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• v.30 no.1
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• pp.1-15
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• 2022

This article focuses on stability analysis and fuzzy controller synthesis for large neural network (NN) systems consisting of several interconnected subsystems represented by the NN model. Advanced and fuzzy NN differential inclusion (NNDI) for stability based on the developed algorithm with H infinity can be designed based on the evolved biological design. This representation is constructed using sector linearity for NN models. Sector linearity transforms a non-linear model into a linear model based on proposed operations. New sufficient conditions are realized in the form of LMI (linear matrix inequalities) to ensure the asymptotic stability of the trans-Lyapunov function. This transforms the nonlinear model into a linear model based on multiple rules. At last, a numerical case study with simulations is derived as illustration to prove its feasibility in real nonlinear structures.

• Computers and Concrete
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• v.16 no.1
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• pp.17-35
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• 2015

In this study, linear and non-linear response of a masonry wall that includes an opening was presented. The masonry wall was modeled with two-dimensional finite elements. Smeared crack model that includes the strain softening behavior was selected to the masonry wall material. For the numerical application, linear and non-linear analyses of the masonry wall were carried out using east-west and vertical components of the 1992 Erzincan and 2003 $Bing{\ddot{o}}l$ earthquake acceleration records. Linear and non-linear solutions were compared each other. The displacement and stress results at the selected points of the masonry wall and crack propagation in the masonry wall were presented for both earthquake acceleration records.