• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.906-909
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• 2005

This study provides the method to build the rotor system model using dynamic analysis software. also, it introduces the traditional methods of the rotor system modeling and informs the each merits and demerits. We will make up the flexible system of rotor system model with ADAMS, multi-body dynamics S/W, in order to develop dynamics model and get the response of plant model near to real model through connection the SIMULINK of MATLAB. We will develop the computing dynamics-controling model possible controlled simulation similar to a real model with controlling the plant model.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.34 no.4
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• pp.457-465
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• 2010

In this study, a Taylor series (T-S) model based on the Arrhenius, McVetty, and Monkman-Grant equations was developed using a mathematical analysis. In order to reduce fitting errors, the McVetty equation was transformed by considering the first three terms of the Taylor series equation. The model parameters were accurately determined by a statistical technique of maximum likelihood estimation, and this model was applied to the creep data of alloy 617. The T-S model results showed better agreement with the experimental data than other models such as the Eno, exponential, and L-M models. In particular, the T-S model was converted into an isothermal Taylor series (IT-S) model that can predict the creep strength at a given temperature. It was identified that the estimations obtained using the converted ITS model was better than that obtained using the T-S model for predicting the long-term creep life of alloy 617.

• Journal of Korean Society for Quality Management
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• v.40 no.1
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• pp.49-59
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• 2012

In computer simulation models the output from the computer code is often deterministic, i.e., running the code twice with the same values for the input variables would give the same output. It is discussed why the response surface method with polynomial approximation for the true response function is a good approximation to the computer experiments model. A sequential strategy to find the proper reduced quadratic polynomial model is illustrated with a case study in the military war game computer simulation model.

• Journal of Magnetics
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• v.6 no.1
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• pp.36-41
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• 2001

A micromagnetic model and a single-domain model simulation programs were used to analyze the sensitivity of a $20\mu m\times 60\mu m \times 1000{\AA}$ permalloy strip as a magnetoresistance sensor with bias fields of various directions and magnitudes. The micromagnetic model agrees with the measured sensitivity data better than the single-domain model. The data show the highest peak sensitivity with the bias field at 90$^{\circ}$to the current. The peak sensitivity decreases and the peak broadens as the bias angle decreases. The simulation using the micromagnetic model shows that a bias angle smaller than 90$^{\circ}$eads to magnetization patterns which are free from closure domains or vertices over a wider range of bias fields.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.1001-1002
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• 2010

• Food Science and Biotechnology
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• v.27 no.6
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• pp.1865-1869
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• 2018

This study examined the effects of alfalfa seed germination on growth of Salmonella enterica. We investigated the population changes of S. enterica during early sprout development. We found that the population density of S. enterica, which was inoculated on alfalfa seeds was increased during sprout development under all experimental temperatures, whereas a significant reduction was observed when S. enterica was inoculated on fully germinated sprouts. To establish a model for predicting S. enterica growth during alfalfa sprout development, the kinetic growth data under isothermal conditions were collected and evaluated based on Baranyi model as a primary model for growth data. To elucidate the influence of temperature on S. enterica growth rates, three secondary models were compared and found that the Arrhenius-type model was more suitable than others. We believe that our model can be utilized to predict S. enterica behavior in alfalfa sprout and to conduct microbial risk assessments.

• Applied Chemistry for Engineering
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• v.29 no.6
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• pp.789-798
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• 2018

The role of empirical equation to predict the performance of polymer electrolyte membrane fuel cell is important. The activation, ohmic and mass transfer losses were separated in a polarization curve, and the curve fitting according to each region was performed using Kim's model and Hao's model. Changes of each loss were compared according to operation variables of the temperature, pressure, oxygen concentration and membrane thickness. The existing model showed a good fitting convergence, but less fitting accuracy in the separated loss region. A new model using the convergence coefficient was suggested to improve the accuracy of performance prediction of fuel cells of which results were demonstrated.

• Proceedings of the KSME Conference
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• 2000.11a
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• pp.345-350
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• 2000

In this paper, we introduce a new artificial material model for topology optimization. The present material model, named S-shape material model, accelerates topology optimization process especially in mathematical programming. We overcome the instability and the flatness in heuristic optimization process. Numerical examples show the superiority of the proposed material.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2009.06a
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• pp.949-950
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• 2009

• Korean Management Science Review
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• v.26 no.2
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• pp.19-35
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• 2009

This paper investigated performance of the Markowitz's portfolio selection model with applications to Korean stock market. We chose Samsung-Group-Funds and KOSPI index for performance comparison with the Markowitz's portfolio selection model. For the most recent one and a half year period between March 2007 and September 2008, KOSPI index almost remained the same with only 0.1% change, Samsung-Group-Funds showed 20.54% return, and Markowitz's model, which is composed of the same 17 Samsung group stocks, achieved 52% return. We performed sensitivity analysis on the duration of financial data and the frequency of portfolio change in order to maximize the return of portfolio. In conclusion, according to our empirical research results with Samsung-Group-Funds, investment by Markowitz's model, which periodically changes portfolio by using nonlinear programming with only financial data, outperformed investment by the fund managers who possess rich experiences on stock trading and actively change portfolio by the minute-by-minute market news and business information.