• New & Renewable Energy
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• v.2 no.3
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• pp.15-22
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• 2006

As the distributed generation becomes more reliable and economically feasible, it is expected that a higher application of the distributed generation units would be interconnected to the existing grids. This new market penetration using the distributed generation technology is linked to a large number of factors like economics and performance, safety and reliability, market regulations, environmental issues, or grid connection standards. KEPCO, a government company in Korea, has performed the project to identify and evaluate the performance of Micro Gas Turbine(MGT) technologies focused on 30, 60kW-class grid-connected optimization and combined Heat & Power performance. This paper describes the results for the mechanical, electrical, and environmental tests of MGT on actual grid-connection under Korean regulations. As one of the achievements, the simulation model of Exhaust-gas Absorption Chiller was developed, so that it will be able to analyze or propose new distributed generation system using MGT. In addition, KEPCO carried out the field testing of the MGT Cogeneration system at the R&D Center Building, KEPCO. The field test was conducted in order to respond to a wide variety of needs for heat recovery and utilization. The suggested method and experience for the evaluation of the distributed generation will be used for the introduction of other distributed generation technologies into the grid in the future.

• Smart Structures and Systems
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• v.14 no.6
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• pp.1269-1289
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• 2014

With the sub-stepping technique, the numerical analysis in real-time dynamic hybrid testing is split into the response analysis and signal generation tasks. Two target computers that operate in real-time may be assigned to implement these two tasks, respectively, for fully extending the simulation scale of the numerical substructure. In this case, the integration time-step of solving the dynamic response of the numerical substructure can be dozens of times bigger than the sampling time-step of the controller. The time delay between the real and desired feedback forces becomes more striking, which challenges the well-developed delay compensation methods in real-time dynamic hybrid testing. This paper focuses on displacement prediction and force correction for delay compensation in the real-time dynamic hybrid testing with a large integration time-step. A new displacement prediction scheme is proposed based on recently-developed explicit integration algorithms and compared with several commonly-used prediction procedures. The evaluation of its prediction accuracy is carried out theoretically, numerically and experimentally. Results indicate that the accuracy and effectiveness of the proposed prediction method are of significance.

• Transactions of the Korean Society for Noise and Vibration Engineering
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• v.14 no.3
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• pp.175-184
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• 2004

Ground-borne noise and vibration generated by underground transit system has been recognized as an important environmental problem. This study reviews several of the procedures that have been used to predict ground-borne vibration. The vibration responses are measured at three sites that have different soil qualities. The measured vibration levels are compared with the predicted results by previously used vibration level prediction models. There are some drawbacks to apply these prediction models to selected sites because most of the existing prediction models are primarily based on empirical data and all of them lack of analytical models for the mechanism of ground-borne vibration generation. radiation, and propagation. In this study a numerical method, which is based on explicit differential method, is used to compensate for the shortcomings of existing prediction models. Although numerically computed results are not quantitatively in good agreement with the measured results, the trends are comparable in the sense that vibration level does not decrease monotonically with distance. Also, the site with the deepest tunnel gives the highest vibration level.

• Advances in nano research
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• v.3 no.3
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• pp.143-168
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• 2015

Initiation of crack and its growth simulation requires accurate model of traction - separation law. Accurate modeling of traction-separation law remains always a great challenge. Atomistic simulations based prediction has great potential in arriving at accurate traction-separation law. The present paper is aimed at establishing a method to address the above problem. A method for traction-separation law prediction via utilizing atomistic simulations data has been proposed. In this direction, firstly, a simpler approach of common neighbor analysis (CNA) for the prediction of crack growth has been proposed and results have been compared with previously used approach of threshold potential energy. Next, a scheme for prediction of crack speed has been demonstrated based on the stable crack growth criteria. Also, an algorithm has been proposed that utilizes a variable relaxation time period for the computation of crack growth, accurate stress behavior, and traction-separation atomistic law. An understanding has been established for the generation of smoother traction-separation law (including the effect of free surface) from a huge amount of raw atomistic data. A new curve fit has also been proposed for predicting traction-separation data generated from the molecular dynamics simulations. The proposed traction-separation law has also been compared with the polynomial and exponential model used earlier for the prediction of traction-separation law for the bulk materials.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.3
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• pp.174-183
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• 2000

Non-Parallelism the axial direction occurs during grinding process of long slender shafts. The reason for the axial error is due to elastic deformation of the components, accumulation phenomenon of the grinding and wheel wear during the grinding process. The accumulation phenomenon, the size generation mechanism and the wheel wear process during traverse grinding result in complicated process at each step on the wheel surface. The grinding system stiffness obtained from the stiffness of the center on the tailstock and the workpiece varing according to the relative position of the wheel and the workpiece. Further more, the value of wheel wear increases as the grinding process advances. The above mentioned issues make the shape generation process during traverse grinding quite complicated. This research analyzes the shape generation process in the direction of the work spindle. First, the formulation of the grinding system stiffness was conducted and the simulation analysis method of the traverse grinding was established. Also, a measuring system for assessing the dimensinal accuracy of the workpiece has been developed.

• Proceedings of the KIEE Conference
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• summer
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• pp.737-739
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• 2004

The domestic power system established with Cost-Based-Pricing(CBP) from April 2001. The system is a uniform pricing system. System Operator(50) establishes a Price Setting Schedule by the prediction of consumption and the presented bid price(generation cost) of the generation utility. But the Price Setting Schedule doesn't take account of the constraint of the system. This cause a transmission congestion, constrained-on generation and constrained-off generation. This Paper search the way of the increasing efficiency of domestic power system through the redemption of congestion charge.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.1
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• pp.87-99
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• 2004

In this paper, we have developed a technology-service relationship model which describes the diffusion process of a group of services and relevant technologies, and have applied the developed model to the prediction of the number of subscribers to the next generation mobile service. The technology-service relationship model developed in this paper incorporates the developing process of relevant technologies, a supply-side factor, into the diffusion process of specific services, while many diffusion models and multi-generation diffusion models in previous researches are mainly reflect the demand-side factors. So, the proposed model could effectively applied to the telecommunication services where the developing of the relevant technologies are very essential to the service Penetration. In our application, the Proposed model provides a competitive substitution between the next generation mobile service and the traditional mobile service.

• Journal of the Korean Society for Nondestructive Testing
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• v.36 no.2
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• pp.149-154
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• 2016

The use of nonlinear ultrasonics wave has been accepted as a promising tool for monitoring material states related to microstructural changes, as it has improved sensitivity compared to conventional non-destructive testing approaches. In this paper, third harmonic generation of shear horizontal guided waves propagating in an isotropic plate is investigated using the perturbation method and modal analysis approach. An experimental procedure is proposed to detect the third harmonics of shear horizontal guided waves by electromagnetic transducers. The strongly nonlinear response of shear horizontal guided waves is measured. The accumulative growth of relative acoustic nonlinear response with an increase of propagation distance is detected in this investigation. The experimental results agree with the theoretical prediction, and thus providing another indication of the feasibility of using higher harmonic generation of electromagnetic shear horizontal guided waves for material characterization.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2018.05a
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• pp.457-459
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• 2018

Solar power generation system is a energy generation technology that produces electricity from solar power, and it is growing fastest among renewable energy technologies. It is of utmost importance that the solar power system supply energy to the load stably. However, due to unstable energy production due to weather and weather conditions, accurate prediction of energy production is needed. In this paper, an Artificial Neural Network(ANN) that predicts solar energy using 15 kinds of meteorological data such as precipitation, long and short wave radiation averages and temperature is implemented and its performance is evaluated. The ANN is constructed by adjusting hidden parameters and parameters such as penalty for preventing overfitting. In order to verify the accuracy and validity of the prediction model, we use Mean Absolute Percentage Error (MAPE) and Mean Absolute Error (MAE) as performance indices. The experimental results show that MAPE = 19.54 and MAE = 2155345.10776 when Hidden Layer $Sizes=^{\prime}16{\times}10^{\prime}$.

• Journal of The Korean Association For Science Education
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• v.32 no.3
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• pp.524-531
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• 2012

Categorization is an important human function used to process different stimuli. It is also one of the most important factors affecting measurement of a person's classification ability. Explicit categorization, the representative system by which categorization ability is measured, can verbally describe the categorization rule. The purpose of this study was to develop a prediction model for categorization ability as it relates to the classification process of living organisms using fMRI. Fifty-five participants were divided into two groups: a model generation group, comprised of twenty-seven subjects, and a model verification group, made up of twenty-eight subjects. During prediction model generation, functional connectivity was used to analyze temporal correlations between brain activation regions. A classification ability quotient (CQ) was calculated to identify the verbal categorization ability distribution of each subject. Additionally, the connectivity coefficient (CC) was calculated to quantify the functional connectivity for each subject. Hence, it was possible to generate a prediction model through regression analysis based on participants' CQ and CC values. The resultant categorization ability regression model predictor was statistically significant; however, researchers proceeded to verify its predictive ability power. In order to verify the predictive power of the developed regression model, researchers used the regression model and subjects' CC values to predict CQ values for twenty-eight subjects. Correlation between the predicted CQ values and the observed CQ values was confirmed. Results of this study suggested that explicit categorization ability differs at the brain network level of individuals. Also, the finding suggested that differences in functional connectivity between individuals reflect differences in categorization ability. Last, researchers have provided a new method for predicting an individual's categorization ability by measuring brain activation.